Greenhouse Gas Emissions Standards
for Heavy-Duty Vehicles: Phase 3
Regulatory Impact Analysis
rnA United States
Environmental Protection
Agency
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Greenhouse Gas Emissions Standards
for Heavy-Duty Vehicles: Phase 3
Regulatory Impact Analysis
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
United States
Environmental Protection
Agency
EPA-420-R-24-006
March 2024
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Contents
Contents ii
List of Tables vii
List of Figures xxi
List of Equations xxiii
Executive Summary 1
Chapter 1 Industry Characterization and Technologies to Reduce GHG Emissions 5
1.1 Introduction 5
1.2 Heavy-duty Vehicle Industry 5
1.2.1 Freight Work Performed by and Operation of Heavy-duty Trucks 5
1.2.2 Existing Heavy-Duty Truck Market Benchmarking 8
1.2.3 Heavy-duty Vehicle Sales 17
1.3 Current Regulations and Federal Support for Reducing Heavy-Duty Vehicle GHG Emissions 20
1.3.1 Phase 2 EPA GHG Emission Standards for Heavy-Duty Vehicles and Engines 20
1.3.2 Bipartisan Infrastructure Law (BIL) and Inflation Reduction Act (IRA) 23
1.3.3 California Advanced Clean Trucks Regulation and Other State's Efforts to Increase Adoption of
ZEVs 34
1.4 GHG-Reducing Technologies for ICE-Powered Vehicles 37
1.4.1 Aerodynamics 39
1.4.2 Tire Rolling Resistance 42
1.4.3 Natural Gas Engines 43
1.4.4 Hydrogen-Fueled Internal Combustion Engines 47
1.4.5 Hybrid and Plug-in Hybrid Powertrains 48
1.5 Battery Electric Vehicle Technologies 51
1.5.1 Batteries 51
1.5.2 BEV Safety Considerations 66
1.5.3 BEV System Integration 72
1.5.4 BEV Ancillary Systems 76
1.5.5 BEV Market 78
1.5.6 BEV Research and Development 104
1.6 BEV Charging Infrastructure 105
1.6.1 Overview of BEV Charging Infrastructure 105
1.6.2 Status and Outlook of BEV Charging Infrastructure 109
1.6.3 Other BEV Charging Infrastructure Considerations 121
1.6.4 Power Generation and Transmission 123
1.6.5 Power Distribution 126
1.7 Fuel Cell Electric Vehicle Technology 131
1.7.1 Fuel Cell System 132
1.7.2 Fuel Cell and Battery Interaction 135
1.7.3 Onboard Hydrogen Storage Tanks 136
1.7.4 Fuel Cell Electric Vehicle Safety Considerations 138
1.7.5 FCEV Market 140
1.7.6 FCEV Research and Development 147
1.8 Overview of Hydrogen Industry and Infrastructure 148
1.8.1 Hydrogen Characteristics and Use 148
1.8.2 Hydrogen Infrastructure Basics 149
1.8.3 Status and Outlook of Hydrogen Refueling Infrastructure 155
1.8.4 Environmental Considerations 171
Chapter 2 Technology Assessment 173
2.1 Introduction 173
2.1.1 HD TRUCS Vehicle Types 179
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2.1.2 HD TRUCS Inputs 183
2.2 HD Vehicle Benchmark Characteristics 186
2.2.1 HD Vehicle Activity 186
2.2.2 HD Vehicle Energy Consumption 197
2.2.3 HD Vehicle Sales 213
2.3 ICE Vehicle Technology 221
2.3.1 ICE Vehicle Attributes 221
2.3.2 ICE Vehicle Components and Other Upfront Costs 223
2.3.3 ICE Vehicle Fuel Consumption 233
2.3.4 ICE Vehicle Operating Costs 237
2.4 Battery Electric Vehicle Technology 245
2.4.1 BEV Component Sizing 246
2.4.2 Battery Weight and Volume 260
2.4.3 BEV Component Costs 265
2.4.4 BEV Operating Costs 289
2.5 Fuel Cell Electric Vehicle Technology 297
2.5.1 Fuel Cell Electric Vehicle Component Sizing 298
2.5.2 FCEV Components Costs 304
2.5.3 FCEV Operating Costs 309
2.6 BEV Charging Infrastructure 317
2.6.1 Scope 317
2.6.2 Depot Charging Analysis 318
2.6.3 Public Charging Analysis 328
2.6.4 Other considerations 330
2.7 Technology Adoption 333
2.7.1 Technology Adoption based on TEMPO 335
2.7.2 Payback Schedule for Final Rule 343
2.8 HD TRUCS Functionality 347
2.8.1 Baseline Energy and Fuel Consumption 347
2.8.2 Vehicle Miles Traveled 353
2.8.3 Power Take Off Loads 354
2.8.4 ICE Vehicle Technology 355
2.8.5 BEV Technology 356
2.8.6 FCEV Technology 365
2.8.7 Charging Infrastructure 370
2.8.8 Payback 375
2.9 HD TRUCS Analysis Results 382
2.9.1 HD TRUCS Technology Analysis 382
2.9.2 Payback 392
2.9.3 HD TRUCS Results 402
2.10 Supporting the Feasibility of the Final CO2 Standards 405
2.10.1 Technology Packages to Support the Final Standards 406
2.10.2 Battery Pack Production Levels to Support the Technology Packages 409
2.10.3 EVSE Production Levels to Support the Technology Packages 410
2.10.4 Calculation of the Final CO2 Standards 411
2.10.5 Final CO2 Standards 417
2.10.6 Summary of Costs to Meet the Final Emission Standards 419
2.11 Additional Example Compliance Pathway Technology Packages to Support the Final Standards 431
2.11.1 Technology Effectiveness and Lead Time 434
2.11.2 Technology Package Costs 442
2.11.3 Technology Adoption Rates in the Additional Potential Compliance Pathways 450
2.11.4 Additional Example Potential Compliance Pathways - Manufacturer Costs to Meet the Final
Standards 453
2.11.5 Additional Example Potential Compliance Pathways - Purchaser Cost Considerations 454
2.12 Total Cost of Ownership (TCO) Analysis 469
2.12.1 TCO Analysis Time Horizon 469
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2.12.2 TCO Analysis Residual Value 469
2.12.3 TCO Analysis Financing Costs 470
2.12.4 TCO Analysis Results 471
Chapter 3 Program Costs 474
3.1 IRA Tax Credits 477
3.2 Technology Package Costs 478
3.2.1 Direct Manufacturing Costs 479
3.2.2 Indirect Manufacturing Costs 482
3.2.3 Vehicle Technology Package RPE 484
3.3 Manufacturer Costs 486
3.3.1 Relationship to Technology Package RPE 486
3.3.2 Battery Tax Credits 486
3.3.3 Manufacturer RPE 486
3.4 Purchaser Costs 488
3.4.1 Purchaser RPE 488
3.4.2 Vehicle Purchase Tax Credits 489
3.4.3 Depot Electric Vehicle Supply Equipment Costs 489
3.4.4 Electric Vehicle Supply Equipment Tax Credits 491
3.4.5 Federal Excise Tax and State Sales Tax 492
3.4.6 Purchaser Upfront Costs 493
3.4.7 Operating Costs 496
3.4.8 Analysis of Payback Periods 551
3.5 Social Costs 551
3.5.1 Total Vehicle Technology Package RPE 551
3.5.2 Total EVSE RPE 553
3.5.3 Total Operating Cost 554
3.5.4 Total Social Cost 556
Chapter 4 Emission Inventories 560
4.1 Introduction 560
4.2 Model Data and Methodologies 563
4.2.1 Updates to MOVES4.R3 564
4.2.2 MOVES Inputs for the Reference Case 567
4.2.3 MOVES Inputs for the Final Standards and the Alternative 573
4.2.4 EGU Emissions Analysis Methodology 574
4.2.5 Refinery Emissions Analysis Methodology 580
4.3 National Downstream Emission Inventory Impacts of the Final Standards 586
4.3.1 Analysis Year Impacts 586
4.3.2 Year-Over-Year Impacts 588
4.3.3 Detailed Emission Impacts 596
4.4 National Upstream Emission Inventory Impacts of the Final Standards 605
4.4.1 Analysis Year Impacts 606
4.4.2 Year-over-year Impacts 607
4.5 Net Emissions Impacts of the Final Standards 616
4.5.1 Analysis Year Impacts 616
4.5.2 Year-over-year Impacts 618
4.6 Cumulative GHG Impacts of the Final Standards 626
4.7 Comparison Between the Final Standards and the Alternative 627
4.7.1 Downstream Emission Inventory Comparison 628
4.7.2 Upstream Emission Inventory Comparison 629
4.7.3 Net Emission Inventory Comparison 631
4.7.4 Cumulative GHG Reduction Comparison 633
4.8 Hydrogen Production Comparative Analysis 634
4.9 Refined Fuels Export Sensitivity Analysis 639
4.10 Reference Case ZEV Adoption Sensitivity Analysis 642
4.10.1 ZEV Adoption Rate Calculations 642
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4.10.2 Heavy-Duty Vehicle Manufacturer Costs 644
4.10.3 Downstream Emission Inventory Impacts 646
4.11 Comparison Between the Final Standards and Proposed Standards 649
Chapter 5 Health and Environmental Impacts 653
5.1 Climate Change Impacts from GHG emissions 653
5.2 Climate Benefits 660
5.3 Reserved 673
5.4 Health Effects Associated with Exposure to Non-GHG Pollutants 673
5.4.1 Ozone 674
5.4.2 Particulate Matter 676
5.4.3 Nitrogen Oxides 682
5.4.4 Carbon Monoxide 683
5.4.5 Sulfur Oxides 684
5.4.6 Diesel Exhaust 685
5.4.7 Air Toxics 688
5.4.8 Exposure and Health Effects Associated with Traffic 695
5.5 Welfare Effects Associated with Exposure to Non-GHG Pollutants 703
5.5.1 Visibility 703
5.5.2 Ozone Effects on Ecosystems 704
5.5.3 Deposition 705
5.5.4 Welfare Effects of Air Toxics 706
5.6 Environmental Justice 707
5.6.1 Overview 707
5.6.2 GHG Impacts on Environmental Justice and Vulnerable or Overburdened Populations 708
5.6.3 Non-GHG Impacts 714
Chapter 6 Economic and Other Impacts 721
6.1 Impact on Sales, Fleet Turnover, Mode Shift, Class Shift, and Domestic Production 721
6.1.1 Vehicle Sales and Fleet Turnover 721
6.1.2 Mode Shift 726
6.1.3 Class Shift 727
6.1.4 Domestic Production 728
6.2 Purchaser Acceptance 729
6.3 VMT Rebound 736
6.4 Employment Impacts 737
6.4.1 Background and Literature 737
6.4.2 Potential Employment Impacts of the Final Rule 739
6.4.3 The Factor-Shift Effect 744
6.4.4 The Demand Effect 745
6.4.5 The Cost Effect 745
6.4.6 Overall Effects 746
6.4.7 Employment in Additional Related Sectors 747
6.5 Oil Imports and Electricity and Hydrogen Consumption 750
Chapter 7 Benefits 754
7.1 Benefits of GHG Reductions 754
7.2 Estimated Human Health Benefits of Non-GHG Emission Reductions 764
7.2.1 Approach to Estimating Human Health Benefits 765
7.2.2 Estimating PM2 5-attributable Adult Premature Death 768
7.2.3 Economic Value of Health Benefits 770
7.2.4 Health Benefits Results 771
7.2.5 Characterizing Uncertainty in the Estimated Benefits 783
7.2.6 Benefit-per-Ton Estimate Limitations 784
7.3 Energy Security 786
7.3.1 Review of Historical Energy Security Literature 787
7.3.2 Review of Recent Energy Security Literature 790
7.3.3 Cost of Existing U.S. Energy Security Policies 797
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7.3.4 U.S. Oil Import Reductions Expected from the Final Rule 800
7.3.5 Oil Security Premiums Used in the Final Rule 804
7.3.6 Energy Security Benefits of the Final Rule 808
Chapter 8 Comparison of Benefits and Costs 810
8.1 Methods 810
8.2 Results 811
Chapter 9 Small Business Analysis 819
9.1 Definition of Small Businesses 819
9.2 Categories of Small Businesses Potentially Affected by the Rule 819
9.3 Description of Small Businesses Potentially Affected by the Rule 821
9.3.1 Heavy-Duty Engine Manufacturers 821
9.3.2 Heavy-Duty Conventional Vehicle Manufacturers 821
9.3.3 Heavy-Duty Electric Vehicle Manufacturers 822
9.3.4 Alternative Fuel Engine Converters 822
9.4 Potential Impacts on Small Entities 822
Appendix A - VMT for HD TRUCS 824
Appendix B - Additional MOVES Adoption Rates 827
B. 1 ZEV Sales Percentages in ACT States 828
B.2 ZEV Sales Percentages in non-ACT States 852
B.3 National ZEV Sales Percentages 876
B.4 Reference Case ZEV Adoption Sensitivity Sales Percentages 900
Appendix C - Additional Benefits 924
Appendix D - List of Abbreviations, Acronyms, and Symbols 931
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List of Tables
Table 1-1 Number of U.S. Vehicles, Vessels, and Other Conveyances: 2000-2020 6
Table 1-2 Domestic Mode of Exports and Imports by Tonnage and Value from 2020-2055 7
Table 1-3 Benchmarked Conventional Vehicles with Similar ZEV Options 10
Table 1-4 AEO 2023 Sales Projections in Thousands by Weight Class and Energy Use from 2023 - 2050 20
Table 1-5 Phase 2 CO2 Standards for Model Year (MY) 2027 and Later Vocational Vehicles (g/ton-mile) 20
Table 1-6 Phase 2 Custom Chassis CO2 Emission Standards for Model Year (MY) 2027 and Later (g/ton-mile) 21
Table 1-7 Phase 2 CO2 Standards for Model Year (MY) 2027 and Later Class 7 and Class 8 Tractors (g/ton-mile) .21
Table 1-8 Vehicle Manufacturers Certified to EPA HDV Emission Standards in MY 2024 22
Table 1-9 MY 2027 Engine CO2 Emission Standards for Engines Installed in Tractors (SET cycle) 23
Table 1-10 MY 2027 Engine CO2 Emission Standards for Heavy-Duty Engines Installed in Vocational Vehicles (FTP
cycle) 23
Table 1-11 Engine Manufacturers Certified to EPA HDE Emission Standards in MY 2024 23
Table 1-12 CFI Corridor Program Grant Recipients 27
Table 1-13 California Air Resource Board ACT Regulation ZEV Sales Percentage Schedule 35
Table 1-14 CARB Weight Class Modifiers 35
Table 1-15 GEM Inputs for Vehicles Meeting the Phase 2 MY 2027 Tractor CO2 Emission Standards 38
Table 1-16 GEM Inputs for Vehicles Meeting the Phase 2 MY 2027 Vocational Vehicle CO2 Emission Standards.39
Table 1-17 GEM Inputs for Tractor Aerodynamic Bins (CdA in m2) 41
Table 1-18 Phase 2 Tire Rolling Resistance Technologies 43
Table 1-19 MY 2024 CNG, LNG and Propane Powered Heavy-Duty Vehicle Models 44
Table 1-20 Heavy-Duty Hybrid Vehicle Examples 48
Table 1-21 Battery weight and volume to meet vehicle requirement for two different chemistries 52
Table 1-22 Current Electronic Power Take Off Market Offerings 78
Table 1-23 Models of Battery Electric Heavy-Duty Vehicles through 2024 85
Table 1-24 List of HD BEV Purchase Commitments Compiled by EDF (2022) 96
Table 1-25 Manufacturers of HD BEV Components 104
Table 1-26 DOE Funded BEV Projects Awarded in 2022 105
Table 1-27 Public Charging Stations and EVSE Port Counts 109
Table 1-28 Examples of distribution upgrade costs and lead times from the literature 128
Table 1-29 Current and Projected North American HD Fuel Cell Vehicles 141
Table 1-30 FCEV Component Manufacturers 146
Table 1-31 DOE Funded Hydrogen HDV Projects Awarded in 2022 147
Table 1-32 Hydrogen Production Methods- 149
Table 1-33 Transportation Highlights at H2Hubs 164
Table 1-34 Excerpt from Table 6-2 in RIA Chapter 6.5 on Estimated U.S. Oil Import Reductions and Electricity and
Hydrogen Consumption Increases due to the Final Rule * 165
Table 2-1 HD TRUCS Vehicle Types 180
Table 2-2 HD TRUCS Vehicle ID mapping to ANL vehicles 184
Table 2-3 Operational and Sizing VMT in HD TRUCS 193
Table 2-4 Relative Change in VMT to Vehicle Age of Year 0 for each MOVES Source Type ID 196
Table 2-5 Energy Requirements of HDVs 197
Table 2-6 Model Year 2027 GEM Engine Parameters 201
Table 2-7 Model Year 2027 GEM Drivetrain Parameters 202
Table 2-8 Model Year 2027 GEM Vehicle Input Parameters 203
Table 2-9 Model Year 2027 Additional Technology GEM Inputs 204
Table 2-10 GEM Tractor Default Values 205
Table 2-11 GEM Vocational Vehicle Default Values 205
Table 2-12 Model Year 2027 GEM Axle Work and CO2 Emissions (HVAC load has been removed) 207
Table 2-13 GEM Duty Cycle Distance and Time 207
Table 2-14 GEM Test Cycle Weighting Factors and Average Speed 208
Table 2-15 Weighted Energy Consumption per Mile 209
Table 2-16 Percent Energy Recovery and Energy Recovered per Mile from Regenerative Braking 210
Table 2-17 PTO Energy Use as a Function of Total Energy Consumed from CA Regulation 1432 211
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Table 2-18 PTO Assignment in HD TRUCS 212
Table 2-19 MY 2021 MOVES New Vehicle Sales by sourceTypelD and regClassID 214
Table 2-20 MY 2021 MOVES New Vehicle Sales with Zero Sales Not in HD TRUCS 215
Table 2-21 MY 2021 MOVES New Vehicle Sales Not in III) TRUCS With Sales 215
Table 2-22 Number of HD TRUCS Vehicle Types for each Combination of MOVES sourceTypelD and regClass ID
216
Table 2-23 Number of Sales of MY2021 MOVES New Vehicle Sales for each HD TRUCS Vehicle Type 217
Table 2-24 Final HD TRUCS Sales Shares 219
Table 2-25 Benchmark ICE Vehicle Dimensions and Weight 221
Table 2-26 ICE Powertrain (PT) RPE, Sales Tax and FET for MY 2032 (2022$) 224
Table 2-27 Engine Power used as GEM Inputs and to Determine Engine Cost 227
Table 2-28 MY 2027, MY 2030, and MY 2032 ICE Gearbox Costs in HD TRUCS (2022$) 230
Table 2-29 Binned Direct Manufacturing Costs for ICE Powertrain Components for MY 2032 (2022$) 230
Table 2-30 ICE Powertrain (PT) Direct Manufacturing Cost (DMC) for MY 2032 (2022$) 230
Table 2-31 GEM Fuel Consumption in Miles per Gallon Diesel (MPGD) 234
Table 2-32 Annual Diesel Fuel Consumption from Driving and PTO Use (MY 2032), 10 Year Average 234
Table 2-33 ICE Operating Costs for a MY 2032 Vehicle (2022$, 10-Year Average) 237
Table 2-34 DEF Consumption Rates for Diesel Vehicles in HD TRUCS 240
Table 2-35 Annual DEF Consumption, 10 Year Average 240
Table 2-36 DEF Price per Gallon (2022$) 243
Table 2-37 AEO 2023 Reference Case Diesel Price (2022$) 245
Table 2-38 Battery and Motor Sizes (MY 2032) 246
Table 2-39 HD TRUCS HVAC Power Consumption of a Class 8 Transit Bus 251
Table 2-40 Distribution of VMT forHD TRUCS Temperature Bins 251
Table 2-41 Vehicle Surface Area as a Function of a Class 8 Transit Bus Surface Area 252
Table 2-42 VMT Weighted Battery Conditioning Energy Consumption 255
Table 2-43 Summary of Inverter, Gearbox, and E-motor Data Used for Each Vehicle ID 256
Table 2-44 Combined Inverter, Gearbox, and E-motor Efficiency for each GEM Energy ID 257
Table 2-45 ANL Performance Targets 260
Table 2-46 Battery Size, Weight, and Volume in HD TRUCS 261
Table 2-47 Pack Energy Density 264
Table 2-48 Pack-Level Battery Pack Direct Manufacturing Costs in HD TRUCS (2022$) 269
Table 2-49 Potential value of 45X 10 percent CAM, AAM, and CM credits for a 75-kWh battery 271
Table 2-50 Pack-Level Battery Direct Manufacturing Costs and IRA Tax Credits in HD TRUCS (2022$) 272
Table 2-51 E-Motor Direct Manufacturing Costs inHD TRUCS (2022$) 275
Table 2-52 Power Converter and Electric Accessories Direct Manufacturing Costs in HD TRUCS (2022$) 276
Table 2-53 Auxiliary Converter Direct Manufacturing Costs in HD TRUCS (2022$) 276
Table 2-54 Final Drive Costs inHD TRUCS (2022$) 277
Table 2-55 MY 2027, MY 2030, and MY 2032 BEV Gearbox Costs in HD TRUCS (2022$) 277
Table 2-56 Onboard Charger Direct Manufacturing Costs inHD TRUCS (2022$) 278
Table 2-57 Direct Manufacturing BEV Costs Including IRA Tax Credit for MY 2027 (2022$) 278
Table 2-58 Direct Manufacturing BEV Costs Including IRA Tax Credit for MY 2030 (2022$) 281
Table 2-59 Direct Manufacturing BEV Costs and IRA Tax Credit for MY 2032 (2022$) 283
Table 2-60 BEV Powertrain (PT) RPE, Sales Tax and FET for MY 2032 (2022$) 287
Table 2-61 BEV Operating Costs for a MY 2032 Vehicle (2022$, 10-Year Average) 290
Table 2-62 Maintenance and Repair Scaling Factors for BEV CY 2027 - 2032+ 293
Table 2-63 Retail Electricity Prices for select years (2022 cents/kWh)- 295
Table 2-64 Charging Costs (2022$) 296
Table 2-65 Technical Properties of the FCEV for MY 2032 298
Table 2-66 Powertrain Efficiencies for FCEV 303
Table 2-67 FCEV Direct Manufacturing Costs and IRA Tax Credit for MY 2032 (2022$) 304
Table 2-68 Fuel Cell System Direct Manufacturing Costs (2022$) 307
Table 2-69: Onboard Hydrogen Tank Direct Manufacturing Costs (2022$) 308
Table 2-70 FCEV Powertrain (PT) RPE, Sales Tax and FET for MY 2032 (2022$) 308
Table 2-71 FCEV Operating Costs for a MY 2032 Vehicle (2022$), 10 Year Average 309
Table 2-72 Projected Hydrogen Costs from DOE's Liftoff Report 311
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Table 2-73 EMAH2 Cost Projections 314
Table 2-74 Retail Price of Hydrogen for CYs 2030-2035+ (2022$) used in Final Version of HD TRUCS 315
Table 2-75 Maintenance and Repair Scaling Factors for FCEV CY 2030 - 2035+ 316
Table 2-76 Combined Hardware and Installation Costs per EVSE Port (in 2022$) 320
Table 2-77 Combined Hardware and Installation EVSE Costs used in HD TRUCS (in 2022$) 322
Table 2-78 Summary of per vehicle EVSE costs (in 2022$) 326
Table 2-79 Time to Charge at 2C or 1 MW for Daily Operating VMT 329
Table 2-80 Additional Time to Charge at 2C or 1 MW to Travel the 90th Percentile VMT 330
Table 2-81 Primary Inputs and Outputs for TEMPO 338
Table 2-82 Primary TEMPO Input and Output Disaggregation 339
Table 2-83 Number of Data Points within each Payback Period Provided by the commenter (EDF) 341
Table 2-84 Payback Period Bins for the NPRM and Final Rule 343
Table 2-85: Payback Schedule Used in the Final Rule HD TRUCS 346
Table 2-86 Input Parameters for Hybrid Vehicle Model 350
Table 2-87 Energy Consumption as a Function of Temperature Bands 356
Table 2-88 HD Vehicle Dimensions 357
Table 2-89 Energy Consumption as a Function of Temperature Bands 366
Table 2-90 Example Charging Times (for 400 kWh) 372
Table 2-91 Number of vehicles that can share an EVSE port 372
Table 2-92 Example per-vehicle EVSE Costs in 2022$ 372
Table 2-93 Operation years for each model year (MY) 377
Table 2-94 Maintenance and repair scaling factor for BEV and FCEV 379
Table 2-95 Payback Schedule in HD TRUCS 380
Table 2-96 Weight Difference between BEV and ICE Vehicles in HD TRUCS 383
Table 2-97 Results of the BEV Payback Analysis for MY 2027 (2022$) 393
Table 2-98 Results of the BEV Payback Analysis for MY 2030 (2022$) 395
Table 2-99 Results of the BEV Payback Analysis for MY 2032 (2022$) 399
Table 2-100 Results of the FCEV Payback Analysis for MY 2030 (2022$) 402
Table 2-101 Results of the FCEV Payback Analysis for MY 2032 (2022$) 402
Table 2-102 ZEV Percentages by HD TRUCS Vehicle Type 403
Table 2-103 HD TRUCS Results: Percentage of ZEVs in MYs 2027, 2030, and 2032 405
Table 2-104 Percentage of ZEVs in the MYs 2027, 2030 and 2032 Technology Packages before Product Lead Time
Adjustments 407
Table 2-105 Percentage of ZEVs in the Modeled Potential Compliance Pathway's MYs 2027-2032 Technology
Packages 408
Table 2-106 Percentage of ICE Vehicles in the Modeled Potential Compliance Pathway's MYs 2027-2032
Technology Packages 409
Table 2-107 Sales-Weighted Battery Pack Size and MOVES MY2027 and MY2032 Vehicle Sales 410
Table 2-108 EVSE Port Counts for Depot Charging Analysis 411
Table 2-109 Phase 2 MY 2027 Tractor CO2 Emission Standards (g/ton-mile) 412
Table 2-110 Phase 2 MY 2027 Vocational Vehicle CO2 Emission Standards (g/ton-mile) 412
Table 2-111 Final MY 2027 through 2032+ Vocational Vehicle CO2 Emission Standards (grams/ton-mile) 418
Table 2-112 Final MY 2027 through 2032+ Optional Custom Chassis Vocational Vehicle CO2 Emission Standards
(grams/ton-mile) 418
Table 2-113 Final MY 2027 through MY 2032+ Tractor CO2 Emission Standards (grams/ton-mile) 419
Table 2-114 Final MY 2027 through MY 2032+ Heavy-Haul Tractor CO2 Emission Standards (grams/ton-mile) .419
Table 2-115 Incremental ZEV RPE Costs for MY 2027 (2022$) 420
Table 2-116 Incremental ZEV RPE Costs for MY 2030 (2022$) 422
Table 2-117 Incremental ZEV RPE Costs for MY 2032 (2022$) 425
Table 2-118 Manufacturer Costs to Meet the Final MY 2027 Standards Relative to the Reference Case (2022$)...427
Table 2-119 Manufacturer Costs to Meet the Final MY 2030 Standards Relative to the Reference Case (2022$)...428
Table 2-120 Manufacturer Costs to Meet the Final MY 2032 Standards Relative to the Reference Case (2022$)...428
Table 2-121 MY 2027 Purchaser Per-ZEV Upfront Costs, Operating Costs, and Payback Period (2022$) 429
Table 2-122 MY 2030 Purchaser Per-ZEV Upfront Costs, Operating Costs, and Payback Period (2022$) 430
Table 2-123 MY 2032 Purchaser Per-ZEV Upfront Costs, Operating Costs, and Payback Period (2022$) 430
Table 2-124 Vehicle Manufacturers Certified to EPA HDV Emission Standards in MY 2022 433
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Table 2-125: Aerodynamic Technology Package Adoption Rates for an Additional Compliance Pathway 435
Table 2-126 Tire Rolling Resistance Technology Package Adoption Rates for an Additional Compliance Pathway
435
Table 2-127 GEM Inputs for Tractor ICE Vehicle Technologies that Achieve a 4% C02 Reduction Relative to the
Phase 2 MY 2027 Standards 436
Table 2-128 GEM Results for Phase 3 Additional Compliance Pathway for Tractors 437
Table 2-129 GEM Inputs for Vehicles Meeting the Phase 2 MY 2027 Vocational Vehicle CO2 Emission Standards
437
Table 2-130 Heavy-Duty Engine CO2 Comparison 438
Table 2-131 Effectiveness of Technologies of Vehicles with ICE Relative to the MY 2027 Phase 2 Standards 442
Table 2-132 MY 2027 and Later Incremental Technology Package Cost 443
Table 2-133 MY 2027 and Later Incremental Technology Package Cost 443
Table 2-134 MY 2027 and Later Incremental Technology Package Cost 443
Table 2-135 MY 2027 and Later Incremental Technology Package Cost 444
Table 2-136 FEV Vehicle Class and Application used for each Regulatory Category 444
Table 2-137 Summary of the MY 2027 and Later Incremental Costs for Natural Gas Fueled Vehicles (2022$) 445
Table 2-138 Summary of the MY 2030 and Later Incremental Costs for Hydrogen Fueled ICE Vehicles (2022$) .446
Table 2-139 Autonomie Vehicle Class and Application used for each Regulatory Category 447
Table 2-140 Summary of MY 2027 and Later Direct and Indirect Manufacturing Costs for Hybrid Electric Vehicles
(2022$) 447
Table 2-141 MY 2030 Incremental PHEV Component Costs for Each HD TRUCS Vehicle Type (2022$) 448
Table 2-142 Summary of MY 2030 Incremental RPE for Plug-in Hybrid Electric Vehicles (2022$) 450
Table 2-143 Per Vehicle Cost of Technologies Relative to the MY 2027 Phase 2 Standards (2022$) 450
Table 2-144 Adoption Rates of Technologies to meet Final Standards for MY 2027 Relative to Reference Case. ..451
Table 2-145 Adoption Rates of Technologies to meet Final Standards for MY 2030 Relative to Reference Case. ..451
Table 2-146 Adoption Rates of Technologies to meet Final Standards for MY 2032 and later Relative to Reference
Case 452
Table 2-147 Adoption Rates of Technologies to meet Final Standards for MY 2027 Relative to No ZEV Baseline452
Table 2-148 Adoption Rates of Technologies to meet Final Standards for MY 2030 Relative to No ZEV Baseline453
Table 2-149 Adoption Rates of Technologies to meet Final Standards for MY 2032 and later Relative to No ZEV
Baseline 453
Table 2-150 Average Technology Package Cost Per Vehicle to Meet the MY 2027, MY 2030, and MY 2032 Final
Standards (2022$) Relative to Reference Case 453
Table 2-151 Average Technology Package Cost Per Vehicle to Meet the MY 2027, MY 2030, and MY 2032 Final
Standards (2022$) Relative to No ZEV Baseline 454
Table 2-152 Annual Operating Savings of Tractors with Aerodynamic and Tire Rolling Resistance Improvements
(2022$) 455
Table 2-153 Annual Operating Savings of Natural Gas Heavy-Duty Vehicles (2022$) 456
Table 2-154 Annual Operating Savings of H2-ICE Heavy-Duty Vehicles (2022$) 461
Table 2-155 Annual Operating Savings of Hybrid Heavy-Duty Vehicles (2022$) 463
Table 2-156 Upfront Incremental Technology Costs for Plug-in Hybrid Vehicle Purchasers - MY 2030 and Later
466
Table 2-157 Annual Operating Savings of Plug-in Hybrid Heavy-Duty Vehicles (2022$) 467
Table 2-158 TCO Results for MY 2032 Vehicles (2022$) 471
Table 3-1 GDP Price Deflators* Used to Adjust Costs to 2022 Dollars 477
Table 3-2 Learning Curve applied to BEV, FCEV and ICE Powertrain Costs in the Reference, Final Standards and
Alternative Scenarios 481
Table 3-3 Retail Price Equivalent Factors in the Heavy-Duty and Light-Duty Industries 483
Table 3-4 Dealer new vehicle selling costs for final standards, undiscounted in Millions of 2022 Dollars* 484
Table 3-5 Fleet-Wide Incremental Technology Costs forZEVs, Millions of 2022 dollars* 485
Table 3-6 Battery Tax Credit in Millions of 2022 dollars * 486
Table 3-7 Total Vehicle Package RPE, Battery Tax Credits, and Manufacturer RPE (including Battery Tax Credits)
for the Final Standards Relative to the Reference Case, All Regulatory Classes and All Fuels, Millions of 2022
dollars* 487
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Table 3-8 Total Package RPE, Battery Tax Credits, and Manufacturer RPE (including Battery Tax Credits) for the
Alternative Option Relative to the Reference Case, All Regulatory Classes and All Fuels, Millions of 2022
dollars* 488
Table 3-9 Vehicle Tax Credit in Millions 2022 dollars* 489
Table 3-10 Depot EVSE Costs, Millions 2022 dollars * 491
Table 3-11 Incremental EVSE Tax Credit for the Final Standards Relative to the Reference Case for in Millions 2022
Dollars* 492
Table 3-12 Incremental Federal Excise Tax and State Sales Tax for the Final Standards Relative to the Reference Case
for in Millions 2022 Dollars* 493
Table 3-13 Incremental Purchaser Upfront Costs for the Final Standards Relative to the Reference Case for in Millions
2022 dollars* 495
Table 3-14 Incremental Purchaser Upfront Costs for the Alternative Option Relative to the Reference Case in Millions
2022 dollars* 496
Table 3-15 Charging Prices by Type of Charge Point (2022 dollars per kWh)* 498
Table 3-16 Hydrogen Price (2022 dollars per kg) 498
Table 3-17 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
2% discounting) 499
Table 3-18 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
3% discounting) 499
Table 3-19 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
7% discounting) 500
Table 3-20 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
2% discounting) 501
Table 3-21 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
3% discounting) 501
Table 3-22 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
7% discounting) 502
Table 3-23 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
2% discounting) 502
Table 3-24 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
3% discounting) 503
Table 3-25 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars,
7% discounting) 504
Table 3-26 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting) 504
Table 3-27 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting) 505
Table 3-28 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting) 506
Table 3-29 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting) 506
XI
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Table 3-30 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting) 507
Table 3-31 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting) 508
Table 3-32 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting) 509
Table 3-33 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting) 510
Table 3-34 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting) 511
Table 3-35 Annual Undiscounted Pre-Tax Fuel Costs for the Final Standards Relative to the Reference Case, Millions
of 2022 dollars * 512
Table 3-36 Annual Undiscounted Pre-Tax Fuel Costs for the Alternative Relative to the Reference Case, Millions of
2022 dollars * 513
Table 3-37 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 2%
discounting) 514
Table 3-38 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 3%
discounting) 515
Table 3-39 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 7%
discounting) 515
Table 3-40 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 2%
discounting) 516
Table 3-41 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 3%
discounting) 516
Table 3-42 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 7%
discounting) 517
Table 3-43 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 2%
discounting) 518
Table 3-44 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 3%
discounting) 518
Table 3-45 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each MOVES
Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022 dollars, 7%
discounting) 519
Table 3-46 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2% discounting) ....520
Table 3-47 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3% discounting) ....520
Table 3-48 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7% discounting) ....521
Table 3-49 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2% discounting) ....522
Table 3-50 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3% discounting) ....523
xil
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Table 3-51 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7% discounting) ....523
Table 3-52 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2% discounting) ....524
Table 3-53 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3% discounting) ....525
Table 3-54 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each MOVES
Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7% discounting) ....526
Table 3-55 Annual Undiscounted DEF Costs for the Final Standards relative to the Reference Case, Millions of 2022
dollars* 527
Table 3-56 Annual Undiscounted DEF Costs for the Alternative relative to the Reference Case, Millions of 2022
dollars* 528
Table 3-57: Values for Determining Maintenance and Repair in Equation 3-1 530
Table 3-58 Scalars of Maintenance and Repair based on Vehicle Fuel Type by Calendar Year 530
Table 3-59 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting) 531
Table 3-60 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting) 531
Table 3-61 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting) 532
Table 3-62 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting) 532
Table 3-63 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting) 532
Table 3-64 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting) 533
Table 3-65 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for
each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting) 533
Table 3-66 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for
Each MOVES Source Type, ICE compared to BEV Costs for the Final Standards Case* (cents/mile in 2022
dollars, 3% discounting) 533
Table 3-67 Maintenance and Repair Per Mile for Model Year 2032 Vehicles Calendar Year 2032 to 2055 for Each
MOVES Source Type, ICE to BEV for the Final Standards Case* (cents/mile in 2021 dollars, 7% discounting)
534
Table 3-68 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting) 534
Table 3-69 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting) 535
Table 3-70 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting) 536
Table 3-71 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting) 537
Table 3-72 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting) 538
xill
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Table 3-73 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting) 539
Table 3-74 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting) 540
Table 3-75 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting) 541
Table 3-76 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for
each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting) 542
Table 3-77 Annual Undiscounted Total Maintenance & Repair Costs for the Final Standards Relative to the Reference
Case, Millions of 2022 dollars * 543
Table 3-78 Annual Undiscounted Total Maintenance & Repair Costs for the Alternative Relative to the Reference
Case, Millions of 2022 dollars * 544
Table 3-79 Annual Insurance Costs for the Final Standards and Alternative Relative to the Reference Case, Millions
of 2022 Dollars* 545
Table 3-80 Annual State Registration Fees on ZEVs for the Final Standards and Alternative Relative to the Reference
Case, Millions of 2022 Dollars* 546
Table 3-81 Battery Replacement and ICE Engine Rebuild Costs Frequency and Costs in 2022 Dollars 548
Table 3-82 Annual Battery Replacement and ICE Engine Rebuild Insurance Costs for the Final Standards and
Alternative Relative to the Reference Case, Millions of 2022 Dollars* 549
Table 3-83 Annual EVSE Replacement Costs for the Final Standards and Alternative Relative to the Reference Case,
Millions of 2022 Dollars* 550
Table 3-84 Total Package RPE Cost Impacts of the Final Standards Relative to the Reference Case, All Regulatory
Classes and All Fuels, Millions of 2022 dollars* 552
Table 3-85 Total Package RPE Cost Impacts of the Alternative Option Relative to the Reference Case, All Regulatory
Classes and All Fuels, Millions of 2022 dollars* 553
Table 3-86 Total EVSE Cost in the Reference, Final Standards, Alternative, Change between Final Standards and
Reference Case, Change between Alternative and Reference Case; All Regulatory Classes and All Fuels,
Millions of 2022 dollars* 554
Table 3-87 Total Operating Cost Impacts of the Final Standards Relative to the Reference Case, All Regulatory Classes
and All Fuels, Millions of 2022 dollars* 555
Table 3-88 Total Operating Cost Impacts of the Alternative Option Relative to the Reference Case, All Regulatory
Classes and All Fuels, Millions of 2022 dollars* 556
Table 3-89 Total Technology, Operating and EVSE Social Cost Impacts of the Final Standards Relative to the
Reference Case, All Regulatory Classes and All Fuels, Millions of 2022 dollars* 557
Table 3-90 Total Technology, Operating and EVSE Social Cost Impacts of the Alternative Option Relative to the
Reference Case, All Regulatory Classes and All Fuels, Millions of 2022 dollars* 558
Table 4-1 MOVES source type definitions 565
Table 4-2 MOVES regulatory class definitions 565
Table 4-3 MOVES4.R3 Energy Efficiency Ratios forHD BEVs 566
Table 4-4 HD ZEV adoption rates in California's ACT rule 568
Table 4-5 Reference case ZEV adoption rate for ACT states 570
Table 4-6 Sales ratios for projecting reference case ZEV adoption in non-ACT States 571
Table 4-7 Reference case ZEV adoption rate for non-ACT states 572
Table 4-8 National heavy-duty ZEV adoption in the reference case 572
Table 4-9 National heavy-duty ZEV adoption in the control case for the final standards 574
Table 4-10 National heavy-duty ZEV adoption in the control case for the alternative 574
Table 4-11 Incremental EGU emission factors used to estimate EGU emissions increases attributable to additional HD
ZEV adoption in the final rulemaking 579
Table 4-12 Refinery emission apportionment factors by fuel type 582
Table 4-13 Refinery emission inventory apportioned by refinery type and fuel type 582
Table 4-14 Refinery emission rates for the refining of gasoline 583
Table 4-15 Refinery emission rates for the refining of diesel 583
xiv
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Table 4-16 Annual downstream heavy-duty GHG emission reductions from the final standards in calendaryears (CYs)
2035, 2045, and 2055 587
Table 4-17 Annual downstream heavy-duty criteria pollutant and air toxic emission reductions from the final standards
in calendaryears (CYs) 2035, 2045, and 2055 587
Table 4-18 Year-over-year CH4 and N20 emission reductions from the final standards 588
Table 4-19 Year-over-year CO2 and CO2Q emission reductions from the final standards 589
Table 4-20 Year-over-year emission inventory reductions for the final standards for select criteria pollutants 590
Table 4-21 Annual GHG emission increases from EGUs from the final standards in calendaryears (CYs) 2035, 2045,
and 2055 606
Table 4-22 Annual criteria pollutant emission increases from EGUs from the final standards in calendar years (CYs)
2035,2045, and 2055 606
Table 4-23 Annual GHG emission reductions from refineries from the final standards in calendar years (CYs) 2035,
2045, and 2055 606
Table 4-24 Annual criteria pollutant emission reductions from refineries from the final standards in calendar years
(CYs) 2035, 2045, and 2055 607
Table 4-25 Year-over-year EGU emission increases from the final standards for CH4 and N20 608
Table 4-26 Year-over-year EGU emission increases from the final standards for CO2 and CChe 609
Table 4-27 Year-over-year EGU emission inventory increases for criteria pollutants from the final standards 611
Table 4-28 Year-over-year refinery GHG emission reductions from the final standards 613
Table 4-29 Year-over-year refinery criteria pollutant emission reductions from the final standards 615
Table 4-30 Annual net impactsA on GHG emissions from the final standards in calendar years (CYs) 2035, 2045, and
2055 617
Table 4-31 Annual net impactsA on criteria pollutant emissions from the final standards in calendaryears (CYs) 2035,
2045, and 2055 617
Table 4-32 Year-over-year net emission impactsA of the final standards on emissions of CH4 and N20, in metric tons
618
Table 4-33 Year-over-year net emission impactsA of the final standards on CO2 emissions and CO2Q emissions, in
million metric tons (MMT) 619
Table 4-34 Year-over-year net emission impactsA of the final standards on NOx and VOC emissions, in U.S. tons
621
Table 4-35 Year-over-year net emission impactsA of the final standards on emissions of particulate matter and SO2 in
U.S. tons 624
Table 4-36 Cumulative 2027-2055 downstream heavy-duty GHG emission reductions from the final standards....627
Table 4-37 Cumulative 2027-2055 GHG emission increases from EGUs from the final standards 627
Table 4-38 Cumulative 2027-2055 GHG emission reductions from refineries from the final standards 627
Table 4-39 Cumulative 2027-2055 net GHG emission impactsA (in MMT) reflecting the final standards 627
Table 4-40 Annual downstream HD GHG emission reductions from the alternative in calendaryears (CY) 2035,2045,
and 2055 628
Table 4-41 Annual downstream HD criteria pollutant and air toxic emission reductions from the alternative in calendar
years (CYs) 2035, 2045, and 2055 628
Table 4-42 Annual GHG emission increases from EGUs from the alternative in calendar years (CY) 2035, 2045, and
2055 630
Table 4-43 Annual criteria pollutant emission increases from EGUs from the alternative in calendaryears (CYs) 2035,
2045, and 2055 630
Table 4-44 Annual GHG emission reductions from refineries due to the alternative in calendaryears (CY) 2035,2045,
and 2055 630
Table 4-45 Annual criteria pollutant emission reductions from refineries due to the alternative in calendaryears (CYs)
2035,2045, and 2055 631
Table 4-46 Annual net impactsA on GHG emissions from the alternative in calendaryears (CYs) 2035,2045, and 2055
631
Table 4-47 Annual net impactsA on criteria pollutant emissions from the alternative in calendar years (CYs) 2035,
2045, and 2055 632
Table 4-48 Cumulative 2027-2055 downstream HD GHG emission reductions from the final standards and the
alternative 633
Table 4-49 Cumulative 2027-2055 GHG emission increases from EGUs from the final standards and the alternative
634
XV
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Table 4-50 Cumulative 2027-2055 GHG emission reductions from refineries from the final standards and alternative
634
Table 4-51 Cumulative 2027-2055 net GHG emission impactsA (inMMT) of the alternative 634
Table 4-52 Lifecycle CChe emissions for hydrogen fuel production pathways from GREET in calendar year 2030
636
Table 4-53 Calculated average annual lifecycle CChe per kWh generated from EGUs (kgCChe/kWh) 637
Table 4-54 Electricity required to produce hydrogen using PEM electrolysis (kWh/kg H2) 637
Table 4-55 Annual GHG emission reductions from refineries from the final standards in calendar year 2055 for our
main modeling case and fuel export sensitivity case 639
Table 4-56 Annual criteria pollutant emission reductions from refineries from the final standards in calendaryear 2055
for our main modeling case and fuel export sensitivity case 640
Table 4-57 Annual net impactsA on GHG emissions from the final standards in calendar years (CYs) 2035, 2045, and
2055, analyzed with our fuel exports sensitivity case 640
Table 4-58 Annual net impactsA on criteria pollutant emissions from the final standards in calendaryears (CYs) 2035,
2045, and 2055, analyzed with our fuel exports sensitivity case 641
Table 4-59 Cumulative 2027-2055 net GHG emission impactsA (in MMT), reflecting the final standards analyzed
with our fuel exports sensitivity case 641
Table 4-60 National heavy-duty ZEV adoption in the sensitivity reference case 643
Table 4-61 National heavy-duty ZEV adoption in the sensitivity analysis for the final standards 644
Table 4-62 Manufacturer costs to meet the final MY 2027 standards through the potential compliance pathway relative
to the sensitivity reference case (2022$) 645
Table 4-63 Manufacturer costs to meet the final MY 2030 standards through the potential compliance pathway relative
to the sensitivity reference case (2022$) 645
Table 4-64 Manufacturer costs to meet the final MY 2032 standards through the potential compliance pathway relative
to the sensitivity reference case (2022$) 645
Table 4-65 Annual downstream heavy-duty GHG emission reductions from the final standards in calendaryears (CYs)
2035, 2045, and 2055, relative to the sensitivity reference case 646
Table 4-66 Annual downstream heavy-duty criteria pollutant and air toxic emission reductions from the final standards
in calendaryears (CYs) 2035, 2045, and 2055, relative to the sensitivity reference case 647
Table 4-67 Cumulative 2027-2055 downstream HD GHG emission reductions from the final standards relative to the
main reference case and sensitivity reference case 648
Table 4-68 HD ZEV adoption rates for the proposed standards as presented in the NPRM 649
Table 4-69 National heavy-duty ZEV adoption in the control case for the FRM modeling of the proposed standards
650
Table 4-70 Annual downstream heavy-duty GHG emission reductions from the proposed standards in calendaryears
(CYs) 2035, 2045, and 2055 650
Table 4-71 Cumulative 2027-2055 downstream HD GHG emission reductions from the final standards and the
proposed standards 651
Table 4-72 Cumulative 2027-2055 net GHG emission impactsA (in MMT) reflecting the proposed standards 651
Table 5-1 Annual Rounded SC-CO . SC-CII:. and SC-N.-O Values, 2027-2055 672
Table 6-1 Fossil Fuel Reductions due to the Final Rule, Millions of Gallons 750
Table 6-2 Estimated U.S. Oil Import Reductions and Electricity and Hydrogen Consumption Increases due to the Final
Rule* 752
Table 6-3 Estimated U.S. Oil Import Reductions due to the Final Rule under the Refinery Sensitivity * 753
Table 7-1 Benefits of Reduced CO2 Emissions from the Rule, Millions of 2022 dollars 755
Table 7-2 Benefits of Reduced CH4 Emissions from the Rule, Millions of 2022 dollars 756
Table 7-3 Benefits of Reduced N2O Emissions from the Rule, Millions of 2022 dollars 757
Table 7-4 Benefits of Reduced GHG Emissions from the Final Rule, Millions of 2022 dollars 758
Table 7-5 Human Health Effects of PM2.5 767
Table 7-6 PM2 5-related Benefit Per Ton values (2022$) associated with the changes of NOx, SO2 and directly emitted
PM2 5 emissions for (A) Onroad Heavy-Duty Diesel Vehicles, (B) Onroad Heavy-Duty Gasoline Vehicles, (C)
Electricity Generating Units, and (D) Refineries 772
Table 7-7 Summary of the estimated tons of reduced NOx, SO2 and direct PM2 5 per year from Heavy-Duty Diesel
Vehicles and the associated monetized PM2 5-related health benefits (millions, 2022$) for the final program
773
xvi
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Table 7-8 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Heavy-Duty Gasoline
Vehicles and the associated monetized PM2 5-related health benefits (millions, 2022$) for the final program
774
Table 7-9 Summary of the estimated tons of increased NOx, SO2 and direct PM2.5 per year from EGUs and the
associated monetized PM2 5-related health impacts (millions, 2022$) for the final program 775
Table 7-10 Summary of the estimated tons of reduced NOx, SO2 and direct PM2 5 per year from Refineries and the
associated monetized PM2 5-related health benefits (millions, 2022$) for the final program 776
Table 7-11 Year-over-year monetized PM2 5-related health benefits (millions, 2022$) associated with Onroad Heavy-
Duty Vehicle and upstream (EGU plus refinery) emissions from the final program 777
Table 7-12 Summary of the estimated tons of reduced NOx, SO2 and direct PM2 5 per year from Heavy-Duty Diesel
Vehicles and the associated monetized PM2 5-related health benefits (millions, 2022$) for the alternative
program 778
Table 7-13 Summary of the estimated tons of reduced NOx, SO2 and directPM2 5 per year from Heavy-Duty Gasoline
Vehicles and the associated monetized PM2 5-related health benefits (millions, 2022$) for the alternative
program 779
Table 7-14 Summary of the estimated tons of increased NOx, S02 and direct PM2.5 per year from EGUs and the
associated monetized PM2 5-related health impacts (millions, 2022$) for the alternative program 780
Table 7-15 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Refineries and the
associated monetized PM2 5-related health benefits (millions, 2022$) for the alternative program 781
Table 7-16 Year-over-year monetized PM2 5-related health benefits (millions, 2022$) associated with Onroad Heavy-
Duty Vehicle and upstream (EGU plus refinery) emissions from the alternative program 782
Table 7-17 Unqualified Criteria Pollutant Health and Welfare Benefits Categories 784
Table 7-18 Oil Import Reduction Factor based on AEO 2022 802
Table 7-19 Oil Import Reduction Factor based on AEO 2023 802
Table 7-20 Projected Trends in U.S. Oil Exports/Imports, Net Refined Petroleum Product Exports, Net Crude
Oil/Refined Petroleum Product Exports, Oil Consumption and U.S. Oil Import Reductions Resulting from the
Final Rule for Selected Years from 2027 to 2055 (MMBD) 803
Table 7-21 Macroeconomic Oil Security Premiums for Final Rule from 2027-2055 (2022$/Barrel)* 807
Table 7-22 Energy Security Benefits from the Final Rule (millions of 2022 dollars) 808
Table 8-1 Vehicle-Related Technology Costs Associated with the Final Rule and Alternative, Millions of 2022 dollars
811
Table 8-2 Vehicle-Related Operating Savings Associated with the Final Rule, Millions of 2022 dollars * 812
Table 8-3 Vehicle-Related Operating Savings Associated with the Alternative, Millions of 2022 dollars * 812
Table 8-4 Energy Security Benefits Associated with the Final Rule and Alternative, Millions of 2022 dollars 812
Table 8-5 Climate Benefits from Reduction in GHG Emissions Associated with the Final Rule and Alternative,
Millions of 2022 dollars 813
Table 8-6 Monetized PM2 5-related Emission Benefits Associated with the Final Rule and Alternative, Millions of
2022 dollars 814
Table 8-7 Total Benefits Associated with the Final Rule and Alternative, Millions of 2022 dollars 815
Table 8-8 Summary of Vehicle Costs, Operating Savings, and Benefits of the Final Rule, Billions of 2022 Dollars
816
Table 8-9 Summary of Vehicle Costs, Operating Savings, and Benefits of the Alternative, Billions of 2022 Dollars
817
Table 8-10 Transfers Associated with the Final Rule, Millions of 2022 Dollars 818
Table 8-11 Transfers Associated with the Alternative, Millions of 2022 Dollars 818
Table 9-1 Primary Small Business NAICS Categories Affected by this Rule 820
Table 9-2 Summary of Small Entity Impacts 823
Table A-l VMTby Vehicle Age 824
Table B-l Proportion of tractor ZEVs that are BEVs and FCEVs for MY 2030 and beyond 827
Table B-2 ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) in ACT states 828
Table B-3 ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) in ACT states 829
Table B-4 ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) in ACT states 830
Table B-5 ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) in ACT states ...831
Table B-6 ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) in ACT states ...832
Table B-7 ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) in ACT states 833
Table B-8 ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) in ACT states...834
xvii
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Table B-9 ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) in ACT states...835
Table B-10 ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) in ACT states ....836
Table B-l 1 ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) in ACT states 837
Table B-12 ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) in ACT states....838
Table B-13 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks (sourceTypelD 52) in
ACT states 839
Table B-14 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD 52) in
ACT states 840
Table B-15 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD 52) in
ACT states 841
Table B-16 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks (sourceTypelD 53) in
ACT states 842
Table B-17 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD 53) in
ACT states 843
Table B-18 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 53) in
ACT states 844
Table B-19 ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) in ACT states 845
Table B-20 ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) in ACT states 846
Table B-21 ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) in ACT states ...847
Table B-22 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD 61) in
ACT states 848
Table B-23 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD 61) in
ACT states 849
Table B-24 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD 62) in
ACT states 850
Table B-25 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 62) in
ACT states 851
Table B-26 ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) in non-ACT states
852
Table B-27 ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) in non-ACT states
853
Table B-28 ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) in non-ACT states
854
Table B-29 ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) in non-ACT states
855
Table B-30 ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) in non-ACT states
856
Table B-31 ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) in non-ACT states 857
Table B-32 ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) in non-ACT states
858
Table B-33 ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) in non-ACT states
859
Table B-34 ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) in non-ACT states
860
Table B-35 ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) in non-ACT states
861
Table B-36 ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) in non-ACT states
862
Table B-37 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks (sourceTypelD 52) in
non-ACT states 863
Table B-38 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD 52) in
non-ACT states 864
Table B-39 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD 52) in
non-ACT states 865
Table B-40 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks (sourceTypelD 53) in
non-ACT states 866
xviii
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Table B-41 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD 53) in
non-ACT states 867
Table B-42 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 53) in non-
ACT states 868
Table B-43 ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) in non-ACT states
869
Table B-44 ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) in non-ACT states
870
Table B-45 ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) in non-ACT states
871
Table B-46 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD 61) in
non-ACT states 872
Table B-47 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD 61) in
non-ACT states 873
Table B-48 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD 62) in
non-ACT states 874
Table B-49 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 62) in non-
ACT states 875
Table B-50 National ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) 876
Table B-51 National ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) 877
Table B-52 National ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) 878
Table B-53 National ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) 879
Table B-54 National ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) 880
Table B-55 National ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) 881
Table B-56 National ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) 882
Table B-57 National ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) 883
Table B-58 National ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) 884
Table B-59 National ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) 885
Table B-60 National ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) 886
Table B-61 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks (sourceTypelD
52) 887
Table B-62 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
52) 888
Table B-63 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
52 ) 889
Table B-64 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks (sourceTypelD
53 ) 890
Table B-65 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
53) 891
Table B-66 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD
53) 892
Table B-67 National ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) 893
Table B-68 National ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) 894
Table B-69 National ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) 895
Table B-70 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
61) 896
Table B-71 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
61 ) 897
Table B-72 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
62 ) 898
Table B-73 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD
62) 899
Table B-74 National ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) in the
reference case ZEV adoption sensitivity analysis 900
Table B-75 National ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) in the
reference case ZEV adoption sensitivity analysis 901
xix
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Table B-76 National ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) in the
reference case ZEV adoption sensitivity analysis 902
Table B-77 National ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) in the
reference case ZEV adoption sensitivity analysis 903
Table B-78 National ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) in the
reference case ZEV adoption sensitivity analysis 904
Table B-79 National ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) in the reference
case ZEV adoption sensitivity analysis 905
Table B-80 National ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) in the
reference case ZEV adoption sensitivity analysis 906
Table B-81 National ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) in the
reference case ZEV adoption sensitivity analysis 907
Table B-82 National ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) in the
reference case ZEV adoption sensitivity analysis 908
Table B-83 National ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) in the
reference case ZEV adoption sensitivity analysis 909
Table B-84 National ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) in the
reference case ZEV adoption sensitivity analysis 910
Table B-85 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks (sourceTypelD
52) in the reference case ZEV adoption sensitivity analysis 911
Table B-86 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
52) in the reference case ZEV adoption sensitivity analysis 912
Table B-87 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
52) in the reference case ZEV adoption sensitivity analysis 913
Table B-88 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks (sourceTypelD
53) in the reference case ZEV adoption sensitivity analysis 914
Table B-89 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
53) in the reference case ZEV adoption sensitivity analysis 915
Table B-90 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD
53) in the reference case ZEV adoption sensitivity analysis 916
Table B-91 National ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) in the
reference case ZEV adoption sensitivity analysis 917
Table B-92 National ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) in the
reference case ZEV adoption sensitivity analysis 918
Table B-93 National ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) in the
reference case ZEV adoption sensitivity analysis 919
Table B-94 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
61) in the reference case ZEV adoption sensitivity analysis 920
Table B-95 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
61) in the reference case ZEV adoption sensitivity analysis 921
Table B-96 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
62) in the reference case ZEV adoption sensitivity analysis 922
Table B-97 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD
62) in the reference case ZEV adoption sensitivity analysis 923
Table C-l Interim Social Cost of GHG Values, 2027-2055 (2022 $/metric ton) 925
Table C-2 Benefits of reduced C02 emissions from the final standards using the interim SC-GHG values (Millions of
2022 dollars) 926
Table C-3 Benefits of reduced CH4 emissions from the final standards using the interim SC-GHG values (Millions of
2022 dollars) 927
Table C-4 Benefits of reduced N20 emissions from the final standards using the interim SC-GHG values (Millions of
2022 dollars) 928
Table C-5 Benefits of reduced GHG emissions from the final standards using the interim SC-GHG values (Millions
of 2022 dollars) 929
Table C-6 Summary of costs, fuel savings and benefits of the final standards (billions of 2022 dollars) 930
xx
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List of Figures
Figure 1-1 Total Weight of Shipments by Transportation Mode 6
Figure 1-2 Value of Freight Moved Between the U.S., Canada, and Mexico 8
Figure 1-3 2023 HD Sales Percentages by AEO Categories (AEO 2023) 18
Figure 1-4 AEO 2022 Sales Percent by Weight Class and Energy Use for 2023 and 2050 (AEO 2023) 19
Figure 1-5 Minerals used in electric cars compared to conventional cars 54
Figure 1-6 Potential upstream mined critical materials supply, tonnes/year, grouped by location of mine production
58
Figure 1-7 Modeled lithium-ion cell production capacity in North America from 2018 to 2035 by country 64
Figure 1-8 Modeled lithium-ion cell production capacity in North America from 2018 to 2035 by transportation sector
65
Figure 1-9 Modeled MSP lithium-ion battery cell production capacity through 2035 66
Figure 1-10 Complete Coach Works' process for repowering conventional buses to battery electric buses 73
Figure 1-11 Spartan Emergency Response places the battery packs of their Vector fire truck strategically to improve
handling 75
Figure 1-12 Bollinger Motors' commercial electric trucks, (a) Cab-forward design increases cargo space over
conventional cabs, (b) Platform enables the trucks to be upfit to fill a wide variety of purposes, (c) Battery packs
in the ladder frame are flexible enough 76
Figure 1-13 Heavy-Duty Electric Trucks Available in the U.S. by Model Year 85
Figure 1-14 Example charging station with four EVSE ports and six connectors 106
Figure 1-15 Private Fleet Level 2 and DCFC Ports (Data Source: AFDC Station Locator as shown in Brown et al.
2024) 110
Figure 1-16 Example of Temporal Power Supply (Source: EIA) 125
Figure 1-17 Electricity power distribution infrastructure is shown above and is that portion of the grid between the
transmission system and the customer meter. Charging infrastructure for HD BEV is behind the meter. (Source:
Kevala, as seen in TEIS) 126
Figure 1-18 U.S. Department of Energy's H2@Scale Concept 149
Figure 1-19 DOE Comparison of Domestic Hydrogen Production Pathways 151
Figure 1-20 FHWA-Designated Alternative Fuel Corridors for Hydrogen Hydrogen Round 1,2, 3,4, 5,6 and 7: Ready
(straight lines) and Pending (dotted lines) 158
Figure 1-21 Map of Regional Clean Hydrogen Hubs 163
Figure 2-1 Relative Change in VMT from Vehicle Age in Year 0 to Age in Year 9 196
Figure 2-2 Direct Manufacturing Cost of a Diesel Engine as a Function of Engine Power in 2020$ (these costs are
adjusted to 2022$ inHD TRUCS) 227
Figure 2-3 M&R Cost Per Mile (2022$/mi) 244
Figure 2-4 Modeled HVAC Power Demand of a Class 8 Transit Bus as a Function of Ambient Temperature 250
Figure 2-5 MOVES National VMT Distribution as a Function of Temperature for 2b-8 HD Vehicles 251
Figure 2-6 Modeled Power Demand for Battery Conditioning for Class 8 Transit Bus with a 300 kWh Battery 254
Figure 2-7 Electric Drive Component Costs from (Nair et al. 2022) 274
Figure 2-8: Operating Efficiency of a Fuel Cell 302
Figure 2-9 Payback Curve Data Provided in Comments 335
Figure 2-10 Adoption rate as a function of payback period for data received from NREL and the commenter (EDF).
340
Figure 2-11 Adoption rate curve developed by the commenter (EDF) Compared to the Adoption rate curve produced
by EPA, both using TEMPO data to show reproducibility between to datasets 342
Figure 2-12 Adoption rate as a function of payback period for different averaging methods 343
Figure 2-13 Maximum Adoption Rate Caps in Payback Schedules for Final Rule 345
Figure 2-14 Adoption Rate to Payback Period Comparison for FRM 347
Figure 4-1 Heavy-duty BEV charging profiles for weekdays for the interim reference case 578
Figure 4-2 Heavy-duty BEV charging profiles for weekends for the interim reference case 578
Figure 4-3 Net U.S. imports of refined liquid fuels and crude oil prices since 1995 584
Figure 4-4 Yearly downstream CH4 inventory for the reference case and final standards from 2027 through 2055 591
Figure 4-5 Yearly downstream N2O inventory for the reference case and final standards from 2027 through 2055 592
xxi
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Figure 4-6 Yearly downstream CChe inventory for the reference case and final standards from 2027 through 2055
593
Figure 4-7 Yearly downstream NOx inventory for the reference case and final standards from 2027 through 2055594
Figure 4-8 Yearly downstream PM2 5 inventory for the reference case and final standards from 2027 through 2055
595
Figure 4-9 Yearly downstream VOC inventory for the reference case and final standards from 2027 through 2055
596
Figure 4-10 Downstream CO2 reductions from the final standards by regulatory class, source type, fuel type, and
emission process for calendar years (CY) 2035, 2045, and 2055 598
Figure 4-11 Downstream CH4 reductions from the final standards by regulatory class, source type, fuel type, and
emission process for calendar years (CY) 2035, 2045, and 2055 599
Figure 4-12 Downstream NOx reductions from the final standards by regulatory class, source type, fuel type, and
emission process for calendar years (CY) 2035, 2045, and 2055 601
Figure 4-13 Downstream PM2 5 reductions from the final standards by regulatory class, source type, fuel type, and
emission process for calendar years (CY) 2035, 2045, and 2055 602
Figure 4-14 Downstream VOC reductions from the final standards by regulatory class, source type, fuel type, and
emission process for calendar years (CY) 2035, 2045, and 2055 604
Figure 4-15 Yearly GHG emissions increase from EGUs from the final standards from 2027 through 2055 610
Figure 4-16 Yearly criteria pollutant emissions increase from EGUs from the final standards from 2027 through 2055
612
Figure 4-17 Yearly GHG emissions reductions from refineries from the final standards from 2027 through 2055 .614
Figure 4-18 Yearly criteria pollutant emissions reductions from refineries from the final standards from 2027 through
2055 616
Figure 4-19 Year-over-year net CO2 emission impacts of the final standards from 2027 through 2055 620
Figure 4-20 Year-over-year net NOx emission impacts of the final standards from 2027 through 2055 622
Figure 4-21 Year-over-year net VOC emission impacts of the final standards from 2027 through 2055 623
Figure 4-22 Year-over-year net PM2.5 emission impacts of the final standards from 2027 through 2055 625
Figure 4-23 Year-over-year net SO2 emission impacts of the final standards from 2027 through 2055 626
Figure 4-24 Yearly downstream C02e inventory for the reference case, final standards, and alternative from 2027
through 2055 629
Figure 4-25 Comparison of net C02e emission impacts of the final standards and alternative from 2027 through 2055
633
Figure 4-26 Comparison of projected lifecycle C02e/kg of delivered hydrogen from distributed grid PEM electrolysis
to alternative hydrogen production pathways from 2028 through 2055 638
Figure 4-27 Yearly downstream C02e inventory for the reference case and final standards from 2027 through 2055,
including both our main modeling and reference case sensitivity analysis 648
Figure 6-1 Workers per million dollars in sales, adjusted for domestic production 741
Figure 7-1 U.S. Tight Oil Production by Producing Regions (in MMBD) and West Texas Intermediate (WTI) Crude
Oil Spot Price (in U.S. Dollars per Barrel), Source: EIA- 795
XXll
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List of Equations
Equation 2-1 MY 2030 Payback Schedule Calculation 345
Equation 2-2 Weighted Energy Consumption per Mile for Tractors 348
Equation 2-3 Weighted Energy Consumption per Mile for Vocational Vehicles 348
Equation 2-4 Duty Cycle Weighted Average Air Conditioning Energy Requirement 349
Equation 2-5 Road Load Power 350
Equation 2-6 Negative Road Load Power 351
Equation 2-7 Regenerative Braking Power 351
Equation 2-8 Recovered Energy 351
Equation 2-9 Tractive Energy 352
Equation 2-10 Percent Regenerative Braking 352
Equation 2-11 Energy Recovered from Regenerative Braking 352
Equation 2-12 ZEV Baseline Line Energy Consumption Per Mile 353
Equation2-13 ZEV Vehicle Level Energy Consumption Per Mile 353
Equation 2-14 VMT for Vehicle Age i 353
Equation 2-15 Cumulative VMT over Year i 354
Equation 2-16 PTO Calculation 354
Equation 2-17 ICE Vehicle Fuel Consumption 355
Equation 2-18 DEF Consumption 355
Equation 2-19 Cost of the ICE powertrain system 355
Equation 2-20 SAR for Each Vehicle ID to SA of a Class 8 Bus 356
Equation 2-21 Energy Consumption from Heating or Cooling per mile 357
Equation 2-22 Battery Conditioning per mile 357
Equation 2-23 BEV Baseline Energy Consumption 358
Equation 2-24 BEV Temperature Energy Consumption per Mile 358
Equation 2-25 Total Energy Consumption Per Mile For BEV 359
Equation 2-26 Battery Pack Sizing 359
Equation 2-27 Total number of battery cycles for vehicle age 0 to age 9 360
Equation 2-28 Battery single cycle 360
Equation 2-29 Actual daily energy use 360
Equation 2-30 Daily possible energy use 360
Equation 2-31 Weight of the Battery Pack 361
Equation 2-32 Motor Mass 361
Equation 2-33 Weight of BEV Powertrain 361
Equation 2-34 Payload Impact 361
Equation 2-35 Pack Volume 362
Equation 2-36 Power Required for Vehicle Acceleration 362
Equation 2-37 Power Required for 6% Slope 363
Equation 2-38 Power of Electric Motor 363
Equation 2-39 Cost of the BEV powertrain system 364
Equation 2-40 Cost of the Battery Pack 364
Equation 2-41 Cost of the E-Motor 365
Equation 2-42 Power of Fuel Cell Stack 365
Equation 2-43 FCEV Battery Pack Sizing 366
Equation 2-44 FCEV Total Energy Consumption Per Mile 367
Equation 2-45 FCEV Temperature Energy Consumption per Mile 367
Equation 2-46 Total Energy Consumption Per Mile For FCEV 368
Equation 2-47 Maximum Daily Energy Consumption of a FCEV 368
Equation 2-48 Required Hydrogen Storage Weight 368
Equation 2-49 Daily Operational Energy Consumption of a FCEV 369
Equation 2-50 Required Hydrogen Weight for Operating the FCEV 369
Equation 2-51 Cost of the FCEV powertrain system 369
Equation 2-52 Cost of the Fuel Cell System 369
Equation 2-53 Cost of Hydrogen Tank 370
xxill
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Equation 2-54 Hours to Charge by EVSE Type 370
Equation 2-55 Number of vehicles shared per EVSE port 371
Equation 2-56 Actual number of vehicles sharing an EVSE port 371
Equation 2-57 Per vehicle EVSE cost 372
Equation 2-58 New BEV sales by model year 373
Equation 2-59 EVSE port counts 373
Equation 2-60 Power at 2C charge rate 374
Equation 2-61 Daily Energy Consumption 374
Equation 2-62 Time for Mega-watt Charging 375
Equation 2-63 Additional Energy Consumption to Achieve 90th Percentile Daily VMT from 50th Percentile Daily
VMT 375
Equation 2-64 Time to Mega-watt Charge from 50th Percentile Daily VMT to 90th Percentile Daily VMT 375
Equation 2-65 Payback period for each vehicle 375
Equation 2-66 Upfront cost delta between ICE and ZEV 375
Equation 2-67 Upfront costs for ICE or FCEV 376
Equation 2-68 Upfront costs for BEV 376
Equation 2-69 Annual operating cost 376
Equation 2-70 Cumulative operational savings 376
Equation 2-71 Annual Diesel Fuel Consumption Cost 377
Equation 2-72 Annual Electricity Fuel Consumption Cost 377
Equation 2-73 Annual Hydrogen Consumption Cost 378
Equation 2-74 Annual Maintenance and Repair of ICE Cost 378
Equation 2-75 Annual Maintenance and Repair of BEV Cost 379
Equation 2-76 Annual Maintenance and Repair of FCEV Cost 379
Equation 2-77 Annual insurance cost 379
Equation 2-78 Sales-Weighted Vehicle Percentage 380
Equation 2-79 Aggregated Technical Adoption 381
Equation 2-80 Sales Weighted Battery Size for each MOVES SourceType ID and RegClass ID 381
Equation 2-81 Annual Battery Demand for each MY in GWh 381
Equation 2-82 Calculation for MY 2032 SI LHD Urban Standard 415
Equation 2-83 Calculation for MY 2032 SI LHD Multi-Purpose Standard 415
Equation 2-84 Calculation for MY 2032 SI LHD Regional Standard 415
Equation 2-85 Calculation for MY 2032 SI MHD Urban Standard 415
Equation 2-86 Calculation for MY 2032 SI MHD Multi-Purpose Standard 415
Equation 2-87 Calculation for MY 2032 SI MHD Regional Standard 415
Equation 2-88 Residual Value Fraction 469
Equation 2-89 Interest Paid per Year per Powertrain Type 470
Equation 2-90 Total Interest per Year 470
Equation 3-1 Maintenance and repair costs dollars per mile as a function of age and vehicle type 529
Equation 4-1 Calculation of HD BEV energy consumption rates using Energy Efficiency Ratio (EER) 566
Equation 4-2 Calculation method of an incremental EGU emission factor from a reference and control cases 579
xxiv
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Executive Summary
The Environmental Protection Agency (EPA) is promulgating new greenhouse gas (GHG)
emissions standards for model year (MY) 2032 and later heavy-duty highway vehicles that phase
in starting as early MY 2027 for certain vehicle categories. The phase in revises certain MY
2027 GHG standards that were established previously under EPA's Greenhouse Gas Emissions
and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles - Phase 2 rule
("HD GHG Phase 2"). Although there have been significant emissions reductions achieved by
previous rulemakings, GHG emissions from HD vehicles continue to adversely impact public
health and welfare, and there is a critical need for further GHG reductions. The transportation
sector is the largest U.S. source of GHG emissions, representing 29 percent of total GHG
emissions.1 Within the transportation sector, heavy-duty vehicles are the second largest
contributor to GHG emissions and are responsible for 25 percent of GHG emissions in the
sector.2 GHG emissions have significant impacts on public health and welfare as evidenced by
the well-documented scientific record and as set forth in EPA's Endangerment and Cause or
Contribute Findings under Section 202(a) of the CAA.3 Additionally, major scientific
assessments continue to be released that further advance our understanding of the climate system
and the impacts that GHGs have on public health and welfare both for current and future
generations.
We estimate this rule will achieve approximately 1 billion metric tons in net CCh-equivalent
emission reductions from 2027 through 2055 and would continue to provide reductions
thereafter. These anticipated GHG emission reductions will make an important contribution to
efforts to limit climate change and its anticipated impacts benefiting all U.S. residents, including
populations such as people of color, low-income populations, tribes and Indigenous
communities, and/or children that may be especially vulnerable to various forms of damages
associated with climate change. In our modeled potential compliance pathway, we project that
manufacturers' compliance with the final GHG emission standards will lead to an increase in HD
ZEVs relative to our reference case (i.e., without the rule), which will also result in downstream
reductions of vehicle emissions of non-GHG pollutants that contribute to ambient concentrations
of ozone, particulate matter (PM2.5), nitrogen dioxide (NO2), CO, and air toxics. Exposure to
these non-GHG pollutants is linked to adverse human health impacts such as premature death as
well as other adverse public health and environmental effects.
The health and environmental effects associated with GHG emissions are a classic example of
a negative externality (an activity that imposes uncompensated costs on others). With a negative
externality, an activity's social cost (the cost borne to society imposed as a result of the activity
taking place) exceeds its private cost (the cost to those directly engaged in the activity). In this
case, as described below and in Chapter 5, GHG emissions from heavy-duty vehicles impose
public health and environmental costs on society. However, these added costs are not reflected in
the costs of those using these vehicles. The current market and regulatory scheme do not correct
this externality because firms in the market are rewarded for minimizing their production costs,
including the costs of pollution control, and do not benefit from reductions in emissions. In
1 EPA (2023). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2021 (EPA-430-R-23-002, published
April 2023).
2 Id.
3 74 FR 66496, December 15, 2009; see also 81 FR 54422, August 15, 2016.
1
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addition, firms that may take steps to reduce air pollution may find themselves at a competitive
disadvantage compared to firms that do not. The GHG emission standards that EPA is finalizing
help address this market failure and reduce the negative externality from these emissions by
providing a regulatory incentive for vehicle manufacturers to produce engines that emit fewer
harmful pollutants and for vehicle owners to use those cleaner engines.
This Regulatory Impact Analysis (RIA) contains supporting documentation for the EPA final
rulemaking and addresses requirements in Clean Air Act Section 317 and requirements under
Executive Order (E.O.) 12866 to estimate the benefits and costs of major new pollution control
regulations. The preamble to the Federal Register notice associated with this document provides
the full context for the EPA final rule, including statutory and executive order reviews in Section
X, and it references this RIA throughout.
This document contains the following Chapters:
Chapter 1 Industry Characterization and Technologies to Reduce Greenhouse Gas
Emissions
This chapter provides an overview of the HD industry, GHG-reducing technologies, and
market information for each of the affected industries for background information purposes. To
assess the impacts of GHG regulations upon the affected industries, it is important to understand
the nature of the industries impacted by the regulations. These industries include the
manufacturers of Class 2b/3 incomplete vehicles through Class 8 trucks, engines, and on-road
equipment. Users of these vehicles, including large fleets and corporations, have become
increasingly interested in incorporating GHG-reducing technologies for internal combustion
engine (ICE)-powered vehicles (e.g., hybrids, hydrogen ICEs) and zero-emission vehicles
(ZEVs) into their operation - and technologies for vehicles with ICE, along with a range of
electrification, exist today and continue to evolve to further reduce and eliminate exhaust
emissions from new motor vehicles. We discuss these technologies in detail in this chapter.
Chapter 2 Technology Assessment
This chapter describes the operational characteristics and costs that we used to estimate the
heavy-duty technologies' feasibility and suitability and the analysis for the modeled potential
compliance pathway's technology package that supports the feasibility of the final standards for
MYs 2027 through 2032. Our analysis for this final rule further shows that a diverse range of HD
vehicle technologies are feasible and may be used to comply with the final standards to reduce
GHG emissions, including ICE (including alternative-fueled), hybrid, and plug-in hybrid vehicle
technologies, hydrogen-fueled ICE technologies (H2 ICE), BEV technologies, and FCEV
technologies. To conduct the analysis, EPA developed a flexible spreadsheet-based framework
called the Heavy-Duty Technology Resource Use Case Scenario (HD TRUCS) tool.
HD TRUCS evaluates the design features needed to meet the energy and power demands of
various HD vehicle types. To build technology packages using HD TRUCS, we created 101
representative vehicles in HD TRUCS that cover the full range of weight classes within the
scope of the final standards (Class 2b through 8 vocational vehicles and tractors). The
representative vehicles cover many aspects of work performed by the industry. This work was
translated into total energy and power demands per vehicle type based on everyday use of HD
vehicles, ranging from moving goods and people to mixing cement. We then identified the
2
-------
technical properties and costs required to meet the vehicles' operational needs using GHG-
reducing technologies under the final standards.
Chapter 3 Program Costs
This chapter presents estimates of the technology package, manufacturer, consumer, and
social costs. In addition, the manufacturer and consumer cost analyses quantitatively include
three tax credits from the Inflation Reduction Act as appropriate, specifically the battery tax
credit under section 13502 (for both manufacturer and consumer costs), the vehicle tax credit
under section 13403 (for consumer costs), and electric vehicle supply equipment (EVSE) tax
credit under section 13404 (for consumer costs). The technology package costs are presented as
direct manufacturing costs and associated indirect costs, which together represent the estimated
costs incurred by manufacturers (i.e., regulated entities) to comply with the final standards.
Chapter 4 Emission Inventories
This chapter presents our analysis of the national emissions impacts of GHGs from the final
rule for calendar years 2027 through 2055 from both downstream and some upstream sources.
We estimated onroad downstream national inventories using an updated version of EPA's Motor
Vehicle Emission Simulator (MOVES) model (MOVES4.R3), and we estimated upstream
emissions sources using the 2022 post-IRA version of the Integrated Planning Model (IPM)
combined with our estimate of the final rule's impacts on refinery emissions.
Chapter 5 Health and Environmental Impacts
This chapter presents a discussion of the climate change impacts of GHGs; health and
environmental effects associated with exposure to ambient concentrations of non-GHG
pollutants; as well as environmental justice impacts from the emissions changes associated with
the final rulemaking. The discussion of health impacts is mainly focused on describing the
effects of air pollution on the population in general. Additionally, children are recognized to have
increased vulnerability and susceptibility related to air pollution and other environmental
exposures; this and effects for other vulnerable and susceptible groups are discussed in this
chapter.
Chapter 6 Economic and Other Impacts
This chapter discusses potential impacts of the final rule on vehicle sales including potential
shifts among modes and classes of vehicles, and between domestic and foreign sales. It also
discusses the acceptance of GHG-reducing technologies by HD purchasers and the potential for
rebound effects on vehicle miles traveled. This chapter then discusses the potential impacts of
the final rule on employment. Finally, this chapter discusses the impacts of the final rule on U.S.
oil imports and electricity consumption.
Chapter 7 Benefits
This chapter describes benefits attributable to the final rule from three sources: climate
benefits, criteria pollutant health benefits, and energy security benefits. We estimate the social
benefits of GHG reductions expected to occur as a result of the final standards using estimates of
the social cost of greenhouse gases (SC-GHG), specifically using the social cost of carbon (SC-
CO2), social cost of methane (SC-CH4), and social cost of nitrous oxide (SC-N2O). We monetize
the economic benefits from improvements in human health resulting from criteria pollutant
3
-------
emissions reductions using PM2.5-related benefit-per-ton values. This chapter also describes
energy security impacts, including monetized benefits, associated with an expected reduction in
demand for liquid fuels.
Chapter 8 Net Benefits
This chapter compares the estimated range of total benefits to total costs associated with the
final rule. Benefits include those associated with reductions of GHGs, monetized health benefits
from changes in PM2.5, energy security benefits, fuel savings, and vehicle-related operational
savings. Total costs include costs for both new technology and the operating costs associated
with that new technology. The chapter presents three different methods for comparing benefits to
costs.
Chapter 9 Small Business Analysis
This chapter presents an analysis of the potential impacts of the final rule on small entities
that will be subject to the HD vehicle provisions of this final rule. The small businesses
considered in this analysis include manufacturers of the following types: heavy-duty
conventional vehicles and heavy-duty electric vehicles. The analysis estimates that no small
entities in these manufacturer categories will experience an impact of 3% or more of their annual
revenue as a result of our final rule.
4
-------
Chapter 1 Industry Characterization and Technologies to Reduce GHG
Emissions
1.1 Introduction
To assess the impacts of the final greenhouse gas (GHG) regulations upon the affected
industries, it is important to understand the nature of the industries impacted by the regulations.
These industries include the manufacturers of Class 2b/3 incomplete vehicles4 through Class 8
trucks, engines, and on-road equipment. Users of these vehicles, including large fleets and
corporations, have become increasingly interested in incorporating highway heavy-duty (HD)
vehicles using zero emissions vehicle (ZEV) technologies into their operations. To meet this
demand, many HD vehicle manufacturers and suppliers have been conducting research on
battery electric vehicle (BEV) technologies and hydrogen fuel cell electric vehicle (FCEV)
technologies. Initial vehicles from this research investment are now entering the market.
Adoption of these ZEVs requires the establishment of HD vehicle charging and hydrogen
refueling infrastructure. This chapter provides an overview of the heavy-duty industry, an
overview of GHG-reducing technologies, and market information for each of the affected
industries for background information purposes.
1.2 Heavy-duty Vehicle Industry
Heavy-duty vehicles perform many different types of work including moving people and
goods, cleaning streets, and providing access to fix utilities. Here we focus on the size of the
goods-moving market to highlight the importance and impact of the sector.
1.2.1 Freight Work Performed by and Operation of Heavy-duty Trucks
In 2021, heavy-duty trucks carried 65 percent of all freight moved in the U.S. by tonnage and
63 percent by value in the U.S, and heavy-duty trucks are expected to move freight at an even
greater rate in the future. According to the U.S. Department of Transportation's (DOT's) Federal
Highway Administration (FHWA), the U.S. transportation system moved, on average, an
estimated 53.6 million tons of goods worth an estimated $54 billion (in U.S. 2021$) per day in
2021. Of this, heavy-duty trucks moved over 12 billion tons of freight worth an estimated $11
trillion in 2021, or an average of nearly 33 million tons of freight worth $30 billion per day. The
FHWA's 2022 Freight Analysis Framework estimates that this tonnage will increase about 1.6
percent per year from 2023 to 2050, and that the value of the freight moved is increasing faster
4 Complete heavy-duty vehicles at or below 14,000 lbs. GVWR are chassis-certified under 40 CFR part 86, while
incomplete vehicles at or below 14,000 lbs. GVWR may be certified to either 40 CFR part 86 (meeting standards
under subpart S) or 40 CFR part 1037 (installed engines would then need to be certified under 40 CFR part 1036).
Class 2b and 3 vehicles are primarily chassis-certified complete commercial pickup trucks and vans. We separately
proposed a combined light-duty and medium-duty rulemaking to set more stringent standards for complete and
incomplete vehicles at or below 14,000 lbs. GVWR that are certified under 40 CFR part 86, subpart S. The standards
finalized in this rule will apply for all heavy-duty vehicles above 14,000 lbs. GVWR, except as noted in 40 CFR
1037.150(1). The final standards in this rule will also apply for incomplete heavy-duty vehicles at or below 14,000
lbs. GVWR if vehicle manufacturers opt to certify those vehicles under 40 CFR part 1037 instead of certifying under
40 CFR part 86, subpart S.
5
-------
than the tons transported. Figure 1-1 shows the total tons of freight moved by each mode of
freight transportation in 2021, and projections for 2030 and 2050.5
25000
20000
15000
c
= 10000
5000
12021
12030
2050
Truck
Rail
Water Air Other, Multiple Pipeline
Unknown Modes
Figure 1-1 Total Weight of Shipments by Transportation Mode
According to the 2020 Highway Statistics published by the U.S. FHWA,6 in 2020 there were
just over 2.9 million combination tractors (e.g. Class 7 and 8) registered in the U.S out of a total
of over 13 million trucks of all types (private and commercial) registered in the U.S. Table 1-1
presents the number of trucks compared to the number of vessels and other modes of
transportation that move freight.6
Table 1-1 Number of U.S. Vehicles, Vessels, and Other Conveyances: 2000-2020
Mode of
Transportation
Classification
2000
2010
2020
Highway
Trucks
8,022,649
10,770,054
13,479,382
Trucks, single-unit 2-axle 6-tire or more
5,926,030
8,217,189
10,500,105
Trucks, combination
2,096,619
2,552,865
2,979,277
Total highway vehicles
225,821,241
250,070,048
275,924,442
Rail
Locomotive, Class 1
20,028
23,893
23,544
Freight cars, total
1,380,796
1,309,029
1,658,423
Freight cars. Class
560,154
397,730
252,400
Freight cars, Nonclass
132,448
101,755
Freight cars, car companies and shippers
688,194
809,544
Water
Nonself-propelled vessels
31,372
30,265
34,168
Self-propelled vessels
9,293
9,618
10,333
Total vessels
40,665
39,883
44,501
5 U.S. Department of Transportation, Bureau of Transportation Statistics, Freight Facts and Figures 2022. Available
online: https://data.bts.gOv/stories/s/Moving-Goods-in-the-United-States/bcyt-rqmu.
6 U.S. Department of Transportation, Bureau of Transportation Statistics, Freight Facts and Figures 2020. "Number
of trucks, locomotives, rail cars, and vessels" Available online: https://data.bts.gov/stories/s/Freight-Transportation-
System-Extent-Use/r3vy-npqd.
6
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In terms of growing international trade, trucks are the most common mode used to move
imports and exports between both borders and inland locations. Table 1-2 shows the tons and
value moved by truck compared to other transportation methods.
Table 1-2 Domestic Mode of Exports and Imports by Tonnage and Value from 2020-20557
Domestic
Mode
Tons (thousands)
Value (millions of 2017 $)
2020
2030
2050
2020
2030
2050
Grand Total
2,308,598
2,891,495
3,979,273
3,599,583
4,866,814
7,861,618
Truck
956,117
1,154,776
1,759,076
2,318,916
3,060,420
5,041,065
Rail
425,270
493,251
764,314
323,598
397,136
655,231
Water
182,221
290,304
382,976
76,488
133,005
190,200
Air
(including
truck-air)
4,401
5,363
8,806
458,346
614,850
1,012,423
Multiple
modes and
mail
132,907
181,206
269,643
226,276
386,166
644,729
Pipeline
484,425
632,470
688,627
146,840
182,538
197,914
Other and
unknown
3,262
10,317
17,135
10,786
52,763
91,445
No domestic
mode
119,995
123,808
88,696
38,334
39,937
28,611
Conversely, transportation of foreign trade is dominated by movement via water with trucks
hauling approximately 11 percent of imported freight followed by pipeline and rail. As of 2022,
Canada was the top trading partner with the U.S. in terms of the value of the merchandise traded
($361 billion in U.S. 2017$), Mexico was second ($219 billion in U.S. 2017$), Japan was third
($188 billion in U.S. 2017$). Truck traffic is the most heavily utilized transportation mode from
the two North American trade partners, Mexico, and Canada. As of 2021, almost 63 percent of
the value and over 29 percent of the total imported and exported freight moved between the U.S.,
Canada, and Mexico was hauled by truck, as shown in Figure 1-2.8
7 U.S. Department of Transportation, Bureau of Transportation Statistics, Freight Facts and Figures 2022. Available
online: https://data.bts.gOv/stories/s/Moving-Goods-in-the-United-States/bcyt-rqmu.
8 U.S. Department of Transportation, Bureau of Transportation Statistics 2019. Available online:
https://data.bts.gOv/stories/s/International-Freight-Gateways/4s7k-yxvu.
7
-------
900 250
Air Other Pipeline Rail Truck Water
Value (billions of current U.S. dollars) Weight (millions of short tons)
Figure 1-2 Value of Freight Moved Between the U.S., Canada, and Mexico
1.2.2 Existing Heavy-Duty Truck Market Benchmarking
The heavy-duty vehicle segment is a dynamic industry that includes a variety of types of
vehicles and possible configurations. This final program will address heavy-duty vehicles that
fall into the following regulatory categories established by EPA: vocational vehicles in Classes
2b-8 and tractors in Classes 7 and 8.
Class 2b and 3 vocational vehicles at issue in this final program include certain incomplete9
pickups, incomplete vans, and vocational vehicles such as heavy-duty work truck-type pickups
and related van-type vehicles that are in a limited build configuration and ready to receive final
outfitting by body building companies. The latter case involves the manufacture of vehicles that
may be used for a variety of commercial purposes, including use as ambulances, shuttle buses,
etc. Class 4-8 vocational vehicles encompass a wide range of heavy-duty vehicles such as
delivery trucks, school buses, etc. Combination tractors typically operate as either short-haul or
long-haul trucks. Combination tractors are designed either with sleeping quarters (sleeper cab) or
without sleeping quarters (day cab). Generally, day cab tractors are used to haul trailers over
shorter distances, typically into metropolitan areas. Sleeper cab tractors generally haul trailers
longer distances between cities and states with trips well over 1,000 miles in length.
To understand the existing heavy-duty industry, we performed an analysis of current internal
combustion engine (ICE) powered heavy-duty vehicles in the market and their capabilities to
generate typical power requirements and rates of energy consumption. This information was then
used to help inform our decisions on technical feasibilities of HD vehicle technologies, including
9 As explained and defined in 40 CFR 1037.801, the primary use of the term "incomplete vehicle" is to distinguish
whether a vehicle is complete when it is first sold as a vehicle, where an incomplete vehicle is defined as not a
complete vehicle and a complete vehicle is defined as a functioning vehicle that has the primary load carrying
device or container (or equivalent equipment) attached. Incomplete vehicles may also be cab-complete vehicles.
8
-------
zero-emission vehicle (ZEV) technologies,10 to include in the technology packages for the final
program (which form a potential compliance pathway to demonstrate the feasibility of the final
GHG emission standards) using an internally developed tool discussed in detail in RIA Chapter
2.
We selected 76 ICE vehicles that represent much of the heavy-duty industry and that also had
similar ZEV options available in MY 2021. Some of these vehicle types can be used for multiple
duty cycles. Table 1-3 lists the publicly available information collected to benchmark basic
powertrain and performance criteria including make; model; vehicle type; weight class; fuel
type; engine manufacturer, model, displacement, mass, power, and torque; transmission make,
model, and mass; fuel tank size; mass of fuel; Diesel Exhaust Fluid (DEF) tank size; mass of
DEF; total mass of the engine, transmission, fuel, and DEF; vehicle minimum wheelbase; and
vehicle width.
10 We use the term ZEV to refer to technologies that result in zero tailpipe emissions. Example ZEV technologies
include battery electric vehicles and fuel cell vehicles.
9
-------
Table 1-3 Benchmarked Conventional Vehicles with Similar ZEV Options
Vehicle
Width
(m)
2.4
2.4
2.4
2.4
2.4
2.4
2.4
2.4
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
Mill.
Wheel-
base
(m)
4.3
4.3
4.3
3.6
3.6
3.6
3.5
3.5
5.5
5.5
c--
c--
4.3
4.3
5..6
Total
System
Mass
(kg)
551
593
1153
1153
1359
1171
ON
536
1452
1066
1452
1066
1040
1324
1040
1324
1040
DEF
Mass
(kg)
VN
VN
232
232
232
VN
VN
VN
VN
VN
VN
VN
VN
VN
VN
VN
VN
Tank
Size (L)
VN
VN
57
57
57
VN
VN
VN
VN
VN
VN
VN
VN
VN
VN
VN
VN
Fuel
Mass
(kg)
129
c--
193
193
193
159
ON
386
VN
386
VN
258
258
258
258
258
Tank
Size (L)
254
LZZ
LZZ
LZZ
LZZ
235
-------
Make
Blue Bird11
T3
s-
3
s
3
ITi
ITi
ITi
ITi
ITi
ITi
303
ITi
379
379
379
379
379
Type
Diesel
Gas
Gas
Diesel
Gas
Diesel
Gas
Diesel
Gas
Gas
Gas
Gas
Diesel
Diesel
Diesel
Diesel
Diesel
Transmission
—
£g
297
150
150
150
150
150
150
150
150
295
295
295
295
299
Model
B400R
10R140
10R140
10R140
10R140
10R140
10R140
10R140
10R140
6R140
6R140
6R140
DT12-HE
DT12-HE
DT12-HE
DT12-HE
Endurant
MFR
Allison
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Detroit
Diesel
Detroit
Diesel
Detroit
Diesel
Detroit
Diesel
Eaton
Engine
Torque
(Nm)
1166
542
355
1119
635
1119
635
1119
635
635
635
635
2508
2508
2373
2779
2305
Power
(kW)
224
224
205
246
261
246
261
246
261
261
261
261
377
391
377
447
373
Mass
(kg)
769
204
204
499
281
499
281
499
281
281
281
281
1128
1128
1233
1287
1017
Disp
(L)
ON
3.5
3.5
6.7
7.3
6.7
7.3
6.7
7.3
7.3
7.3
7.3
12.8
12.8
14.8
15.6
-------
Model
L9
3.5
Ecoboos
3.5
PFDI
6.7
Powerst
VN
6.7
Powerst
VN
6.7
Powerst
VN
VN
VN
VN
DD13
DD13
Gen5
DDI 5
DD16
X12
MFR
Cummins
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Ford
Detroit
Diesel
Detroit
Diesel
Detroit
Diesel
Detroit
Diesel
Cummins
Wgt
Class
00
ITi
ITi
5,6
5,6
3,4
00
00
00
00
00
Type
Transit
Bus
Panel
Van
Panel
Van
Straight
Truck
Straight
Truck
Straight
Truck
Straight
Truck
Straight
Truck
Straight
Truck
Panel
Van
Panel
Van
Panel
Van
Tractor
Tractor
Tractor
Tractor
Tractor
Vehicle
Model
E-Z Rider II
35'
Transit
Transit
F-450
F-450
F-550
F-550
F-600
F-600
F-53
F-59
E-Series
Cutaway
Cascadia
Cascadia
Cascadia
Cascadia
Cascadia
Make
Eldorado National
Ford17
s-
O
tin
S-
o
tin
00
S-
o
tin
o
tin
ON
s-
O
tin
o
tin
O
-------
£g
322
322
322
193
229
290
225
214
258
258
298
298
298
298
298
Fuel
Tank
Size (L)
379
379
379
LZZ
LZZ
IT>
303
341
265
284
303
303
350
350
350
350
350
Type
Diesel
Diesel
Diesel
Diesel
Gas
Gas
Gas
Diesel
Diesel
Gas
Diesel
Diesel
Diesel
Diesel
Diesel
Diesel
Diesel
Mass
(kg)
299
442
442
147
147
147
197
197
147
297
297
VN
VN
VN
VN
VN
o
"8
C/3
£/)
C
Model
Endurant
UltraShift
Plus VCS
UltraShift
Plus VCS
2200
2200
6R140
2200
B300
B300
2200
B400R
B400R
VN
VN
VN
VN
VN
H
MFR
Eaton
Eaton
Eaton
Allison
Allison
Ford
Allison
Allison
Allison
Allison
Allison
Allison
VN
VN
VN
VN
VN
Torque
(Nm)
2508
2508
1559
895
498
644
644
759
759
644
759
759
1373
1569
1569
1745
1844
Power
(kW)
373
377
283
224
230
261
261
179
179
261
179
179
250
280
280
295
302
Engine
Mass
(kg)
1430
1128
769
485
VN
281
281
485
485
281
485
485
066
VN
VN
VN
VN
Disp
(L)
IT>
12.8
ON
6.7
7.3
7.3
6.7
6.7
7.3
6.7
6.7
11.2
9.9
9.9
9.9
12.3
Model
X15
DD13
L9
ISB 6.7
VN
VN
VN
ISB 6.7
ISB 6.7
VN
ISB 6.7
ISB 6.7
D6AC
D6HB3
8
D6HA3
8
D6HA4
OA
D6CB4
1
MFR
Cummins
Detroit
Diesel
Cummins
Cummins
GM
Ford
Ford
Cummins
Cummins
Ford
Cummins
Cummins
Hyundai
Hyundai
Hyundai
Hyundai
Hyundai
Wgt
Class
OO
7, 8
7, 8
IT>
IT>
6,7
6,7
7, 8
7, 8
7, 8
OO
OO
OO
OO
OO
Vehicle
Type
Tractor
Straight
Truck
Straight
Truck
Straight
Truck
Straight
Truck
Transit
Bus
Transit
Bus
Transit
Bus
Transit
Bus
Transit
Bus
Transit
Bus
Transit
Bus
Straight
Truck
Straight
Truck
Straight
Truck
Straight
Truck
Straight
Truck
Model
Cascadia
M2 112
M2 112
MT45
MT45
Trolley
Villager
Mainstreet
Streetcar
View
Commuter
Urban
Xcient
Xcient
Xcient
Xcient
Xcient
13
-------
Make
_c
%
'55
&
O
s-
_C
%
'55
&
_c
"§)
'55
&
_C
'55
&
32
Freightliner
Hometown
Manufacturing 33
Hometown
Manufacturing34
Hometown
Manufacturing35
Hometown
Manufacturing36
Hometown
Manufacturing37
Hometown
Manufacturing38
Hometown
Manufacturing39
Hyundai40
o
'3
G
1
O
'3
G
1
O
'3
G
1
O
'3
G
1
Vehicle
Width
(m)
-------
MFR
Allison
Allison
Allison
PACC
AR
PACC
AR
Allison
VN
VN
Allison
Eaton
Eaton
VN
VN
ZF
Allison
Allison
Eaton
Engine
Torque
(Nm)
613
895
895
2508
2305
1661
400
2102
1966
705
976
949
976
1166
895
2305
2508
Power
(kW)
160
186
186
380
339
265
120
339
306
149
194
261
194
194
186
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Motorcoach
Industries 46
Motorcoach
Industries 47
International48
International49
International50
New Flyer51
Nova Bus52
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Endurant
Endurant
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Eaton
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Cummins
Volvo
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1.2.3 Heavy-duty Vehicle Sales
The U.S. Energy Information Administration's (EIA's) Annual Energy Outlook (AEO) sales
estimates60 from the 2023 AEO report ("AEO 2023")61 were used to characterize sales in the
HDV market. The overall vehicle class sales percentages for calendar year (CY) 2023 are shown
in Figure 1-3. Total heavy-duty sales in 2023 were over 730,000 units, with 35.8 percent
56 PACCAR Engine. Available online: https://paccarpowertrain.com/wp-
content/uploads/2022/03/P AC56_PX9SpecSheet_2021_Final_HighResDigital.pdf
57 Thomas Built Buses. Saf-T-Liner C2 School Bus. Available online: https://thomasbuiltbuses.com/school-
buses/saf-t-liner-c2/.
58 Volvo Trucks USA. VNR: It's Time to Meet the Family—Specifications. Available online:
https://www.volvotrucks.us/trucks/vnr/specifications/.
59 Autocar, LLC. ACTT 4X2. Available online:
https ://d3 w5dxa 1 iffln. cloudfront. net/media/1754/actt_4x2_dot_specs_v2 .pdf.
60 Although AEO sales estimates for heavy-duty vehicles do not include buses, RVs, and emergency vehicles, the
sales estimates are still useful in predicting trends in the heavy-duty market by overall percentage of new vehicle
sales in different weight classes as well as percentage of new vehicle sales by energy type.
61 U.S. Energy Information Administration, Annual Energy Outlook 2023, Table 49: Freight Transportation Energy
Use available here: https://www.eia.gov/outlooks/aeo/data/browser/#/?id=58-
AE02023&cases=ref2023&sourcekey=0
17
-------
belonging to Class 3 vehicles (including complete and incomplete), 25.5 percent belonging to
Class 4-6 vehicles, and 38.7 percent belonging to Class 7-8 vehicles. Comparatively, by 2050
projected sales for Class 3 heavy-duty vehicles (including complete and incomplete) will
increase to 45.1 percent while Class 4-6 sales will increase to 27.1 percent and Class 7-8
vehicles will decrease to 27.8 percent, see Figure 1-3.
100.0%
90.0%
80.0% 38.7%
70.0%
36.9% 35.3% 33.5% 31.5% 29.7% 27.8%
u 60.0%
1c
g 50.0%
| 40.0%
¦Z.
> 30.0%
o
X 20.0%
10.0%
0.0%
25.5%
25.2%
26.3%
26.9%
27.1%
27.2%
27.1%
•II
2023 2025 2030 2035 2040 2045 2050
I Class 3 ¦ Class 4-6 ¦ Class 7-8
Figure 1-3 2023 HD Sales Percentages by AEO Categories (AEO 2023)
As shown in Figure 1-4, AEO 2023 estimates for the full range of Class 3 vehicles show that
there will be no BEV or FCEV vehicle sales in 2023, hybrid sales will be 0.2% of sales and
alternative fuel vehicles will make up 4.6% of sales. AEO 2023 estimates Class 4-6 vehicles
BEV and FCEV sales comprise less than 0.1 percent of total sales in 2023. Hybrid sales also are
estimated to make up less than 0.1 percent of sales while alternate fuel vehicles make up 2.1
percent of vehicle sales in 2023 for Class 4-6 vehicles. AEO 2023 estimates for Class 7-8
vehicles are that BEV, FCEV, and hybrid sales make up less than 0.1 percent and alternate fuel
vehicles are 1.5 percent of sales in 2023.
AEO 2023 estimates for 2050 show that for Class 3 vehicles, BEVs and FCEVs will still have
no sales, as shown in Figure 1-4. Hybrid vehicles are estimated to make up about 1 percent of
sales and alternate fuel vehicles make up 4.2 percent of sales in 2050 for Class 3 vehicles. For
Class 4-6 vehicles in 2050, BEV sales are estimated in AEO 2023 to still be less than 0.1 percent
of total sales while FCEVs will be less than 1 percent, as shown in Figure 1-4. In 2050, hybrid
sales are estimated to still make up less than 1 percent of sales while alternate fuel vehicles are
estimated to increase to 6.6 percent of vehicle sales for Class 4-6 vehicles. For Class 7-8
vehicles, AEO 2023 estimates that BEV and FCEV sales will continue to make up less than 0.3
percent of sales in 2050, as shown in Figure 1-4. In 2050, hybrid sales are expected to be less
than 0.5 percent of sales and alternate fuel vehicles are expected to increase to 2.8 percent of
sales for Class 7-8 vehicles.
18
-------
100%
90%
70%
60%
50%
30%
20%
10%
0.0%
- 0.5%
Class 3
Class 4-6
2023
Class 7-8
Class 3
Class 4-6
2050
Class 7-8
¦ FCEV
¦ Gas Hybrid
¦ Diesel Hybrid
¦ BEV
¦ Flex Fuel
¦ CNG
¦ Propane
¦ Gasoline
¦ Diesel
Figure 1-4 AEO 2022 Sales Percent by Weight Class and Energy Use for 2023 and 2050 (AEO 2023)
Table 1-4 contains the raw values of projections from AEO 2023.62 Their projections do not
include any assumptions for new regulations beyond those established by November 2022.63 The
Bipartisan Infrastructure Law and the Inflation Reduction Act are both included in AEO 2023 as
they were passed in November of 2021 and August of 2022 respectively. The 2050 Class 3-6
vehicle sales are 1.5 times the 2023 sales levels and Classes 7-8 include about a 12 percent
decrease in sales between 2023 and 2050. Alternative fuel vehicles are also projected to increase
from 2023 to 2050 with a 1.4 times increase for Class 3, a 5.1 times increase for Classes 4-6, and
a 1.7 times increase for Classes 7-8. Hybrids increase from about 650 sales in 2023 to almost
4,000 sales in 2050 for Class 3, increase from 0 sales in 2023 to over 1,700 sales for Classes 4-6,
and increase from 0 sales in 2022 to almost 900 sales in 2050 for Classes 7-8. Fuel cells are not
seen as an option for Class 3 vehicles but are expected to increase from 0 sales in 2023 to over
1,300 sales in 2050 for Classes 4-6 and from 0 sales in 2023 to over 800 sales in 2050 for
Classes 7-8.
62 U.S. Energy Information Administration, Amiual Energy' Outlook, Table 49: Freight Transportation Energy Use.
Available here: https://www.eia.gov/outlooks/aeo/data/browser/#/?id=58-AE02022®ion=0.
63 For example, California has adopted the Advanced Clean Truck (ACT) Regulation, which includes a
manufacturer requirement for zero-emission track sales. ACT is not included in AEO 2022. EPA granted the ACT
rale waiver requested by California under CAA section 209(b) on March 30, 2023. 88 FR 20688, April 6, 2023
(signed by the Administrator on March 30, 2023). ACT and other state's efforts to increase ZEV sales are discussed
in greater detail in RIA Chapter 1.3.3.
19
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Table 1-4 AEO 2023 Sales Projections in Thousands by Weight Class and Energy Use from 2023 - 2050
Heavy
-duty Vehicle Sales (thousands)
Weight
Class 3
Class 4-6
Class 7 and 8
Class
Year
2023
2030
2040
2050
2023
2030
2040
2050
2023
2030
2040
2050
Diesel
142.57
166.84
195.80
227.60
111.86
121.07
131.93
139.16
277.07
268.67
257.36
238.36
Gasoline
106.85
118.57
134.13
153.52
70.74
74.62
79.84
83.55
1.47
1.37
1.30
1.20
Propane
0.28
0.32
0.59
1.23
0.19
0.24
0.49
0.78
0.17
0.16
0.15
0.14
Compressed
0.00
0.00
0.00
0.00
0.08
0.03
0.01
0.00
4.04
2.91
4.46
6.90
Natural Gas
Flex Fuel
11.86
11.59
13.88
15.73
3.56
6.93
13.42
15.09
0.00
0.00
0.00
0.00
Battery
0.00
0.00
0.00
0.00
0.06
0.02
0.01
0.00
0.04
0.02
0.00
0.00
Electric
Diesel
0.32
0.41
0.96
1.84
0.00
0.25
0.41
0.72
0.00
0.13
0.19
0.35
Hybrid
Gasoline
0.33
0.39
1.02
2.04
0.00
0.22
0.49
1.00
0.00
0.26
0.35
0.54
Hybrid
Fuel Cell
0.00
0.00
0.00
0.00
0.00
0.43
0.73
1.35
0.00
0.43
0.53
0.82
1.3 Current Regulations and Federal Support for Reducing Heavy-Duty Vehicle GHG
Emissions
In this section, we discuss the EPA greenhouse gas emission regulations for heavy-duty
engines and vehicles, recent Federal Government legislation to support reductions in greenhouse
gas emissions, and the California Air Resources Board's Advanced Clean Trucks program.
1.3.1 Phase 2 EPA GHG Emission Standards for Heavy-Duty Vehicles and Engines
The Heavy-Duty Greenhouse Gas Phase 2 ("FED GHG Phase 2") program sets CO2 standards
separately for vehicles and engines. The phase in of the standards began in MY 2021 followed
by more stringent standards in MY 2024 and MY 2027. The Phase 2 heavy-duty vehicle (HDV)
emission standards are sub-categorized within the following groups: Vocational Vehicles
(segmented as specified in Table 1-5), Custom Chassis (segmented as specified in Table 1-6),
and Class 7 and Class 8 Tractors (segmented as specified in Table 1-7). The vehicle emission
standards finalized in this rulemaking will follow the vehicle classification used in the HD GHG
Phase 2 CO2 emission standards as defined in 40 CFR 1037.140. This final rule revises many of
these Phase 2 MY 2027 standards in the tables, as described in preamble Section II and RIA
Chapter 2.10.64
Table 1-5 Phase 2 CO2 Standards for Model Year (MY) 2027 and Later Vocational Vehicles (g/ton-mile)
Engine Cycle
Vehicle size
Multi-purpose
Regional
Urban
Compression-ignition
Light HDV
330
291
367
Compression-ignition
Medium HDV
235
218
258
Compression-ignition
Heavy HDV
230
189
269
Spark-ignition
Light HDV
372
319
413
Spark-ignition
Medium HDV
268
247
297
64 See 81 FR 73478, October 25, 2016.
20
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Table 1-6 Phase 2 Custom Chassis CO2 Emission Standards for Model Year (MY) 2027 and Later (g/ton-
mile)
Vehicle Type
Assigned vehicle service class
MY 2027+
School bus
Medium HDV
271
Motor home
Medium HDV
226
Coach bus
Heavy HDV
205
Other bus
Heavy HDV
286
Refuse hauler
Heavy HDV
298
Concrete mixer
Heavy HDV
316
Mixed-use vehicle
Heavy HDV
316
Emergency vehicle
Heavy HDV
319
Table 1-7 Phase 2 CO2 Standards for Model Year (MY) 2027 and Later Class 7 and Class 8 Tractors (g/ton-
mile)
Subcategory
Phase 2 MY
2027+
Class 7 Low-Roof (all cab styles)
96.2
Class 7 Mid-Roof (all cab styles)
103.4
Class 7 High-Roof (all cab styles)
100.0
Class 8 Low-Roof Day Cab
73.4
Class 8 Low-Roof Sleeper Cab
64.1
Class 8 Mid-Roof Day Cab
78.0
Class 8 Mid-Roof Sleeper Cab
69.6
Class 8 High-Roof Day Cab
75.7
Class 8 High-Roof Sleeper Cab
64.3
Heavy-Haul Tractors
48.3
The vehicle manufacturers that certified to EPA standards for MY 2022 are those listed in
Table 1-8. The manufacturer names with indicate that they have EPA certifications for BEVs.
The manufacturer names with 'A' indicate they have certifications for FCEVs.
21
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Table 1-8 Vehicle Manufacturers Certified to EPA HDV Emission Standards in MY 202465
Alexander Dennis Limited
Ford Motor Co
PACCAR Inc*A
An Yuan Bus Manufacture Co.*
General Motors LLC
Proterra Operating Company,
Inc*
ARBOC Specialty Vehicles,
LLC
Gillig LLC*
REE Automotive*
Autocar, LLC*
Global Environment Product
Inc*
Rosenbauer Motors LLC
Battle Motors, Inc.*
Greenpower Motor Co.*
SEA Electric*
Blue Bird Body Company*
Grove US LLC
Seagrave Fire Apparatus LLC
BYD Auto Industry Company
Ltd*
Hino Motors, Ltd
Spartan Fire LLC
Cenntro Automotive*
HME Inc
Temsa Skoda Sabanci Ulasim
Araclari A.S.*
Chanjc*
Hyundai Motor Co A
Tesla*
CHTC
Irizar Sociedad Coop.
Terex Corporation
Daimler Coaches North
America
Isuzu Motors Limited
The Shy ft Group*
Daimler Truck North America
LLC*
Kovatch Mobile Equipment
Corp.
Tiffon Motor Homes Inc
Dennis Eagle Inc
Lion Electric Co*
Unique Electric Sol.*
Distinctive Services, Inc.
Mitsubishi Fuso Truck and Bus
Van Hool N.V.*
e-Roll*
Motor Coach Industries*
Vicinity Motor (Bus) Corp*
Eldorado National-California
Inc*A
Navistar, Inc*
Volvo Group Trucks,
Technology, Powertrain
Engineering, a Division of Mack
Trucks*
Envirotech Drive Systems Inc*
New Flyer of America, Inc*A
Workhorse*
E-One Inc
Newell Coach
XOS, Inc*
EVO Bus GmbH*
Nikola Corporation* A
Zeus Electric Chassis, Inc*
FCA US LLC
Nova Bus*
Ferrara Fire Apparatus Inc*
Oshkosh Corporation*
The CO2 engine standards are divided by the type of vehicle where the engine will be
installed—tractor or vocational vehicles—and then further divided by engine category. The
engine standards for engines used in tractors and vocational vehicles are found in 40 CFR
1036.108 and the MY 2027 standards are shown in Table 1-9 and Table 1-10. The standards for
engines installed in tractors decrease 3.4% between MY 2021 and MY 2027. The standards for
engines installed in vocational vehicles decrease between 1.8-2% from MY 2021 to MY 2027.
65 U.S. Environmental Protection Agency. "Annual Certification Data for Vehicles, Engines, and Equipment".
Available online: https://www.epa.gov/compliance-and-fuel-economy-data/annual-certification-data-vehicles-
engines-and-equipment.
22
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Table 1-9 MY 2027 Engine CO2 Emission Standards for Engines Installed in Tractors (SET cycle)
Engine Category
CO2 Emissions
Standard (g/bhp-hr)
Medium HD
457
Heavy HD
432
Table 1-10 MY 2027 Engine CO2 Emission Standards for Heavy-Duty Engines Installed in Vocational
Vehicles (FTP cycle)
Engine Category
CO2 Emissions
(g/bhp-hr)
Light HD
552
Medium HD
535
Heavy HD
503
HD Spark Ignition
627
The engine manufacturers that currently certify to EPA standards are listed in Table 1-11.
These certifications are for compression ignition and spark ignition engines.
Table 1-11 Engine Manufacturers Certified to EPA HDE Emission Standards in MY 202465
AGA Systems, LLC
FPT Industrial S.p.A
PACCAR Inc
Agility Powertrain Systems LLC
General Motors, LLC
PARNELL USA, Inc
Bi-Phase technologies, LLC
Greenkraft, Inc
Power Solutions International, Inc
Blossman Services, Inc
Hino Motors, Ltd
Powertrain Integration LLC
Clean Fuel USA, Inc
Icom North America LLC
Roush Industries Inc
Cummins, Inc.
IMPCO Technologies, Inc
Team Quality Services, Inc
Detroit Diesel Corporation
Isuzu Motors Limited
Volvo Group Trucks, Technologies,
Powertrain Engineering, a Division
of Mack Trucks
Encore TEC LLC
Landi Renzo USA Corp
Wing Power Systems
FCAUS LLC
Navistar, Inc
Ford Motor Company
NGV Motori USA, LLC
1.3.2 Bipartisan Infrastructure Law (BIL) and Inflation Reduction Act (IRA)
1.3.2.1 BIL
The BIL66 was enacted on November 15, 2021, and contains provisions to support the
deployment of low- and zero-emission transit buses, school buses, and trucks that service ports,
as well as electric vehicle charging infrastructure and hydrogen. These provisions include
Section 71101 establishing EPA's Clean School Bus Program,67 with $5 billion to fund the
replacement of ICE school buses with clean and zero-emission buses over five years. In its first
66 United States, Congress. Public Law 117-58. Infrastructure Investment and Jobs Act of 2021. Congress.gov,
www.congress.gov/bill/117th-congress/house-bill/3684/text. 117th Congress, House Resolution 3684, passed 15
Nov. 2021.
67 U.S. Environmental Protection Agency. "2022 Clean School Bus (CSB) Rebates Program Guide," EPA-420-B-
22-025, May 2022. Available online:
https://nepis.epa.gov/Exe/ZyPDF.cgi/P1014WNH.PDF?Dockey=P1014WNH.PDF.
23
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phase of funding for the Clean School Bus Program, EPA awarded nearly $1 billion in rebates
(up to a maximum of $375,000 per bus, depending on the bus fuel type, bus class size, and
school district prioritization status)68 for approximately 2,400 replacement clean and zero-
emission buses and associated infrastructure costs.69'70 Nearly 95% of the replacement buses are
BEVs. In January 2024, EPA awarded nearly $1 billion in competitive grant funding to purchase
new school buses and eligible infrastructure (up to $395,000 per bus with charging
infrastructure).71'72'73 EPA also anticipates awarding at least $500 million through a second phase
of rebates (up to a maximum of $345,000 per bus with charging infrastructure).74'75 The
application period for the rebate program closed in January 2024 and will be awarded in April or
May 2024.76 Recipients of both the grant and second rebate funding opportunity can determine
the split between funding for the bus and supporting infrastructure.77
The BIL also includes funding for DOT's Federal Transit Administration (FTA) Low or No
Emission competitive grant program,78 with over $5.5 billion over five years to support the
purchase of zero- or low-emission transit buses and associated infrastructure.79 Grants were
awarded to state and local government authorities for $1.66 billion in FY 2022 and $1.7 billion
68 U.S. Environmental Protection Agency. "2022 Clean School Bus (CSB) Rebates Program Guide". May 2022.
Available online: https://nepis.epa.gov/Exe/ZyPDF.cgi/P1014WNH.PDF?Dockey=P1014WNH.PDF.
69 Some recipients are able to claim up to $20,000 per bus for charging infrastructure.
70 U.S. Environmental Protection Agency, "EPA Clean School Bus Program Second Report to Congress Fiscal Year
2022," EPA-420-R-23-002, February 2023. Available online: https://www.epa.gov/system/files/documents/2023-
02/420r23002.pdf.
71 Funding levels are dependent on the bus fuel type, class size, and school district prioritization status. Selectees
may also be eligible for IRA tax credits applicable to their bus and infrastructure purchases such as the Commercial
Clean Vehicle Credit and the Alternative Fuel Vehicle Purchasing Property Credit.
72 U.S. Environmental Protection Agency. "2023 Clean School Bus (CSB) Grant Program: Notice of Funding
Opportunity (NOFO): EPA-OAR-OATQ-23-06". Available online:
https://www.epa.gov/system/files/documents/2023-04/2023-csb-grant-nofo-4-20-23.pdf.
73 U.S. Environmental Protection Agency. "Biden-Harris Administration announces nearly $1B in awards for clean
school buses across the nation as part of Investing in America Agenda". January 8, 2024. Available online:
https://www.epa.gov/newsreleases/biden-harris-administration-announces-nearly-lb-awards-clean-school-buses-
across#:~:text=In%20April%202023%2C%20EPA%20announced,and%201ow%2Demission%20school%20buses.
74 Funding levels are dependent on the bus fuel type, class size, and school district prioritization status.
75 U.S. Environmental Protection Agency, Office of Transportation and Air Quality. "2023 Clean School Bus
Rebates Program Guide". September 2023. Available online:
https ://nepis. epa.gov/Exe/ZyPDF. cgi?Dockey=P 1018JIT.pdf.
76 U.S. Environmental Protection Agency, Office of Transportation and Air Quality. "2023 Clean School Bus
Rebates Program Guide". September 2023. Available online:
https ://nepis. epa.gov/Exe/ZyPDF. cgi?Dockey=P 1018JIT.pdf.
77 U.S. Environmental Protection Agency, Office of Transportation and Air Quality. "2023 Clean School Bus
Rebates Program Guide". September 2023. Available online:
https ://nepis. epa.gov/Exe/ZyPDF. cgi?Dockey=P 1018JIT.pdf.
78 U.S. Department of Transportation, Federal Transit Administration. "Low or No Emission Vehicle Program -
5339(c)". Available online: https://www.transit.dot.gov/lowno.
79 U.S. Department of Transportation, Federal Transit Administration. "Bipartisan Infrastructure Law Fact Sheet:
Grants for Buses and Bus Facilities". Available online: https://www.transit.dot.gov/funding/grants/fact-sheet-buses-
and-bus-facilities-program.
24
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in FY 2023, contributing to the purchase of more than 1,800 ZEV transit buses so far over two
years.80'81
The BIL includes up to $7.5 billion to help build out a national network of EV charging and
hydrogen fueling administered by DOT's Federal Highway Administration (FHWA) with
support from the Joint Office of Energy and Transportation (JOET). This includes $5 billion for
the National Electric Vehicle Infrastructure (NEVI) Formula Program (under Division J, Title
VIII).82 In September 2022, the FHWA approved the first set of plans for the NEVI program
covering all 50 states, Washington, D.C., and Puerto Rico. The approved plans provide $1.5
billion in funding for fiscal years (FY) 2022 and 2023 to expand charging on over 75,000 miles
of highway.83 In November 2023, the FHWA completed NEVI plan approvals for FY 2024.84
Ohio was the first state to open a NEVI-funded station near Columbus in December 2023.85 New
York and Pennsylvania followed with stations in Kingston and Pittstown, respectively.86'87
Another 30 states have released solicitations with some already awarding contracts and installing
charging stations.88 Over $600 million was awarded for state plans for FY 202489'90 One of the
80 U.S. Department of Transportation, Federal Transit Administration. "Biden-Haris Administration Announces
Over $1.6 Billion in Bipartisan Infrastructure Law Funding to Nearly Double the Number of Clean Transit Buses on
America's Roads". August 16, 2022. Available online: https://www.transit.dot.gov/1800buses.
81 U.S. Department of Transportation, Federal Transit Administration. "Biden-Harris Announces Nearly $1.7 Billion
to Help Put Better, Cleaner Buses on the Roads in Communities Across the Country". June 26, 2023. Available
online: https://www.transit.dot.gov/about/news/biden-harris-administration-announces-nearly-17-billion-help-put-
better-cleaner-buses.
82 U.S. Department of Transportation, Federal Highway Administration. "Memorandum: National Electric Vehicle
Infrastructure Formula Program (Update)". June 2, 2023. Available online:
https://www.fhwa.dot.gov/environment/nevi/formula_prog_guid/90d_nevi_formula_program_guidance.pdf.
83 U.S. Department of Transportation. "Historic Step: All Fifty States Plus D.C. and Puerto Rico Greenlit to Move
EV Charging Networks Forward, Covering 75,000 miles of Highway." September 27, 2022. Available online:
https://www.transportation.gov/briefing-room/historic-step-all-fifty-states-plus-dc-and-puerto-rico-greenlit-move-
ev-charging.
84 U.S. Department of Transportation. "Biden-Harris Administration Announces Grants to Upgrade Almost 4,500
Public Electric Vehicle Chargers". January 18, 2024. Available online: https://www.transportation.gov/briefing-
room/biden-harris-administration-announces-grants-upgrade-almost-4500-public-
electric#:~:text=In%20November%202023%2C%20FHWA%20approved,funding%20to%20implement%20those%
20plans.
85 Joint Office of Energy and Transportation. "First Public EV Charging Station Funded by NEVI Open in
America". December 13, 2023. Accessed December 18, 2023, at: https://driveelectric.gov/news/first-nevi-funded-
stations-open.
86 Joint Office of Energy and Transportation. "New York Continues NEVI Charging Station Momentum".
December 15, 2023. Accessed December 18, 2023, at: https://driveelectric.gov/news/new-york-NEVI-charging-
station-momentum.
87 Joint Office of Energy and Transportation. "Pennsylvania Continues Shift Toward Thriving Electric
Transportation Sector". January 23, 2024. Accessed February 24, 2024, at https://driveelectric.gov/news/new-
pennsylvania-nevi-station.
88 Joint Office of Energy and Transportation. " 2024 Q1 NEVI Progress Update," February 16, 2024. Accessed
February 24, 2024, at: https://driveelectric.gov/news/nevi-update-ql.
89 U.S. Department of Transportation. "Biden-Harris Administration Announces Grants to Upgrade Almost 4,500
Public Electric Vehicle Chargers". January 18, 2024. Available online: https://www.transportation.gov/briefing-
room/biden-harris-administration-announces-grants-upgrade-almost-4500-public-
electric#:~:text=In%20November%202023%2C%20FHWA%20approved,funding%20to%20implement%20those%
20plans.
90 Joint Office of Energy and Transportation. "State Plans for Electric Vehicle Charging". Available online:
https://driveelectric.gov/state-plans/.
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stated goals of this infrastructure funding is to support equitable access to charging across the
country.91 Accordingly, FHWA instructed states to incorporate public engagement in their NEVI
Formula Program planning process, including reaching out to Tribes, and rural, underserved, and
disadvantaged communities among other stakeholders. While jurisdictions are not required to
build stations specifically for heavy-duty vehicles, FHWA's guidance encourages states to
consider station designs and power levels that could support heavy-duty vehicles.92
In September 2023, JOET announced that up to $100 million in NEVI funding would be
available to increase reliability of the existing charging infrastructure network with funds going
to repair or replace charging equipment.93 This will complement efforts of the National Charging
Experience Consortium (ChargeX Consortium). Launched in May 2023 by JOET and led by
U.S. DOE labs, the ChargeX Consortium will develop solutions and identify best practices for
common problems related to the consumer experience, e.g., payment processing and user
interface, vehicle-charger communication, and diagnostic data sharing.94 Relatedly, in January
2024, JOET announced $46.5 million in federal funding to support 30 projects to increase
charging access, reliability, resiliency, and workforce development. This includes projects to
increase the commercial capacity for testing and certification of high-power electric vehicle
chargers, which will accelerate the deployment of interoperable, safe, and efficient electric
vehicle and charger systems.95
The remaining $2.5 billion administered by FHWA is for the Charging and Fueling
Infrastructure (CFI) Discretionary Grant Program (under Section 11401).96 In January 2024, over
$600 million in grants under the CFI Program (for FY 2022 to 2023) was announced to deploy
BEV charging and alternative fueling infrastructure projects in communities and along corridors
in 22 states and Puerto Rico. This first round of CFI grants is expected to fund the construction
of about 7,500 EVSE charging ports.97'98 Table 1-12 includes an example of projects awarded
specifically for the corridor portion of the program. To support these programs, in February
91 U.S. Department of Transportation, Federal Highway Administration. "Memorandum: National Electric Vehicle
Infrastructure Formula Program Guidance (Update)". June 2, 2023. Available online:
https://www.fhwa.dot.gov/environment/nevi/formula_prog_guid/90d_nevi_formula_program_guidance.pdf
92 U.S. Department of Transportation, Federal Highway Administration. "Memorandum: National Electric Vehicle
Infrastructure Formula Program Guidance (Update)". June 2, 2023. Available online:
https://www.fhwa.dot.gov/environment/nevi/formula_prog_guid/90d_nevi_formula_program_guidance.pdf
93 Joint Office of Energy and Transportation. "Biden-Harris Administration to Invest $100 Million for EV Charger
Reliability." September 13, 2023. Available online: https://driveelectric.gov/news/ev-reliability-funding-
opportunity.
94 Joint Office of Energy and Transportation. "Joint Office Announces National Charging Experience Consortium".
May 18, 2023. Available online: https://driveelectric.gov/news/chargex-consortium.
95 Joint Office of Energy and Transportation. "New Funding Enhances EV Charging Resiliency, Reliability, Equity,
and Workforce Development". January 19, 2024. Accessed February 24, 2024, at:
https://driveelectric.gov/news/workforce-development-ev-projects.
96 U.S. Department of Transportation, Federal Highway Administration. "Memorandum: National Electric Vehicle
Infrastructure Formula Program Guidance (Update)". June 2, 2023. Available online:
https://www.fhwa.dot.gov/environment/nevi/formula_prog_guid/90d_nevi_formula_program_guidance.pdf.
97 Joint Office of Energy and Transportation. "Biden-Harris Administration Bolsters Electric Vehicle Future with
More than $600 Million in New Funding". January 11, 2024, https://driveelectric.gov/news/new-cfi-funding.
98 U.S. Department of Transportation. "Biden-Harris Administration Announces $623 Million in Grants to Continue
Building Out Electric Vehicle Charging Network". January 11, 2024. Available online:
https://highways.dot.gov/newsroom/biden-harris-administration-announces-623-million-grants-continue-building-
out-electric.
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2023, DOE announced $7.4 million in funding to develop seven medium- and heavy-duty BEV
charging and hydrogen corridor infrastructure plans: from Georgia to New Jersey (along 1-95),
Indiana to Ohio (along 1-80), Houston to Los Angeles (along I-10), and around Los Angeles (I-
710 Corridor), the Northeast (New Jersey to Maine), San Francisco Bay Area, and the Greater
Salt Lake City Region."
Table 1-12 CFI Corridor Program Grant Recipients100
Lead Applicant State: Project Name
Amount
CFI
Program
CA: City of Blythe WattEV I-10 Truck Charging Terminal
$19,635,156
EV Charging
CA: FY 2023 San Joaquin Valley 1-5 Electric Freight Corridor
(Valley EFC) Project
$56,008,096
EV Charging
CA: Workforce and Renewable Hydrogen for Light - to Heavy
-Duty ZEV Fueling in DAC
$7,156,982
Hydrogen
CO: Colorado with Hydrogen Refueling Infrastructure on the
1-25 Corridor (Hy-25)
$8,977,947
Hydrogen
ID: City of Idaho Falls Corridor Charging Infrastructure
$3,002,856
EV Charging
NC: Empower Durham: Equitable EV Charging in the City of
Durham, NC - Corridor Component
$4,864,000
EV Charging
NM: New Mexico Clean Fuel Build-out Project for Medium -
and Heavy-duty Electric Corridors along Interstate 10
Unincorporated Hidalgo and Dona Ana Counties
$63,898,809
EV Charging
NY: Urban Area Strategies to Electrify Light - to Heavy -
duty Mobility in NYC - Corridor Component
$15,000,000
EV Charging
PR: Puerto Rico Corridors: Alternative Charging and Fueling
Infrastructure for All, PR-2, PR-22, and PR-52
$51,480,000
EV Charging
TX: Charging and Fueling Infrastructure (CFI) Corridor
Program for the Texas Hydrogen and Electric Freight
Infrastructure (Tx-HEFTI) Project
$70,000,000
Hydrogen
WA: Port Angeles
$2,103,611
EV Charging
WA: Catalyzing Zero-Emission Drayage Trucking
Infrastructure & Opportunities in the Seattle-Tacoma Region
$12,000,000
EV Charging
The BIL funds other programs that could support HD vehicle electrification. For example,
there is continued funding of the Congestion Mitigation and Air Quality (CMAQ) Improvement
Program, with more than $2.5 billion authorized each year from FY 2022 through FY 2026. The
BIL (Section 11115) amended the CMAQ Improvement Program to add, among other things,
"the purchase of medium- or heavy-duty zero emission vehicles and related charging equipment"
99 U.S. Department of Energy. "Biden-Harris Administration Announces Funding for Zero-Emission Medium- and
Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities". February 15, 2023.
Available online: https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-
medium-and-heavy-duty-vehicle.
100 U.S. Department of Transportation, Federal Highway Administration. "Charging and Fueling Infrastructure
Program Grant Recipients: FY 2022- FY 2023 Grant Award Recipients". Available online:
https://highways.dot.gov/sites/fhwa.dot.gov/files/CFI%20Grant%20Awards%20Project%20Descriptions%20FY22-
23.pdf.
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to the list of activities eligible for funding. The BIL establishes a program under Section 11402
"Reduction of Truck Emissions at Port Facilities" that includes grants to be administered through
FHWA aimed at reducing port emissions, including through electrification. In addition, the BIL
includes funding for DOT's Maritime Administration (MARAD) Port Infrastructure
Development Program101 and DOT's Federal Highway Administration (FHWA) Carbon
Reduction Program (Section 11403).102
The BIL also targets batteries used for BEVs and FCEVs. It funds DOE's Battery Materials
Processing and Battery Manufacturing program,103 which grants funds to promote U.S.
processing and manufacturing of batteries for automotive and electric grid use through
demonstration projects, the construction of new facilities, and the retooling, retrofitting, and
expansion of existing facilities. This includes a total of $3 billion for battery material processing
and $3 billion for battery manufacturing and recycling, with additional funding for a lithium-ion
battery recycling prize competition, research and development activities in battery recycling,
state and local programs, and the development of a collection system for used batteries. In
addition, the BIL includes $200 million for the Electric Drive Vehicle Battery Recycling and
Second-Life Application Program for research, development, and demonstration of battery
recycling and second-life applications.
Hydrogen provisions of the BIL include $9.5 billion in funding for several programs to
accelerate progress towards the Hydrogen Shot goal, launched on June 7, 2021, to reduce the
cost of clean hydrogen104 production by 80% to $1 for 1 kg in 1 decade105 and jumpstart the
hydrogen market in the United States. This includes a total of $8 billion for the Department of
Energy's Regional Clean Hydrogen Hubs Program to establish networks of clean hydrogen
producers, potential consumers, and connective infrastructure in close proximity. The BIL
provisions establishing this program include several diversity requirements. For example, the
program must fund at least one hub each that produces hydrogen using fossil fuels, renewable
energy, and nuclear power; and a minimum of two hubs must be sited in natural gas-producing
regions.106'107 Additional provisions in the BIL include $1 billion for a Clean Hydrogen
101 U.S. Department of Transportation, Maritime Administration. "Bipartisan Infrastructure Law: Maritime
Administration". Available online: https://www.maritime.dot.gov/about-us/bipartisan-infrastructure-law-maritime-
administration.
102 U.S. Department of Transportation, Federal Highway Administration. "Bipartisan Infrastructure Law, Fact
Sheets: Carbon Reduction Program (CRP)". April 20, 2022. Available online: https://www.fhwa.dot.gov/bipartisan-
infrastructure-law/crp_fact_sheet.cfm.
103 U.S. Department of Energy. "Biden Administration Announces $3.16 Billion From Bipartisan Infrastructure Law
to Boost Domestic Battery Manufacturing and Supply Chains". May 2, 2022. Available online:
https://www.energy.gov/articles/biden-administration-announces-316-billion-bipartisan-infrastructure-law-boost-
domestic.
104 The BIL defines "clean hydrogen" as hydrogen produced in compliance with the GHG emissions standard
established under 42 U.S. Code section 16166(a), including production from any energy source, where the standard
developed shall define the term to mean hydrogen produced with a carbon intensity equal to or less than 2 kilograms
of carbon dioxide-equivalent produced at the site of production per kilogram of hydrogen produced.
105 Satyapal, Sunita. "2022 AMR Plenary Session". U.S. Department of Energy, Hydrogen and Fuel Cell
Technologies Office. June 6, 2022. Available online: https://www.energy.gov/sites/default/files/2022-06/hfto-amr-
plenary-satyapal-2022-1 .pdf.
106 U.S. Department of Energy, Office of Clean Energy Demonstrations. "Regional Clean Hydrogen Hubs".
Available online: https://www.energy.gov/oced/regional-clean-hydrogen-hubs.
107 42 United States Code 16161a. "Regional clean hydrogen hubs". Effective on March 19, 2024. Available online:
https://uscode.house.gov/view.xhtml?req=granuleid:USC-prelim-title42-sectionl6161a&num=0&edition=prelim.
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Electrolysis Program and $500 million for Clean Hydrogen Manufacturing and Recycling
Initiatives.108 More details about hydrogen initiatives launched by the BIL are in Chapter 1.8.3.
1.3.2.2 IRA Sections 13502 and 13403
The IRA,109 which was enacted on August 16, 2022, contains several provisions relevant to
vehicle electrification and the associated infrastructure via tax credits, grants, rebates, and loans
through CY 2032, including two key provisions that provide a tax credit to reduce the cost of
producing qualified batteries (battery tax credit) and to reduce the cost of purchasing qualified
ZEVs (vehicle tax credit). The battery tax credit in "Advanced Manufacturing Production
Credit" in IRA section 13502 and the "Qualified Commercial Clean Vehicles" vehicle tax credit
in IRA section 13403 are included quantitatively in our analysis, including for our potential
compliance pathway.
IRA section 13502, "Advanced Manufacturing Production Credit," provides tax credits for the
production and sale of battery cells and modules of up to $45 per kilowatt-hour (kWh), and for
10 percent of the cost of producing applicable critical minerals (including those found in
batteries and fuel cells, provided that the minerals meet certain specifications), when such
components or minerals are produced in the United States. These credits begin in CY 2023 and
phase down starting in CY 2030, ending after CY 2032. This tax credit has the potential to
noticeably reduce the cost of qualifying batteries and by extension, the cost of BEVs and FCEVs
with qualifying batteries. We did not include a detailed cost breakdown of fuel cells
quantitatively in our analysis, but the potential impact on fuel cells may also be significant
because platinum (an applicable critical mineral commonly used in fuel cells) is a contributor to
the cost of fuel cells.110
We limited our assessment of this IRA section 13502 tax credit provision in our Chapter 2
analysis to the tax credits for battery cells and modules. Pursuant to the IRA, qualifying battery
cells must have an energy density of not less than 100 watt-hours per liter, and we expect that
batteries for heavy-duty BEVs, PHEVs and FCEVs will satisfy (indeed, surpass) this
requirement as described in RIA Chapter 2.4.2.2. Qualifying battery cells must be capable of
storing at least 12 watt-hours of energy and qualifying battery modules must have an aggregate
capacity of not less than 7 kWh (or, for FCEVs, not less than 1 kWh); typical battery cells and
modules for motor vehicles also satisfy (and surpass) these requirements.111 Additionally, the
ratio of the capacity of qualifying cells and modules to their maximum discharge amount shall
not exceed 100:1. We expect that battery cells and modules in heavy-duty BEVs, PHEVs, and
FCEVs will also meet this requirement because the high costs and weight of the batteries and the
108 U.S. Department of Energy. "DOE Establishes Bipartisan Infrastructure Law's $9.5 Billion Clean Hydrogen
Initiatives". February 15, 2022. Available online: https://www.energy.gov/articles/doe-establishes-bipartisan-
infrastructure-laws-95-billion-clean-hydrogen-initiatives.
109 Inflation Reduction Act of 2022, Pub. L. No. 117-169, 136 Stat. 1818(2022) ("Inflation Reduction Act" or
"IRA"), available at https://www.congress.gOv/l 17/bills/hr5376/BILLS-l 17hr5376enr.pdf.
110 Leader, Alexandra & Gaustad, Gabrielle & Babbitt, Callie. (2019). The effect of critical material prices on the
competitiveness of clean energy technologies. Materials for Renewable and Sustainable Energy. 8. 10.1007/s40243-
019-0146-z.
111 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6, October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1406494585829.
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competitiveness of the heavy-duty industry will pressure manufacturers to allow as much of their
batteries to be useable as possible. We did not consider the tax credits for critical minerals
quantitatively in our analysis. However, we note that any applicability of the critical mineral tax
credit may further reduce the costs of batteries.
We included this battery tax credit by reducing the direct manufacturing costs of batteries in
BEVs and FCEVs, but not the associated indirect costs. See RIA 2.4.3. As discussed in Section
II.D.2.ii.b of the preamble, our assessment of North American and worldwide battery and cell
manufacturing capacity is that capacity is rapidly growing to accommodate demand. Thus, we
have chosen to model this tax credit by assuming that HD BEV and FCEV manufacturers fully
utilize the module tax credit (which provides $10 per kWh) and gradually increase their
utilization of the cell tax credit (which provides $35 per kWh) for MY 2027-2029 until MY
2030 and beyond, when they earn 100 percent of the available cell and module tax credits.
Further discussion of this battery tax credit and our battery costs can be found in RIA Chapter
2.4.3.1.
IRA section 13403, "Qualified Commercial Clean Vehicles," creates a tax credit of up to
$40,000 per Class 4 through 8 HD vehicles above 14,000 pounds GVWR with a battery capacity
of at least 15 kWh (up to $7,500 for vehicles under 14,000 pounds GVWR with a battery
capacity of at least seven kWh, such as Class 2b or 3 vehicles) that are acquired for use or lease
of a qualified commercial clean vehicle. This tax credit is available from CY 2023 through CY
2032 and is based on the lesser of the incremental cost of the clean vehicle over a comparable
ICE vehicle or the specified percentage of the basis of the clean vehicle, up to the maximum
$40,000 limitation. By effectively reducing the price a vehicle owner must pay for a HD ZEV
and the incremental difference in cost between it and a comparable ICE vehicle—by $40,000 in
many cases—more vehicle purchasers will be poised to take advantage of the cost savings
anticipated from total cost of ownership, including operational cost savings from fuel and
maintenance and repair compared with ICE vehicles. Among other specifications, these vehicles
must be on-road vehicles (or mobile machinery) that are propelled to a significant extent by a
battery-powered electric motor or are qualified fuel cell motor vehicles (also known as fuel cell
electric vehicles, FCEVs). For the former, the battery must have a capacity of at least 15 kWh (or
7 kWh if it has a gross vehicle weight rating of less than 14,000 pounds (Class 3 or below)) and
must be rechargeable from an external source of electricity. This limits the qualified vehicles to
BEVs and plug-in hybrid electric vehicles (PHEVs), in addition to FCEVs. Since this tax credit
overlaps with the model years for which we are finalizing standards (MYs 2027 through 2032),
we included it in our calculations for each of those years in our analysis to develop our potential
compliance pathway's technology packages to support the feasibility of for our final standards
(see Chapter 2).
For BEVs and FCEVs, the per-vehicle tax credit is equal to the lesser of the following, up to
the cap limitation: (A) 30 percent of the BEV or FCEV cost, or (B) the incremental cost of the
BEV or FCEV when compared to a comparable (in size and use) ICE vehicle. The limitation on
this tax credit is $40,000 for vehicles with a gross vehicle weight rating of equal to or greater
than 14,000 pounds (Class 4-8 commercial vehicles) and $7,500 for vehicles with a gross
vehicle weight rating of less than 14,000 pounds (commercial vehicles Class 3 and below). For
example, if a BEV with a gross vehicle weight rating equal to or greater than 14,000 pounds
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costs $350,000 and a comparable ICE vehicle costs $150,000,112 the tax credit would be the
lesser of the following, subject to the limitation: (A) 30 percent x $350,000 = $105,000 or (B)
$350,000 - $150,000 = $200,000. (A) is less than (B), but (A) exceeds the limit of $40,000, so
the tax credit would be $40,000. For PHEVs, the per-vehicle tax credit follows the same
calculation and cap limitation as for BEVs and FCEVs except that (A) is 15 percent of the PHEV
cost.
For details on how we estimated the impact of the tax credit in our feasibility analysis see
Chapters 2.4.3.5 (BEVs), 2.5.2.3 (FCEVs), and 2.11.5 (PHEVs). In the final rule, PHEVs are not
included in our modeled potential compliance pathway's technology packages but are included
in our additional example potential compliance pathways that are provided as another example of
the many ways that manufacturers may choose to comply with the final standards; this tax credit
would also serve to effectively reduce the price a vehicle owner must pay for a HD PHEV for
any incremental difference in cost between it and a comparable ICE vehicle. The tax credit
amounts for each vehicle type included in our analysis for the modeled potential compliance
pathway in MYs 2027 and 2032 are shown in RIA Chapter 2.9.2.
We project that the impact of the IRA vehicle tax credit will be significant, as shown in RIA
Chapter 2.8.2. In many cases, the incremental cost (with the tax credit) of a BEV compared to an
ICE vehicle is eliminated, leaving only the state and federal taxes and the cost of the electric
vehicle supply equipment (if applicable) as an added upfront cost to the BEV owner. Similarly,
in some cases, the tax credit eliminates the upfront cost of a FCEV compared to an ICE vehicle,
leaving only state and federal taxes.
1.3.2.3 IRA Sections 13404
Section 13404, "Alternative Fuel Refueling Property Credit," modifies an existing tax credit
that applies to alternative fuel refueling property (e.g., electric vehicle charging equipment and
hydrogen fueling stations) and extends the tax credit through CY 2032. The credit also applies to
refueling property that stores or dispenses specified clean-burning fuels, including at least 85
percent hydrogen, into the fuel tank of a motor vehicle. Starting in CY 2023, this provision
provides a tax credit of up to 30 percent of the cost of the qualified alternative fuel refueling
property (e.g., HD BEV charging and hydrogen refueling equipment), up to $100,000 per item
when located in low-income or non-urban area census tracts and certain other requirements are
met. We expect that many HD BEV owners will need charging equipment installed in their
depots for overnight or other off-shift charging, and this tax credit will effectively reduce the
costs of installing charging infrastructure and, in turn, further effectively reduce the total costs
associated with owning a BEV for many HD vehicle owners. Additionally, this tax credit will
offset some of the costs of installing high-powered public and private charging equipment that
may be necessary to charge HD BEVs with minimal downtime during the day. Similarly, we
expect that this tax credit will reduce the costs associated with refueling heavy-duty FCEVs,
whose owners may rely on public hydrogen refueling stations or those installed in their depots.
We expect this tax credit will help incentivize the build out of the charging and hydrogen
112 Sharpe, B., Basma, H. "A meta-study of purchase costs for zero-emission trucks." International Council on Clean
Transportation. February 17, 2022. Available online: https://theicct.org/wp-content/uploads/2022/02/purchase-cost-
ze-trucks-feb22-l.pdf
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refueling infrastructure necessary for high BEV and FCEV adoption, which will further support
increased BEV and FCEV uptake.
For the final rule, we have quantified the impact of this tax credit in our analysis by
estimating that 60% of the EVSE installations will qualify for the tax credit, including for our
potential compliance pathway. See RIA Chapter 2.6.2.1.2.
1.3.2.4 Other IRA Provisions
There are many other provisions of the IRA that we expect will support application of BEV
and FCEV technologies in the heavy-duty fleet. Due to the complexity of analyzing the
combined potential impact of these provisions, we did not quantify their potential impact in our
assessment of costs and feasibility, but we note that they are expected to help to reduce many
obstacles to application of BEV and FCEV technologies in HD vehicles and may further support
ZEV adoption rates at the levels we currently project in the potential compliance pathway's
technology packages for the final program.
Section 60101, "Clean Heavy-Duty Vehicles," amends the CAA to add new section 132 (42
U.S.C. 7432) and appropriates $1 billion to the Administrator, including $600 million for
carrying out this new requirement generally and $400 million to specifically make awards to
eligible recipients/contractors that propose to replace eligible vehicles to serve one or more
communities located in an air quality area designated pursuant to CAA section 107 as
nonattainment for any air pollutant. This section requires the Administrator to implement a
program to make awards of grants and rebates to eligible recipients (defined as States,
municipalities, Indian tribes, and nonprofit school transportation associations), and to make
awards of contracts to eligible contractors for providing rebates, for up to 100 percent of costs
for: 1) the incremental costs of replacing a Class 6 or Class 7 heavy-duty vehicle that is not a
zero-emission vehicle with a zero-emission vehicle (as determined by the Administrator based on
the market value of the vehicles); 2) purchasing, installing, operating, and maintaining
infrastructure needed to charge, fuel, or maintain zero-emission vehicles; 3) workforce
development and training to support the maintenance, charging, fueling, and operation of zero-
emission vehicles; and 4) planning and technical activities to support the adoption and
deployment of zero-emission vehicles. A Technical Request for Information was issued in 2023
to collect information to inform the development of the Clean Heavy-Duty Vehicles and the
Clean Ports Program, described next.113 A notice of funding opportunity is expected in spring
2024.
Section 60102, "Grants to Reduce Air Pollution at Ports," amends the CAA to add a new
section 133 (42 U.S.C. 7433) and appropriates $3 billion, $750 million of which is for projects
located in areas of nonattainment for any air pollutant, to reduce air pollution at ports. In
February 2024, EPA released a Notice of Funding Opportunity to solicit applications in
anticipation of awarding up to $2.79 billion for zero-emission port equipment and infrastructure
at U.S. ports. The competitive grant program funding can be used to purchase new eligible
battery-electric and hydrogen fuel cell vehicles, vessels, powertrains, and other mobile
113 U.S. Environmental Protection Agency. "Clean Heavy-Duty Vehicle Program". Available online:
https://www.epa.gov/inflation-reduction-act/clean-heavy-duty-vehicle-program.
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equipment and related infrastructure to be used for eligible equipment directly serving a port, as
well as support expenses related to deployment.114
Section 60103, "Greenhouse Gas Reduction Fund," amends the CAA to add a new section
134 (42 U.S.C. 7434) and appropriates $27 billion, $15 billion of which is for low-income and
disadvantaged communities, in FY 2022 and available through FY 2024, for a greenhouse gas
reduction grant program. The program supports direct investments in qualified projects at the
national, regional, State, and local levels, and indirect investments to establish new or support
existing public, quasi-public, not-for-profit, or nonprofit entities that provide financial assistance
to qualified projects. The program focuses on the rapid deployment of low- and zero-emission
products, technologies, and services to reduce or avoid GHG emissions and other forms of air
pollution.
Section 60104, "Diesel Emissions Reductions," appropriates $60 million (2 percent of which
must be reserved for administrative costs necessary to carry out the section's provisions), in FY
2022 and available through FY 2031, for grants, rebates, and loans under section 792 of the
Energy Policy Act of 2005 (42 U.S.C. 16132) to identify and reduce diesel emissions resulting
from goods movement facilities and vehicles servicing goods movement facilities in low-income
and disadvantaged communities to address the health impacts of such emissions on such
communities.
Section 70002 appropriates $3 billion in FY 2022 and available through FY 2031 for the
United States Postal Service to purchase ZEVs ($1.29 billion) and to purchase, design, and
install infrastructure to support zero-emission delivery vehicles at facilities that the United States
Postal Service owns or leases from non-Federal entities ($1.71 billion).
Section 13501, "Extension of the Advanced Energy Project Credit," under section 48C(e) of
the Internal Revenue Code allocates $10 billion in tax credits for facilities to domestically
manufacture advanced energy technologies, subject to certain application and other requirements
and limitations. Qualifying properties now include light-, medium-, or heavy-duty electric or fuel
cell vehicles along with the technologies, components, or materials for such vehicles and the
associated charging or refueling infrastructure. They also include hybrid vehicles with a gross
vehicle weight rating of not less than 14,000 pounds along with the technologies, components, or
materials for them.
Sections 50142, 50143, 50144, 50145, 50151, 50152, and 50153 collectively appropriate
nearly $13 billion to support low- and zero-emission vehicle manufacturing and energy
infrastructure. These provisions are intended to help accelerate the ability for industry to meet
the demands spurred by the previously mentioned IRA sections, both for manufacturing vehicles,
including BEVs and FCEVs, and for energy infrastructure.
Section 13204, "Clean Hydrogen," amends section 45V of the Internal Revenue Code (i.e.,
Title 26) to offer a tax credit to produce qualified clean hydrogen at a qualifying clean hydrogen
production facility that use a process that results in a lifecycle GHG emissions rate of not greater
than 4 kg of C02e per kg of hydrogen. This hydrogen production tax credit is eligible for
114 U.S. Environmental Protection Agency, Office of Transportation and Air Quality. "Clean Ports Program: Zero-
Emission Technology Deployment Competition". February 2024. Available online:
https://www.epa.gOv/system/files/documents/2024-02/2024-clean-ports-ze-tech-deploymt-competition-2024-02.pdf.
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qualified clean hydrogen production facilities whose construction begins before January 1, 2033,
and is available during the 10-year period beginning on the date such facility was originally
placed in service. The credit increases to a maximum of $3 per kilogram produced as the
lifecycle GHG emissions rate is reduced to less than 0.45 kg of C02e per kg of hydrogen.
Facilities that received credit for the construction of carbon capture and direct air capture
equipment or facilities (i.e., under 45Q) do not qualify, and prevailing wage and apprenticeship
requirements apply. Section 60113, "Methane Emissions Reduction Program," amends the CAA
by adding Section 136 and appropriates $850 million to EPA to support methane mitigation and
monitoring, plus authorizes a new fee of $900 per ton on "waste" methane emissions that
escalates after two years to $1,500 per ton. These combined incentives promote the production of
hydrogen in a manner that minimizes its potential greenhouse gas implications.
While there are challenges facing greater adoption of heavy-duty ZEV technologies, the IRA
provides many financial incentives to overcome these challenges and thus provides support for
the utilization of HD vehicle technologies with the potential for large reductions in greenhouse
gas emissions during the MYs at issue in this rulemaking, which in turn supports our final rule.
We expect IRA sections 13502, 13403 and 13404 to support the adoption of HD ZEV
technologies in the market, as detailed in our assessment of the appropriate GHG standards we
are finalizing. Additionally, we expect IRA sections 60101-60104, 70002, 13501, 50142-50145,
50151-50153, and 13204 to further accelerate ZEV adoption, but we are not including them
quantitatively in our analyses. Furthermore, our upstream modeling of electricity generation unit
(EGU) and refinery emissions, as described in RIA Chapter 4.3.3, also quantitatively reflects the
following tax credit provisions of the IRA that affect power sector operations: the Clean
Electricity Investment and Production Tax Credits (sections 13702 and 13701), the credit for
Carbon Capture and Sequestration (section 13104), the Zero-Emission Nuclear Power
Production Credit (section 13105), the Credit for the Production of Clean Hydrogen (section
13204), and the Advanced Manufacturing Production Tax Credit (13502).
1.3.3 California Advanced Clean Trucks Regulation and Other State's Efforts to Increase
Adoption ofZEVs
HD vehicle sales and on-road vehicle populations are significant in the state of California.
Approximately ten percent of U.S. HD ICE vehicles in 2016 were registered in California.115
The California Air Resources Board (CARB) adopted the Advanced Clean Trucks (ACT)
Regulation on March 15, 2021.116 EPA granted the ACT rule waiver requested by California
under CAA section 209(b) on March 30, 2023.
The ACT Regulation requires manufacturers who certify Class 2b through 8 chassis or
complete vehicles with combustion engines to sell zero-emission trucks as an increasing
percentage of their annual state sales from MY 2024 to MY 2035. The ACT Regulation is
applicable for all vehicles sold in California with gross vehicle weight rating greater than 8,500
pounds.
The ACT Regulation requires a specified percentage of heavy-duty ZEVs each model year
with increasing percentages for each subsequent model year, as reflected in Table 1-13. The
115 FHWA. U.S. Highway Statistics. Available online at: https://www.Jhwa.dot.gov/policyinformation/statistics.cfin.
116 California Air Resources Board, Final Regulation Order - Advanced Clean Trucks Regulation. Filed March 15,
2021. Available at: https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2019/act2019/fro2.pdf.
34
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percentages are categorized by Class 2b-3 vehicles, Class 4-8 vocational vehicles, and Class 7-8
tractors. Major program milestones include MYs 2030 and 2035, which require 30 percent and
55 percent of Class 2b-3 vehicles, 50 percent and 75 percent of Class 4-8 vocational vehicles,
and 30 percent and 40 percent of Class 7-8 tractors that are produced to be ZEVs for those
model years, respectively.
Table 1-13 California Air Resource Board ACT Regulation ZEV Sales Percentage Schedule
Model Year
Class 2b-3
Group
Class 4-8
Group
Class 7-8
Tractors
Group
2024
5%
9%
5%
2025
7%
11%
7%
2026
10%
13%
10%
2027
15%
20%
15%
2028
20%
30%
20%
2029
25%
40%
25%
2030
30%
50%
30%
2031
35%
55%
35%
2032
40%
60%
40%
2033
45%
65%
40%
2034
50%
70%
40%
2035 and beyond
55%
75%
40%
ACT includes a credit program that allows credits generated for each ZEV and near zero-
emission vehicle (NZEV)117 to offset deficits generated from the production and sale in
California of vehicles and tractors. Credits may be banked, traded, sold and otherwise transferred
between manufacturers. Table 1-14 describes the multipliers for credits and deficits by vehicle
class. Credits for NZEVs may only be generated through MY 2035. The generated credits have a
set time frame for expiration based on the model year in which the credits were generated.
Credits generated by certifying ZEVs between MY 2021 through MY 2023 expire in MY 2030
and credits accumulated during MY 2024 and later model years expire after five model years.
Table 1-14 CARB Weight Class Modifiers
Vehicles in
the Class
2b-3
Class 4-5
Vehicles in the
Class 4-8
Group
Class 6-7
Vehicles in the
Class 4-8
Group
Class 8
Vehicles in
the Class 4-8
Group
Vehicles in
the Class 7
and 8
Tractor
Group
Weight
Class
Modifier
0.8
1
1.5
2
2.5
117 NZEV is an on-road hybrid electric vehicle that has the capability to charge the battery from an off- vehicle
conductive or inductive electric source and achieves minimum all-electric range per CARB. See, e.g., footnote 1 at
https://ww2.arb.ca.gov/resources/fact-sheets/advanced-clean-trucks-credit-summary-through-2022-model-
year#_ftnl.
35
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The ACT Regulation also has a provision for hybrid vehicles being sold in MYs 2030 and
beyond, which requires that a hybrid have an all-electric 75-mile range.116
Outside of California, a number of states have signaled interest in greater adoption of HD
ZEV technologies and/or establishing specific goals to increase the HD electric vehicle market.
For example, ACT had been proposed or adopted by other states (Colorado118, Maryland119,
Massachusetts120, New Mexico121, New York122, New Jersey123, Oregon124, Rhode Island125,
Vermont126, and Washington127) under CAA section 177 as of February 2024.128 As another
example, the Memorandum of Understanding (MOU), "Multi-State Medium- and Heavy-Duty
Zero Emission Vehicle," (Multi-State MOU) organized by Northeast States for Coordinated Air
Use Management (NESCAUM), sets targets "to make all sales of new medium- and heavy-duty
vehicles [in the jurisdictions of the signatory states and the District of Columbia] zero emission
vehicles by no later than 2050" with an interim goal of 30 percent of all sales of new medium-
and heavy-duty vehicles being zero emission vehicles no later than 2030.129 The Multi-State
MOU was signed by the governors of 17 states including California, Colorado, Connecticut,
Hawaii, Maine, Maryland, Massachusetts, New Jersey, New York, North Carolina, Nevada,
Oregon, Pennsylvania, Rhode Island, Vermont, Virginia, and Washington, as well as the mayor
of the District of Columbia. The Multi-State MOU outlines these jurisdictions' more specific
commitments to move toward ZEVs through the Multi-State ZEV Task Force and provides an
action plan for zero-emission medium- and heavy-duty vehicles with measurable sales targets
and a focus on overburdened and underserved communities. Several states that signed the Multi-
118 Colorado Clean Trucks. Available online: https://cdphe.colorado.gov/cleantrucking
119 Maryland Md. Code Regs. 26.11.43.04. Available online:
https://www.law.cornell.edu/regulations/maryland/COMAR-26-ll-43-04
120 Final Advanced Clean Truck Amendments, 1461 Mass. Reg. 29 (Jan. 21, 2022). Available online:
https://www.mass.gov/doc/310-cmr-740-advanced-clean-truck-amendments/download
121 New Mexico Advanced Clean Trucks. Available online:
https://cloud.env.nm.gov/air/resources/_translator.php/NoP4WdlEyorPC~sl~BWz~sl~H2+PXdCQEKefUZ70u8Vg
q~sl~x2ZYzqalzexRjWPJMkpMtY7aK2mnJ9AoOIZEOEbuZDv5gjdz5ZLJvJUhgZUY7TTUnFGi~sl~XBzQ4GPo
+3bjoke7jG9.pdf
122 Medium- and Heavy-Duty (MHD) Zero Emission Truck Annual Sales Requirements and Large Entity Reporting,
44 N.Y. Reg. 8 (Jan. 19, 2022), available at https://dos.ny.gov/system/files/documents/2022/01/011922.pdf.
123 Advanced Clean Trucks Program and Fleet Reporting Requirements, 53 N.J.R. 2148(a) (Dec. 20, 2021),
available at https://www.nj,gov/dep/rules/adoptions/adopt_20211220a.pdf (pre-publication version).
124 Clean Trucks Rule 2021, DEQ-17-2021 (Nov. 17, 2021), available at
http://records.sos.state.or.us/ORSOSWebDrawer/Recordhtml/8581405.
125 Rhode Island Advanced Clean Trucks. Available online: https://dem.ri.gov/environmental-protection-bureau/air-
resources/advanced-clean-cars-ii-advanced-clean-trucks
126 Vermont Low Emission Vehicle and Zero Emission Vehicle Rules. Available online:
https://dec.vermont.gOv/sites/dec/files/aqc/laws-regs/documents/Chapter_40_LEV_ZEV_rule_adopted.pdf.
127 Low emission vehicles, Wash. Admin. Code. § 173-423-070 (2021), available at
https://app.leg. wa.gov/wac/default. aspx?cite=173-423-070
128 Oregon, Washington, New York, New Jersey, and Massachusetts adopted ACT in 2021 beginning in MY 2025
while Vermont and New Mexico adopted ACT beginning in MY 2026 and Colorado in MY 2027.
129 Northeast States for Coordinated Air Use Management (NESCAUM), Multi-state Medium- and Heavy-duty Zero
Emission Vehicle Memorandum of Understanding, available at https://www.nescaum.org/documents/mhdv-zev-mou-
20220329.pdf/ (hereinafter "Multi-State MOU").
36
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State MOU have since adopted California's ACT program, pursuant to CAA section 177, and we
anticipate more jurisdictions will follow with similar proposals.130
1.4 GHG-Reducing Technologies for ICE-Powered Vehicles
The CO2 emissions of HD vehicles vary depending on the configuration of the vehicle. Many
aspects of the vehicle impact its emissions performance, including the engine, transmission,
drive axle, aerodynamics, and rolling resistance.
The technologies we considered for tractors include technologies that we analyzed in Phase 2
such as improved aerodynamics; low rolling resistance tires; tire inflation systems; efficient
engines, engines fueled with natural gas, transmissions, drivetrains, and accessories; and
extended idle reduction for sleeper cabs. We analyzed the overall effectiveness of the technology
packages using EPA's Greenhouse Gas Emissions Model (GEM), which was used for analyzing
the technology packages that support the Phase 2 vehicle CO2 emission standards and is used by
manufacturers to demonstrate compliance with the Phase 2 standards. EPA's GEM model
simulates road load power requirements over various duty cycles to estimate the energy required
per mile for HD vehicles. The inputs for the individual technologies that make up the fleet
average technology package that meets the Phase 2 MY 2027 CO2 tractor emission standards are
shown in Table 1-15.131 The comparable table for vocational vehicles is shown in Table 1-16.132
The technology package for vocational vehicles include technologies such as low rolling
resistance tires; tire inflation systems; efficient engines, transmissions, and drivetrains; weight
reduction; and idle reduction technologies. Note that the HD GHG Phase 2 standards (like the
Phase 1 and 3 standards) are performance-based; EPA does not require this specific technology
mix, rather the technologies shown in Table 1-15 and Table 1-16 are potential pathways for
compliance.
130 See, e.g., Final Advanced Clean Truck Amendments, 1461 Mass. Reg. 29 (Jan. 21, 2022) (Massachusetts).
Medium- and Heavy-Duty (MHD) Zero Emission Truck Annual Sales Requirements and Large Entity Reporting, 44
N.Y. Reg. 8 (Jan. 19, 2022) (New York), available at https://dos.ny.gov/system/files/documents/2022/01/011922.pdf.
Advanced Clean Trucks Program and Fleet Reporting Requirements, 53 N.J.R. 2148(a) (Dec. 20, 2021) (New
Jersey), available at https://www.nj.gov/dep/rules/adoptions/adopt_20211220a.pdf (pre-publication version). Clean
Trucks Rule 2021, DEQ-17-2021 (Nov. 17, 2021), available at
http://records.sos.state.or.us/ORSOSWebDrawer/Recordhtml/8581405 (Oregon). Low emission vehicles, Wash.
Admin. Code. § 173-423-070 (2021), available at https://app.leg.wa.gov/wac/default.aspx?cite=l73-423-070; 2021
Wash. Reg. 587356 (Dec. 15, 2021); Wash. Reg. 21-24-059 (Nov. 29, 2021) (amending Wash. Admin. Code.
§§ 173-423 and 173-400), available at https://lawfilesext.leg.wa.gov/law/wsrpdf/2021/24/21-24-059.pdf
(Washington).
131 81 FR at 73616, October 25, 2016.
132 81 FR at 73714, October 25, 2016.
37
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Table 1-15 GEM Inputs for Vehicles Meeting the Phase 2 MY 2027 Tractor CO2 Emission Standards
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low Roof
Mid Roof
High Roof
Low Roof
Mid Roof
High Roof
Low Roof
Mid Roof
High
Roof
Engine Fuel Map
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
11L
11L
11L
15L
15L
15L
15L
15L
15L
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
350 HP
350 HP
350 HP
455 HP
455 HP
455 HP
455 HP
455 HP
455 HP
Aerodynamics (CdA in m2)
5.12
6.21
5.67
5.12
6.21
5.67
5.08
6.21
5.26
Steer Tire Rolling Resistance (CRR in kg/metric ton)
5.8
5.8
5.6
5.8
5.8
5.6
5.8
5.8
5.6
Drive Tire Rolling Resistance (CRR in kg/metric ton)
6.2
6.2
5.8
6.2
6.2
5.8
6.2
6.2
5.8
Extended Idle Reduction Weighted Effectiveness
N/A
N/A
N/A
N/A
N/A
N/A
3%
3%
3%
Transmission = 10 speed Manual Transmission
Gear Ratios = 12.8, 9.25, 6.76, 4.90, 3.58, 2.61, 1.89, 1.38, 1.00, 0.73
Drive Axle Ratio = 3.21 for day cabs, 3.16 for sleeper cabs
6x2 Axle Weighted Effectiveness
N/A
N/A
N/A
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
Transmission Type Weighted Effectiveness =
1.6%
Neutral Idle Weighted Effectiveness
0.2%
0.2%
0.2%
0.2%
0.2%
0.2%
0.03%
0.03%
0.03%
Direct Drive Weighted Effectiveness = 1.0%
Transmission Efficiency Weighted Effectiveness = 0.7%
Axle Efficiency Improvement = 1.6%
Air Conditioner Efficiency Improvements =
0.3%
Accessory Improvements = 0.2%
Predictive Cruise Control =0.8%
Automatic Tire Inflation Systems = 0.4%
Tire Pressure Monitoring System = 0.7%
38
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Table 1-16 GEM Inputs for Vehicles Meeting the Phase 2 MY 2027 Vocational Vehicle CO2 Emission
Standards
LHD (Class 2b-5)
MHD (Class 6-7)
HHD (Class 8)
Urban
Multi-
purpose
Regional
Urban
Multi-
purpose
Regional
Urban
Multi-
purpose
Regional
SI Engine Fuel Map
2018 MY 6.8L, 300 hp engine
CI Engine Fuel Map
2027 MY 7L,
200 hp Engine
2027 MY 7L,
270 hp Engine
2027 MY 11L,
350 hp Engine
2027 MY 11L,
350 hp Engine and
2027 MY 15L
455hp Engine
Torque Converter Lockup in 1st Gear (adoption rate)
50%
50%
50%
50%
50%
50%
30%
30%
0%
6x2 Disconnect Axle (adoption rate)
0%
0%
0%
0%
0%
0%
0%
25%
30%
Automatic Engine Shutdown (adoption rate)
70%
70%
90%
70%
70%
90%
70%
70%
90%
Stop-Start (adoption rate)
30%
30%
0%
30%
30%
0%
20%
20%
0%
Neutral Idle (adoption rate)
60%
60%
0%
60%
60%
0%
70%
70%
0%
Steer Tire Rolling Resistance (CRR kg/metric ton)
6.8
6.2
6.2
6.7
6.2
6.2
6.2
6.2
6.2
Drive Tire Rolling Resistance (CRR kg/metric ton)
6.9
6.9
6.9
7.5
6.9
6.9
7.5
6.9
6.9
Weight Reduction (pounds)
75
75
75
75
75
75
125
125
125
Technologies exist today and continue to evolve to improve the efficiency of the engine,
transmission, drivetrain, aerodynamics, and tire rolling resistance in HD vehicles and therefore
reduce their CO2 emissions. As shown here in Table 1-15 and Table 1-16, there are a variety of
such technologies. We also discussed many of these technologies when we promulgated the HD
GHG Phase 2 program.133 In developing the Phase 2 CO2 emission standards, we developed
technology packages that were premised on a mix of projected technologies and potential
technology adoption rates of less than 100 percent. As discussed in Section II.F.4, there is an
opportunity for further improvements and increased adoption through MY 2032 for many of
these technologies. Furthermore, we also considered additional technologies such as H2-ICE,
hybrids, and natural gas engines. Each of these technologies is discussed in this section and RIA
Chapter 1.4.
1.4.1 Aerodynamics
We evaluated the potential for additional GHG performance gains from aerodynamic
improvements. Up to 25 percent of the fuel consumed by a sleeper cab tractor traveling at
highway speeds is used to overcome aerodynamic drag forces, making aerodynamic drag a
133 See 71 FR 73478 (October 25, 2016) and Regulatory Impact Analysis Greenhouse Gas Emissions and Fuel
Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles - Phase 2. Chapter 2. EPA-420-R-16-900.
August 2016
39
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significant contributor to a Class 7 or 8 tractor's GHG emissions and fuel consumption.134
Because aerodynamic drag varies by the square of the vehicle speed, small changes in the tractor
aerodynamics can have a large impact on the GHG emissions of a tractor. With much of their
driving at highway speed, the GHG emission reductions of reduced aerodynamic drag for Class 7
or 8 tractors can be significant.135
Improving the vehicle shape may include revising the fore components of the vehicle such as
rearward canting/raking or smoothing/rounding the edges of the front end components (e.g.,
bumper, headlights, windshield, hood, cab, mirrors) or integrating the components at key
interfaces (e.g., windshield/glass to sheet metal) to alleviate fore vehicle drag. Finally,
improvements may include redirecting the air to prevent areas of low pressure and slow moving
air (thus, eliminating areas where air builds creating turbulent vortices and increasing drag).
Techniques such as blocking gaps in the sheet metal, ducting of components, shaping or
extending sheet metal to reduce flow separation and turbulence are methods being considered by
manufacturers to direct air from areas of high drag (e.g., underbody and tractor-trailer gap).
As discussed in the Phase 2 RIA, the National Research Council of Canada performed an
assessment of the aerodynamic drag effect of various tractor components.136 Based on the
results, there is the potential to improve tractor aerodynamics by 0.206 wind averaged coefficient
of drag area (CdA) with the addition of wheel covers, drive axle wrap around splash guards, and
roof fairing rear edge filler. Up to 0.460 CdA improvement is possible if the side and fender
mirrors are replaced with a camera system, as suggested by the study, and combined with the
wheel covers, drive axle wrap around splash guards, and roof fairing rear edge filler. In our
Phase 2 analysis, considering the wind average drag performance of heavy-duty tractors at the
time, this study demonstrated the possibility to improve tractors an additional ~1 percent with
some simple changes.
In Phase 2, the tractor aerodynamic performance was evaluated using the wind averaged
coefficient of drag area results measured during aerodynamic testing as prescribed in 40 CFR
1037.525. The results of the aerodynamic testing were used to determine the aerodynamic bin
and CdA input value for GEM, as prescribed in 40 CFR 1037.520 and shown in Table l-17Table
1-17.
134 Assumes travel on level road at 65 MPH. (21st Century Truck Partnership Roadmap and Technical White
Papers, December 2006. U.S. Department of Energy, Energy Efficiency and Renewable Energy Program. 21CTP-
003. p.36.
135 Reducing Heavy-Duty Long Haul Combination Truck Fuel Consumption and C02 Emissions, ICCT, October
2009.
136 Jason Leuschen and Kevin R. Cooper (National Research Council of Canada), Society of Automotive Engineer
(SAE) Paper #2006-01-3456: "Full-Scale Wind Tunnel Tests of Production and Prototype, Second-Generation
Aerodynamic Drag-Reducing Devices for Tractor-Trailers.," November 2, 2006.
40
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Table 1-17 GEM Inputs for Tractor Aerodynamic Bins (CdA in m2)
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low
Mid
High
Low
Mid
High
Low
Mid
High
Low
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Bin I
6.00
7.00
7.45
6.00
7.00
7.45
6.00
7.00
7.15
Bin II
5.60
6.65
6.85
5.60
6.65
6.85
5.60
6.65
6.55
Bin III
5.15
6.25
6.25
5.15
6.25
6.25
5.15
6.25
5.95
Bin IV
4.75
5.85
5.70
4.75
5.85
5.70
4.75
5.85
5.40
Bin V
4.40
5.50
5.20
4.40
5.50
5.20
4.40
5.50
4.90
Bin VI
4.10
5.20
4.70
4.10
5.20
4.70
4.10
5.20
4.40
Bin VII
3.80
4.90
4.20
3.80
4.90
4.20
3.80
4.90
3.90
EPA conducted aerodynamic testing for the Phase 2 final rule.137 As shown in Phase 2 RIA
Chapter 3.2.1.2, the most aerodynamic high roof sleeper cabs tested had a CdA of approximately
5.4 m2, which is a Bin IV tractor. Therefore, we concluded that prior to 2016 manufacturers were
producing high roof sleeper cabs that range in aerodynamic performance between Bins I and IV.
Bin V is achievable through the addition of aerodynamic features that improve the aerodynamics
on the best pre-2016 sleeper cabs tested by at least 0.3 m2 CdA. The features that could be added
include technologies such as wheel covers, drive axle wrap around splash guards, and roof
fairing rear edge filler, and active grill shutters. In addition, manufacturers continue to improve
the aerodynamic designs of the front bumper, grill, hood, and windshield.
Our analysis of high roof day cabs is similar to our assessment of high roof sleeper cabs. Also,
as shown in Phase 2 RIA Chapter 3.2.1.2, the most aerodynamic high roof day cab tested by
EPA achieved Bin IV. Our assessment is that the same types of additional technologies that
could be applied to high roof sleeper cabs could also be applied to high roof day cabs to achieve
Bin V aerodynamic performance. Finally, because the manufacturers have the ability to
determine the aerodynamic bin of low and mid roof tractors from the equivalent high roof
tractor, this assessment also applies to low and mid roof tractors.
For our modeled potential compliance pathway in Phase 3 tractors' technology packages, the
vehicles with ICE portion of the technology package for the MY 2027 high roof sleeper cab
tractor includes 20 percent Bin III, 30 percent Bin IV, and 50 percent Bin V reflecting our
assessment of the fraction of high roof sleeper cab tractors. We continue to project, as we
projected in the Phase 2 rulemaking, that manufacturers could successfully apply these
aerodynamic packages by MY 2027. The weighted average for tractors of this set of adoption
rates is equivalent to a tractor aerodynamic performance near the border between Bin IV and Bin
V.
The Phase 2 standards for vocational vehicles were not projected to be met with the use of
aerodynamic improvements.
137 US EPA. Regulatory Impact Analysis Greenhouse Gas Emissions and Fuel Efficiency Standards for
Medium- and Heavy-Duty Engines and Vehicles - Phase 2. Chapter 3. EPA-420-R-16-900. August 2016.
41
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1.4.2 Tire Rolling Resistance
Energy loss associated with tires is mainly due to deformation of the tires under the load of
the vehicle, known as hysteresis, but smaller losses result from aerodynamic drag, and other
friction forces between the tire and road surface and the tire and wheel rim. Collectively the
forces that result in energy loss from the tires are referred to as rolling resistance. Tires with
higher rolling resistance lose more energy, thus using more fuel and producing more CO2
emissions in operation, while tires with lower rolling resistance lose less energy, and use less
fuel, producing less CO2 emissions in operation.
A tire's rolling resistance is a factor considered in the design of the tire and is affected by the
tread and casing compound materials, the architecture of the casing, tread design, and the tire
manufacturing process. It is estimated that 35 to 50 percent of a tire's rolling resistance is from
the tread and the other 50 to 65 percent is from the casing.138 Tire inflation can also impact
rolling resistance in that under-inflated tires can result in increased deformation and contact with
the road surface.
In Phase 2, we developed four levels of tire rolling resistance, as shown in Table l-18Table
1-18. The levels included the baseline (average) from 2010, Level I and Level 2 from Phase 1,
and Level 3 that achieves an additional 25 percent improvement over Level 2. The Level 2
threshold represents an incremental step for improvements beyond today's SmartWay level and
represents the best in class rolling resistance of the tires we tested for Phase l.139 The Level 3
values represented the long-term rolling resistance value that EPA projected could be achieved in
the MY 2025 timeframe. Given the multiple year phase-in of the Phase 2 standards, EPA
expected that tire manufacturers will continue to respond to demand for more efficient tires and
will offer increasing numbers of tire models with rolling resistance values significantly better
than the typical low rolling resistance tires offered in 2016.
138 "Tires & Truck Fuel Economy," A New Perspective. Bridgestone Firestone, North American Tire, LLC, Special
Edition Four, 2008.
139 U.S. EPA. SmartWay Verified Low Rolling Resistance Tires Performance Requirements. Available online:
https://www.epa.gov/sites/default/files/2016-02/documents/420fl2024.pdf
42
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Table 1-18 Phase 2 Tire Rolling Resistance Technologies
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low
Mid
High
Low
Mid
High
Low
Mid
High
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Roof
Steer Tires (CRR in kg/metric ton)
Base
7.8
7.8
7.8
7.8
7.8
7.8
7.8
7.8
7.8
Level 1
6.6
6.6
6.6
6.6
6.6
6.6
6.6
6.6
6.6
Level 2
5.7
5.7
5.7
5.7
5.7
5.7
5.7
5.7
5.7
Level 3
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
Drive Tires (CRR in kg/metric ton)
Base
8.1
8.1
8.1
8.1
8.1
8.1
8.1
8.1
8.1
Level 1
6.9
6.9
6.9
6.9
6.9
6.9
6.9
6.9
6.9
Level 2
6.0
6.0
6.0
6.0
6.0
6.0
6.0
6.0
6.0
Level 3
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
In the modeled compliance pathway for the Phase 3 tractors' technology packages, the
vehicles with ICE portion of the technology package for the MY 2027 included steer and drive
tires that on average performed at a Level 2 rolling resistance. We continue to project, as we
projected in the Phase 2 rulemaking, that manufacturers could successfully apply tires that on
average perform at this level by MY 2027.
1.4.3 Natural Gas Engines
Natural-gas powered heavy-duty vehicles are very similar to gasoline and diesel fueled ICE-
powered vehicles. The engine functions the same as a gasoline or diesel fueled ICE. Two key
differences are the fuel storage and delivery systems. The fuel delivery system delivers high-
pressure natural gas from the fuel tank to the fuel injectors located on the engine. Similar to
gasoline or diesel fuel, natural gas is stored in a fuel tank, or cylinder, but requires the ability to
store the fuel under high pressure.
There are different ways that heavy-duty engines can be configured to use natural gas as a
fuel. The first is a spark-ignition natural gas engine. An Otto cycle SI heavy-duty engine uses a
spark plug for ignition and burns the fuel stoichiometrically. Due to this, the engine-out
emissions require use of a three-way catalyst to control criteria pollutant emissions. The second
is a direct injection natural gas that utilizes a compression-ignition (CI) cycle. The CI engine
uses a small quantity of diesel fuel (pilot injection) as an ignition source along with a high
compression ratio engine design. The engine operates lean of stoichiometric operation, which
leads to engine-out emissions that require aftertreatment systems similar to diesel ICEs, such as
diesel oxidation catalysts, selective catalytic reduction systems, and diesel particulate filters. The
CNG CI engine is more costly than a diesel CI engine because of the special natural gas/diesel
fuel injection system. The NG SI engine and aftertreatment system is less costly than a NG CI
engine and aftertreatment system but is less fuel efficient than a NG CI engine because of the
lower compression ratio.
In addition to differences in engine architecture, the natural gas fuel can be stored two ways -
compressed (CNG) or liquified (LNG). A CNG tank stores pressurized gaseous natural gas and
the system includes a pressure regulator. An LNG tank stores liquified natural gas that is
43
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cryogenically cooled but stored at a lower pressure than CNG. The LNG tanks often are double-
walled to help maintain the temperature of the fuel, and include a gasification system to turn the
fuel from a liquid to a gas before injecting the fuel into the engine. An important advantage of
LNG is the increased energy density compared to CNG. Because of its higher energy density,
LNG can be more suitable for applications such as long-haul applications.
Natural gas engines are a mature technology. Cummins manufactures natural gas engines that
cover the complete range of heavy-duty vehicle applications, with engine displacements ranging
from 6.7L to 12L. Heavy-duty CNG and LNG vehicles are available today in the fleet. EIA
estimates that approximately 4,400 CNG and LNG heavy-duty vehicles were sold in 2022 and
approximately 50,000 CNG and LNG vehicles are in the U.S. heavy-duty fleet.140 Manufacturers
are producing CNG and LNG vehicles in all of the vocational and tractor categories, especially
buses, refuse hauler, street sweeper, and tractor applications, as shown in Table 1-19.141
Table 1-19 MY 2024 CNG, LNG and Propane Powered Heavy-Duty Vehicle Models
Manufacturer
Model
Category
Fuel
Power System
Autocar
ACMD
Refuse
LNG
CNG
Cummins L9N 8.9L Near Zero
Autocar
ACMD
Vocational
Cab Chassis
CNG
LNG
Cummins L9N 8.9L Near Zero
Autocar
ACTT Severe Duty Terminal Tractor
Tractor
LNG
CNG
Cummins B6.7N Near Zero
Autocar
ACX
Vocational
Cab Chassis
CNG
LNG
Cummins L9N 8.9L Near Zero
Cummins ISX12N 11,9L Near Zero
Autocar
ACX
Refuse
LNG
CNG
Cummins ISX12N 11,9L Near Zero
Cummins L9N 8.9L Near Zero
Autocar
DC-64
Vocational
Cab Chassis
LNG
CNG
Cummins ISX12N 11,9L Near Zero
Autocar
DC-64R
Refuse
CNG
LNG
Cummins ISX12N 11,9L Near Zero
Battle Motors
LOW ENTRY TILT 2
Vocational
Cab Chassis
CNG
Cummins L9N 8.9L Near Zero
Cummins B6.7N Near Zero
Battle Motors
LOW NARROW TILT
Vocational
Cab Chassis
CNG
Cummins L9N 8.9L Near Zero
Cummins B6.7N Near Zero
Blue Bird
All American Activity
Passenger Van
Shuttle Bus
CNG
Cummins L9N 8.9L Near Zero
Blue Bird
All American Rear Engine - Class 7
School Bus
CNG
Cummins L9N 8.9L Near Zero
Blue Bird
Micro Bird 5G Activity
Passenger Van
Shuttle Bus
Propane
Ford 7.3L V8
Blue Bird
Micro Bird G5 - Class 3
School Bus
Propane
Ford 7.3L V8
Blue Bird
Vision - Class 7
School Bus
Propane
Ford 7.3L V8
Blue Bird
Vision Activity
Passenger Van
Shuttle Bus
Propane
Ford 7.3L V8
Elgin
Broom Bear
Street Sweeper
CNG
Cummins L9N 8.9L Near Zero
Elgin
Crosswindl
Street Sweeper
CNG
Cummins L9N 8.9L Near Zero
Elgin
Pelican
Street Sweeper
CNG
Cummins B6.7N Near Zero
140 EIA. Annual Energy Outlook 2023. Table 49. Available Online:
https://www.eia.gov/outlooks/aeo/data/browser/#/?id=58-AE02023&cases=ref2023&sourcekey=0
141 Department of Energy Alternative Fuels Data Center. Available Online:
https://afdc.energy.gov/vehicles/search/results?manufacturer_id=67,205,117,394,415,201,113,5,408,481,9,13,ll,45
8,81,435,474,57,416,141,197,417,121,475,53,397,418,85,414,17,21,143,476,492,23,484,398,27,477,399,31,207,396
,489,107,465,487,193,460,35,459,115,37,147,480,199
44
-------
ENC
AXESS 32'
Transit Bus
LNG
CNG
Cummins L9N 8.9L Near Zero
Allison Transmission hybrid drive
ENC
AXESS 35'
Transit Bus
LNG
CNG
Cummins L9N 8.9L Near Zero
ENC
AXESS 40'
Transit Bus
LNG
CNG
Cummins L9N 8.9L Near Zero
ENC
E-Z RIDER II 30'
Transit Bus
CNG
LNG
Cummins L9N 8.9L Near Zero
ENC
E-Z RIDER II 32'
Transit Bus
CNG
LNG
Cummins L9N 8.9L Near Zero
ENC
E-Z RIDER II 35'
Transit Bus
CNG
LNG
Cummins L9N 8.9L Near Zero
Ford
F-59 Stripped Chassis
Vocational
Cab Chassis
CNG
E85/Hybrid Electric
CNG - Bi-fuel
Propane - Bi-fuel
Propane
Ford 7.3L V8
Freightliner
114SDNG- Class 8
Vocational
Cab Chassis
LNG
CNG
Cummins L9N 8.9L Near Zero
Cummins ISX12N 11,9L Near Zero
Freightliner
Cascadia Natural Gas
Tractor
CNG
LNG
Cummins ISX12N 11,9L Near Zero
Freightliner
M2 112 NG
Vocational
Cab ChassisTractor
CNG
LNG
Cummins L9N 8.9L Near Zero
Gillig
BRT, BRT Plus, Commuter
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Gillig
Low Floor, Low Floor Plus
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Gillig
Trolley
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Global
M4
M4HSD CNG
Street Sweeper
CNG
Cummins B6.7N Near Zero
Heil
Environmental
Front Loader: Half Pack (incl Automated),
Half Pack Sierra,
Half Pack LowRider (incl Automated)
Refuse
CNG
Cummins L9N 8.9L Near Zero
Heil
Environmental
Rear Loader: PT1100,
PowerTrak Commercial,
DuraPack 5000,
DuraPack 4060 Split Body,
PT1000
Refuse
CNG
Cummins L9N 8.9L Near Zero
Heil
Environmental
Side Loader: DuraPack Python,
DuraPack Rapid Rail,
Liberty,
Rapid Rail
Refuse
CNG
Cummins L9N 8.9L Near Zero
Hometown
Manufacturing
Carriage
Passenger Van
Shuttle Bus
CNG
Propane
Ford 7.3L V8
Hometown
Manufacturing
Commuter
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Hometown
Manufacturing
Low-Floor Urban
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Hometown
Manufacturing
Mainstreet
Passenger Van
Shuttle Bus
CNG
Cummins L9N 8.9L Near Zero
Hometown
Manufacturing
Streetcar
Passenger Van
Shuttle Bus
CNG
Cummins L9N 8.9L Near Zero
Hometown
Manufacturing
View
Transit Bus
Propane
CNG
Ford 7.3L V8
Hometown
Manufacturing
Villager
Passenger Van
Shuttle Bus
CNG
Propane
Ford 7.3L V8
Kenworth
T180
T280
Vocational
Cab Chassis
CNG
LNG
Cummins L9N 8.9L Near Zero
Kenworth
T380
T480
Vocational
Cab Chassis
CNG
LNG
Cummins L9N 8.9L Near Zero
Mack
Anthem - Class 8
Tractor
CNG
LNG
Cummins ISX12N 11,9L Near Zero
45
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Mack
Granite
Vocational
Cab Chassis
CNG
LNG
Cummins L9N 8.9L Near Zero
Mack
LR
Refuse
LNG
CNG
Cummins L9N 8.9L Near Zero
Mack
LR
Vocational
Cab Chassis
LNG
CNG
Cummins L9N 8.9L Near Zero
Mack
TerraPro Cab Over
Vocational
Cab Chassis
LNG
CNG
Cummins L9N 8.9L Near Zero
Mack
TerraPro Cab Over
Refuse
LNG
CNG
Cummins L9N 8.9L Near Zero
MCI
D4000 Commuter Coach
Transit Bus
CNG
Cummins ISX12N 11,9L Near Zero
MCI
D4500 Commuter Coach
Transit Bus
CNG
Cummins ISX12N 11,9L Near Zero
McNeilus
Atlantic Front Loader - Class 8
Refuse
CNG
Cummins L9N 8.9L Near Zero
Cummins ISX12N 11,9L Near Zero
McNeilus
Rear Loader: Standard,
Heavy-Duty,
Extra Compaction,Tag Axle,
Split Body,
M2 - Class 8
Refuse
CNG
Cummins ISX12N 11,9L Near Zero
Cummins L9N 8.9L Near Zero
McNeilus
Side Loader: AutoReach,
Manual
Automated,
Zero Radius - Class 8
Refuse
CNG
Cummins L9N 8.9L Near Zero
Cummins ISX12N 11,9L Near Zero
McNeilus
Standard,
Bridgemaster,
Oshkosh S-Series - Class 8
Vocational
Cab Chassis
CNG
Cummins ISX12N 11,9L Near Zero
Cummins L9N 8.9L Near Zero
New Flyer
Xcelsior CNG 35'
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
New Flyer
Xcelsior CNG 40'
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
New Flyer
Xcelsior CNG 60'
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Nitehawk
Osprey II sweeper
Street Sweeper
Propane - Bi-fuel
GMC 6.0L V8
Nitehawk
Raptor II sweeper
Street Sweeper
CNG
Propane - Bi-fuel
GMC 6.0L V8
Nova Bus
LFS CNG - Class 8
Transit Bus
CNG
Cummins L9N 8.9L Near Zero
Peterbilt
365 - Class 6
Vocational
Cab Chassis
CNG
LNG
Cummins B6.7N Near Zero
Cummins L9N 8.9L Near Zero
Peterbilt
520
Vocational
Cab Chassis
CNG
Cummins L9N 8.9L Near Zero
Cummins ISX12N 11,9L Near Zero
Peterbilt
535 - Class 5
Vocational
Cab Chassis
CNG
LNG
Cummins B6.7N Near Zero
Peterbilt
536 - Class 6
Vocational
Cab Chassis
LNG
CNG
Cummins B6.7N Near Zero
Cummins L9N 8.9L Near Zero
Peterbilt
537 - Class 7
Vocational
Cab Chassis
LNG
CNG
Cummins L9N 8.9L Near Zero
Cummins B6.7N Near Zero
Peterbilt
548 - Class 8
Vocational
Cab Chassis
LNG
CNG
Cummins B6.7N Near Zero
Cummins L9N 8.9L Near Zero
Peterbilt
567 - Class 8
TractorVocational
Cab Chassis
CNG
LNG
Cummins L9N 8.9L Near Zero
Cummins ISX12N 11,9L Near Zero
Peterbilt
579
TractorVocational
Cab Chassis
CNG
LNG
Cummins ISX12N 11,9L Near Zero
Schwarze
Industries
A7 Tornado sweeper - Class 6
Street Sweeper
CNG
Schwarze
Industries
A7 Zephyr sweeper - Class 6
Street Sweeper
CNG
Schwarze
Industries
M6 Avalanche
Street Sweeper
CNG
TICO
Pro Spotter
Tractor
CNG
LNG
Cummins B6.7N Near Zero
46
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TYMCO
500x
Street Sweeper
CNG
Cummins L9N 8.9L Near Zero
TYMCO
600
Street Sweeper
CNG
Cummins L9N 8.9L Near Zero
TYMCO
HSP
Street Sweeper
CNG
Cummins L9N 8.9L Near Zero
1.4.4 Hydrogen-Fueled Internal Combustion Engines
Currently, hydrogen fueled internal combustion engines (H2-ICE) are in the demonstration
stage. H2-ICE is a technology that provides nearly zero tailpipe emissions for hydrocarbons,
carbon monoxide, and carbon dioxide. H2-ICE require less exhaust aftertreatment. These
systems may not require the particulate filter (DPF) components. However, NOx emissions are
still formed during the H2-ICE combustion process and therefore a selective catalytic reduction
(SCR) system and diesel oxidation catalyst (DOC) would be required, though it may be smaller
in size than that used in a comparable diesel-fueled ICE. The use of lean air-fuel ratios, and not
exhaust gas recirculation (EGR), is the most effective way to control NOx in a H2-ICE, as EGR
is less effective with H2 due to the absence of CO2 in the exhaust gas.
H2-ICE can be developed using an OEM's existing tooling, manufacturing processes, and
engine design expertise. H2-ICE engines are very similar to existing ICEs and can leverage the
extensive technical expertise manufacturers have developed with existing products. Similarly,
H2-ICE products can be built on the same assembly lines as other ICE vehicles, by the same
workers and with many of the same component suppliers.
H2-ICE incorporate several differences from their diesel baseline. Components such as the
cylinder head, valves, seals, piston, and piston rings would be unique to the H2-ICE to control
H2 leakage during engine operation. Another difference between a diesel-fueled ICE and a H2-
ICE is the fuel storage tanks. The hydrogen storage tanks are more expensive than today's diesel
fuel tanks. The fuel tanks likely to be used by H2-ICE are identical to those used by a fuel cell
electric vehicle (FCEV) and they may utilize either compressed storage (350 or 700 Bar
pressure) or cryogenic storage (temperatures as low as -253 Celsius). Please refer to Chapter
1.7.2 of this document for the discussion regarding H2 fuel storage tanks.
H2-ICE may hasten the development of hydrogen infrastructure because they do not require
as pure of hydrogen as FCEVs. Hydrogen infrastructure exists in limited quantities in some parts
of the country for applications such as forklifts, buses, and LDVs and HDVs at ports. Federal
funds are being used to support the development of additional hubs and other hydrogen related
infrastructure items through the BIL and IRA, as described in more detail in Chapter 1.8.
Since neat hydrogen fuel does not contain any carbon, H2-ICE fueled with neat hydrogen
produce zero HC, CH4, CO, and CO2 engine-out emissions.142 However, as explained in Section
III.C.2.xviii, we recognize that, like CI ICE, there may be negligible, but non-zero, CO2
emissions at the tailpipe of H2-ICE that use SCR and are fueled with neat hydrogen due to
contributions from the aftertreatment system from urea decomposition; thus, for purposes of 40
CFR 1036 we are finalizing an engine testing default CO2 emission value (3 g/hp-hr) option
(though manufacturers may instead conduct testing to demonstrate that the CO2 emissions for
their engine is below 3 g/hp-hr). Under this final rule, consistent with treatments of such
142 Note, NOx and PM emission testing is required under existing 40 CFR part 1036 for engines fueled with neat
hydrogen.
47
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contributions from the aftertreatment system from urea decomposition for diesel ICE vehicles,
we are not including such contributions as vehicle emissions for H2-ICE vehicles.143 Thus, H2-
ICE technologies that run on neat hydrogen, as defined in 40 CFR 1037.150(f) and discussed in
Section III.C.3.ii of the preamble, have HD vehicle CO2 emissions that are deemed to be zero for
purposes of 40 CFR 1037. Therefore, the technology effectiveness (in other words CO2 emission
reduction) for the vehicles that are powered by this technology is 100 percent.
1.4.5 Hybrid and Plug-in Hybrid Powertrains
The heavy-duty industry has also been developing hybrid powertrains, as shown in Table
1-20. Hybrid powertrains consist of an ICE as well as an electric drivetrain. The ICE uses a
consumable fuel (e.g., diesel) to produce power which can either propel the vehicle directly or
charge the traction battery from which the electric motor draws its energy. These two sources of
power can be used in combination to do work and move the vehicle, or they may operate
individually, switching between the two sources. Plug-in hybrid electric vehicles (PHEVs) are a
combination of ICE and electric vehicles, so they have an ICE and a battery, an electric motor,
and a fuel tank, and plug-in to the electric grid to recharge the battery. PHEVs use both gasoline
or diesel and electricity as fuel sources.
Table 1-20 Heavy-Duty Hybrid Vehicle Examples144
Transmission
Heavy-Duty Power
Manufacturer
Model
Category
Fuel
Make
System
Broom Bear
Street
Plug-in Hybrid
Electric CNG -
Compressed
Cummins L9N 8.9L
Elgin
CNG Hybrid
Sweeper
Natural Gas
Near Zero
Elgin
Broom Bear
Plug-In
Hybrid
Street
Sweeper
Diesel/Hybrid
Electric Plug-in
Hybrid Electric
Cummins ISL 9L
Cummins ISL
ENC
AXESS 32'
Transit Bus
Diesel/Hybrid
Electric
Allison,
Voith, ZF
9L Allison
Transmission hybrid
drive
Cummins ISL
ENC
AXESS 35'
Transit Bus
Diesel/Hybrid
Electric
Allison,
Voith, ZF
9L Allison
Transmission hybrid
drive
Cummins ISL
ENC
AXESS 40'
Transit Bus
Diesel/Hybrid
Electric
Allison,
Voith, ZF
9L Allison
Transmission hybrid
drive
E-Z RIDER
Diesel/Hybrid
Allison,
Cummins ISL
ENC
II 30'
Transit Bus
Electric
Voith, ZF
9L Cummins
143 The results from the fuel mapping test procedures prescribed in 40 CFR 1036.535 are fuel consumption values,
therefore the CO2 emissions from urea decomposition is not included in the results.
144 Department of Energy Alternative Fuels Data Center. Available Online:
https://afdc.energy.gov/vehicles/search/results?view_mode=grid&search_field=vehicle&search_dir=desc&per_page
=8¤t=true&display _length=25&model_year=2024&fuel_id=57,45,61,-
l&all_categories=y&manufacturer_id=67,205,117,394,415,201,113,5,408,481,9,13,ll,458,81,435,474,57,416,141,
197,417,121,475,53,397,418,85,414,17,21,143,476,492,23,484,398,27,477,399,31,207,396,489,107,465,487,193,46
0,35,459,115,37,147,480,199,-1
48
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ISB6.7 Allison
Transmission hybrid
drive BAE Systems
HybriDrive
Cummins ISL
ENC
E-Z RIDER
II 32'
Transit Bus
Diesel/Hybrid
Electric
Allison,
Voith, ZF
9L Cummins
ISB6.7 Allison
Transmission hybrid
drive BAE Systems
HybriDrive
Cummins
ENC
E-Z RIDER
II 35'
Transit Bus
Diesel/Hybrid
Electric
Allison,
Voith, ZF
I SB 6.7 Cummins ISL
9LBAE Systems
HybriDrive Allison
Transmission hybrid
drive
BRT, BRT
Cummins
Gillig
Plus,
Commuter
Transit Bus
Diesel/Hybrid
Electric
Voith,
Allison, ZF
I SB 6.7 Cummins ISL
9L
Low Floor,
Gillig
Low Floor
Plus
Transit Bus
Diesel/Hybrid
Electric
Global
M4 Hybrid
Street
Sweeper
Diesel/Hybrid
Electric
Global
Cummins I SB 6.7
Hometown
Passenger
Van/Shuttle
Diesel/Hybrid
Allison B300,
Manufacturing
Streetcar
Bus
Electric
B400
Cummins I SB 6.7
D4000
MCI
Commuter
Coach
Transit Bus
Diesel/Hybrid
Electric
Allison
Cummins ISL 9L
D4500
MCI
Commuter
Coach
Transit Bus
Diesel/Hybrid
Electric
Allison
Cummins ISL 9L
Cummins
New Flyer
Xcelsior
Hybrid 35'
Transit Bus
Diesel/Hybrid
Electric
Allison, BAE
ISB6.7 Allison
Transmission hybrid
drive BAE Systems
HybriDrive
Cummins
New Flyer
Xcelsior
Hybrid 40'
Transit Bus
Diesel/Hybrid
Electric
Allison, BAE
ISB6.7 Allison
Transmission hybrid
drive BAE Systems
HybriDrive
Cummins ISL 9L BAE
New Flyer
Xcelsior
Hybrid 60'
Transit Bus
Diesel/Hybrid
Electric
Allison, BAE
Systems
HybriDrive Allison
Transmission hybrid
drive
Cummins ISL
LFS Artie
9L Allison
Transmission H 50
Nova Bus
HEV - Class
8
Transit Bus
Diesel/Hybrid
Electric
Allison, BAE
EP BAE Systems
HDS300
Nova Bus
LFS HEV -
Class 8
Transit Bus
Diesel/Hybrid
Electric
Allison, BAE
Cummins I SB 6.7
49
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Hybrid powered vehicles can provide CO2 emission reductions from splitting or blending of
ICE and electric operation. Hybrid vehicles reduce CO2 emissions through four primary
mechanisms:
• In a series hybrid powertrain, the ICE operates as a generator to create electricity for the
battery. Series hybrids can be optimized through downsizing, modifying the operating cycle,
or other control techniques to operate at or near its most efficient engine speed-load
conditions more often than is possible with a conventional engine-transmission driveline.
Power loss due to engine downsizing can be mitigated by employing power assist from the
secondary, electric driveline.
• Hybrid vehicles typically include regenerative braking systems that capture some of the
energy normally lost while braking and store it in the traction battery for later use. That
stored energy is typically used to provide additional torque upon initial acceleration from
stop or additional power for moving the vehicle up a steep incline.
• Hybrid powertrains allow the engine to be turned off when it is not needed, such as when the
vehicle is coasting or when the vehicle is stopped. Furthermore, some vehicle systems such
as cabin comfort and power steering can be electrified if a 48V or higher battery system is
incorporated into the vehicle. The electrical systems are more efficient than their
conventional counterparts which utilize an accessory drive belt on a running engine. When
the engine is stopped these accessory loads are supported by the traction battery.
• Plug-in hybrid vehicles can further reduce CO2 emissions by increasing the battery storage
capacity and adding the ability to connect to the electrical power grid to fully charge the
battery when the vehicle is not in service, which can significantly expand the amount of all-
electric operation.
Hybrid vehicles can utilize a combination of some or all of these mechanisms to reduce fuel
consumption and CO2 emissions. The magnitude of the CO2 reduction achieved depends on the
utilization/optimization of the above mechanisms and the powertrain design decisions made by
the manufacturer.
Hybrid technology is well established in the U.S. light-duty market, where some
manufacturers have been producing light-duty hybrid models for several decades and others are
looking to develop hybrid models in the future. Hybrid powertrains are available today in a
number of heavy-duty vocational vehicles including passenger van/shuttle bus, transit bus, street
sweeper, refuse hauler, and delivery truck applications. Hybrid transit buses have been purchased
for use in cities including Philadelphia, PA and Toronto, Canada. Heavy-duty hybrid vehicles
may include a power takeoff (PTO) system that is used to operate auxiliary equipment, such as
the boom/bucket on a utility truck or the water pump on a fire truck. Utility trucks with electric
PTOs where the electricity to power the auxiliary equipment can be provided by the battery have
been sold.
50
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Plug-in hybrid electric vehicles run on both electricity and fuel. Many PHEV models are
available today in the light-duty market.145 Today there is a limited number of PHEV heavy-duty
models. Light-duty manufacturers that also produce heavy-duty vehicle could bring PHEVs to
market in the LHD and MHD segments in less time than for the HHD and tractor segments. The
utility factor is the fraction of miles the vehicle travels in electric mode relative to the total miles
traveled. The percent CO2 emission reduction is directly related to the utility factor. The greater
the utility factor, the lower the tailpipe CO2 emissions from the vehicle. The utility factor
depends on the size of the battery and the operator's driving habits.
1.5 Battery Electric Vehicle Technologies
The application of battery electric vehicle technologies primarily results in the effective
replacement of the ICE powertrain with a battery electric propulsion system. The battery electric
propulsion system includes a battery pack that provides the power to the motor to move the
vehicle.
Battery technology improvements are being widely researched in industry and academia with
goals to lengthen vehicle range and increase battery life. Examples of battery technologies that
would result in a significant jump in battery performance include semi-solid state and solid-state
designs. Improvements in charging strategies can also increase a battery's operational life and
have been demonstrated in transit bus applications.
1.5.1 Batteries
The batteries used for today's BEVs are highly advanced; however, the fundamental theory of
the battery continues to include two half-cell electrodes separated by a membrane separator that
is submerged in a conductive electrolyte. These half-cells, together, make up a battery cell.
During charge and discharge cycles, a chemical reaction takes place at each of the electrodes
when ions, such as lithium, move through a conductive medium between the electrodes. Here, an
electron is either released or consumed, in turn generating an electric current. This electricity is
used to perform work— converting the electric current into mechanical work using an electric
motor. While some heat is generated during the chemical process, all reactions are contained
within the cell and no emissions are produced from the battery cell itself on-board the vehicle.
1.5.1.1 Battery Design Parameters
Battery design involves balancing considerations of cost146 and performance parameters
including specific energy147 and power, energy density148, temperature impact on performance,
145 US Department of Energy. Fueleconomy.gov. Available online:
https://fueleconomy.gov/feg/PowerSearch.do?action=alts&path=3&year=2024&vtype=Plug-
in+Hybrid&srchtyp=yearAfv&rowLimit=50&pageno=l
146 Cost, here, is associated with cost of the battery design produced at scale instead of the decrease in cost of
batteries from high volume production. This cost may be associated with using more expensive minerals (nickel and
cobalt instead of iron phosphate). Alternatively, some battery cell components may be more expensive for the same
chemistry. For example, power battery cells are more expensive to manufacture than energy battery cells because
these cells require thinner electrodes which are more complex to produce.
147 Battery specific energy (also referred to as gravimetric energy density) is a measure of battery energy per unit of
mass.
148 Battery energy density (also referred to as volumetric energy density) is a measure of battery energy per unit of
volume.
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durability, and safety. These parameters typically vary based on the battery chemistry of the
cathode and anode materials, and the conductive electrolyte medium at the cell level. Different
battery chemistries have different intrinsic values. External factors such as ambient temperature
can also affect the performance of the battery. There are extensive bodies of work within each of
these areas that are beyond the scope of this document. Nonetheless, because of the novel nature
of these technologies for HD application, we provide a brief overview of the different energy and
power capacities of batteries depending on their battery chemistries.
Design choices about the different energy and power capacities to emphasize in a battery can
depend on its battery chemistry. Common battery chemistries today include nickel-manganese-
cobalt (NMC), nickel-cobalt-aluminum (NCA), and iron-phosphate (LFP) based-chemistries.
Nickel-based chemistries typically have higher gravimetric and volumetric energy densities than
iron phosphate-based chemistries. Batteries have a nested design: a group of cells are typically
placed inside a module and a group of modules are placed inside a pack. While the modules and
packs provide design simplicity and structure support, energy or power is only housed at the
chemistry level. Therefore, any additional mass such as the cell, module, and pack casings will
only add to the weight of the battery without increasing the energy of the overall system. In
recent years, some pack producers have eliminated the module in favor of a "cell-to-pack"
design.149 Here, the module is eliminated where cells are placed directly into battery packs
without the intermediate module component; the purpose is to reduce both weight and volume of
the battery pack and thus increase the specific energy and energy density of the pack,
respectively.
Specific energy and power and energy density are a function of how much energy or power
can be stored per unit mass or volume; these values typically have units of Watt-hour per
kilogram (Wh/kg), Watt per kilogram (W/kg) or Watt-hour per liter (Wh/L), respectively.
Therefore, for a given battery weight, the energy (in kilowatt-hour or kWh) can be calculated. A
battery chemistry with high specific energy and a lower weight may yield the same amount of
energy as a battery chemistry with a lower specific energy and higher weight. An example of
this can be found in Table 1-21.
Table 1-21 Battery weight and volume to meet vehicle requirement for two different chemistries
Battery
Chemistry
Vehicle Energy
Requirement
(kWh)
Specific Energy
(Wh/kg)
Weight of
Battery (kg)
Energy
Density
(Wh/L)
Volume of
Battery (L)
A
100
200
500
400
250
B
100
100
1,000
200
500
External factors, especially temperature, can have a strong influence on the performance of
the battery; for example, lower temperatures typically result in lower useable energy. For more
efficient operation, batteries are maintained at a particular operating temperature range; this is
commonly referred to as conditioning of the battery. Heavy-duty BEVs today include thermal
management systems to keep the battery operating within a desired temperature range. If the
battery is plugged in overnight, the manufacturer may allow for grid energy to maintain this
temperature range. Generally, this is referred to as pre-conditioning. However, during vehicle
149 BYD's "blade" cells are an example of cell-to-pack technology.
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operation, the energy will have to come from the energy stored within the battery itself without
the ability to rely on grid energy. Therefore, additional energy for battery conditioning will be
required for vehicles operating in hot and cold climates.150 Cold temperatures, in particular, can
result in reduced useable energy as a result of reduced mobility of the lithium ions in the liquid
electrolyte; for the driver, this may mean lower range. Battery thermal management is also used
during hot ambient temperatures to keep the battery from overheating.
Another important battery design consideration is the durability of the battery. Durability is
frequently associated with cycle life, where cycle life is the number of times a battery can fully
charge and discharge before the battery is no longer usable for its original purpose. In 2015 the
United Nations Economic Commission for Europe (UN ECE) began studying the need for a
Global Technical Regulation (GTR) governing battery durability in light-duty vehicles. In 2021
it finalized United Nations Global Technical Regulation No. 22, "In-Vehicle Battery Durability
for Electrified Vehicles,"151 or GTR No. 22, which provides a regulatory structure for contracting
parties to set standards for battery durability in light-duty BEVs and PHEVs. Likewise, although
not finalized, the UN ECE GTR working group began drafting language for HD BEVs and
PHEVs. Loss of electric range could lead to a loss of utility, meaning electric vehicles are driven
less and therefore displace less distance travelled that might otherwise be driven in conventional
vehicles. Furthermore, a loss in utility could also dampen purchaser sentiment.
For batteries that are used in HD BEVs, the state-of-health (SOH) is an important design
factor.152 The environmental performance of electrified vehicles may be affected by excess
degradation of the battery system over time. However, the durability of a battery is not limited
to the cycling of a battery; there are many phenomena that can impact the duration of usability of
a battery. As a battery goes through charge and discharge cycles, the SOH of the battery
decreases. Capacity fade, increase in internal resistance, and voltage loss, for example, are other
common metrics to measure the SOH of a battery. These parameters together help better
determine and define the longevity or durability of the battery. The SOH and, in turn, the cycle
life of the battery is determined by both the chemistry of the battery as well as external factors
including temperature. The rate at which the battery is discharged as well as the rate at which it
is charged will also impact the SOH of the battery. Lastly, calendar aging, or degradation of the
battery while not in use, can also contribute to the deterioration of the battery.
There are a number of ways to improve and prolong the battery life in a vehicle. We included
additional energy for conditioning the battery in our analysis for sizing the batteries and for
operating costs. Furthermore, we considered the impact of deterioration on battery size. This is
discussed in Chapter 2.4.1.
150 AAA Report. "AAA Electric Vehicle Range Testing: AAA proprietary research into the effect of ambient
temperature and HVAC use on driving range and MPGe". Available on:
https://www.aaa.com/AAA/common/AAR/files/AAA-Electric-Vehicle-Range-Testing-Report.pdf
151 United Nations Economic Commission for Europe, Addendum 22: United Nations Global Technical Regulation
No. 22, United Nations Global Technical Regulation on In-vehicle Battery
Durability for Electrified Vehicles, April 14, 2022. Available at: https://unece.org/sites/default/files/2022-
04/ECE_TRANS_ 180a22e.pdf
152 See Section III.B of the preamble for information on the durability monitoring requirements we are finalizing.
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1.5.1.2 Critical Minerals and Battery Market
In Section II.D.2.ii.c of the Preamble and RTC section 17.2, we provide a thorough analysis of
recent events in the growth of U.S. and global battery manufacturing capacity, review the role
and importance of critical minerals, and considered the outlook for availability of both the
critical minerals themselves, and their related supply chains. Citations for the content in this
section can be found in Preamble Section II.D.2.ii.c, except where cited here. We show there that
of the four minerals considered critical for battery manufacture (lithium, cobalt, nickel, and
graphite), domestic lithium supply and refining capacity plus capacity available from Free Trade
Agreement (FTA) countries appears to be largely sufficient to accommodate domestic lithium-
ion battery demand in the mid- and long-term, and that the U.S. could be one of the worldwide
leaders in production by 2035. The three remaining critical minerals, are unlikely to be sourced
domestically within the rule's timeframe, but can be adequately sourced by supplies from FTA
and Mineral Security Partnership (MSP) countries, and (for cobalt and graphite in particular)
from other countries with which the U.S. has strong ties as well (for example through defense
treaties or other agreements or partnerships). In this regard, we discuss the bilateral and multi-
lateral agreements with various non-FTA/MSP countries that help provide an assurance of
supply. We also discuss availability of manganese, which is important to battery manufacture
but is not classified as a critical mineral, and examine pathways to securing manganese supply.
The focus on lithium, cobalt, nickel, manganese, and graphite, stems from the fact that their
increased use is unique to BEVs compared with ICE vehicles (Figure 1-5 below)
l£A, licence: CC pY 4,0
O Copper ® Lithium O Nickel • Manganese O Cobalt O Graphite O Zinc O Rare earths O Others
Figure 1-5 Minerals used in electric cars compared to conventional cars
In those same Preamble and RTC discussions, we show that there is sufficient battery cell
production capacity to satisfy demand from the heavy-duty sector. We further discuss
availability of supply for battery components, including cathode and anode active materials.
We also note that further development of a secure, diversified mineral supply chain is already
being accelerated by the provisions of the Inflation Reduction Act (IRA) and the Bipartisan
Infrastructure Law (BIL), as well as ongoing efforts by the Executive Branch:
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• The IRA offers sizeable tax incentives for domestic production of batteries and critical
minerals, including production tax credits that apply to domestically produced cells,
modules, and packs, electrode active materials, and critical minerals, that can reduce
battery manufacturing cost by thirty percent or more.
• The BIL provides $7.9 billion to support development of the domestic supply chain
for battery manufacturing, recycling, and critical minerals. Provisions extend across
critical minerals mining and recycling research, USGS energy and minerals research,
rare earth elements extraction and separation research and demonstration, and
expansion of DOE loan programs in critical minerals and recycling.
• Through these provisions, DOE is actively working to prioritize points in the domestic
supply chain to target with accelerated development, and rapidly funding those areas
through numerous programs and funding opportunities.
• With BIL funding and heavy private investment153, more than half of the capital
investment that the Department of Energy's Li-Bridge alliance considers necessary for
supply chain investment to 2030 has already been committed.
• The White House announced the IPEF Critical Minerals Dialogue, an initiative to support
U.S. expansion and development of the critical mineral supply chain. IPEF is the Indo-
Pacific Economic Framework for Prosperity (IPEF), a partnership between Australia,
Brunei, Fiji, India, Indonesia, Japan, Republic of Korea, Malaysia, New Zealand, the
Philippines, Singapore, Thailand, and Viet Nam154 More broadly, the IPEF's pillars
spanning trade, supply chains, clean economy, and fair economy form a foundation to
ensure tangible benefits that fuel economic activity and investment, promote sustainable
and inclusive economic growth, and benefit workers and consumers across the region.155
The IPEF Supply Chain Agreement entered into force on February 24, 2024.156
• The State Department also sent delegations to Chile, the Philippines, and South Korea, led
by Under Secretary Jose W. Fernandez, to strengthen cooperation around critical mineral
supply chains. 157
• The State Department launched the Minerals Investment Network for Vital Energy
Security and Transition, or MINVEST, in 2023: a public-private partnership between the
153 Automotive News. "Private companies fund most EV battery manufacturing investment, DOE says". Available
online: https://www.autonews.com/suppliers/us-ev-battery-manufacturing-investment-led-private-companies-doe-
says
154 The White House. "FACT SHEET: In San Francisco, President Biden and 13 Partners Announce Key Outcomes
to Fuel Inclusive, Sustainable Growth as Part of the Indo-Pacific Economic Framework for Prosperity". November
16, 2023. Available online: https://www.whitehouse.gov/briefing-room/statements-releases/2023/ll/16/fact-sheet-
in-san-francisco-president-biden-and-13-partners-announce-key-outcomes-to-fuel-inclusive-sustainable-growth-as-
part-of-the-indo-pacific-economic-framework-for-prosperity/
155 UD Department of Commerce. "Indo-Pacific Economic Framework. Accessed March 11, 2024. Available online:
https ://www. commerce .gov/ipef
156 U.S. Department of Commerce. "U.S. Department of Commerce Announces Upcoming Entry into Force of the
IPEF Supply Chain Agreement". Available online: https://www.commerce.gov/news/press-releases/2024/01/us-
department-commerce-announces-upcoming-entry-force-ipef-supply-chain
157 U. S. Department of State. "Under Secretary Fernandez's Travel to Vietnam, the Philippines, and the Republic of
Korea". January 19, 2024. Available online: https://www.state.gov/under-secretary-fernandezs-travel-to-vietnam-
the-philippines-and-the-republic-of-korea/
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U.S. Department of State and SAFE Center for Critical Minerals Strategy to spur
investment in mining, processing, and recycling opportunities.158 The State Department's
ambassadors and commercial experts also connect U.S. companies with mining and
opportunities internationally through the Direct Line for American Business program.159
• The White House and the European Union together announced support for the Lobito
Corridor, which connects the Democratic Republic of the Congo and Northwest Zambia to
regional and global trade through the Port of Lobito in Angola. The corridor will reduce
transport time, lower costs, and reduce the carbon footprint of metals exports from the
region. The United States and the E.U. also intend to support sustainable economic
development in the three countries, including clean energy projects and supporting
diversified investment in critical minerals and clean energy supply chains.160 In February
2024, the MSP announced the signing of an MOU between DRC's state mining company,
Gecamines, and the Japan Organization for Metals and Energy Security (JOGMEC), to
collaborate on exploration, production, and processing of critical minerals in the
DRC.161 Shortly thereafter, Gecamines announced the transfer of exclusive mining rights
for five mining areas to its subsidiary Entreprise Generale du Cobalt (EGC); EGC
Chairman describes this action as "the beginning of the standardization of artisanal cobalt
mining," which has been linked to human rights violations.162
• The U.S. Trade Representative facilitated an agreement between the U.S. and India to
develop a roadmap on critical minerals and supply chains to increase cooperation and
achieve economically meaningful outcomes.163
• The USGS collaborated with the federal geological surveys of Canada and Australia to
release a compilation of minerals resource datasets.164
158 U. S. Department of State. "MINVEST: Minerals Investment Network for Vital Energy Security and Transition".
Available online: https://www.state.gov/minvest
159 U.S. Department of State. "Direct Line for American Business". Available online: https://www.state.gov/direct-
line-for-americanbusiness/
160 The White House. "Joint Statement from the United States and the European Union on Support for Angola,
Zambia and the Democratic Republic of the Congo's commitment to Further Develop the Lobito Corridor and the
U.S.-EU Launch of a Greenfield Rail Line Feasibility Study". September 9, 2023. Available online:
https://www.whitehouse.gOv/briefing-room/statements-releases/2023/09/09/joint-statement-from-the-united-states-
and-the-european-union-on-support-for-angola-zambia-and-the-democratic-republic-of-the-congos-commitment-to-
further-develop-the-lobito-corridor-and-the/
161 U.S. Department of State. "The Minerals Security Partnership Announces Collaboration in Minerals Exploration,
Production, and Processing Between GECAMINES in the Democratic Republic of the Congo and JOGMEC in
Japan". February 5, 2024. Available online: https://www.state.gov/the-minerals-security-partnership-announces-
collaboration-in-minerals-exploration-production-and-processing-between-gecamines-in-the-democratic-republic-
of-the-congo-and-jogmec-in-japan/
162 Reuters. "Congo's Gecamines and Entreprise Generale du Cobalt sign mining deal". February 7, 2024. Available
online: https://www.reuters.com/markets/commodities/congos-gecamines-entreprise-generale-du-cobalt-sign-
mining-deal-2024-02-07/
163 Office of the United States Trade Representative. "Joint Statement on the United States-India Trade Policy
Forum". January 12, 2024. Available online: https://ustr.gov/about-us/policy-offices/press-office/press-
releases/2024/january/joint-statement-united-states-india-trade-policy-forum
164 U.S. Geological Survey. "Australia, Canada and US Unify Critical Minerals Data. August 17, 2023. Available
online: https://www.usgs.gov/news/technical-announcement/australia-canada-and-us-unify-critical-minerals-data
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• USAID granted funds through the Just Energy Transition Green Minerals Challenge to 11
partners across 15 countries throughout Africa, Asia, and Latin America, to combat
corruption and increase transparency and integrity in global critical minerals supply
chains.165
• DOI, through its International Technical Assistance Program, is working with partners
around the world to advance technical capacity and improve governance for clean energy
minerals projects. Recent work includes working with Argentina to build capacity for
sustainable lithium development.166
• USAID, in collaboration with the U.S. Commercial Service, formalized a $5 million
technical assistance program to develop the Philippines' critical minerals sector.167
• In September 2023, President Biden met with the presidents of Kazakhstan, Kyrgyzstan,
Tajikistan, Turkmenistan, and Uzbekistan (C5+1), launching the C5+1 Critical Minerals
Dialogue and committing to principles of partnership. The Dialogue aims to strengthen
economic cooperation, support sustainable development, and advance the development of
a robust minerals industry in the region.168
• The U.S. Trade and Development Agency (USTDA), which advances economic
development and U.S. export opportunities abroad, recently accepted proposals for a
contractor to assess potential critical minerals projects in Sub-Saharan Africa.169
EPA recognizes that the global minerals industry and battery supply chain are already
anticipating and preparing for accelerated growth in demand for critical minerals resulting from
already-existing expectations of greatly increased global ZEV production and sales in the future,
as well as expectations of growing demand for these materials in other areas of clean energy and
decarbonization. Thus, in the context of evaluating the impact of the final standards on demand
for critical minerals and development of the domestic supply chain, EPA recognizes that much of
the anticipated growth in global mineral demand stems not from the incremental effect of the
final standards but from these ongoing forces that are already driving the global industry to
increase mineral production. While the U.S. will need imports to bolster supply for most key
minerals, these imports can come from friendly nations, and is also bolstered by growing
domestic supply, especially for lithium. The analysis also finds that, with the appropriate policies
and enabling approaches in place, the U.S. is capable of securing the minerals it needs by relying
on domestic production as well as trade relationships with allies and partners (Figure 1-6).
165 United States Agency for International Development. "Powering a Just Energy Transition Green Minerals
Challenge". Available online: https://www.usaid.gov/anti-corruption/document/powering-just-energy-transition-
green-minerals-challenge
166 U.S. Department of the Interior. "Energy and Minerals". Available online: https://www.doi.gov/itap/energy-and-
minerals
167 U.S. Embassy in the Philippines. "Partnership Launched To Implement U.S.-Funded Php280 Million Program
For Philippine Critical Minerals Sector
168 The White House. "C5+1 Leaders' Joint Statement". September 21, 2023. Available online:
https://www.whitehouse.gov/briefing-room/statements-releases/2023/09/21/c51-leaders-joint-statement/
169 U.S. Trade and Development Corporation. "Clean Energy and Critical Minerals Desk Study: Sub-Saharan
Africa". Available online: https://www.ustda.gov/business_opp_ustda/clean-energy-and-critical-minerals-desk-
study-sub-saharan-africa/
57
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Lithium
2000K
1500K
tn
a>
§ 1000K
500K
OK
2025 2030
Cobalt
2035
2025
Supply Proximity and Alliances
¦ FEOC
¦ Non FTA (Non MSP)
¦ MSP Partner
¦ FTA
¦ Domestic
2030
2035
U S Demand
- ANL-High
— ANL-Low
CO
a>
CO
I
c
C
o
4M
3M
2M
1M
0M
Graphite
2025 2030
Nickel
2035
2025
2030
2035
Figure 1-6 Potential upstream mined critical materials supply, tonnes/year, grouped by location of mine
production
Relatedly, EPA notes that the IRA, the BIL, and ongoing activity on the part of Executive
Branch agencies are actively addressing the need for further development of the domestic supply
chain to supply growing demand for critical minerals. The provisions of the IRA and BIL were
in fact developed with the intent of growing the domestic supply chain for critical minerals and
related products and to achieve mineral security as the industry pursues clean energy technology.
Accordingly, EPA expects that the BIL and IRA will prove instrumental in meeting incremental
needs of the supply chain under the final standards, and that the ongoing efforts to build and
strengthen partnerships with friendly countries are in process to fill any supply gaps that cannot
be met domestically.
1.5.1.3 Additional Information on Critical Mineral Supply Chain Development
This section provides additional detailed evidence of recent developments in the growth of the
critical mineral supply chain, and other specific topics relevant to this topic. Citations for all of
the examples listed in this section may be found in a Memo to the Docket titled "DOE
Communication to EPA Regarding Critical Mineral Projects." We then go on to discuss further
developments and analysis since proposal (and see preamble section II.D.2.C ii and RTC section
17.2 for additional information.)
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A number of additional U.S. government efforts are underway to accelerate lithium and
critical minerals production:
• In February 2023, President Biden signed a presidential waiver of some statutory
requirements (Waiver) authorizing the use of the Defense Production Act (DP A) to
allow the Department of Defense (DoD) to more aggressively build the resiliency of
America's defense industrial base and secure its supply chains including for critical
minerals and energy storage. Since many of the investments needed in areas like
mining and processing of critical minerals can be very costly and take several years,
the Waiver permits the DoD to leverage DPA Title III incentives against critical
vulnerabilities, and removes the statutory spending limitation for aggregate action
against a single shortfall exceeding $50 million. This in turn allows the DoD to make
more substantial, longer-term investments.170
• In December 2022, the Blue Ribbon Commission on Lithium Extraction in California
issued a report detailing actions to support the further develop geothermal power with
the potential co-benefit lithium recovery from existing and new geothermal facilities
in the Salton Sea geothermal resource area. The three owners developing projects in
California may produce 600 kt/y LCE from geothermal brines around 2030.171
• In June 2022, the United States formed the Minerals Security Partnership (MSP),172
whose goal is to ensure that critical minerals are produced, processed, and recycled in
a manner that supports the ability of countries to realize the full economic
development benefit of their geological endowments. The MSP will help catalyze
investment from governments and the private sector for strategic opportunities —
across the full value chain —that adhere to the highest environmental, social, and
governance standards.173 In November 2023, the United States announced a similar
further initiative, the Minerals Investment Network for Vital Energy Security and
Transition (MINVEST), a new public private partnership with the nonprofit SAFE's
Center for Critical Minerals Strategy. The MINVEST Partnership will promote public-
private dialogue and spur investment in strategic mining, processing, and recycling
170 U.S. Department of Defense. "President Biden Signs Presidential Waiver of Statutory Requirements for Supply
Chain Resilience". February 28, 2023. Available online:
https://www.defense.gov/News/Releases/Release/Article/3312486/president-biden-signs-presidential-waiver-of-
statutory-requirements-for-supply/.
171 "Report of the Blue Ribbon Commission on Lithium Extraction in California". Available online:
https://efiling.energy.ca.gov/GetDocument.aspx?tn=247861. See also the extended discussion and analysis of
domestic lithium availability in the report of Argonne National Laboratory discussed in detail in preamble section
II.D.2.c.ii and TRC section 17.2.
172 MSP partners include Australia, Canada, Finland, France, Germany, Japan, the Republic of Korea, Sweden, the
United Kingdom, the United States, and the European Commission.
173 Stark, Vicky. "Italy Joins US-Led Mineral Security Partnership for Ethical Mining". February 6, 2023. Available
online: https://www.voanews.eom/a/italy-joins-us-led-mineral-security-partnership-for-ethical-
mining/6950081 .html.
59
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opportunities that adhere to high environmental, social, and governance (ESG)
standards.174
Preamble II.D.l.ii mentioned $3.4 billion in DOE Loan Program projects that were recently
awarded to aid in the extraction, processing and recycling of lithium and other critical minerals
to support continued market growth. Details on these projects are provided below.
• A $50M BIL grant to Lilac plans to build out domestic manufacturing capacity for the
company's patented ion-exchange technology to increase production of lithium from
brine resources with minimal environmental impact and streamlined project
development timelines and develop domestic lithium projects.175
• A $141,7M BIL grant to Piedmont Lithium plans to accelerate the construction of the
Tennessee Lithium project in McMinn County as a world-class lithium hydroxide
operation, which is expected to more than double the domestic production of battery-
grade lithium hydroxide. The project is being designed to produce lithium hydroxide
from spodumene concentrate using the innovative Metso:Outotec process flow sheet,
enabling lower emissions and carbon intensity as well as improved capital and
operating costs relative to incumbent operations.176
• A $150M BIL grant to Albemarle plans to support a portion of the cost to construct a
new, commercial-scale U.S.-based lithium concentrator facility at Albemarle's Kings
Mountain North Carolina location. Albemarle's "mega-flex" conversion facility would
be capable of accommodating multiple feedstocks, including spodumene from the
proposed reopening of the company's hard rock mine in Kings Mountain; its existing
lithium brine resources in Silver Peak, Nevada, and other global resources; as well as
potential recycled lithium materials from existing batteries. The facility is expected to
eventually produce up to 100,000 metric tons of battery-grade lithium per year to
support domestic manufacturing of up to 1.6 million EVs per year.177
• A $700 million DOE loan to Ioneer Rhyolite Ridge LLC plans to help develop
domestic processing capabilities of lithium carbonate for nearly 400,000 EV batteries
from the Rhyolite Ridge Lithium-Boron Project in Esmeralda County, Nevada.178
174 U.S. Department of State. "MINVEST: Minerals Investment Network for Vital Energy Security and Transition".
Available online: https://www.state.gov/minvest.
175 Lilac Solutions. "Lilac Solutions Selected by U.S. Department of Energy for $50 Million Award to Unlock U.S.
Lithium Production". October 19, 2022. Available online: https://lilacsolutions.com/2022/10/lilac-solutions-
selected-by-u-s-department-of-energy-for-50-million-award-to-unlock-u-s-lithium-production/.
176 Piedmont Lithium. "Piedmont Lithium Selected for $141.7 Million Grant by United States Department of Energy
for Tennessee Lithium Project". October 19. 2022. Available online:
https://www.businesswire.com/news/home/2022101900568 l/en/Piedmont-Lithium-Selected-for-141,7-Million-
Grant-by-United-States-Department-of-Energy-for-Tennessee-Lithium-Project.
177 Albemarle Corporation. "Albemarle Secures DOE Grant for U.S.-Based Lithium Facility to Support Domestic
EV Supply Chain". PRNewswire. October 19, 2022. Available online: https://www.prnewswire.com/news-
releases/albemarle-secures-doe-grant-for-us-based-lithium-facility-to-support-domestic-ev-supply-chain-
301653808.html.
178 U.S. Department of Energy, Loan Programs Office. "LPO Announces Conditional Commitment to Ioneer
Rhyolite Ridge to Advance Domestic Production of Lithium and Boron, Boost U.S. Battery Supply Chain". January
13, 2023. Available online: https://www.energy.gov/lpo/articles/lpo-announces-conditional-commitment-ioneer-
rhyolite-ridge-advance-domestic-production.
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• A $2 billion DOE loan to Redwood Materials plans to construct and expand its battery
materials recycling campus in McCarran, Nevada. It would be the first U.S. facility to
support production of anode copper foil and cathode active materials in a fully closed-
loop lithium-ion battery manufacturing process by recycling end-of-life battery and
production scrap and remanufacturing that feedstock into critical materials, supporting
EV production of more than 1 million per year. Redwood Materials will use both new
and recycled feedstocks—comprised of critical materials like lithium, nickel, and
cobalt—to produce approximately 36,000 metric tons per year of ultra-thin battery-
grade copper foil for use as the anode current collector, and approximately 100,000
metric tons per year of cathode active materials.179
• A $375 million DOE loan to Li-Cycle plans to help finance a high efficiency, low-
emission resource recovery facility for batteries in Rochester, New York. The Li-
Cycle project will use hydrometallurgical recycling to efficiently recover battery-grade
lithium carbonate, cobalt sulfate, nickel sulfate, and other critical materials from
manufacturing scrap materials and used batteries to enable a circular economy.180
ANL assesses that domestic lithium production is currently limited, but the next decade could
see a surge from promising projects that are already underway, potentially satisfying domestic
demand and allowing the U.S. to become a global leading producer of lithium depending in part
on the progress of permitting and other contingencies common to any new mining operations. As
described in Preamble section II.D.2.c.ii.c, the U.S. government is actively working through
various programs to streamline U.S. mining as well as promote and pursue partnerships and
resource development opportunities in FTA countries, MSP countries, and allies. ANL also notes
that in both the near and medium term, a significant portion of domestic lithium demand can be
met by lithium in the U.S and in FTA countries, with several MSP partners likely to add
capacity. ANL identifies several potential mitigation approaches for any remaining risk,
including collaborative efforts with FTA and MSP partners to ensure mining project success in
the U.S, FTA and non-FTA countries, pursuing offtake agreements for stockpiling lithium from
U.S producers to alleviate downward price pressure that could discourage development of new
sources, and strengthening recycling in the U.S. and ally nations.
Regarding lithium, DOE finds that there are significant efforts to scale lithium supply both
domestically and also in the FTA countries. The majority of early stage and exploration projects
are in Australia, Canada, and the U.S. DOE assesses that the U.S. is well positioned in securing
lithium materials domestically, particularly if all projects underway (particularly later stage
projects) are successful. Global lithium mining supply is anticipated to more than double in the
next five years. In fact, if lithium demand does not match this supply, it could lead to oversupply
and create downward price pressure. Several U.S. projects are in the construction stage,
179 U.S. Department of Energy, Loan Programs Office. "LPO Offers Conditional Commitment to Redwood
Materials to Produce Critical Electric Vehicle Battery Components From Recycled Materials". February 9, 2023.
Available online: https://www.energy.gov/lpo/articles/lpo-offers-conditional-commitment-redwood-materials-
produce-critical-electric-vehicle.
180 U.S. Department of Energy, Loan Programs Office. "LPO Announces a Conditional Commitment for Loan to Li-
Cycle's U.S. Battery Resource Recovery Facility to Recover Critical Electric Vehicle Battery Materials". February
27, 2023. Available online: https://www.energy.gov/lpo/articles/lpo-announces-conditional-commitment-loan-li-
cycles-us-battery-resource-recovery.
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including at Fort Cady, Thacker Pass, Rhyolite Ridge, and King Mountains, with others
undergoing prefeasibility or feasibility studies, e.g., Great Salt Lake. Through such projects the
U.S. lithium supply is expected to more than double by 2025, and the U.S. is poised to become a
global key player in lithium industry if all ongoing projects come to fruition and can overtake
current key players such as Australia, Argentina and Chile. The majority of U.S. lithium
production is likely to come from brines, which are relatively cheaper to produce compared to
lithium from spodumene deposits. Both in the near term and the medium term a significant
portion of lithium will be available domestically and in FTA countries, likely enough to meet
domestic demand. Several FTA and MSP partners, such as Canada and Germany, are likely to
add capacity over the medium term, further strengthening U.S. lithium availability. DOE
assesses that the U.S. largely has sufficient lithium supply to meet domestic demand of battery
manufacturers under a number of reasonable demand scenarios. Only in the near term will the
U.S. likely depend on imported lithium, and sufficient additional capacity exists in FTA
countries to meet this import demand. Specifically, international trade will continue to be
important in the next three years as the U.S. scales domestic production; from 2025, if all U.S.
projects currently underway commence production and scale as expected, the U.S. may have
sufficient lithium to meet domestic manufacturer demand with an opportunity to be a net
exporter of lithium. See generally, ANL at pp. 33-36.
Although currently there is no alternative to lithium in manufacturing on-road BEV batteries,
several alternatives are under development that may provide an alternative, either in on-road
batteries, or in non-road applications whose use of these alternatives would reduce competition
for lithium in on-road applications. Citations for these examples may be found in a memo to the
docket.181
• BNEF estimates that sodium-ion batteries are scaling for use in applications that do
not require the high-performance capabilities of large EV batteries, including
stationary energy storage and 2- and 3-wheeled vehicles. Substitution from lithium to
alternative chemistries could alleviate price pressures as soon as 2026.182
• A new PNNL molten salt battery design, which uses Earth-abundant and low-cost
materials, has demonstrated superior charge/discharge capabilities at lower operating
temperatures while maintaining high energy storage capacity compared to
conventional sodium batteries.183
• NASA's Solid-state Architecture Batteries for Enhanced Rechargeability and Safety
(SABERS) research for aerospace applications will likely have spin-off benefits for
the automotive sector. As lithium-ion based liquid electrolytes are not suitable for
aircraft, the development of a scalable, solid state battery that is safer, more energy
181 Safoutin, Michael. Memorandum to docket EPA-HQOAR-2022-0985. "DOE Communication to EPA
Regarding Critical Mineral Projects". April 2023.
182 BloombergNEF. "Top 10 Energy Storage Trends in 2023". January 11, 2023. Available online:
https://about.bnef.com/blog/top-10-energy-storage-trends-in-2023/.
183 Hede, Karyn. "New Sodium, Aluminum Battery Aims to Integrate Renewables for Grid Resiliency". February 7,
2023. Pacific Northwest National Laboratory. Available online: https://www.pnnl.gov/news-media/new-sodium-
aluminum-battery-aims-integrate-renewables-grid-
resiliency?utm_campaign=News%20Releases&utm_medium=email&_hsmi=244877345&_hsenc=p2ANqtz-
9mA8d2QBItlO8ZzPiHk_CqrKoJr8IjLhfsBtyTJmoYJmXQbQ7tGvdsdVcg2W4j7c5_LLSmXmd0YZPyV4vMOQ
X5VcTydQ&utm_content=244877345&utm_source=hs_email.
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dense, and capable of faster charging has high commercialization potential in on-road
vehicles applications, and can reduce lithium demand.184'185
Finally, a large amount of research and development is taking place to increase circularity and
effective use of lithium and other critical minerals. Beyond commercial technologies, continued
research and development with industry and academia through the United States Advanced
Battery Consortium (USABC), Critical Minerals Institute (CMI), and ARPA-E will expand the
recycling and recovery of lithium to help expand the use of unconventional supplies to help pace
the growing demand for EVs:
• A $2M USABC grant to American Battery Technology Company (ABTC) in Fernley,
Nevada will help develop a recycling development program to demonstrate a scaled,
fully-domestic, integrated processing cycle for the universal recycling of large format
Li-ion batteries in coordination with partners in the battery supply chain.186
• The CMI's EC-LEACH project successfully demonstrated a lOx scale-up of
electrochemical leaching for lithium-ion batteries black mass, e-waste comprised of
crushed and shredded battery cells, with a capacity up to 500 g/day, achieving over
96% leaching efficiency for all metals. The scale up demonstrated leaching under
higher voltage while maintaining lower currents and used conventional power
electronics.187'188
• $39 million in ARPA-E funding for the Mining Innovations for Negative Emissions
Resource Recovery (MINER) program will help develop market-ready technologies
that will increase domestic supplies of critical elements, including copper, nickel,
lithium, cobalt, rare earth elements, that are required for the clean energy transition.
The MINER program will fund research that increases the mineral yield while
decreasing the required energy, and subsequent emissions, to mine and extract energy-
relevant minerals.189
EPA has carefully considered the substantive and detailed comments offered by the various
commenters regarding battery manufacturing. In light of additional information that EPA has
collected through continued research and the public comments, the evidence continues to support
our previous assessment that domestic and global battery manufacturing is well positioned to
deliver sufficient battery production to allow manufacturers to meet the standards.
184 Gould, John. "NASA Seeks to Create a Better Battery with SABERS". NASA. April 7, 2021. Available online:
https://www.nasa.gov/feature/nasa-seeks-to-create-a-better-battery-with-sabers.
185 Clancy, Ryan. "NASA battery for electric aircraft ready to take-off'. February 19, 2023. Available online:
https://electronics360.globalspec.com/article/19317/nasa-battery-for-electric-aircraft-ready-to-take-off.
186 Advanced Battery Technology Company. "US Advanced Battery Consortium". Available online:
https ://americanbattery technology. com/projects/usabc-proj ect/.
187 AMES National Laboratory. "CMI Project 2.1.11: Lithium, cobalt & platinum group metals recovery from
lithium-ion batteries & e-waste". Available online: https://www.ameslab.gov/index.php/cmi/cmi-project-3111-li-co-
pgm-recovery-li-ion-batteries-and-e-waste.
188 AMES National Laboratory. "Scale-up of electrochemical leaching". March 1, 2021. Available online:
https://www.ameslab.gov/index.php/cmi/research-highlights/scale-up-of-electrochemical-leaching-cell.
189 ARPA-E. "MINER—Miner Innovations for Negative Emissions Resource Recovery". Available online:
https://arpa-e.energy.gov/sites/default/files/documents/files/MINER_Final%20Project%20Descriptions.pdf.
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Based on announced investments in battery cells production, companies have announced over
1,300 GWh/year in battery production in North America by 2030 (Figure 1-7).
Planned Li-ion Cell Production Capacity in North America
1500
L—
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Figure 1-7 Modeled lithium-ion cell production capacity in North America from 2018 to 2035 by country
EPA finds that there is sufficient North American battery production capacity for HDVs
within the rule's timeframe, and ANL projects at least 45 GWh of announced cell production
will be dedicated to HDV BEVs by 2030 (Figure 1-8). See ANL, "Quantification of
Commercially Planned Battery Component Supply in North American Through 2035" (ANL-
24/14) (March 2024) at 23. Moreover, end use for some battery cell manufacturing facilities has
not been announced, and it is likely that this North American capacity can service HDV
applications in greater than announced amounts.
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Planned Li-ion Cell Production Capacity in North America
1500
| 1200
?
CD
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Data as of February 2024
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Figure 1-8 Modeled lithium-ion cell production capacity in North America from 2018 to 2035 by
transportation sector
The three most recent projections of capacity (from BNEF, Roland Berger, and S&P Global
in 2020-2021) that were collected by ANL at that time exceeded the corresponding projections of
demand by a significant margin in every year for which they were projected, suggesting that
global battery manufacturing capacity is responding strongly to increasing demand. The updated
ANL supports the continuation of this trend. Figure 1-9 shows projected battery cell production
in MSP countries through 2035: the sum of announced battery cell production capacity in MSP
countries (outside North America) exceeds the sum in North America, with both reaching 1,300
GWh/year by 2030.
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Planned Li-ion Cell Production Capacity in MSP Countries
1500
1200
5 900
600
300
Data as of February 2024
_ /
/
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i i Other
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Figure 1-9 Modeled MSP lithium-ion battery cell production capacity through 2035
In consideration of this updated information on battery component and cell manufacturing, it
continues to be our assessment that the industry is well positioned to support the battery and cell
demand that is projected under the modeled potential compliance pathway supporting the
feasibility of the final standards, including taking into consideration uncertainties that generally
accompany forward-looking projections.
1.5.2 BEV Safety Considerations
EPA assessed potential safety issues associated with BEV technologies and FCEV
technologies, noting potential safety issues and means of securely managing those issues. EPA
has been in communication with NHTSA190 to ascertain the latest status on risks associated with;
mass of BEV and the impact of that mass on crash outcomes, BEV shock risk especially as it
pertains to mechanics and first responders, BEV and FCEV fire and explosion risk, FCEV
explosion risk in enclosed structures like tunnels.191 Updates from NHTSA are included in the
appropriate sections below. FCEV, HEV, and PHEV technologies all include use of batteries
with significant energy levels and voltages high enough to cause harm if not handled safely.
Battery safety associated with BEVs are discussed below. These same battery safety
considerations apply to FCEV, HEV, and PHEV. FCEV safety will be covered in section 1.7.4
and will focus on hydrogen as the battery aspects are covered with BEV below. The ICE safety
aspects of HEV and PHEV are aligned with current ICE technologies, and are well understood
1911 Landgraf, Michael. Memorandum to docket EPA-HQ-OAR-2022-0985. Summary of NHTSA Safety
Communications. February 14, 2024.
191 Kuppa, Shaslii. "HD safety for BEV and H2 FCV" email reply October 24, 2023.
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and managed with today's technology and its use. HEV and PHEV will not be separately
discussed as the battery aspect of safety is covered with our discussion of BEV safety while ICE
considerations do not require discourse.
BEVs receive, store, and utilize large amounts of electrical energy. The stored electrical
energy resides as chemical energy in the battery. This electrical and chemical energy must be
safely controlled during charging, while held by the battery and other high voltage components,
and when providing vehicle power. The electrical energy must be isolated from humans to
prevent shock. The electrical energy also needs isolation so that a short does not allow harmful
amounts of electricity to leak to and through other components, causing damage. Finally, the
chemical energy held in the battery must be managed so it is not allowed to generate excessive
heat that could harm surrounding components or cause a thermal event.
Both LD and HD BEVs are progressing beyond 400V systems with some LD BEVs at 800V
and Tesla considering 800V for their HD tractor.192 Systems of 400V up to 800V are clearly high
voltage and carry high voltage risk, as high voltage is considered to be 60V DC up to 1,500V
DC 193 xhe safety of a HD BEV benefits from the significant work conducted in the LD BEV
sector addressing the BEV risk factors. Risk factors related to battery capacity will generally be
greater for HD BEVs, as they often, though not always, need to be larger and do more work than
the LD BEV.
HD BEV systems must always maintain safe operation. As with any on-road vehicle, they
must be robust during temperature extremes as well as rain and snow. The systems must be
designed for reasonable levels of immersion, including immersion in salt water or brackish
water. BEV systems must be designed to be crashworthy and limit damage that compromises
safety. If the structure is compromised by a severe impact, the systems must provide first
responders with a way to safely conduct their work at an accident scene. The HD BEV systems
must be designed to ensure the safety of users, occupants, and the general public in their vicinity.
As shown in section 1.5.5, almost 180 BEV vehicle models are available in MY 2023 while over
180 are expected in MY 2024 (per literature review) suggesting that many manufactures are
meeting safety standards over a wide range of HD BEVs.
1.5.2.1 Charging Safety
Charging involves electricity flowing into the vehicle at power levels that are capable of
harming people and equipment. To ensure safety, the vehicle and charging system must:194
• Isolate individuals from the high voltage electricity that is present in the vehicle and
charger. (High voltage must not be present within 1 second of charger disconnect.);
• Establish and monitor a ground path;
192 Randall, Chris. "Tesla considers using 800-volt architecture for trucks". Electrive. Updated on November 7,
2023. https://www.electrive.com/2022/04/22/tesla-considers-using-800-volt-architecture-for-trucks/
193 Global Technical Regulation No. 20 page 20
https://unece.org/fileadmin/DAM/trans/main/wp29/wp29wgs/wp29gen/wp29registry/ECE-TRANS-180a20e.pdf
194 Part 571305 - Federal Motor Vehicle Safety Standards - Electric Powered Vehicles
https://www.govinfo.gov/content/pkg/CFR-2017-title49-vol6/xml/CFR-2017-title49-vol6-
part5 71. xml#seqnum571.305
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• Monitor the process for isolation faults and shorts;
• Exchange information;
• Indicate if the vehicle is in active drive mode; and
• Notify the operator if action is required to complete charging safely.
Complexities with the battery design and reactions occurring in the battery cells drive the
need for feedback from the battery to the charging system. This charge management is handled
within the vehicle with AC chargers or within the DC charging equipment that is external to the
vehicle. The safety of HD vehicle charging systems has benefitted from the more extensive LD
vehicle development and deployment. Some of the industry codes and standards that guide safe
deployment of BEV charging systems are:
• Society of Automotive Engineers (SAE) J-1772, conductive charging
• SAE J-2954/2, inductive charging
• SAE J-3072, grid support from the EV
• SAE J-3271, megawatt charging system (up to 1500V/3000A) requirements
Other related standards have been developed by NHTSA,195 International Electrotechnical
Commission (TEC), National Electric Code (NEC), and Underwriters Laboratories (UL). These
standards ensure safety in various ways. Using J-1772 as an example, mechanical features are
prescribed that ensure electricity is flowing only when the connecter is safely coupled and the
electricity is separated from the user. Likewise, as the connecter is disconnected after charging,
power flow is stopped before any high voltage parts are exposed to the user. Continuing with the
J-1772 example, it contains signaling features that allow communication between the vehicle and
charger to ensure charging is only taking place when safe to do so.
1.5.2.2 Battery Safety
BEV batteries receive, store, and discharge electrical power. BEV batteries require both the
proper physical design and the proper controls (or battery management system) to allow them to
safely accept and deliver power throughout the life of the vehicle. The battery design must
provide external short circuit protection, over and under charge protection, and over temperature
protection. NHTSA has a rulemaking proposal to address EV battery fire risk with planned
publication in 2024. Some of the design and controls standards that ensure BEV can accept and
deliver power robustly, without overheating or failing, are shown below.
• SAE J2464-202108, safety and abuse testing at the component level. This guide
describes a body of tests which may be used as needed for abuse testing of electric or
hybrid electric vehicle rechargeable energy storage systems (RESS) to determine the
response of such electrical energy storage and control systems to conditions or events
which are beyond their normal operating range.
195 For example, "DC and AC Charging Safety Evaluation Procedure Development, Validation, and Assessment".
Published Date : 2019-07-01 Report Number : DOT HS 812 778 Available online:
https://rosap.ntl.bts.gov/view/dot/41933
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• SAE J2929-201102, safety standard for lithium-based cells. This SAE Standard
defines a minimum set of acceptable safety criteria for a lithium-based rechargeable
battery system to be considered for use in a vehicle propulsion application as an
energy storage system connected to a high voltage power train.
• NHTSA DOT 49 CFR 571.305 EV Safety is adding battery requirements per RIN:
2127-AM43
Other related standards have been developed by IEC, International Standards Organization
(ISO) and UL.
1.5.2.3 Battery Protection from the Environment, Road Hazards, and Immersion
The BEV battery must be designed to handle external challenges. A HD BEV and its battery
will be exposed to vibration, temperature extremes, temperature cycling, water, and mechanical
impact from items such as road debris. The water may arrive as rain, snow, and/or soaking rains
that later freeze. The vehicle may drive through or be exposed to water with varying levels of salt
that will be a much better conductor of electricity and can be corrosive over time. The batteries
must hold up to impact from foreseeable types of road debris. The standards that address these
conditions are SAE J2464, safety and abuse testing, and others from IEC and ISO.
1.5.2.4 BEV Safety Regarding Crash and Maintenance
The crash test performance of today's LD electric vehicles shows that they are at least as safe
as ICE vehicles.196 This conclusion is based on a 2021 report and assessment of LDV by the
Insurance Institute for Highway Safety (IIHS). IIHS found that driver and passenger injury
claims from 2011 to 2019 were 40% lower for electric vehicles versus "identical" conventional
vehicles.197 As explained earlier in this section, we coordinated with NHTSA to assess any
potential safety concerns, including due to vehicle weight and crash safety. NHTSA has shared
that they are not aware of differences in crash outcomes between electric and non-electric
vehicles. They confirmed they are monitoring this topic closely and are conducting extensive
research on the differences between ICE and electric vehicles. Their research includes
investigating size- and weight-related compatibility implications relative to overall road safety.
Additionally, NHTSA's CAFE proposal198, issued on July 28, 2023 for all light passenger
vehicles, includes estimates of the safety impacts of EV weight. NHTSA reports that, "Change in
vehicle mass affects the prevalence of injuries and fatalities on roadways. Increases in vehicle
mass might confer additional safety to vehicle occupants while also reducing safety for
pedestrians, cyclists, and other vulnerable road users, as well as for road users with lower mass
vehicles". But this light passenger vehicle Preliminary RIA goes on to say, "Across all
alternatives, mass changes relative to the baseline result in small reductions in overall fatalities,
196 Bartlett, Jeff. "Ford and Volvo Earn Top Safety Picks as Insurance Study Shows Electric Cars Are Safe".
Consumer Reports published on April 22, 2021. https://www.consumerreports.org/car-safety/electric-cars-prove-
safe-in-iihs-crash-tests-and-insurance-claims-a2640558822/
197 Insurance Institute for Highway Safety. "With more electric vehicles comes more proof of safety". Published on
April 22, 2021. https://www.iihs.org/news/detail/with-more-electric-vehicles-comes-more-proof-of-safety
198 US Department of Transportation, National Highway Traffic Safety Administration. "Preliminary Regulatory
Impact Analysis. Corporate Average Fuel Economy Standards for Passenger Cars and Light Trucks for Model Years
2027 and Beyond and Fuel Efficiency Standards for Heavy-Duty Pickup Trucks and Vans for Model Years 2030
and Beyond. July, 2023. Available online: https://www.nhtsa.gov/sites/nhtsa.gov/files/2023-08/NHTSA-2127-
AM55-PRIA-tag.pdf
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injuries, and property damage. These results may seem counterintuitive given the agency's
previous analyses. This outcome amounts to noise around zero." Regarding HD BEV weight, it
is important to acknowledge that current HD ICE vehicles have much more weight the LD
vehicles. Even a large SUV at 6,000 lbs is dwarfed by a Class 8 loaded truck at 80,000 pounds.
Although the HD BEV Class 8 could go to 82,000 pounds, the weight ratio increase of 13.3X
(80,000 / 6,000) to 13.7X (82,000 / 6,000) should prove insignificant. The Class 8 weight
increase of 2,000 pounds is just an example for demonstration purposes, many HD BEV trucks,
and especially those where significant early adoption is expected, have little to no weight gain.
For HD BEVs to uphold battery/electrical safety during and after a crash, they are designed to
maintain high voltage isolation, prevent leakage of electrolyte and volatile gases, maintain
internal battery integrity, and withstand external fire that could come from the BEV or other
vehicle(s) involved in a crash. The internal battery integrity is important to prevent fire risk from
developing within the battery over time. Standards driving design and process for optimizing
crash and post-crash safety have been completed by IEC and ISO as well as:
• National Highway Traffic Safety Administration (NHTSA) FMVSS 305, electrolyte
spillage and electrical shock protection
• NHTSA DOT HS 812 789, post-crash stranded energy tools and procedures
• SAE J1766, crash integrity testing. This SAE Recommended Practice is applicable to
Electric, Fuel Cell and Hybrid vehicle designs that are comprised of at least one
vehicle propulsion voltage bus with a nominal operating voltage greater than 60 and
less than 1,500 VDC, or greater than 30 and less than 1,000 VAC. This Recommended
Practice addresses post-crash electrical safety, retention of electrical propulsion
components and electrolyte spillage.
• SAE J2990, first and second responder recommended practice. xEVs involved in
incidents present unique hazards associated with the high voltage system (including
the battery system). These hazards can be grouped into three categories: chemical,
electrical, and thermal. The potential consequences can vary depending on the size,
configuration, and specific battery chemistry. This RP aims to describe the potential
consequences associated with hazards from xEVs and suggest common procedures to
help protect emergency responders, tow and/or recovery, storage, repair, and salvage
personnel after an incident has occurred with an electrified vehicle.
An important aspect of crash safety is knowledge and training for first responders and those
handling crashed BEV vehicles. First responders must know how to locate and perform high
voltage disconnects. They must also know to check for high voltage sources so they can avoid or
disconnect or drain those energy sources. This is especially true if they are in contact with the
vehicle to free an occupant. NHTSA is working on providing emergency response guides for
each vehicle make and model which will be on NHTSA's website. BEV fire occurrence analysis
shows that BEVs are less likely to catch fire than vehicles powered by internal combustion
engines. Recent analysis combining car fire data from NTSB with sales data from the Bureau of
Transportation Statistics shows gas vehicle fires occur in over 1,500 vehicles per 100,000 sales
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while BEV fires are just over 25 fires per 100,000 sales.199 Although BEVs can behave
differently in fires from ICE vehicles, emergency responders have been gaining experience in
BEV fire response and there are protocols and guidance at the federal and private levels in
support of first responders. Real world operation and testing has shown that large amounts of
water (2,600 gallons for a 600 lbs. li-ion battery) are needed for BEV firefighting to cool the
batteries and eliminate the risk of fire.200 There has been considerable advancement in BEV
firefighting, and additional work in this area is underway. For example, BEST (Battery
Extinguishing System Technology) can pierce the battery case and apply water directly to the
battery, extinguishing the fire with as little as 500 gallons in an hour201. Safe storage of crashed
vehicles is critical as internal battery failure reactions may occur days after the crash and
reignite. Recommendations for safe storage of damaged BEV include: ID and label the damaged
vehicles, park the damaged vehicles in a safe zone (generally 50 feet away from buildings and
combustible materials), create an EV fire response plan, conduct regular inspections.202
Protocols and guidance exist to mitigate shock risk to mechanics during maintenance and
repair. Performing standard maintenance on BEVs leads to new or increased risk compared to
ICE vehicles and requires corresponding safety training due to the following:203
• the presence of high voltage components and cabling capable of delivering a fatal
electric shock;
• the storage of electrical energy with the potential to cause explosion or fire;
• components that may retain a dangerous voltage even when a vehicle is switched off;
• electric motors or the vehicle itself that may move unexpectedly due to magnetic
forces within the motors;
• manual handling risks associated with battery replacement;
• the potential for the release of explosive gases and harmful liquids if batteries are
damaged or incorrectly modified;
• the possibility of people being unaware of vehicles being in motion because when they
are electrically driven they are silent in operation;
199 Wright, Justin. "Gas vs. Electric Car Fires [2024 Findings]". December 19, 2023. Available online:
https://www.autoinsuranceez.com/gas-vs-electric-car-fires/
200 Moore, Ron. "University of Extrication: Electric Vehicle Fire Suppression" Firehouse. Published on March 14,
2022. Available online: https://www.firehouse.eom/operations-training/article/21255066/university-of-extrication-
electric-vehicle-fire-suppression
201 Margaretten, Emily. " New firefighting device helps Mountain View extinguish electric vehicle fires faster, using
less water". Palo Alto online. January 4, 2024. Available online:
https://www.paloaltoonline.eom/news/2024/01/04/new-firefighting-device-helps-mountain-view-extinguish-electric-
vehicle-fires-faster-using-less-water/
202 O'Shaughnessy, Micah. "EV Hazards: Tips to Reduce Fire and Storage Hazards in Your Dealership". KPA. July
13, 2022. Available online: https://kpa.io/blog/ev-hazards-tips-to-reduce-fire-and-storage-hazards-in-your-
dealership/
203 Health and Safety Executive - Electric and Hybrid Vehicles https://www.hse.gov.uk/mvr/topics/electric-
hybrid.htm Accessed February 2, 2023.
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• the potential for the electrical systems on the vehicle to affect medical devices such as
pacemakers.
While the systems have safety guards and checks, personnel must be able to verify that those
systems are operating correctly. NHTSA confirmed that the current FMVSS No. 305 specifies
protection systems to mitigate shock risk to mechanics and emergency responders. Maintenance
personnel will need appropriate personal protective equipment (PPE), testing equipment, and
manufacturer-specified service procedures on use. Review of literature by safety systems
providers204, state technology offices205, and NHTSA206 show consistent messaging on the need
for proper equipment, PPE, training, disconnection or lock out and isolation of high energy
systems.
In sum, the public and private sectors have been working diligently to address BEV safety
considerations. While current standards are appropriate, optimization efforts will continue as the
HD BEV industry matures. Heavy-duty BEVs can be and are designed and operated safely.
1.5.3 BEV System Integration
While both BEV and ICE vehicle technologies have some components in common, as
described in Chapter 1 and 2, there are also many components that differ between the two
vehicle types. The arrangement of a vehicle's components can have a significant impact on its
energy efficiency, volumetric and gravimetric payload capacity, and cost. Currently, some BEVs
are designed very similarly to comparable ICE vehicles, while other BEVs are designed more
from a "ground-up" approach, allowing them to better take advantage of the characteristics
unique to BEVs, such as the flexibility of placement in battery mass and the modularity of
battery pack sizes.
HD vehicles fill a diverse set of requirements, necessitating different approaches to BEV
component integration. This chapter gives a few examples of BEV systems and integration to
illustrate the current state of HD BEV design and provides a projection of potential future
evolution of the technology that we have assessed and determined is feasible during the time
frame considered in this rulemaking.
1.5.3.1 Integration into Existing ICE Vehicle Design
Some HD vehicle outfitters take existing ICE vehicles and upgrade componentry;207 this
allows the vehicle owner to update a vehicle without purchasing an entirely new vehicle, saving
cost. This has traditionally been done while maintaining the type of powertrain (e.g.,
compression ignition ICE), but may also be done to convert ICE vehicles to BEVs as Complete
204 "Electric And Hybrid Vehicle Risks". EINTAC. Accessed February 8, 2024. Available online:
https://eintac.com/risks-working-electric-hybrid-vehicles/
205 "High Voltage Safety with Hybrids and Electric Vehicles". Massachusetts Office of Technical Assistance.
Accesssed on February 8, 2024. Available online:
https://www.mass.gov/files/high_voltage_safety_with_hybrids_and_electric_vehicles.pdf
206 "Electric and Hybrid Vehicles". US Department of Transportation. National Highway Traffic Administration.
Accessed February 8, 2024. Available online: https://www.nhtsa.gov/vehicle-safety/electric-and-hybrid-
vehicles#:~:text=Exposed%20electrical%20components%2C%20wires%2C%20and,or%20flammable%20gases%2
0and%20fire.
207 This concept of replacement of ICE with BEV components can be applied to new vehicles without a complete
vehicle re-design. Our standards would not apply to in-use products, so do not require repowering.
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Coach Works does with buses, as shown in Figure 1-10. Additional outfitters taking this
approach include Unique Electric Solutions (UES),208 Revo Powertrains,209 and Blue Bird.'10
Complete Coach Works repowers buses by stripping the chassis down to the frame; removing
all interior and exterior components; removing the diesel engine; installing a battery electric
powertrain; installing light-weight flooring, seats, and windows and energy-efficient lighting;
and conducting a final inspection. In the example shown in Figure 1-10, the bus was upgraded
beyond a powertrain replacement by adding in lightweight and energy-efficient components to
reduce the energy demands on the battery. Such an approach may have certain advantages and
disadvantages. For example, the cost of such a bus conversion would likely be lower than the
cost of purchasing a new battery electric bus, but the placement and size of the powertrain
components would be constrained to the space that the diesel engine originally occupied. This
latter consideration may be limiting for some of the components and specifications, e.g., the
capacity of the battery packs.
208 UES. "EV Conversions for Commercial Vehicles - UES". https://www.uesmfg.com/. Accessed on October 5,
2022.
209 Revo Powertrains. "Revo Electric Powertrains". https://www.revopowertrains.com/. Accessed on October 5,
2022.
2I" Barclay, J. "Blue Bird to Offer Electric Repower Option for Gasoline- and Propane-Powered School Buses".
Business Wire. Published on August 3,2022. https://www.businesswire.eom/news/home/20220803005655/en/Blue-
Bird-to-Offer-Electric-Repower-Option-for-Gasoline~and-Propane-Powered-School-Buses/. Accessed on October
5, 2022.
211 Complete Coach Works. "Zero Emission Propulsion System", https://zepsdrive.com/. Accessed on September 18,
2022.
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1.5.3.2 HD Vehicles with ICE and BEV Components
Spartan Emergency Response offers a fire truck called Vector, which the company purports to
be an electric fire truck.212 It is capable of all-electric operation for both driving and pumping
water using its sizeable 327 kWh battery. The vehicle also comes with a range-extending option
where the ICE that can recharge the battery at low charge; in this version, the vehicle functions
similar to that of a series hybrid213. While this fire truck does not benefit from a fully electric
vehicle's omission of an engine and associated components, the Vector fire truck was designed
to take advantage of the battery's mass by placing them such that the truck has a lower center of
gravity, which provides better handling and maneuverability, as shown in Figure 1-11. This
design decision demonstrates one way that an electric vehicle could provide an advantage over a
comparable ICE vehicle. Additional manufacturers of HD vehicles that include ICE components
but may also operate in all-electric modes include Kenworth,214 US Hybrid,215 and Pierce
Manufacturing.216
Low Center of Gravity Battery Placement
Provides better handling, less sway while cornering and is farther from cab occupants in a crash
212 Spartan Fire, LLC. "Vector - Spartan Emergency Response", https://spartaner.com/prodncts/vector/. Accessed on
September 18, 2022.
213 In a series hybrid, the engine is used to charge the battery which in turn powers the e-motor. The engine does not
directly drive the powertrain using a transmission.
214 Kenworth. "Kenworth Delivers Two Range-Extended Electric Prototype Trucks for Commercial Service".
Published on February 17, 2021. https://www.kenworth.com/about-us/news/kenworth-delivers-two-range-extended-
electric-prototype-trucks-for-commercial-service/. Accessed on October 5, 2022.
215 US Hybrid. "Long Haul & Drayage - US Hybrid", https://www.ushybrid.com/applications/long-haul-drayage/.
Accessed on October 5, 2022.
216 Pierce Manufacturing. Inc. "Vollerra™ Electric Fire Truck | Pierce Mfg". https://www.piercemfg.com/electric-
fire-trucks/pierce-volterra. Accessed on January 8, 2023.
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Figure 1-11 Spartan Emergency Response places the battery packs of their Vector fire truck strategically to
improve handling
1.5.3.3 Integration into Vehicle Ladder Frame
Bollinger Motors approaches BEV design by constraining the battery packs and other BEV
powertrain components to the ladder frame of their vehicles,217 like trends in LD BEV design.
This provides three advantages over an ICE vehicle, as illustrated in Figure 1-12. First, as shown
in Figure l-12(a), the relatively small size of the e-motor allows Bollinger Motors to bring the
cab forward, which improves visibility and increases cargo space. Second, as depicted in Figure
l-12(b), this design provides a literal platform upon which to tailor the BEV to each customer's
needs. Third, as shown in Figure l-12(c), the battery capacity can be easily adjusted with the
same general layout to accommodate different energy demands for a range of vehicles across
duty cycles and gross weight vehicle rating (GVWR), which allows Bollinger Motors to reduce
some of the engineering costs. Other manufacturers placing battery packs in the ladder frame of
HD BEVs include Volvo,218 Peterbilt,219 Navistar,220 and Xos.221
217 Bollinger Motors Inc. "TRUCKS - BOLLINGER MOTORS", https://bollingermotors.com/trucks/. Accessed on
September 18, 2022.
Bollinger Motors Inc. "CLASS 3-6 FLEET-READY ELECTRIC TRUCKS - BOLLINGER MOTORS".
https://bollingermotors.com/class-3-through-6-electric-truck-platforms/. Accessed on September 18, 2022.
218 Howard, B. "Volvo Plans Big Electric Trucks for Local, Regional Hauls". Extreme Tech. Published on
September 24, 2019. https://www.extremetech.com/extreme/298830-volvo-plans-big-electric-trucks-for-local-
regional-hauls. Accessed on October 5, 2022.
219 Peterbilt. "220EV'. https://www.peterbilt.com/download/file/7696. Accessed on October 5, 2022.
220 Green Car Congress. "Navistar launches new medium-duty electric International eMV Series; in production and
available to order". Green Car Congress. Published on September 2, 2021.
https://www.greencarcongress.com/2021/09/20210902-emv.html. Accessed on October 5, 2022.
221 Xos. "Powertrain - Powered by Xos helps to electrify vehicles and equipment".
https://xostrucks.com/powertrain/. Accessed on October 5, 2022.
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(a)
(b)
(c)
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B jp ^V7
CLASS 3
GVWR 14,000
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Figure 1-12 Bollinger Motors' commercial electric trucks, (a) Cab-forward design increases cargo space over
conventional cabs, (b) Platform enables the tracks to be upfit to fill a wide variety of purposes, (c) Battery
packs in the ladder frame are flexible enough
1.5.4 BEV Ancillary Systems
1.5.4.1 Heating, Ventilation, and Air Conditioning (HVAC)
The use of energy to heat or cool the cabin of the vehicle can require energy from a power
source, typically the battery itself. As a result of the large interior cabins of some heavy-duty
vehicles, such as a school bus, this may require a heat pump. Cabin heat can be provided by
using a positive temperature coefficient (PTC) electric resistance heater. PTC electric heaters
convert electrical energy into thermal energy. PTC energy conversion efficiency from electrical
to thermal energy is 100 percent.
Heat pumps provide both heat and air conditioning (A/C) by utilizing a thermodynamic cycle
to move thermal energy, rather than directly converting energy from another form. Heat pump
system hardware and operation is fundamentally the same as a standard air conditioner. The
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addition of a reversing valve can change the direction in which thermal energy is moved. Heat
pump heating efficiency is very high, normally exceeding 100 percent because they can move
more thermal energy than the amount of electrical energy that is consumed to move it. Efficiency
is dependent on ambient air temperature. Heat pump efficiency is described by the coefficient of
performance (COP), a ratio of the useful thermal energy (heat) provided by the system, to the
electrical energy that it consumed. Modern heat pumps achieve a COP ranging from 1.0, equal to
100 percent efficiency in very low ambient temperatures, to 4.0 or higher - 400 percent or higher
efficiency, at moderate temperatures. In other sectors, heat pumps are currently and increasingly
in use for water heating222, industrial process heat223, LD electric vehicles224, and international
market heavy-duty vehicles225. Rapid development of heat pumps in established and rising
markets indicate both the appropriateness and heightened interest in adopting the technology.
Heat pump manufacturers are developing and commercializing residential systems that operate
with a minimum efficiency of 210 percent-240 percent at 5°F, and operating as low as -15°F (at
100 percent efficiency).226 With a growing HD BEV market, we expect HVAC manufacturers
will develop and expand their vehicle heat pump products.
Vehicles with a particularly high heating load or extended idle requirement may use auxiliary
cabin heat systems. Fuel operated heaters (FOH), also known as direct fired heaters (DFH), are
small standalone air or coolant heaters that combust diesel or gasoline solely as the source of
heat. Emissions from combustion are directly exhausted outside the vehicle.
FOHs may be used in ZEV applications operating in extreme low temperatures, or where a
reduction in driving range is unacceptable. Considering the applications most appropriate for
electrification in MYs 2027 through 2032, the sustainability goals of both fleets and OEMs
purchasing electric vehicles, and the high efficiency of heat pumps and sensitivities of FOH
emissions, we believe that it is unlikely that FOH will be the primary solution for cabin heat.
1.5.4.2 Electric Power Take Off
Vehicles equipped today with an electric power take off (ePTO) are a small portion of the
overall heavy-duty industry and are typically equipped on utility vehicles.227 The ePTO's are
powered by the batteries for a period of time, with the vehicle engine off, until the battery charge
is depleted to the minimum allowable level. The vehicle's ICE then restarts to run the ePTO,
charge the ePTO battery pack, or both. Some systems also have a plug-in option to recharge the
222 U.S. International Trade Commission. "Residential Heat Pump (Hybrid) Water Heater Market, Production, and
Trade". Executive Briefings on Trade, February 2022.
https://www.usitc.gov/publications/332/executive_briefings/ebot_residential_heat_pump_hybrid_water_heaters.pdf.
Accessed January 24, 2023.
223 Hockenos, P. "In Europe's Clean Energy Transition, Industry Turns to Heat Pumps". Yale Environment 360.
Published January 19, 2023. https://e360.yale.edu/features/europe-industrial-heat-pumps. Accessed January 24,
2023.
224 Osaka, S. "Why you might want a heat pump in your electric car". Washington Post. Published on January 7,
2023. https://www.washingtonpost.com/climate-solutions/2023/01/07/electric-vehicles-cold-winter-range/.
Accessed January 24, 2023.
225 Garry, M. "C02 Heat Pumps Found to Outperform Electric Heaters in Electric Buses". R744. (ATMOsphere).
Published January 25, 2022. https://r744.com/co2-heat-pumps-found-to-outperform-electric-heaters-in-electric-
buses/. Accessed January 24, 2023.
226 U.S. Department of Energy. See www.energy.gov/sites/default/files/2022-02/bto-cchp-fact-sheet-021822.pdf
227 PTO units are auxiliary power units used to power other work required by the HDV; these work units include
lifting buckets in bucket trucks, lifting garbage cans or mixing cement.
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batteries (plug-in hybrid). Three manufacturers offer these systems on a range of vocational
vehicles. These vehicles are summarized in Table 1-22. Two all-electric vehicles with ePTOs
are also listed - one for utility and one for refuse trucks.
Table 1-22 Current Electronic Power Take Off Market Offerings
Make
Model
Vehicle Type
Altec Industries
JEMS LE - plug-in/hybrid228
Utility, Digger Derricks, Service
Body Trucks
Altec Industries
JEMS SE - plug-in/hybrid228
Utility, Digger Derricks, Service
Body Trucks
Altec Industries
All Electric228
Utility
Odyne Systems, LLC
ePTO- plug-in/hybrid229
Utility, Compressors, Dump
Trucks, Septic Trucks, etc.
Mack
LR Electric230
Refuse Trucks
1.5.5 BEV Market
Since 2012, manufacturers have developed a number of prototype and demonstration HD
BEV projects establishing technological feasibility and durability of BEV technology for specific
applications used for specific services.231 In 2019, approximately 60 makes and models of HD
BEVs were available for purchase, with additional product lines in prototype or other early
development stages.232'233'234 This market has been growing since MY 2018 and is projected to
reach about 180 models of heavy-duty battery electric trucks by MY 2024 (see Section 1.5 in this
chapter).235
Current production volumes of HD BEVs originally started increasing in the transit bus
market, where electric bus sales grew from 300 to 650 in the United States between 2018 to
228 Altec. "JEMS Electrifying your MD/HD Fleet". Available here https://www.altec.com/green-fleet-2/ Accessed
on 3/13/2023.
229 Odyne. "System Overview". Available here: https://www.odyne.com/system-overview/. Accessed on 1/26/2023.
230 https ://www. macktrucks. com/trucks/lr-electric/
231 NACFE (2019) "Guidance Report: Viable Class 7/8 Electric, Hybrid and Alternative Fuel Tractors", available
online at: https.V/nacfe. org/clownloacls/viable-class- 7-8-alternative-vehicles/.
232 Nadel, S. and Junga, E. (2020). "Electrifying Trucks: From Delivery Vans to Buses to 18-Wheelers." American
Council for an Energy-Efficient Economy White Paper, available at: https://aceee.org/white-paper/electrifying-
trucks-delivery-vans-buses-18.
233 The composition of all-electric truck models was: 36 buses, 10 vocational trucks, 9 step vans, 3 tractors, 2 street
sweepers, and 1 refuse truck (Nadel and Junga (2020) citing AFDC (Alternative Fuels Data Center). 2018. "Average
Annual Vehicle Miles Traveled by Major Vehicle Categories." www.afdc.energy.gov/data/widgets/10309.
234 Note that there are varying estimates of BEV and FCEV models in the market; NACFE (2019) "Guidance
Report: Viable Class 7/8 Electric, Hybrid and Alternative Fuel Tractors", available at:
https://nacfe.org/downloads/viable-class-7-8-alternative-vehicles/. (NACFE 2019) provided slightly lower estimates
than those included here from Nadel and Junga 2020. A recent NREL study suggests that there may be more models
available, but it is unclear how many are no longer on the market since the inventory includes vehicles introduced
and used in commerce starting in 2012 (Smith et al. 2019).
235 Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. "Heavy-Duty ZEV Models Available in the US
throughMY2024." October 2023.
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2019,236-237 In 2020, the market continued to expand beyond transit, with approximately 900 HD
BEVs sold in the United States and Canada combined, consisting of transit buses (54 percent),
school buses (33 percent), and straight trucks (13 percent).238 By 2021, M.J. Bradley's analysis
of the HD BEV market found that 30 manufacturers had at least one BEV model for sale and an
additional nine companies had made announcements to begin BEV production by 2025.239 In
April 2022, the Environmental Defense Fund (EDF) projected deployments and major orders of
electric trucks and buses in the United States to rise to 54,000 by 2025 based on an analysis of
formal statements and announcements by auto manufacturers, as well as analysis of the
automotive press and data from financial and market analysis firms that regularly cover the auto
industry.240 Given the dynamic nature of the BEV market, the number and types of vehicles
available are increasing fairly rapidly.241
EPA conducted an analysis of manufacturer-supplied end-of-year production reports provided
to us as a requirement of the process to certify HD vehicles to our GHG emission standards.242
Based on the end-of-year production reports for MY 2019, manufacturers produced
approximately 350 certified HD BEVs. This is out of nearly 615,000 HD diesel ICE vehicles
produced in MY 2019 and represents approximately 0.06 percent of the HD vehicles market. In
MY 2020, 380 HD BEVs were certified, an increase of 30 BEVs from 2019. The BEVs were
certified in a variety of the Phase 1 vehicle subcategories, including light, medium, and heavy
heavy-duty vocational vehicles and vocational tractors. Out of the 380 HD BEVs certified in MY
2020, a total of 177 unique makes and models were available for purchase by 52 manufacturers
in Classes 3-8. In MY 2021, EPA certified 1,163 heavy-duty BEVs, representing 0.2 percent of
the HD vehicles. We note that these HD BEV certifications preceded implementation of
incentives in the 2022 IRA, which we expect to increase adoption (and certification) of BEV and
FCEV technology in the heavy-duty sector.
Based on current trends, manufacturer announcements, the 2021 BIL and 2022 IRA, and
state-level actions, electrification of the HD market is expected to substantially increase over the
next decade from current levels. The projected rate of growth in electrification of the HD vehicle
sector currently varies widely. After passage of the IRA, EDF's September 2022 report update
projected deployments and major orders of electric trucks and buses to rise to 166,000 by the end
236 Tigue, K. (2019) "U.S. Electric Bus Demand Outpaces Production as Cities Add to Their Fleets" Inside Climate
News, November 14. https://insideclimatenews.org/news/14112019/electric-bus-cost-savings-health-fuel-charging.
237 Note that ICCT (2020) estimates 440 electric buses were sold in the U.S. and Canada in 2019, with 10 of those
products being FCEV pilots. The difference in estimates of number of electric buses available in the U.S. may lie in
different sources looking at production vs. sales of units.
238 International Council on Clean Transportation. "Fact Sheet: Zero-Emission Bus and Truck Market in the United
States and Canada: A 2020 Update." Pages 3-4. May 2021.
239 M.J. Bradley and Associates (2021) "Medium- and Heavy-Duty Vehicles: Market Structure, Environmental
Impact, and EV Readiness." Page 21. July 2021.
240 Environmental Defense Fund. "Electric Vehicle Market Update: Manufacturer Commitments and Public Policy
Initiatives Supporting Electric Mobility in the U.S. and Worldwide". April 2022. Available online:
https://blogs.edf.org/climate41 l/files/2022/04/electric_vehicle_market_report_v6_april2022.pdf.
241 Union of Concerned Scientists (2019) "Ready for Work: Now Is the Time for Heavy-Duty Electric Vehicles,"
available at www.ucsusa.org/resources/ready-work.
242 Memo to Docket. Heavy-Duty Greenhouse Gas Emissions Certification Data. March 2023. Docket EPA-HQ-
OAR-2022-0985.
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of 2022.243 ERM updated an analysis for EDF that projected five scenarios that span a range of
between 13 and 48 percent Class 4-8 ZEV sales in 2029, with an average of 29 percent.244 The
International Council for Clean Transportation (ICCT) and Energy Innovation conducted an
analysis of the impact of the IRA on electric vehicle uptake, projecting between 39 and 48
percent Class 4-8 ZEV sales in 2030 across three scenarios and between 47 and 56 percent in
203 5.245
One of the most important factors influencing the extent to which BEVs are available for
purchase and market entry is the cost of lithium-ion batteries, the single most expensive
component of a BEV. According to Bloomberg New Energy Finance, average lithium-ion
battery costs have decreased by more than 85 percent since 2010, primarily due to global
investments in battery production and ongoing improvements in battery technology.246 A number
of studies, including the Sharpe and Basma meta-study of direct manufacturing costs from a
variety of papers, show that battery pack costs are projected to continue to fall during this
decade.247'248'249 Cost reductions in battery packs for electric trucks are anticipated due to
continued improvement of cell and battery pack performance and advancements in technology
associated with energy density, materials for cells, and battery packaging and integration.250
As the cost of components has come down, manufacturers have increasingly announced their
projections for zero-emission HD vehicles, and these projections signify a rapid increase in
BEVs and FCEVs over the next decade. For example, Volvo Trucks and Scania announced a
243 Environmental Defense Fund. "Electric Vehicle Market Update: Manufacturer Commitments and Public Policy
Initiatives Supporting Electric Mobility in the U.S. and Worldwide". September 2022. Available online:
https://blogs.edf.org/climate41 l/files/2022/09/ERM-EDF-Electric-Vehicle-Market-Report_September2022.pdf.
244 Robo, Ellen and Dave Seamonds. Technical Memo to Environmental Defense Fund: Investment Reduction Act
Supplemental Assessment: Analysis of Alternative Medium- and Heavy-Duty Zero-Emission Vehicle Business-As-
Usual Scenarios. ERM. August 19, 2022. Available online:
https://www.erm. com/contentassets/154d08e0d0674752925cd82c66b3e2b 1/edf-zev-baseline-technical-memo-
addendum.pdf.
245 ICCT and Energy Innovation. "Analyzing the Impact of the Inflation Reduction Act on Electric Vehicle Uptake
in the United States". January 2023. Available online: https://theicct.org/wp-content/uploads/2023/01/ira-impact-
evs-us-jan23-2.pdf.
246 Bloomberg. "Battery Pack Prices Cited Below $100/kWh for the First Time in 2020, While Market Average Sits
at $137/kWh". Available online: https://about.bnef.com/blog/battery-pack-prices-cited-below-100-kwh-for-the-
first-time-in-2020-while-market-average-sits-at-137-kwh/.
247 Mulholland, Eamonn. "Cost of electric commercial vans and pickup trucks in the United States through 2040."
Page 7. January 2022. Available at https://theicct.org/wp-content/uploads/2022/01/cost-ev-vans-pickups-us-2040-
jan22.pdf.
248 Environmental Defense Fund. "Technical Review of Medium- and Heavy-Duty Electrification Costs for 2027-
2030." February 2, 2022. Available online: https://blogs.edf.org/climate41 l/files/2022/02/EDF-MDHD-
Electrification-vl.6_20220209.pdf.
249 Sharpe, Ben and Hussein Basma. "A meta-study of purchase costs for zero-emission trucks". The International
Council on Clean Transportation, Working Paper 2022-09 (February 2022). Available online: https://theicct.org/wp-
content/uploads/2022/02/purchase-cost-ze-trucks-feb22-l.pdf.
250 Sharpe, Ben and Hussein Basma. "A meta-study of purchase costs for zero-emission trucks". The International
Council on Clean Transportation, https://theicct.org/wp-content/uploads/2022/02/purchase-cost-ze-trucks-feb22-
l.pdf.
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global electrification target of 50 percent of trucks sold being electric by 2030.251 Daimler
Trucks North America has committed to offering only what they refer to as "carbon-neutral"
trucks in the United States by 2039 and expects that by 2030 as much as 60 percent of its sales
will be ZEVs.252'253 Navistar has a goal of having 50 percent of its sales volume be ZEVs by
2030, and it has committed to achieve 100 percent zero emissions by 2040.254 Cummins targets
net-zero carbon emissions by 20 5 0.255>256
On a parallel path, large private HD fleet owners are also increasingly committing to
expanding their electric fleets.257 A report by the International Energy Agency (IEA) provides a
comprehensive accounting of recent announcements made by UPS, FedEx, DHL, Walmart,
Anheuser-Busch, Amazon, and PepsiCo for fleet electrification.258 Amazon and UPS, for
example, placed orders in 2020 for 10,000 BEV delivery vans from EV start-ups Rivian and
Arrival, respectively, and Amazon has plans to scale up to 100,000 BEV vans by 2030.259>260
Likewise, in December 2022, PepsiCo added the first of 100 planned Tesla Semis to its fleet.261
These announcements include not only orders for electric delivery vans and semi-trucks, but
more specific targets and dates to full electrification or net-zero emissions. Amazon, FedEx,
251 Scania, ' Scania's Electrification Roadmap,' Scania Group, November 24, 2021,
https://www.scania.com/group/en/home/newsroom/news/2021/Scanias-electrification-roadmap.html; AB Volvo,
'Volvo Trucks Launches Electric Truck with Longer Range,' Volvo Group, January 14, 2022,
https://www.volvogroup.com/en/news-and-media/news/2022/jan/news-4158927.html.
252 David Cullen, 'Daimler to Offer Carbon Neutral Trucks by 2039,' (October 25, 2019).
https://www.truckinginfo.com/343243/daimler-aims-to-offer-only-co2-neutral-trucks-by-2039-in-key-markets.
253 Deborah Lockridge, 'What Does Daimler Truck Spin-off Mean for North America?,' Trucking Info (November
11, 2021). https://www.truckinginfo.com/10155922/what-does-daimler-truck-spin-off-mean-for-north-america.
254 Navistar presentation at the Advanced Clean Transportation (ACT) Expo, Long Beach, CA (May 9-11, 2022).
255 Cummins, Inc. "Cummins Unveils New Environmental Sustainability Strategy to Address Climate Change,
Conserve Natural Resources." November 14, 2019. Last accessed on September 10, 2021 at
https://www.cummins.eom/news/releases/2019/l 1/14/cummins-unveils-new-environmental-sustainability-strategy-
address-climate.
256 Environmental Defense Fund (2022) September 2022 Electric Vehicle Market Update: Manufacturer
Commitments and Public Policy Initiatives Supporting Electric Mobility in the U.S. and Worldwide, available
online at: https://blogs. edf.org/climate41 l/fles/2022/09/ERM-EDF-Electric-Vehicle-Market-
Report_September2022.pdf.
257 Environmental Defense Fund (2021) EDF analysis finds American fleets are embracing electric trucks. July 28,
2021. Available online at: https://blogs.edf.org/energyexchange/2021/07/28/edf-analysis-finds-american-fleets-are-
embracing-electric-trucks/.
258 International Energy Association. Global EV Outlook 2021. April 2021. Available online at:
https://iea.blob.core.windows.net/assets/ed5f4484-J556-4110-8c5c-4ede8bcba63 7ZGlobalEVOutlook2021.pdf
259 Amazon, Inc. "Introducing Amazon's first custom electric delivery vehicle." October 8, 2020. Last accessed on
October 18, 2022 at https://www.aboutamazon.com/news/transportation/introducing-amazons-first-custom-electric-
delivery-vehicle.
260 Arrival Ltd. "UPS invests in Arrival and orders 10,000 Generation 2 Electric Vehicles." April 24, 2020. Last
accessed on October 18, 2022 at https://arrival.com/us/en/news/ups-invests-in-arrival-and-orders-l 0000-
generation-2-electric-vehicles.
261 Akash Sriram. "Musk delivers first Tesla truck, but no update on output, pricing." Reuters. December 2, 2022.
Last accessed on January 4, 2023 at https://www.reuters.com/business/autos-transportation/musk-delivers-first-
tesla-semi-trucks-2022-12-02/
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DHL, and Walmart have set a commitment to fleet electrification and/or achieving net-zero
emissions by 2040.262263'264'265'266267
The lifetime total cost of ownership (TCO), of which payback calculations play a critical part,
also includes maintenance and fuel costs, is likely a primary factor for HD vehicle and fleet
owners considering BEV and FCEV purchases. In fact, a 2018 survey of fleet owners showed
"lower cost of ownership" as the second most important motivator for electrifying their fleet.268
An ICCT analysis from 2019 suggests that TCO for light and medium heavy-duty BEVs could
reach cost parity with comparable diesel ICE vehicles in the early 2020s, while heavy HD BEVs
and FCEVs are likely to reach cost parity with comparable diesel ICE vehicles closer to the 2030
timeframe.269 Recent findings from Phadke et al. suggest that BEV TCO could be 13 percent less
than that of a comparable diesel ICE vehicle if electricity pricing is optimized.270 These studies
do not consider the IRA. The Rocky Mountain Institute found that because of the IRA, the TCO
of electric trucks will be lower than the TCO of comparable diesel trucks about five years faster
than without the IRA. They expect cost parity as soon as 2023 for urban and regional duty cycles
that travel up to 250 miles and 2027 for long-hauls that travel over 250 miles.271
262 We recognize that certain delivery vans will likely fall into the Class 2b and 3 regulatory category, the vast
majority of which are not covered in this rule's proposed updates; we are addressing this category in a separate light
and medium-duty vehicle rulemaking.
263 Robo, Ellen and Dave Seamonds. Technical Memo to Environmental Defense Fund: Investment Reduction Act
Supplemental Assessment: Analysis of Alternative Medium- and Heavy-Duty Zero-Emission Vehicle Business-As-
Usual Scenarios. ERM. August 19, 2022. Available online:
https://www.erm. com/contentassets/154d08e0d0674752925cd82c66b3e2b 1/edf-zev-baseline-technical-memo-
addendum.pdf.
264 FedEx Corp. "FedEx Commits to Carbon-Neutral Operations by 2040." March 3, 2021. Last accessed on October
18, 2022 at https://newsroom.fedex.com/newsroom/asia-english/sustainability2021.
265 Deutsche Post DHL Group. "Zero emissions by 2050: DHL announces ambitious new environmental protection
target." March 2017. Last accessed on October 18, 2022 at https://www.dhl.com/global-
en/delivered/sustainability/zero-emissions-by-2050.html.
266 Walmart Inc. "Walmart Sets Goal to Become a Regenerative Company." September 21, 2020. Last accessed on
October 18, 2022 at https://corporate.walmart.com/newsroom/2020/09/21/walmart-sets-goal-to-become-a-
regenerative-company.
267 Complete heavy-duty vehicles at or below 14,000 pounds. GVWR are chassis-certified under 40 CFR part 86,
while incomplete vehicles at or below 14,000 pounds. GVWR may be certified to either 40 CFR part 86 (meeting
standards under subpart S) or 40 CFR part 1037 (installed engines would then need to be certified under 40 CFR
part 1036). Class 2b and 3 vehicles are primarily chassis-certified complete commercial pickup trucks and vans. We
intend to pursue a combined light-duty and medium-duty rulemaking to set more stringent standards for complete
and incomplete vehicles at or below 14,000 pounds. GVWR that are certified under 40 CFR part 86, subpart S. The
standards proposed in this rule would apply for all heavy-duty vehicles above 14,000 pounds. GVWR, except as
noted in 40 CFR 1037.150(1). The proposed standards in this rule would also apply for incomplete heavy-duty
vehicles at or below 14,000 pounds. GVWR if vehicle manufacturers opt to certify those vehicles under 40 CFR part
1037 instead of certifying under 40 CFR part 86, subpart S.
268 The primary motivator for fleet managers was "Sustainability and environmental goals"; the survey was
conducted by UPS and GreenBiz.
269 ICCT (2019) "Estimating the infrastructure needs and costs for the launch of zero-emissions trucks"; available
online at: https.V/theicct. org/publications/zero-emission-truck-infrastructure.
270 Phadke, A., et. al. (2021) "Why Regional and Long-Haul Trucks are Primed for Electrification Now"; available
online at: https://eta-publications.lbl.gov/sites/default/files/updated_5yinal_ehdv_report_033121.pdf.
271 Kahn, Ari, et. al. "The Inflation Reduction Act Will Help Electrify Heavy-Duty Trucking". Rocky Mountain
Institute. August 25, 2022. Available online: https://rmi.org/inflation-reduction-act-will-help-electrify-heavy-duty-
trucking/.
82
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As the ICCT and Phadke et al. studies suggest, fuel costs are an important part of TCO. While
assumptions about vehicle weight and size can make direct comparisons between HD ZEVs and
ICE vehicles challenging, data show greater energy efficiency of battery-electric and fuel cell
technology relative to ICE technologies.272'273 Better energy efficiency leads to lower electricity
or hydrogen fuel costs for ZEVs relative to ICE fuel costs.274'275 Maintenance and service costs
are also an important component within TCO; although there is limited data available on actual
maintenance costs for HD ZEVs, early experience with BEV medium HD vehicles and transit
buses suggests the potential for lower maintenance costs after an initial learning period
component durability should be greatly improved.276 We expect similar trends for FCEVs, as
discussed in Chapter 2 of the RIA.
To facilitate HD fleets transitioning to ZEVs, some manufacturers are currently including
maintenance in leasing agreements with fleets. It is unclear the extent to which a full-service
leasing model will persist or will be transitioned to a more traditional purchase model after an
initial period of learning.277'278
The growth in federal and state incentive programs will continue to play an important role in
the HD ZEV market. In a 2017 survey of fleet managers, upfront purchase price was listed as the
primary barrier to HD fleet electrification. This suggests that federal incentive programs like
those in the BIL and IRA (discussed in Section 1.3) to offset ZEV purchase costs, as well as state
and local incentives and investments, can be influential in the near term, with improvements in
BEV and FCEV component costs playing an increasing role in reducing costs in the longer
term.279'280 For example, BEV incentive programs for transit and school buses have experienced
growth and are projected to continue to influence BEV markets. The Los Angeles Department of
Transportation (LADOT) is one of the first transit organizations in the country to develop a
program committed to transitioning its transit fleets to ZEVs by 2030—a target that is 10 years
sooner than CARB's Innovative Clean Transportation (ICT) regulation requiring all public
272 NACFE (2019) "Guidance Report: Viable Class 7/8 Electric, Hybrid and Alternative Fuel Tractors", available
online at: https.V/nacfe. org/clownloacls/viable-class- 7-8-alternative-vehicles/.
273 Nadel, S. and Junga, E. (2020) "Electrifying Trucks: From Delivery Vans to Buses to 18-Wheelers". American
Council for an Energy-Efficient Economy White Paper, available online at: https://aceee.org/white-
paper/electrifying-trucks-delivery-vans-buses-18.
274 NACFE (2019) "Guidance Report: Viable Class 7/8 Electric, Hybrid and Alternative Fuel Tractors", available
online at: https.V/nacfe. org/clownloacls/viable-class- 7-8-alternative-vehicles/.
275 Nadel, S. and Junga, E. (2020) "Electrifying Trucks: From Delivery Vans to Buses to 18-Wheelers". American
Council for an Energy-Efficient Economy White Paper, available online at: https://aceee.org/white-
paper/electrifying-trucks-delivery-vans-buses-18.
276 U.S. Department of Energy Alternative Fuels Data Center (AFDC), "Developing Infrastructure to Charge Plug-In
Electric Vehicles", https://afdc.energy.gov/fuels/electricity_infrastructure.html (accessed 2-27-20).
277 Fisher, J. (2019) "Volvo's First Electric VNR Ready for the Road." Fleet Owner, September 17.
www.fleetowner.com/blue-fleets/volvo-s-first-electric-vnr-ready-road.
278 Gnaticov, C. (2018). "Nikola One Hydrogen Electric Semi Hits the Road in Official Film." Carscoops, Jan. 26.
www.carscoops.com/2018/01/nikola-one-hydrogen-electric-semi-hits-road-official-film/.
279 Other barriers that fleet managers prioritized for fleet electrification included: Inadequate charging infrastructure-
- our facilities, inadequate product availability, inadequate charging infrastructure- public; for the full list of top
barriers see Nadel and Junga (2020), citing UPS and GreenBiz 2018.
280 Nadel, S. and Junga, E. (2020) "Electrifying Trucks: From Delivery Vans to Buses to 18-Wheelers". American
Council for an Energy-Efficient Economy White Paper, available online at: https://aceee.org/white-
paper/electrifying-trucks-delivery-vans-buses-18.
83
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transit to be electric by 2040.281 Since these announcements, LADOT has purchased 27 BEV
transit and school buses from BYD and Proterra; by 2030, the number of BEV buses in the
LADOT fleet is expected to grow to 492 buses. Outside of California, major metropolitan areas
including Chicago, Seattle, New York City, and Washington, DC, have zero-emissions transit
programs with 100 percent ZEV target dates ranging from 2040 to 2045.282'283'284'285 EV school
bus programs, frequently in partnership with local utilities, are also being piloted across the
country and are expanding under EPA's Clean School Bus Program (CSB).286 These programs
initially included school districts in, but not limited to, California, Virginia, Massachusetts,
Michigan, Maryland, Illinois, New York, and Pennsylvania.287'288'289'290'291 Going forward, they
will continue to expand with BIL funding of over $5 billion over the next five years (FY 2022-
2026) to replace existing school buses with zero-emission and low-emission models, as
discussed more in Section 1.3.
There are also extensive federal and state incentive programs to support transportation
electrification infrastructure. For example, as discussed in more detail in this section, Federal
Highway Administration (FHWA) -approved plans providing $1.5 billion in funding for
expanding charging on over 75,000 miles of highway encourage states to consider station
designs and power levels that could support heavy-duty vehicles. See further discussion in RTC
section 6.1.
In summary, the HD ZEV market is growing rapidly, and ZEV technologies are expected to
expand to many applications across the HD sector. As the industry is dynamic and changing
rapidly, the examples presented here represent only a sampling of the ZEV HD investment
281 LADOT, (2020). "LADOT Transit Zero-Emission Bus Rollout Plan"
https://ww2.arb.ca.gOv/sites/default/files/2020-12/LADOT_ROP_Reso_ADA12172020.pdf.
282 Sustainable Bus. "CTA Chicago tests electric buses and pursues 100% e-fleetby 2040". April 29, 2021.
Available online: https://www. sustainable-bus. com/electric-bus/cta-chicago-electric-buses/.
283 Pascale, Jordan. "Metro Approves Plans For Fully Electric Bus Fleet By 2045". DCist. June 10, 2021. Available
online: https://dcist.com/story/21/06/10/metro-goal-entirely-electric-bus-fleet-2045/.
284 King County Metro. "Transitioning to a zero-emissions fleet". Available online:
https://kingcounty.gov/depts/transportation/metro/programs-projects/innovation-technology/zero-emission-
fleet, aspx.
285 Hallum, Mark. "MTA's recent purchase of zero emissions buses will be 33% bigger than expected". AMNY.
May 25, 2021. Available online: https://www.amny.com/transit/mta-says-45-to-60-more-buses-in-recent-
procurement-will-be-zero-emissions/.
286 U.S. Environmental Protection Agency. "Clean School Bus Program". Available online:
https://www.epa.gov/cleanschoolbus.
287 Commonwealth of Massachusetts. "EV Programs & Incentives". Available online: https://www.mass.gov/info-
details/ev-programs-incentives.
288 Morris, Charles. "NYC's new school bus contract includes electric bus pilot". Charged—Electric Vehicles
Magazine. July 7, 2021. Available online: https://chargedevs.com/newswire/nycs-new-school-bus-contract-includes-
electric-bus-pilot/.
289 Soneji, Hitesh, et. al. "Pittsburg USD Electric School Bus Final Project Report". Olivine, Inc. September 23,
2020. Available online: https://olivineinc.eom/wp-content/uploads/2020/lO/Pittsburg-USD-Electric-School-Bus-
Final-Project-Report-Final.pdf.
290 Shahan, Cynthia. "Largest Electric School Bus Program in United States Launching in Virginia". CleanTechnica.
January 12, 2020. Available online: https://cleantechnica.com/2020/01/12/largest-electric-school-bus-program-in-
united-states-launching-in-virginia/.
291 St. John, Jeff. "Highland Electric Raises $235M, Lands Biggest Electric School Bus Contract in the US", gtm.
February 25, 2021. Available online: https://www.greentechmedia.com/articles/read/on-heels-of-253m-raise-
highland-electric-lands-biggest-electric-school-bus-contract-in-the-u.s.
84
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policies and markets. The following sections provide a more detailed characterization of the HD
ZEV technologies in the current and projected ZEV market.
The current heavy-duty market offers battery electric vehicles available for sale as both new
design BEVs and through conversions of ICE vehicles to BEVs. This market has been growing
since MY 2018 and is projected to reach about 180 models of heavy-duty battery electric trucks
by MY 2024,292 see Figure 1-13 for a summary of the number of battery electric heavy-duty
trucks available by model year as identified by literature review.
Heavy-Duty ZEV Models Available in the U.S. per
Model Year
..nil
2018 2019 2020 2021 2022 2023 2024
Model Year
Figure 1-13 Heavy-Duty Electric Trucks Available in the U.S. by Model Year
A list of battery electric heavy-duty trucks available to the public through MY 2024 is in
Table 1-23.
Table 1-23 Models of Battery Electric Heavy-Duty Vehicles through 2024
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
ARBOC
Specialty
Vehicles
Equess Charge293
Transit Bus
Class 7;
Class 8
New
2021
Arrival
Van294
Panel Van
Class 4
New
2021
Arrival
Bus295
Transit Bus
Class 7
New
2024
Autocar
E-ACTT296
Yard Truck
Class 8
New
2021
292 Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. "Heavy-Duty ZEV Models Available in the US
through MY2024." October 2023.
293 ARBOC Specialty Vehicles. Equess Charge. Available online: https://arbocsv.com/models/equess-charge/.
294 Arrival. Van. Available online: https://arrival.com/us/en/topic/van
295 Arrival. Bus. Available online: https://arrival.com/topic/bus
296 Autocar. E-ACTT. Available online: https://www.autocartruck.com/actt/eactt/
200
180
160
U1
cu 140
T3
^ 120
o 100
_q 80
60
40
20
0
85
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Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Avevai
E12 303297
Transit Bus
Class 8
New
2023
Avevai
E12 373298
Transit Bus
Class 8
New
2023
Avevai
XL299
Panel Van
Class 4
New
2024
Battle Motors
LET300
Refuse
Class 6;
Class 7;
Class 8
New
2022
Battle Motors
LET 2301
Refuse
Class 7
New
2022
Blue Arc
EV302
Panel Van
Class 3;
Class 4;
Class 5;
Class 6
New
2022
Blue Arc
EV5 303
Straight
Truck
Class 5
New
2023
Blue Bird
Electric All
American Bus304
Shuttle Bus;
Transit Bus
40-59
ft; Class
8
New
2019
Blue Bird
Electric All
American Bus304
Shuttle Bus;
Transit Bus
40-59
ft; Class
7
New
2019
Blue Bird
Electric All
American School
Bus304
Public
School Bus
Class 8
New
2019
Blue Bird
Electric All
American School
Bus304
Public
School Bus
Class 7
New
2019
Blue Bird
Electric Vision
Bus305
Shuttle Bus;
Transit Bus
30-39
ft; Class
6; Class
7
New
2019
Blue Bird
Electric Vision
School bus305
Public
School Bus
Class 6;
Class 7
New
2020
Blue Bird
Micro Bird G5306
Public
School Bus
Class 4
Conversion
2020
Bollinger Motors
B4307
Chassis Cab
Class 4
New
2022
Bollinger Motors
B5 308
Chassis Cab
Class 5
New
2023
297 Avevai. E12 303. Available online: https://avevai.eom/wp-content/uploads/2023/08/AVEVAI-A12-Tech-
Specs.pdf
298 Avevai. E12 373. Available online: https://avevai.eom/wp-content/uploads/2023/08/AVEVAI-A12-Tech-
Specs.pdf
299 Avevai. XL. Available online: https://avevai.com/iona-xl/
300 Battle Motors. LET. Available online: https://battlemotors.com/pages/lnt-ev
301 Battle Motors. LET 2. Available online: https://battlemotors.com/pages/let-ii-ev-specs
302 Blue ARC. EV. Available online: https://bluearcev.eom/#specifications
303 Blue ARC. EV5. Available online: https://bluearcev.com/wp-content/uploads/2023/03/bluearc-ev5-sell-sheet.pdf
304 Blue Bird. All American Electric. Available online: https://www.blue-
bird.com/images/RE_Electric_Spec_Sheet_09_30_22.pdf
305 Blue Bird. Vision Electric. Available online: https://www.blue-bird.com/buses/vision/vision-electric-bus
306 Blue Bird Micro Bird. G5 Electric. Available online: https://www.microbird.com/g5-electric
307 Bollinger Motors. B4. Available online: https://bollingermotors.com/trucks/
308 Bollinger Motors. B5. Available online: https://bollingermotors.com/trucks/
86
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Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
BrightDrop
ZEVO 600309
Panel Van
Class 3
New
2023
BrightDrop
ZEVO 40031CI
Panel Van
Class 3
New
2023
BYD Motors
6F311
Straight
Truck
Class 6
New
2020
BYD Motors
6F/6F+311
Straight
Truck
Class 6
New
2021
BYD Motors
6R312
Refuse
Class 6
New
2020
BYD Motors
8R313
Refuse
Class 8
New
2019
BYD Motors
8TT314
Tractor
Class 8
New
2019
BYD Motors
8Y315
Yard Truck
Class 8
New
2019
BYD Motors
C10M316
Coach Bus
> 40 ft;
Class 8
New
2020
BYD Motors
C10MS317
Coach Bus
> 40 ft;
Class 8
New
2019
BYD Motors
C6M318
Coach Bus
20-24
ft; Class
4; Class
5
New
2019
BYD Motors
C8M319
Coach Bus
30-39
ft; Class
8
New
2019
BYD Motors
C8MS320
Coach Bus
30-39
ft; Class
8
New
2021
BYD Motors
C9M321
Coach Bus
30-39
ft; Class
8
New
2019
BYD Motors
K11M322
Transit Bus
> 40 ft;
Class 8
New
2019
BYD Motors
K7M323
Transit Bus
30-39
ft; Class
7
New
2020
309 Brightdrop. ZEVO 600. Available online: https://www.gobrightdrop.com/products/brightdrop-zevo
310 Brightdrop. ZEVO 400. Available online: https://www.gobrightdrop.com/products/brightdrop-zevo
311 BYD. 6F. Available online: https://en.byd.com/truck/class-6-truck/#:~:text=Cab%20%26%20Chassis-
,The%20BYD%206F%20is%20the%20world's%20first%20commercially%20available%20all,of%20performance%
2C%20endurance%20and%20reliability.
312 BYD. 6R. Available online: https://en.byd.com/truck/class-6-refuse-truck/
313 BYD. 8R. Available online: https://en.byd.com/truck/class-8-refuse-truck/
314 BYD. 8TT. Available online: https://en.byd.com/truck/class-8-day-cab/
315 BYD. 8Y. Available online: https://en.byd.com/truck/terminal-tractor/
316 BYD. C10M. Available online: https://en.byd.com/bus/bus-clOm/
317 BYD. C10MS. Available online: https://en.byd.com/bus/bus-clOms/
318 BYD. C6M. Available online: https://en.byd.com/bus/bus-c6m/
319 BYD. C8M. Available online: https://en.byd.com/bus/bus-c8m/
320 BYD. C8MS. Available online: https://en.byd.com/bus/bus-c8ms/
321 BYD. C9M. Available online: https://en.byd.com/bus/bus-c9m/
322 BYD. K11M. Available online: https://en.byd.com/bus/kllm/
323 BYD. K7M. Available online: https://en.byd.com/bus/k7m/
87
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Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
BYD Motors
K7M-ER324
Shuttle Bus;
Transit Bus
30-39
ft; Class
8
New
2020
BYD Motors
K8M325
Transit Bus
30-39
ft; Class
8
New
2019
BYD Motors
K9M326
Transit Bus
30-39
ft; Class
8
New
2019
BYD Motors
K9MD327
Transit Bus
30-39
ft; Class
8
New
2019
BYD Motors
Type D School
Bus328
Public
School Bus
Class 8
New
2021
BYD Motors
Type A School
Bus329
Public
School Bus
Class 6
New
2023
Canoo
MPDV l330
Panel Van
Class 3
New
2024
CityFreighter
CF1331
Step Van
Class 4;
Class 5
New
2024
Complete Coach
Works
ZEPS332
Transit Bus
Class 8
Conversion
2020
Dulevo
D.zero2333
Street
Sweeper
New
2020
ElDorado
National
AXESS EVO 32334
Transit Bus
Class 8
New
2023
ElDorado
National
AXESS EVO 35334
Transit Bus
Class 8
New
2023
ElDorado
National
AXESS EVO 40334
Transit Bus
Class 8
New
2023
Envirotech Drive
Systems
Incorporated
C Series335
Panel Van
Class 4
New
2019
Envirotech Drive
Systems
Incorporated
C Series Cutaway,
Urban Cab Over336
Straight
Truck
Class 4
New
2019
324 BYD. K7MER. Available online: https://en.byd.com/bus/k7mer/
325 BYD. K8M. Available online: https://en.byd.com/bus/k8m/
326 BYD. K9M. Available online: https://en.byd.com/bus/k9m/
327 BYD. K9MD. Available online: https://en.byd.com/bus/k9md/
328 BYD. Type D Electric School Bus. Available online: https://en.byd.com/bus/school-bus/school-bus-d/
329 BYD. Type A School Bus. Available online: https://en.byd.com/bus/school-bus/school-bus-a/
330 Canoo. MPDV 1. Available online: https://www.canoo.com/mpdv/
331 CityFreighter. CF1. Available online: https://www.cityfreighter.com/
332 Complete Coach Works. ZEPS. Available online: http://www.completecoach.com/wp-
content/uploads/2013/07/ZEPS-Brochure.pdf
333 Dulevo. D.Zero2. Available online: https://www.dulevo.com/us/products/street-sweepers/dulevo-d-zero2/
334 ElDorado National. Axess EVO Specifications. Available online: https://www.eldorado-ca.com/axess-evo-be
335 Envirotech Drive Systems. Logistics Van. Available online: https://evtvusa.com/vehicles/logistics-van/
336 Envirotech Drive systems. Cutaway Van. Available online: https://evtvusa.com/vehicles/cutaway-van/
88
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Envirotech Drive
Systems
Incorporated
Urban Cab Over337
Straight
Truck
Class 3
New
2020
Ford
eTransit338
Panel Van
Class 4
New
2022
Freightliner
eCascadia339
Tractor
Class 8
New
2022
Freightliner
eM2340
Straight
Truck
Class 6;
Class 7
New
2023
Freightliner
MT50e341
Step Van;
Straight
Truck
Class 5
New
2020
Gillig
29342
Transit Bus
25-29
ft; 30 -
39 ft;
Class 8
New
2020
Global
Environmental
Products
M3EV343
Street
Sweeper
Class 6;
Class 7
New
2020
Global
Environmental
Products
M4EV344
Street
Sweeper
Class 6;
Class 7
New
2020
GreenPower
Motor Company
BEAST345
Public
School Bus
Class 8
New
2020
GreenPower
Motor Company
Nano Beast346
Public
School Bus
Class 5
New
2023
GreenPower
Motor Company
AV Star347
Shuttle Bus
Class 4
New
2020
GreenPower
Motor Company
EV Star CarGo348
Panel Van
Class 4
New
2019
GreenPower
Motor Company
EV Star CarGo
Plus349
Straight
Truck
Class 4
New
2021
337 Envirotech Drive Systems. Urban Truck. Available online: https://evtvusa.com/vehicles/urban-truck/
338 Ford. E-Transit Cargo Van. Available online: https://www.ford.com/commercial-trucks/e-transit/models/cargo-
van/
339 Freightliner. eCascadia. Available online: https://freightliner.eom/trucks/ecascadia/specifications/#tab-l
340 Freightliner. eM2. Available online: https://freightliner.com/trucks/em2/specifications/
341 Freightliner Custom Chassis. eM2 Walk-in Van. Available online: https://www.electricwalkinvan.com/
342 Gillig. Battery Electric Bus. Available online: https://www.gillig.com/battery-electric
343 Global Environmental Products. M3EV. Available online: https://globalsweeper.com/products/mechanical/m3-
electric-100-plug-in
344 Global Environmental Products. M4EV. Available online: https://globalsweeper.com/products/mechanical/m4-
electric-100-plug-in
345 Greenpower Motor Company. Beast. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/BEASTBrochure.pdf
346 GreenPower Motor Company. Nano Beast. Available online: https://greenpowermotor.com/gp-products/nano-
beast-school-bus/
347 Greenpower Motor Company. AV Star. Available online: https://greenpowermotor.com/gp-products/av-star/
348 Greenpower Motor Company. EV Star Cargo. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EVSTARCBrochure.pdf
349 Greenpower Motor Company. EV Star Cargo +. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EVSTARC+Brochure.pdf
89
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
GreenPower
Motor Company
EV Star CC350
Straight
Truck
Class 4
New
2021
GreenPower
Motor Company
EV Star351
Shuttle Bus
Class 4
New
2020
GreenPower
Motor Company
EV Star Plus352
Paratransit;
Shuttle Bus
Class 4
New
2020
GreenPower
Motor Company
EV250353
Transit Bus
30-39
ft; Class
8
New
2019
GreenPower
Motor Company
EV3 5 0354
Transit Bus
40-59
ft; Class
8
New
2019
GreenPower
Motor Company
EV5 5 0355
Transit Bus
> 40 ft;
Class 8
New
2019
GreenPower
Motor Company
SYNAPSE 72356
Public
School Bus
Class 8
New
2019
GreenPower
Motor Company
SYNAPSE357
Shuttle Bus;
Transit Bus
30-39
ft; Class
8
New
2019
Hino
L6e358
Straight
Truck
Class 6
New
2023
Hino
M5e359
Straight
Truck
Class 5
New
2023
Hometown
Manufacturing
Villager360
Transit Bus
Class 6;
Class 7
New
2021
Hometown
Manufacturing
Mainstreet361
Transit Bus
Class 6;
Class 7
New
2021
Hometown
Manufacturing
Streetcar362
Transit Bus
Class 7;
Class 8
New
2021
350 Greenpower Motor Company. EV Star CC. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EVSTARCC_Brochure.pdf
351 Greenpower Motor Company. EV Star. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EVSTARBrochure.pdf
352 Greenpower Motor Company. EV Star +. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EVSTAR+Brochure.pdf
353 Greenpower Motor Company. EV250. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EV250_brochure.pdf
354 Greenpower Motor Company. EV350. Available online: https://greenpowermotor.com/wp-
content/uploads/Brochures/EV350_brochure.pdf
355 Greenpower Motor Company. EV550. Available online: https://greenpowermotor.com/gp-products/ev550-bus/
356 Greenpower Motor Company. Synapse 72. Available online: https://greenpowermotor.com/greenpowers-
synapse-72-school-bus-commences-demonstration-tour/
357 Greenpower Motor Company. Synapse Shuttle Bus. Available online: https://greenpowermotor.com/greenpower-
delivers-synapse-shuttle/
358 Hino. L6e. Available online: https://www.hino.com/electricvehicle.html
359 Hino. M5e. Available online: https://www.hino.com/electricvehicle.html
360 Hometown Manufacturing. Villager. Available online: https://hometown-mfg.com/trolleys/villager
361 Hometown Manufacturing. Mainstreet. Available online: https://hometown-mfg.com/trolleys/mainstreet
362 Hometown Manufacturing. Streetcar. Available online: https://hometown-mfg.com/trolleys/streetcar
90
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Hometown
Manufacturing
View363
Transit Bus
Class 6;
Class 7
New
2021
Hometown
Manufacturing
Commuter364
Transit Bus
Class 7;
Class 8
New
2021
Hometown
Manufacturing
Urban365
Transit Bus
Class 7;
Class 8
New
2021
Hyundai
Electric City366
Transit Bus
Class 7
New
2020
IC Bus
CE Electric367
Public
School Bus
Class 7
New
2021
Kalmar
T2E+368
Yard Truck
Class 8
New
2020
Kenworth
K270E369
Straight
Truck
Class 6
New
2020
Kenworth
K370E369
Straight
Truck
Class 7
New
2020
Kenworth
T680E370
Tractor
Class 8
New
2020
Lightning
Systems
Transit Bus371
Transit Bus
Class 6
Conversion
2020
Lightning
Systems
Transit Cargo
Van372
Panel Van
Class 4
Conversion
2020
Lightning
Systems
ZEV4 373
Shuttle Bus
Class 4
Conversion
2023
Lightning
Systems
ZEV4 374
Public
School Bus
Class 4
Conversion
2023
Lightning
Systems
ZEV4 375
Straight
Truck
Class 4
Conversion
2023
Lightning
Systems
ZEV3376
Panel Van
Class 3
Conversion
2023
Lightning
Systems
ZEV3377
Ambulance
Class 3
Conversion
2023
363 Hometown Manufacturing. View. Available online: https://hometown-mfg.com/buses/view
364 Hometown Manufacturing. Commuter. Available online: https://hometown-mfg.com/buses/commuter
365 Hometown Manufacturing. Urban. Available online: https://hometown-mfg.com/buses/low-floor-urban
366 Hyundai. Elec City. Available online: https://trucknbus.hyundai.com/global/en/products/bus/elec-city
367 IC Bus. CE Electric. Available online: https://www.icbus.com/-
/media/Project/Navistar/ICBus/ICBus/Electric/NAV22_IC_BUS_eCE_SpecSheet_2022_rd02.pdf
368 Kalmar Ottawa. T2E+. Available online:
https://www.kalmarglobal.eom/4946e2/globalassets/media/268794/268794_Kalmar-Ottawa-Electric-Terminal-
Tractor-T2E-_Brochure-web.pdf.pdf
369 Kenworth. K270e K370e. Available online: https://www.kenworth.com/trucks/k270e-k370e/
370 Kenworth. T680e. Available online: https://www.kenworth.com/trucks/t680e/
371 Lightning eMotors. City Transit Bus Repower. Available online: https://lightningemotors.com/buses/
372 Lightning eMotors. ZEV3 Transit Cargo Van. Available online: https://lightningemotors.com/zev3-transit-cargo-
van/
373 Lightning eMotors. ZEV4 Shuttle Bus. Available online: https://lightningemotors.eom//lightningelectric-class4-
shuttle/
374 Lightning eMotors. ZEV4 Public School Bus. Available online: https://lightningemotors.com/type-a-school-bus/
375 Lightning eMotors. ZEV4 Straight Truck. Available online: https://lightningemotors.eom//lightningelectric -
class4-cutaway/
376 Lightning eMotors. ZEV3 Ambulance. Available online: https://lightningemotors.com/ambulances/
377 Lightning eMotors. ZEV3 Panel Van. Available online: https://lightningemotors.com/zev3-transit-cargo-van/
91
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Lion Electric
Lion5378
Straight
Truck
Class 5
New
2023
Lion Electric
Lion6379
Straight
Truck
Class 6
New
2021
Lion Electric
Lion8P ASL379
Refuse
Class 8
New
2021
Lion Electric
Lion8P379
Straight
Truck
Class 8
New
2019
Lion Electric
Lion8P Rel379
Refuse
Class 8
New
2021
Lion Electric
Lion8T379
Tractor
Class 8
New
2021
Lion Electric
Bucket Truck379
Bucket
Truck
Class 8
New
2021
Lion Electric
LionA380
Public
School Bus
Class 6
New
2019
Lion Electric
LionC381
Public
School Bus
Class 6;
Class 7
New
2019
Lion Electric
LionD382
Public
School Bus
Class 8
New
2019
Lion Electric
LionM383
Paratransit
Class 6
New
2020
Mack Trucks
LR384
Refuse;
Straight
Truck
Class 8
New
2021
Mack Trucks
MD385
Straight
Truck
Class 5
New
2023
Mercedes Benz
eCitaro386
Transit Bus
Class 8
New
2021
Mercedes Benz
eACTROS 600387
Straight
Truck
Class 8
New
2023
Mercedes Benz
eACTROS 600387
Tractor
Class 8
New
2023
Motiv Power
Systems
E-450388
Straight
Truck
Class 4
Conversion
2021
Motiv Power
Systems
E-450389
Shuttle Bus
Class 6
Conversion
2020
Motiv Power
Systems
F-53390
Step Van
Class 6
Conversion
2021
378 Lion Electric. Lion5. Available online: https://thelionelectric.com/documents/en/LionTruck-SpecSheet-202305-
SCREEN-ENUS.pdf
379 Lion Electric. Lion6, Lion8, Lion8 Bucket, Lion8 Refuse ASL, Lion8 Refuse REL, Lion8T. Available online:
https://thelionelectric.com/documents/en/Lion8_all_applications.pdf
380 Lion Electric. LionA. Available online: https://thelionelectric.com/documents/en/onepager_LionA_EN.pdf
381 Lion Electric. LionC. Available online: https://thelionelectric.com/documents/en/BrochureLionCang.pdf
382 Lion Electric. LionD. Available online: https://thelionelectric.com/documents/en/liond_specs_en.pdf
383 Lion Electric. LionM. Available online: https://thelionelectric.com/documents/en/spec_LionM_EN_US.pdf
384 Mack Trucks. LR Electric. Available online: https://www.macktrucks.com/trucks/lr-electric/specs/
385 Mack Trucks. MD Electric. Available online: https://www.macktrucks.com/trucks/md-electric/
386 Mercedes Benz Bus. eCitaro. Available online: https://www.mercedes-benz-
bus.com/en_DE/models/ecitaro/technology.html
387 Mercedes Benz Truck. eACTROS 600. Available online: https://eactros600.mercedes-benz-
trucks.eom/int/en/eactros-600/showroom.html#eactros600_technical-data
388 Motiv Power Systems. E-450. Available online: https://www.motivps.com/application/electric-box-truck/
389 Motiv Power Systems. Shuttle Bus. Available online: https://www.motivps.com/application/electric-step-van/
390 Motiv Power Systems. Step Vans. Available online: https://www.motivps.com/vehicles/step-vans/
92
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Motiv Power
Systems
Argo391
Straight
Truck
Class 6
New
2024
Motor Coach
Industries
D45 CRT Charge392
Coach Bus
40-59
ft; Class
8
New
2020
Motor Coach
Industries
D45 CRTe LE392
Coach Bus
40-59
ft; Class
8
New
2020
Motor Coach
Industries
J4500e392
Coach Bus
40-59
ft; Class
8
New
2020
Navistar
eMV393
Straight
Truck
Class 6;
Class 7
New
2021
New Flyer
XCELSIOR Charge
NG394
Transit Bus
35, 40,
60 ft;
Class 7;
Class 8
New
2021
Nikola
Tre395
Tractor
Class 8
New
2023
Nova Bus
LFSe396
Transit Bus
Class 8
New
2018
Nova Bus
LFSe+397
Transit Bus
Class 8
New
2021
Optimal Inc
SI398
Shuttle Bus
Class 5
Conversion
2021
Optimal Inc
El399
Chassis Cab
Class 5
Conversion
2021
Orange EV
HUSK-e400
Yard Truck
Class 8
New
2023
Orange EV
eTriever401
Yard Truck
Class 8
New
2021
Peterbilt
220EV402
Straight
Truck
Class 6;
Class 7
New
2021
Peterbilt
520EV403
Refuse;
Straight
Truck
Class 8
New
2021
Peterbilt
579EV404
Tractor
Class 8
New
2021
391 Motiv Power Systems. Argo. Available online: https://www.motivps.com/vehicles/building-the-future/
392 Motor Coach Industries. Electric Series Specs. Available online: https://www.mcicoach.com/coach/electric-
series/specs/
393 International Trucks. eMV. Available online: https://www.internationaltrucks.com/trucks/emv-series/detailed-
specs
394 New Flyer. Xcelsior Charg NG. Available online: https://www.newflyer.com/bus/xcelsior-charge-ng/
395 Nikola. Tre BEV. Available online: https://nikolamotor.com/tre-bev
396 Nova Bus. LFSe. Available online: https://us.novabus.com/blog/bus/lfse/
397 Nova Bus. LFSe+. Available online: https://us.novabus.com/blog/bus/lfse-plus/
398 Optimal EV. SI. Available online: https://www.optimal-ev.com/sl
399 Optimal EV. El. Available online: https://www.optimal-ev.com/el
400 Orange EV. HUSK-e. Available online: https://orangeev.com/wp-content/uploads/2023/09/OEV-HUSK-e-
Product-Sheetpdf
401 Orange EV. eTriever. Available online: https://orangeev.com/etriever/
402 Peterbilt. 220EV. Available online: https://www.peterbilt.com/trucks/electric/220EV
403 Peterbilt. 520EV. Available online: https://www.peterbilt.com/trucks/electric/520EV
404 Peterbilt. 579EV. Available online: https://www.peterbilt.com/trucks/electric/579EV
93
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Phoenix
E450405
Shuttle Bus
25-29
ft; Class
4
New
2019
Phoenix
E450405
Straight
Truck
Class 4
New
2020
Phoenix
E450406
Public
School Bus
Class 4
New
2019
Proterra
ZX5+ 35'407
Transit Bus
35 ft;
Class 8
New
2021
Proterra
ZX5+ 3 51407
Transit Bus
35 ft;
Class 8
New
2021
Proterra
ZX5+ 40'408
Transit Bus
40 ft;
Class 8
New
2021
Proterra
ZX5+ 40'408
Transit Bus
40 ft;
Class 8
New
2021
Proterra
ZX5 MAX408
Transit Bus
40 ft;
Class 8
New
2021
Proterra
ZX5 MAX408
Transit Bus
40 ft;
Class 8
New
2021
Rizon
el6M409
Straight
Truck
Class 4
New
2023
Rizon
el6L409
Straight
Truck
Class 4
New
2023
Rizon
el8M409
Straight
Truck
Class 5
New
2023
Rizon
el8L409
Straight
Truck
Class 5
New
2023
SEA Electric
5e410
Straight
Truck
Class 5
New
2023
SEA Electric
Ford F-59e411
Panel Van
Class 5,
Class 6
Conversion
2021
SEA Electric
SV6e412
Straight
Truck
Class 6
New
2023
405 Phoenix. E450 Shuttle Bus and Straight Truck. Available online: https://www.phoenixmotorcars.com/wp-
content/uploads/2021/08/ZEUS-400-500-FLYER-TRUCKS-AND-SHUTTLE-FOR-SITE-AUGUST-2021 .pdf
406 Phoenix. E450 Public School Bus. Available online: https://www.phoenixmotorcars.eom/products/#bus
407 Proterra. ZX5+ 35' Bus. Available online: https://www.proterra.com/wp-
content/uploads/2022/09/SPEC_3 5 001 Q4 2022 V 1_09_0 l_22.pdf
408 Proterra. ZX5+ and ZX5 Max 40' Bus. Available online: https://www.proterra.com/wp-
content/uploads/2022/09/SPEC_40_001_Q4_2022_V1_09_0122-1 .pdf
409 Rizon. el6M, el6L, el8M, el8L. Available online: https://assest.rizontruck.eom/rizonassets/2023/10/RIZON-
Product-Brochure-Oct-23-min.pdf?_fsi=8UPB9mCy
410 SEA Electric. 5e. Available online: https://www.sea-electric.com/wp-content/uploads/2023/06/SEA-5e-
eBrochure-0623 .pdf
411 SEA Electric. F-59e. Available online: https://www.sea-electric.com/wp-content/uploads/2023/08/SEA-F59e-
eBrochure-0723 -%E2%80%93 -US A.pdf
412 SEA Electric. SV6e. Available online: https://www.sea-electric.eom/wp-content/uploads/2023/08/SEA-SV6e-
eBrochure-0223 .pdf
94
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
SEA Electric
Type C School
Bus413
Public
School Bus
Class 6
Conversion
2022
Terraline
TangraLHl414
Tractor
Class 8
New
2023
Terberg
YT203-EV415
Yard Track
Class 8
New
2020
Tesla
Semi416
Tractor
Class 8
New
2024
Thomas Built
eC2 Jouley417
Public
School Bus
Class 7
New
2019
US Hybrid
eVan418
Panel Van
Class 3
Conversion
2022
Van Hool NV
CX45E419
Coach Bus;
Shuttle Bus;
Transit Bus
Class 8
New
2020
Van Hool NV
TDX25e420
Coach Bus
Class 8
New
2023
Vicinity Motors
VMC 1200421
Straight
Track
Class 3
New
2023
Vicinity Motors
Lightning EV422
Transit Bus
Class 6
New
2020
Volvo
VNR423
Tractor
Class 8
New
2021
Volvo
VNR423
Straight
Track
Class 8
New
2021
Workhorse
Group Inc.
W4 CC424
Straight
Track
Class 4
New
2023
Workhorse
Group Inc.
W750425
Panel Van
Class 4
New
2023
Workhorse
Group Inc.
W56426
Step Van
Class 5,
Class 6
New
2023
Xos
sv
Step Van
Class 6
New
2023
Xos
HDXT427
Tractor
Class 8
new
2022
413 SEA Electric. Type C Public School Bus. Available online: https://www.sea-electric.com/wp-
content/uploads/2023/08/SEA-Type-C-School-Bus-eBrochure-0223.pdf
414 Terraline. TangraLHl. Available online: https://terralinetracks.com/tangra-lhl/
415 Terberg Special Vehicles. YT203-EV. Available online:
https://www.terbergspecialvehicles.eom/en/vehicles/terminal-tractors/#YT203-EV
416 Tesla. Semi. Available online: https://www.tesla.com/semi
417 Thomas Built Buses. Saf-T-Liner C2 Jouley. Available online: https://thomasbuiltbuses.com/school-buses/saf-t-
liner-c2-jouley/
418 US Hybrid. eVan. Available online: https://ushybrid.com/wp-
content/uploads/2022/05/USH_eVan_Productsheet_2022_V8.pdf
419 VanHool. CX45e. Available online: https://www.vanhool.com/en/vehicles/coaches/coaches-usa/cx45e
420 VanHool. TDX25e Astromega. Available online: https://www.vanhool.com/en/vehicles/coaches/coaches-
usa/tdx25e-astromega-usa
421 Vicinity Motor Co. VMC 1200. Available online:
https://vicinitymotorcorp.com/images/pdf/VMC1200SpecificationsFlyer.pdf
422 Vicinity Motor Co. Lightning EV. Available online: https://vicinitymotorcorp.com/modelsm/vicinity-lightning-
ev.html
423 Volvo. VNR Electric. Available online: https://www.volvotracks.us/tracks/vnr-electric/
424 Workhorse Group. W4 CC. Available online: https://workhorse.eom/wp-content/uploads/2023/05/CV-W4CC-
Specs-2305v6.pdf
425 Workhorse Group. W750. Available online: https://workhorse.com/wp-content/uploads/2023/05/CV-W750-
Specs-2305v4.pdf
426 Workhorse Group. W56. Available online: https://workhorse.com/wp-content/uploads/2023/05/CV-W56-Specs-
2305v2.pdf
427 XOS Tracks. HDXT. Available online: https://www.xostracks.com/hdxt
95
-------
Make
Model
Vehicle
Type
Weight
Class
New Design or Existing
Design Conversion
First
Model
Year
Xos
MDXT428
Straight
Truck
Class 6;
Class 7
New
2022
Hexagon
Purus eM2429
Straight
Truck
Class 6;
Class 7
Conversion
2021
Zeus
Electric Chassis430
Straight
Truck
Class 5;
Class 7
New
2023
1.5.5.1 Purchase Commitments of Battery Electric Vehicles
A report by The Environmental Defense Fund (EDF) summarized several publicly announced
heavy-duty electric vehicle purchase commitments during 2022.431 These announcements can be
found at the references in Table 1-24 below. These announcements were made prior to the
passage of the Inflation Reduction Act and therefore do not include purchase commitments that
may result from consideration of the various tax incentives and other incentives that currently are
available in the market, as summarized in Chapter 1.3.2 of this document.
Table 1-24 List of HD BEV Purchase Commitments Compiled by EDF (2022)431
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
4 Gen Logistics
20
No
Class 8 Tractor
-Kenworth T680E
A. Duie Pyle Inc.
2
Yes
Class 4 Box Truck
-FUSO eCanter
A.P. Moller-Maersk
300
No
Class 8 Tractor
-Einride AB
A&R Logistics
2
Yes
Class 8 Tractor
-Peterbilt Model 579EV
AE Cargo Group Inc,
1
No
Yard tractor
N/A
AJR Trucking
15
No
Class 8 Tractor
-Kenworth T680E
Albertsons Cos.
12
Partially
Class 8 Tractor
-10 Tesla semitrucks
-2 Volvo VNR Electric truck
Alco
1
Yes
Terminal Tractor
-Orange EV T-Series
Alsco
4
Yes
Class 4 Step Van
-EPIC F-59 F
Amazon
102,500
Partially
Class 2b Cargo Van
Class 8 Tractor
Class 6 Tractor
Class 2b Delivery Van
-100,000 Rivian Cargo Van
-1250 Lion Electric
-1250 Lion Electric
-TBA BEV ProMaster
Amherst County
2
No
Class 8 Tractor
-N/A
Anderson DuBose
1
Yes
Terminal Tractor
-Orange EV
Anheuser-Busch Cos.
841
Partially
Class 8 Tractor
-21 BYD 8TT
-800 Nikola Fuel Cell
-40 Tesla semi trucks
428 XOS Trucks. MDXT. Available online: https://www.xostrucks.com/mdxt
429 Hexagon Purus. eM2. Available online: https://hexagonpurus.com/our-solutions/battery-and-fuel-cell
430 Zeus. Electric Vocational Trucks. Available online: https://zeuselectricchassis.com/electric-vocational-trucks/
431 Environmental Defense Fund. Electric Fleet Deployment & Commitment List. Available here:
https://docs.google.eom/spreadsheets/d/110m2Dolmj Semrb_DT40YNGou4o2m2Ee-KLSvHC-
5v Ac/edit#gid=2049738669
96
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
ARAMARK and Operating
Companies
31
Yes
Class 5 Step Van
-Motiv Power Systems F-59
Benore Logistic Systems
1
Yes
Class 8 Tractor
-Peterbilt Model 579EV
Best Transportation
4
No
Terminal tractors
N/A
Bettaway Beverage
Distributors Inc.
2
No
Distribution tractors
N/A
Biagi Bros. Inc.
1
Yes
Class 8 Tractor
-Peterbilt 579EV
Bimbo Bakeries USA and
Operating Companies
105
Yes
Class 5 Step Van
Class 5 Step Van
-100 Motiv F-59
-5 Motiv F-59
Black Horse Carriers
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Blue Earth Compost, Inc
1
No
Class 5 Step Van
-N/A
Borough of Bergenfield
2
No
Class 8 Refuse
N/A
C&V Contractors
1
Yes
Class 4 Truck
-Phoenix Motorcars Zeus
500
Camrett Logistics
1
Yes
Class 8 Tractor
-Volvo VNR
City Furniture
6
Partial
Terminal Tractor
Class 8 Tractor
-1 Kalmar Ottawa Electric
-5 Tesla Semis
City of Englewood
2
No
Class 8 Refuse
N/A
City of Hyattsville
1
No
Class 6 Refuse
-BYD 6R
City of Jersey City
5
Yes
Class 6 Refuse
-BYD 6R
City of Los Angeles Center
for Green Innovation
1
Yes
Class 6 Box Truck
-ROUSH CleanTech's Ford
F-650
City of Madison Fire
Department
1
Yes
Class 8 Fire Truck
-Pierce Volterra zero-
emissions pumper
City of Newark
2
No
Class 8 Refuse
N/A
City of Ocala
5
No
Class 6 Refuse
-BYD 6R
City of Paterson
2
No
Class 8 Refuse
N/A
City of Perth Amboy
2
No
Class 8 Refuse
N/A
City of Pittsburgh
7
No
Class 8 Bucket Truck
Class 3 Vans
Class 8 fire trucks
N/A
City of Trenton
2
No
Class 8 Refuse
N/A
City of Wilmington, NC
1
No
Class 8 Refuse
-Lion Electric
City of Woodland, CA
2
Yes
Class 4 Truck
-Phoenix Motorcars Zeus
500
Consolidated Edison of New
York
1
No
Class 8 Bucket Truck
-Custom built by Lion
Electric and Posi-Plus
Core-Mark International Inc.
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Costco
1
Yes
Class 8 Tractor
-Freightliner eCascadia
County of Chautauqua
1
Yes
Yard Tractor
-Orange EV T-Series
Covenant Logistics
50
No
Class 8 Tractor
-10 Nikola Tre (BEVs)
- 40 Nikola Tre (FCEV)
DHE
12
Partially
Class 8 Tractor
-12 Volvo VNR Electric
97
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
DHL Worldwide Express
256
Partially
Class 8 Tractor
Class 3 Step Van
Class 3 Delivery Van
-100N/A Tesla Semi
-4 BYD 8TT
-63 Workhorse NGEN-1000
-100 Lightning Electric
Dickinson Fleet Services LLC
5
No
Class 6 Work Truck
-Xos Medium Duty
Dimension Fabricators
1
Yes
Terminal Tractor
-Orange EV T-Series
DocGo
1
Yes
Class 3 ambulance
-Ford Transit T350 Type II
Dole
5
Yes
Yard Tractor
-Orange EV
Donlen
100
No
Class 4
-Udelv Transporters
Dot Foods Inc./ Dot
Transportation
1
Yes
Terminal Tractor
-Orange EV T-Series
Eco-Cycle
1
Yes
Class 8 Refuse
-Mack LR Electric
EcoMaine
2
No
Class 8 Refuse
-Lion Refuse
Einride
200
No
Class 8 Tractor
-BYD 8TT
Elate Moving, LLC
1
No
Class 6 Box Truck
-N/A
Elizabeth Board of Education
4
No
Class 8 Refuse
Class 4 Delivery Trucks
-N/A
eTrucks
20
No
Class 3 Step Van
-Workhorse C1000
EV Semi-Fleet
50
No
Class 8 Tractor
-50 Tesla Semi
-1 Nikola Tre BEV
F&G, LLC
1
No
Yard Tractor
-NA
Fairfax County Department of
Public Works and
Environmental Services
5
No
Class 8 Refuse
Class 4 Van
-Workhorse C1000
Fastenal Co.
1
Yes
Class 6 Box Truck
-Freightliner eM2
FedEx Corp.
2,641
Partially
Class 3 Cargo Van
Class 8 Tractor
Class 4 Step Van
Class 4 Medium-duty
truck
-2500 GM Zevo 600 Cargo
Van
-20 Tesla semi-trucks
-1 Workhorse Progen
concept Step Van
-120 XOS
Firefly Transportation
Services
1
Yes
Terminal Tractor
-T-Series Tandem
Fleetmaster Express Inc.
18
Partially
Class 8 Tractor
-12 Volvo VNR Electric
-2 Peterbilt Model 579EV
-2 Tesla Semis
-2 Dana Inc.
Fluid Truck
50
Yes
Class 4 Box Truck
- Lightning Electric
Forest River, Inc.
150
No
Class 4 Cutaway
-EV Star Cab and Chassis
Frito-Lay North America
50
Partially
Class 6 Box Truck
Terminal Tractor
Class 2b Van
-6 Peterbilt 220ev
-3 BYD 8Y
-41 Ford E-Transit
GATR Truck Centers
1,150
No
Class 5 Box Truck
-SEA Hino M5
Glovis America
30
No
Class 8 Tractor
-Hyundai XCIENT
98
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
Goodwill Industries
International
11
Yes
Class 6 Box Truck
-BYD T7
Green Mountain Power Corp.
2
No
Class 8 Bucket Truck
-Lion8 Bucket Truck
GSC Logistics
3
Yes
Class 8 Tractor
-BYD 8TT
Harbor Freight Transportation
Corp
2
No
Yard tractor
N/A
Heniff Transportation Systems
Inc.
100
No
Class 8 Tractor
-Nikola Tre
Heritage Environmental
Services, LLC
100
No
Class 8 Tractor
Class 6 Box Truck
-80 Lion8
-20 Lion6
Hub Group
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Hudson County Motors Inc
4
No
Class 8 Tractor
N/A
IKEA Distribution Services
North America
5
Yes
Terminal Tractor
- Kalmar's Ottawa T2
terminal tractor
Intelligent Labor and Moving
1
Yes
Class 6 Box Truck
-SEA Electric
International Motor Freight
4
No
Yard tractors
Class 8 Tractor
N/A
Iron Mountain Information
Management Inc.
1
Yes
Class 6 Box Truck
-Freightliner eM2
J.B. Hunt
8
Partially
Class 8 Tractor
Class 6 Box Truck
Class 4 Box Truck
-1 Navistar Fuel Cell Truck
-1 Freightliner eCascadia
-1 Freightliner eM2
- 5 Mitsubishi Fuso eCanter
J&M Sanitation
2
Yes
Class 8 Refuse
-BYD 8R
Jackson Township School
District
2
No
Class 8 Refuse
N/A
Jersey City
5
No
Class 8 Refuse
-BYD 8R
Karat Packaging
10
No
Class 8 Tractor
-Tesla Semi
KeHE Distributors
2
Yes
Class 8 Tractor
-Freightliner eCascadia
King County
1
Yes
Class 8 Tractor
-Kenworth T680E
Kingbee Rentals
25
No
Class 4 Cargo Van
-Envirotech Vehicles
Knight-Swift Transportation
Holdings
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Kraft Heinz Company
3
Yes
Terminal Tractor
-Orange EV T-Series
L&R Group
50
No
Class 4 Shuttle Bus
-Phoenix Motorcars Zeus
400
Lazer Spot Inc.
25
No
Yard Tractor
-Orange EV
Lemcor Solid Waste Transfer
Station
2
No
Yard Tractor
N/A
Liberty Ashes, Inc
2
No
Class 6 Refuse
-1 Battle One Severe Duty
Refuse
-1 Battle One Crew Cab
Manhattan Beer Distributors
LLC
5
No
Class 8 Tractor
-Volvo VNR Electric truck
99
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
McLane Co Inc.
12
Yes
Terminal Tractor
Class 8 Tractor
-Orange EV Terminal Truck
-XOS HDXT
MDB Transportation
10
No
Class 6 Box Truck
-Kenworth K270E
Meijer
4
No
Class 8 Tractor
- Tesla Semi
Merchants Fleet
18,010
Partially
Class 3 Cargo Van
Class 2b Cargo Van
Class 5 Step Van
-12600 GMZevo 600
-5,400 GM Zevo 400
-10 XOS Step van
Mesa Fire and Medical
Department
1
No
Class 8 Fire engine
-E-ONE Vector fire truck
Mondelez International Inc.
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Municipality of Anchorage
Department of Solid Waste
Services
2
Yes
Class 8 Tractor
-Peterbilt Model 220EV and
Model 520EV
Murphy Road Recycling, LLC
1
No
Yard Tractor
-N/A
National Grid Service Co and
Operating Companies
TBA
No
Class 2b Van
-TBA Ford E-Transit
New Legend Inc
50
No
Class 8 Tractor
-Freightliner eCascadia
Airgas
2
No
Class 8 Tractors
-Hyzon Fuel Cell
New York City Department of
Sanitation
17
Yes
Class 8 Refuse
-Mack LR Electric
NFI Transportation
117
Yes
Class 8 Tractor
Yard Tractor
-30 Freightliner eCascadia
-27 Kalmar Ottawa Electric
T2E Terminal Tractors
-60 Volvo VNR
Pacific Gas & Electric
(PG&E)
10
No
Class 4 Step Van
-MT50e
Pan-O-Gold Baking Co.
4
No
-N/A
-N/A
Patton Logistics Group
5
No
Class 8 Tractor
-Volvo VNR
Penske Logistics
814
Partially
Class 8 Tractor
Class 6 Box Truck
Class 4 Box Truck
Class 2b van
Yard Tractor
-10 Freightliner eCascadia
-10 Freightliner eM2
-21 Freightliner
eCascadia/eM2
-4 Fuso eCanter
-2 ROUSH Ford F650
-5 Navistar International
eMV trucks
-751 Ford E-Transit
-TBA
PepsiCo Inc.
149
Partially
Class 8 Tractor
Class 6 Box Truck
Terminal Tractor
Class 2b vans
-100 Tesla semi-trucks
- 40 Ford E-Transit
Performance Team
126
No
Class 8 Tractor
-Volvo VNR Electric
PGT Trucking Inc.
100
No
Class 8 Tractor
-Nikola Tre
100
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
Phil Haupt Electric
1
Yes
Class 4 Utility Truck
-ZEUS 500 Electric Utility
Truck
Pitt Ohio Transportation
Group
6
Yes
Class 4 Box Trucks
Class 8 Tractors
Class 7 Box Trucks
-N/A
-N/A
-Vovo VNR Electric
Port of Oakland
42
Yes
Class 4 Utility Truck
Class 8 Tractor
-2 Phoenix Motorcars Zeus
500
-10 Peterbilt Model 579EV
- 30 XCIENT Fuel Cell
heavy-duty tractors
Port of San Diego
14
No
Class 3 trucks
Class 3 vans
-N/A
-N/A
Pride Group Enterprises
6,570
Partially
Class 8 Tractor
Class 3 Step Van
Class 6 Box Trucks
Class 8 Box trucks
-150 Tesla Semi
-6320 Workhorse C-1000
-100 Lion6 and Lion8 trucks
Pritchard Auto Company
500
No
Class 3 Step Van
-Workhorse C-1000
Producers Dairy Foods Inc.
2
Yes
Class 8 Tractor
-Volvo VNR
Purolator
1
Yes
Class 6 Delivery Van
-Cummins Step Van
Quality Custom Distribution
44
Yes
Class 8 Tractor
-Volvo VNR Electric
Rail Management Services
10
Yes
Yard Tractor
-Orange EV T-Series
Ramsey/Washington
Recycling & Energy
1
Yes
Yard Tractor
-Orange EV T-Series
Recology
2
Yes
Class 8 Refuse
-BYD 8R
Red Hook Terminals LLC
10
Yes
Yard tractors
-BYD 8Y
Regional Industries LLC
5
No
Class 8 Refuse
N/A
Republic National
Distributing Company
5
No
Class 7 Tractor
-XOS MDXT
Republic Services Inc.
1
Yes
Class 8 Refuse
-Mack LR Electric
Reyes Holdings and Operating
Companies
30
No
Class 8 Tractor
-Tesla Semi
Ruan
8
Partially
Terminal Tractor
Class 8 Tractor
-3 Orange EVs
-5 Tesla semi-trucks
Ryder System, Inc.
6
Partially
Class 5 Cargo Van
Class 6 Box Truck
Class 8 Tractor
-1 Freightliner eM2
-1 Freightliner eCascadia
-4 N/A
Sacramento County
2
Yes
Class 8 Refuse
-ElecTruck
Sacramento Municipal Utility
District
5
Yes
Class 3 Work Truck
-Zeus Electric Work Truck
Saia Inc.
103
Yes
Class 8 Tractor
Class 6 Box Truck
-2 VNR Electric trucks
-1 Freightliner eM2
-100 Nikola Tre
Santa Barbara Public Library
1
Yes
Class 4 Step Van
-Ford F-450 Retrofit
Schneider National Inc.
50
Yes
Class 8 Tractor
-Freightliner eCascadia
101
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
Shippers Transport Express
Inc.
15
No
Class 8 Tractor
-Peterbilt Model 579EV
Sonwil Distribution Center, In
1
Yes
Yard Tractor
-Orange EV T-Series
Southern California Edison
Co.
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Southern Counties Express
1
Yes
Class 8 Tractor
-Toyota (Kenworth) T680E
Staples Inc.
1
Yes
Class 5 Box Truck
-SEA Hino 195 EV
Stolt Trucking, Inc.
3
No
-N/A
-N/A
Sunbelt Rentals Inc.
5
Yes
Class 8 Tractor
-Peterbilt Model 579EV
Super Store Industries
1
Yes
Yard Tractor
-Orange EV T-Series
Sysco and Operating
Companies
851
Partially
Class 8 Tractor
-50 Tesla semi-trucks
-801 Freightliner eCascadia
Tacoma Harbor
6
No
Yard Tractor
-N/A
Temco Logistics
1
Yes
Class 6 Box Truck
-Freightliner eM2
Terminal Consolidation Co
1
Yes
Terminal Tractor
-Orange EV T-Series
The Kroger Co.
10
No
Class 8 Tractor
-Tesla semi-trucks
The Los Angeles City Fire
Department
1
Yes
Class 8 Fire engine
-Rosenbauer RTX Fire
Truck
Titan Freight
4
No
Class 8 Tractor
-Freightliner eCascadia
Toms River Township
1
No
Class 8 Refuse
N/A
Total Transportation Services
104
Partially
Class 8 Tractor
Class 8 Drayage
-2 Toyota (Kenworth)
T680E
-100 Nikola Tre
-1 TranspowerFuel Cell
-1 U.S. Hybrids Fuel Cell
Town of Cary
1
No
Class 8 Refuse
-N/A
Town of North Stonington
1
No
Class 8 Refuse
-N/A
Town of West New York
4
No
Class 8 Garbage trucks
Class 4 Shuttle buses
N/A
Township of Woodbridge
5
No
Class 8 Refuse
Class 4 Shuttle buses
N/A
Two Men and a Truck
Columbus
1
No
Class 6 Box Truck
-SEA Electric Conversion
UniFirst Corp.
3
Yes
Class 5 step van
-Xos Medium Duty
UPS Inc.
12,635
Partially
Class 8 Tractor
Class 6 Delivery Van
Class 6 Box Truck
Class 4 Step Van Retrofit
Class 4 Step Van
Class 4 Cargo Van
Class 3 Step Van
-4 Fuel Cell Electric Vehicle
Delivery Van
-3 Toyota (Kenworth)
T680E
-N/A Xos Medium Duty
-1000 Workhorse C1000
-125 Tesla Semi
-10000 Arrival Van
-2 Fuso eCanter
-1 Freightliner eCascadia
- 1500 Unique Electric
Solutions
102
-------
Fleet
EVs Deployed
/ Ordered
Vehicles
Delivered
Vehicle Type
Vehicle Model
US Foods
30
Yes
Class 8 Tractor
Class 6 Box Track
-Freightliner eCascadia
-Freightliner eM2
USA Truck Inc.
10
No
Class 8 Tractor
-10 Nikola Tre
USPS
10,034
Yes
Class 3 Step Van
Class 4 Step Van
-8 Cummins
-7 Motiv E-450
-10,019 Oshkosh Defense
Next Generation Delivery
Vehicle
Valley Malt
1
Yes
Class 2b
-Ford E-Transit
Velocity Track Rental &
Leasing
1
Yes
Class 8 Tractor
-Freightliner eCascadia
Wakefern Food Corp.
4
No
Terminal Tractor
N/A
Walmart Inc.
6,110
No
Class 3 Cargo Van
Class 2b Van
-5000 GM Zevo 400 and
Zevo 600 Cargo Van
-1110 Ford E-Transit
Waste Connections and
Operating Companies
2
yes
Class 8 Refuse
-Lion 8R
Waste Resource Technology,
Inc.
1
Yes
Class 8 Refuse
-BYD 8R
Watsontown Trucking
Company
1
No
Class 8 Tractor
-Volvo VNR
WattEV
50
No
Class 8 Tractor
-Volvo VNR
Werner Enterprises
1
Yes
Class 8 Tractor
-Peterbilt 579EV
XPO Logistics
102
Partially
Class 8 Tractor
Class 6 Box Track
Class 4 Box Track
-1 Freightliner eCascadia
-1 Freightliner eM2
-100 CityFreighter CF1
Yellow Corp. (YRC Freight)
4
Yes
Terminal Tractor
-Orange EV
Estes
12
No
Class 8 Tractor
-Freightliner eCascadia
XL Fleet
1
Yes
Class 6 Refuse Track
-Curbtender
Giant
2
Yes
Class 5 Step Van
-Motiv F-59
Xcel Energy
2
No
Class 8 Bucket Track
-Terex Optima 55
Oatly
5
No
Class 8 Tractor
-Einride AB
Paterson Fire Department
2
No
Class 6 Ambulance
-Demers eFX Prototype
Ambulances
RoadOne
1
Yes
Class 8 Tractor
-Nikola Tre
United Rental
30
No
Class 2b Cargo Van
-Ford E-Transit
GE Appliance
N/A
No
N/A
N/A
Sunburst Track Lines
1
Yes
Class 8 Drayage
-Nikola
Zeem Solutions
10
No
Class 5 Stepvan
-XOS Stepvan
City of Mobile
1
No
Class 8 Refuse
-Mack LR Electric
City of Gilbert
1
No
Class 8 Fire Track
-Pierce Manufacturing
Volterra
Altec
1
Yes
Class 8 Bucket Track
-Navistar eMV
Michigan State University
18
No
Class 2b
-Ford e-Transit
Wegmans
9
No
Yard Tractor
-N/A
Beyond Meat
5
No
Class 8 Tractor
-Einride AB
103
-------
1.5.5.2 BEV Components Manufacturers
A small number of HD ICE vehicle component suppliers and startups have developed
components specifically for HD BEVs. See Table 1-25 for a partial list of manufacturers of HD
BEV components.
Table 1-25 Manufacturers of HD BEV Components
Component
Manufacturers
Low Voltage Battery
Same manufacturers as for ICE vehicles432
Charge Port
ITT Cannon, Phoenix Contact, TE Connectivity
DC/DC Converter
Borg Warner, Eaton, EG Tronics, InMotion
Traction Motor
BAE, Borg Warner, Cummins, Dana, Lightning Systems, Meritor, Proterra,
SEA Drive, Siemens, ZF
Onboard Charger
Borg Warner, Dana, Eaton
Power Electronics Controller
Borg Warner, EG Tronics
Thermal System
Same manufacturers as for ICE vehicles433
Traction Battery Pack
Borg Warner, CATL, Cummins, Dana, LG Chem, Panasonic, Proterra,
Samsung SDI, Tesla, Volvo, XALT
Transmission
Eaton
Aux System - Air Conditioner
Compressor
Guchen, Rheinmetal
Aux System - Heater
Guchen, Rheinmetal, Webasto
Aux System - Blower
Same manufacturers as for ICE vehicles434
Aux System - Power Steering
Pump
Allied Motion, Bosch, HydraPulse, ZF
Aux System - Air Compressor
Hydrovane, Ingersoll Rand, Wabco
Auxiliary Power Unit (APU)
Carrier, Go Green APU, Phillips & Temro, Thermo King
1.5.6 BEV Research and Development
DOE has a Vehicle Technologies Office focused on research, development, and
demonstration of electrification technologies across sectors, including transportation. Through
the 21st Century Truck Partnership, DOE is collaborating with truck manufacturers, major
suppliers, and interagency partners to focus on removing barriers to wide-scale truck
electrification. They are working directly with industry through SuperTruck 3 to reduce
emissions of freight transportation, with the projects listed in Table l-26awarded for 2022
through 2026 focused on HD BEVs.435
432 Manufacturers of Low Voltage Batteries includes Alliance and East Penn
433 Manufacturers of Thermal Systems includes American Radiator, AP Air Inc, and CoolStar
434 Manufacturers of Aux System - Blower includes Four Seasons, Mahle, TYC, UAC, and Valeo
435 U.S. Department of Energy. "DOE Projects Zero Emissions Medium- and Heavy-Duty Electric Trucks Will Be
Cheaper than Diesel-Powered Trucks by 2035". March 2022. Available online:
https://www.energy.gov/articles/doe-projects-zero-emissions-medium-and-heavy-duty-electric-trucks-will-be-
cheaper-diesel.
104
-------
Table 1-26 DOE Funded BEV Projects Awarded in 2022436
Company
Project Description
Award Amount*
PACCAR Inc
Develop eighteen Class-8 battery electric and fuel cell vehicles
with advanced batteries and a megawatt charging station will also
be developed and demonstrated.
$32,971,041
Volvo Group North
America, LLC
Develop 400-mile range Class 8 battery electric tractor-trailer as
well as megawatt charging station.
$18,070,333
General Motors, LLC
Develop and demonstrate four hydrogen fuel cell and four battery
electric Class 4-6 trucks. The project will also focus on
development of clean hydrogen via electrolysis and clean power
for fast charging
$26,061,726
* Subject to appropriations.
1.6 BEV Charging Infrastructure
1.6.1 Overview of BEV Charging Infrastructure
The work performed by heavy-duty vehicles has been described in Chapter 1.5 of this
document. HD BEVs require electricity for charging their batteries before work can be
performed. It is necessary for this electric power be delivered at the appropriate time, rate, and
location such that business or other operational needs are met. This section provides an overview
of BEV charging infrastructure today; upcoming infrastructure investments; and considerations,
challenges and costs associated with future infrastructure needs for HD BEVs.
1.6.1.1 Definitions
BEV charging infrastructure consists of the equipment (hardware and software) used to
charge an electric vehicle. Terminology for charging infrastructure varies in the literature, with
terms like "charger", "plug", "outlet", and "port" sometimes being used interchangeably.437 In
this RIA, we generally use the following terminology, which is consistent with DOE's
Alternative Fuels Data Center.438 A station is the physical location where charging occurs. A
station may have multiple electric vehicle supply equipment (EVSE) ports that provide
electricity to a vehicle.439 The number of vehicles that can simultaneously charge at the station is
equal to the number of EVSE ports. Each port may also have multiple connectors or plugs to
accommodate vehicles that use different connector types, but each port can charge just one
vehicle at a time. The relationship between a station, EVSE ports, and connectors is shown in
Figure 1-14.440
436 U.S. Department of Energy. "DOE Announces Nearly $200 Million to Reduce Emissions From Cars and Trucks.
November 1, 2021. Available online: https://www.energy.gov/articles/doe-announces-nearly-200-million-reduce-
emissions-cars-and-trucks.
437 Except where noted, when citing external studies, we attempt to map the terms used in the study to those we
define above for consistency.
438 U.S. Department of Energy. Alternative Fuels Data Center. "Electric Vehicle Charging Stations". Available
online: https://afdc.energy.gov/fuels/electricity_stations.html.
439 EVSE ports may be part of a wall-mounted unit or on a pedestal in the ground.
440 Ibid.
105
-------
One Station
EVSE Port - equipment that can charge one vehicle
Connectors - may have one or more per port
Figure 1-14 Example charging station with four EVSE ports and six connectors
We do not include electric power infrastructure—power generation, transmission, and
distribution systems—in our definition of BEV charging infrastructure. We discuss the
relationship between BEV charging infrastructure and electric power infrastructure in Chapters
1.6.4 and 1.6.5.
1.6.1.2 Types of EVSE Ports and Connectors
EVSE ports vary by power type and power level. There are two power types: alternating
current (AC) charging, where AC-to-direct current (DC) conversion takes place on-board the
vehicle, and DC fast charging (DCFC), where AC-to-DC conversion takes place prior to entering
the vehicle. Both AC charging and DCFC are further delineated by different power outputs,
though generally DCFC offers higher power and therefore faster charging times. Common AC
charging types are Level 1 (up to about 2 kilowatt (kW))441 and Level 2 (up to 19.2 kW),442
though there is also a standard for higher-powered AC charging.443 DCFC is available today in a
wide range of power levels (e.g., 50-350 kW). Most vehicle models currently use the SAE J1772
standard connector for Level 1 and 2 charging.444 There are multiple connectors for DCFC,
including Combined Charging System (CCS), CHAdeMO, and the North American Charging
441 Schey, Stephen. Kang-Ching Chu, and John Smart. 2022. "Breakdown of Electric Vehicle Supply
Equipment Installation Costs. Idaho National Laboratory." Available online:
https ://inldigitallibrary. inl.gov/sites/sti/sti/Sort_63124.pdf.
442 U.S. Department of Energy. Alternative Fuels Data Center. "Electric Vehicle Charging Stations". Available
online: https://afdc.energy.gov/fuels/electricity_stations.html.
443 SAE. "SAE International Releases New Specification (SAE J3068) for Charging of Medium and Heavy Duty
Electric Vehicles". April 26, 2018. Available online: https://www.sae.org/news/press-room/2018/04/sae-
international-releases-new-specification-sae-j3068-for-charging-of-medium-and-heavy-duty-electric-vehicles.
444 Tesla vehicles use the NACS connector for AC charging, though a J1772 adapter is available.
106
-------
Standard (NACS) connector445 developed by Tesla.446'447 OEMs producing HD BEVs may also
use proprietary connectors.448
How much time it takes a vehicle to charge will vary significantly based on the power level of
the EVSE port and the amount of electricity (kWh) needed, among other factors. For example,
using a 19.2 kW-rated Level 2 port, it will take longer than three hours to add 60 kWh449, which
we assessed as the amount of electricity that would be sufficient for many Class 4-5 Step Vans
on most days. By contrast, it may take under one-and-a-half hours using DCFC-50 kW and just
under 30 minutes with DCFC-150 kW. In this example, Level 2 charging would be sufficient
provided the vehicle has the necessary three or more hours to charge. Otherwise, DCFC may be
needed. (See also further discussion regarding dwell times for charging in Chapter 2.6). Level 1
charging in this same example could take over 30 hours, illustrating that Level 1 may not be
practical for HD BEV applications and therefore are not part of EPA's analysis of the costs of
the Phase 3 rule. For this reason, we focus the remainder of our infrastructure discussion and
analysis on AC Level 2 and DCFC ports.
A standard for even higher-powered DCFC, the Megawatt Charging System (MCS), is
currently under development and being advanced by the National Renewable Energy Laboratory
(NREL), the Charging Interface Initiative (CharIN), and others.450 The MCS standard (expected
to be finalized in 2024) has a potential charge rate of 3.75 MW.451 An MCS system from ABB
E-Mobility was tested with a Scania electric truck as part of a pilot this year; ABB is planning
commercial release as early as 2024.452 Daimler Truck North America and Portland General
Electric opened a megawatt-level charging for HD BEVs at the "Electric Island" station near
Daimler's North American headquarters, with most of the eight chargers available for public
445 The NACS connector began as a proprietary standard. It is currently undergoing the standardization process by
SAE.
446 U.S. Department of Energy. Alternative Fuels Data Center. "Electric Vehicle Charging Stations". Available
online: https://afdc.energy.gov/fuels/electricity_stations.html.
447 SAE. "SAE International Announces Standard for NACS Connector, Charging PKI and Infrastructure
Reliability". June 27, 2023. Available online: https://www.sae.org/news/press-room/2023/06/sae-international-
announces-standard-for-nacs-connector.
448 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". Available
online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-infrastructure-
assessment-ab-2127. See Commission Report (July 2021).
449 Charging rate may also vary based on the state of charge of the battery, e.g., by slowing down when the battery is
nearly full. In these examples (intended to be illustrative), we assume charging occurs at or near the stated power of
the EVSE.
450 National Renewable Energy Laboratory (NREL). "Industry Experts, Researchers Put Charging Systems for
Electric Trucks to the Test". August 30, 2021. Available online: https://www.nrel.gov/news/program/2021/industry-
experts-researchers-put-charging-systems-for-electric-trucks-to-test.html.
451 Kane, Mark. "CharIN Officially Launches The Megawatt Charging System (MCS)". Inside EVs. June 15, 2022.
Available online: https://insideevs.com/news/592360/megawatt-charging-system-mcs-launch/.
452 Manthey, Nora. "Scania tests ABB's megawatt charging system for next-gen electric trucks". Electrive. October
5, 2023. Available online: https://www.electrive.eom/2023/05/10/scania-tests-abbs-megawatt-charging-system-for-
next-gen-electric-trucks/.
453 Daimler Truck North America. "Daimler Trucks North America, Portland General Electric open first-of-its-kind
heavy-duty electric truck charging site." April 2021. Available online:
https://northamerica.daimlertruck.eom/PressDetail/daimler-trucks-north-america-portland-general-2021-04-21/
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Other charging methods that could become more common in the future include wireless and
pantograph charging. With wireless charging (covered by the SAE J2954/2 standard454) a vehicle
is parked above a charging pad and power is transferred via induction to charge the battery.455
For pantograph charging systems (covered by the SAE J3105/2 standard456), structures on top of
the HD vehicle roof connect to overhead charging. HD BEVs may be able to charge via
pantograph while parked overnight or at critical locations on their routes.457 Since these
pantograph systems can supply power en-route, the truck battery can potentially be downsized,
keeping cost and weight down while allowing space for additional cargo. Prototype systems
exist in Europe and development is underway by Siemens Mobility, Continental Engineering
Services, Webasto, and RWTH Aachen University.458'459
1.6.1.3 Types of Charging Stations
While charging stations may be deployed in a wide variety of locations and configurations
based on future needs, for our purposes, we broadly categorize charging as either depot or en-
route charging. Depot stations may be at warehouses, yards, distribution centers, secure lots, or
other locations where the vehicles are parked off shift. HD vehicles with return-to-base
operations, in which vehicles return to a centralized location to park overnight, may be
particularly well suited for depot charging. As described in Chapter 2.6, we anticipate that many
heavy-duty BEV owners will opt to purchase and install sufficient EVSE ports for depot
charging at or near the time of vehicle purchase to ensure operational needs are met. We expect
many depot stations to be privately owned or operated for fleets.
En-route charging allows vehicles to charge during their shift or on the way to their next
location. We expect many en-route charging stations to be publicly accessible and for simplicity
we refer to en-route charging as public charging throughout this document. However, we note
that some en-route charging may also occur at privately owned and operated stations. We project
that BEV sleeper cab tractors, coach buses, and certain day cab tractors, will utilize public
charging in our modeled potential compliance pathway supporting the standards' feasibility. See
RIA Chapter 2.6.
454 SAE International. "Wireless Power Transfer for Heavy-Duty Electric Vehicles". December 16, 2022. Available
online: https://www.sae.org/standards/content/j2954/2_202212/.
455 Oak Ridge National Laboratory. "Successful delivery: ORNL demonstrates bi-directional wireless charging on
hybrid UPS truck". April 21, 2020. Available online: https://www.ornl.gov/news/successful-delivery-ornl-
demonstrates-bi-directional-wireless-charging-hybrid-ups-truck.
456 SAE International. "Electric Vehicle Power Transfer System Using Conductive Automated Connection Devices
Vehicle-Mounted Pantograph (Bus-Up)". January 20, 2020. Available online:
https://www.sae.org/standards/content/j3105/2_202001/.
457 Transport for London. "New rapid, wireless bus charging technology introduced as part of the capital's journey
to zero emission". October 26, 2022. Available online: https://tfl.gov.uk/info-for/media/press-
releases/2022/october/new-rapid-wireless-bus-charging-technology-introduced-as-part-of-the-capital-s-journey-to-
zero-emission.
458 Randall, Chris. "Continental & Siemens to cooperate on truck pantographs". ElectricDrive.com. July 29, 2021.
Available online: https://www.electrive.com/2021/07/29/continental-siemens-to-cooperate-on-truck-pantographs/.
459 Webasto. "E-Truck with pantograph: Webasto supports pioneering pilot project". August 29, 2022. Available
online: https://www.automotiveworld.com/news-releases/e-truck-with-pantograph-webasto-supports-pioneering-
pilot-project/.
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1.6.2 Status and Outlook of BEV Charging Infrastructure
1.6.2.1 Stations and EVSE Ports Available Today
DOE's Alternative Fuels Data Center (AFDC) Station Locator provides counts of charging
stations and EVSE ports. These counts show the rapid growth in overall charging infrastructure
in recent years. There are over 60,000 public charging stations in the U.S. today with more than
160,000 EVSE ports.460'461 This is more than double the 74,000 EVSE ports as of the end of
2019.462 Table 1-27 shows the breakdown in U.S. public stations and EVSE ports as of February
18, 2024, for Level 2 and DCFC charging.463
Table 1-27 Public Charging Stations and EVSE Port Counts
Type
Stations464
EVSE Ports
Level 2
53,482
124,396
DCFC
9,278
39,347
However, it is important to note that many of these stations may not be designed to
accommodate large vehicles. For example, stations designed for HD vehicles may require more
space for ingress and egress, higher canopies or roofs that can fit tall cargo boxes, and longer
charging cords. Stations may also not be designed to commingle passenger cars with trucks and
buses.465 Notwithstanding those limitations, some stations designed for light-duty vehicles may
be able to accommodate (or be modified in the future to accommodate) medium-duty or small
heavy-duty vehicles and so we include discussion of them here. As previously noted, AC Level 1
ports are less likely to meet HD BEV needs so they are not included in these counts. As
discussed in Chapter 1.6.1.2 of this document, there is no universal connector type for DCFC at
this time, so the number of stations and ports that can serve a given vehicle may be lower than
what is shown in Table i_27.466'467
In addition to public charging infrastructure, the AFDC Station Locator includes counts of
private EVSE ports used by fleets. Collecting information on private ports is challenging and the
data set is not complete. For the private port data that has been collected as of the third calendar
460 U.S. Department of Energy. Alternative Fueling Station Locator. Alternative Fuels Data Center. Available
online: https://afdc.energy.gov/stations/#/analyze?country=US&fuel=ELEC.
461 If we include EVSE ports that are temporarily unavailable for maintenance or other short-term causes, the
number of ports is over 170,000.
462 U.S. Department of Energy, Alternative Fuels Data Center. U.S. Public Electric Vehicle Charging Infrastructure.
2023. Available online: https://afdc.energy.gov/data/10972.
463U.S. Department of Energy. Alternative Fueling Station Locator. Alternative Fuels Data Center. Available online:
https://afdc.energy.gov/stations/#/analyze?country=US&fuel=ELEC.
464 Stations with both L2 and DCDC ports are listed in both rows.
465 While the downloadable data for AFDC Station Locator includes a field designating the largest class of vehicle
that can access a station, many public stations in the data set have no such identifier.
466 Adapters are available that allow Tesla vehicles (which use NACS connectors) to plug into J1772/CCS (and
CHAdeMO) ports. Most stations in the U.S. have either a J1772/CCS or a NACS connector.
467 DOE, Alternative Fuels Data Center. "Electric Vehicle Charging Stations." Available at:
https://afdc.energy.gov/fuels/electricity_stations.html.
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quarter of 2023,468 NREL reports that about 44% of the private EVSE ports were used primarily
for fleets.469 Figure 1-15 shows a breakdown of AC Level 2 and DCFC private fleet EVSE ports
in the Station Locator by vehicle type.470 471 NREL notes that efforts are underway to increase
data collection for private fleets including school buses, transit buses, and other fleets serving
MD and HD vehicles.
Figure 1-15 Private Fleet Level 2 and DCFC Ports (Data Source: AFDC Station Locator as shown in Brown
et al. 2024472)
We also note that there are a variety of charging stations for heavy-duty vehicles that are
planned or in development, as discussed in the following section, and these would not yet be
reflected in the Station Locator.
1.6.2.2 Charging infrastructure Investments and Outlook
While dedicated HD charging infrastructure may be limited today, we expect it to expand
significantly over the next decade. A recent assessment by Atlas Public Policy estimated that $30
billion in public and private investments had been committed as of the end of 2023 specifically
468 Among the private ports in the AFDC Station Locator, information on fleet use and vehicle classes was collected
for about 88% of ports.
469 Brown, Abby, Jeff Cappellucci, Alexia Heinrich, and Emma Cost. "Electric Vehicle Charging Infrastructure
Trends from the Alternative Fueling Station Locator: Third Quarter 2023." Golden, CO: National Renewable
Energy Laboratory. NREL/TP-5400-88223. 2024. Available online: https://www.nrel.gov/docs/fy24osti/88223.pdf.
4711 Multiple vehicle types (e.g., LD, MD, or HD) may use the same EVSE stations or ports. Categorizations in the
chart reflect the largest class of vehicle that can use a given station.
471 The NREL report also includes private fleet Level 1 EVSE ports. We did not include these in the figure.
472 Ibid.
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for charging infrastructure for medium- and heavy-duty BEVs.473 The U.S. government is
making large investments in charging infrastructure through the BIL474 and the IRA,475 as
discussed in Chapter 1.3.2 of this document. This includes extending and modifying a tax credit
that could cover up to 30% of the costs for procuring and installing certain charging
infrastructure (subject to a $100,000 per item cap) and billions of dollars in funding programs
that could support charging infrastructure either on its own or alongside the purchase of a HD
BEV.
Private investments will also play a critical role in meeting future infrastructure needs. Much
of this will likely be charging infrastructure purchased by individual BEV or fleet owners for
depot charging. (See Chapter 2.6 of this document for information on our analysis of depot
charging needs and costs.) However, vehicle manufacturers, charging network providers, energy
companies and others are also investing in public or other stations that could support public
charging.
Several projects aim to offer public charging for electric trucks or other commercial vehicles.
For example, Daimler Truck North America is involved in Greenlane, an initiative in the U.S.
with electric power generation company NextEra Energy Resources and BlackRock Renewable
Power to collectively invest $650 million to create a nationwide charging network for
commercial electric vehicles.476 They plan to start with construction in Southern California in
early 2024 and expand to cover key routes on the East and West Coast and in Texas with a later
stage of the project also supporting hydrogen fueling stations.477 Volvo Group and Pilot
announced their intent to offer public charging for medium- and heavy-duty BEVs at priority
locations throughout the network of 750 Pilot and Flying J North American truck stops and
travel plazas478'479 In 2022, TeraWatt secured over $1 billion in capital to build public charging
stations and turnkey infrastructure solutions480 in 19 states and acquired land for 7 charging
stations along a freight corridor that connects California's Port of Long Beach with El Paso,
473 Lepre, Nicole. "Estimated $30 Billion Committed to Medium- and Heavy-Duty Charging Infrastructure in the
United States." Atlas Public Policy. EVHub. January 26, 2024. Available online:
https://www.atlasevhub.com/data_story/estimated-30-billion-committed-to-medium-and-heavy-duty-charging-
infrastructure-in-the-united-states/.
474 Infrastructure Investment and Jobs Act, Pub. L. No. 117-58, 135 Stat. 429 (2021). Available online:
https://www.congress.gOv/l 17/plaws/publ58/PL AW-117publ58.pdf.
475 Inflation Reduction Act, Pub. L. No. 117-169, 136 Stat. 1818 (2022). Available online:
https://www.congress.gOv/l 17/plaws/publl69/PLAW-l 17publl69.pdf
476 NextEra Energy. News Release: "Introducing Greenlane: Daimler Truck North America, NextEra Energy
Resources and BlackRock Forge Ahead with Public Charging Infrastructure Joint Venture." April 28, 2023.
Accessible online: https://newsroom.nexteraenergy.com/2023-04-28-Introducing-Greenlane-Daimler-Truck-North-
America,-NextEra-Energy-Resources-and-BlackRock-Forge-Ahead-with-Public-Charging-Infrastructure-Joint-
Venture?l=12.
477 Greenhalgh, Keiron. "Greenlane to Break Ground on Charging Network in Early 2024". October 4, 2023.
Available online: https://www.ttnews.com/articles/greenlane-charging-2024.
478 Adler, Alan. "Pilot and Volvo Group add to public electric charging projects". FreightWaves. November 16,
2022. Available online: https://www.freightwaves.com/news/pilot-and-volvo-group-add-to-public-electric-charging-
projects.
479 Kane, Mark. "Pilot and Flying J Stations To Get Fast Chargers for EV Trucks". InsideEVs. December 30, 2022.
Available online: https://insideevs.com/news/628605/pilot-stations-fast-chargers-ev-trucks/.
480 TW. "TeraWatt Raises Over $1 Billion to Scale Commercial EV Charging Centers Across America". September
13, 2022. Available online: https://terawattinfrastructure.com/ideas/terawatt-raises-over-l-billion-to-scale-
commercial-ev-charging-centers-across-america/.
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Texas.481 In late 2023, they broke ground on a site in the ports area of South Los Angeles with
20 pull-through stalls for up to 125 trucks per day, scheduled to be operational in 2024.482 Two
sites in California's Inland Empire region to support up to 500 trucks per day are scheduled to
open in 2025.483 Tesla is developing charging equipment for their semi-trucks that will recharge
up to 70 percent of the Tesla semi-truck's 500-mile range in 30 minutes.484
Fleets are installing chargers. IKEA is collaborating with Electrify America and its business
unit, Electrify Commercial, to install over 200 150-kW and 350-kW fast chargers for public use
and delivery fleets at 25 retail locations in 18 states by the end of 2023.485 Amazon says it has
already deployed thousands of chargers for its fleet of electric delivery vans at over 100 sites
nationwide.486 Amazon has also installed close to 300 chargers for HD BEVs.487 Walmart
announced plans to grow their network of 1,300 fast chargers at more than 280 locations to
thousands at Walmart and Sam's Club locations from coast-to-coast by 2030.488 FedEx is also
installing charging infrastructure, and has already deployed 500 chargers at its California
facilities.489
Other investments will support regional or local travel needs. For example, in California,
Forum Mobility announced a $400 million investment led by CBRE Investment Management for
DCFCs for BEV trucks that are planned for operation at the San Pedro and Oakland ports.490'491
The company received an additional $100 million from Homecoming Capital. They are building
seven stations by the end of 2024 plus two stations in 2025 with a total of more than 700
chargers. By the end of 2027, they plan to install charging at another 15 sites to service 1,900
481 Marshall, Aarian. "The Trans-American Race to Build Chargers for Electric Trucks". March 28, 2023. Wired.
Available online: https://www.wired.com/story/the-trans-american-race-to-build-chargers-for-electric-trucks/
482 Morris, Charles. "TeraWatt Infrastructure breaks ground on heavy-duty EV charging site near Port of Long
Beach". Charged. November 29, 2023. Available online: https://chargedevs.com/newswire/terawatt-infrastructure-
breaks-ground-on-heavy-duty-ev-charging-site-near-port-of-long-beach/.
483 Greenhalgh, Keiron. "TerraWatt Buys Two California Sites for Heavy-Duty EV Charging: Facilities to be
Operational in 2025". Transport Topics. October 23, 2023. Available online:
https://www.ttnews.com/articles/terawatt-california-ev-charge.
484 Tesla. "Semi: The Future of Trucking is Electric." Available online: https://www.tesla.com/semi.
485 Electrify America. "IKEA U.S. and Electrify America announce collaboration for ultra-fast public and fleet
charging at over 25 IKEA retail locations". Available online: https://media.electrifyamerica.com/en-us/releases/191.
486Amazon staff. "Everything you need to know about Amazon's electric delivery vans from Rivian." October 17,
2023. Available online: https://www.aboutamazon.com/news/transportation/everything-you-need-to-know-about-
amazons-electric-delivery-vans-from-rivian.
487 Keith, Scott. "Amazon adds 5,000th Rivian electric delivery van to U.S. fleet". FleetOwner. July 18, 2023.
Available online: https://www.fleetowner.com/emissions-efficiency/media-gallery/21269714/amazon-now-has-
5000-rivian-electric-delivery-vans-in-us-fleet.
488 Kapadia, Vishal. "Leading the Charge: Walmart Announces Plans to Expand Electric Vehicle Charging
Network." April 6, 2023. Available online: https://corporate.walmart.com/news/2023/04/06/leading-the-charge-
walmart-announces-plan-to-expand-electric-vehicle-charging-network.
489 Sickels, David. "Brightdrop produces 150 electric delivery vans for FedEx Fleet". August 10, 2022. Available
online: https://www.thebuzzevnews.com/brightdrop-electric-vans-fedex/.
490 Joint Office of Energy and Transportation. "Private Sector Continues to Play Key Part in Accelerating Buildout
of EV Charging Networks." February 15, 2023. Available online: https://driveelectric.gov/news/private-
innvestment.
491 Margaronis, Stas. "Backed by Amazon & CBRE, Forum Mobility is building harbor truck charging stations in
California". American Journal of Transportation. April 4, 2023. Available online:
https://www.ajot.com/insights/full/ai-backed-by-amazon-cbre-forum-mobility-is-building-harbor-truck-charging-
stations-in-california.
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trucks.492 Forum Mobility also received $4.5 million to build a BEV charging depot in
Livermore, CA, as part of a network of chargers for drayage trucking carriers moving freight.493
Logistics and supply chain corporation NFI Industries is partnering with Electrify America to
install 34 DCFC ports (150 kW and 350kW) to support their BEV drayage494 fleet that will
service the ports of LA and Long Beach.495 In El Monte California, Schneider National has
installed a 4.8 megawatt station with 16 EV chargers that can each charge two HD BEVs.496'497
With funding from California, Volvo is partnering with Shell Recharge Solutions and three truck
dealerships to deploy five publicly accessible charging stations by 2023 that will serve medium-
and heavy-duty BEVs in southern California between ports and industrial centers.498
Outside of California, DTNA is working with the State of Michigan and DTE to develop a
truck stop charging station in Michigan that could serve as a prototype for broader truck stop
deployment.499 Voltera aims to build a BEV charging station in Garden City, GA,500 and has
committed billions to developing sites in the U.S.501 One Energy recently announced the
energization of a 30 megawatt charging hub intended to service multiple HD BEV fleet operators
in Findlay, Ohio; the site has the capacity to charge 90 trucks at the same time.502'503
492 Margaronis, Stas. "Backed by Amazon & CBRE, Forum Mobility is building harbor truck charging stations in
California". American Journal of Transportation. April 4, 2023. Available online:
https://www.ajot.com/insights/full/ai-backed-by-amazon-cbre-forum-mobility-is-building-harbor-truck-charging-
stations-in-california.
493 East Bay Community Energy. "East Bay Community Energy and Forum Mobility Announce Innovative
Financing for First of Its Kind Electric Truck Charging Depot in Livermore". PR Newswire. Available online:
https://www.prnewswire.com/news-releases/east-bay-community-energy-and-forum-mobility-announce-innovative-
financing-for-first-of-its-kind-electric-truck-charging-depot-in-livermore-301849030.html.
494 Drayage trucks typically transport containers or goods a short distance from ports to distribution centers, rail
facilities, or other nearby locations.
495 NFI. "Electrify America and NFI Industries Collaborate on Nation's Largest Heavy-Duty Electric Charging
Infrastructure Project." September 1, 2021. Available online: https://www.nfiindustries.com/about-nfi/news/nations-
largest-electric-truck-charging-infrastructure-project/.
496 Carpenter, Susan. "New charging depot can power 32 heavy-duty electric trucks at the same time". Spectrum
News. June 7, 2023. Available online: https://spectrumnewsl.com/ca/la-west/environment/2023/06/07/new-
charging-depot-can-power-32-heavy-duty-electric-trucks-at-the-same-time
497 Adler, Alan. "Megawatt charging for electric trucks arriving in small loads". June 9, 2023. Available online:
https://www.freightwaves.com/news/megawatt-charging-for-electric-trucks-arriving-in-small-loads.
498 Borras, Jo. "Volvo Trucks Building an Electric Semi Charging Corridor". CleanTechnica. July 16, 2022.
Available online: https://cleantechnica.com/2022/07/16/volvo-trucks-building-an-electric-semi-charging-corridor/.
499 Daimler Trucks North America Press Release. "State of Michigan partners with Daimler Truck North America
and DTE Energy to build Michigan's 'truck stop of the future." June 29, 2023. Available online:
https://northamerica.daimlertruck.com/pressdetail/state-of-michigan-partners-with-daimler-2023-06-29/
500 Guan, Nancy. "EVs trucks are coming to Georgia Ports. A charging station is planned for Garden City".
Savannah Morning News. Available online: https://www.savannahnow.com/story/news/2023/05/29/ev-truck-
charging-station-garden-city/70254024007/.
501 Voltera. "Voltera Launches as Turnkey Charging Infrastructure Solution for Companies Operating EVs, with
Plans for Multibillion-Dollar Investment". Globe Newswire. August 9, 2022. Available online:
https://www.globenewswire.com/news-release/2022/08/09/2495043/0/en/Voltera-Launches-as-Turnkey-Charging-
Infrastructure-Solution-for-Companies-Operating-EVs-With-Plans-for-Multibillion-Dollar-Investment.html.
502 BusinessWire. "One Energy Energizes the Largest Electric Semi-Truck Charging Site in US at 30 MW Megawatt
Hub Site in Ohio". October 9, 2023. Available online:
https://www.businesswire.com/news/home/20231009589668/en/.
503 HDT Truckinginfo. "Megawatt Truck Charging Hub in Ohio". October 12, 2023. Available online:
https://www.truckinginfo.com/10207881/megawatt-truck-charging-hub-opens-in-ohio.
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A variety of solutions are being offered for, or explored by, fleets. For example, WattEV is
planning a network of public charging depots connecting ports to warehouses and distribution
centers as part of its "Truck-as-a-Service" model, in which customers pay a per mile rate for use
of, and charging for, a HD electric truck.504 They opened a five megawatt public truck charging
station that can charge 26 trucks simultaneously at the Port of Long Beach in 20 23.505 WattEV's
first station under construction in Bakersfield, CA, is planned to have integrated solar and
eventually be capable of charging 200 trucks each day;506 additional stations are under
development in San Bernardino and Gardena.507 Zeem Solutions also offers charging to fleets
along with a lease for one of its medium- or heavy-duty BEVs (via its "Transportation-as-a-
Service" model). Zeem's first depot station opened last year in the Los Angeles area and will
support the charging of vans, trucks, airport shuttles, and tour buses (among other vehicles) with
its 77 DCFC ports and 53 L2 ports.508
Some other companies are starting with mobile charging units while they test or pilot
vehicles.509 For example, PACCAR has partnered with Heliox to offer 40 kW and 50 kW mobile
charging units to its dealers and customers of the Kenworth and Peterbilt brands510 and Sysco,
which plans to deploy 800 Class 8 tractors in the next few years, plans to use mobile charging
units to begin their truck deployments while 14 charging stations are being installed.511 Dannar
offers mobile power platforms with up to 500 kWh of energy (or "exportable power") for offroad
work vehicles and emergency applications.512 BP pulse offers portable charging on wheels as
well as upcycled shipping containers with built in electrical infrastructure that can be used with
different charging equipment and placed onsite without significant construction.513 Mullen
Automotive offers a mobile charging truck that can deliver up to 150 kW of power through either
L2 or DCFC ports.514 Xos Hub mobile charging units offer up to 390 kWh of energy and can
504 WattEV. "WattEV Orders 50 Volvo VNR Electric Trucks". May 23, 2022. Available online:
https://www.wattev.com/post/wattev-orders-50-volvo-vnr-electric-trucks.
505 Adler, Alan. "WattEV opens public truck charging depot in Long Beach port". July 24, 2023. Available online:
https://www.freightwaves.com/news/wattev-opens-public-truck-charging-depot-in-long-beach-port.
506 WattEV. "WattEV Breaks Ground on 21st Century Truck Stop". December 16, 2021. Available online:
https://www.wattev.com/post/wattev-breaks-ground-on-21st-century-truck-stop.
507 WattEV. "Our Charging Sites". Available online: https://www.wattev.com/charging-stations.
508 Zeem. "Zeem Solutions Launches First Electric Vehicle Transportation-As-A-Service Depot." March 30, 2022.
Available online:https://www.businesswire.com/news/home/20220330005269/en/Zeem-Solutions-Launches-First-
Electric-Vehicle-Transportation-As-A-Service-Depot.
509 Mobile charging units are EVSE that can move to different locations to charge vehicles. Depending on the unit's
specifications and site, mobile charging units may be able to utilize a facility's existing infrastructure (e.g., 240 V
wall outlets) to recharge. Mobile charging units may have wheels for easy transport.
510 Hampel, Carrie. "Heliox to be global charging partner for Paccar". Electrive.com. September 24, 2022. Available
online: https://www.electrive.com/2022/09/24/heliox-to-be-global-charging-partner-for-paccar/.
511 Morgan, Jason. "How Sysco Corp. plans to deploy 800 battery electric Class 8 trucks (and that's just the
beginning)". Fleet Equipment. November 14, 2022. Available online: https://www.fleetequipmentmag.com/sysco-
battery-electric-trucks/.
512 DANNAR. "DANNAR platforms provide off-grid export power along with power for planned daily and seasonal
needs, as well as unexpected emergency response". Available online: https://www.dannar.us.com/platforms/.
513 BP pulse. "Rapidly deploy EV charging infrastructure with Inrush mobile and non-permanent charging
solutions." Available online: https://bppulsefleet.com/fleet/products/non-permanent-and-mobile-charging/.
514 Mullen. "Mullen Announces New Mobile EV Charging Truck Delivering Level 2 and Level 3 DC Fast
Charging". Available online: https://news.mullenusa.com/mullen-announces-new-mobile-ev-charging-truck-
delivering-level-2-and-level-3-dc-fast-charging.
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charge up to five vehicles at a time.515 Cummins and Heliox are partnering on a mobile 50 kW
DC charger.516
Truck manufacturers are working closely with their customers to support depot charging
infrastructure. For example, PACCAR sells a range of EVSEs to customers directly.517 Mack
Trucks partnered with two charging solution companies so that they can offer customers the
ability to acquire EVSE solutions directly from their dealers.518 DTNA also announced a
partnership to provide their customers with EVSE solutions.519 Similarly, Navistar partnered
with Quanta Services, Inc. to provide BEV infrastructure solutions, that include support in the
design, construction, and maintenance of EVSE at depots.520 Nikola has partnered with
ChargePoint to provide fleet customers with a suite of options for charging infrastructure and
software (e.g., for charge management).521 AMPLY Power, which was acquired by BP in 2021,
provides charging equipment and services for a variety of fleets, including van, truck, and bus
fleets.522
Domestic manufacturing capacity is also increasing. DOE estimates that over $500 million in
investments to support the domestic manufacturing of BEV charging equipment, with companies
planning to produce more than one million chargers (including 60,000 DCFCs) in the U.S. each
year.523'524 The White House estimates over $25 billion in commitments to expand the U.S.
charging network has been announced as of January 2024.525 Workforce development is on the
515 XOS. "XOS Energy Solutions". Available online: https://www.xostrucks.eom/xes/#mobilecharging.
516 Cummins. "Cummins and Heliox to Partner on Electric Vehicle Charging Solutions for Fleet Customers". May
23, 2023. Available online: https://www.cummins.com/news/releases/2023/05/16/cummins-and-heliox-partner-
electric-vehicle-charging-solutions-fleet.
517 PACCAR. "Electric Vehicle Chargers." Accessed on November 1, 2023. Available online:
https://www.paccarparts.com/technology/ev-chargers/
518 Volvo Group Press Release. "Mack Trucks Enters Partnerships with Heliox, Gilbarco to Increase Charging
Accessibility." February 14, 2023. Available online: https://www.volvogroup.com/en/news-and-
media/news/2023/feb/mack-trucks-enters-partnerships-with-heliox-gilbarco-to-increase-charging-accessibility.html
519 Daimler Trucks North America Press Release. "Electrada, Daimler partner for electric charging." October 3,
2023. Available online: https://www.truckpartsandservice.com/alternative-power/battery-
electric/article/15635568/electrada-daimler-partner-for-chargers
520 Navistar Press Release. "Navistar Partners With Infrastructure Solutions Provider Quanta Services." May 3,
2023. Available online: https://news.navistar.eom/2023-05-03-Navistar-Partners-With-Infrastructure-Solutions-
Provider-Quanta-Services
521 Nikola. "Nikola and ChargePoint Partner to Accelerate Charging Infrastructure Solutions". November 8, 2022.
Available online: https://nikolamotor.com/press_releases/nikola-and-chargepoint-partner-to-accelerate-charging-
infrastructure-solutions-212/.
522 BP. Press Release: "bp takes first major step into electrification in the US by acquiring EV fleet charging
provider AMPLY Power". December 7, 2021. Available online: https://www.bp.com/en/global/corporate/news-and-
insights/press-releases/bp-takes-first-major-step-into-electrification-in-us-by-acquiring-ev-fleet-charging-provider-
amply-power.html.
523 U.S. Department of Energy, Vehicle Technologies Office. "FOTW #1314, October 30, 2023: Manufacturers
Have Announced Investments of Over $500 million in More Than 40 American-Made Electric Vehicle Charger
Plants". October 30, 2023. Available online: https://www.energy.gov/eere/vehicles/articles/fotw-1314-october-30-
2023-manufacturers-have-announced-investments-over-500.
524 DOE, "Building America's Clean Energy Future". 2024. Available online: https://www.energy.gov/invest.
525 The White House, "FACT SHEET: Biden-Harris Administration Announces New Actions to Cut Electric
Vehicle Costs for Americans and Continue Building Out a Convenient, Reliable, Made-in-America EV Charging
Network", January 19, 2024. Accessed at: https://www.whitehouse.gov/briefing-room/statements-
releases/2024/01/19/fact-sheet-biden-harris-administration-announces-new-actions-to-cut-electric-vehicle-costs-for-
americans-and-continue-building-out-a-convenient-reliable-made-in-america-ev-charging-network/.
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rise. For example, the Siemens Foundation announced they will invest $30 million over ten years
focused on the EV charging sector.526 As of early 2023, about 20,000 people had been certified
to install EV charging stations through a national Electric Vehicle Infrastructure Training
Program.527 These important early actions and market indicators suggest strong growth in
charging and refueling ZEV infrastructure in the coming years.
States and utilities are also engaged. Seventeen states plus the District of Columbia (and the
Canadian province Quebec) developed a "Multi-State Medium- and Heavy-Duty Zero-Emission
Vehicle Action Plan," which includes recommendations for planning for, and deploying,
charging infrastructure.528 California is planning to invest $1.9 billion in state funding through
2027 in BEV charging and hydrogen fueling infrastructure (and related projects), including about
one billion specific to infrastructure for trucks and buses.529 The Edison Electric Institute
estimates that electric companies are investing about $4 billion to advance charging
infrastructure and fleets.530 The National Electric Highway Coalition, a group that includes more
than 60 electric companies and cooperatives that serve customers in 48 states and D.C.531 aims to
provide fast charging along major highways in their service areas. Other utilities, like the
Jacksonville Electric Authority (JEA) are supporting infrastructure through commercial
electrification rebates. JEA is offering rebates of up to $30,000 for DCFC stations and up to
$5,200 for Level 2 stations.532 In the west, Nevada Energy was supporting fleets by offering
rebates for up to 75% of the project costs for Level 2 ports and up to 50% of the project costs for
DCFC stations (subject to caps and restrictions).533'534
And there are additional initiatives that are gearing up to further support HD ZEV
infrastructure deployment. For example, in March 2024, the U.S. released a National Zero-
Emission Freight Corridor Strategy535 that, "sets an actionable vision and comprehensive
approach to accelerating the deployment of a world-class, zero-emission freight network across
526 Lienert, Paul. "Siemens to invest $30 million to train U.S. EV charger technicians". Reuters. September 6, 2023.
Available online: https://www.reuters.com/business/autos-transportation/siemens-invest-30-million-train-us-ev-
charger-technicians-2023 -09-06/.
527 IBEW. "IBEW Members Answer Call for National Electric Vehicle Program". April 2023. Available online:
https://www.ibew.org/articles/23ElectricalWorker/EW2304/Politics.0423.html.
528 ZEV Task Force. "Multi-State Medium- and Heavy-Duty Zero-Emission Vehicle Action Plan: A Policy
Framework to Eliminate Harmful Truck and Bus Emissions". July 2022. Available online:
https://www.nescaum.org/documents/multi-state-medium-and-heavy-duty-zev-action-plan-dual-page.pdf.
529 California Energy Commission. "CEC Approves $1.9 Billion Plan to Expand Zero-Emission Transportation
Infrastructure". February 14, 2024. Available online: https://www.energy.ca.gov/news/2024-02/cec-approves-19-
billion-plan-expand-zero-emission-transportation-infrastructure.
530 Joint Office of Energy and Transportation. "Private Sector Continues to Play Key Part in Accelerating Buildout
of EV Charging Networks." February 15, 2023. https://driveelectric.gOv/news/#private-investment.
531 Edison Electric Institute. Issues & Policy: National Electric Highway Coalition. Available online:
https://www.eei.org/en/issues-and-policy/national-electric-highway-coalition.
532 U.S. Department of Energy. Alternative Fuels Data Center. Florida Laws and Incentives." See Docket ID EPA-
HQ-OAR-2022-0985-0290.
533 Level 2 rebates are applicable to fleets with between 2 and 10 ports, and subject to a $5,000/port cap. DCFC
rebates are limited to 5 stations and are capped to the lesser of $400/kW or $40,000 per station.
534 U.S. Department of Energy. Alternative Fuels Data Center. Commercial Electric Vehicle Charging Station
Rebates—Nevada Energy. Available online: https://afdc.energy.gov/laws/12118. (Note: the program ended in June
2023).
535 Joint Office of Energy and Transportation. "National Zero-Emission Freight Corridor Strategy" DOE/EE-2816
2024. March 2024. Available at https://driveelectric.gov/files/zef-corridor-strategy.pdf.
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the United States by 2040. The strategy focuses on advancing the deployment of zero-emission
medium- and heavy-duty vehicle (ZE-MHDV) fueling infrastructure by targeting public
investment to amplify private sector momentum, focus utility and regulatory energy planning,
align industry activity, and mobilize communities for clean transportation."536 The strategy has
four phases. The first phase, from 2024-2027, focuses on establishing freight hubs defined "as a
100-mile to a 150-mile radius zone or geographic area centered around a point with a significant
concentration of freight volume (e.g., ports, intermodal facilities, and truck parking), that
supports a broader ecosystem of freight activity throughout that zone."537 The second phase,
from 2027-2030, will connect key ZEV hubs, building out infrastructure along several major
highways. The third phase, from 2030-2045, will expand the corridors, "including access to
charging and fueling to all coastal ports and their surrounding freight ecosystems for short-haul
and regional operations."538 The fourth phase, from 2035-2040, will complete the freight
corridor network. This corridor strategy provides support for the development of HD ZEV
infrastructure that corresponds to the modeled potential compliance pathway for meeting the
final standards.
Also in 2024, Daimler, Volvo, and Navistar, who collectively represent approximately 70
percent of HD sales in the U.S., formed an industry group called the Powering America's
Commercial Transportation (PACT) coalition to advance best practices and advocate for climate
policies that can accelerate the construction of infrastructure for HD ZEV fleets.539
1.6.2.3 Future BEV Charging Infrastructure Needs
We expect the many public and private investments and initiatives described in Chapters 1.3.2
and 1.6.2.2 above to significantly expand BEV charging infrastructure for HD vehicles over the
next decade. However, more infrastructure will be needed as BEV adoption grows. In Chapter
2.6 of this document, we describe how we accounted for charging infrastructure needs and costs
associated with the utilization of HD BEV technologies in the potential compliance pathway that
supports the feasibility of the final standards. In this section, we discuss a few recent assessments
of charging infrastructure needs from the literature and how they compare to our final rule
analysis.
Estimates of how much charging infrastructure will be needed to support BEVs vary widely
among studies based on differing assumptions about the population and mix of BEVs, the
assumed mix of depot versus public charging, charging power levels, and EVSE utilization
536 Joint Office of Energy and Transportation. "Biden-Harris Administration, Joint Office of Energy and
Transportation Release Strategy to Accelerate Zero-Emission Freight Infrastructure Deployment." March 12, 2024.
Available online: https://driveelectric.gov/news/decarbonize-freight.
537 Joint Office of Energy and Transportation. "National Zero-Emission Freight Corridor Strategy" DOE/EE-2816
2024. March 2024. Available at https://driveelectric.gov/files/zef-corridor-strategy.pdf. See page 3.
538 Joint Office of Energy and Transportation. "National Zero-Emission Freight Corridor Strategy" DOE/EE-2816
2024. March 2024. Available at https://driveelectric.gov/files/zef-corridor-strategy.pdf. See page 8.
539 PACT. Updated Release. "Cross-Industry Coalition, Powering America's Commercial Transportation, Launches
to Accelerate Zero-Emission Vehicle Infrastructure Deployments". BusinessWire. February 9, 2024. Available
online: https://www.businesswire.com/news/home/20240130152674/en/Cross-Industry-Coalition-Powering-
America%E2%80%99s-Commercial-Transportation-Launches-to-Accelerate-Zero-Emission-Vehicle-Infrastructure-
Deployments.
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among other factors. A recent ICCT study (Ragon et al. 2023)540 estimated charging needs for
1.1 million Class 4 to 8 BEVs in 2030. The study projected that a mix of 522,000 (DC-50 kW
and DC-150 kW) EVSE ports could meet overnight charging needs541 along with 28,500 DC-350
kW ports and 9,540 DC-2 MW ports used for opportunity charging. An Atlas Public Policy
analysis (McKenzie et al. 2021) estimated that about 500,000 EVSE ports (ranging from Level 2
to DC-150 kW) would be needed at depots to support over one million Class 3 to 8 trucks in
2030 along with a significant buildout of en-route charging infrastructure.542 The study found
that the number of en-route ports needed could vary significantly based on the power level, e.g.,
for long-haul trucking, up to 93,000 350-kW DCFC ports or up to 19,000 2-MW DCFC ports
may be needed along with about 7,000-32,000 DCFCs used for en-route charging by other
trucks.543 A study by the Goldman School of Public Policy (Phadke et al. 2021)544 projects that
about 85,000 (DC-50 kW to DC-300 kW) ports, mainly at depots and warehouses, will be
needed to support Class 2b-7 BEVs by 2035 and 300,000 (DC-125 kW to 1 MW) ports will be
needed across 2,700 truck stops to support Class 7-8 tractors under a scenario in which 100
percent of new MD and HD vehicle sales are BEVs by 2035.
The Coordinating Research Council (CRC) released a study545 in September 2023 that
estimated charging and hydrogen refueling infrastructure needs to support ZEVs at levels
consistent with several finalized CARB regulations and two of EPA's proposed vehicle
standards, including those in the NPRM.546 It found that 432,000 (L2 to DC-350 kW) EVSE
ports would be needed at depots in 2030 along with about 45,500 (DC-150 kW to 1 MW) public
ports to meet the charging needs of 920,000 MD and HD BEVs. The CRC projects that within
two years infrastructure needs will grow to 709,000 depot ports and 91,800 public DCFC ports to
support a fleet of 1.7 million MD and HD BEVs. Ricardo completed a feasibility study of the
proposed rule (Kuhn et. al 2023) and estimated that about 1.5 million EVSE ports will be
required at depots in 2032 along with about 7,500 highway ports to support about 1.5 million
540 Ragon, Pierre-Louis et al. "Near-term Infrastructure Deployment to Support Zero-Emission Medium- and Heavy-
Duty Vehicles in the United States." May 2023. Available online: https://theicct.org/wp-
content/uploads/2023/05/infrastructure-deployment-mhdv-may23.pdf.
541541 Overnight charging in the study is expected at depots except for long-haul vehicles, which are expected to use
public charging.
542 McKenzie, Lucy, James Di Filippo, Josh Rosenberg, and Nick Nigro. "U.S. Vehicle Electrification Infrastructure
Assessment: Medium- and Heavy-Duty Truck Charging". Atlas Public Policy. November 12, 2021. Available
online: https://atlaspolicy.eom/wp-content/uploads/2021/l 1/2021-11-
12_Atlas_US_Electrification_Infrastructure_Assessment_MD-HD-trucks.pdf.
543 Some numbers discussed for the Atlas study were taken from graphs and should be considered approximate. The
Atlas study uses the term "on-road" charging.
544 Phadke, Amol et al. Goldman School of Public Policy, University of California Berkeley. "2035, The Report—
Transportation:
Plummeting Costs and Dramatic Improvements in Batteries Can Accelerate Our Clean Transportation Future". April
2021. Available online: http://www.2035report.eom/transportation/wp-content/uploads/2020/05/2035Report2.0-
l.pdf.
545 Coordinating Research Council. "Assess the Battery-Recharging and Hydrogen-Refueling Infrastructure Needs,
Costs and Timelines Required to Support Regulatory Requirements for Light-, Medium-, and Heavy-Duty Zero-
Emission Vehicles." Prepared by ICF. September 2023. Available online: https://crcao.org/wp-
content/uploads/2023/09/CRC_Infrastructure_Assessment_Report_ICF_09282023_Final-Report.pdf.
546 The study accounted for CARB's Advanced Clean Cars II, Advanced Clean Trucks, and Advanced Clean Fleets
regulations and EPA's proposed Multipollutant Emissions Standards for MY2027 and Later Light-Duty and
Medium-Duty Vehicles and proposed Greenhouse Gas Emissions Standards - Phase 3.
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medium- and heavy-duty BEVs.547 A recent CEC assessment (Davis et al. 2023) estimated that
109,000 (L2 to DC-150 kW) EVSE ports will be needed at depots to support 155,000 BEVs
expected in California in 2030 along with about 5,500 (DC-350 kW to 1.5 MW) public ports.548
As discussed in Chapter 2.10.3, in our final rule analysis, we estimate that about 520,000
EVSE ports at depots will be needed to support MY2027-MY2032 depot-charged BEVs (see
RIA Chapter 2.8.7.2 for information on how this was estimated), at a ratio of 1.2 BEVs per
EVSE port. It should be noted that the mix of depot charging equipment also differs among
studies. Our analysis focused on the lowest cost EVSE option that could meet daily charging
needs; as such, 88% of the projected EVSE ports in the final rule analysis are Level 2. The CRC
and Ricardo studies also found the highest number of ports needed at depots would be Level 2
(consistent with our analysis), while the other studies focused more on DCFC.
The projected needs for public or en-route charging vary even more widely in the studies
discussed above with power levels ranging from 125 kW to 2 MW. One of the key questions for
future public charging needs, particularly for long-haul vehicles, is how many stations will be
needed to provide geographic coverage across the country. Ragon et al. 2023 projects that as
much as 85% of the charging needs for long-haul BEVs could be covered by building stations
every 50 miles along the National Highway Freight Network (NHFN) for a total of just 844
stations.549 McKenzie et al. 2021 also centered its long-haul analysis on the primary NHFN
suggesting fewer than 500 stations would be needed if spaced every 100 miles.550'551
Another key question is the pace of charging infrastructure buildout. Ragon et al. 2023 found
that early charging needs for MHD BEVs will be concentrated in select counties and states, e.g.,
estimating that Texas, California, and Florida will collectively account for almost 25% of
charging needs (on an energy basis) in 20 3 0.552 In a supplemental analysis submitted to EPA that
assumed 100 mile intervals between stations, ICCT estimated that only between 100 and 210
electrified truck stops on priority corridors may be needed by 2030, assuming a given level of
BEV long-haul tractors.553 Analyses of this type can help inform priority areas for infrastructure
deployment and facilitate a phased buildout. See RTC 6.1 for additional discussion on recent
547 Kuhn et. al. "Feasibility study of EPA NPRM Phase 3 GHG standards for Medium Heavy-Duty Vehicles.
Version: 3.0". Ricardo, prepared for Truck and Engine Manufacturers Association. July 19, 2023.
548 Davis, Adam et. al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment: Assessing Charging Needs to Support Zero-Emission Vehicles in 2030 and 2035."
August 2023. Available online: https://www.energy.ca.gov/publications/2023/second-assembly-bill-ab-2127-
electric-vehicle-charging-infrastructure-assessment.
549 Ragon, Pierre-Louis et al. "Near-term Infrastructure Deployment to Support Zero-Emission Medium- and Heavy-
Duty Vehicles in the United States." May 2023. Available online: https://theicct.org/wp-
content/uploads/2023/05/infrastructure-deployment-mhdv-may23.pdf.
550 The Atlas study (McKenzie et al. 2021) assumed stations would be spaced every 100 miles and have 10 ports
each for a total of 4,151 ports across the primary NHFN or 5,785 ports across the full NHFN.
551 McKenzie, Lucy, James Di Filippo, Josh Rosenberg, and Nick Nigro. "U.S. Vehicle Electrification Infrastructure
Assessment: Medium- and Heavy-Duty Truck Charging". Atlas Public Policy. Available online:
https://atlaspolicy.com/wp-content/uploads/2021/ll/2021-ll-
12_Atlas_US_Electrification_Infrastructure_Assessment_MD-HD-trucks.pdf.
552 Ragon, Pierre-Louis et al. "Near-term Infrastructure Deployment to Support Zero-Emission Medium- and Heavy-
Duty Vehicles in the United States." May 2023. Available online: https://theicct.org/wp-
content/uploads/2023/05/infrastructure-deployment-mhdv-may23.pdf.
553 ICCT. "Supplemental comments of the International Council on Clean Transportation on the EPA Phase 3 GHG
Proposal." January 3, 2023. Docket ID: EPA-HQ-OAR-2022-0985-2703.
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assessments of charging infrastructure needs from the literature and how they compare to our
final rule analysis. See RTC 7 (Distribution) for EPA's further consideration of this issue in the
context of needed distribution grid buildout and extent of an initial HD BEV public charging
network. For a discussion of how we accounted for depot and public infrastructure costs, see
Chapter 2.6. of this RIA.
1.6.2.4 Charging Costs
Beyond upfront costs, BEV owners will purchase the electricity that their vehicles consume.
The cost of the electricity can vary based on the applicable retail electricity rate as determined by
provider, location, time of use (TOU) and other factors. Fleets may also pay demand charges
based on the maximum power used during a month. As noted in a report by the National
Association of Regulatory Utility Commissioners, many utilities offer rates to incentivize
charging at off-peak times such as time of use rates or real-time pricing.554 Some utilities are also
piloting approaches to reduce demand charges for BEV fleet customers or station providers, e.g.,
by suspending them or offering alternatives during initial years of operation.555'556 Since demand
charges are typically assessed based on the peak power (measured in kW) used in a billing cycle,
they can be particularly challenging for stations with multiple high-powered DCFCs. Demand
charge rates vary widely by utility557 and location, ranging from $0/kW (no demand charge) to
over $50/kW according to an NREL survey.558 The use of onsite battery storage, renewable
generation, or managed charging may help to lower peak demands at some stations and reduce
these costs (as discussed in Chapter 1.6.5 of this document as well as in RTC section 7
(Distribution)).
The price to charge at public stations may be higher than for depot charging, as noted by a
recent Atlas analysis, since the public charging price may incorporate the profit margin of the
third-party charging provider along with operating expenses, and costs associated with charging
equipment depreciation.559 Prices at public stations may also vary in structure, e.g., costs may be
assessed per kWh of electricity, per minute of charging, via a monthly subscription fee, or
another method with rates varying based on power level or other factors.560'561 See Chapter 2.6.4
for a description of how estimated public charging cost on a $/kWh, accounting for amortized
554 NARUC. "Electric Vehicles: Key Trends, Issues, and Considerations for State Regulators". October 2019.
Available online: https://pubs.naruc.org/pub/32857459-0005-B8C5-95C6-1920829CABFE.
555 Ibid.
556 ZEV Task Force. "Multi-State Medium- and Heavy-Duty Zero-Emission Vehicle Action Plan: A Policy
Framework to Eliminate Harmful Truck and Bus Emissions". July 2022. Available online:
https://www.nescaum.org/documents/multi-state-medium-and-heavy-duty-zev-action-plan-dual-page.pdf
557 In some cases, utilities may apply different demand charge rates ($/kW) based on whether a customer's
maximum power usage in a given billing cycle occurs on or off peak.
558 McLaren, Joyce, Nicholas Laws, and Kate Anderson. "Identifying Potential Markets for Behind-the-Meter
Battery Energy Storage: A Survey of U.S. Demand Charges". National Renewable Energy Lab. August 2017.
Available online: https://www.nrel.gov/docs/fyl7osti/68963.pdf.
559 Satterfield, Chris and Nick Nigro. "Assessing Financial Barriers to Adoption of Electric Trucks: A Total Cost of
Ownership Analysis". Atlas Public Policy. February 2020. Available online: https://atlaspolicy.com/wp-
content/uploads/2020/02/Assessing-Financial-Barriers-to-Adoption-of-Electric-Trucks.pdf.
560 U.S. DOE Alternative Fuels Data Center. "Charging Infrastructure Operation and Maintenance." Available
online: https://afdc.energy.gov/fuels/electricity_infrastructure_maintenance_and_operation.html.
561 In some states, there are prohibitions for entities other than utilities to sell electricity. Charging may be priced by
time or session instead of on a $/kWh basis.
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cost of equipment, land costs, operation and maintenance, distribution upgrades, and profits,
among other factors.
1.6.3 Other BEV Charging Infrastructure Considerations
There are challenges and important considerations beyond costs when developing and
deploying charging infrastructure. These include interoperability, station design and siting
considerations, and the potential need for distribution system upgrades or other grid
considerations.
1.6.3.1 Interoperability
As discussed in Chapter 1.6.1, there is currently no universal standard for DCFC connectors,
limiting the EVSE ports and stations a particular vehicle may use.562 This may pose a challenge
for public, en-route charging network providers trying to serve a wide range of vehicles and for
BEV drivers who may need to travel longer distances to find a station with the right connector
type. Depending on business requirements, fleets may also need to support varying makes and
models of HD BEVs that use different connectors,563 limiting the ability to share and optimize
the use of depot charging equipment. Once fleet owners have installed a particular connector
type at their depot, it could limit their ability to buy new vehicles without incurring additional
EVSE costs. In some cases, adapters may be an option. For example, Tesla released a CCS Type
1 adapter in September of 2022 that allows some of their cars to charge at CCS ports installed by
other providers.564 We also note movement toward standardized connectors. For example, the
National Electric Vehicle Standards and Requirements Final Rule issued by the Federal Highway
Administration in February 20 2 3 565 requires each DCFC port funded under the NEVI Formula
Program, or as part of a publicly-accessible EV charging project under Title 23, U.S.C., to have a
Combined Charging System (CCS) Type 1 connector.566 Additionally, as discussed in Chapter
1.6.1.2, a non-proprietary standard for higher-power charging, MCS, is currently in
development.567
Physical connectors are only one aspect of interoperability. Communication protocols
between the network and chargers and between the charger and vehicle facilitate the flow of key
charging and billing information such as authentication, vehicle state of charge, and power
levels.568 The National Electric Vehicle Standards and Requirements Final Rule requires the use
562 Some EVSE ports are available with multiple connector types.
563 California Energy Commission. Electric Vehicle Charging Infrastructure Assessment—AB 2127. Available
online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-infrastructure-
assessment-ab-2127.
564 Halvorson, Bengt. "$250 CCS adapter lets Tesla EVs roam other charging networks". Green Car Reports.
September 25, 2022. Available online: https://www.greencarreports.com/news/1137268_tesla-ccs-adapter-north-
america-up-to-250-kw.
565 88 FR 12724. February 28, 2023. Available online: https://www.federalregister.gov/documents/2023/02/28/2023-
03500/national-electric-vehicle-infrastructure-standards-and-requirements.
566 Additional non-proprietary connectors are allowed, provided each DCFC port has a CCS Type 1 connector.
567 SAE International. "Megawatt Charging System for Electric Vehicles J3271". Available online:
https ://www. sae .org/standards/content/j 3271/
568 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030." July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-
infrastructure-assessment-ab-2127.
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of Open Charge Point Protocol for the former and ISO 15118 for the latter.569 The rule also
requires the use of Open Charge Point Interface for communication between charging
networks.570 Such requirements support standard communication for BEV charging—advancing
interoperability. We also note that the MCS incorporates ISO 15118.571
1.6.3.2 Station Design and Siting Considerations
How to best design and site depot charging stations will depend on fleets' vehicle mix,
operational needs, and site specifics. All sites need to have sufficient space for charging
equipment, with some stations potentially needing to accommodate onsite storage and generation
equipment as well.572 The canopy or roof height of the station and charging cords need to be
appropriately sized for the BEVs in the fleet and the station needs sufficient space for vehicle
ingress and egress. As discussed in Chapter 2.6.2, installation costs may be higher for sites with
longer distances between the charging equipment and electrical panel or where panel upgrades
are needed. Site ownership is another consideration. As noted in a report by the California
Energy Commission, installing charging equipment or making associated electrical upgrades
could depend on landlord-tenant relationships.573 In certain cases, responsibility for charging
infrastructure may be shared among different parties—potentially complicating planning and
upkeep. In addition to the above, siting and design for public or other en-route stations will need
to account for the operational needs, characteristics, and travel patterns of the different BEVs
they may support. See further discussion in RTC section 7 (Distribution).
The construction of any new charging station requires compliance with various building and
safety regulations.574 Permitting times vary based on state or local jurisdiction, site specifics, and
other factors. For example, Electrify America reported that the permitting process took an
average of 13 weeks for its U.S. "ultra-fast" DCFC stations in 2021, but took over twice as long
for stations in New Jersey.575 Utility interconnection also adds time to the process. After site
construction was complete, Electrify America found an additional 12 weeks was required on
average for inspection, commissioning and other steps before a site was energized.576
569 88 FR 12724. February 28, 2023. Available online: https://www.federalregister.gov/documents/2023/02/28/2023-
03500/national-electric-vehicle-infrastructure-standards-and-requirements.
570 See rulemaking for required version numbers, implementation timeline and other details.
571 Kane, Mark. "CharIN Officially Launches The Megawatt Charging System (MCS)". Inside EVs. June 15, 2022.
Available online: https://insideevs.com/news/592360/megawatt-charging-system-mcs-launch/.
572 National Renewable Energy Laboratory (NREL). "Medium- and Heavy-Duty Electric Vehicle Charging".
Available online: https://www.nrel.gov/transportation/medium-heavy-duty-vehicle-charging.html.
573 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-
infrastructure-assessment-ab-2127.
574 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-
infrastructure-assessment-ab-2127.
575 Electrify America. "2021 National Annual Report to U.S. EPA". April 30, 2022. Available online:
https://media.electriIyamerica.com/assets/documents/original/872-2021AnnualReportNationalPublicFINAL.pdf.
576 Electrify America. "2021 National Annual Report to U.S. EPA". April 30, 2022. Available online:
https ://media. electrifyamerica.com/assets/documents/original/872-2021AnnualReportNationalPublicFINAL .pdf.
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Both permitting and utility interconnection times could be longer for larger, more complex,
and/or higher-power charging stations. For example, California's "Electric Vehicle Charging
Station Permitting Guidebook" notes that under a recent state law to help streamline the
permitting process, jurisdictions have twice as long (50 business days) to review and either
approve or deny a permit application for a site with 26 or more stations than one with 25 or
fewer.577 Special permits, such as a right of way permit or an encroachment permit may be
required for stations that need a new utility electrical service or for which trenching under a
current right of way is needed respectively—adding to the station deployment timeline. If
upgrades to the electricity distribution system are required, this could further extend the timeline
(as discussed in Chapter 1.6.5 of this document below.)
1.6.4 Power Generation and Transmission
HD BEV-related power generation and transmission actions and their costs are small when
compared to historical levels of total power generation. Analysis by others concurs stating that,
"the generation and transmission infrastructure that could be needed to meet the demand - is
quite small relative to historic periods of growth in demand for electricity."578 We project the
additional generation needed to meet the demand of HD BEVs in the final rule to be relatively
modest; the energy required for HD BEVs is estimated to be 22,000 GWh in 2032 and 120,000
GWh in 2050, as shown in Chapter 6.5. These loads represent only 0.5 percent and 3 percent,
respectively, of the total 2022 electricity demand. Even when the electricity loads projected from
the HD rule are combined with those from the in process Multi-Pollutant Emissions Standards
for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles and other rules relating
to the EGU sector, it is projected that the rules are unlikely to adversely affect resource
adequacy.579 Using MOVES analysis to determine demand and IPM to calculate the required
electricity generation for these two rules combined shows the national increased generation from
transportation electrification to be 0.4 percent at 2030 and 4.5 percent at 2050. Planning for and
adding infrastructure for additional electricity generation and transmission is a standard practice
for North American Electric Reliability Corporation (NERC), the six regional entities, and
utilities, and is not a challenge specific to HD BEV needs. See Section II.D.2.C. of the Preamble
and RTC section 7.1 for a discussion of grid reliability.
Electric transmission needs are defined in DOE's National Transmission Needs Study as "the
existence of present or expected electric transmission capacity constraints or congestion in a
geographic area". The study suggests that an "upgraded, uprated, or new transmission facility—
including alternative transmission solutions" can help "improve the reliability and resilience of
the power system; alleviate transmission congestion and unscheduled flows; alleviate power
transfer capacity limits between neighboring regions; deliver cost-effective generation to meet
demand; and/or meet projected future generation, electricity demand, or reliability
577 Hickerson, Heather and Hannah Goldsmith. CALIFORNIA GOVERNOR'S OFFICE OF BUSINESS AND
ECONOMIC DEVELOPMENT. "Electric Vehicle Charging Station Permitting Guidebook". January 2023.
Available online: https://static.business.ca.gov/wp-content/uploads/2019/12/GoBIZ-EVCharging-Guidebook.pdf.
578 Hibbard, Paul. "Heavy Duty Vehicle Electrification Planning for and Development of Needed Power System
Infrastructure". Analysis Group for EDF. June 2023. Available online: https://blogs.edf.org/climate411/wp-
content/blogs.dir/7/files/Analysis-Group-HDV-Charging-Impacts-Report.pdf.
579 U.S. EPA. "Technical Memorandum for Multi-Pollutant Emissions Standards for Model Years 2027 and Later
Light-Duty and Medium-Duty Vehicles, and Greenhouse Gas Emissions Standards for Heavy-Duty Vehicles -
Phase 3". February 2024
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requirements."580 This transmission needs study includes multiple scenarios with various levels
of demand but is not specific to HD BEV power needs.
Technologies such as grid-enhancing technologies (GETs), which are supported by the Office
of Electricity (OE), can help optimize transmission for HD BEVs and all users.581 DOE support
of transmission projects is shown by the $10.5 billion for the five-year period covering FY22
through FY26 to enhance the resilience of the electric grid, deploy technologies to enhance grid
flexibility, and demonstrate innovative approaches to power sector infrastructure resilience and
reliability.582
Electricity generation and transmission demand will depend on the time of day that charging
occurs, the type or power level of charging, and the use of onsite storage and vehicle-to-grid
(V2G) or other vehicle-grid integration technology, among other considerations. There are a
variety of approaches that can reduce peak loads and/or align loads with plentiful or low carbon
electricity. For example, depending on operational needs, BEVs may be scheduled to charge
when the electricity demand is easier to meet. To illustrate the available energy based on time of
day, the ERCOT (Electric Reliability Council of Texas) energy generation versus time of day is
shown for July 19, 2023.583 ERCOT and July 18 were chosen as the Texas grid was handling
significant loads due to hot weather. The peak level of energy generated and transmitted of
82,182 MWh occurs at 6 pm as driven by customer use. The minimum power generated and
transmitted is 54,419 MWh at 6 am. The theoretical energy available at 6 am (peak minus
580 U.S. Department of Energy. "National Transmission Needs Study". October 2023. Available Online:
https://www.energy.gov/sites/default/files/2023-10/National_Transmission_Needs_Study_2023.pdf
581 Jenkins, Sandra. "Grid-Enhancing Technologies: From R&D to Reality". Department of Electricity, Department
of Energy. November 13, 2023. Available Online: https://www.energy.gov/oe/articles/grid-enhancing-
technologies-rd-reality-0
582 BIL-Grid Resilience and Innovation Partnerships (GRIP). NETL for DOE. Accessed February 26, 2024. .
Available online: https://netl.doe.gov/bilhub/grid-resilience/grip.
583 EIA. "U.S. Energy generation by energy source". Accessed November 24, 2023. Available online:
https://www.eia.gov/electricity/gridmonitor/expanded-
view/electric_overview/US48/US48/GenerationByEnergySource-4/edit
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minimum) is 27,763 MWh, almost 34 percent of the peak. A check of minimum power vs
maximum for the 48 lower states shows theoretical available power to again be 34%.
Electric Reliability Council of Texas, Inc. (ERCO) electricity generation
by energy source 7/18/2023 - 7/19/2023, Eastern Time
megawatthours
— Wind — Solar — Hydro — Other
^ — Natural gas — Coal — Nuclear — Total Generation
eia' Data source: U.S. Energy Information Administration
Figure 1-16 Example of Temporal Power Supply (Source: EIA)
Significant power is available overnight for use by depots (as well as public charging that
occurs over night). Many HD BEV at depots will be able to start charging late at night when
other loads have ceased, taking advantage of lower cost electricity that is readily available
without grid improvements. HD BEV using public charging, and some unique depot
applications, may not be able to draw power when it is plentiful and lower cost. These
applications may decide to implement stationary batteries that draw power at times and loads that
are convenient and lowest cost and then have the power available for HD BEV as needed. V2G
technology, which allows electricity to be drawn from vehicles that are not in use, could even
allow BEVs to enhance grid reliability.584 V2G success was shown by San Diego Gas and
Electric, Cajon Valley Union School District and Nuvve in the summer of 2022.585 The DOE
584 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-veliicle-charging-
infrastructure-assessment-ab-2127.
585 Business Wire. "SDG&E and Cajon Valley Union School District Flip the Switch on Region's First Veliicle-to-
Grid Project Featuring Local Electric School Buses Capable of Sending Power to the Grid". July 26, 2022.
Available online: https://www.businesswire.com/news/home/20220726006137/en/SDGE-and-Cajon-Valley-Union-
School-District-Flip-the-Switch-on-Region%E2%80%99s-First-Veliicle-to-Grid-Project-Featuring-Local-Electric-
School-Buses-Capable-of-Sending-Power-to-the-Grid
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Multi-State Transportation Electrification Impact Study (TEIS)586 estimates the potential costs
and benefits associated with electrical distribution system upgrades that may incur as a result of
BEV demand resulting from this final rule in addition to demand from the LMDV rule. The
TEIS reflects very significant reductions in peak demand (including an actual reduction in peak
demand in some states between a no action case and a case reflecting GHG standards for both
the LJVII1D and HDV sectors) even if only minimal managed charging techniques are utilized.587
1.6.5 Power Distribution
In addition to the infrastructure (EVSE and ports) needed for charging, some amount of
supporting electrification infrastructure between a transmission line and the EVSE may be
needed (see Figure 1-17). As discussed in Chapter 2.6.4, significant (and localized) increases in
load from charging stations could, in some cases, require upgrades to the electricity distribution
system. In general, such upgrades will be needed if the station power needs exceed the existing
capacity on the system (or hosting capacity). This could include additional transformers, feeders,
and new or upgraded substations. How much these upgrades cost and how long they take to
implement will depend on the charging load.
Transmission
System
H'
II Transformer I
Bank I
Feeder
SB
Behind the
Meter
Distribution
Substation
Figure 1-17 Electricity power distribution infrastructure is shown above and is that portion of the grid
between the transmission system and the customer meter. Charging infrastructure for HD BEV is behind the
meter. (Source: Kevala, as seen in TEIS)588
While needs will be site specific, one recent study (Borlaug et al. 2021) estimated that loads
of just 200 kW or higher could trigger the need for an onsite distribution transformer, which
could take three to eight months to deploy.589 New charging loads of several megawatts or
higher—likely only relevant for stations with many high-power DCFC unit ports, and especially
58 National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, Kevala Inc.. and U.S.
Department of Energy. "Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-.
Medium-, and Heavy-Duty Electric Vehicles". DOE/EE-2818. U.S. Department of Energy. March 2024.
187 See, e.g.. TEIS at 62.
188 National Renewable Energy Laboratory, Lawrence Berkeley National Laboratoiy, Kevala Inc., and U.S.
Department of Energy. "Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-.
Medium-, and Heavy-Duty Electric Vehicles". DOE/EE-2818. U.S. Department of Energy. March 2024 .
188 National Renewable Energy Laboratory, Lawrence Berkeley National Laboratoiy, Kevala Inc., and U.S.
Department of Energy. "Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-.
Medium-, and Heavy-Duty Electric Vehicles". DOE/EE-2818. U.S. Department of Energy. March 2024.
589 Borlaug, B.. Muratori. VI.. Gilleran, M. et al. "Heavy-duty truck electrification and the impacts of depot charging
on electricity distribution systems". Nat Energy 6, 673-682 (2021). Available online:
https://www.nature.com/articles/s41560-021-00855-0.
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for public stations where HD BEVs may require immediate charging—could require more
significant distribution system upgrades such as those to feeder circuits, breakers, or, in certain
situations, new substations. Borlaug et al. 2021 found that such upgrades could take months to
several years to implement.590
An EPRI survey of distribution utilities with 18 respondents from different areas of the
country found significant variation in the lead time needed for distribution upgrades, e.g.,
ranging from 18 months to 10 years for a new substation, though EPRI identified typical
timeframes from the most common responses.591 EPRI asked respondents to estimate the
distribution component work usually required for various load sizes and, separately, to estimate
typical interconnection times when these upgrades are needed. Taken together, EPRI found up to
a year of lead time may be typical for 1 MW of new load and one to two years for 5 MW. Larger
loads of 10 MW or 20 MW were associated with longer typical lead times of two to three and
three to five years, respectively. However, as previously discussed, upgrades are not required if
sufficient hosting capacity exists. In these cases, the EPRI survey found the typical
interconnection time was under six months.592 EPRI continues to work with utilities, fleet
operators, manufacturers, and charging providers through their EVs2Scale initiative.593
Table 1-28 shows a summary of cost and timing estimates for distribution component
upgrades or buildout in Borlaug et. al. 2021, the EPRI survey, and a recent ICCT study (Basma
et al. 2023). These reports have different scopes, assumptions and methods. Borlaug et al. 2021
assessed distribution upgrades for depot stations, Basma et al. 2023 modeled charging costs
associated with 20 MW public charging stations designed to serve class 8 long-haul trucks, and
EPRI estimated typical lead times by surveying distribution utilities. Therefore, estimates shown
may not be directly comparable. As discussed in Chapter 2.4, we accounted for distribution
upgrade costs in final rule analysis, informed by Basma et al. 2023.
590 Ibid.
591 EPRI. "EVs2Scale2030™ Grid Primer". August 29, 2023 Available online:
https://www.epri.eom/research/products/000000003002028010
592 Ibid.
593 EPRI. "EVs2Scale2030". Accessed February 26, 2024. Available Online: https://msites.epri.com/evs2scale2030
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Table 1-28 Examples of distribution upgrade costs and lead times from the literature594
Component
ICCT (Basma et al.
2023) 595
Borlaug et al. 2021596
EPRI597 598
New Substation
NA
$4-3 5M
24-48 months
36-60 months
Substation Upgrade
$3.1M599
$3-5M600
12-18 months
24-36 months
New/Upgraded Feeder
$0.9M
$2-12M
3-12 months
12-24 months (new)
6-12 months (upgraded)
Transformer
$0.6M
< $0.2M
NA
3-8 months
As described in RIA Chapter 2.10.3, we estimated the total number of EVSE ports that will be
required to support the depot-charged BEVs in the potential compliance pathway's technology
packages developed to support the MY 2027-2032 standards. We estimated approximately
520,000 EVSE ports will be needed across all six model years. The majority (88 percent) of
these are Level 2 ports, followed by low-power DCFCs. It would take about fifty Level 2 (19.2
kW) EVSE ports or twenty DC-50 kW ports at a depot to generate 1 MW of additional
(localized) load. As noted above, EPRI suggested the typical lead time for distribution upgrades
at this level is up to a year. As seen in Table 1-28, the longest lead times are typically associated
with the need for a new substation or upgrades to an existing substation. These upgrades are
most likely to be needed at stations with many high-power DCFC ports (such as the 20 MW
public stations modeled in Basma et al. 2023)—if the stations are sited in areas without sufficient
capacity and without measures to mitigate the charging load. However, as described in detail in
RTC 7 (Distribution), we project that only a handful of substation upgrades nationwide would be
needed by 2032 to accommodate demand posed by the Phase 3 rule (assuming compliance via
the potential compliance pathway modelled to support feasibility of the Phase 3 standards).
We discuss in preamble II.D.2.c.iii and RTC section 7 (Distribution) the potential demand
posed by a HDV Phase 3 rule at the national, regional, and parcel level, including estimates of
the amount of distribution grid buildout (i.e. transformers, feeders, and substations (both
upgraded and new)) that could be needed within the Phase 3 rule's 2027-2032 timeframe.
594 See reports for more details on these estimates. Costs for metering are not shown above.
595 Basma, Hussein. "Total Cost of Ownership of Alternative Powertrain Technologies for Class 8 Long-Haul
Trucks in the United States". ICCT. 2023 Available online: https://theicct.org/publication/tco-alt-powertrain-long-
haul-trucks-us-apr23/.
596 Borlaug, B., Muratori, M., Gilleran, M. et al. "Heavy-duty truck electrification and the impacts of depot charging
on electricity distribution systems". Nat Energy 6, 673-682 (2021). Available online:
https://www.nature.com/articles/s41560-021-00855-0.
597 As noted above, respondents of the EPRI survey provided a range of responses. In the table above, the most
common interconnection time range selected by respondents is shown.
598 EPRI. "EVs2Scale2030™ Grid Primer". August 29, 2023 Available online:
https://www.epri.eom/research/products/000000003002028010
599 Includes $2M for a substation transformer and $ 1. 1M for "feeders, tie, and transfer switches".
600 A separate estimate of $0.4 M and 6-12 months was provided for adding a feeder breaker to a substation.
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If distribution grid buildout is needed, then there are ways to minimize its extent, timing, and
cost. A report by the Interstate Renewable Energy Council identified such utility coordination
as an emerging best practice to help streamline station deployments. The report also highlighted
the potential value of utilities providing hosting capacity maps (HCMs) that identify grid
capacity constraints.601 As of mid-2022, requirements for HCMs or related analyses were in
place in ten states identified by Lawrence Berkeley National Laboratory.602 While the specific
requirements and contents of HCMs vary, where applicable, such maps could help station
developers determine whether area feeders or substations have sufficient additional capacity for
charging or other loads. As of January 2024, utilities offer 39 unique maps covering 24 states and
the District of Columbia.603 Should a new facility be involved, distribution system capacity and
interconnection can be factored into the site selection process604 and, when possible, utilities can
work with station developers to evaluate multiple potential sites before a selection is made.605
One Energy is minimizing distribution upgrade costs at their recently energized 30 MW site
in Findlay, Ohio (mentioned in Chapter 1.6.2.2). The Findlay Megawatt Hub is served by a
138,000 volt transmission line. The readily available power allows One Energy to target
deployment of high-capacity charging equipment in months rather than years.606 Station
placement is optimized by locating where hosting capacity exists and thereby keeping power
distribution infrastructure costs down.
Many of the actions that reduce peak loads and energy generation needs (discussed in 1.6.4
above) also minimize user costs, and at the same time, can reduce the extent of distribution
buildout required. Some of the actions minimize upfront distribution system buildout cost and
timing while other actions align power use with cheap and plentiful energy for ongoing
operational savings. For example, managed charging covers a range of actions with varying
degrees of complexity. Time of use (TOU) charges may motivate users to charge when power is
plentiful and less expensive. Charging at lower power levels (e.g., 50 kW rather than 350 kW) is
another way to reduce the instantaneous power demand on the grid while helping the user save
on "demand charges", the maximum power level demanded over a given month (discussed in
Chapter 1.6.2.4). As noted in a report by the California Energy Commission, managed or smart
charging could also enable increasing renewable use if charging load is shifted to times with
601 Hernandez, Mari. IREC "Paving the Way Emerging Best Practices for Electric Vehicle Charger Interconnection".
June 2022. Available online: https://irecusa.org/wp-content/uploads/2022/06/EV-Paper-3-Charger-
Interconnection_compressed.pdf.
602 Schwartz, Lisa. "State Regulatory Approaches for Distribution Planning". National Association of State Utility
Consumer Advocates 2022 Mid-Year Meeting. June 14, 2022. Available online: https://www.nasuca.org/wp-
content/uploads/2021/10/NASUCA-Schwartz-distribution-planning-20220610.pdf.
603 U.S. Department of Energy. "U.S. Atlas of Electric Distribution System Hosting Capacity Maps". Accessed
March 2024. Available online: https://www.energy.gov/eere/us-atlas-electric-distribution-system-hosting-capacity-
maps.
604 Pournazeri, Sam. "Criteria to consider when siting EV charging infrastructure for medium- and heavy-duty
vehicles". ICF. April 28, 2022. Available online: https://www.icf.com/insights/transportation/medium-heavy-duty-
ev-charging.
605 Hernandez, Mari. IREC "Paving the Way Emerging Best Practices for Electric Vehicle Charger Interconnection".
June 2022. Available online: https://irecusa.org/wp-content/uploads/2022/06/EV-Paper-3-Charger-
Interconnection_compressed.pdf.
606 Truckinginfo. "Megawatt Truck Charging Hub in Ohio". October 12, 2023. Available online:
https://www.truckinginfo.com/10207881/megawatt-truck-charging-hub-opens-in-ohio
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excess solar or wind power that might otherwise be curtailed.607 Companies like Octopus Energy
have developed systems and apps that help customers align their BEV charging with wind and
solar energy when it is cheap and, and at the same time, plentiful.608 The service was launched in
Texas in 2023.609 Onsite battery storage, if deployed at charging stations, could also reduce
potential grid impacts by optimizing when power is drawn from the grid while still providing
power to vehicles when needed. FreeWire is one example of a company offering charging
solutions that combine stationary batteries with chargers. This FreeWire technology allows users
to charge the unit's 160 kWh battery slowly when electric rates are low and then charge the BEV
from the unit (not grid) at 200 kW when convenient.610 Because the unit charges at low power,
infrastructure costs and time to install may be reduced.
Other strategies could help station developers accommodate BEV charging demand for a
selected site. For example, automated load management or power control systems are being
explored as a way to dynamically limit total charging load and ensure it doesn't exceed available
capacity611—potentially reducing the need for some distribution upgrades. As noted above, the
use of onsite battery storage, managed charging, as well as onsite renewable generation may also
be able to reduce demand on the grid; some station operators may also opt for these technologies
to mitigate demand charges associated with peak power.612 The virtual power plant (VPP) is an
extension of this strategy. The VPP replaces historical electrical power generation, transmission,
and distribution with aggregations of distributed energy resources (DER). The DER tend to use
renewable sources like solar and wind that are spread through the network for their power
source. Since continuity is not ensured with solar and wind, stationary batteries (and even
available BEV) absorb excess electricity generation and store it for future use. When charging
loads (from BEV or other electricity users) exceed the power generated at any point in time, the
battery energy (stationary or even from available BEV) is deployed. The power generation
systems communicate with the storage and user systems to ensure utility grade service.613
Finally, we note that innovative or alternative charging options could reduce costs and
deployment time in some situations. Some of the options shared below allow the HD BEV user
to immediately deploy charging resources without the need for distribution upgrades or
interconnection to the grid. For example, as discussed in Chapter 1.6.2.2, some companies plan
to use mobile charging units while stations are being deployed so BEVs can be incorporated into
607 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-
infrastructure-assessment-ab-2127.
608 HD use is not yet reflected in this app.
609 Octopus Energy. "Unlock the cheapest energy rates with smart features from Octopus Energy". Available online:
https ://octopusenergy .com/smart-features
610 Freewire. "Boost Charger 200 - FreeWire's most powerful and flexible solution in ultrafast EV charging".
Accessed November 11, 2023. Available online: https://freewiretech.com/dc-boost-charger-200/
611 Nuwe and Enel X. "BRIEF - Automated Load Management for EVSE Interconnection". July 14, 2020.
Available online: https://docs.cpuc.ca.gov/PublishedDocs/Efile/G000/M354/K191/354191323.PDF.
612 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-
infrastructure-assessment-ab-2127.
613 Downing, Jennifer, et al. "Pathways to Commercial Liftoff: Virtual Power Plants". September 2023. Available
online: https://liftoff.energy.gOv/wp-content/uploads/2023/10/LIFTOFF_DOE_VVP_10062023_v4.pdf
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the fleet without waiting for EVSE installation and utility interconnection. Mobile charging units
(and on-demand mobile charging services) are available at a variety of power levels and
configurations (e.g., the dual port Mobi EV charger by FreeWire Technologies provides AC
power up to 11 kW614 while Lightning eMotors offers units with five 80 kW DCFC ports.615)
Mobile charging units could also be a potential solution for locations in which it is challenging or
costly to make upgrades needed to install EVSE ports,616 as they can be recharged at locations
(and times) with sufficient capacity. Standalone charging canopies with integrated solar cells and
battery storage that don't need to be connected to the grid may be an option for remote or other
locations where it is costly or difficult to install EVSE.617 Integrated distributed generation and
storage such as PV-integrated charging (i.e., off-grid solar),618 linear generators,619'620 and fuel
cells621 can potentially offer additional support.622
1.7 Fuel Cell Electric Vehicle Technology
Fuel cell technologies that run on hydrogen have been in existence for decades, though they
are just starting to enter the heavy-duty transportation market. Hydrogen fuel cell electric
vehicles (FCEVs) are similar to BEVs in that they have batteries and use an electric motor
instead of an internal combustion engine to power the wheels. Unlike BEVs that need to be
plugged in to recharge, FCEVs have fuel cell stacks that use a chemical reaction involving
hydrogen to generate electricity. Fuel cells with electric motors are more efficient than ICEs that
run on gasoline or diesel, requiring less energy to fuel.623
614 FreeWire Technologies. "Mobi EV Charger Data Sheet". 2023 Available online:
https://freewiretech.com/products/mobi-ev/.
615 Lightning eMotors. "Lightning energy Lightning Mobile Go anywhere power for a go anywhere world." January
2023. Available online: https://lightningemotors.com/wp-
content/uploads/2023/01/LE_Lightning_Mobile_sheet_Jan2023_vl_online.pdf.
616 Alexander, Matt et al. California Energy Commission. "Assembly Bill 2127 Electric Vehicle Charging
Infrastructure Assessment Analyzing Charging Needs to Support Zero-Emission Vehicles in 2030". July 2021.
Available online: https://www.energy.ca.gov/programs-and-topics/programs/electric-vehicle-charging-
infrastructure-assessment-ab-2127.
617 Morris, Charles. "Solar-powered off-grid EV charging stations offer surprisingly attractive cost advantages".
Charged EV Fleet & Infrastructure News. December 13, 2022. Available online:
https://chargedevs.com/features/solar-powered-off-grid-ev-charging-stations-offer-surprisingly-attractive-cost-
advantages/.
618 U.S. Department of Energy, Solar Energy Technologies Office. "Federal Solar Tax Credits for Businesses".
Available online: https://www.energy.gov/eere/solar/federal-solar-tax-credits-businesses.
619 Mainspring. "Local power generation for the zero carbon future". Available online:
https ://www. mainspringenergy .com/.
620 Sandridge, Breanna. "DOE Funding GM Pilot Program to Demonstrate Real-Life Applications of Fuel Cells for
Fleet and Commercial Customers". EnergyTech. March 8, 2024. Available online:
https://www.energytech.com/emobility/article/21284243/doe-funding-gm-pilot-program-to-demonstrate-real-life-
applications-of-fuel-cells-for-fleet-and-commercial-customers.
621 U.S. Department of Energy. "The #H2IQ Hour. Today's Topic: Caterpillar Hydrogen Fuel Cell Generator
Backup System". March 2024. Available online: https://www.energy.gov/sites/default/files/2024-03/h2iqhour-
02232024.pdf.
622 ANL. Innovative Charging Solutions for Deploying the National Charging Network: Technoeconomic Analysis.
March 2024.
623 U.S. Department of Energy, Alternative Fuels Data Center. "Hydrogen Basics". Available online:
https://afdc.energy.gov/fuels/hydrogen_basics.html.
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Hydrogen FCEVs are considered in the modeled potential compliance pathway due to several
factors. They do not emit air pollution at the tailpipe—only heat and pure water.624 With current
and near-future technologies, energy can be stored more densely onboard a vehicle as gaseous or
liquid hydrogen than it can as electrons in a battery, which enables longer ranges. HD FCEVs
can package more energy onboard with less weight than batteries in today's BEVs, which allows
for their potential use in HD sectors that are difficult for BEV technologies due to payload
impacts. HD FCEVs also have rapid refueling times.625
The following sections discuss key technology components unique to heavy-duty FCEVs.
1.7.1 Fuel Cell System
A fuel cell stack is a module that may contain hundreds of fuel cell units that generate
electricity, typically combined in series.626 A heavy-duty FCEV may have several fuel cell stacks
to meet the power needs of a comparable ICE vehicle. A fuel cell system includes the fuel cell
stacks and "balance of plant" (BOP) components (e.g., pumps, sensors, compressors,
humidifiers) that support the fuel cell operations.
Though there are many types of fuel cell technologies, polymer electrolyte membrane (PEM)
fuel cells are typically used in transportation applications because they offer high power density,
and therefore have low weight and volume. They can operate at relatively low temperatures,
which allows them to start quickly.627 PEM fuel cells are built using membrane electrode
assemblies (MEA) and supportive hardware. The MEA includes the PEM electrolyte material,
catalyst layers (anode and cathode), and gas diffusion layers.628 Hydrogen fuel and oxygen enter
the MEA and chemically react to generate electricity, which is either used to propel the vehicle
or stored in a battery to meet future power needs. The process creates excess water vapor and
heat.
Key BOP components include the air supply system that provides oxygen, the hydrogen
supply system, and the thermal management system. With the help of compressors and sensors,
these components monitor and regulate the pressure and flow of the gases supplied to the fuel
cell along with relative humidity and temperature. Similar to ICEs and batteries, PEM fuel cells
require thermal management systems to control the operating temperatures. It is necessary to
control operating temperatures to maintain stack voltage and the efficiency and performance of
the system. There are different strategies to mitigate excess heat that comes from operating a fuel
cell. For example, a HD vehicle may include a cooling system that circulates cooling fluid
through the stack.629 As the fuel cell ages and becomes less efficient, more waste heat will be
generated that requires removal. A cooling system may be designed to accommodate end-of-life
624 U.S. Department of Energy, Fuel Cell Technologies Office. "Fuel Cells". November 2015. Available online:
https://www.energy.gov/sites/prod/files/2015/ll/f27/fcto_fuel_cells_fact_sheet.pdf.
625 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "The #H2IQ Hour: Heavy-Duty
Vehicle Decarbonization". September 21, 2023. Available online: https://www.energy.gov/sites/default/files/2023-
10/h2iqhour-09212023.pdf.
626 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Fuel Cell Systems". Available
online: https://www.energy.gov/eere/fuelcells/fuel-cell-systems.
627 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Types of Fuel Cells". Available
online: https://www.energy.gov/eere/fuelcells/types-fuel-cells.
628 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Parts of a Fuel Cell". Available
online: https://www.energy.gov/eere/fuelcells/parts-fuel-cell.
629 Hyfindr. "Fuel Cell Stack". Available online: https://hyfindr.com/fuel-cell-stack/.
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needs, which can be up to two times greater than they are at the beginning of life.630 Waste heat
recovery solutions are also emerging.631 The excess heat also can in turn be used to heat the
cabin, similar to ICE vehicles. Power consumed to operate BOP components can also impact the
fuel cell system's overall efficiency.632'633
Oxygen (O2) from the air enters the positive electrode (cathode) of the cell and hydrogen gas
(H2) enters the negative electrode (anode). A catalyst separates the hydrogen molecules in the
fuel into protons and electrons. The electrons create a direct flow of electricity. The protons flow
through the electrolyte membrane and create excess water vapor, which is purged along with any
contaminants. The electrochemical reaction also produced heat, which must be effectively
managed.634 To improve fuel cell performance, the air and hydrogen fuel that enter the system
may be compressed, humidified, and/or filtered.635 A fuel cell operates best when the air and the
hydrogen are free of contaminants, since contaminants can poison and damage the catalyst. PEM
fuel cells require hydrogen that is over 99 percent pure, which can add to the fuel production
cost.636'637 Hydrogen produced from natural gas tends to initially have more impurities (e.g.,
carbon monoxide and ammonia, associated with the reforming of hydrocarbons) than hydrogen
produced from water through electrolysis.638 There are standards such as ISO 14687 that include
hydrogen fuel quality specifications for use in vehicles to minimize impurities.639
Fuel cell durability is important in heavy-duty applications, given that vehicle owners and
operators often have high expectations for drivetrain lifetimes in terms of years, hours, and
miles. Fuel cells can be designed to meet durability needs (i.e., the ability of the stack to
maintain its performance over time). Considerations must be included in the design to
accommodate operations in less-than-optimized conditions. For example, prolonged operation at
630 Pardhi, Shantanu, et. al. "A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology,
Hydrogen, Energy and Thermal Management Systems". Energies 15(24). December 2022. Available online:
https://www.mdpi.com/1996-1073/15/24/9557.
631 Baroutaji, Ahmad, et. al. "Advancements and prospects of thermal management and waste heat recovery of
PEMFC". International Journal of Thermofluids: Volume 9. February 2021. Available online:
https://www. sciencedirect.com/science/article/pii/S2666202721000021.
632 Hoeflinger, Johannes and Peter Hofmann. "Air mass flow and pressure optimization of a PEM fuel cell range
extender system". International Journal of Hydro gen Energy. Volume 45:53. October 30, 2020. Available online:
https://www.sciencedirect.com/science/article/pii/S0360319920327841.
633 Pardhi, Shantanu, et. al. "A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology,
Hydrogen, Energy and Thermal Management Systems". Energies 15(24). December 2022. Available online:
https://www.mdpi.com/1996-1073/15/24/9557.
634 U.S .Environmental Protection Agency. "Assessment of Fuel Cell Technologies at Ports". Prepared for EPA by
Eastern Research Group, Inc. EPA-420-R-22-013. July 2022. Available online:
https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1015AQX.pdf.
635 U.S .Environmental Protection Agency. "Assessment of Fuel Cell Technologies at Ports". Prepared for EPA by
Eastern Research Group, Inc. EPA-420-R-22-013. July 2022. Available online:
https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1015AQX.pdf.
636 Hyfindr. "Hydrogen PEM Fuel Cell". Available online: https://hyfindr.com/pem-fuel-cell/.
637 U.S. DRIVE Partnership. "Hydrogen Production Tech Team Roadmap". U.S. Department of Energy. November
2017. Available online: https://www.energy.gov/eere/vehicles/articles/us-drive-hydrogen-production-technical-
team-roadmap.
638 Nguyen, Huu Linh, et. al. "Review of the Durability of Polymer Electrolyte Membrane Fuel Cell in Long-Term
Operation: Main Influencing Parameters and Testing Protocols". Energies 14(13). July 2021. Available online:
https://www.mdpi.com/1996-1073/14/13/4048.
639 International Organization for Standardization. "ISO 14687: 2019, Hydrogen fuel quality—Product
specification". November 2019. Available online: https://www.iso.org/standard/69539.html.
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high voltage (low power) or when there are multiple transitions between high and low voltage
can stress the system. As a fuel cell system ages, a fuel cell's MEA materials can degrade, and
performance and maximum power output can decline. The fuel cell can become less efficient,
which can cause it to generate more excess heat and consume more fuel.640 DOE's ultimate long-
term technology target for Class 8 HD trucks is a fuel cell lifetime of 30,000 hours,
corresponding to an expected vehicle lifetime of 1.2 million miles.641 A voltage degradation of
10 percent at rated power by end-of-life is considered by DOE when evaluating targets.
Currently, the fuel cell stack is the most expensive component of a heavy-duty FCEV,642
which is the most expensive part of a heavy-duty FCEV, primarily due to the technological
requirements of manufacturing rather than raw material costs.643 Larger production volumes are
anticipated as global demand increases for fuel cell systems for HD vehicles, which could
improve economies of scale. Durability improvements are anticipated to also result in decreased
operating costs, as they could extend the life of fuel cells and reduce the need for parts
replacement.644 Fuel cells contain PEM catalysts that typically are made using precious metals
from the platinum group, which are expensive but efficient and can withstand conditions in a
cell.
The U.S. Geological Survey's 2022 list of critical minerals includes platinum (as one of
several platinum group metals, or PGMs), as used in catalytic converters. Critical minerals are
defined in the Energy Act of 2020 as being essential to the economic or national security of the
U.S. and vulnerable to supply chain disruption.645 DOE's 2023 Critical Materials Assessment,
performed independently from a global perspective and focused on the importance of materials
to clean energy technologies in future years, identifies PGMs used in hydrogen electrolyzers
such as platinum and iridium as critical. They screened out PGMs used in catalytic converters,
such as rhodium and palladium. This distinction was made due to the increased focus on
hydrogen technologies, including long-distance HD trucks, to achieve carbon emissions
640 Nhuyen, Huu Linh, et. al. "Review of the Durability of Polymer Electrolyte Membrane Fuel Cell in Long-Term
Operation: Main Influencing Parameters and Testing Protocols". Energies 14(13). July 2021. Available online:
https://www.mdpi.com/1996-1073/14/13/4048.
641 Marcinkoski, Jason et. al. "Hydrogen Class 8 Long Haul Truck Targets". U.S. Department of Energy. October
31, 2019. Available online:
https://www.hydrogen.energy.gov/pdfs/19006_hydrogen_class8_long_haul_truck_targets.pdf.
642 Papageorgopoulos, Dimitrios. "Fuel Cell Technologies Overview". U.S. Department of Energy. June 6, 2023.
Available online:
https://www.hydrogen.energy.gOv/docs/hydrogenprogramlibraries/pdfs/review23/fc000_papageorgopoulos_2023_o.
pdf.
643 Deloitte China and Ballard. "Fueling the Future of Mobility: Hydrogen and fuel cell solutions for transportation,
Volume 1". 2020. Available online:
https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/finance/deloitte-cn-fueling-the-future-of-mobility-
en-200101.pdf.
644 Deloitte China and Ballard. "Fueling the Future of Mobility: Hydrogen and fuel cell solutions for transportation,
Volume 1". 2020. Available online:
https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/finance/deloitte-cn-fueling-the-future-of-mobility-
en-200101.pdf.
645 87 FR 10381. "2022 Final List of Critical Minerals". U.S. Geological Survey. February 24, 2022. Available
online: https://www.federalregister.gov/documents/2022/02/24/2022-04027/2022-final-list-of-critical-minerals.
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reductions, and an anticipated decrease in the importance of catalytic converters in the medium
term (i.e., the 2025 to 2035 timeframe).646
Efforts are underway to minimize or eliminate the use of platinum in catalysts.647 DOE issued
a Funding Opportunity Announcement (FOA) in 2023 in anticipation of growth in hydrogen and
fuel cell technologies and systems. A portion of the FOA is designed to enable improvements in
recovery and recycling, and applicants are encouraged to find ways to reduce or eliminate PGMs
from catalysts in both PEM fuel cells and electrolyzers to reduce reliance on virgin feedstocks.648
1.7.2 Fuel Cell and Battery Interaction
The instantaneous power required to move a FCEV can come from either the fuel cell, the
battery, or a combination of both. Interactions between the fuel cells and batteries of a FCEV can
be complex and may vary based on application. Each manufacturer likely will employ a unique
strategy to optimize the durability of these components and manage costs. The strategy selected
will impact the size of the fuel cell and the size of the battery.
The fuel cell can be used to charge the battery that in turn powers the wheels (series hybrid or
range-extending), or it can work with the battery to provide power (parallel hybrid or primary
power) to the wheels. In the emerging HD FCEV market, when used to extend range, the fuel
cell tends to have a lower peak power potential and may be sized to match the average power
needed during a typical use cycle, including steady highway driving. At idle, the fuel cell may
run at minimal power or turn off based on state of charge of the battery. The battery is used
during prolonged high-power operations such as grade climbing and is typically in charge-
sustaining mode, which means the average state of charge is maintained above a certain level
while driving. When providing primary power, the fuel cell tends to have a larger peak power
potential, sized to match all power needs of a typical duty cycle and to meet instantaneous power
needs. The battery is mainly used to capture energy from regenerative braking and to help with
acceleration and other transient power demands.649
Based on how the fuel cell stacks and batteries are managed, manufacturers may use different
types of batteries in HD FCEVs. Energy battery cells are typically used to store energy for
applications with distance needs=. Power battery cells are typically used to provide additional
high power for applications with high power needs.650
646 U.S. Department of Energy. "Critical Materials Assessment". July 2023. Available online:
https://www.energy.gov/sites/default/files/2023 -07/doe-critical-material-assessment_07312023 .pdf.
647 Berkeley Lab. "Strategies for Reducing Platinum Waste in Fuel Cells. November 2021. Available online:
https://als.lbl.gov/strategies-for-reducing-platinum-waste-in-fuel-cells/.
648 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Bipartisan Infrastructure Law: Clean
Hydrogen Electrolysis, Manufactuijng, and Recycling: Funding Opportunity Announcement Number DE-FOA-
0002922". March 15, 2023 (Last Updated: March 31, 2023). Available online: https://eere-
exchange.energy.gov/Default.aspx#FoaIda9a89bda-618a-4fl3-83f4-9b9b418c04dc.
649 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential". Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6. October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1406494585829.
650 Sharpe, Ben and Hussein Basma. "A Meta-Study of Purchase Costs for Zero-Emission Trucks". International
Council on Clean Transportation. February 2022. Available online: https://theicct.org/publication/purchase-cost-ze-
trucks-feb22/.
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1.7.3 Onboard Hydrogen Storage Tanks
Fuel cell vehicles carry hydrogen fuel onboard using multiple large tanks. Hydrogen has high
gravimetric density (amount of energy stored per unit of mass) but extremely low volumetric
density (amount of energy stored per volume) so it must be compressed or liquified for use.
There are various techniques for storing hydrogen onboard a vehicle, depending on how much
fuel is needed to meet range requirements. Most transportation applications today use Type IV
tanks,651 which typically include a plastic liner wrapped with a composite material such as
carbon fiber that can withstand high pressures with minimal weight.652'653 High-strength carbon
fiber accounts for over 50 percent of the cost of a Type IV onboard storage system at production
volumes of over 100,000 systems per year.654
Some existing fuel cell buses use compressed hydrogen gas at 350 bars (-5,000 pounds per
square inch, or psi) of pressure, but other applications are using tanks with increased compressed
hydrogen gas pressure at 700 bar (-10,000 psi) for extended driving range.655 A Heavy-Duty
Vehicle Industry Group was formed in 2019 to standardize 700 bar high-flow fueling hardware
components globally that meet fueling speed requirements (i.e. so that fill times are similar to
comparable HD ICE vehicles, as identified in DOE technical targets for Class 8 long-haul
tractor-trailers).656 High-flow refueling rates for heavy-duty vehicles of 60 to 80 kg hydrogen in
under 10 minutes were recently demonstrated in a DOE lab setting.657'658'659
As we stated in the NPRM, geometry and packing challenges may constrain the amount of
gaseous hydrogen that can be stored onboard and, thus, the maximum range of trucks that travel
651 Type I-III tanks are not typically used in transportation for reasons related to low hydrogen density, metal
embrittlement, weight, or cost.
652 Langmi, Henrietta et. al. "Hydrogen storage". Electrochemical Power Sources: Fundamentals, Systems, and
Applications. 2022. Portion available online: https://www.sciencedirect.com/topics/engineering/compressed-
hydrogen-
storage#:~:text=There%20are%20four%20standard%20types,cylinders%20with%20nonload%20bearing%20nonme
tallic.
653 U.S. Department of Energy, Fuel Cell Technologies Office. "Hydrogen Storage". March 2017. Available online:
https://www.energy.gov/sites/prod/files/2017/03/f34/fcto-h2-storage-fact-sheet.pdf.
654 Houchins, Cassidy and Brian D. James. "2019 DOE Hydrogen and Fuel Cell Program Review: Hydrogen Storage
Cost Analysis". Strategic Analysis. May 2019. Available online:
https ://www. hydrogen, energy .gov/pdfs/review 19/st 100 J ames_2019_o .pdf.
655 Basma, Hussein and Felipe Rodriquez. "Fuel cell electric tractor-trailers: Technology overview and fuel
economy". Working Paper 2022-23. International Council on Clean Transportation. July 2022. Available online:
https://theicct.org/wp-content/uploads/2022/07/fuel-cell-tractor-trailer-tech-fuel-jul22.pdf.
656 NextEnergy. "Hydrogen Heavy Duty Vehicle Industry Group to Standardize Hydrogen Refueling, Bringing
Hydrogen Closer to Wide Scale Adoption". October 8, 2021. Available online: https://nextenergy.org/hydrogen-
heavy-duty-vehicle-industry-group-partners-to-standardize-hydrogen-refueling/.
657 DOE suggests that 60 kg of H2 will be required to achieve a 750-mile range in a Class 8 tractor-trailer truck,
assuming a fuel economy of 12.4 miles per kilogram. In the DOE lab, one fill (61.5 kg) was demonstrated from the
fueling station into seven type-IV tanks of a HD vehicle simulator, and the second fill (75.9 kg) was demonstrated
from the station into nine tanks.
658 Marcinkoski, Jason et. al. "Hydrogen Class 8 Long Haul Truck Targets". U.S. Department of Energy. October
31, 2019. Available online:
https://www.hydrogen.energy.gov/pdfs/19006_hydrogen_class8_long_haul_truck_targets.pdf.
659 Martineau, Rebecca. "Fast Flow Future for Heavy-Duty Hydrogen Trucks: Expanded Capabilities at NREL
Demonstration High-Flow-Rate Hydrogen Fueling for Heavy-Duty Applications". National Renewable Energy Lab.
June 2022. Available online: https://www.nrel.gov/news/program/2022/fast-flow-future-heaw-dutv-hvdrogen-
trucks.html.
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longer distances without a stop for fuel.660 Liquid hydrogen is emerging as a cost-effective
onboard storage option for long-haul operations; however, the technology readiness of liquid
storage and refueling technologies is still relatively low compared to compressed gas
technologies.661'662 Therefore, given our assessment of technology readiness, liquid storage tanks
were not included in the potential compliance pathway that supports the feasibility and
appropriateness of our standards.
Liquid hydrogen requires cryogenic storage at temperatures reaching -253 degrees Celsius at
atmospheric pressure. Preparing hydrogen for storage as a liquid is more energy intensive than
gaseous storage. For example, compression and cooling can require 10 kWh of energy per kg of
hydrogen for liquid, compared to 3 to 5 kWh per kg of hydrogen for 700 bar compressed
hydrogen and 2 kWh per kg hydrogen for 350 bar.663'664 Nonetheless, companies like Daimler
and Hyzon are pursuing onboard liquid hydrogen to minimize potential payload impacts and
maintain the flexibility to drive up to 1,000 miles between refueling, comparable to today's
diesel ICE vehicle refueling ranges.665'666
Cryo-compressed hydrogen, a hybrid storage system option that combines compressed
hydrogen gas and liquid hydrogen, is under development but is even less ready for
commercialization than liquid hydrogen.667
In the NPRM, we requested comment and data related to packaging space availability
associated with FCEVs and projections for the development and application of liquid hydrogen
in the HD transportation sector over the next decade. Only one comment was received on this
issue, from a vehicle manufacturer, who stated that they believe liquid hydrogen is required to
meet the packaging requirement for vehicles with a 500-mile range, consistent with our
assessment at the proposal. The same commenter also included 90th percentile daily VMT
estimates of 484 miles for Class 8 day cabs and 724 miles for sleeper cab tractors, based on an
18-day snapshot of telematics data, because they said they believe EPA is overestimating ZEV
application suitability.
660 Basma, Hussein and Felipe Rodriquez. "Fuel cell electric tractor-trailers: Technology overview and fuel
economy". Working Paper 2022-23. International Council on Clean Transportation. July 2022. Available online:
https://theicct.org/wp-content/uploads/2022/07/fuel-cell-tractor-trailer-tech-fuel-jul22.pdf.
661 Basma, Hussein and Felipe Rodriquez. "Fuel cell electric tractor-trailers: Technology overview and fuel
economy". Working Paper 2022-23. International Council on Clean Transportation. July 2022. Available online:
https://theicct.org/wp-content/uploads/2022/07/fuel-cell-tractor-trailer-tech-fuel-iul22.pdf.
662 Gomez, Julian A. and Diogo M.F. Santos. "The Status of On-Board Hydrogen Storage in Fuel Cell Electric
Vehicles". Designs 2023: 7(4). Available online: https://www.mdpi.eom/2411-9660/7/4/97.
663 At low heating value, one kg of H2 includes 33.3 kWh of useable energy, which is about the same amount of
energy as a gallon of diesel.
664 Gomez, Julian A. and Diogo M.F. Santos. "The Status of On-Board Hydrogen Storage in Fuel Cell Electric
Vehicles". Designs 2023: 7(4). Available online: https://www.mdpi.eom/2411-9660/7/4/97.
665 Daimler Truck. "Development milestone: Daimler Truck tests fuel-cell truck with liquid hydrogen". June 2022.
Available online: https://media.daimlertruck.com/marsMediaSite/en/instance/ko/Development-milestone-Daimler-
Truck-tests-fuel-cell-truck-with-liquid-hvdrogen.xhtml?oid=51975637.
666 Hyzon. "Hyzon Motors, Chart Industries to Develop Liquid Hydrogen Fuel Cell-Powered Truck, Targeting 1000-
Mile Range". July 2021. Available online: https://www.hvzonmotors.com/in-the-news/hvzon-motors-chart-
industries-to-develop-liquid-hvdrogen-fuel-cell-powered-truck-targeting-1000-mile-range.
667 Basma, Hussein and Felipe Rodriquez. "Fuel cell electric tractor-trailers: Technology overview and fuel
economy". Working Paper 2022-23. International Council on Clean Transportation. July 2022. Available online:
https://theicct.org/wp-content/uploads/2022/07/fuel-cell-tractor-trailer-tech-fuel-jul22.pdf.
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For the final rule, we contracted FEV Group to conduct a packaging analysis for Class 8 long-
haul FCEVs that store 700-bar gaseous hydrogen onboard.668 FEV found ways to package six
hydrogen tanks to deliver up to a 500-mile range with a sleeper cab using a 265-inch wheelbase.
All tanks could be at the back of the cab and the batteries mounted outside of the frame rails, or
four of the tanks could be behind the cab and two tanks mounted to the side frame under the cab
if the battery pack can be placed between the frame rails. This would allow a long-haul tractor to
meet a daily operational VMT requirement of 420 miles. If a HD FCEV refuels once en-route,
then it could cover a 90th percentile VMT requirement of as far as 724 miles in a day (essentially
matching the 90th percentile VMT noted by the commenter). A refueling event during the day
should not be a burden, given that refueling times are as short as 20 minutes or less and are
considered a key benefit of HD FCEVs.669
Based on our review of the literature for the NPRM and after consideration of the comments
received and additional information, our assessment is that most HD vehicles likely have
sufficient physical space to package gaseous hydrogen storage tanks onboard,670 including long-
haul sleeper cabs that travel up to 420 miles per day, or longer if they refuel en-route.
1.7.4 Fuel Cell Electric Vehicle Safety Considerations
FCEVs have two potential risk factors that must be addressed through proper design, process,
and training: hydrogen and electricity. Electricity risks are identical to those of BEVs and, thus,
are discussed in Chapter 1.5.2. Hydrogen risks can occur throughout the process of fueling a
vehicle. FCEVs must be designed so that hydrogen can be safely delivered to a vehicle and then
transferred into a vehicle's onboard storage tanks and fuel cell stacks. Hydrogen is flammable
across a wide range of concentrations and can cause explosions if it is not handled properly. If
hydrogen escapes during a fueling operation or from a vehicle fueling system, it can form a
combustible mixture with air. The flammability range of hydrogen, 4% to 75%, is much greater
than other common fuels.671 Hydrogen has a lower ignition energy than gasoline vapor of 0.02
mJ compared to 0.24 mJ, so hydrogen will ignite more easily. Hydrogen is colorless, odorless,
and tasteless so detecting leaked hydrogen is difficult. Even when ignited, the hydrogen flames
are almost invisible so visually detecting a hydrogen fire is difficult and flame detectors are
highly recommended. Fortunately, hydrogen is light and quickly rises and diffuses into the
atmosphere to the point where it is no longer flammable, so flammable concentrations are less
likely to exist. In June 2023, the World Forum for Harmonization of Vehicle Regulations under
the United Nations Economic Commission for Europe adopted the Phase 2 amendments to the
Global Technical Regulation (GTR) No. 13, 'Hydrogen and fuel cell vehicles.' The amendments
reflect extensive revisions to GTR No. 13, including improvements of test procedures, extension
of the applicability of the regulation to heavy vehicles, and a better reflection of the state-of-the-
668 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
669 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "The #H2IQ Hour. Today's Topic:
Heavy-Duty Vehicle Decarbonization". September 21, 2023. Available online:
https://www.energy.gov/sites/default/files/2023-10/h2iqhour-09212023.pdf.
670 Kast, James et. al. "Designing hydrogen fuel cell electric trucks in a diverse medium and heavy duty market".
Research in Transportation Economics: Volume 70. October 2018. Available online:
https://www.sciencedirect.com/science/article/pii/S0739885916301639.
671 Center for Hydrogen Safety. "Hydrogen Flammability". Accessed on February 2, 2023. Available online:
https://www.aiche.org/sites/default/files/docs/pages/the_elemental_-_hydrogen_flammability.pdf.
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art with respect to hydrogen vehicles. Acceptance of the draft amendments has put into place the
first regulation for heavy-duty vehicles fueled by hydrogen.672
Components and systems that store and move hydrogen are designed to accommodate small
hydrogen molecules that are challenging to contain. Even with properly designed systems, small
leaks are common. The vehicles themselves may have minor leaks but must not leak hydrogen
into areas that can capture the rising gas. If vehicles are indoors for storage or repair, proper
passive ventilation must include outlet openings at the high point of the enclosure so the
hydrogen can vent. Active ventilation is also an option as fans and actuators exist that are
classified for use where hydrogen could be present. If a FCEV is outdoors under a roof, the roof
design should ensure that rising hydrogen does not have the opportunity to accumulate in any
traps.
Use of hydrogen in a FCEV drives design considerations and standard procedures that help
ensure safety during and after a crash. In-tank solenoid valves673 are used to turn off hydrogen
flow if needed to prevent an uncontrolled release of hydrogen. The solenoid will close if a
prescribed level of impact is detected. First responders can help ensure solenoid closure by
turning the vehicle off or physically interrupting the 12V supply as the solenoid default (no
power) is off. If the physical integrity of the hydrogen storage tank is at risk due to fire, a
thermally activated pressure relief device (TPRD) will vent the hydrogen. FCEV designs protect
the hydrogen handling components. Since a crash may cause physical damage that releases
hydrogen, care is taken to avoid traps where hydrogen can accumulate. Training of first
responders for unique FCEV dangers and protocol is crucial. Vehicle specific emergency
response documentation that helps the first responders apply their training safely and efficiently
should be made readily available to first responders. Finally, post-crash, an initial inspection
should be completed to verify the vehicle can be safely removed from the crash site. The FCEV
should then be stored in an isolated area where final inspection and risk remediation can be
implemented.674'675
Hydrogen has been handled, used, stored, and moved in industrial settings for more than 50
years, and there are established methods for doing so safely.676 There is also federal oversight
and regulation throughout the hydrogen supply chain system.677 Safety training and education
are key for maintaining reasonable risk while handling and using hydrogen. For example,
hydrogen-related fuel cell vehicle risks can be mitigated through:
672 International Energy Agency. "Global Hydrogen Review 2023". December 2023. Available online:
https://iea.blob.core.windows.net/assets/ecdfc3bb-d212-4a4c-9ff7-6ce5blel9cef/GlobalHydrogenReview2023.pdf.
673 A solenoid valve is a valve utilizing an electromagnet formed by a coil of wire in the shape of a cylinder. When it
carries a current, it acts like a magnet and the movable core is drawn into the coil causing the valve to either open or
close.
674 SAE International J2990-1. "Gaseous Hydrogen and Fuel Cell Vehicle First and Second Responder
Recommended Practice". June 2016.
675 SAE International. "WIP: Gaseous Hydrogen and Fuel Cell Vehilce First and Second Responder Recommended
Practice J2990/1". December 2, 2019. Available online: https://www.sae.Org/standards/content/j2990/l/.
676 Hydrogen Tools. "Best Practices Overview". Pacific Northwest National Laboratory. Accessed on February 2,
2023. Available online: https://h2tools.org/bestpractices/best-practices-overview.
677 Baird, Austin R. et. al. "Federal Oversight of Hydrogen Systems". Sandia National Laboratories. SAND2021-
2955. March 2021. Available online: https://energv.sandia.gov/wp-content/uploads/2021/03/H2-Regulatory-Map-
Report SAND2021-2955.pdf.
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• proper no/low leak designs for: infrastructure, hydrogen fill equipment, vehicle
connectors, and vehicle storage and supply;
• ambient hydrogen concentration monitoring and alarm;
• hydrogen pressure monitoring in the vehicle and infrastructure to indicate leaks;
• proper ventilation in and around hydrogen fueling equipment and fuel cell vehicles;
• vehicle controls to ensure the vehicle cannot be driven while fueling equipment is
attached; and
• vehicle controls that isolate hydrogen storage in the case of an accident.678
The following codes and standards are in place to guide safe use of hydrogen:
• SAE J2578, Recommended Practice for General Fuel Cell Vehicle Safety
• SAE J2579, Standard for Fuel Systems in Fuel Cell and Other Hydrogen Vehicles
• SAE J2990, Hybrid and EV First and Second Responder Recommended Practice (with
recommendations for hazards associated with hydrogen vehicles) OSHA standard 29
CFR 1910.103 on Hydrogen
Hydrogen risk is usually reduced due to its buoyancy and rapid dissipation. These physical
aspects of hydrogen have less positive impact in enclosures like tunnels. DOE/Sandia National
Laboratories is working with other authorities to evaluate safety in tunnels.679 Per NHTSA, DOE
is also working with local authorities to evaluate safety and travel of FCEV in tunnels like
Boston and Baltimore harbor tunnels. If these studies find it prudent to restrict HD FCEV from
the tunnels, HD FCEV would need to use the same alternative routes currently used by fuel
tankers and the like.680 FCEVs including their storage systems, like ICE vehicles, are required to
meet the Federal Motor Vehicle Safety Standards (FMVSS) for crash safety so that the systems
will maintain their integrity after the specified crash conditions. Additional FCEV safety
information is available in RTC Section 4.9. EPA obtained additional NHTSA safety input
regarding comments and updates for the final rulemaking.681
1.7.5 FCEV Market
The fuel cell market for heavy-duty vehicles is not as far along as the market for heavy-duty
BEVs. When EPA conducted an analysis of manufacturer-supplied end-of-year production
678 Hydrogen Tools. "Hydrogen Infrastructure and Vehicle Safety". Pacific Northwest National Laboratory.
Accessed on February 2, 2023. Available online: https://h2tools.org/safetv-hvdrogen-vehicles-and-infrastructure-
bulletin.
679 Glover, et. al. "Hydrogen Fuel Cell Vehicles in Tunnels". Sandia National Laboratories. SAND2020-4507 R.
April 2020. Available online: https://energy.sandia.gov/wp-content/uploads/2020/05/Hydrogen-Fuel-Cell-Vehicles-
in-Tunnels_SAND2020-204507r.pdf.
680 Cole, Matt. "Colorado DOT to study allowing hazmat trucks to travel through I-70's Eisenhower Tunnel".
Overdrive. April 12, 2019. Available Online:
https://www.overdriveonline.com/business/article/14896160/colorado-dot-to-study-allowing-hazmat-trucks-to-
travel-through-i-70s-eisenhower-tunnel.
681 Landgraf, Michael. Memorandum to docket EPA-HQ-OAR-2022-0985. Summary of NHTSA Safety
Communications. February 14, 2024.
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reports provided to us as a requirement of the process to certify HD vehicles to our GHG
emission standards, based on the end-of-year production reports for MY 2019, there were no HD
FCEVs certified through MY 2021. Some models are available now and others are still being
developed and tested but are anticipated in the coming decade. According to the Global
Commercial Vehicle Drive to Zero Zero-Emission Technology Inventory (ZETI), the following
fuel cell vehicles are expected to become commercially available for production in the United
States and Canada region by CY 2024, as shown in Table 1-29.682
Table 1-29 Current and Projected North American HD Fuel Cell Vehicles
OEM
Vehicle
Class
Range
Est. Payload
Energy Capacity
First
Available
Year
Hyzon
Hyzon
Class 8
500 mi
70 kg
2022
International
HD Hydrogen
Fuel Cell Truck
Class 8
500 mi
2024
Kenworth/T oyota
T680
Class 8
400 mi
110,000 lbs
2023
Nikola
Tre
Class 8
500 mi
40,000 lbs
2023
Nikola
Two
Class 8
900 mi
40,000 lbs
2024
Toyota
Beta
Class 8
300 mi
88,185 lbs
40 kg
2023
Hyzon
Econic Refuse
Class 8
125 mi
2000 lbs
25 kg
2019
Unique Electric
FCCC MT-55 FC
Class 6
140 mi
4000 lbs
2021
Solutions (UES)
UES
F-59 FC
Class 6
140 mi
4000 lbs
2021
UES
International 1652
FC
Class 6
150 mi
4000 lbs
2020
ElDorado National
AXESS FC 35 ft
Transit
Bus
260 mi
42 seats
2020
ElDorado National
AXESS FC 40 ft
Transit
Bus
260 mi
43 seats
2020
New Flyer
Xcelsior
CHARGE H2 -
40 ft
Transit
Bus
350 mi
40 seats
38 kg
2020
New Flyer
Xcelsior
CHARGE H2 -
60 ft
Transit
Bus
350 mi
52 seats
60 kg
2020
Cenntro Electric
LM864H
Class 7
186 mi
81,571 lbs
1680 L
2023
Group
40 kg (ci>, 350 bar est.
Hyundai
XCient
Class 8
249 mi
42,990 lbs
32 kg
2023
The Hydrogen Fuel Cell Partnership states that fuel cell electric buses have been in
commercial development for 20 years and, as of May 2020, 60 buses are in operation or in
planning in the U.S.683 As of October 2022, California's Innovative Clean Transit program
identified over 2000 FCEV transit bus potential future purchases throughout the state.684
682 CALSTART. "Drive to Zero's Zero-Emission Technology Inventory (ZETI) Tool Version 8.0". Accessed
November 2023. Available online: https://globaldrivetozero.org/tools/zeti/.
683 Hydrogen Fuel Cell Partnership. "Buses & Trucks". Available online: https://h2fcp.org/buses_trucks.
684 California Air Resources Board. "Fuel Cell Electric Bus Deployment in California: FCEB-Deployment-
Map.pdf'. Last updated 10/22/2022. Available online: https://ww2.arb.ca.gov/sites/default/files/2022-10/FCEB-
Deployment-Map.pdf.
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Deployments have occurred so far, for example, in Los Angeles County, where Foothill Transit
began operating 33 FCEV transit buses in 2023 and ordered 19 additional FCEV buses;685 and in
Orange County, where the Transportation Authority is operating 10 FCEB transit buses and has
fueling station capacity to for up to 50 buses that is scalable to 100 buses with additional fuel
storage and components.686 In addition, the Regional Transportation Commission of Southern
Nevada awarded a contract for seven FCEV transit buses with an option to purchase up to 100
additional buses over the duration of a five-year contract.687 The Champagne-Urbana Transit
District in Illinois has two FCEV transit buses that run on electrolysis powered by solar
energy,688 and a project in Montgomery County, Maryland, plans to follow suit with 13 buses.689
Several Class 6 to 8 HD FCEVs have been demonstrated in California. For example, there
was successful testing of 10 Toyota-Kenworth Class 8 fuel cell tractors in the Port of Los
Angeles and surrounding area through the Zero- and Near-Zero Emissions Freight Facilities
"Shore to Shore" project (Spring 2019-2023);690'691 four FCEV walk-in delivery vans (February
2019 to Fall 2022),692 and then 15 more FCEV delivery vans (Winter 2019-2022).693 A current
project will build and deploy at least 30 fuel cell trucks at the Port of Oakland along with a
hydrogen fueling station (August 2021 to Spring 2025).694'695
Additional Class 8 FCEVs are under development. Some may be for nonroad applications
such as yard tractors at ports or are not expected for production until after 2024. For example:
685 Foothill Transit. "Greening Big". August 22, 2023. Available online: https://www.foothilltransit.org/greeningbig.
686 Orange County Transportation Authority. "Hydrogen Fuel Cell Electric Bus". Available online:
https://www.octa.net/about/about-octa/environmental-sustainability/fuel-cell/.
687 NFI Group Inc. "NFI receives third zero-emission contract from RTC, for up to 107 New Flyer fuel cell-electric
buses, expanding sustainable, high-capacity mobility in Southern Nevada". April 28, 2023. Available online:
https://www.globenewswire.com/news-release/2023/04/28/2657341/0/en/NFI-receives-third-zero-emission-
contract-from-RTC-for-up-to-107-New-Flyer-fuel-cell-electric-buses-expanding-sustainable-high-capacity-
mobility-in-Southern-Nevada.html.
688 Hays, Emily. "Hydrogen buses come to Champaign-Urbana mass transit". October 19, 2021. Available online:
https ://ipmnewsroom. org/hydrogen-buses-roll-out-from-urbana/.
689 Gallucci, Maria. "This East Coast bus depot will make its own carbon-free fuel". May 18, 2023. Available
online: https://www.canarymedia.com/articles/public-transit/this-east-coast-bus-depot-will-make-its-own-carbon-
free-fuel.
690 Heavy Duty Trucking. "FCEV Drayage Trucks Prove Themselves in LA Port Demonstration Project" September
22, 2022. Available online: https://www.truckinginfo.com/10181655/fcev-drayage-trucks-prove-themselves-in-la-
port-demonstration-proj ect.
691 California Air Resources Board. "LCTI: Port of Los Angeles "Shore to Store" Project. Available online:
https ://ww2. arb. ca.gov/lcti-port-los-angeles-shore-store-proj ect.
692 California Air Resources Board. "LCTI: Next Generation Fuel Cell Delivery Van Deployment". Available
online: https://ww2.arb.ca.gov/lcti-next-generation-fuel-cell-delivery-van-deployment.
693 California Air Resources Board. "LCTI: Fuel Cell Hybrid Electric Delivery Van Deployment". Available online:
https://ww2.arb.ca.gov/lcti-fuel-cell-hybrid-electric-delivery-van-deployment.
694 Adler, Alan. "Hyundai's Xcient positioned for instant US fuel cell truck leadership". FreightWaves. November
29, 2022. Available online: https://www.freightwaves.com/news/hyundais-xcient-positioned-for-instant-us-fuel-cell-
truck-leadership.
695 California Air Resources Board. "LCTI: NorCAL Zero-Emission Regional ad Drayage Operations with Fuel Cell
Electric Trucks. Available online: https://ww2.arb.ca.gov/lcti-norcal-zero-emission-regional-and-drayage-
operations-fuel-cell-electric-trucks.
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• Nikola commercially launched the MY2024 Tre FCEV at their manufacturing facility
in Coolidge, Arizona, which has an expected production capacity of approximately
2,400 BEV and FCEV trucks per year.696
o Nikola's Tre FCEV received eligibility for the California Air Resources Board
(CARB) Hybrid and Zero Emission Truck and Bus Voucher Incentives Project
(HVIP) program in California, which means that customers can receive a
point-of-sale incentive starting at $240,000 per truck with warranty and service
support.697
• Hyzon Motors has a Class 8 FCEV and a FCEV conversion that qualify for HVIP.
• Hyundai XCIENT Class 8 truck qualifies for HVIP.698
• PACCAR and Toyota are expanding efforts to develop and produce FCEV Kenworth
T680 and Peterbilt 579 truck models with initial customer deliveries planned for
2024.699
o Toyota received a Zero Emission Powertrain (ZEP) Executive Order from
CARB for a new heavy-duty fuel cell electric powertrain kit that includes
hydrogen fuel storage tanks, fuel cell stacks, batteries, and electric motors and
transmission. This means the powertrain complies with CARB regulations for
zero-emission powertrains.
• DTNA and Cummins are collaborating to validate Freightliner Cascadia trucks with
Cummins fuel cell powertrains for use in North America in 2024, pending success.700
• Volvo and Daimler joined forces in the European Union to launch cellcentric to
accelerate the use of hydrogen fuel cells in long-haul trucks.701
o They completed successful road tests in the Arctic Circle in early 2023.702
o Volvo Trucks is developing a Class 8 truck with a 600-mile range.703
696 Nikola. "Nikola Celebrates the Commercial Launch of Hydrogen Fuel Cell Electric Truck in Coolidge, Arizona".
September 28, 2023. Available online: https://www.nikolamotor.com/press releases/nikola-celebrates-the-
commercial-launch-of-hvdrogen-fuel-cell-electric-truck-in-coolidge-arizona/.
697 Nikola Corporation. "Nikola Tre FCEV Receives CARB HVIP Incentive Eligibility". PR Newswire. February 7,
2023. Available online: https://www.prnewswire.com/news-releases/nikola-tre-fcev-receives-carb-hvip-incentive-
eligibility-301740512.html.
698 California HVIP. "Tractor". Accessed November 2023. Available online: https://californiahvip.org/vehicle-
category/heavy-duty/.
699 Toyota Newsroom. "PACCAR and Toyota Expand Hydrogen Fuel Cell Truck Collaboration to Include
Commercialization. May 2, 2023. Available online: https://pressroom.toyota.com/paccar-and-toyota-expand-
hydrogen-fuel-cell-truck-collaboration-to-include-commercialization/.
700 AfterMarket News. "DTNA, Cummins Collaborate on Hydrogen Fuel Cell Trucks". May 16, 2022. Available
online: https://www.aftermarketnews.com/dtna-cummins-collaborate-on-hydrogen-fuel-cell-trucks-forward-in-
north-america/.
701 OEM Off-Highway Magazine. "Daimler and Volvo Launch Strategy for Fuel Cell Joint Venture". April 29,
2021. Available online: https://www.oemoffhighway.com/electronics/power-systems/press-release/21403767/volvo-
group-global-daimler-and-volvo-launch-strategy-for-fuel-cell-joint-venture.
702 Fisher, John. "Volvo finding fuel cell success in Arctic conditions". FleetOwner. May 30, 2023. Available online:
https://www.fleetowner.com/emissions-efficiency/article/21266721/volvo-testing-fuel-cell-tech-in-arctic-conditions.
703 Edelstein, Stephen. "Volvo fuel-cell semi: 600 miles, 15-minute refueling with green hydrogen still not widely
available". June 21, 2022. Available online: https://www.greencarreports.com/news/1136248_volvo-fuel-cell-semi-
600-miles-15-minute-refueling-green-hydrogen.
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• Isuzu and Honda announced a partnership in Japan to develop fuel cell technology for
heavy-duty trucks for the market, scheduled to launch in 2027.704
• Hino built a Class 8 FCEV prototype.705
• Scania plans to deliver fuel cell trucks to customers in Switzerland in 2024 and
2025.706
• Quantron received an order for 500 Class 8 FCEVs in the U.S. for delivery by
2024.707'708
o Quantron US is preparing to launch a 750-mile Class 8 FCEV tractor in North
America in 2024 that can store 80 kg of hydrogen at 700 bar of pressure.709
• Symbio, a joint venture between Faurecia and Michelin, received a California Energy
Commission grant to support establishment of a facility to assemble regional HD
FCEV Class 8 trucks, medium-duty FCEVs, and fuel cell power systems. They are
demonstrating a regional-haul Class 8 truck along a 400-mile route under the Symbio
H2 Central Valley Express Project.710
• In December 2022, Air Liquide, Hyzon Motors, and the TALKE Group began a
demonstration of a hydrogen fuel cell electric truck in the Port of Houston.711
• A zepp.solutions long-range sleeper truck called Europa is scheduled to enter
operation in late 2023.712
• Autocar announced that they will be making Class 8 vocational FCEVs such as
cement mixers and dump trucks using Hydrotec fuel cell "power cubes" made by
704 Honda. "Isuzu Selects Honda as Partner to Develop and Supply Fuel Cell System for its Fuel Cell-Powered
Heavy-duty Truck Scheduled to be Launched in 2027". May 15, 2023. Available online:
https://global.honda/en/newsroom/news/2023/c230515aeng.html.
705 Hino Trucks. "Hino Trucks Reveals First XL8 Fuel Cell Electric Truck Prototype". August 31, 2021. Available
online: https://www.hino.com/press20210831.html.
706 Scania. "Scania to deliver fuel cell trucks in Switzerland". November 8, 2022. Available online:
https://www.scania.com/group/en/home/newsroom/news/2022/scania-to-deliver-fuel-cell-trucks-to-
switzerland.html#:~:text=We%20now%20develop%20Scania's%20first,Switzerland%20in%202024%20and%2020
25.
707 FuelCellsWorks. "Quantron US Receives Order for 500 Class 8 Hydrogen Fuel Cell Powered Trucks". October
12, 2022. Available online: https://fuelcellsworks.com/news/quantron-us-receives-order-for-500-class-8-hydrogen-
fuel-cell-powered-trucks/.
708 Quantron AG. "Up to 500 QUANTRON Class 8 Fuel Cell Trucks for US-based TMP Logistics Group Ltd. PR
Newswire. October 12, 2022. Available online: https://www.prnewswire.eom/news-releases/up-to-500-quantron-
class-8-fuel-cell-trucks-for-us-based-tmp-logistics-group-ltd-301647751 .html.
709 Crissey, Jeff. "Quantron has long-range ambitions for U.S. Class 8 hydrogen fuel cell truck". Clean Trucking.
November 9, 2023. Available online: https://www.cleantrucking.com/hydrogen/article/15638212/quantron-has-
longrange-ambitions-for-us-class-8-hydrogen-fuel-cell-
truck?utm_source=email&utm_medium=email&utm_campaign=AD2023+CT+Quantron-to-enter-US-
market_NL_Engaged&utm_term=AE3110CJC&ust_id=5634G474310 lH9J&utm_content= 11-21-2023.
710 Symbio. "Symbio North America received grant award from California Energy Commission for manufacturing
hydrogen fuel cell vehicle power systems and vehicle assembly". May 2, 2023. Available online:
https://www.symbio.one/en/news-and-media/symbio-north-america-received-grant-award-california-energy-
commission-manufacturing.
711 Air Liquide. "Air Liquide fuels first hydrogen fuel cell truck demonstration at Port of Houston". January 12,
2023. Available online: https://usa.airliquide.com/hyzon-port-of-houston.
712 FuelCellsWorks. "zepp.solutions Unveils Specifications of New Hydrogen-Powered Truck: 'Europa' to Launch
in Q4 2023". February 7, 2023. Available online: https://fuelcellsworks.com/news/zepp-solutions-unveils-
specifications-of-new-hydrogen-powered-truck-europa-to-launch-in-q4-2023/.
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General Motors. They expect to start producing vehicles at a plant in Birmingham,
Alabama, in 2026.713
• Hybot, a Chinese company, unveiled a gaseous FCEV sleeper cab called H49 with a
range of over 600 miles, expected to be officially launched into mass production in
2025.714GM and Honda have started production of fuel cells in Brownstown, MI, to
power commercial trucks and other applications.715
Fleets are also starting to purchase HD FCEVs:
• Nikola has agreements with fleets to purchase or lease over 200 Class 8 trucks upon
satisfactory completion of demonstrations.716'717'718'719
o In addition, AJR Trucking announced purchase of 50 Nikola Tre FCEVs, with
deliveries expected through 2024.720
• Amazon signed an agreement with Plug Power,721'722 a company building an end-to-
end hydrogen ecosystem, to supply hydrogen for up to 800 HD long-haul trucks or
30,000 forklifts (which are commonly powered using hydrogen) starting in 2025
through 2040.723
• Walmart is purchasing hydrogen from Plug Power.724 Walmart plans to expand pilots
of fuel cell forklifts, yard trucks, and possibly HD long-haul trucks by 2040.725
713 HDT Truckinginfo. "Autocar, GM to Produce Fuel-Cell Electric Vocational Trucks". December 8, 2023.
Available online: https://www.truckinginfo.com/10211875/autocar-and-gm-announce-electric-truck-joint-venture.
714 Collins, Leigh. "Chinese start-up unveils world's first gaseous-hydrogen truck with 1,000km range".
Hydrogenlnsight. December 14, 2023. Available online:https://www.hydrogeninsight.com/transport/chinese-start-
up-unveils-worlds-first-gaseous-hydrogen-truck-with-1 -000km-range/2-1 -1570968.
715 Tingwall, Eric. "The Next Diesel? GM and Honda Start U.S. Production of Hydrogen Fuel Cells. January 25,
2024. Available online: https://www.motortrend.com/news/honda-general-motors-hydrogen-fuel-cell-production-
start/.
716 HDT Truckinginfo. "Pennsylvania Flatbed Carrier to Lease 100 Nikola Tre FCEVs." October 14, 2021.
Available online: https://www.truckinginfo.com/10153974/pennsylvania-flatbed-carrier-to-lease-100-nikola-tre-evs.
717 Green Car Congress. "Covenant Logistics Group signs letter of intent for 10 Nikola Tre BEVs and 40 Tre
FCEVs." January 12, 2022. Available online: https://www.greencarcongress.com/2022/01/20220112-covenant.html.
718 Adler, Alan. "Plug Power will buy up to 75 Nikola fuel cell trucks." Freightwaves. December 15, 2022.
Available online; https://www.freightwaves.com/news/plug-power-will-buy-up-to-75-nikola-fuel-cell-trucks.
719 Nikola. "Nikola Corporation Reports Third Quarter 2023 Results." November 2, 2023. Available online:
https://www.nikolamotor.com/press_releases/nikola-corporation-reports-third-quarter-2023-results/.
720 AJR Trucking. "AJR Trucking Announces Order for 50 Nikola Tre FCEVs". May 2, 2023. Available online:
https ://www. aj rtrucking. com/blog/aj r-trucking-announces-order-for-50-nikola-tre-fcevs/.
721 Plug Power. "About Us". Available online: https://www.plugpower.com/about-us/.
722 Adler, Alan. "Forklift-fueling hydrogen network holds long-haul trucking potential: Amazon, Walmart
distribution centers could form a backbone". FreightWaves. April 21, 2023. Available online:
https://www.freightwaves.com/news/todays-forklift-fueling-hydrogen-network-holds-long-haul-trucking-potential.
723 Amazon. "Amazon adopts green hydrogen to help decarbonize its operations". August 25, 2022. Available
online: https://www.aboutamazon.com/news/sustainability/amazon-adopts-green-hydrogen-to-help-decarbonize-its-
operations.
724 Plug Power. "Plug Supplies Walmart with Green Hydrogen to Fuel Retailer's Fleet of Material Handling Lift
Trucks". April 19, 2022. Available online: https://www.ir.plugpower.com/press-releases/news-details/2022/Plug-
Supplies-Walmart-with-Green-Hydrogen-to-Fuel-Retailers-Fleet-of-Material-Handling-Lift-Trucks/default.aspx.
725 Proactive. "WalMart eyes benefits of hydrogen delivery vehicles in wider trials". Proactive 13:17. June 8, 2022.
Available online: https://www.proactiveinvestors.co.uk/companies/news/984360/walmart-eyes-benefits-of-
hydrogen-delivery-vehicles-in-wider-trials-984360.html.
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• Plug Power has agreed to purchase up to 75 Nikola Class 8 fuel cell trucks over the
next three years in exchange for supplying the company with hydrogen fuel.726
• Performance Food Group, Inc. (PFG) entered an agreement with Hyzon for five
FCEVs with 110 kW fuel cell systems, and possibly 15 or more FCEVs with 200 kW
systems pending a successful vehicle trial.727
As the costs of components and hydrogen fuel decrease over time, we expect the HD FCEV
market to grow.
1.7.5.1 FCEV Component Manufacturers
Currently, most of the components of a fuel cell vehicle are the same as components in a HD
BEV. See Table 1-30 for an abbreviated list of manufacturers of HD FCEV-specific components
that are additional to a HD BEV.
Table 1-30 FCEV Component Manufacturers
Component
Manufacturers
PEM Fuel Cell Stack728
Bosch, Ballard, Nuvera, Advent, Cummins, GM Hydrotec, Toyota
Hydrogen Tank729
Quantum, Hanwha Cimarron (Hanwha Solutions), Voith
This list includes Bosch, who announced an investment of $200 million in South Carolina to
produce fuel cell stacks for hydrogen fuel cell trucks,730 and General Motors, who announced
726 Adler, Alan. "Plug Power will buy up to 75 Nikola fuel cell trucks". Freightwaves. December 15, 2022.
Available online: https://www.freightwaves.com/news/plug-power-will-buy-up-to-75-nikola-fuel-cell-trucks.
727 HDT Truckinginfo. "Performance Food Group Plans to Buy Hyzon Fuel Cell Trucks". June 9, 2023. Available
online: https://www.truckinginfo.com/10200499/performance-food-group-to-purchase-hyzon-fuel-cell-trucks.
728 Advent. "Advent Fuel Cells: Digi-Tronic". Available online: https://www.advent.energy/advent-digi-tronic/.:
Nuvera. "What distinguishes Nuvera fuel cell stacks?". Available online: https://www.nuvera.com/technology.:
Ballard. "Heavy Duty Modules: FCmove". Available online: https://www.ballard.com/fuel-cell-solutions/fuel-cell-
power-products/motive-modules.: Bosch. "Fuel-cell stacks: the recipe for success in mass manufacturing".
Available online: https://www.bosch.com/stories/fuel-cell-stack/.: GM. "Hydrotec". Available online:
https://www.gm.com/commitments/hydrotec.; acceleraby Cummins. "Technologies: Fuel Cells". Available online:
https://www.accelerazero.com/fuel-cells.; Shepard, Paul. "News: Cummins Acquires Hydrogenics for Fuel Cell and
Hydrogen Production Tech". September 2019. Available online: https://eepower.com/news/cummins-acauires-
hvdro genics-for-fuel-cell-and-hvdro gen-production-tech/#.
729 Quantum Fuel Systems. "Scalable Hydrogen Fuel Systems and Infrastructure". Available online:
https://www. qtww. com/product/hvdrogen/.: Hanwha Cimarron. "Hanwha Cimarron developed distinguished Type-4
technology that enables Hydrogen storing tanks for Fuel Cell". Available online: https://hanwhacimarron.com/on-
vehicle/.: Voith. "Plug & Drive H2 Storage System". Available online: https://voith.com/corp-en/drives-
transmissions/drive-h2.html.
730 Ohnsman, Alan. "Bosch Is Investing $200 Million to Make Fuel Cells for Hydrogen Trucks in South Carolina".
Forbes. August 31, 2022. Available online: https://www.forbes.com/sites/alanohnsman/2022/08/3Q/bosch-to-make-
fuel-cells-for-hvdro gen-trucks-in-south-carolina/?sh=3 da3 873b2242.
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that it will supply fuel cells to Navistar.731 Toyota also announced plans to assemble fuel cell
modules for use in heavy-duty commercial trucks starting in 2023.732
1.7.6 FCEV Research and Development
DOE has a Hydrogen and Fuel Cell Technologies Office focused on research, development,
and demonstration of hydrogen and fuel cell technologies across sectors, including
transportation. Through the 21st Century Truck Partnership and SuperTruck 3, they are working
with industry stakeholders to reduce emissions of freight transportation, 733 with the projects
listed in Table 1-31 for 2022 through 2026 focused on fuel cell trucks.
Table 1-31 DOE Funded Hydrogen HDV Projects Awarded in 2022734
Company
Project Description
Award Amount*
Daimler Trucks North
America, LLC
Develop and demonstrate two 2 Class-8 fuel cell trucks with 600-
mile range, 25,000-hour durability, equivalent payload capacity
and range to diesel.
$25,791,669
Ford Motor Company
Develop and demonstrate five hydrogen fuel cell electric Class-6
Super Duty trucks targeting cost, payload, towing, and refueling
times that are equivalent to conventional gasoline trucks.
$24,952,314
General Motors, LLC
Develop and demonstrate four hydrogen fuel cell and four battery
electric Class 4-6 trucks. The project will also focus on
development of clean hydrogen via electrolysis and clean power
for fast charging
$26,061,726
* Subject to appropriations.
DOE also works with industry through the Million Mile Fuel Cell Truck (M2FCT) multi-lab
consortium to advance the efficiency and durability of PEM fuel cells at a pre-competitive level
to enable their commercialization for heavy-duty vehicle applications with an initial focus on
long-haul trucks.735
731 Eisenstein, Paul A. "GM Enters The Fuel Cell Business, Will Power Navistar Trucks". Forbes: Wheels. October
4, 2021. Available online: https://www.forbes.com/wheels/news/gm-enters-fuel-cell-business-power-navistar-
trucks/.
732 Zurschmeide, Jeff. "Toyota Expands U.S. Fuel Cell Manufacturing for Heavy Trucks". The Detroit Bureau. July
12, 2023. Available online: https://www.thedetroitbureau.eom/2023/07/toyota-expands-u-s-fuel-cell-manufacturing-
for-heavy-trucks/.
733 U.S. Department of Energy. "DOE Projects Zero Emissions Medium- and Heavy-Duty Electric Trucks Will Be
Cheaper than Diesel-Powered Trucks by 2035". March 2022. Available online:
https://www.energv.gov/articles/doe-proiects-zero-emissions-medium-and-heaw-dutv-electric-trucks-will-be-
cheaper-diesel.
734 U.S. Department of Energy. "DOE Announces Nearly $200 Million to Reduce Emissions From Cars and Trucks.
November 1, 2021. Available online: https://www.energy.gov/articles/doe-announces-nearly-200-million-reduce-
emissions-cars-and-trucks.
735 Million Mile Fuel Cell Truck. "Zero-emission Fuel Cell Trucks powered by Hydrogen: Envisioning a future fleet
of emission-free heavy-duty vehicles". U.S. Department of Energy, Available online:
https://millionmilefuelcelltruck.org/.
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1.8 Overview of Hydrogen Industry and Infrastructure
This section provides a basic overview of hydrogen infrastructure and then discusses the
status and outlook of an early market hydrogen refueling network for HD FCEVs.
1.8.1 Hydrogen Characteristics and Use
Hydrogen is the lightest and most abundant element in the universe, composed of one proton
and one electron. It has low volumetric density, so it must be compressed or liquified for use, but
high gravimetric density, with about 2.5 to 3 times the energy content per unit of mass than
gasoline or diesel.736
Today, hydrogen is mainly used in oil refining and other industrial sectors such steel
production, and as a feedstock to produce chemicals like methanol or ammonia for products such
as fertilizer. As additional renewable electricity from wind and solar technologies is added to the
grid, hydrogen could be used as an energy carrier to seasonally store excess energy to help
balance intermittent supply with varying demand.737 Hydrogen could also be used as a fuel for
hard-to-decarbonize transportation modes like heavy-duty trucks, rail, and marine vessels.
In 2020, DOE began characterizing the growth potential of a diverse hydrogen industry in the
United States through an H2@Scale initiative. The overarching vision highlights opportunities
for hydrogen as an essential feedstock and energy carrier that can enable zero and near-zero
emissions across multiple sectors, along with energy security and resiliency. Its expansive use
can lead to economies of scale that can drive revenue prospects while making hydrogen more
affordable.738 The range of sectors that could participate in a larger H2 economy are
demonstrated in Figure 1-18.739
736 Chukwudi Tashie-Lewis, Bernard and Somtochukwu Godfrey Nnabuife. "Hydrogen Production, Distribution,
Storage and Power Conversion in a Hydrogen Economy—A Technology Review". Chemical Engineering Journal
Advances, Volume 8. November 15, 2021. Available online:
https://www.sciencedirect.eom/science/article/pii/S2666821121000880#bib0012.
737 In May 2022, renewable power exceeded demand for power in California for the first time in history. Satyapal,
Sunita. "2022 AMR Plenary Session". U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office.
June 6, 2022. Available online: https://www.energy.gov/sites/default/files/2022-06/hfto-amr-plenary-satyapal-2022-
l.pdf.
738 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "H2@Scale". Available online:
https://www.energy.gov/eere/fuelcells/h2scale.
739 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "H2@Scale". Available online:
https ://www. energy. gov/eere/fuelcells/h2scale.
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Conventional Storage
Transportation
Synthetic
Fuels
Upgrading
Oil/
Ammonia/
Fertilizer
Fossil
with CCUS
Metals
Production
Chemical/Industrial
Processes
Gas
Infrastructure
Heat/Distributed
Power
CCUS: Carbon Capture, Uti ligation, and Slorage
Figure 1-18 U.S. Department of Energy's H2@Scale Concept
1.8.2 Hydrogen Infrastructure Basics
As FCEV adoption grows, more hydrogen refueling infrastructure will be needed to support
the HD FCEV fleet. Infrastructure is required during the production, distribution and storage, and
dispensing of hydrogen fuel.
1.8.2.1 Hydrogen Production
Hydrogen can be produced using different feedstocks (e.g., natural gas, water), power
sources, and production methods or processes, as listed in Table 1-32.
Table 1-32 Hydrogen Production Methods740'741
Power Source
Production Process
Coal
Gasification with or without carbon capture and storage (CCS)
W Adapted from EPA's Office of Air Quality and Standards (OAQPS) draft Technical Support Document on
Hydrogen in Combustion Turbine Electric Generating Units, which includes more detailed information about
hydrogen production methods.
U.S. Enviromnental Protection Agency, Office of Air and Radiation. "Hydrogen in Combustion Turbine Electric
Generating Units: Technical Support Document". May 23,2023. Available online:
https://www.epa.gov/system/files/documents/2023-05/TSD%20-
%20Hydrogen%20in%20Combustion%20Tuibine%20EGUs.pdf.
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Natural Gas
Steam Methane Reforming (SMR) and Autothermal Reforming (ATR) with or
without CCS, Methane Pyrolysis
Nuclear
Thermal energy for gasification or SMR, Electrolysis (low and high
temperature), and Thermochemical
Renewable
Electrolysis, Photoelectrochemical (PEC), Thermochemical
Others
Byproduct hydrogen and hydrogen derived from biomass, byproducts, and
refuse; Electrolysis*
*Note that electrolysis can also be produced using grid electricity
Hydrogen production methods are at different levels of technology readiness and range in cost
and carbon emissions intensity.742 The U.S. Department of Energy supports clean hydrogen
production from diverse resources and conducts well-to-gate analysis743 to characterize the
emissions of hydrogen production using state of the art tools, such as Argonne National
Laboratory's GREET model.
Figure 1-19 compares current well-to-gate carbon intensities of several domestic hydrogen
production pathways.744
742 U.S. Department of Energy, Hydrogen Program. "Clean Hydrogen Production Standard Guidance". June 2023.
Available online: https://www.hydrogen.energy.gov/library/policies-acts/clean-hydrogen-production-standard,
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/clean-hydrogen-production-standard-
guidance.pdf.
743 Well-to-gate is a system boundary used to evaluate lifecycle emissions from feedstock generation or extraction
through to the point of production.
744 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
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Comparison of domestic hydrogen production pathways
PTC value, $/kg
$3.00 $1.00
3.75
$0.50
Production method
Carbon intensity1,
kg C02e/kg H2
%
2022 US
production
Reformation (SMR or ATR)
without CCS2
Reformation (SMR or ATR)
with >90% CCS3
Electrolysis (from renewables
and nuclear)4
Electrolysis (from grid
electricity)5
Pyrolysis6
-95%
<5%
<1%
<1%
-U—H-
<1%
10
15
25
1 Excludes renewable natural gas feedstocks that would result in negative carbon intensities. Carbon intensities shown are well-to-gate
2 Capex: SMR facility capex (100k Nm3/h capacity): $215 million (current and 2030): reference case natural gas: $4.8/MMBtu (current). $3/MMBtu (2030); high case natural gas: $4.8/MMBtu (current),
$3.3/MMBtu (2030); high case based on EIA Advanced Energy Outlook 2022 high oil price scenario. Range for current reformation costs based on +/- 25% natural gas price.
3 Unit costs assumptions are the same as (1), plus CCS capex (for 100k Nm3 I h SMR facility): $145 million (current), $135 million (2030). Currently operational projects with CCS may have lower than 90%
capture rates. Negative values not shown but feasible with high percentages of RNG.
4 Assumes alkaline electrolyzer with installed capex: $1400/kW (current. 2MW electrolyzer, 450 Nm3/h), $425 / kW (2030, -90MW electrolyzer. 20,000 Nm3/h); reference case based on NREL ATB Class 5
onshore wind: capacity factor: 42% (current), 45% (2030), LCOE: $31/MWh (current). $22/MWh (2030); low case based on NREL ATB Class 1 onshore wind: capacity factor: 48% (current), 54% (2030), LCOE:
$27/MWh (current). $18/MWh (2030); high case based on NREL ATB Class 9 onshore wind: capacity factor: 27% (current), 30% (2030), LCOE: $48/"MWh (current). $33/MWh (2030)
5 Electricity unit costs are based on median, top quartile, and bottom quartile 2030 grid LCOE by census region from EIA Annual Energy Outlook 2022; assumes the same electrolyzer installed capex as (5);
median LCOE: $68/MWh (current), $63/MWh (2030); top quartile LCOE: $66/MWh (current), $627MWh (2030): bottom quartile LCOE: $89/MWh (current), $80/MWh (2030); Grid carbon intensities are based on
data from the Carnegie Mellon Power Sector Carbon Index as well as national averages in grid mix carbon intensity - in some states, grid carbon intensity can be as high as 40 kg C02e / kg H2 (absent power
import / export across sate lines that can lower the carbon intensity of consumption, relative to generation)
6 Values with RNG not shown (which could include negative carbon intensities)
Sources: Hydrogen Council. NREL Annual Technology Baseline 2022, EIA Annual Energy Outlook 2022
Figure 1-19 DOE Comparison of Domestic Hydrogen Production Pathways745
The figure shows that today in the United States, over 95 percent of hydrogen is produced
from natural gas through a process called steam methane reforming (SMR). Auto-thermal
reforming (ATR) is another gas reforming technology that is less prevalent today but has slightly
better performance and economics when paired with carbon capture technologies.746 The
methane in natural gas reacts with high-temperature steam under pressure and in the presence of
a catalyst to create hydrogen and carbon monoxide (CO). The CO then reacts with steam to
create carbon dioxide and more hydrogen.747 To reduce GHG impact, efforts are underway to
test the potential of capturing the CO2 created by SMR or ATR and either storing it underground
or using it commercially. This potential strategy is commonly referred to as carbon capture and
745 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
littps://liftoffenergy.gov/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
?46 Oni, A.O.,et. al. "Comparative assessment of blue hydrogen from steam methane reforming, autothermal
reforming, and natural gas decomposition technologies for natural gas-producing regions". Energy Conversion and
Management, Volume 254. February 15,2022. Available online:
https://www.sciencedirect.com/science/article/pii/SO 196890422000413.
747 U.S. Department of Energy, Hy drogen and Fuel Cell Technologies Office. "Hydrogen Production: Natural Gas
Reforming". Available online: littDs://www.energv.gov/eere/fuelcells/hvdrogen-Droduction-natural-gas-reforming.
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storage (CCS).748 A concern with SMR or ATR and CCS is methane leakage, since methane is a
greenhouse gas that is more potent than CO2 at trapping heat in the atmosphere.749 EPA finalized
a rule in 2023 to reduce methane from both new and existing sources in the oil and natural gas
industry that could help address this problem.750
Electrolysis, which does not involve methane, is the process of splitting water. Electrolyzers
are viable today. They function like fuel cells in reverse: fuel cells consume hydrogen and
oxygen to make electricity and water, while electrolyzers consume electricity and water to make
hydrogen and oxygen. When powered using the standard electricity grid, lifecycle emissions can
vary significantly by region across the country depending on the carbon intensity of the grid.
Over time as the grid decarbonizes, grid electrolysis would get cleaner. When powered using
renewable or nuclear energy, electrolyzers have low GHGs on a lifecycle emissions basis.751'752
Electrolysis is, however, energy intensive. DOE is investing in baseload energy resources
including nuclear reactors to scale low-GHG hydrogen production quickly and reduce
technology costs,753 and in hydropower dams that can also offer baseload energy for hydrogen
production.754'755 Electricity production at large existing reactors and dams is difficult to ramp up
and down. The desire to operate even when demand for electricity is low makes electricity
storage systems such as electrolytic hydrogen attractive as additive technologies for these large
generation assets in the near term. The potential for large-scale storage of excess hydrogen in
underground salt or lined hard rock caverns for later use when needed is an area of active
research.756 In the longer term, the need to balance electrical load across non-emitting generation
assets such as wind, solar, nuclear, and hydro will create additional opportunities for hydrogen
storage technologies.
Pyrolysis is similar to biomass gasification (a process that uses heat, steam, and oxygen to
convert biomass to hydrogen and other byproducts) but without the use of oxygen. Both
processes can use methane generated from the decay of biomass, which can range from
748 When also discussing the possibility of using CO2 commercially, this strategy is referred to as carbon capture,
utilization, and storage (CCUS).
749 The GHG intensities of hydrogen made using methane (SMR, ATR, and pyrolysis) also depend on the extent of
methane leaks during the production and transportation of the natural gas feedstock.
750 U.S. Environmental Protection Agency. "EPA's Final Rule for Oil and Natural Gas Operations Will Sharply
Reduce Methane and Other Harmful Pollution". December 2, 2023. Available online:
https://www.epa.aov/controllina-air-pollution-oil-and-natural-aas-operations/epas-final-rule-oil-and-natural-aas.
751 Electrolysis powered by solar or wind energy can include indirect upstream emissions of GHGs associated with
building the system components and potential land use impacts.
752 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Hydrogen Production Pathways".
Available online: https://www.energv.gov/eere/fuelcells/hvdrogen-production-pathwavs.
753 U.S. Department of Energy, Office of Nuclear Energy. "3 Nuclear Power Plants Gearing Up for Clean Hydrogen
Production". November 9, 2022. Available online: https://www.energy.gov/ne/articles/4-nuclear-power-plants-
gearing-clean-hydrogen-production.
754 McCue, Dan. "IRA Expected to Be 'Transformative' for Hydropower Sector". The Well News: Well Powered.
August 22, 2022. Available online: https://www.thewellnews.com/energy/ira-expected-to-be-transformative-for-
hydropower-sector/.
755 Ashcroft, Nathan and Pietro Di Zanno. "Hydropower: A Cost-Effective Source of Energy for Hydrogen
Production". Power. November 1, 2021. Available online: https://www.powermag.com/hydropower-a-cost-
effective-source-of-energy-for-hydrogen-production/.
756 U.S. Department of Energy. "Bulk Storage of Gaseous Hydrogen: 2022 Workshop Summary Report". February
10-11, 2022. Available online: https://www.energy.gov/sites/default/files/2022-05/bulk-storage-gaseous-hydrogen-
2022_0.pdf.
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agricultural crop or forest residues to organic municipal solid waste or animal-based
wastestreams. These technologies do not involve combustion but may require the use of a
catalyst.757 Pyrolysis has other market dependences that drive uncertainty, so is considered to
have lower potential as a low-GHG pathway than SMR with CCS and electrolysis.758
1.8.2.2 Hydrogen Distribution and Storage
Hydrogen can be commercially delivered today in either gaseous or liquid form. Through
2030, we expect that gaseous or liquid trucking to hydrogen refueling stations from central
production facilities is likely to be a primary method of distributing hydrogen. Tube trailers that
carry compressed hydrogen gas contain long cylinders that are stacked on a trailer, like those that
carry compressed natural gas. They can carry up to 900 kg of hydrogen per trailer.759 Gaseous
delivery requires less capital than liquid delivery and can be cost-effective at smaller scales and
shorter distances.760 Delivery using cryogenic liquid tanker trucks is more economical for longer
distances and higher volume demands, with the potential to carry roughly five times the amount
of energy in a comparable truck of gaseous hydrogen.761 Liquefaction requires about 30 percent
more energy to cool the hydrogen below -253 degrees Celsius (-423 degrees Fahrenheit) and can
result in boil-off during delivery, despite the quality of the insulation of the "dewar" or tank.762
An alternative to trucking hydrogen to a fueling station is to produce hydrogen onsite. This
can be costly but can offer a solution for locations that require larger volumes of hydrogen on a
regular basis. Consumers can purchase methane reformers or electrolyzers. Access to existing
natural resources and feedstocks such as natural gas and water at low cost, the carbon intensity
and cost of electricity, and other factors can be influential.763
On-site hydrogen storage is required throughout the supply chain such as at central hydrogen
production facilities, transport terminals, and end-use refueling stations for HD FCEVs. There
are common high-pressure gaseous storage vessels and super-insulated, low-pressure vessels to
store liquid hydrogen. Hydrogen infrastructure can also require geologic or underground bulk
storage to handle variations in demand throughout the year. There are few existing salt caverns
757 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Hydrogen Production: Biomass
Gasification". Available online: https://www.energy.gov/eere/fuelcells/hydrogen-production-biomass-gasification.
758 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
759 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Hydrogen Tube Trailers". Available
online: https://www.energy.gov/eere/fuelcells/hvdrogen-tube-trailers.
760 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
761 Mulder, Brandon. "Liquid hydrogen seen as 'holy grail' for hydrogen uptake in the mobility sector: Linde COO".
S&P Global: Commodity Insights. November 16, 2021. Available online:
https://www.spglobal.com/commoditvinsights/en/market-insights/latest-news/energv-transition/111621-liquid-
hvdrogen-seen-as-holv-grail-for-hvdrogen-uptake-in-mobilitv-sector-linde-coo.
762 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Liquid Hydrogen Delivery".
Available online: https://www.energy.gov/eere/fuelcells/liquid-hvdrogen-deliverv.
763 Quimby, Tom. "Producing hydrogen on-site 'gives flexibility now'". CCJ. July 27, 2022. Available online:
https://www.ccjdigital.eom/alternative-power/hydrogen-fuel-cell/article/15294540/producing-hydrogen-onsite-
gives-flexibility-now.
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used for hydrogen storage today. The use of hydrogen stored underground for FCEVs requires
further investigation due to the introduction of possible impurities.764
In the long term,765 a dedicated hydrogen pipeline system could be cost-effective as hydrogen
utilization and production volumes grow and provide economies of scale.766 Dedicated hydrogen
pipelines can move hydrogen from low-cost production regions to clusters of demand, which can
make it easier to then truck hydrogen to individual stations in lower volumes.767 In the U.S.,
there is a network of about 1,600 miles of existing pipeline networks that are concentrated in
areas where hydrogen is currently produced and consumed, primarily in the Gulf Coast region.768
To fill gaps in distribution in the short term, mobile fueling is another option, where fuel
providers can deliver a self-contained unit of product that can directly fuel a vehicle. Mobile
fuelers can be deployed quickly and can help meet the immediate and initial fueling needs of
smaller and growing fleets at lower capital costs than a permanent refueling station. Mobile
fueling can be deployed during the construction of a fueling station, and may be viable for
remote locations or for operations that require limited amounts of fuel.769
1.8.2.3 Hydrogen Fueling Stations
Once onsite, hydrogen may need to be conditioned for consumption in vehicles using
compressors, dispensers, chillers, and the like. Fuel is typically dispensed into FCEVs as a
pressurized gas. The development of HD refueling stations will necessitate the establishment of
uniform measures (e.g., refueling protocols, purity standards, metering requirements, component
standardization) to ensure that stations perform efficiently, effectively, and safely. Safety-related
codes and standards associated with fueling FCEVs are discussed in Chapter 1.7.4.
As is the case with BEVs (see Chapter 1.6.1.3), fleets adopting fuel cell technologies may opt
for a private depot fueling model. Many of today's diesel fleet vehicles are fueled at private
depots and, upon conversion, may prefer to maintain this model. However, we considered
FCEVs in our modeled potential compliance pathway for select applications, including some day
cab and sleeper cab tractors, that travel longer distances. We project that these vehicle
applications would be less likely to return to base for regular fueling and would likely need to
use public en-route refueling on the way to their next location.
764 U.S. DOE EERE Hydrogen and Fuel Cell Technologies Office, On-Site and Bulk Hydrogen Storage,
https://www.energy.gov/eere/fuelcells/site-and-bulk-hydrogen-storage.
765 We do not anticipate long-distance pipelines in the near-term so do not address topics such as potential for metal
embrittlement or hydrogen blending with natural gas.
766 Ogden, Joan et. al. "Natural gas as a bridge to hydrogen transportation fuel: Insights from the literature". Energy
Policy, Volume 115. April 2018. Available online:
https://www.sciencedirect.com/science/article/pii/S0301421517308741.
767 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
768 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Hydrogen Pipelines". Available
online: https://www.energy.gov/eere/fuelcells/hydrogen-
pipelines#:~:text=Approximately%201%2C600%20miles%20of%20hydrogen,as%20the%20Gulf%20Coast%20regi
on.
769 U.S. Department of Energy, Alternative Fuels Data Center. "Hydrogen Fueling Stations". Available online:
https://afdc.energy.gov/fuels/hydrogen_stations.html.
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1.8.3 Status and Outlook of Hydrogen Refueling Infrastructure
Chapter 1.3.2 includes a description of numerous provisions in BIL and IRA designed to
support the deployment of ZEVs and supportive infrastructure, including policies and incentives
to reduce the cost of clean hydrogen production and jumpstart the hydrogen market in the United
States. These programs are informed by demand scenarios to increase clean hydrogen production
from nearly zero today to 10 million metric tons (MMT) per year by 2030, 20 MMT per year by
2040, and 50 MMT per year by 2050.770
EPA has seen progress on the implementation of BIL and IRA funding and other provisions to
incentivize the establishment of clean hydrogen supply chain infrastructure. In June 2021, DOE
launched a Hydrogen Shot goal to reduce the cost of clean hydrogen production by 80 percent to
$1 per kilogram in one decade.771 In March 2023, DOE released a Pathways to Commercial
Liftoff Report on "Clean Hydrogen" to catalyze more rapid and coordinated action across the full
technology value chain. Since the NPRM, the federal government has continued to deliver on
BIL and IRA commitments. In June 2023, the U.S. National Clean Hydrogen Strategy and
Roadmap was finalized, informed by extensive industry and stakeholder feedback, setting forth
an all-of-government approach for achieving large-scale production and use of hydrogen and an
assessment of the opportunity for hydrogen to contribute to national decarbonization goals across
sectors over the next 30 years.772 Also in June 2023, DOE updated Clean Hydrogen Production
Standard (CHPS) guidance that establishes a target for lifecycle (defined as "well-to-gate") GHG
emissions associated with hydrogen production, accounting for multiple requirements within the
BIL provisions.773 In October 2023, DOE announced the selection of seven Regional Clean
Hydrogen Hubs (H2Hubs) in different regions of the country that will receive a total of $7 billion
to kickstart a national network of hydrogen producers, consumers, and connective infrastructure
while supporting the production, storage, delivery, and end-use of hydrogen. The investment will
be matched by recipients to leverage a total of nearly $50 billion for the hubs, which are
expected to reduce 25 million metric tons of carbon dioxide emissions each year from end uses
ranging from industrial steel to HD transportation.774
770 U.S. Department of Energy. "U.S. National Clean Hydrogen Strategy and Roadmap". June 2023. Available
online: https://www.hydrogen.energy.gov/library/roadmaps-vision/clean-hydrogen-strategy-roadmap,
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/us-national-clean-hydrogen-strategy-
roadmap.pdf.
771 Satyapal, Sunita. "2022 AMR Plenary Session". U.S. Department of Energy, Hydrogen and Fuel Cell
Technologies Office. June 6, 2022. Available online: https://www.energy.gov/sites/default/files/2022-06/hfto-amr-
plenary-satyapal-2022-l.pdf.
772 U.S. Department of Energy. "U.S. National Clean Hydrogen Strategy and Roadmap". June 2023. Available
online: https://www.hydrogen.energy.gov/library/roadmaps-vision/clean-hydrogen-strategy-roadmap,
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/us-national-clean-hydrogen-strategy-
roadmap.pdf.
773 U.S. Department of Energy, Hydrogen Program. "Clean Hydrogen Production Standard Guidance". June 2023.
Available online: https://www.hydrogen.energy.gov/library/policies-acts/clean-hydrogen-production-standard,
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/clean-hydrogen-production-standard-
guidance.pdf.
774 U.S. Department of Energy. "Biden-Harris Administration Announces $7 Billion For America's First Clean
Hydrogen Hubs, Driving Clean Manufacturing and Delivering New Economic Opportunities Nationwide". October
13, 2023. Available online: https://www.energy.gov/articles/biden-harris-administration-announces-7-billion-
americas-first-clean-hydrogen-hubs-driving.
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Several programs initiated by BIL and IRA investments that could influence the character of
the emerging hydrogen production market are under ongoing development. In March 2023, DOE
announced $750 million for research, development, and demonstration efforts to reduce the cost
of clean hydrogen. This is the first phase of $1.5 billion in BIL funding dedicated to advancing
electrolysis technologies and improving manufacturing and recycling capabilities.775 In July
2023, DOE released a Notice of Intent to invest up to $1 billion in a demand-side initiative (to
offer "demand pull") to support the H2Hubs.776 In January 2024, DOE selected a consortium to
design and implement the program.777 (H2Hub negotiations are still underway.778) And in
December 2023, the Treasury Department and Internal Revenue Service proposed regulations to
offer income tax credit of up to $3 per kg for the production of qualified clean hydrogen at a
qualified clean hydrogen facility (often referred to as the production tax credit, PTC, or 45 V), as
established in the IRA.779 Final program designs are expected after this rule is finalized.780'781
See Section 8.1 of the RTC for additional detail.
1.8.3.1 Current Refueling Network
Currently, DOE's Alternative Fuels Data Center (AFDC) lists 65 public retail hydrogen
fueling stations in the United States, primarily for light-duty vehicles in California.782 When
775 U.S. Department of Energy. "Biden-Harris Administration Announces $750 Million to Advance Clean Hydrogen
Technologies". March 15, 2023. Available online: https://www.energy.gov/articles/biden-harris-administration-
announces-750-million-advance-clean-hydrogen-
technologies#:~:text=This%20funding%E2%80%94the%20first%20phase,the%20widespread%20use%20of%20cle
an.
776 U.S. Department of Energy. "Biden-Harris Administration to Jumpstart Clean Hydrogen Economy with New
Initiative to Provide Market Certainty and Unlock Private Investment". July 5, 2023. Available online:
https://www.energy.gov/articles/biden-harris-administration-jumpstart-clean-hydrogen-economy-new-initiative-
provide-market.
777 U.S. Department of Energy, Office of Clean Energy Demonstrations. "DOE Selects Consortium to Bridge Early
Demand for Clean Hydrogen, Providing Market Certainty and Unlocking Private Sector Investment". January 14,
2024. Available online: https://www.energy.gov/oced/articles/doe-selects-consortium-bridge-early-demand-clean-
hydrogen-providing-market-certainty.
778 U.S. Department of Energy, Office of Clean Energy Demonstrations. "Funding Notice: Regional Clean Hydrogen
Hubs". Available online: https://www.energy.gov/oced/funding-notice-regional-clean-hydrogen-hubs.
779 88 FR 89220. Section 45V Credit for Production of Clean Hydrogen; Section 48(a)(15) Election To Treat Clean
Hydrogen Production Facilities as Energy Property. December 26, 2023. Available online:
https://www.federalregister.gOv/documents/2023/12/26/2023-28359/section-45v-credit-for-production-of-clean-
hydrogen-section-48al5-election-to-treat-clean-hydrogen.
780 As the value of the PTC credit is based on lifecycle greenhouse gas emissions associated with the hydrogen
production process, there is significant potential for the PTC to reduce overall GHG emissions associated with
hydrogen production in the coming years. An analysis by Rhodium Group estimates that the proposed regulations
could reduce between 8 and 236 million metric tons of C02-equivalent emissions cumulatively between 2024 and
2035 because of the PTC, pending final decisions about the rule.
781 King, et. al. "How Clean Will US Hydrogen Get? Unpacking Treasury's Proposed 45V Tax Credit Guidance".
Rhodium Group. January 4, 2024. Available online: https://rhg.com/research/clean-hydrogen-45v-tax-guidance/.
782 U.S. Department of Energy, Alternative Fuels Data Center. "Hydrogen Fueling Station Locations". See
Advanced Filters, Fuel, "Hydrogen" checked (not "include non-retail stations"). Accessed February 15, 2024.
Available online: https://afdc.energv.gov/fuels/hvdrogen locations.html#/analvze?Iuel=HY.
156
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including private, planned, and temporarily unavailable stations in a search, there are 99
refueling station locations nationwide.783'784'785
There are also several nationally designated corridor-ready or corridor-pending Alternative
Fueling Corridors for hydrogen.786 Corridor-ready designations have a sufficient number of
fueling stations to allow for corridor travel. The designation requires that public hydrogen
stations be no greater than 150 miles apart and no greater than five miles off the highway.787
Corridor-pending designations may have public stations separated by more than 150 miles, but
stations cannot be greater than five miles off the highway.788 The purpose of the Alternative Fuel
Corridors program is to support the needed changes in the transportation sector that assists in
reducing greenhouse gas emissions and improves the mobility of vehicles that employ alternative
fuel technologies across the U.S.789 Figure 1-20 shows the most recent map of mostly "pending"
hydrogen corridors, with two corridor-ready designations for hydrogen in California.
783 U.S. Department of Energy, Alternative Fuels Data Center. See Advanced Filters, Station, all "Access" and
"Status" options checked. Accessed February 15, 2024. Available online:
https://afdc.energy.gov/fuels/hvdrogen locations.html#/analvze?fuel=HY.
784 When including non-retail stations, there are 132. Non-retail stations involve special permissions from the
original equipment manufacturers to fuel along with pre-authorization from the station provider.
785 U.S. Department of Transportation, Hydrogen and Fuel Cell Technologies Office. "Fact of the Month #18-01,
January 29". 2018. Available online: https://www.energy.gov/eere/fuelcells/fact-month-18-01-january-29-there-are-
39-publicly-available-hydrogen-fueling.
786 U.S. Department of Transportation, Federal Highway Administration. HEPGIS. "Hydrogen (AFC Rounds 1-7)".
Accessed January 2024. Available online: https://hepgis-
usdot.hub.arcgis.com/apps/el552ac704284d30ba8e504e3649699a/explore..
787 U.S. Department of Transportation, Federal Highway Administration. "Memorandum, INFORMATION: Request
for Nominations—Alternative Fuel Corridor (Round 7/2023)". May 18, 2023. Available online:
https://www.fhwa.dot.gOv/environment/alternative_fuel_corridors/nominations/2023_request_for_nominations_r7.p
df.
788 U.S. Department of Transportation, Federal Highway Administration. "Alternative Fuel Corridors: Frequently
Asked Questions FAST Act Section 1413—Alternative Fuel Corridor Designations Updated December 2020 to
Support Round 5". Available online:
https://www.fhwa.dot.gov/environment/alternative_fuel_corridors/resources/faq/.
789 U.S. Department of Transportation, Federal Highway Administration. "Alternative Fuel Corridors". Available
online: https://www.fhwa.dot.gov/environment/alternative_fuel_corridors/.
157
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S*ajtt|e
San Francisco
Los>Angeles
v....
' /'UNITED
Ottawa
** * * .
""*! ; Toronto ;
*-'ff .¦•'-? >¦*-
„ - %< Dejtroil • • Boston
Chicago.-. • .* >-¦»
"/NewYork
pRIIijdelphla
"Denver ...s.jATES V / ,
.... Washington
: v ; v.-y-L
; s - .*»«¦ ; j* *. -J. 'i
' *+ * «I * * **, • S,, ¦"*
*j : " if* . ,¦** ; Atlanta
...A \ ,
~ j » v
J +_ * n
'.Houston'
Miami
Monterrey
Figure 1-20 FHWA-Designated Alternative Fuel Corridors for Hydrogen790Hydrogen Round 1, 2,3,4,5,6
and 7: Ready (straight lines) and Pending (dotted lines)
1.8.3.2 The Evolving Hydrogen Market and Investment
While many companies produce hydrogen for their own internal use, the list of companies
that produce and sell hydrogen in North America (i.e., "merchant" producers of hydrogen) is
much smaller. Three companies—Air Products, Air Liquide, and Linde—produce a large
majority of the merchant hydrogen for North American markets. Their products are
predominantly produced via SMR.791
As government and commercial support for both low-GHG hydrogen as a transportation fuel
and electrolytic hydrogen in general have grown in recent years, existing companies such as
Siemens and Cummins and new participants such as Plug Power and Nel Hydrogen have
emerged in this space to supply these products.792 These companies have diverse business
models. Some focus on production of hydrogen only, while others seek to become turnkey
solutions for companies looking to source hydrogen for vehicle use. Production strategies vary as
well, with some companies focusing on centralized production while others invest in onsite
production models. It is too early to tell whether growth in hydrogen supply and demand will
lead to a shifting landscape in the merchant hydrogen sector, or whether the established market
790U.S. Department of Transportation, Federal Highway Administration. HEPGIS. ''Hydrogen (AFC Rounds 1-7)"1
Accessed January 2024. Available online: https://hepgis-
usdot.hub.arcgis.com/apps/el552ac704284d30ba8e504e3649699a/explore.
Hydrogen Tools. "Merchant Hydrogen Plant Capacities in North America". Pacific Northwest National
Laboratory. January 2016. Available online: https://h2tools.org/hvarc/hvdrogeii-data/merchant-hvdrogen-plant-
capacities-north-america.
792 Kearney Energy Transition Institute. "Hydrogen applications and business models". June 2020. Available online:
https://www.kearney.com/documents/17779499/18269679/Hydrogen+FactBook+Final+-+June+2020.pdf/01ae498b-
3d38-deca-2a61-6fi07699ddel?t=1592252815706.
158
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players will expand their portfolio to meet the need for low-GHG hydrogen as well. According to
Cipher's Clean Technology Tracker, as of September 2023, there is $45,752 billion in total clean
hydrogen production project investment in the United States,793 with 1 percent in projects that
are in operation (close to $500,000), 7 percent ($3.2 million) under construction, and a majority
still classified as announced.794 DOE has started tracking private sector announcements of
domestic electrolyzers and fuel cell manufacturing facilities. So far, over $1.8 billion in new
investments has been announced for over 10 new or expanded facilities with the capacity to
manufacture approximately 10 GW of electrolyzers per year.795 BIL and IRA programs are under
ongoing development, but we anticipate that investment strategies (e.g., that connect producers
of hydrogen with end users of fuel) will amplify and become clearer over time after the rule is
finalized as policy and process details start to settle. We also expect this rule will provide greater
certainty to the market to support timely development of hydrogen refueling stations.
DOE announced $98 million in grants to help build five hydrogen fueling stations for HD
freight trucks in Texas and create a hydrogen corridor from California to Texas. They also
announced grants for two public hydrogen fueling stations in California and three public stations
in Colorado.796 As of 2023, California expects to have at least seven stations capable of fueling
HD vehicles by 2027.797
There is a broad awareness that, as hydrogen production scales, midstream (e.g., distribution
and storage) and downstream (e.g., refueling station) infrastructure will need to expand to enable
end users of hydrogen that are not co-located with production at hubs. Midstream and
downstream infrastructure could account for half of the necessary investment through 2030 ($45-
103 billion) to get to commercial liftoff of a clean hydrogen market.798
The following sampling of announcements to date indicate private sector involvement and
interest in establishing a refueling station network for HD FCEVs:
• By the end of 2026, Nikola plans to have 60 hydrogen refueling stations in place.
793 According to the Clean Technology Tracker, clean hydrogen production refers to the production of hydrogen fuel
with proton exchange membrane (PEM) electrolyzers and solid oxide electrolyzer cells (SOEC) or through other
methods such as methane pyrolysis and natural gas with carbon capture.
794 Cipher News. "Tracking a new era of climate solutions: Cleantech growth across the U.S." Accessed February
2024. Available online: https://ciphernews.eom/cleantech-tracker/#definitions.
795 U.S. Department of Energy. "Building America's Clean Energy Future—Hydrogen: Electrolyzers and Fuel
Cells". Accessed February 2024. Available online: https://www.energy.gov/invest.
796 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Biden-Harris Administration
Announces $623 Million in Grants for EV Charging and Alternative Fueling—Including More Than $90 Million for
Hydrogen Infrastructure". January 30, 2024. Available online: https://www.energy.gov/eere/fuelcells/articles/biden-
harris-administration-announces-623-million-grants-ev-charging-and.
797 Crowell, et. al. "Joint Agency Staff Report on Assembly Bill 8: 2023 Annual Assessment of the Hydrogen
Refueling Network in California". CEC/CARB. December 2023. Available online:
https://www.energy.ca.gov/sites/default/files/2023-12/CEC-600-2023-069.pdf.
798 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
159
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o In August 2023, Nikola received a grant of $58.2 million to build six refueling
stations for HD FCEVs in California.799
o Nikola and Voltera formed a strategic partnership to develop 50 Hyla refueling
stations for commercial vehicles throughout North America over five years
(i.e., through 2027 to 2028).800
o In February 2024, Nikola opened its first private hydrogen refueling station in
Ontario, CA, that can fuel up to 40 Class 8 FCEVs every day.801
• Daimler Truck North America, LLC (DTNA), NextEra Energy Resources, LLC, and
BlackRock Alternatives announced Greenlane, a $650 million joint venture to
develop, design, and operate a nationwide public charging and hydrogen fueling
network for MHDV BEVs and FCEVs.802
• Libertad Power, Hyundai Motor Company, and Diesel Direct partnered to develop a
hydrogen-fueled Southwest Clean Freight Corridor, with plans to build an electrolysis
plant by 2025 to produce 20 to 30 tons of hydrogen per day to start to supply stations
in four states (i.e., Texas, New Mexico, Arizona, and California).803
• FirstElement is providing hydrogen fuel at 700 bar pressure through its True Zero
network of liquid refueling stations in California to test Hyundai XCIENT truck.804
Mobile refueling can help fill initial temporary gaps in the refueling station network in the near-
term as fleets transition to FCEVs:
• Under the Hyla brand, Nikola launched flexible mobile fueling trailers to support
previously announced projects with Buckeye, AZ (150 tpd); Plug Power (up to 125
799 Balaraman, Kavya. "Nikola bags $58.2 million for hydrogen stations to fuel heavy-duty vehicles". Pv Magazine.
August 11, 2023. Available online: https://pv-magazine-usa.com/2023/08/ll/nikola-bags-58-2-million-for-
hvdrogen-stations-to-fuel-heaw-duty-vehicles/.
800 Ohnsman, Alan. "Nikola Partners With Voltera To Build Up To 50 Stations For Hydrogen Trucks. Forbes. May
2, 2023. Available online: https://www.forbes.eom/sites/alanohnsman/2023/05/02/nikola-partners-with-voltera-to-
build-up-to-50-stations-for-hydrogen-trucks/?sh=4dfcc722fb0d.
801 Balaraman, Kavya. "Nikola opens hydrogen refueling station for heavy-duty vehicles in California". PR
Newswire. February 9, 2024. Available online: https://www.pv-magazine.com/2024/02/09/nikola-opens-hydrogen-
refueling-station-for-heavy-duty-vehicles-in-california/.
802 NextEra Energy Resources, LLC; Daimler Truck North America, LLC; BlackRock Alternatives. "Introducing
Greenlane: Daimler Truck North America, NextEra Energy Resources and BlackRock Forge Ahead with Public
Charging Infrastructure Joint Venture". PR Newswire. April 28, 2023. Available online:
https://www.prnewswire.com/news-releases/introducing-greenlane-daimler-truck-north-america-nextera-energy-
resources-and-blackrock-forge-ahead-with-public-charging-infrastructure-joint-venture-301811101 .html.
803 Tank Storage News America. "NM to be Part of Clean Freight Corridor". September 29, 2022. Available online:
https://tankstoragenewsamerica.com/nm-to-be-part-of-clean-freight-corridor/.
804 Williams, Bret. "FirstElement Fuel's H2 refueling stations support Hyundai Motor's fuel cell truck pilot program.
Hydrogen Fuel News. March 16, 2023. Available online: https://www.hydrogenfuelnews.com/h2-refueling-
firstelement-hy undai/8557730/.
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tpd); Terre Haute, Indiana (50 tpd); Crossfield, Alberta, Canada (60 tpd); and Clinton
County, Pennsylvania (100 tpd).805
o Nikola signed purchase orders with Chart Industries, Inc, for multiple liquid
hydrogen storage tanks, mobile and modular refueling stations, and liquid
hydrogen transport trailers to support the quick deployment of HD FCEVs by
meeting immediate and interim fueling needs.806
• Hyundai is partnering with FirstElement for high capacity mobile refuelers at 128 kg
per hour to support HD FCEV OEM truck pilots.807'808
• Air Products offers portable fueling units that hold 150 kg of hydrogen for both short-
and long-term deployments that can be delivered to customers with very short lead-
times.809
• J.B. Hunt is piloting a Hydrogen Truck Ecosystem that includes General Motors
Hydrotec Fuel Cell Power Cube technology, which uses Navistar and OneH2's
modular, mobile, and scaleable hydrogen production and fueling capabilities.810'811
Some states have taken action:
• Illinois passed legislation to create a $1 per kg tax credit for end users of zero-carbon
hydrogen in 2026 and 2027.812
805 Buckley, Julian. "Nikola launches Hyla to support hydrogen fuel distribution". Power Progress. January 26,
2023. Available online: https://www.powerprogress.com/news/nikola-launches-hyla-to-support-hydrogen-fuel-
distribution/8026221 .article.
806 Nikola. "Chart Industries and Nikola Execute Strategic Partnership for Hydrogen-Related Equipment". March 30,
2023. Available online: https://www.nikolamotor.com/press_releases/chart-industries-and-nikola-execute-strategic-
partnership-for-hydrogen-related-
equipment/#:~:text=Nikola%20has%20recently%20signed%20purchase,advance%20the%20efforts%20to%20decar
bonize.
807 FirstElement Fuel. "FirstElement Fuel partners with Hyundai Motor on hydrogen refueling of class 8 fuel cell
electric trucks, driving over 25K miiles with zero emissions". PR Newswire. March 14, 2023. Available online:
https://www.prnewswire.com/news-releases/firstelement-fuel-partners-with-hyundai-motor-on-hydrogen-refueling-
of-class-8-fuel-cell-electric-trucks-driving-over-25k-miles-with-zero-emissions-301770655.html.
808 Williams, Bret. "FirstElement Fuel's H2 refueling stations support Hyundai Motor's fuel cell truck pilot program.
Hydrogen Fuel News. March 16, 2023. Available online: https://www.hydrogenfuelnews.com/h2-refueling-
firstelement-hy undai/8557730/.
809 Air Products. "Portable Hydrogen Fueler". Available online: https://www.airproducts.com/services/portable-
hydrogen-fueler.
810 Navistar International Corporation. "Navistar Collaborates with General Motors and OneH2 To Launch
Hydrogen Truck Ecosystem". PR Newswire. January 27, 2021. Available online:
https://www.prnewswire.com/news-releases/navistar-collaborates-with-general-motors-and-oneh2-to-launch-
hydrogen-truck-ecosystem-301216246.html.
811 Navistar. "Hydrogen Fuel Cell: Modular, Mobile, and Scalable". Available online:
https://www.navistar.com/en/our-path-forward/hydrogen-fuel-cell.
812 Martin, Polly. "Illinois introduces tax credit for 'zero-carbon' hydrogen users in hard-to-abate sectors—for two
years only". Hydrogenlnsight. July 26, 2023. Available online: https://www.hydrogeninsight.com/policy/illinois-
introduces-tax-credit-for-zero-carbon-hydrogen-users-in-hard-to-abate-sectors-for-two-years-only/2-1-1491693.
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• Colorado passed legislation to provide up to $1 per kg for the use of clean hydrogen in
hard-to-decarbonize sectors.813
• Pennsylvania has a Regional Clean Hydrogen Hubs Tax Credit for qualified taxpayers
who purchase clean hydrogen or natural gas for use in a manufacturing facility in the
state. The credit offers $0.18 per kg of clean hydrogen from a H2Hub in the state
and/or $0.47 per kg of natural gas.814
• California lawmakers passed Senate Bill 1291 in 2022 that requires all cities and
counties in the state to develop an expedite streamlined permitting process for
hydrogen fueling stations that meet certain criteria until 2030.815
Hydrogen refueling network investment plans and players will continue to evolve as programs
spurred by federal investment through BIL and IRA are implemented.816
1.8.3.3 Hydrogen Hubs
As mentioned in Chapter 1.8.3, in October 2023, seven Regional Clean Hydrogen Hubs
(H2Hubs) were awarded $7 billion in funding to launch a national hydrogen network:
813 Toor, Will. "A new Colorado law makes it a top site for clean hydrogen developers, but it's not a model for
federal rules". UtilityDive. May 25, 2023. Available online: https://www.utilitydive.com/news/colorado-clean-
hydrogen-tax-credit-
incentives/651199/#:%7E:text=The%20use%20tax%20credit%20is,heavy%2Dduty%20trucking%20and%20aviatio
n.
814 Pennsylvania Department of Revenue. "Regional Clean Hydrogen Hubs Tax Credit". Available online:
https://www.revenue.pa.gov/IncentivesCreditsPrograms/PAEDGE/Pages/Regional-Clean-Hydrogen-Hubs-Tax-
Credit.aspx.
815 California Governor's Office of Business and Economic Development. "Hydrogen Station Permit Streamlining
Fact Sheet". August 2023. Available online: https://business.ca.gov/wp-content/uploads/2023/08/SB-1291-
Hydrogen-Station-Permit-Streamlining-Fact-Sheet.pdf.
816 U.S. Department of Energy. "U.S. National Clean Hydrogen Strategy and Roadmap". June 2023. Available
online: https://www.hvdrogen.energv.gov/librarv/roadmaps-vision/clean-hvdrogen-strategy-roadmap.
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/us-national-clean-hydrogen-strategy-
roadmap.pdf.
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SELECTED REGIONAL CLEAN HYDROGEN HUBS
Pacific Northwest
Hydrogen Hub
California
Hydrogen Hub
Alliance for Renewable Clean
Hydrogen Energy Systems
(ARCHES)
Heartland
Hydrogen Hub
Heartland Hub (HH2H)
Gulf Coast
Hydrogen Hub
HyVelocity H2Hub
Figure 1-21 Map of Regional Clean Hydrogen Hubs817
H2Hubs were chosen based on technical merit and impact, including the ability to deploy
infrastructure and produce at least 50 to 100 metric tons of clean hydrogen per day; financial and
market viability; workplan (e.g., speed and project management details); management team and
project partners; and community benefits plan.818 Table 1-33 indicates the types of
transportation-related interests per hub.
817 U.S. Department of Energy, Office of Clean Energy Demonstrations. "Regional Clean Hydrogen Hubs Selections
for Award Negotiations". Available online: https://www.energy.gov/oced/regional-clean-hydrogen-liubs-selections-
award-negotiations.
818 U.S. Department of Energy, Office of Clean Energy Demonstrations. "Regional Clean Hydrogen Hubs Selections
for Award Negotiations". Available online: https://www.energy.gov/oced/regional-clean-hydrogen-hubs-selections-
award-negotiations.
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Table 1-33 Transportation Highlights at H2Hubs
Hub Name
Location
(Prime Contractor)
Total Federal
Cost Share
Transportation Highlights*
Appalachian Regional
Clean Hydrogen Hub
(ARCH2)
West Virginia, Ohio,
Pennsylvania
(Battelle)
Up to $925
million
H2 pipelines, fueling stations
Fuel cell electric mining trucks, HD
vehicles
California's Alliance for
Regional Clean
Hydrogen Energy
Systems (ARCHES)
California
(Alliance for Renewable
Clean Hydrogen Energy
Systems LLC)
Up to $1.2
billion
Freight network between California
and Pacific Northwest Hubs,
fueling stations
HD vehicles, port equipment, public
transit
Gulf Coast's HyVelocity
Hydrogen Hub (H2Hub)
Texas
(HyVelocity, Inc.)
Up to $1.2
billion
H2 pipeline, refueling stations
HD vehicles, marine fuel
Heartland Hydrogen
Hub (HH2H)
Minnesota, North Dakota,
South Dakota
(Energy & Environmental
Research Center)
Up to $925
million
Open access storage and pipeline
infrastructure
Mid-Atlantic Clean
Hydrogen Hub
(MACH2)
Pennsylvania, Delaware,
New Jersey
(Mid-Atlantic Clean
Hydrogen Hub, Inc.)
Up to $750
million
Expanded pipeline infrastructure,
upgraded bus mechanic depots,
refueling stations
HD vehicles, refuse and sweeper
trucks
Midwest Alliance for
Clean Hydrogen
(MachH2)
Illinois, Indiana,
Michigan
(MachH2)
Up to $ 1
billion
Refueling stations
HD vehicles, sustainable aviation
fuel
Pacific Northwest
Hydrogen Hub (PNW
H2)
Washington, Oregon,
Montana
(Pacific Northwest
Hydrogen Association)
Up to $ 1
billion
Freight network between California
and Pacific Northwest Hubs
HD vehicles, ports
* Transportation highlights only represent a portion of proposed hub activity and, thus, would only receive a portion of
H2Hubs funds.
H2Hubs would produce approximately three million metric tons of hydrogen per year. They may
expand and are still subject to change, pending final negotiations in 2024.819
1.8.3.4 Projected Demand
Our potential compliance pathway for the final rule projects relatively modest hydrogen
demand, even compared to amounts presently available. The final rule projects that hydrogen
consumption from FCEVs will be a small proportion of total hydrogen currently produced (see
819 U.S. Department of Energy, Office of Clean Energy Demonstrations. "Regional Clean Hydrogen Hubs National
Briefing: October 16, 2023". Available online: https://www.energy.gov/oced/regional-clean-hydrogen-hubs-
selections-award-negotiations.
164
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Table 1-34). Furthermore, as noted earlier in this section, programs under BIL and IRA are
anticipated to potentially increase clean hydrogen production from 10 MMT per year by 2030 to
20 MMT per year by 2040. This represents an average growth in clean hydrogen production of 1
MMT per year in the 2030s, which far outpaces our projected growth of hydrogen consumption
from FCEVs in the potential compliance pathway developed to support the feasibility of the final
rule.
Table 1-34 Excerpt from Table 6-2 in RIA Chapter 6.5 on Estimated U.S. Oil Import Reductions and
Electricity and Hydrogen Consumption Increases due to the Final Rule *
Calendar
Year
Hydrogen Consumption
(1000 metric tons per year)
% of 2020 U.S. Hydrogen Consumption*
2030
17
0.2%
2031
51
0.5%
2032
130
1.3%
* According to DOE, 10 million metric tons of hydrogen is produced annually.820
1.8.3.5 Assessment of Future Hydrogen Refueling Infrastructure Needs
As FCEV adoption grows, more hydrogen refueling infrastructure will be needed to support
the HD FCEV fleet. Infrastructure is required during the production, distribution, storage, and
dispensing of hydrogen fuel.
We reviewed literature that assesses hydrogen infrastructure needs for the HD transportation
sector. The authors used differing analytical approaches and a large range of assumptions about
the production, distribution and storage, and dispensing of hydrogen fuel to estimate hydrogen
demand for HD FCEVs and the number of refueling stations required to meet that demand. Liu
et. al821 was one of the first to conduct a national assessment of hydrogen fueling needs to
support the national long-haul trucking fleet. They found that at 10 percent HD FCEV
penetration in 2025, 3553 small- and medium-sized hydrogen refueling stations would be needed
along major corridors. Minjares et. al822 evaluated infrastructure needed to support a goal of 100
percent sales of zero-emission tractor-trailers by 2040. They projected BEV charging stations
along with over 220 hydrogen refueling stations by 2030, growing to close to 3000 by 2040. A
Ricardo study for the Truck and Engine Manufacturers Association823 investigated the feasibility
of EPA's proposed Phase 3 GHG standards and found that about 10 percent of HD ZEV sales
through 2032 would equate to around 128,000 FCEV and H2-ICE vehicles, or a hydrogen
demand of about 0.9 million tons per year by 2032. FCEVs and H2-ICE would not start to ramp
820 Satyapal, Sunita. "U.S. DOE Hydrogen Program Annual Merit Review (AMR) Plenary Remarks". U.S.
Department of Energy. June 5, 2023. Available online: https://www.energy.gov/sites/default/files/2023-06/h2amr-
plenary-satyapal-2023_0.pdf.
821 Liu, et. al. "Evaluating national hydrogen refueling infrastructure requirement and economic competitiveness of
fuel cell electric long-haul trucks". Mitigation and Adaption Strategies for Global Change. November 21, 2019.
Available online: https://link.springer.com/article/10.1007/sll027-019-09896-z
822 Minjares, et. al. "Infrastructure to support a 100% zero-emission tractor-trailer fleet in the United States by
2040". International Council on Clean Transportation. September 2021. Available online: https://theicct.org/wp-
content/uploads/202 l/12/ze-tractor-trailer-fleet-us-hdvs-sept21 .pdf.
823 Kuhn et. al. "Feasibility study of EPA NPRM Phase 3 GHG standards for Medium Heavy-Duty Vehicles.
Version: 3.0". Ricardo, prepared for Truck and Engine Manufacturers Association. July 19, 2023.
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up until around 2030. They concluded that 696 hydrogen refueling stations would be needed to
meet this demand, with 219 stations in Texas and California and 130 stations connected to these
networks. The Coordinating Research Council (CRC)824 evaluated infrastructure needs based on
EPA's proposed rule along with other rules in California. They estimated that one percent of the
total fleet would result in a demand of 0.89 million metric tons of hydrogen in 2035. They
concluded that even with low FCEV penetration, HD FCEVs can play an important role in the
long-haul sector. Based on their analysis, buildout of about 600 hydrogen refueling stations by
2030 (370 for HD trucks and buses and 230 for LD cars in California) would increase to about
1350 hydrogen refueling stations for trucks and buses and over 400 hydrogen refueling stations
for LD cars in 2035. This review showed how station needs are likely to vary based on demand.
Several papers examined infrastructure costs in the 2030 timeframe, as discussed further in
Chapter 2.5.3.1. In general, the authors concluded that economies of scale are important to
reduce costs throughout the supply chain. Liu et. al recognized that fueling station availability
and location (e.g., distance between stations) and capacity (i.e., station size) are key to
determining station costs; when there are more trucks on the road and larger stations, fuel costs
are lower. They found that HD FCEV costs and liquefaction costs are also important for cost-
competitiveness.825 Ricardo noted that HD hydrogen refueling station costs are likely to follow
the cost reduction pattern of stations for LD vehicles due to economies of scale. They compared
cumulative sales in the HD hydrogen market now to the early commercialization of LD FCEVs
in 2016 and assumed station cost reductions of about 45 percent by 2032.826 The Coordinating
Research Council (CRC) suggested that station buildout could become faster and easier as
economies of scale are achieved, among other factors, and applied a 70 percent reduction in
station installation costs from a 2020 baseline by 2035. They recognized that economies of scale
throughout the hydrogen supply chain, along with technology advancements and growth in use
and demand, are needed to reduce the retail price of hydrogen.827
Most researchers of papers that we reviewed agree that it is not necessary to build a national
infrastructure network for HD FCEVs all at once. Liu et. al recognized that FCEV technology
may not be widely accepted in all regions of the U.S. at the same time. They found that station
costs vary by region based on total hydrogen demand and suggested targeting regions with lower
station costs (so high hydrogen demand) for initial station deployment. Though considering
limited data, they found the West South Central and Pacific regions could potentially have some
824 Coordinating Research Council. "Assess the Battery-Recharging and Hydrogen-Refueling Infrastructure Needs,
Costs, and Timelines Required to Support Regulatory Requirements for Light-, Medium-, and Heavy-Duty Zero-
Emission Vehicles. Final Report". Prepared by ICF. CRC Report No. SM-CR-9. September 2023. Available online:
https://crcao.org/wp-content/uploads/2023/09/CRC_Infrastructure_Assessment_Report_ICF_09282023_Final-
Report, pdf.
825 Liu, et. al. "Evaluating national hydrogen refueling infrastructure requirement and economic competitiveness of
fuel cell electric long-haul trucks". Mitigation and Adaption Strategies for Global Change. November 21, 2019.
Available online: https://link.springer.com/article/10.1007/sll027-019-09896-z
826 Kuhn et. al. "Feasibility study of EPA NPRM Phase 3 GHG standards for Medium Heavy-Duty Vehicles.
Version: 3.0". Ricardo, prepared for Truck and Engine Manufacturers Association. July 19, 2023.
827 Coordinating Research Council. "Assess the Battery-Recharging and Hydrogen-Refueling Infrastructure Needs,
Costs, and Timelines Required to Support Regulatory Requirements for Light-, Medium-, and Heavy-Duty Zero-
Emission Vehicles. Final Report". Prepared by ICF. CRC Report No. SM-CR-9. September 2023. Available online:
https://crcao.org/wp-content/uploads/2023/09/CRC_Infrastructure_Assessment_Report_ICF_09282023_Final-
Report, pdf.
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of the lowest station costs.828 Ricardo identified California and Texas as the dominant states with
the largest hydrogen demand by 2032. They noted that California's decarbonization policies and
the large HD truck market and existing hydrogen resources in Texas could play roles. They
called for investment and support for public refueling stations along Alternative Fuel Corridors
and in key truck clusters such as ports, airports, railroads, warehouses, and freight hubs to
support HD FCEV deployment.829 CRC recognized a strategy laid out by CARB to start with
smaller capacity stations to ensure adequate spatial coverage, and then gradually progress to
larger capacity stations as demand increases. They suggested that California would lead in
buildout due to existing policies, followed by other states starting in 2030 (i.e., a six-year lag,
based on our proposed rule). According to their analysis, Texas would have the second largest
need for refueling infrastructure based on estimated hydrogen demand.830 Fulton et. al found that
in California in the 2030 timeframe, smaller, lower-use hydrogen refueling stations could offer
sufficient coverage and dominate a network in the near-term but then decline as demand grows
and larger stations become more economical.831 Ragon et. al noted that an infrastructure network
does not need to be built all at once and should be prioritized in the near-term in areas with high
energy needs from MHDV traffic flows. This conclusion was focused on BEV charging
infrastructure in the 2030 timeframe but the high-level takeaway could also apply to the
development of FCEV refueling stations. As the market develops, they suggested that
infrastructure needs could expect to expand along freight corridors that connect priority hubs or
industrial nodes.832
As discussed further in Chapter 2.5.3.1, we revised projections for HD FCEV adoption based
on relatively low production volumes in the MY 2030 to 2032 timeframe, indicative of an early
market technology rollout. As a result, hydrogen demand in the modeled potential compliance
pathway in the final rule is smaller than projected in the NPRM and in these studies in the MY
2030 to 2032 timeframe. It is closer to about 130,000 metric tons of hydrogen per year by 2032,
or 1.3% of current production. Our assessment is that early market buildout of a hydrogen
refueling station network to support modest FCEV adoption levels in the modeled potential
compliance pathway is feasible in the 2030 to 2032 timeframe.
We are not suggesting that a full national hydrogen infrastructure network needs to be in place
by 2030 or 2032, and specifically note that a full national hydrogen infrastructure network is not
necessary to accommodate the demand that we posit for HD FCEVs in our modeled potential
828 Liu, et. al. "Evaluating national hydrogen refueling infrastructure requirement and economic competitiveness of
fuel cell electric long-haul trucks". Mitigation and Adaption Strategies for Global Change. November 21, 2019.
Available online: https://link.springer.com/article/10.1007/sll027-019-09896-z
829 Kuhn et. al. "Feasibility study of EPA NPRM Phase 3 GHG standards for Medium Heavy-Duty Vehicles.
Version: 3.0". Ricardo, prepared for Truck and Engine Manufacturers Association. July 19, 2023.
830 Coordinating Research Council. "Assess the Battery-Recharging and Hydrogen-Refueling Infrastructure Needs,
Costs, and Timelines Required to Support Regulatory Requirements for Light-, Medium-, and Heavy-Duty Zero-
Emission Vehicles. Final Report". Prepared by ICF. CRC Report No. SM-CR-9. September 2023. Available online:
https://crcao.org/wp-content/uploads/2023/09/CRC_Infrastructure_Assessment_Report_ICF_09282023_Final-
Report, pdf.
831 Fulton, et. al. "California Hydrogen Analysis Project: The Future Role of Hydrogen in a Carbon-Neutral
California—Final Synthesis Modeling Report". UC Davis Institute of Transportation Studies. April 19, 2023.
Available online: https://escholarship.org/uc/item/27m7g841.
832 Ragon, Pierre-Louis et al. "Near-term Infrastructure Deployment to Support Zero-Emission Medium- and Heavy -
Duty Vehicles in the United States." May 2023. Available online: https://theicct.org/wp-
content/uploads/2023/05/infrastructure-deployment-mhdv-may23.pdf.
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compliance pathway. Through BIL and IRA incentives and private investment spurred by
H2Hubs, we conclude there is opportunity to concentrate HD FCEV hydrogen demand from the
modeled potential compliance pathway in priority areas. Secure and sufficient demand from
local or regional anchor fleets would offer certainty that could help lower infrastructure costs in
targeted regions and enable expansion over time. This strategy is supported in the literature,
which include regional analyses that demonstrate that infrastructure buildout can start in targeted
regions. The analyses also indicate that station financial prospects can vary by region and tend to
be more favorable in areas with higher demand (i.e. high energy needs from HD traffic flows),
while station costs are anticipated to drop with growth in demand and related economies of scale.
Similar to BEVs, as explained in RTC Section 7.1, the infrastructure needed to meet this initial
demand may be centered in a discrete sub-set of states and counties where freight activity is
concentrated. Thus, the select vehicle applications for which we project FCEV adoption could
start traveling within or between regional hubs in this timeframe where hydrogen development is
prioritized initially.
Along these lines, in March 2024, the U.S. released a National Zero-Emission Freight
Corridor Strategy,833 released in March 2024, that, "sets an actionable vision and comprehensive
approach to accelerating the deployment of a world-class, zero-emission freight network across
the United States by 2040. The strategy focuses on advancing the deployment of zero-emission
medium- and heavy-duty vehicle (ZE-MHDV) fueling infrastructure by targeting public
investment to amplify private sector momentum, focus utility and regulatory energy planning,
align industry activity, and mobilize communities for clean transportation."834 The strategy has
four phases. The first phase, from 2024-2027, focuses on establishing freight hubs defined "as a
100-mile to a 150-mile radius zone or geographic area centered around a point with a significant
concentration of freight volume (e.g., ports, intermodal facilities, and truck parking), that
supports a broader ecosystem of freight activity throughout that zone."835 The second phase,
from 2027-2030, will connect key ZEV hubs, building out infrastructure along several major
highways. The third phase, from 2030-2045, will expand the corridors, "including access to
charging and fueling to all coastal ports and their surrounding freight ecosystems for short-haul
and regional operations."836 The fourth phase, from 2035-2040, will complete the freight
corridor network. This corridor strategy provides further support for the development of HD
ZEV infrastructure that corresponds to the modeled potential compliance pathway for meeting
the final standards.
833 Joint Office of Energy and Transportation. "National Zero-Emission Freight Corridor Strategy" DOE/EE-2816
2024. March 2024. Available at https://driveelectric.gov/files/zef-corridor-strategy.pdf.
834 Joint Office of Energy and Transportation. "Biden-Harris Administration, Joint Office of Energy and
Transportation Release Strategy to Accelerate Zero-Emission Freight Infrastructure Deployment." March 12, 2024.
Available online: https://driveelectric.gov/news/decarbonize-freight.
835 Joint Office of Energy and Transportation. "National Zero-Emission Freight Corridor Strategy" DOE/EE-2816
2024. March 2024. Available at https://driveelectric.gov/files/zef-corridor-strategy.pdf. See page 3.
836 Joint Office of Energy and Transportation. "National Zero-Emission Freight Corridor Strategy" DOE/EE-2816
2024. March 2024. Available at https://driveelectric.gov/files/zef-corridor-strategy.pdf. See page 8.
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1.8.3.6 Lead Time and Early Market Buildout
Hydrogen refueling infrastructure is currently limited in scope, so we evaluated the potential
pace of buildout.
DOE's Liftoff Report identifies a path to scale hydrogen that involves three phases of
potentially rapid market growth: near-term expansion (-2023-2026), industrial scaling (-2027-
2034), and long-term growth (-2035+). The report acknowledges that there are both
opportunities and challenges for sectors with few decarbonization alternatives like heavy-duty
transportation end uses, including long-haul trucks.837 It lays out a scenario where low-GHG
hydrogen could be emerging for long-haul trucks during the timeframe of this rule (i.e., through
2032):
• Hydrogen will start getting cleaner:
o By 2030, there is incentive to produce up to 10 MMT per year of hydrogen for
new markets using low-GHG pathways (i.e., in addition to some portion of
incumbent demand for conventional hydrogen).
¦ Industry expects electrolyzer costs to drop significantly by 2030,
though this is reliant on the availability of low-cost low-GHG
electricity that also needs to scale.
o This shift can start with existing end users that already have hydrogen
infrastructure that connects production with end-use demand (e.g.,
industrial/chemicals).
o New projects that receive hub funding are expected to break ground in the
near-term and advance new networks of shared infrastructure.
• It will be challenging to establish regional infrastructure networks for end uses but
doing so can start to lower the delivered cost of hydrogen:
o During industrial scaling, privately funded hydrogen infrastructure projects
will come online and start to build the midstream distribution and storage
networks to connect greater numbers of producers and offtakers.
o Increasing production volumes will reduce costs that drive adoption of
hydrogen in new sectors like heavy-duty FCEVs.
o Hydrogen will initially be dispersed through centralized regional hubs, and
then eventually through a more distributed network of infrastructure, followed
by anchors such as dedicated hydrogen pipelines and geologic storage in the
long term.
The literature also supports our conclusion that there is sufficient lead time. Fulton et. al.
noted that heavy-duty refueling station funding, design, and planning should start one to two
837 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
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years before deployment.838 CRC noted that full station development (i.e., design, permitting,
construction, and commissioning) takes about two years, assuming no major hurdles. In
California, they estimated that about 20 percent of more recent projects took up to 2.6 years to
build.839 The California Energy Commission has evaluated hydrogen refueling station
development in California since 2010. Their planned network of 200 stations is mainly for light-
duty vehicles but has at least 13 stations with the capability to serve HD FCEVs.840 Station
development times have generally decreased over time, from a median or typical time spent of
around 1500 days in 2010 to about 500 days in 2019 (i.e., about two years if considering
business days) for projects that have completed all phases of development.841 They expect some
increase in median development times as projects delayed by the COVID-19 pandemic are
completed but regularly monitor progress and work to improve the deployment process.842
We note further, as one commenter points out, that hydrogen infrastructure development
might have certain advantages over BEV infrastructure that favor its rapid deployment such as
existing petroleum infrastructure that can be leveraged in some instances and fewer potential
policy and process challenges (e.g., associated with utility commission regulations).
We recognize that these plans will require sustained support to come to fruition, and our
assessment, in consultation with relevant federal agencies, is that our projections are supported
and correspond to our measured approach in our modeled compliance pathway for FCEVs. There
are many complex factors at play, and we have taken a close look at how the ramp-up period
over the next decade is critical. In our modeled potential compliance pathway, we evaluated the
existing and projected future hydrogen refueling infrastructure and considered FCEVs only in the
MY 2030 and later timeframe to better ensure that our compliance pathway provides adequate
time for early market infrastructure development. We conclude that a phased and targeted
approach can offer sufficient lead time to meet the projected refueling needs that correspond to
the technology packages for the final rule's potential compliance pathway, as further discussed in
RIA Chapter 2.1. Additionally, EPA is committed to ensuring the Phase 3 program is
successfully implemented and, as described in preamble Section II.B.2.iii, in consideration of
concerns raised regarding inherent uncertainties about the future, we are including a commitment
to monitor progress on infrastructure development in the final rule.
838 Fulton, et. al. "California Hydrogen Analysis Project: The Future Role of Hydrogen in a Carbon-Neutral
California—Final Synthesis Modeling Report". UC Davis Institute of Transportation Studies. April 19, 2023.
Available online: https://escholarship.org/uc/item/27m7g841.
839 Coordinating Research Council, Inc. "Assess the Battery-Recharging and Hydrogen-Refueling Infrastructure
Needs, Costs, and Timelines Required to Support Regulatory Requirements for Light-, Medium-, and Heavy-Duty
Zero-Emission Vehicles: Final Report". Prepared by ICF. CRC Report No. SM-CR-9. September 2023. Available
online: https://crcao.org/wp-
content/uploads/2023/09/CRC_Infrastructure_Assessment_Report_ICF_09282023_Final-Report.pdf.
840 The CEC has invested nearly $40 million in medium- and heavy-duty hydrogen infrastructure.
841 Berner, et al. "Joint Agency Staff Report on Assembly Bill 8: 2022 Annual Assessment of Time and Cost Needed
to Attain 100 Hydrogen Refueling Stations in California". California Energy Commission & California Air
Resources Board. December 2022. Available online: https://www.energy.ca.gov/sites/default/files/2022-12/CEC-
600-2022-064.pdf.
842 Berner, et al. "Joint Agency Staff Report on Assembly Bill 8: 2022 Annual Assessment of Time and Cost Needed
to Attain 100 Hydrogen Refueling Stations in California". California Energy Commission & California Air
Resources Board. December 2022. Available online: https://www.energy.ca.gov/sites/default/files/2022-12/CEC-
600-2022-064.pdf.
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1.8.4 Environmental Considerations
As mentioned in RIA Chapters 1.8.2.1 and 1.8.3, the environmental impacts of different
hydrogen pathways can vary. Recent investment and policy interest in hydrogen is rooted in its
decarbonization potential and we expect that hydrogen production will become cleaner in the
coming years. Depending on how the hydrogen market scales, additional considerations may
need to be addressed.
Scientists are continuing to evaluate the potential of hydrogen to have indirect warming
impacts. Hydrogen does not absorb and trap heat within the Earth's atmosphere and is therefore
not considered a direct greenhouse gas. However, studies show that there are indirect radiative
effects caused by the presence of emitted hydrogen in the troposphere.843 Limited research
suggests that hydrogen released to the troposphere may affect ozone concentrations and prolong
the lifetime of methane.844'845'846'847'848 The Intergovernmental Panel on Climate Change (IPCC)
and United Nations Framework Convention on Climate Change (UNFCCC) have not identified
and established a global warming potential849 associated with hydrogen.850 Its secondary impacts
on warming should mitigate over time as methane emissions are controlled.851
Due to its extremely small molecular size, there can be leakage of gaseous hydrogen during
production, transportation, storage, and dispensing into vehicles. It may need to be vented or
purged when used in equipment. Such losses are presently expected to be small, due to the
relatively small volumes of hydrogen in production today (e.g., 10 MMT produced per year in
the United States and 90 MMT per year globally, compared to up to 660 MMT of global low-
843 Derwent, R., et al. "Global environmental impacts of the hydrogen economy". International Journal of Nuclear
Hydrogen Production and Applications, 1(1), 57. May 2006. Available online:
https://doi.org/10.1504/IJNHPA.2006.009869.
844 Hydrogen gas released into the atmosphere can have climate and air quality effects through atmospheric chemical
reactions. In particular, hydrogen is known to react with the hydroxyl radical, reducing concentrations of the
hydroxyl radical in the atmosphere. Because the hydroxyl radical is important for the destruction of many other
gases, a reduction in hydroxyl radical concentrations will lead to increased lifetimes of many other gases—including
methane and tropospheric oxone. This means that hydrogen gas emissions can also indirectly contribute to warming
through increased concentrations of methane and ozone.
845 Forster, Piers, et al. "Changes in Atmospheric Constituents and in Radiative Forcing". IPCC. p. 106. February
2018. Available online: https://www.ipcc.ch/site/assets/uploads/2018/02/ar4-wgl-chapter2-l.pdf.
846 Ocko, Ilissa B. and Steven P. Hamburg, Environmental Defense Fund. "Climate consequences of hydrogen
emissions". Atmospheric Chemistry and Physics: 22. July 20, 2022. Available online:
https://acp.copernicus.org/articles/22/9349/2022/.
847 Sand, Maria, et. al. "A multi-modal assessment of Global Warming Potential of hydrogen". Communications
Earth & Environment. June 7, 2023. Available online: https://www.nature.com/articles/s43247-023-00857-8.
848 Warwick, Nicola J., et. al. "Atmospheric composition and climate impacts of a future hydrogen economy".
Atmospheric Chemistry and Physics: Volume 23, Issue 20. October 25, 2023. Available online:
https://acp.copernicus.org/articles/23/13451/2023/acp-23-13451-2023-discussion.html.
849 A Global Warming Potential (GWP) is a quantified measure of the globally averaged relative radiative forcing
impacts of a particular GHG relative to carbon dioxide.
850 IPCC. "Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth
Assessment Report of the Intergovernmental Panel on Climate Change". Geneva, Switzerland: IPCC. 2021.
Available online: https://report.ipcc.ch/ar6/wg 1/IPCC AR6 WGI_FullReport.pdf
851 U.S. Environmental Protection Agency." EPA's Final Rule for Oil and Natural Gas Operations Will Sharply
Reduce Methane and Other Harmful Pollution". December 2, 2023. Available online:
https://www.epa.gov/controlling-air-pollution-oil-and-natural-gas-operations/epas-final-rule-oil-and-natural-gas.
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GHG hydrogen potential in 2050 to meet climate goals).852 Even as hydrogen scales and much
larger volumes are produced, with the attendant potential for emissions of hydrogen to oxidize in
the atmosphere, we expect the benefits of low-GHG hydrogen as part of a low-carbon economy
to outweigh any such effects in the future.853 Furthermore, there is financial incentive to improve
how to measure, monitor, evaluate, and manage hydrogen losses throughout the value
chain.854'855 Research is underway to understand ways to ensure that climate benefits of
hydrogen can be maximized and any potential adverse effects minimized.856
852 Hydrogen Council and McKinsey & Company. "Hydrogen Insights 2022: An updated perspective on hydrogen
market development and actions required to unlock hydrogen at scale". September 2022. Available online:
https://hydrogencouncil.com/wp-content/uploads/2022/09/Hydrogen-Insights-2022-2.pdf.
853 Arrigoni, A. and Bravo Diaz, L. "Hydrogen emissions from a hydrogen economy and their potential global
warming impact". EUR 31188 EN, Publications Office of the European Union, Luxembourg, 2022, ISBN 978-92-
76-55848-4, doi: 10.2760/065589, JRC130362. Available online:
https://publications.irc.ec.europa.eu/repositorv/handle/JRC130362.
854 Fan, Zhiyuan, et. al. "Hydrogen Leakage: A Potential Risk for the Hydrogen Economy". Columbia SIP A, Center
on Global Energy Policy. July 5, 2022. Available online:
https://www.energypolicy.columbia.edu/publications/hydrogen-leakage-potential-risk-hydrogen-economy/.
855 Koch blank, Thomas, et. al. "Hydrogen Reality Check #1: Hydrogen is Not a Significant Warming Risk". Rocky
Mountain Institute. May 9, 2022. Available online: https://rmi.org/hvdrogen-realitv-check-1 -hydrogen-is-not-a-
significant-warming-risk/.
856 Frazer-Nash Consultancy. "Fugitive Hydrogen Emissions in a Future Hydrogen Economy". March 2022.
Available online:
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1067137/fugitive-
hydrogen-emissions-future-hydrogen-economy.pdf.
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Chapter 2 Technology Assessment
2.1 Introduction
This chapter describes the operational characteristics and costs that we used to estimate
heavy-duty technologies' feasibility and suitability and the analysis for the modeled potential
compliance pathway's technology package that supports the feasibility of the final standards for
MYs 2027 through 2032. For manufacturers, costs are typically direct manufacturing costs
(DMC), but also retail price equivalents (RPE), which include DMC and indirect costs, in some
cases as appropriate. We also evaluated purchaser upfront costs and operating costs. Additional
discussion of DMC, indirect costs, and RPE, as well as purchaser upfront costs and operating
costs, can be found in Chapter 3.2 of the RIA.
Many technologies have been demonstrated to reduce GHG emissions and are considered
technically feasible for HD vehicles. Our analysis for this final rule further shows that a diverse
range of HD vehicle technologies are feasible and may be used to comply with the final
standards to reduce GHG emissions, including ICE (including alternative-fueled), hybrid, and
plug-in hybrid vehicle technologies, hydrogen-fueled ICE technologies (H2 ICE), BEV
technologies, and FCEV technologies. To conduct the portion of our analysis with regard to BEV
and FCEV technologies, EPA developed a flexible spreadsheet-based framework called the
Heavy-Duty Technology Resource Use Case Scenario (HD TRUCS) tool.857 The tool in its
current form is used to evaluate ICE vehicles, BEV, FCEVs, and PHEVs but could easily be
adapted to evaluate other technologies.
While we acknowledge and are aware of other tools and models that perform related functions
and have gathered important insights from them,858'859'860'861 HD TRUCS has proven to be an
excellent analytic tool for assessing heavy-duty vehicle suitability, cost, and payback
comparisons between BEV and FCEV technologies (which we refer to as ZEVs collectively
within this RIA) as compared to a comparable ICE vehicle, based on data and resources available
to EPA at the time of the analysis. Because Clean Air Act section 202(a)(l)-(2) requires EPA to
consider lead time and costs in establishing standards, and because manufacturers (and
purchasers) of HD vehicles are profit-generating enterprises that are seeking to reduce costs,
EPA then undertook an analysis to identify the technologies that would be most effective at
857 See Memorandum to docket EPA-HQ-OAR-2022-0985. "Heavy-Duty Technology Resource Use Case Scenario
Tool (HD TRUCS). Final Rule." March 2024.
858 For example, as cited in the endnotes: ACT Research's report mentions a proprietary Total Cost of Ownership
model; Ledna et. al uses the National Renewable Energy Laboratory's Transportation Energy & Mobility Pathway
Options Model (TEMPO) model; and California Air Resources Board's report refers to an assessment matrix
developed by the Truck and Engine Manufacturers Association (EMA). Chapter 2.1.2 also discusses our use of
Argonne National Laboratory's BEnefit ANalysis (BEAN) and Autonomie models.
859 Mitchell, George. Memorandum to docket EPA-HQ-OAR-2022-0985. ACT Research Co. LLC. "Charging
Forward" 2020-2040 BEV & FCEV Forecast & Analysis, updated December 2021.
860 Ledna et. al. "Decarbonizing Medium- & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost
Analysis". U.S. Department of Energy, National Renewable Energy Laboratory. March 2022. Available online:
https://www.nrel.gov/docs/fV22osti/82081.pdf.
861 California Air Resources Board. Advanced Clean Trucks Regulation: Public Hearing Notice and Related
Material, "Appendix E: Zero Emission Truck Market Assessment". Posted October 22, 2019. Available online:
https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2019/act2019/appe.pdf
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reducing GHG emissions and are feasible and cost-effective at doing so in the MYs 2027-2032
time frame to include in technology packages and model as a potential compliance pathway for
the final standards. This analysis included using HD TRUCS. ZEV technologies for the heavy-
duty sector have developed markedly since EPA promulgated the Phase 2 rule, and we anticipate
future improvements and increase in use in the heavy-duty sector, as discussed in Chapter l.862
At the same time, EPA modeled other technologies (included in technology packages with
different mixes of technologies as examples of other potential compliance pathways, as
discussed in RIA Chapters 1.4.3 and 2.11) recognizing that OEMs can legally and practically
choose many different ways to achieve CO2 emissions reductions to comply with the final
standards.
Regarding our approach to thoroughly analyze potential ZEV technologies, we used HD
TRUCS to evaluate the design features needed to meet the energy and power demands of various
HD vehicle types when using ZEV technologies. To assess these ZEV technologies using HD
TRUCS, we created 101 representative vehicles in HD TRUCS that cover the full range of
weight classes within the scope of the final standards (i.e., Class 2b through 8 vocational vehicles
and tractors). The representative vehicles cover many aspects of work performed by the industry.
This work was translated into total energy and power demands per vehicle type based on
everyday use of HD vehicles, ranging from moving goods and people to mixing cement. We then
identified the technical properties required for a BEV or FCEV to meet the operational needs of a
comparable ICE vehicle.863
Since batteries can add weight and volume to a BEV,864 we evaluated battery mass and
physical volume required to package a battery pack. If the performance needs of a BEV resulted
in a battery that was too heavy or large, then we did not consider the BEV for that application in
our technology packages because of the impact on payload and, thus, potential work
accomplished relative to a comparable ICE vehicle.865
To evaluate costs, including costs of compliance for manufacturers as well as purchaser costs
related to purchasing and operating ZEVs, we sized vehicle components that are unique to ZEVs
to meet the work demands of each representative vehicle. We determined the cost of each
powertrain component based on sizing to assess the difference in total powertrain costs between
the ICE and ZEV powertrains. We accounted for the IRA battery tax credit and vehicle purchase
tax credit. We also compared operating costs due to fuel and electricity consumption as well as
vehicle maintenance and repair, and we included the cost to procure, install, and support depot
862 BEVs and FCEVs may be well-suited to many heavy-duty applications because these technologies have high
low-end torque, which may provide benefits for heavy vehicles at low speeds.
863 Heavy-duty vehicles are typically powered by a diesel-fueled compression-ignition (CI) engine, though the
heavy-duty market includes vehicles powered by gasoline-fueled spark-ignition (SI) engines and alternative-fueled
ICEs. We selected diesel-powered ICE vehicles as the baseline vehicle for the assessment in HD TRUCS in our
analysis because a diesel-fueled CI engine is broadly available for all of the 101 vehicle types and diesel engines are
more efficient than SI engines.
864 Smith, David et. al. "Medium- and Heavy-Duty Vehicle Electrification: An Assessment of Technology and
Knowledge Gaps". U.S. Department of Energy: Oak Ridge National Laboratory and National Renewable Energy
Laboratory. December 2019. Available online: https://info.ornl.gov/sites/publications/Files/Publ36575.pdf.
865 This does not necessarily mean that a BEV with a large battery weight and volume would not be technically
feasible for a given HD vehicle use, but rather this is an acknowledgement that we considered impacts of increased
battery size on feasibility considerations like payload capacity as well as cost and payback within the selection of
HD vehicle technologies for the technology packages.
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charging infrastructure for BEVs (including accounting for the IRA EVSE tax credit). We have
also assessed the cost of public charging infrastructure with respect to certain BEV applications,
and analyzed that cost as part of the cost to charge (assessed as $/kWh of electricity), similar to
ICE vehicles' infrastructure and fuel costs. For FCEVs, we likewise analyzed hydrogen
infrastructure costs as part of the cost of hydrogen fuel.
We relied on research and findings discussed in RIA Chapter 1 and throughout this RIA
Chapter 2 to conduct the HD TRUCS analysis. For MYs 2027 through 2029, our modeled
compliance pathway's technology package focuses primarily on BEV technology using depot
charging. Our modeling finds, and research supports, that BEV technologies can become cost-
competitive for some duty cycles of HD vehicles by the late 2020s.866'867'868 Given that there are
many more BEV models available today compared to FCEV models (e.g., see RIA Chapters
1.7.5 and 1.7.6), we reasoned that BEV technology adoption is likely to happen sooner than the
adoption of FCEV technology.
Starting in MY 2030, we also considered FCEV technology and BEVs using public charging
for select applications in our HD TRUCS analysis. BEV technology is more efficient than FCEV
technology but may not be as suitable for all applications, such as when the vehicle operating
needs, such as long range, result in battery mass that may raise challenges in relation to the
payload that the vehicle needs to carry. In cases like this, we considered either BEVs with
smaller batteries (that may require enroute charging and the consequent use of public charging
away from the depot) or FCEVs (which have shorter refueling times than BEVs with large
batteries). FCEVs are more efficient than diesel vehicles and can have shorter refueling times
than batteries.869'870 We considered FCEVs and BEVs using public charging in the technology
packages for applications that travel longer distances and/or carry heavier loads (i.e., for those
that may be sensitive to refueling times or payload impacts). This included coach buses and
tractors.
Though fuel cell technology is still emerging in HD vehicle applications, based on our review
of the literature as well as information provided in public comments, FCEVs are a viable,
866 Ledna et. al. "Decarbonizing Medium- & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost
Analysis". U.S. Department of Energy, National Renewable Energy Laboratory. March 2022. Available online:
https://www.nrel.gov/docs/fV22osti/82081.pdf.
867 Hall, Dale and Nic Lutsey. "Estimating the Infrastructure Needs and Costs for the Launch of Zero-Emission
Trucks". White Paper: The International Council on Clean Transportation. August 2019. Available online:
https://theicct.org/wp-content/uploads/2021/06/ICCT EV HDVs Infrastructure 20190809.pdf.
868 Robo, Ellen and Dave Seamonds. Technical Memo to Environmental Defense Fund: Investment Reduction Act
Supplemental Assessment: Analysis of Alternative Medium- and Heavy-Duty Zero-Emission Vehicle Business-As-
Usual Scenarios. ERM. August 19, 2022. Available online:
https://www.erm.com/contentassets/154d08e0d0674752925cd82c66b3e2bl/edf-zev-baseline-technical-memo-
addendum.pdf.
869 A technology is more energy efficient if it uses less energy to do the same amount of work. Energy can be lost as
it moves through the vehicle's components due to heat and friction.
870 Cunanan, Carlo et. al. "A Review of Heavy-Duty Vehicle Powertrain Technologies: Diesel Engine Vehicles,
Battery Electric Vehicles, and Hydrogen Fuel Cell Electric Vehicles". Clean Technol. Available online:
https://www.mdpi. com/25 71-879 7/3/2/28.
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technically feasible ZEV technology for heavy-duty transportation.871'872'873 FCEVs are available
today with more models expected by the 2030 timeframe (see RIA Chapter 1.7.5).874'875'876
Inclusion of FCEVs in the technology packages starting in MY 2030 takes into consideration
additional lead time to allow manufacturers to design, develop, and manufacture HD FCEV
models. Fuel cell technology in other sectors has been in existence for decades877 and has been
demonstrated to be technically feasible in heavy-duty transportation.878 Interim research and
development (R&D) technical targets and projects (see RIA Chapter 1.7.7) are in place to
facilitate necessary improvements in the performance, durability, and costs of hydrogen-fueled
long-haul HD tractors in 2030.879 With substantial federal investment in low-GHG hydrogen
production (see RIA Chapter 1.3.2), we anticipate that the price of hydrogen fuel will drop
enough to make HD FCEVs cost-competitive with comparable ICE vehicles for some vehicle
applications during the 10-year payback period. Hydrogen infrastructure is expected to need the
additional time prior to MY 2030 to further develop, as discussed in greater detail in RIA
Chapter 1.8, but we project the refueling needs can be met by MY 20 3 0.880 We also recognize
the impact regulations (e.g., through regulatory certainty) can have on technology and refueling
infrastructure development and deployment.
After considering operational characteristics and costs, the next step in our HD TRUCS
analysis was determining the payback period, which is the number of years it will take to offset
any incremental cost increase of a ZEV over a comparable ICE vehicle. Lastly, we assessed and
871 Mihelic, Rick et. al. "Making Sense of Heavy-Duty Hydrogen Fuel Cell Tractors". North American Council for
Freight Efficiency. December 16, 2020. Available online: https://nacfe.org/research/electric-trucks/making-sense-of-
heavy-duty-hydrogen-fuel-cell-tractors/.
872 Cunanan, Carlo et. al. "A Review of Heavy-Duty Vehicle Powertrain Technologies: Diesel Engine Vehicles,
Battery Electric Vehicles, and Hydrogen Fuel Cell Electric Vehicles". Clean Technol. Available online:
https://www.mdpi. com/25 71-879 7/3/2/28.
873 Cullen et. al. "New roads and challenges for fuel cells in heavy-duty transportation". Nature Energy. March 25,
2021. Available online: https://www.nature.com/articles/s41560-021-00775-z.
874 International Energy Agency. "Energy Technology Perspectives 2023". January 2023. Available online:
https://iea.blob.core.windows.net/assets/a86b480e-2b03-4e25-bael-
dal395e0b620/EnergyTechnologyPerspectives2023.pdf.
875 McKinsey & Company, McKinsey Center for Future Mobility. "Preparing the world for zero-emission trucks".
September 2022. Available online:
https://www.mckinsey.eom/~/media/mckinsey/industries/automotive%20and%20assembly/our%20insights/preparin
g%20the%20world%20for%20zero%20emission%20trucks/preparing-the-world-for-zero-emission-trucks.pdf,
876 Divis, Andrej, et. al. "Fuel for Thought: The commercial vehicle fleet accelerates toward ZEV adoption". S&P
Global Mobility. July 26, 2023. Available online: https://www.spglobal.com/mobility/en/research-analysis/fuel-for-
thought-the-commercial-vehicle-fleet-accelerates.html.
877 U.S. Energy Information Administration. "Hydrogen explained: Use of hydrogen". Last updated January 20,
2022. Available online: https://www.eia.gov/energvexplained/hvdrogen/use-of-hvdrogen.php.
878 Toyota. "Toyota, Kenworth Prove Fuel Cell Electric Truck Capabilities with Successful Completion of Truck
Operations forZANZEFF Project". September 22, 2022. Available online: https://pressroom.tovota.com/tovota-
kenworth-prove-fuel-cell-electric-truck-capabilities-with-successful-completion-of-truck-operations-for-zanzeff-
project/.
879 Marcinkoski, Jason et. al. "DOE Advanced Truck Technologies: Subsection of the Electrified Powertrain
Roadmap—Technical Targets for Hydrogen-Fueled Long-Haul Tractor-Trailer Trucks. October 31, 2019. Available
online: https://www.hvdrogen.energy.gov/pdfs/19006 hydrogen class8 long haul truck targets.pdf.
880 U.S. Department of Energy. "U.S. National Clean Hydrogen Strategy and Roadmap". June 2023. Available
online: https://www.hydrogen.energy.gov/librarv/roadmaps-vision/clean-hydrogen-strategv-roadmap.
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/us-national-clean-hydrogen-strategy-
roadmap.pdf.
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applied a payback schedule to the payback periods, which resulted in percentages of BEV
technologies and FCEV technologies we then considered in the technology packages for the
modeled potential compliance pathway to support the feasibility of the standards.
From a vehicle's emission standard compliance perspective, BEVs and FCEVs both emit zero
grams of CO2 per ton-mile at the tailpipe. Our HD TRUCS analysis discussed in this chapter
focuses on these two technologies as part of one pathway for complying with the standards, but
there are other technologies we included in technology packages with different mixes of
technologies as examples of other potential compliance pathways as described in RIA Chapter 1
and Chapter 2.11 that can reduce CO2 emissions, including Fh fueled ICE vehicles that also emit
0 g CO2 out of the engine.881 Manufacturers may choose to utilize the technologies that work best
for their business case and the operator's needs in meeting the final performance-based
standards.
The remainder of RIA Chapter 2.1 provides an overview of the structure of the HD TRUCS
tool. RIA Chapters 2.1 through 2.6 discuss tool inputs used to compare ZEV technologies to a
comparable diesel ICE vehicle. RIA Chapter 2.2 explains how we established benchmark
performance requirements for each HD TRUCS vehicle, independent of the powertrain. RIA
Chapter 2.3 describes diesel vehicle components, upfront technology costs, diesel fuel
consumption, and operational costs. RIA Chapter 2.4 describes BEV components, how
components were sized in HD TRUCS to meet the performance requirements of heavy-duty
vehicles, upfront technology costs, BEV energy consumption, and operational costs. RIA
Chapter 2.5 describes FCEV components, how components were sized in HD TRUCS to meet
the performance requirements of heavy-duty vehicles, upfront technology costs, FCEV energy
consumption, and operational costs. RIA Chapter 2.6 contains a discussion of BEV charging and
infrastructure. RIA Chapter 2.7 explains technology adoption approaches considered in the
heavy-duty sector. RIA Chapter 2.8 summarizes the methodologies used in HD TRUCS to assess
energy consumption of heavy-duty vehicles and ZEVs and evaluate technology feasibility,
payback, and adoption rates in the technology packages for the modeled compliance pathway to
support the final standards. RIA Chapter 2.9 shows the results of the analysis. RIA Chapter 2.10
summarizes the final standards. Chapter 2.11 describes three additional example potential
compliance pathways. Chapter 2.12 describes a TCO (total cost to own) analysis that
complements the HD TRUCs payback analysis.
The final version of HD TRUCS has a number of improvements to the proposal's version that
were made based on consideration of stakeholder comments and additional information. These
include both refinements to certain inputs and addressing a few minor errors in inputs, as
described in the following sections and in RTC Section 3.
881 Hydrogen-powered internal combustion engines (H2-ICE) fueled with neat hydrogen emit zero engine-out CO2
emissions (as well as zero engine-out HC, CH4, CO emissions). We recognize that there may be negligible, but non-
zero, CO2 emissions at the tailpipe of H2-ICE that use selective catalytic reduction (SCR) aftertreatment systems
and are fueled with neat hydrogen due to contributions from the aftertreatment system from urea decomposition. As
further explained in preamble Section III, H2-ICE are considered to emit near zero CO2 emissions under our part
1036 regulations and are deemed zero under out part 1037 regulations, consistent with our treatment of CO2
emissions that are attributable to the aftertreatment systems in compression-ignition ICEs. H2-ICE also emit certain
criteria pollutants. H2-ICE are not included in what we refer to collectively as ZEVs throughout this final rule. Note,
NOx and PM emission testing is required under existing 40 CFR part 1036 for engines fueled with neat hydrogen.
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Much of the material in this and other chapters of this RIA reflects EPA's long-standing
expertise in the area of mobile source emissions and regulatory standards development. EPA's
Office of Transportation and Air Quality (OTAQ) has more than fifty years of experience in
developing standards to reduce air pollution and greenhouse gas emissions from mobile sources.
This work has historically involved not only broad stakeholder engagement and foundational
work in regulatory design but also the development of deep scientific and technical expertise in
the engineering and science surrounding the measurement, modeling, and control of mobile
source emissions. This has included the development of sophisticated modeling tools to assess
mobile source-related air quality problems; establishing national and international standards to
reduce emissions; implementing standards through certification processes and in-use monitoring
strategies; developing fuel efficiency programs and technologies; and researching, evaluating,
and developing advanced technologies and new strategies for controlling emissions. Staff have a
variety of technical, legal, policy, and communications backgrounds to work effectively with
diverse stakeholders throughout this process. This includes employing well over a hundred staff
with undergraduate and graduate degrees in mechanical engineering, electrical engineering,
automotive engineering, computer science and engineering, chemical engineering, material
science, physics, chemistry, and other engineering, science, and related fields, including
economics.
OTAQ also staffs and operates the National Vehicle and Fuel Emissions Laboratory (NVFEL)
in Ann Arbor, Michigan. For nearly 50 years, NVFEL has been a world-class, state-of-the-art
testing facility that provides emission testing support for EPA programs related to light- and
heavy-duty vehicles, heavy-duty engines, and nonroad engines, including testing of gasoline and
diesel engines and vehicles, HEVs, PHEVs, BEVs, electric machines, and high-voltage batteries.
EPA staff each year conduct hundreds of tests of vehicles and engines to measure emissions, fuel
economy, and performance metrics. EPA also represents the United States Government at the
United Nation's World Forum for the Harmonization of Vehicle Regulations, and where EPA
OTAQ employees have chaired several working groups that have developed Global Technical
Regulations to establish international test procedures and emission standard for light-duty
vehicles, motorcycles, heavy-duty engines and vehicles, and electric vehicles. EPA OTAQ staff
also routinely works with major independent technical automotive laboratories and engineering
contractors - the very same firms that are utilized by many of the light and heavy-duty engine
and vehicle manufacturers. These include multi-year contracts with Southwest Research Institute
and FEV North America. EPA utilize these contracts to expand our access to additional
laboratory testing capabilities and expertise, including expertise in light and heavy-duty vehicle
technology assessments. OTAQ has established Cooperative Agreements with major
transportation research universities, including the University of Michigan, the University of
California - Davis, and Michigan State University. EPA OTAQ has utilized interagency
agreements with several of the Department of Energy and the Department of Transportation
national laboratories to collaborate on transportation sources research investigations, and the
National Vehicle and Fuel Emissions Laboratory has a long-standing, multi-decadal Cooperative
Research and Development Agreement with the major U.S. car manufacturers and the California
Air Resources Board to "identify, encourage, evaluate and envelope instrumentation and
techniques to accurately and efficiently measure emission from motor vehicles."
EPA OTAQ staff have authored and co-authored hundreds of peer reviewed articles in the
engineering, scientific, and economic literature, including publications by the Society of
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Automotive Engineers, the American Society of Mechanical Engineers, the Energy Policy
journal, the International Review of Environmental and Resource Economics, the World Electric
Vehicle Journal, Transportation Research, the International Journal of Environmental Research
and Public Health, and many others. The EPA publications in the literature cover a wide range of
topics, including the development of emission reduction technologies, new test vehicle and
engine testing procedures, technology cost projections based on vehicle and sub-system tear-
down assessments, vehicle and engine performance and emissions benchmarking, emission
measurement programs, vehicle modeling techniques, vehicle fuel testing programs, and public
health assessments of transportation emissions. EPA OTAQ employees have also frequently
been asked to serve as peer reviewers for a number of these journals. EPA OTAQ employees
working at the National Vehicle and Fuel Emissions Laboratory have also been granted over 100
U.S. patents covering a wide range of engine, and vehicle related technologies, including
technologies for reducing criteria pollutant and GHG emissions, improving fuel efficiency, and
technologies for the measurement of mobile source emissions.
2.1.1 HD TRUCS Vehicle Types
HD TRUCS includes 101 heavy-duty vehicle types that are representative of the wide range
of duty cycles and use cases in the HD industry. These 101 categories encompass 22 different
vehicle applications, which are further disaggregated by weight class, duty cycle, and daily
vehicle miles traveled (VMT).
The initial list of HD TRUCS vehicles was based on work the Truck and Engine
Manufacturers Association (EMA) and California Air Resources Board (CARB) conducted for
CARB's Advanced Clean Trucks (ACT) Regulation.882 That assessment contained 87 "market
segments". We first consolidated the list, eliminated some of the more unique vehicles with
fewer than 100 sales in California (like mobile laboratories), and assigned operational
characteristics for the vocational vehicles that correspond to the urban, multi-purpose (MP), and
regional duty cycles used in EPA's Greenhouse Gas Emissions Model (GEM).883'884 Secondly,
we added additional vehicles to reflect vehicle applications that were represented in EPA's 2019
Annual Production Volume (PV) Reports into Engine and Vehicle Compliance Information
Systems.885
For the FRM version of HD TRUCS, EPA made certain refinements to the 101 vehicle types
after consideration of comments on the proposal, including comments that said HD TRUCS
882 California Air Resources Board. Advanced Clean Trucks Regulation: Public Hearing Notice and Related
Material, "Appendix E: Zero Emission Truck Market Assessment". Posted October 22, 2019. Available online:
https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2019/act2019/appe.pdf.: California Air Resources Board,
Final Regulation Order - Advanced Clean Trucks Regulation. Filed March 15, 2021. Available online:
https ://ww2. arb. ca. gov/sites/default/files/barcu/regact/2019/act2019/fro2 .pdf.
883 GEM is an EPA vehicle simulation tool used to certify HD vehicles. HD TRUCS uses the version GEM2, which
was developed for EPA's Phase 2 Greenhouse Gas rulemaking. A detailed description of GEM is beyond the scope
of this document but can be found in the Phase 2 RIA or in GEM documentation on EPA's website. For more
information about how GEM was used to simulate road load power requirements for various duty cycles over the
default road load profiles to estimate work performed by HD vehicles, please see Miller, Neil. Memorandum to
docket EPA-HQ-OAR-2022-0985. "Gem Inputs and Results". November 2023.
884 U.S. Environmental Protection Agency. "Greenhouse Gas Emissions Model (GEM) for Medium- and Heavy-
Duty Vehicle Compliance". Available online: https://www.epa.gov/regulations-emissions-vehicles-and-
engines/greenhouse-gas-emissions-model-gem-medium-and-heaw-dutv.
885 US EPA, 2019 Annual Production Volume Reports into Engine and Vehicle Compliance Information System.
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should include tractors that are designed to use public charging. First, because three of the 101
vehicle types in the proposal were redundant to three other vehicle types, we aggregated the sales
of those vehicles into the corresponding vehicle types that remained. Second, we added three
additional tractors vehicle types. This resulted in 101 vehicle types in HD TRUCS for the final
rule.886. More specifically, we aggregated four light-heavy RVs from one vehicle type into two
light-heavy RVs different vehicle types, and also aggregated two light-heavy shuttle buses from
one vehicle type into one light-heavy shuttle bus vehicle type. We then reassessed all the tractors
vehicle types, such that there are now four day cabs vehicle types and three sleeper cabs vehicle
types that are modeled in our analysis to use public charging, starting in model year 2030. In
addition, of the tractors vehicle types that were designed for public charging, one day cab and
one sleeper cab were updated to reflect a more aerodynamic tractor design than the average
tractor aerodynamics used in the technology assessment to support the Phase 2 standards; this is
described in more detail in Chapter 2.2.2.1.Two day cabs and one sleeper cabs are assessed as
FCEVs, and the tractors with the shortest daily VMT were generally assessed as BEVs with
depot charging. For the final rule analysis, we evaluated the heavy-haul tractor with BEV
technology instead of with fuel cell technology as we did in the NPRM. In addition, for the final
rule analysis, we evaluated the coach buses with BEV technology in addition to fuel cell
technology, recognizing that there are currently BEV coach buses in the market today.
Table 2-1 summarizes the 101 unique vehicle types represented in HD TRUCS and how they
are categorized, each with a vehicle identifier (Vehicle ID), HD TRUCS vehicle application,
vehicle weight class, MOVES887 SourceTypelD and RegClassID, and GEM Energy ID.
Table 2-1 HD TRUCS Vehicle Types
Vehicle ID
Vehicle Application
Weight
Class
MOVES
source
TypelD
MOVES
regClassID
GEM Energy ID888 a
01 V_Amb_C14 -5MP
Ambulance
4-5
52
42
LHDM
02V_Amb_C12b-3_MP
Ambulance
2b-3
52
42
LHDM
03V_Amb_C14-5_U
Ambulance
4-5
52
42
LHDU
04V_Amb_C12b-3_U
Ambulance
2b-3
52
42
LHDU
05T_Box_C18_MP
Box Truck
8
52
47
HHDM
06T_Box_C18_R
Box Truck
8
53
47
HHDR
07T_Box_C16 -7MP
Box Truck
6-7
52
46
MHDM
08T_Box_C16 -7_R
Box Truck
6-7
53
46
MHDR
09T_Box_C18_U
Box Truck
8
52
47
HHDU
886 Note, while having exactly 101 vehicles is not meaningful to the analysis itself, maintaining the same overall 101
vehicle types made other updates to HD TRUCS easier as a practical matter. Before consolidating any vehicle types
we first verified that no assessment insight was lost, through confirming that the vehicle types that were aggregated
were effectively redundant.
887 MOVES is EPA's MOtor Vehicle Emissions Simulator, a state-of-the-art emission modeling system that
estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants,
greenhouse gases, and air toxics.
888 For the proposal, each tractor in HD TRUCS was assigned a GEM Energy ID for a Low Roof Tractor. However,
for the final rule, we have updated all tractors to use the high-roof default values in GEM. This update was made
because we found that high-roof tractors were the most common certification configuration in MY 2021. Because
the energy consumption rate for high roof tractors is typically higher than for low roof tractors, this is a conservative
assumption.
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Vehicle ID
Vehicle Application
Weight
Class
MOVES
source
TypelD
MOVES
regClassID
GEM Energy ID888 a
10T_Box_C16-7_U
Box Truck
6-7
52
46
MHDU
1 lT_Box_C12b-3_U
Box Truck
2b-3
52
42
LHDU
12T_Box_C12b-3_R
Box Truck
2b-3
52
42
LHDR
13T_Box_C12b-3_MP
Box Truck
2b-3
52
42
LHDM
14T_Box_C14-5_U
Box Truck
4-5
52
42
LHDU
15T_Box_C14-5_R
Box Truck
4-5
52
42
LHDR
16T_Box_C14-5_MP
Box Truck
4-5
52
42
LHDM
17B_Coach_C18_R
Coach Bus
8
41
47
Coach Bus
18B_Coach_C18_MPb
Coach Bus
8
41
47
Coach Bus
19 C_Mix_C18_MP
Cement Mixer
8
52
47
Concrete Mixer
20T_Dump_C18_U
Dump Truck
8
52
47
HHDU
21 T_Dump_C18_MP
Dump Truck
8
52
47
HHDM
22T_Dump_C16 -7MP
Dump Truck
6-7
52
46
MHDM
23 T_Dump_C18_U
Dump Truck
8
52
47
HHDU
24T_Dump_C16 -7_U
Dump Truck
6-7
52
46
MHDU
2 5 T_F ire_C18_MP
Fire Truck
8
52
47
HHDM
26T_Fire_C18_U
Fire Truck
8
52
47
HHDU
27T_Flat_C16-7_MP
Flatbed/Stake Truck
6-7
52
46
MHDM
2 8T_Flat_C16 -7_R
Flatbed/Stake Truck
6-7
52
46
MHDR
2 9T_Flat_C16 -7_U
Flatbed/Stake Truck
6-7
52
46
MHDU
30Tractor_DC_C18
TractorDC
8
61
47
C8DCHR
3 lTractor_DC_C17
TractorDC
7
61
46
C7DCHR
32Tractor_SC_C18
TractorSC
8
62
47
C8_SC_HR_CdA036
3 3 T ractorD CC18
TractorDC
8
61
47
C8_D CHRCd AO 3 6
34T_Ref_C18_MP
Refuse
8
51
47
Refuse Truck
3 5 T_Ref_C16 -7MP
Refuse
6-7
51
46
MHDM
36T_Ref_C18_U
Refuse
8
51
47
Refuse Truck
3 7T_Ref_C16 -7_U
Refuse
6-7
51
46
MHDU
38RVC18R
RV
8
54
47
RV
39RVC16-7R
RV
6-7
54
46
MHDR
40RVC14-5R
RV
4-5
54
42
LHDR
4 lTractor_DC_C17b
TractorDC
7
61
46
C7DCHR
42RVC18MP
RV
8
54
47
RV
43RV_C16-7_MP
RV
6-7
54
46
MHDM
44RV_C14-5_MP
RV
4-5
54
42
LHDM
45Tractor_DC_C18b
TractorDC
8
61
47
C8DCHR
46B_School_C18_MP
School Bus
8
43
47
HHDM
47B_School_C16-7_MP
School Bus
6-7
43
46
School Bus
48B_School_C14-5_MP
School Bus
4-5
43
42
LHDM
49B_School_C12b-3_MP
School Bus
2b-3
43
42
LHDM
50B_School_C18_U
School Bus
8
43
47
HHDU
5 lB_School_C16-7_U
School Bus
6-7
43
46
School Bus
52B_School_C14-5_U
School Bus
4-5
43
42
LHDU
53B_School_C12b-3_U
School Bus
2b-3
43
42
LHDU
54Tractor_SC_C18
TractorSC
8
62
47
C8SCHR
181
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Vehicle ID
Vehicle Application
Weight
Class
MOVES
source
TypelD
MOVES
regClassID
GEM Energy ID888 a
55B_Shuttle_C12b-3_MP
Shuttle Bus
2b-3
42
42
LHDM
56B_Shuttle_C14-5_U
Shuttle Bus
4-5
41
42
LHDU
57B_Shuttle_C12b-3_U
Shuttle Bus
2b-3
41
42
LHDU
5 8B_Shuttle_C16 -7MP
Shuttle Bus
6-7
42
46
MHDM
5 9B_Shuttle_C16 -7_U
Shuttle Bus
6-7
41
46
MHDU
60 SPlo w_C16 -7MP
Snow Plow
6-7
52
46
MHDM
61 S_Plow_C18_MP
Snow Plow
8
52
47
HHDM
62 SPlo w_C16 -7_U
Snow Plow
6-7
52
46
MHDU
63 S_Plow_C18_U
Snow Plow
8
52
47
HHDU
64V_Step_C16-7_MP
Step Van
6-7
52
46
MHDM
65V_Step_C14-5_MP
Step Van
4-5
52
42
LHDM
66 V_Step_C12b -3MP
Step Van
2b-3
53
42
LHDM
67V_Step_C16-7_U
Step Van
6-7
52
46
MHDU
68V_Step_C14-5_U
Step Van
4-5
52
42
LHDU
69V_Step_C12b-3_U
Step Van
2b-3
53
42
LHDU
70 S_S weep_C16 -7_U
Street Sweeper
6-7
52
46
MHDU
71 T_T anker_C18_R
Tanker Truck
8
52
47
HHDR
72TT ankerCI 8_MP
Tanker Truck
8
52
47
HHDM
73T_Tanker_C18_U
Tanker Truck
8
52
47
HHDU
74T_Tow_C18_R
Tow Truck
8
52
47
HHDR
7 5 T_T o w_C16 -7_R
Tow Truck
6-7
52
46
MHDR
76T_Tow_C18_U
Tow Truck
8
52
47
HHDU
77T_Tow_C16-7_U
Tow Truck
6-7
52
46
MHDU
78Tractor_SC_C18
TractorSC
8
62
47
C8SCHR
79Tractor_SC_C18b
TractorSC
8
62
47
C8SCHR
80Tractor_DC_C18
TractorDC
8
52
47
C8HH
81T ractorD CC17
TractorDC
7
61
46
C7DCHR
82Tractor_DC_C18
TractorDC
8
61
47
C8DCHR
83 T ractor_DC_C17
TractorDC
7
61
46
C7DCHR
84Tractor_DC_C18
TractorDC
8
61
47
C8DCHR
85B_Transit_C18_MP
Transit Bus
8
42
47
Transit Bus
86BT ransit_C16 -7MP
Transit Bus
6-7
42
46
MHDM
87B_Transit_C18_U
Transit Bus
8
42
48
Transit Bus
8 8B_T ransit_C16 -7_U
Transit Bus
6-7
42
46
MHDU
89T_Utility_C18_MP
Utility Truck
8
52
47
HHDM
90T_Utility_C18_R
Utility Truck
8
52
47
HHDR
9 lT_Utility_C16-7_MP
Utility Truck
6-7
52
46
MHDM
92T_Utility_C16-7_R
Utility Truck
6-7
52
46
MHDR
93T_Utility_C14-5_MP
Utility Truck
4-5
52
42
LHDM
94T_Utility_C12b-3_MP
Utility Truck
2b-3
52
42
LHDM
95T_Utility_C14-5_R
Utility Truck
4-5
53
42
LHDR
96T_Utility_C12b-3_R
Utility Truck
2b-3
53
42
LHDR
97T_Utility_C18_U
Utility Truck
8
52
47
HHDU
98T_Utility_C16-7_U
Utility Truck
6-7
52
46
MHDU
99T_Utility_C14-5_U
Utility Truck
4-5
52
42
LHDU
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Vehicle ID
Vehicle Application
Weight
Class
MOVES
source
TypelD
MOVES
regClassID
GEM Energy ID888 a
100T_Utility_C12b-3_U
Utility Truck
2b-3
52
42
LHDU
10 lTractor_DC_C18
Yard Tractor
8
61
47
C8DCHR
aLHD is light heavy-duty, MHD is medium heavy-duty, HHD is heavy heavy-duty, U is urban, R is regional, M
is multi-purpose, SC is sleeper cab, DC is day cab, HH is heavy haul, HR is high roof.
b These vehicle types were analyzed as FCEVs. The remaining vehicles were analyzed as BEVs.
It should be noted that while the vehicles are identified throughout this document using
several different vehicle characteristics as well as vehicle performance metrics, we sometimes
show the vehicles grouped in different ways. This is due to the differences in categorization
among underlying data sources. For example, vehicles in MOVES are grouped differently than
the GEM subcategories (or, for that matter, different than the regulatory subcategories in the
Phase 3 standards). In most cases, we will show the results for the 101 HD TRUCS vehicle types
listed in Table 2-1, and include additional aggregation as applicable.
2.1.2 HD TRUCS Inputs
Inputs to the analysis were chosen based on our assessment of available literature, analysis,
engineering judgement, comments on the NPRM, and other information about vehicles in the
HD market, as described in later chapters. We presume that values from literature represent
calendar year (CY). However, because model year certification in the heavy-duty industry
largely follows the calendar year, calendar year and model year values are typically the same.
Baseline energy consumption is based largely on results from EPA's GEM model (see RIA
Chapter 2.2.2), and the targets to determine the peak power requirement are generally based on
the ANL Autonomie model (see RIA Chapter 2.4.1.2). Activity data is based on multiple data
sources, including National Renewable Energy Laboratory's (NREL) detailed FleetDNA data
(see RIA Chapter 2.2.1). Vehicle sales estimates are generally based on EPA's MOVES 4.R3
(see RIA Chapter 2.2.3). Many of the cost estimates and BEV and FCEV technical assumptions
originated from ANL's Autonomie889 and BEAN890 tools used for DOE's Vehicle Technologies
Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) Research and
Development (R&D) Benefits Analysis of 2022; 891>892 however, some of these assumptions have
been updated for the final version of HD TRUCS based on consideration of comments received
and on new data. Table 2-2 shows the HD TRUCS vehicle ID mapping to ANL vehicle
categories. In the proposal, most cost values that are derived from ANL's 2022 BEAN tool were
889 Autonomie is a vehicle system simulation tool used to assess the energy consumption, performance, and costs of
multiple advanced vehicle technologies.
890 BEAN was developed to quantify the impact of individual vehicle component technologies on costs. ANL has
worked for years with industry stakeholders and other national laboratories to develop these tools.
891 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6, October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1406494585829.
892 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
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incorrectly identified as being in 2019$, when in fact they are in 2020$. This has been corrected
in the final rule.
Table 2-2 HD TRUCS Vehicle ID mapping to ANL vehicles
Vehicle ID
ANL Purpose
ANL RegCode
ANL Class
01V Amb C14-5 MP
Service
Medium
4
02V Amb C12b-3 MP
Van
Medium
3
03V Amb C14-5 U
Service
Medium
4
04V Amb C12b-3 U
Van
Medium
3
05T Box C18 MP
Vocational
Heavy
8
06T Box C18 R
Vocational
Heavy
8
07T Box C16-7 MP
Box
Medium
6
08T Box C16-7 R
Box
Medium
6
09T Box C18 U
Vocational
Heavy
8
10T Box C16-7 U
Box
Medium
6
11T Box C12b-3 U
Box
Medium
3
12T Box C12b-3 R
Box
Medium
3
13T Box C12b-3 MP
Box
Medium
3
14T Box C14-5 U
Box
Medium
4
15T Box C14-5 R
Box
Medium
4
16T Box C14-5 MP
Box
Medium
4
17B Coach C18 R
Transit
Heavy
8
18B Coach C18 MP
Transit
Heavy
8
19C Mix C18 MP
Vocational
Heavy
8
20T Dump C18 U
Vocational
Heavy
8
21T Dump C18 MP
Vocational
Heavy
8
22T Dump C16-7 MP
Vocational
Medium
7
23T Dump C18 U
Vocational
Heavy
8
24T Dump C16-7 U
Vocational
Medium
7
25T Fire C18 MP
Vocational
Heavy
8
26T Fire C18 U
Vocational
Heavy
8
27T Flat C16-7 MP
Vocational
Medium
7
28T Flat C16-7 R
Vocational
Medium
7
29T Flat C16-7 U
Vocational
Medium
7
30Tractor DC C18
Drayage
DayCab
8
31 Tractor DC C17
Tractor
DayCab
7
32Tractor SC C18
Longhaul
Sleeper
8
33Tractor DC C18
Tractor
DayCab
7
34T Ref C18 MP
Refuse
Heavy
8
35T Ref C16-7 MP
Vocational
Medium
7
36T Ref C18 U
Refuse
Heavy
8
37T Ref C16-7 U
Vocational
Medium
7
38RV C18 R
Transit
Heavy
8
39RV C16-7 R
School
Medium
7
40RV C14-5 R
StepVan
Medium
4
41 Tractor DC C17
Tractor
DayCab
7
42RV C18 MP
Transit
Heavy
8
43RV C16-7 MP
School
Medium
7
44RV C14-5 MP
StepVan
Medium
4
45Tractor DC C18
Regional
DayCab
8
46B School C18 MP
Transit
Heavy
8
47B School C16-7 MP
School
Medium
7
48B School C14-5 MP
StepVan
Medium
4
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49B School C12b-3 MP
School
Medium
3
50B School C18 U
Transit
Heavy
8
5 IB School C16-7 U
School
Medium
7
52B School C14-5 U
StepVan
Medium
4
53B School C12b-3 U
School
Medium
3
54Tractor SC C18
Longhaul
Sleeper
8
55B Shuttle C12b-3 MP
School
Medium
3
56B Shuttle C14-5 U
StepVan
Medium
4
57B Shuttle C12b-3 U
School
Medium
3
58B Shuttle C16-7 MP
School
Medium
7
59B Shuttle C16-7 U
School
Medium
7
60S Plow C16-7 MP
Vocational
Medium
7
61S Plow C18 MP
Vocational
Heavy
8
62 S Plow C16-7 U
Vocational
Medium
7
63 S Plow C18 U
Vocational
Heavy
8
64V Step C16-7 MP
StepVan
Medium
6
65V Step C14-5 MP
StepVan
Medium
4
66V Step C12b-3 MP
Van
Medium
3
67V Step C16-7 U
StepVan
Medium
6
68V Step C14-5 U
StepVan
Medium
4
69V Step C12b-3 U
Van
Medium
3
70S Sweep C16-7 U
Vocational
Medium
7
71T Tanker C18 R
Vocational
Heavy
8
72T Tanker C18 MP
Vocational
Heavy
8
73T Tanker C18 U
Vocational
Heavy
8
74T Tow C18 R
Vocational
Heavy
8
75T Tow C16-7 R
Vocational
Medium
7
76T Tow C18 U
Vocational
Heavy
8
77T Tow C16-7 U
Vocational
Medium
7
78Tractor SC C18
Longhaul
Sleeper
8
79Tractor SC C18
Longhaul
Sleeper
8
80Tractor DC C18
Vocational
Heavy
8
81 Tractor DC C17
Tractor
DayCab
7
82Tractor DC C18
Regional
DayCab
8
83Tractor DC C17
Tractor
DayCab
7
84Tractor DC C18
Beverage
DayCab
8
85B Transit C18 MP
Transit
Heavy
8
86B Transit C16-7 MP
School
Medium
7
87B Transit C18 U
Transit
Heavy
8
88B Transit C16-7 U
School
Medium
7
89T Utility C18 MP
Vocational
Heavy
8
90T Utility C18 R
Vocational
Heavy
8
91T Utility C16-7 MP
Vocational
Medium
7
92T Utility C16-7 R
Vocational
Medium
7
93T Utility C14-5 MP
Service
Medium
4
94T Utility C12b-3 MP
Van
Medium
3
95T Utility C14-5 R
Service
Medium
4
96T Utility C12b-3 R
Van
Medium
3
97T Utility C18 U
Vocational
Heavy
8
98T Utility C16-7 U
Vocational
Medium
7
99T Utility C14-5 U
Service
Medium
4
100T Utility C12b-3 U
Van
Medium
3
lOlTractor DC C18
Beverage
DayCab
8
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2.2 HD Vehicle Benchmark Characteristics
HD TRUCS is designed to evaluate future HD ZEVs that can meet the energy demands of
many different types of HD ICE vehicles. To accomplish this, we have "benchmarked" HD
vehicle activity and typical rates of energy consumption at the axle893 for a wide range of vehicle
applications, weight classes, and duty cycles. We also collected data that is used to assign new
vehicle sales distributions for all HD TRUCS vehicle types.
RIA Chapter 2.2.1 describes key vehicle activity metrics in HD TRUCS which includes
annual and daily vehicle miles traveled (VMT). Annual activity is primarily used for calculating
operational costs, and daily activity894 is important for sizing ZEV components.
RIA Chapter 2.2.2 describes the rate of energy consumption required of HD vehicles,
including the demand of power take off units (PTOs) and the recovered energy from regenerative
braking.
HD TRUCS also includes the sales distribution of new HD vehicles, so that each of the 101
vehicle types represented in HD TRUCS can be assigned a fraction of new vehicle sales. This
allows us to create sales-weighted adoption rates for consideration for the technology packages.
RIA Chapter 2.2.3 describes how the sales weighting distributions were estimated for each HD
TRUCS vehicle category.
2.2.1 HD Vehicle Activity
In RIA Chapter 2.2.1, we describe how we used time-related assumptions and VMT
considerations in HD TRUCS to establish performance benchmarks for HD ZEVs.
2.2.1.1 Time-Related Assumptions
2.2.1.1.1 Operating Days Per Year
In HD TRUCS, all vehicles, other than Recreational Vehicles (RVs), operate 250 days per
year.895 We are using 250 operating days per year based on 50 weeks of 5 working days. RVs,
however, are assumed to operate only 8 days per year (see Chapter RIA 2.2.1.2 for additional
explanation).
2.2.1.1.2 Operating Hours Per Day
In our HD TRUCS analysis, the vehicles operate for 8 hours a day. Daily operating hours are
used to calculate the amount of energy needed per day for heating, ventilation, and air
893 RIA Chapter 2.2 generally describes HD vehicle energy consumption rates that do not include powertrain-
specific losses and energy demands. The powertrain-specific diesel, BEV, and FCEV losses and demands are
described in RIA Chapters 2.3, 2.4, and 2.5, respectively.
894 While ICE vehicles may not require daily refueling, BEVs and FCEVs in HD TRUCS are assumed to re-charge
or refuel every day; therefore, we size ZEV components to meet the daily energy and/or power demand that is
needed to accommodate a day of work.
895 North American Council for Freight Efficiency (NACFE). "Electric Trucks Have Arrived: The Use Case for
Heavy-Duty Regional Haul Tractors—Run on Less Electric Report". May 5, 2022. Available online:
https://nacfe.org/wp-content/uploads/edd/2022/05/HD-Regional-Haul-Report-FINAL.pdf. NACFE used 250 days
per year for diesel and electric Class 8 tractors (regional haul) & vans and step vans.
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conditioning (HVAC) based on the vehicles' power demand for HVAC, as described in RIA
Chapters 2.4.1.1.1 through 2.4.1.1.3, and 2.5.1.2.2.
2.2.1.1.3 Year-by-Year Assessment
In the NPRM version of HD TRUCS, we used 10-year average values to assess operating
costs; this approach was improved upon for the final version of HD TRUCS. For the final
version for HD TRUCS, we have assessed each year of operation using the appropriate changes
that occur over time for inputs such as VMT, maintenance and repair, and fuel costs. We have
however, continued to show many 10-year average values in Chapter 2 of the RIA in order to
provide the reader with values that are comparable to the proposal and DRIA.896 Also, for values
such as maintenance and repair that increase with vehicle age, an average value may be more
informative, as a single value. This is discussed in greater detail in the VMT and operating costs
sections, RIA Chapters 2.2.1.2, 2.3.4, 2.4.4, and 2.5.3 and in the payback analysis section, RIA
Chapter 2.8.8, and Appendix A to this RIA shows VMT for each of the first ten years of
operation.
2.2.1.2 Vehicle Miles Traveled (VMT)
Vehicle miles traveled, or VMT, is one way to consider heavy-duty vehicle activity. In HD
TRUCS, VMT is used to determine the daily and yearly use or operation of a vehicle, to size
BEV battery packs, H2 storage tanks for FCEVs, and other components, and to estimate depot
infrastructure needs. We relied on multiple sources to determine the VMT applied in HD
TRUCS for each vehicle. The sources for daily VMT we considered were based on our
assessment of data availability. We have listed them in order of publication date, the level of
detail included in the data, and whether the data was collected from in-use vehicles: NREL's
FleetDNA897 database, a University of California, Riverside898 (UC-Riverside) database, the
Department of Transportation's Bureau of Transportation Statistic's 2002 Vehicle Inventory and
Use Survey899 (2002 VIUS), California Air Resource Board (CARB) Large Entity Reporting900,
or independent sources, as discussed below. Values included in HD TRUCS by vehicle type are
shown in Table 2-3.
2.2.1.2.1 Operational VMT
The 50th percentile daily VMT is used to estimate costs associated with operating HD
vehicles such as the annual fuel or electricity costs and maintenance and repair costs (see RIA
Chapters 2.3.4, 2.4.4, and 2.5.3). We used the 50th percentile daily VMT as a proxy for the
average amount of work done by a vehicle during a normal workday. For the final rule, we are
896 Please note that the DRIA was generally presented in 2021$, and the final RIA is generally shown in 2022$, and
the 2022 dollar basis is 7 percent higher than the 2021 dollar basis.
897 NREL. Fleet DNA: Commercial Fleet Vehicle Operating Data. Available online
https://www.nrel.gov/transportation/fleettest-fleet-dna.html
898 Zhang, Chen, Karen Ficenec, Andrew Kotz, Kenneth Kelly, Darrell Sonntag, Carl Fulper, Jessica Brakora,
Tiffany Mo, and Sudheer Ballare. 2021. Heavy-Duty Vehicle Activity Updates for MOVES Using NREL Fleet
DNA and CE-CERT Data. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5400-79509.
https://www.nrel.gov/docs/IV21osti/79509.pdf.
899 United States Census Bureau. 2002 Vehicle Inventory and Use Survey. Available online
https://www.census.gov/librarv/publications/2002/econ/census/vehicle-inventorv-and-use-survev.html.
900 CARB. Large Entity Fleet Reporting. Available online https://ww2.arb.ca.gov/sites/default/files/2022-
02/Large Entity Reporting Aggregated Data ADA.pdf.
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continuing this approach as proposed, as our assessment is that an operational VMT at the 50th
percentile is a conservative but reasonable means of evaluating payback. For VMT data sources
that only included annual VMT, we used the 250 days per year described above to calculate an
average daily VMT. We used the 50th percentile VMT to represent the daily VMT for vehicle
age at year 0, the first year of operation, in HD TRUCS. A typical HD vehicle's VMT changes
with age. See RIA Chapter 2.2.1.2.4 for the change in VMT we used in HD TRUCS.
2.2.1.2.2 Sizing VMT
A daily "Sizing VMT"901 value was used to calculate the storage capacity needs of a BEV
battery, number of BEV battery cycles, and the EVSE size requirements for depot-charged
BEVs, as well as onboard hydrogen storage capacity for the FCEVs. For the proposal, we
generally selected the 90th percentile VMT because we projected that manufacturers will design
their ZEVs to meet most daily VMT needs, but not the most extreme operations. For the
proposal, EPA's analysis assumed that all BEVs would be predominantly charged at a depot. For
example, ZEVs designed for 100th percentile daily VMT needs are likely unnecessarily heavy
and expensive for most operations, which may limit their appeal in the market. During the
timeframe covered in this analysis, we took into consideration that the vehicles that require daily
VMT greater than the 90th percentile could either be ICE powered or could also use en-route
public charging or hydrogen refueling during the day to meet their needs. In the proposal, the
90th percentile VMT was also referred to as the "sizing VMT."
EPA received comments about the 90th percentile VMT that was used in the proposal version
of HD TRUCS for sizing BEV batteries and FCEV hydrogen tanks.902 The American Council for
an Energy-Efficient Economy (ACEEE), Environmental Defense Fund (EDF), and California
Air Resource Board (CARB) all commented that the sizing VMT was too high as manufacturers
would provide multiple battery sizes for their vehicles to allow fleets to tailor the battery sizes to
their routes and daily VMT rather than purchase a battery larger than they require which would
negatively affect payload and the cost of the vehicle. Some commenters stated that the 90th
percentile VMT was too low. Daimler Truck North America (DTNA) commented that the sizing
VMT was too low and disputed both the choice of a 90th percentile and the mileage estimate of
that 90th percentile, submitting 90th percentile data on day cabs and sleeper cabs, based on
telematic data collected over 18 days in May of 2023, that showed higher 90th percentile daily
VMT than the HD TRUCS proposal estimates for the 90th percentile daily VMT for long range
sleeper and day cabs. POET commented that customers would not purchase vehicles with a
range significantly lower than 100 miles.
Our assessment is that 1) the 90th percentile approach will cover the majority of fleet
operations where fleets are using daily depot charging, 2) battery sizes to meet shorter daily
VMTs (i.e. using a lower sizing VMT) would mean that these depot charged BEVs would be
unavailable for some market segments in our analysis, and 3) battery sizes to meet longer daily
VMTs (that is, using a sizing VMT greater than our 90th percentile) would be unnecessarily large
for many applications where fleets are using daily depot charging. Thus, we disagree that fleets
will not purchase a once per day depot charging BEV that can fulfill the 90th percentile of daily
901 Sizing VMT is an important part of calculating the overall storage capacity of a BEV's battery or a FCEV's
hydrogen tank size in HD TRUCS, but there are also other factors that add battery capacity and increase hydrogen
tank size. Those factors are described in RIA Chapters 2.4.1.1.3 and 2.5.1.2.
902 See RTC Section 3.3.1 for more information about comments received on this topic.
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use cases. However, as a conservative cost assumption, and in response to comment that
purchasers may avoid purchasing vehicles with a sizing range below 100 miles, we are adding an
additional constraint for minimum battery sizing, such that no vehicle in HD TRUCS is designed
for less than 100 miles of range, i.e., any vehicle with 90th percentile VMT of less than 100 miles
in our analysis has been assigned a sizing VMT of 100 miles. 903
After consideration of comment, we updated our approach in this final rule in recognition that
in some instances, notably when public charging is an option, maintaining sizing at the 90th
percentile could lead to unnecessary expense (as these vehicles would have larger batteries than
required to meet the majority of fleet needs) and may create potential payload impacts
unnecessarily, which could lead some fleets to not purchase such vehicles. We thus agree with
commenters who noted that if the 90th percentile VMT yields a battery that may negatively affect
payload and adds unnecessary cost, then public charging may be the preferred option.
For the final rule, we sized batteries in BEVs that we expect to be charged en route using
public charging starting in MY 2030 at the 50th percentile daily VMT.904 For the longest range
day cabs and sleeper cabs, on days when these vehicles are required to travel longer distances,
we find that less than 30 minutes of mid-day charging at 1 MW is sufficient to meet the HD
TRUCS 90th percentile VMT905 assuming vehicles start the day with a full battery.906 The MY
2030-MY 2032 vehicles that are expected to charge publicly, have a higher charging cost
assigned to their operating cost calculations (see RIA Chapter 2.4.4.2) and do not include an
EVSE as part of their up-front purchase costs because they are expected to use public charging.
Similarly, the FCEV tractor with the longest range is also sized at the 50th percentile VMT to
ensure that there is room for packaging of the hydrogen tanks and because we expect they can
refuel once mid-route per day. For the final rule, we assigned all BEV sleeper cabs and long
range day cab tractors to use public charging, rather than depot charging. The ability to charge
publicly means that the batteries of long-range vehicles can be sized more appropriately for
typical use. Therefore, we sized the batteries such that their range is equal to the 50th percentile
VMT (i.e., the average daily operating VMT) at year zero.907 This does not mean that BEV
tractors in our HD TRUCS analysis cannot drive a higher percentile daily VMT; it just means
that they would have to stop and charge in order to cover a longer distance day.
903 See the next section and RIA Chapter 2.9.1 discussing applications for which certain HD TRUCS representative
vehicles were modified for the final rule in ways that also increased the battery sizing assumptions and/or limited
projected utilization of ZEV technologies in our modeled compliance pathway, and further discussing why EPA
regards these modifications as reasonably conservative.
904 The publicly-charged coach bus, 17B_Coach_C18_R, and the FCEV coach bus, 18B_Coach_C18_MP, however,
are sized to the 90th percentile as described below.
905 The HD TRUCS 90th percentile for the long-range publicly-charged BEV or FCEV day cab and sleeper cab
vehicles are as follows: 32Tractor_SC_C18, 54Tractor_SC_C18, and 79Tractor_SC_C18 have a 571 mile 90th
percentile VMT; 33Tractor_DC_C18, 81Tractor_DC_C17, and 82Tractor_DC_C18 have a 349 mile 90th percentile
VMT. Note that the long-range sleeper cab 90th percentile VMT has been updated from the proposal estimate of 550
miles to 571 miles. Long-range sleeper cabs were assigned a 571 mile 90th percentile value to match the 90th
percentile of the UC Riverside data for their Class 8 long haul tractor.
906 See RIA Chapter 2.6.3 for more information on 2C or 1 MW charging times for publicly-charged vehicle types.
907 The "50th percentile VMT at Year 0" means the 50th percentile daily VMT when the vehicle is new. This
specification is needed for clarity, because operational VMT decreases as vehicles age.
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See the next section (RIA Chapter 2.2.1.2.3) for more information about EPA's analysis for
sizing publicly charged BEVs and long-range sleeper cab FCEVs.908
Concerning the 90th percentile VMT value, DTNA submitted 90th percentile data on day cabs
and sleeper cabs, based on telematic data collected over 18 days in May of 2023, that showed
higher 90th percentile daily VMT than the HD TRUCS proposal estimates for the 90th percentile
daily VMT for long range sleeper and day cabs. As DTNA points out, building batteries to meet
the 90th percentile of the data they presented would increase upfront costs and have greater
payload impacts than EPA had projected for these vehicles. We did not use these data to
calculate the 90th percentile sizing VMT. We discuss the data we did use in the following
section, but note here that we regard these data as more representative than DTNA's because the
data sets are for periods considerably longer than several weeks. Moreover, DTNA's comment
was (properly) directed at EPA's assumption at proposal that all BEVs would be depot charged
and was designed to show that depot charging would be inadequate for certain longer haul tractor
types. As noted above, we agree. As stated above, and as explained in detail in the following
Chapter 2.2.1.2.3, we project that public charging is available for certain day and sleeper cab
tractors, therefore we assigned a 50th percentile sizing VMT for such vehicles. For the long range
tractors, the sizing VMT is generally consistent with the DTNA telematics data — i.e. that the
sizing VMT with one additional en-route charge or hydrogen re-fuel is similar to the 90th
percentile of the DTNA telematics data.909 For example, the long range publicly-charged BEV
sleeper cabs have a sizing (and operational) VMT of 420 miles; therefore, a mid-route charge
will generally allow the driver to exceed the 90th percentile data submitted by DTNA at 724
miles. 910 The long range fuel cell vehicles have a sizing VMT of 349 miles, and could therefore
travel beyond DTNA's 90th percentile data for day cabs with one hydrogen re-fuel.
2.2.1.2.3 VMT Data Sources and Final Rule Updates
For values available in the NREL and UC-Riverside databases, EPA assigned each vehicle a
50th percentile daily VMT and a 90th percentile daily VMT.911 As described above, the 50th
percentile VMT is used to calculate "operational VMT," as described in RIA Chapter 2.2.1.2.1.
The 90th percentile VMT is generally used for "sizing VMT" for vehicles that are expected to
use depot charging, with a few exceptions just noted above for ZEVs that are expected to charge
using public charging or which may refuel once mid-route per day with hydrogen and which
instead use the 50th percentile VMT (at year 0) for sizing, as described in RIA Chapter 2.2.1.2.2.
Not all vehicle applications were reflected in the NREL or UC-Riverside databases. In these
instances, we used 2002 VIUS data. This data was reported as yearly VMT, which we divided by
the assumed 250 operating days per year to estimate the 50th percentile daily VMT. We then
applied factors to the VIUS 50th percentile daily VMT to estimate the 90th percentile daily VMT
908 Moreover, under our modeled potential compliance pathway, ICE vehicles are available to accommodate
applications requiring extremes of sizing VMT.
909 See Comments from Daimler Trucks North America. Docket # EPA-HQ-OAR-2022-0985-1555-A1. Page 23.
910 Designing for a VMT of 420 miles allows the required size tanks to package behind the sleeper cab with a
standard wheelbase length. This is further explained in Chapter 2.9.1.2.
911 If data existed in both the Fleet DNA database and the UC Riverside database, we typically averaged the two
values.
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for vehicles.912 In our final analysis, all factors applied to the VIUS data are unchanged from the
NPRM factors. (Note, however, that some vehicle types that have been updated to a 100 mile
minimum sizing VMT as described in Chapter 2.2.1.2.2).913
For the vehicle applications where VMT was not included in the NREL, UC-Riverside, or
2002 VIUS databases, we relied on consideration of independent sources or comments received
to estimate daily VMT. For coach buses, we have increased the FCEV coach bus sizing VMT to
450 miles, based on consideration of comments received from motor coach companies about
typical daily VMT during multi-day trips. For the BEV coach bus that is expected to be charged
publicly, we have increased the sizing VMT to 300 miles. This value reflects the fact that there
are existing BEV coach buses with an advertised range of 125914-240915 miles but also considers
that as utilization of ZEV technologies increase for coach buses, the demand for longer range
between charging events will also increase.916 For coach bus operational VMT, we have
continued to use annual VMT from motorcoach census data for 2017, divided by 250 operational
days.917 See RTC 2.2.1 for comments received from the motor coach industry and our responses.
For RVs, we used average yearly VMT from a 2009 Federal Highway Administration survey,918
divided by the average number of camping trips per year from a Coleman Company, Inc.
report,919 and multiplied by two (for two driving days per camping trip). For school buses and
shuttle buses, we used DOE's Alternative Fuels Data Center (AFDC) information for Average
Annual Vehicle Miles Traveled by Major Vehicle Category.920
For the final version of HD TRUCS, we corrected the 50th and 90th percentile VMT formulas
for six vehicles to address errors that were raised in comments. EPA made additional changes
after consideration of comments. These include the following and are described in more detail in
this section: the sizing VMT was increased for some utility vehicles and all snow plows. As
noted earlier, for BEV tractors that are projected to charge publicly (32Tractor_SC_C18,
33Tractor DC Cl8, 54Tractor_SC_C18, 78Tractor_SC_C18, 81Tractor_DC_C17 ,
82Tractor_DC_C18, 84Tractor_DC_C18), and the FCEV sleeper cab (79Tractor_SC_C18) were
sized such that their sizing VMT is equal to their operating VMT at year 0.
912 See Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. "Estimating 90th Percentile VMT for
Vehicles using 2002 VIUS Data". October 2023. Document ID: EPA-HQ-OAR-2022-0985-1044.
913 See Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. "Estimating 90th Percentile VMT for
Vehicles using 2002 VIUS Data". October 2023. Document ID: EPA-HQ-OAR-2022-0985-1044.
914 BYD. C8MS. Available online: https://en.byd.com/bus/bus-c8ms/
915 Motor Coach Industries. J4500 Charge. Available online: https://www.mcicoach.com/site-
content/uploads/2023/12/MCI-J4500-CHARGE%E2%84%A2-brochure.pdf
916 See RIA Chapter 2.9.1 for a discussion about the potential for ZEV packaging impacts on coach bus luggage
space and EPA's commensurate limit on utilization of ZEV technologies for coach buses in HD TRUCS.
917 American Bus Association Foundation. "Motorcoach Census: A Study of the Size and Activity of the
Motorcoach Industry in the United States and Canada in 2017". June 5, 2019. Available online:
https://www.buses.org/assets/images/uploads/pdf/FINAL 2017 Census l.pdf.
918 Federal Highway Administration. 2009 National Household Travel Survey: Average Annual Vehicle Miles of
Travel Per Vehicle (Best Estimate) By Vehicle Age and Type. Available online:
https://nhts.ornl.gov/tablesQ9/fatcat/2009/best VEHAGE VEHTYPE.html.
919 Coleman Company, Inc., and the Outdoor Foundation. "2016 American Camper Report". Available online:
https://outdoorindustrv.org/wp-content/uploads/2017/05/2016-Camper-Report FINAL.pdf.
920 U.S. Department of Energy, Alternative Fuels Data Center. "Average Annual Vehicle Miles Traveled by Major
Vehicle Category". Last updated, February 2020; printed October 19, 2022. Available online:
https://afdc.energy.gov/data/widgets/10309.
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The sizing VMT for all snow plows including 60S_Plow_C16-7_MP, 61S_Plow_C18_MP,
62S_Plow_C16-7_U, 63S_Plow_C18_U and the Class 8 regional utility vehicle
90T_Utility_C18_R has been increased. This was done after consideration of comments that
snow plows may need to operate for longer periods of time during adverse winter weather
conditions. For the proposal, we had assumed that snow plows were a unique vehicle, but for the
final rule, we have determined that snow plows are off season dump trucks in parts of the
country that experience harsh winter weather. We therefore increased the sizing VMT of snow
plows to match the sizing VMT of dump trucks.921 After consideration of comments that raised
concerns about the sizing VMT of utility trucks being used in prolonged power-outage situations,
we have increased the sizing VMT to the maximum recorded value in the NREL Fleet DNA
database for the Class 8 regional utility vehicles. We have also limited consideration of the
utilization of ZEV technologies for all regional utility vehicles (of all weight classes) to 0 percent
in MY 2027 and 14 percent in MY 2032, as described in RIA Chapter 2.9.1.
As noted above, we now are projecting that all BEV sleeper cabs would charge publicly,
rather than at depots, and we set the sizing VMT equal to the daily operating VMT at year 0. In
addition, we divided the sleeper cab tractors into four configurations to represent several sizing
and technology approaches. For the sleeper cab tractors with the longest daily operating range,
32Tractor_SC_C18, 54Tractor_SC_C18, and 79Tractor_SC_C18, we used MOVES data to set the
50th percentile operational VMT at 420 miles.922 Sleeper cab, 78Tractor_SC_C18, represents
sleeper cabs with a shorter operating range. For the proposal, this vehicle had a 200 mile daily
operating range; however, for the final rule, we updated this tractor to a 300 mile operating
range. Based on CARB's "Large Entity Fleet Reporting,"923 we used a sales volume share for
the sleeper cab with a shorter range that is consistent with the sum of the percent of total sleeper
cabs that have an estimated daily mileage up to 300 miles, totaling to a 28 percent sales share.
There was one comment related to packaging space availability associated with FCEVs. One
industry commenter stated they believe liquid hydrogen is required to meet the packaging
requirement for vehicles with a 500-mile range. We did not include onboard liquid hydrogen
storage tanks in the final rule due to low technology maturity and our assessment is that there is
adequate space for onboard compressed gaseous hydrogen tanks for the FCEVs that we modeled.
We contracted FEV to independently conduct a packaging analysis for Class 8 long-haul tractors
in support of the rule, and then we conducted an external peer review of the final FEV report.
FEV found ways to package a tractor with six onboard gaseous hydrogen tanks plus a sleeper cab
that is able to travel up to 500 miles.924 Therefore, for the FCEV sleeper cab, 79Tractor_SC_C18,
we set the sizing VMT equal to the daily operating VMT of 420 miles to ensure that packaging is
possible. This does not mean the FCEV tractors in our HD TRUCS analysis cannot travel further
than 420 miles in a day; it just means they would have to stop to refuel to travel a longer
distance. Furthermore, manufacturers could design tractors to hold additional hydrogen tank
921 Pennsylvania DOT. "What do you really know about snowplows?". February 2021. Available online:
https://www.penndot.pa.gov/PennDOTWay/pages/Article.aspx?post=396
922 As noted in Chapter 0, and further described in Chapter 2.2.2.1, one of the long range publicly-charged BEV
sleeper cabs, 32Tractor_SC_C18, was updated to reflect a lower coefficient of aerodynamic drag.
923 California Air Resources Board. "Large Entity Fleet Reporting: Statewide Aggregated Data." Reported in 2021
on 2019 fleet data. Available online: https://ww2.arb.ca.gov/sites/default/files/2022-
02/Large Entity Reporting Aggregated Data ADA.pdf.
924 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
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capacity and achieve even longer distances than we modeled for the final rule. Other factors that
affect battery sizing for BEVs and hydrogen tank sizing for FCEVs are discussed in RIA
Chapters 2.4.1.1.3 and 2.5.1.2.
The day cab tractors in the final rule HD TRUCS analysis are also divided into several
operational distances, technology approaches, and charging strategies. Similar to the proposal,
we relied on the Fleet DNA and UC Riverside data to establish a short-range day cabs (97 miles
of daily operational VMT), mid-range day cabs (120 miles of daily operational VMT), and long-
range day cabs (216 miles of daily operational VMT); however, for the final rule, we ensured
that there were medium heavy-duty and heavy heavy-duty tractors represented for each range
category. The short-range day cabs, 30Tractor_DC_C18 and 31Tractor_DC_C16-7, are depot
charged and have a 90th percentile sizing VMT. The medium heavy-duty mid-range day cab,
83Tractor_DC_C17, is depot charged and uses the 90th percentile sizing VMT, and the heavy
heavy-duty mid-range day cab, 84Tractor_DC_C18, is assumed to be charged publicly, starting
in model year 2030, and uses the 50th percentile VMT for sizing, consistent with the other en-
route charging tractors. There are five long-range day cabs. The long-range medium heavy-duty
and heavy heavy-duty fuel cell vehicles, 41Tractor_DC_C17 and 45Tractor_DC_C18 both use the
90th percentile VMT for sizing. These fuel cell day cab tractors can accommodate the hydrogen
tanks required for 90th percentile VMT. There are also both medium heavy-duty and heavy
heavy-duty BEV long-range day cab tractors, 33Tractor_DC_C18,925 81Tractor_DC_C17, and
82Tractor_DC_C18 that rely on public charging in our analysis, starting in model year 2030;
consistent with all en-route charging sleeper cabs, these tractors have a daily sizing VMT that is
equal to the operating VMT.
The heavy-haul tractor, 80Tractor_DC_C18_HH, is unchanged from the proposal in that we
continue to rely on FleetDNA data for operational VMT (50th percentile) and sizing VMT (90th
percentile).
Table 2-3 lists the operational VMT for vehicles when they are new and the sizing VMT,
along with the data source for these values for each of the 101 vehicles in HD TRUCS.
Table 2-3 Operational and Sizing VMT926 in HD TRUCS
Vehicle ID
Refueling Location
VMT Source
Operational VMT
for year 1 of
Operation (mi/day)
Sizing
VMT
(mi/day)
01V Amb C14-5 MP
Depot
FleetDNA & UCR
34
100
02V Amb C12b-3 MP
Depot
FleetDNA & UCR
49
100
03V Amb C14-5 U
Depot
FleetDNA
39
100
04V Amb C12b-3 U
Depot
FleetDNA
40
100
05T Box C18 MP
Depot
2002 VIUS
66
100
06T Box C18 R
Depot
2002 VIUS
66
100
07T Box C16-7 MP
Depot
FleetDNA & UCR
40
100
08T Box C16-7 R
Depot
FleetDNA & UCR
40
100
09T Box C18 U
Depot
2002 VIUS
66
100
925 Similar to sleeper cab, 32Tractor_SC_C18, the day cab, 33Tractor_DC_C18, was updated to reflect a lower
coefficient of aerodynamic drag. For more details, see RIA Chapter 2.2.2.1.
926 The Operational VMT, shown in Table 2 2, are the daily miles that are assumed for the first year of new vehicle
ownership, as operational VMT changes over time (see RIA Chapter 2.2.1.2.4). See Appendix A to this RIA for a
10-year schedule of operational VMT.
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Vehicle ID
Refueling Location
VMT Source
Operational VMT
for year 1 of
Operation (mi/day)
Sizing
VMT
(mi/day)
10T Box C16-7 U
Depot
FleetDNA
39
105
11T Box C12b-3 U
Depot
FleetDNA & UCR
59
100
12T Box C12b-3 R
Depot
FleetDNA & UCR
59
100
13T Box C12b-3 MP
Depot
FleetDNA & UCR
59
100
14T Box C14-5 U
Depot
FleetDNA & UCR
38
100
15T Box C14-5 R
Depot
FleetDNA & UCR
38
100
16T Box C14-5 MP
Depot
FleetDNA & UCR
38
100
17B Coach C18 R
Public
Independent
158
300
18B Coach C18 MP
H2 Station
Independent
158
450
19C Mix C18 MP
Depot
NRELUCR
89
100
20T Dump C18 U
Depot
2002 VIUS
40
111
2IT Dump C18 MP
Depot
2002 VIUS
40
111
22T Dump C16-7 MP
Depot
FleetDNA & UCR
56
156
23T Dump C18 U
Depot
2002 VIUS
40
111
24T Dump C16-7 U
Depot
FleetDNA & UCR
56
156
25T Fire C18 MP
Depot
2002 VIUS
40
111
26T Fire C18 U
Depot
2002 VIUS
40
111
27T Flat C16-7 MP
Depot
FleetDNA & UCR
40
100
28T Flat C16-7 R
Depot
FleetDNA & UCR
40
100
29T Flat C16-7 U
Depot
FleetDNA & UCR
40
100
30Tractor DC C18
Depot
FleetDNA & UCR
97
136
31Tractor DC C17
Depot
FleetDNA & UCR
97
147
32Tractor SC C18
Public
Independent
420
420
33Tractor DC C18
Public
FleetDNA
216
216
34T Ref C18 MP
Depot
FleetDNA & UCR
52
118
35T Ref C16-7 MP
Depot
2002 VIUS
94
118
36T Ref C18 U
Depot
FleetDNA & UCR
52
118
37T Ref C16-7 U
Depot
2002 VIUS
94
118
38RV C18 R
Depot
Independent
335
335
39RV C16-7 R
Depot
Independent
335
335
40RV C14-5 R
Depot
Independent
335
335
41Tractor DC C17
H2 Station
FleetDNA & UCR
216
349
42RV C18 MP
Depot
Independent
335
335
43RV C16-7 MP
Depot
Independent
335
335
44RV C14-5 MP
Depot
Independent
335
335
45Tractor DC C18
H2 Station
FleetDNA & UCR
216
349
46B School C18 MP
Depot
Independent
48
100
47B School C16-7 MP
Depot
FleetDNA & UCR
51
100
48B School C14-5 MP
Depot
Independent
48
100
49B School C12b-3 MP
Depot
Independent
48
100
5OB School C18 U
Depot
Independent
48
100
5 IB School C16-7 U
Depot
FleetDNA & UCR
51
100
52B School C14-5 U
Depot
Independent
48
100
53B School C12b-3 U
Depot
Independent
48
100
54Tractor SC C18
Public
Independent
420
420
55B Shuttle C12b-3 MP
Depot
Independent
118
150
56B Shuttle C14-5 U
Depot
Independent
118
150
57B Shuttle C12b-3 U
Depot
Independent
118
150
58B Shuttle C16-7 MP
Depot
Independent
118
150
59B Shuttle C16-7 U
Depot
Independent
118
150
60S Plow C16-7 MP
Depot
NRELUCR
40
111
194
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Vehicle ID
Refueling Location
VMT Source
Operational VMT
for year 1 of
Operation (mi/day)
Sizing
VMT
(mi/day)
61S Plow C18 MP
Depot
NRELUCR
44
156
62S Plow C16-7 U
Depot
NRELUCR
40
111
63 S Plow C18 U
Depot
NRELUCR
44
156
64V Step C16-7 MP
Depot
FleetDNA
61
101
65V Step C14-5 MP
Depot
FleetDNA & UCR
38
100
66V Step C12b-3 MP
Depot
FleetDNA & UCR
59
100
67V Step C16-7 U
Depot
FleetDNA
61
101
68V Step C14-5 U
Depot
FleetDNA & UCR
38
100
69V Step C12b-3 U
Depot
FleetDNA & UCR
59
100
70S Sweep C16-7 U
Depot
2002 VIUS
50
100
7IT Tanker C18 R
Depot
2002 VIUS
52
100
72T Tanker C18 MP
Depot
2002 VIUS
52
100
73T Tanker C18 U
Depot
2002 VIUS
52
100
74T Tow C18 R
Depot
2002 VIUS
64
157
75T Tow C16-7 R
Depot
FleetDNA & UCR
56
157
76T Tow C18 U
Depot
2002 VIUS
64
157
77T Tow C16-7 U
Depot
FleetDNA & UCR
56
157
78Tractor SC C18
Public
Independent
300
300
79Tractor SC C18
H2 Station
Independent
420
420
80Tractor DC C18
Depot
Independent
106
180
81Tractor DC C17
Public
FleetDNA & UCR
216
216
82Tractor DC C18
Public
FleetDNA & UCR
216
216
83Tractor DC C17
Depot
FleetDNA
120
214
84Tractor DC C18
Public
Independent
120
120
85B Transit C18 MP
Depot
FleetDNA
136
203
86B Transit C16-7 MP
Depot
FleetDNA
80
219
87B Transit C18 U
Depot
FleetDNA
136
203
88B Transit C16-7 U
Depot
FleetDNA
80
219
89T Utility C18 MP
Depot
FleetDNA & UCR
27
100
90T Utility C18 R
Depot
FleetDNA & UCR
27
100
9IT Utility C16-7 MP
Depot
2002 VIUS
49
100
92T Utility C16-7 R
Depot
2002 VIUS
49
100
93T Utility C14-5 MP
Depot
2002 VIUS
49
100
94T Utility C12b-3 MP
Depot
FleetDNA
23
100
95T Utility C14-5 R
Depot
2002 VIUS
49
100
96T Utility C12b-3 R
Depot
2002 VIUS
49
100
97T Utility C18 U
Depot
FleetDNA
27
100
98T Utility C16-7 U
Depot
2002 VIUS
49
100
99T Utility C14-5 U
Depot
2002 VIUS
49
100
100T Utility C12b-3 U
Depot
FleetDNA
23
100
lOlTractor DC C18
Depot
FleetDNA
60
127
2.2.1.2.4 Vehicle Age Impact on VMT
The VMT of HD vehicles varies with the age of the vehicle. Typically, newer vehicles are
driven more, while older vehicles are driven less. In the NPRM, two schedules were applied to
all vehicles, one for vocational vehicles and one for tractors. For the FRM, we aligned the rate of
change in VMT in HD TRUCS with those in MOVES which allows for additional
disaggregation using the MOVES sourceType ID. There are nine different VMT schedules
195
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applied in HD TRUCS for each of the MOVES source types as shown in Table 2-4 and Figure
2-1.927 The factors are applied to the operational VMT which is assumed to be the operational
VMT for vehicle age at year 0.
Table 2-4 Relative Change in VMT to Vehicle Age of Year 0 for each MOVES Source Type ID
sourceType
ID
sourceType Name
Vehicle Age (Year)
0
1
2
3
4
5
6
7
8
9
41
Other Buses
1.00
0.97
0.94
0.91
0.88
0.85
0.82
0.80
0.77
0.75
42
Transit Bus
1.00
0.97
0.94
0.91
0.88
0.85
0.82
0.80
0.77
0.75
43
School Bus
1.00
0.97
0.94
0.91
0.88
0.85
0.82
0.80
0.77
0.75
51
Refuse Truck
1.00
1.00
1.00
1.00
0.96
0.91
0.87
0.82
0.78
0.73
52
Single Unit Short-haul Truck
1.00
1.00
1.00
1.00
0.95
0.90
0.83
0.78
0.73
0.69
53
Single Unit Long-haul Truck
1.00
1.00
1.00
1.00
0.95
0.88
0.81
0.74
0.69
0.64
54
Motor Home
1.00
1.00
1.00
1.00
1.00
0.99
0.97
0.95
0.95
0.93
61
Combination Short-haul Truck
1.00
1.00
1.00
1.00
0.93
0.87
0.80
0.73
0.67
0.60
62
Combination Long-haul Truck
1.00
1.00
1.00
1.00
0.95
0.89
0.84
0.79
0.74
0.68
1.2
>
c
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2.2.2 HD Vehicle Energy Consumption
In this section, we describe how we evaluated HD vehicle energy consumption requirements,
independent of the powertrain, to better understand how ZEVs could be designed to meet
technical performance requirements.
For each HD TRUCS vehicle type, we determined the baseline energy consumption
requirement that will be needed for ZEVs. We used EPA's GEM model to simulate road load
power requirements for various duty cycles using the default road load profiles to estimate work
performed by HD vehicles (as described in more detail in RIA Chapter 2.2.2.1.1). ZEV baseline
energy includes the energy at the vehicle axle required to move the vehicle down the road (as
described in more detail in RIA Chapter 2.2.2.1.2), the impact of regenerative braking928 (as
described in more detail below in RIA Chapter 2.2.2.1.3), and PTO energy (as described in more
detail in RIA Chapter 2.2.2.1.4). The resulting ZEV baseline energy requirements are shown in
Table 2-5 for each of the HD TRUCS vehicle types.
Other factors can impact energy consumption and power in a manner that may be different
among ICE vehicles, BEVs, and FCEVs. The energy demand for heating, ventilation, and air
conditioning (HVAC) is discussed in RIA Chapter 2.2.2.2. Additional powertrain-specific
impacts on energy consumption and power are described in RIA Chapters 2.3.3, 2.4.1.1, and
2.5.1.2.
Table 2-5 Energy Requirements of HDVs
Vehicle ID
ZEV Baseline Energy Requirements
Axle (kWh/mi)
Regen Braking
(kWh/mi)
PTO (kWh/mi)
ZEV Baseline
Energy (kWh/mi)
01V Amb C14-5 MP
0.86
-0.08
0.00
0.78
02V Amb C12b-3 MP
0.86
-0.08
0.00
0.78
03V Amb C14-5 U
0.82
-0.13
0.00
0.68
04V Amb C12b-3 U
0.82
-0.13
0.00
0.68
05T Box C18 MP
2.07
-0.23
0.00
1.84
06T Box C18 R
2.07
-0.09
0.00
1.97
07T Box C16-7 MP
1.36
-0.14
0.00
1.23
08T Box C16-7 R
1.45
-0.06
0.00
1.39
09T Box C18 U
2.07
-0.37
0.00
1.70
10T Box C16-7 U
1.31
-0.22
0.00
1.09
11T Box C12b-3 U
0.82
-0.13
0.00
0.68
12T Box C12b-3 R
0.91
-0.03
0.00
0.88
13T Box C12b-3 MP
0.86
-0.08
0.00
0.78
14T Box C14-5 U
0.82
-0.13
0.00
0.68
15T Box C14-5 R
0.91
-0.03
0.00
0.88
16T Box C14-5 MP
0.86
-0.08
0.00
0.78
17B Coach C18 R
1.91
-0.09
0.00
1.82
18B Coach C18 MP
1.91
-0.09
0.00
1.82
19C Mix C18 MP
2.02
-0.36
1.48
3.14
20T Dump C18 U
2.07
-0.37
0.14
1.84
2IT Dump C18 MP
2.07
-0.23
0.11
1.95
928 Regenerative braking is the process of slowing down a moving vehicle by using the vehicle's electric motor as a
brake. This process allows the vehicle's electric motor to generate electricity which is then stored in the vehicle's
battery and increases the net efficiency of the vehicle.
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Vehicle ID
ZEV Baseline Energy Requirements
Axle (kWh/mi)
Regen Braking
(kWh/mi)
PTO (kWh/mi)
ZEV Baseline
Energy (kWh/mi)
22T Dump C16-7 MP
1.36
-0.14
0.09
1.32
23T Dump C18 U
2.07
-0.37
0.14
1.84
24T Dump C16-7 U
1.31
-0.22
0.10
1.19
25T Fire C18 MP
2.07
-0.23
0.22
2.06
26T Fire C18 U
2.07
-0.37
0.27
1.96
27T Flat C16-7 MP
1.36
-0.14
0.00
1.23
28T Flat C16-7 R
1.45
-0.06
0.00
1.39
29T Flat C16-7 U
1.31
-0.22
0.00
1.09
30Tractor DC C18
2.18
-0.15
0.00
2.03
31Tractor DC C17
1.80
-0.11
0.00
1.69
32Tractor SC C18
1.74
-0.10
0.00
1.63
33Tractor DC C18
1.86
-0.17
0.00
1.69
34T Ref C18 MP
2.01
-0.36
0.54
2.19
35T Ref C16-7 MP
1.35
-0.14
0.61
1.83
36T Ref C18 U
2.01
-0.36
0.54
2.19
37T Ref C16-7 U
1.28
-0.22
0.67
1.74
38RV C18 R
1.36
-0.05
0.00
1.31
39RV C16-7 R
1.45
-0.06
0.00
1.39
40RV C14-5 R
0.91
-0.03
0.00
0.88
41Tractor DC C17
1.80
-0.11
0.00
1.69
42RV C18 MP
1.36
-0.05
0.00
1.31
43RV C16-7 MP
1.36
-0.14
0.00
1.23
44RV C14-5 MP
0.86
-0.08
0.00
0.78
45Tractor DC C18
2.18
-0.15
0.00
2.03
46B School C18 MP
2.07
-0.23
0.00
1.84
47B School C16-7 MP
1.22
-0.21
0.00
1.02
48B School C14-5 MP
0.86
-0.08
0.00
0.78
49B School C12b-3 MP
0.86
-0.08
0.00
0.78
5OB School C18 U
2.07
-0.37
0.00
1.70
5 IB School C16-7 U
1.22
-0.21
0.00
1.02
52B School C14-5 U
0.82
-0.13
0.00
0.68
53B School C12b-3 U
0.82
-0.13
0.00
0.68
54Tractor SC C18
2.05
-0.09
0.00
1.96
55B Shuttle C12b-3 MP
0.86
-0.08
0.00
0.78
56B Shuttle C14-5 U
0.82
-0.13
0.00
0.68
57B Shuttle C12b-3 U
0.82
-0.13
0.00
0.68
58B Shuttle C16-7 MP
1.36
-0.14
0.00
1.23
59B Shuttle C16-7 U
1.31
-0.22
0.00
1.09
60S Plow C16-7 MP
1.36
-0.14
0.09
1.32
61S Plow C18 MP
2.07
-0.23
0.09
1.93
62S Plow C16-7 U
1.31
-0.22
0.10
1.19
63 S Plow C18 U
2.07
-0.37
0.11
1.81
64V Step C16-7 MP
1.36
-0.14
0.00
1.23
65V Step C14-5 MP
0.86
-0.08
0.00
0.78
66V Step C12b-3 MP
0.86
-0.08
0.00
0.78
67V Step C16-7 U
1.31
-0.22
0.00
1.09
68V Step C14-5 U
0.82
-0.13
0.00
0.68
69V Step C12b-3 U
0.82
-0.13
0.00
0.68
70S Sweep C16-7 U
1.31
-0.22
0.20
1.29
7IT Tanker C18 R
2.07
-0.09
0.14
2.12
72T Tanker C18 MP
2.07
-0.23
0.16
2.00
198
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Vehicle ID
ZEV Baseline Energy Requirements
Axle (kWh/mi)
Regen Braking
(kWh/mi)
PTO (kWh/mi)
ZEV Baseline
Energy (kWh/mi)
73T Tanker C18 U
2.07
-0.37
0.20
1.90
74T Tow C18 R
2.07
-0.09
0.12
2.09
75T Tow C16-7 R
1.45
-0.06
0.09
1.48
76T Tow C18 U
2.07
-0.37
0.16
1.86
77T Tow C16-7 U
1.31
-0.22
0.10
1.19
78Tractor SC C18
2.05
-0.09
0.00
1.96
79Tractor SC C18
2.05
-0.09
0.00
1.96
80Tractor DC C18
3.12
-0.26
0.00
2.86
81Tractor DC C17
1.80
-0.11
0.00
1.69
82Tractor DC C18
2.18
-0.15
0.00
2.03
83Tractor DC C17
1.80
-0.11
0.00
1.69
84Tractor DC C18
2.18
-0.15
0.00
2.03
85B Transit C18 MP
1.99
-0.36
0.00
1.63
86B Transit C16-7 MP
1.35
-0.14
0.00
1.21
87B Transit C18 U
1.99
-0.36
0.00
1.63
88B Transit C16-7 U
1.28
-0.22
0.00
1.06
89T Utility C18 MP
2.07
-0.23
0.08
1.93
90T Utility C18 R
2.07
-0.09
0.07
2.05
9IT Utility C16-7 MP
1.36
-0.14
0.12
1.35
92T Utility C16-7 R
1.45
-0.06
0.12
1.51
93T Utility C14-5 MP
0.86
-0.08
0.09
0.86
94T Utility C12b-3 MP
0.86
-0.08
0.04
0.82
95T Utility C14-5 R
0.91
-0.03
0.08
0.96
96T Utility C12b-3 R
0.91
-0.03
0.08
0.96
97T Utility C18 U
2.07
-0.37
0.11
1.80
98T Utility C16-7 U
1.31
-0.22
0.14
1.22
99T Utility C14-5 U
0.82
-0.13
0.10
0.78
100T Utility C12b-3 U
0.82
-0.13
0.04
0.73
lOlTractor DC C18
2.18
-0.15
0.00
2.03
2.2.2.1 ZEV Baseline Energy Consumption
ZEV baseline energy is the minimum energy required for the HD vehicle to perform its
required work. Here, ZEV baseline energy includes the energy at the axle required to move the
vehicle, impacts of regenerative braking (for vehicles with an electric motor), and the additional
energy required from power take-off (PTO) units, if applicable.
We used EPA's GEM model to simulate road load power requirements for various duty
cycles using the default road load profiles to estimate work performed by HD vehicles. GEM
does this by modeling physical characteristics of a vehicle that include vehicle mass, frontal area,
tire rolling resistance, tire size, gear ratio, accessory loads, as well as reductions in power
demand for weight reduction and other technologies that reduce demand from the vehicle. We
used the engine fuel maps and the vehicle technology inputs to GEM developed to support the
MY 2027 HD GHG Phase 2 vehicle standards929 (see the Phase 2 MY 2027 standards in Table 2-
929 U.S. Environmental Protection Agency and Department of Transportation. Greenhouse Gas Emissions and Fuel
Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles - Phase 2 Regulatory Impact Analysis
(October 25, 2016). Pages 2-136, 2-137, 2-158, 2-159.
199
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109 for tractors, and in Table 2-110 for vocational vehicles for a list of the regulatory
subcategories, including the vocational optional chassis subcategories) except for the BEVs
32Tractor_SC_C18 and 33Tractor_DC_C18.930 For those vehicles we used the GEM inputs for
C8SCHR and C8DCHR, respectively, except we applied a lower coefficient of drag area for
the BEV vehicles (see GEM IDs C8_SC_HR_CdA036 and C8_DC_HR_CdA036) to represent
trucks with a more aerodynamically optimized tractor design. To calculate the new value, we
benchmarked the Tesla Semi which has the lowest coefficient of drag in the market today of
0.36,931'932 We then multiplied the nominal frontal area (9.8 square meters) of these tractors by
the Tesla Semi coefficient of drag, to determine the coefficient of drag area. The GEM input
values also include default mechanical and electrical accessory loads (see Table 2-10 and Table
2-11).933
We used a tool developed in-house to evaluate hybrid vehicle performance to calculate a
weighted percent of energy recovery due to regenerative braking.934 This tool is like GEM in that
it models physical vehicle properties over the Phase 2 duty cycles and uses the Phase 2 weighting
for each regulatory subcategory to calculate the weighted energy recovered. We used the same
Phase 2 vehicle GEM inputs for this tool as we used for the GEM simulations to maintain
consistency in our calculations.
We incorporated PTO calculations into the ZEV baseline energy because they are the key
aspect of work from some HD vehicles. In HD TRUCS, PTO is converted into kilowatt-hour
(kWh) per mile (mi) using the operational hours and operational VMT for vehicles that have a
PTO unit. We recognize that the presentation of PTO in terms of kWh/mi may suggest that all
PTO loads are consumed while the vehicle is moving, but this is not the case for several vehicle
types. Nonetheless, PTO is presented in terms of kWh/mi to help facilitate different calculations
in HD TRUCS.
The total ZEV baseline energy is the summation of axle, regenerative braking, and PTO load
energies, as shown in Table 2-5. Detailed descriptions of these values as well as inputs to GEM
are discussed in RIA Chapters 2.2.2.1.1-2.2.2.1.4.935
2.2.2.1.1 GEM Inputs
Table 2-1 shows the GEM Energy ID that is assigned to each of the 101 vehicles in HD
TRUCS. The tables in this RIA Chapter 2.2.2.1.1 show the GEM input values for each GEM
930 Note that GEM values are sometime applicable to a broader grouping of regulatory subcategories, so we will
generally show GEM values at the regulatory subcategory grouping level that is appropriate. The vocational optional
chassis subcategories are assigned a vocational vehicle services class and duty cycle for GEM simulations, as
described in 40 CFR. 1037.105(h).
931 Inside EVs. "Tesla Semi: Details on Truck Aerodynamics and Drag Coefficient". April 2019. Available online:
https://insideevs.com/news/345710/tesla-semi-details-on-truck-aerodynamics-and-drag-coefficient/
932 Fleetowner. "Musk touts Tesla Semi's range days before first fleet gets EV truck." November 28, 2022. Available
online: https://www.fleetowner.eom/emissions-efficiency/article/21255400/musk-touts-tesla-semis-range-before-
first-truck-deliveries-to-pepsico
933 Note that the HVAC loads are subsequently removed to determine ZEV baseline energy consumption because
HVAC loads differ among different powertrain technologies. See RIA Chapter 2.2.2.1.2 for more detail on the
removal of HVAC loads for ZEV baseline energy.
934 Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. "Simple Hybrid Model". March 2023.
935 See also Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. "GEM Inputs and Results". November
2023.
200
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Energy ID that are used to estimate energy demand at the axle. In the NPRM version of HD
TRUCS, most MHD and HHD vehicles that could be optionally certified under an optional
custom chassis category used GEM input default values for its corresponding optional custom
chassis category; however, for the final version of HD TRUCS, we only used the optional
custom chassis GEM default values for vehicles that are in the same weight class that is assigned
to the Optional Chassis Category. This creates a more accurate estimate of energy consumption.
An example of this is vehicle 46B_School_C18_MP, which was assigned the school bus optional
chassis GEM Energy ID values (for a MHD vehicle) for the NPRM version of HD TRUCS. For
the final version of HD TRUCS, we updated vehicle 46B_School_C18_MP to use GEM Energy
ID values for a heavy heavy-duty multipurpose (HHD M) vocational vehicle which is more
representative of the energy consumption for a Class 8 school bus.
Table 2-6 through Table 2-9 show the engine, drivetrain, tire, and other GEM input
parameters. Any GEM input parameters not listed have a value of zero.
Table 2-6 Model Year 2027 GEM Engine Parameters
GEM Energy ID
Engine File Name
Engine Power
C8 SC HR
Engines\EPA 2027 D SC GENERIC 455 TCA SIM GEMv351.csv
455
C8 DC HR
Engines\EPA 2027 D SC GENERIC 455 TCA SIM GEMv351.csv
455
C7 DC HR
Engines\EPA 2027 D GENERIC 350 TCA SIM GEMv351.csv
350
C8 HH
Engines\EPA 2018 D GENERIC 600 TCA SIM GEMv351.csv
600
HHD R
EnginesYEPA 2027 D Voc GENERIC 455 TCA SIM GEMv351.csv
455
HHD M
EnginesYEPA 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
HHD U
Engine sYEP A 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
MHD R
Engine sYEP A 2027 D GENERIC 270 TCA SIM GEMv351.csv
270
MHD M
Engine sYEP A 2027 D GENERIC 270 TCA SIM GEMv351.csv
270
MHD U
Engine sYEP A 2027 D GENERIC 270 TCA SIM GEMv351.csv
270
LHD R
Engine sYEP A 2027 D GENERIC 200 TCA SIM GEMv351.csv
200
LHD M
Engine sYEP A 2027 D GENERIC 200 TCA SIM GEMv351.csv
200
LHD U
Engine sYEP A 2027 D GENERIC 200 TCA SIM GEMv351.csv
200
RV
EnginesYEPA 2027 D GENERIC 270 TCA SIM GEMv351.csv
270
School Bus
Engine sYEP A 2027 D GENERIC 270 TCA SIM GEMv351.csv
270
Coach Bus
EnginesYEPA 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
Emergency
EnginesYEPA 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
Mixer
EnginesYEPA 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
Transit Bus
EnginesYEPA 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
Refuse Truck
EnginesYEPA 2027 D Voc GENERIC 350 TCA SIM GEMv351.csv
350
201
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Table 2-7 Model Year 2027 GEM Drivetrain Parameters
GEM Energy II)
Transmission File Name
Drive Axle
Config
Drive Axle
Ratio
C8 SC HR
TransmissionsYEPA MT 10 C78 4490 hires.csv
6X4
3.16
C8 DC HR
TransmissionsYEPA MT 10 C78 4490 hires.csv
6X4
3.21
C7 DC HR
TransmissionsYEPA MT 10 C78 4490 hires.csv
4X2
3.21
C8 HH
TransmissionsYEPA MT 18 HH hires.csv
6X4
3.70
HHD R
TransmissionsYEPA MT 10 HHD 4490 hires.csv
6X4
3.76
HHD M
TransmissionsYEPA AT 6 HHD.csv
6X4
4.33
HHD U
TransmissionsYEPA AT 5 HHD 1020 hires.csv
6X4
5.29
MHD R
TransmissionsYEPA AT 6 MHD.csv
4X2
5.50
MHD M
TransmissionsYEPA AT 6 MHD.csv
4X2
5.29
MHD U
TransmissionsYEPA AT 5 MHD 803 hires.csv
4X2
5.29
LHD R
TransmissionsYEPA AT 6 LHD.csv
4X2
4.33
LHD M
TransmissionsYEPA AT 6 LHD.csv
4X2
4.56
LHD U
TransmissionsYEPA AT 5 LHD 803 hires.csv
4X2
4.56
RV
TransmissionsYEPA AT 6 MHD.csv
4X2
5.50
School Bus
TransmissionsYEPA AT 5 MHD 803 hires.csv
4X2
5.29
Coach Bus
TransmissionsYEPA AT 6 HHDBus.csv
4X2
4.33
Emergency
TransmissionsYEPA AT 5 HHD 1020 hires.csv
6X4
5.29
Mixer
TransmissionsYEPA AT 5 HHDMixer.csv
6X4
5.29
Transit Bus
TransmissionsYEPA AT 5 HHD 1020 hires.csv
4X2
5.29
Refuse Truck
TransmissionsYEPA AT 5 HHD 1020 hires.csv
6X4
5.29
202
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Table 2-8 Model Year 2027 GEM Vehicle Input Parameters
Coef. of
Drag
Area
(m2)
Steer Axle
Drive Axle 1
Drive Axle 2
GEM Energy ID
Tire Rolling
Resistance
Tire Rolling
Resistance
Tire Rolling
Resistance
Drive Axle
Tire Size
Coefficient
Coefficient
Coefficient
(rev/mile)
(N/kN)
(N/kN)
(N/kN)
C8 SC HR
5.26
5.6
5.8
5.8
512
C8 SC HR CdA036
3.53
5.6
5.8
5.8
512
C8 DC HR
5.67
5.6
5.8
5.8
512
C8 DC HR CdA036
3.53
5.6
5.8
5.8
512
C7 DC HR
5.67
5.6
5.8
NA
512
C8 HH
6.21
5.8
6.2
6.2
512
HHD R
NA
7.7
7.7
7.7
496
HHD M
NA
7.7
7.7
7.7
496
HHD U
NA
7.7
7.7
7.7
496
MHD R
NA
7.7
7.7
NA
517
MHD M
NA
7.7
7.7
NA
557
MHD U
NA
7.7
7.7
NA
557
LHD R
NA
7.7
7.7
NA
670
LHD M
NA
7.7
7.7
NA
670
LHD U
NA
7.7
7.7
NA
660
RV
NA
5.8
5.8
NA
517
School Bus
NA
5.9
6.3
NA
557
Coach Bus
NA
5.8
5.8
5.8
496
Emergency
NA
6.4
8.1
8.1
496
Mixer
NA
6.7
7.2
7.2
496
Transit Bus
NA
6.7
6.8
NA
517
Refuse Truck
NA
6.7
6.8
6.8
496
203
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Table 2-9 Model Year 2027 Additional Technology GEM Inputs
Extended
GEM Energy ID
Idle
Speed
(RPM)
Weight
Reduction
Intelligent
Controls (%
Effectiveness)
Accessory
Load (%
Effectiveness)
Idle
Reduction
(%
Effectiveness)
Tire Pressure
System (%
Effectiveness)
Other Techs
(%
Effectiveness)
C8 SC HR
600
0
0.8
0.5
3
5.5
C8 SC HR CdA036
600
0
0.8
0.5
3
5.5
C8 DC HR
600
0
0.8
0.5
0
5.7
C8 DC HR CdA036
600
0
0.8
0.5
0
5.7
C7 DC HR
650
0
0.8
0.5
0
5.1
C8 HH
600
0
0.8
0.5
0
9.5
HHD R
600
0
NA
0.0
NA
0.0
0.0
HHD M
650
0
NA
0.0
NA
0.0
0.0
HHD U
650
0
NA
0.0
NA
0.0
0.0
MHD R
750
0
NA
0.0
NA
0.0
0.0
MHD M
750
0
NA
0.0
NA
0.0
0.0
MHD U
750
0
NA
0.0
NA
0.0
0.0
LHD R
750
0
NA
0.0
NA
0.0
0.0
LHD M
750
0
NA
0.0
NA
0.0
0.0
LHD U
750
0
NA
0.0
NA
0.0
0.0
RV
750
0
NA
0.0
NA
0.0
0.0
School Bus
750
0
NA
0.0
NA
0.0
0.0
Coach Bus
650
0
NA
0.0
NA
0.0
0.0
Emergency
650
0
NA
0.0
NA
0.0
0.0
Mixer
650
0
NA
0.0
NA
0.0
0.0
Transit Bus
650
75
NA
0.0
NA
0.0
0.0
Refuse Truck
650
0
NA
0.0
NA
0.0
0.0
We used the default values in GEM for the characteristics such as vehicle mass, rotational
inertia, coefficient of drag (for vocational vehicles), tire rolling resistance (for trailers and
vocational vehicles), payload, and electrical and mechanical accessory power (to account for
additional loads related to accessories such as lights, radio, HVAC, and cooling fans) for each
weight class and vehicle type. Table 2-10 contains values for tractors and Table 2-11 contains
values for vocational vehicles. Additional details about model defaults can be found in the Phase
2 GEM documentation.936
936 U.S. Environmental Protection Agency. "Greenhouse Gas Emissions Model (GEM) v4.0 User Guide". July 2022.
Available online: httos://nepis.epa.gov/Exe/ZvPDF.cgi?Dockev=P1015AND.pdf.
204
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Table 2-10 GEM Tractor Default Values
Regulatory Class
Characteristic
Roof Height
High Roof
Mid Roof
Low Roof
C8DC
Total Weight (kg)
31,297
29,529
29,710
Tire Rolling Resistance (N/kN)
6.2
Rotational Mass (kg)
794
Payload (tons)
19
Electrical Acc Power (W)
1200
Mechanical Acc Power (W)
2300
C8SC
Total Weight (kg)
31,978
30,277
30,390
Tire Rolling Resistance (N/kN)
6.2
Rotational Mass (kg)
794
Payload (tons)
19
Electrical Acc Power (W)
1200
Mechanical Acc Power (W)
2300
C7DC
Total Weight (kg)
22,679
20,910
21,091
Tire Rolling Resistance (N/kN)
6.2
Rotational Mass (kg)
340
Payload (tons)
12.5
Electrical Acc Power (W)
1200
Mechanical Acc Power (W)
2300
C8 HH
Total Weight (kg)
53750
Coefficient of Drag(mA2)
6.21
Tire Rolling Resistance (N/kN)
6.2
Rotational Mass (kg)
794
Payload (tons)
43
Electrical Acc Power (W)
1200
Mechanical Acc Power (W)
2300
Table 2-11 GEM Vocational Vehicle Default Values
Regulatory Class
Total
Weight
(kg)
Coefficient
of Drag
(mA2)
Tire
Rolling
Resistance
(N/kN)
Rotational
Mass (kg)
Payload
(tons)
Electrical
Acc Power
(W)
Mechanical
Acc Power
(W)
HHD
19,051
6.86
7.7
794
7.50
1200
2300
MHD
11,408
5.40
7.7
340
5.60
900
1600
LHD
7,257
3.40
7.7
340
2.85
500
1000
Emergency Vehicles
19,051
6.86
7.7
794
7.50
1200
2300
Cement Mixers
19,051
6.86
7.7
794
7.50
1200
2300
Refuse Trucks
19,051
6.86
7.7
794
7.50
1200
2300
Coach Buses
19,051
6.86
7.7
794
7.50
1200
2300
Transit Buses
19,051
6.86
7.7
794
7.50
1200
2300
Motor Homes
11,408
5.40
7.7
340
5.60
900
1600
School Buses
11,408
5.40
7.7
340
5.60
900
1600
2.2.2.1.2 GEM Energy Consumption at the Axle
To determine energy consumption per mile, we first calculated work performed, or energy
consumed, at the axle (kWh) and CO2 emissions (grams) for each duty cycle as shown in Table
2-12; this was determined for the constant cruise at 55 and 65 miles per hour (MPH) cycles as
205
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well as the transient cycle. The cruise cycles include road grade. The road grade profile for both
the 55 mph and 65 mph duty cycles is based on statistical analysis of the United States' national
distribution of road grades. The minimum grade in these cycles is -5 percent and the maximum
grade is 5 percent. The cycle spends 46 percent of the distance in grades of ± 0.5 percent.
Overall, the cycle spends approximately 66 percent of the time in relatively flat terrain with road
gradients of ± 1 percent.937
We also removed the air conditioning compressor portion of the HVAC loads from axle work
because HVAC loads differ across the range of HD vehicle powertrain technologies such as ICE,
BEV, and FCEV. Therefore, we considered HVAC loads separately from the ZEV baseline
energy consumption that is used for ZEVs. The energy consumption at the axle, as shown in
Table 2-12, was determined by subtracting this HVAC power demand, weighted by GEM duty
cycle, from the GEM output. The power consumption of the HVAC load during the duty cycle
that we removed was 1.0 kilowatt (kW) for LHD and MHD vehicles and 1.5 kW for remainder
of the vehicles based on the mechanical accessory loads developed for HD GHG Phase 2 version
of GEM.938 The HVAC load is calculated assuming that the HVAC system is operating at a
constant load during the entire duty cycle.
937 81 FR 73633.
938 U.S. Environmental Protection Agency. "Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium-
and Heavy-Duty Engines and Truck - Regulatory Impact Analysis." August 2016. EPA 420-R-16-900. See Chapters
4.4.1.9 and 4.4.1.10.
206
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Table 2-12 Model Year 2027 GEM Axle Work and CO2 Emissions939 (HVAC load has been removed)
Cruise 55 MPH
Cruise 65 MPH
Transient Cycle
GEM Energy ID
Axle Work
Grams
Axle Work
Grams
Axle Work
Grams
(kWh)
of CO2
(kWh)
of CO2
(kWh)
of CO2
C8 SC HR
23.5
13855
27.2
15687
8.2
6124
C8 SC HR CdA036
20.4
22.7
8.0
C8 DC HR
24.0
14712
28.0
16860
8.0
6286
C8 DC HR CdA036
20.1
22.5
7.8
C7 DC HR
20.0
12662
24.1
14950
5.9
5169
C8 HH
34.0
21058
37.6
23394
13.4
9982
HHD R
23.5
16537
29.2
20266
5.5
5046
HHD M
23.5
17704
29.0
21596
5.5
5748
HHD U
23.5
21563
28.4
27897
5.5
5736
MHD R
16.7
14321
21.1
17409
3.4
4016
MHD M
16.7
14447
21.1
17465
3.4
4026
MHD U
16.7
14980
21.2
18443
3.4
4043
LHD R
10.5
9626
13.3
11514
2.1
2763
LHD M
10.5
9836
13.4
11868
2.1
2808
LHD U
10.5
10513
13.3
12974
2.1
2820
RV
15.5
13506
19.9
16534
3.2
3854
School Bus
15.6
14247
20.1
17729
3.1
3794
Coach Bus
21.5
15859
27.0
19539
5.1
5423
Emergency
23.4
21493
28.3
27834
5.4
5722
Mixer
22.9
21149
27.8
27525
5.4
5651
Transit Bus
22.6
20628
27.4
26948
5.3
5495
Refuse Truck
22.6
20971
27.5
27363
5.3
5614
The values for work performed during each duty cycle were then divided by the distance of
each duty cycle to determine the energy demand per mile. The distance and duration of each duty
cycle are listed in Table 2-13.
Table 2-13 GEM Duty Cycle Distance and Time
GEM Test Cycle
Distance (miles)
Time (s)
Transient
2.84
668
55 Cruise
13.43
879
65 Cruise
13.43
744
Energy required per mile was then weighted by the applicable Phase 2 weighting factor for
each test cycle and respective regulatory class to adjust consumption based on GEM distance
weighting (by duty cycle) and time weighting (by percent at idle) factors, as well as average
speed during non-idle cycles, as shown in Table 2-14. (Note that the regulatory subcategories
that use the same weight factors are aggregated in the table.)
939 There are two tractors, 33Tractor_DC_C18 and 32Tractor_SC_C18, which when assessed as BEVs were
simulated in GEM with lower aerodynamic drag than their diesel counterparts. This is because typical engine
packaging for diesel vehicles precludes the type of aerodynamic reductions that are available to BEVs. These two
vehicles, when assessed as BEVs, are assigned Gem Energy IDs, BEV, C8_DC_HR_CdA036, and
C8_SC_HR_CdA036. respectively. We did not calculate grams of CO2 for these two GEM Energy IDs because
these are only assessed as BEV vehicles and therefore do not have CO2 emissions.
207
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Table 2-14 GEM Test Cycle Weighting Factors and Average Speed
Regulatory Class
Distance-weighted Factor
(%)
Time-weighted Factor (%)
Average
speed
(MPH)
Transient
55
Cruise
65
Cruise
Drive
idle
Parked
idle
Non-idle
Sleeper Cab
5
9
86
Day Cab
19
17
64
Heavy-haul tractors
19
17
64
Vocational - Regional
20
24
56
0
25
75
28.41
Vocational - Multi-Purpose (2b-7)
54
29
17
17
25
58
23.18
Vocational - Multi-Purpose (8)
54
23
23
17
25
58
23.27
Vocational - Urban (2b-7)
92
8
0
15
25
60
16.25
Vocational - Urban (8)
90
10
0
15
25
60
16.51
The values were summed to calculate the energy consumption by regulatory class. The
resulting values for weighted energy consumption per mile at the axle are shown in Table 2-15.
As described above, HVAC loads have been removed, and neither PTO loads nor regenerative
braking benefits are included in Table 2-15.
For the final rule, we updated the tractor energy consumption values. The updates were made
for two distinct reasons. The first update was made to correct an error in the proposal that
occurred when summing the weighted energy of the three duty cycles. We had added the
weighted value at the transmission for the 65-mph cruise cycle into the tractors rather than using
the weighted value at the axle. This correction had the effect of lowering the tractor energy
consumption values. The second update was to use high-roof tractor Phase 2 inputs. For the
proposal, each tractor in HD TRUCS was assigned a GEM Energy ID for a low roof tractor.
However, for the final rule, we have updated all tractors to use the high-roof default values in
GEM because we found that high-roof tractors were the most common configuration in the MY
2021 Phase 2 vehicle GHG emission certifications. Because the energy consumption rate for
high roof tractors is typically higher than for low roof tractors, this is a conservative approach
and had the effect of raising the energy consumption values. The net effect of both updates
resulted in values that are 3 to 6 percent lower than the proposal for the impacted tractors.
208
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Table 2-15 Weighted Energy Consumption per Mile
GEM Energy ID
Weighted Axle Work per Mile (kWh/mi)
C7 DC HR
1.83
C8 DC HR
2.21
C8 DC HR CdA036
1.89
C8 HH
3.15
C8 SC HR
2.07
C8 SC HR CdA036
1.76
HHD R
2.09
HHD M
2.11
HHD U
2.14
MHD R
1.46
MHD M
1.39
MHD U
1.36
LHD R
0.93
LHD M
0.89
LHD U
0.87
RV
1.38
School Bus
1.30
Coach Bus
1.94
Emergency
2.13
Concrete Mixer
2.10
Transit Bus
2.07
Refuse Truck
2.08
2.2.2.1.3 Regenerative Braking
Regenerative braking is utilized on BEVs and FCEVs, but the amount of potential energy
recovery is dependent on the vehicle properties and drive cycle. The details for calculating our
projections for regenerative (sometimes referred to as "regen") braking energy are in RIA
Chapter 2.8.1. In summary, to calculate percent energy recovery available, we estimated the
braking energy and divided by the total tractive energy (i.e., the energy required to move the
vehicle) for each drive cycle and then weighted the results using the respective GEM test cycle
weighting factors from Table 2-14. We then multiplied these values by the weighted energy
consumption per mile to get energy recovered per mile from regenerative braking. The results
are shown in Table 2-16. This table in the proposal contained incorrect values in the column
titled "Regenerative Braking Energy Recovered (kWh/mile)". The values displayed in the
proposal were the fractional value of the column titled "Regenerative Braking Energy Recovered
(%)" and we have updated the values to reflect the actual regenerative braking used in the final
rule, which are the same value as used in the proposal.
209
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Table 2-16 Percent Energy Recovery and Energy Recovered per Mile from Regenerative Braking
GEM Energy II)
Regenerative
Braking Energy
Recovered (%)
Regenerative
Braking Energy
Recovered
(kWh/mile)
C7 DC HR
6.0
0.11
C8 DC HR
7.0
0.15
C8 DC HR CdA036
8.9
0.17
C8 HH
8.5
0..26
C8 SC HR
4.3
0.09
C8 SC HR CdA036
5.9
0.10
HHD R
4.5
0.09
HHD M
11.1
0.23
HHD U
17.9
0.38
MHD R
3.9
0.06
MHD M
10.1
0.14
MHD U
16.8
0.23
LHD R
3.8
0.04
LHD M
9.8
0.09
LHD U
16.5
0.14
RV
3.9
0.05
School Bus
16.8
0.22
Coach Bus
4.5
0.09
Emergency
17.9
0.18
Concrete Mixer
17.9
0.38
Transit Bus
17.9
0.37
Refuse Truck
17.9
0.37
Note that GEM outputs are by vehicle type. Energy recovered from regenerative braking per
mile for each regulatory subcategory was then applied to the applicable 101 vehicle types in HD
TRUCS. RIA Chapters 2.3, 2.4, and 2.5 discuss how electrical energy and fuel consumption per
mile are attributed to the 101 HD TRUCS vehicle types for ICE vehicles, BEVs, and FCEVs,
respectively.
2.2.2.1.4 Power Take Off (PTO)
Some vocational vehicles selected as representative of the heavy-duty industry have
attachments that perform work, typically by powering a hydraulic pump, which are powered by
PTOs. In HD TRUCS, the vehicle applications with PTO energy consumption estimates include
boom (utility) truck, cement mixer/cement pumper940, dump truck, fire truck, garbage truck
(refuse handler), snowplow, (street) sweeper, tanker truck, and wrecker (tow truck). Information
on in-use PTO energy demand cycles is limited. NREL published two papers describing
investigative work into PTO usage and energy consumption.941'942 These studies, however, were
limited to electric utility vehicles, such as bucket trucks and material handlers. To account for
940 Cement mixer is used to represent both cement mixers and cement pumpers.
941 Konan, Arnaud, et al."Characterization of PTO and Idle Behavior for Utility Vehicles." Sept 2017. NREL.
Available online: https://www.nrel.gov/docs/fV17osti/66747.pdf.
942 Konan, Arnaud, et al. "Fuel and Emissions Reduction in Electric Power Take-Off Equipped Utility Vehicles"
June 2016. NREL. Available online: https://www.nrel.gov/docs/fv 17osti/66737.pdf
210
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PTO usage in HD TRUCS, we relied on a table described in California's Diesel Tax Fuel
Regulations, specifically in Regulation 1432, "Other Nontaxable Uses of Diesel Fuel in a Motor
Vehicle."943 The table for Regulation 1432 covers a wider range of vehicles beyond the electric
utility vehicles in the previously mentioned NREL studies. This table contains "safe-harbor"
percentages that are presumed amounts of diesel fuel used for "auxiliary equipment" operated
from the same fuel tank as the motor vehicle. In California, a person may apply for a fuel tax
refund for diesel fuel that is not used to operate a motor vehicle upon a highway in California.944
In the NPRM, we used this table to estimate PTO energy use as a function of total fuel consumed
by vehicle type, as shown in Table 2-17. We received comment suggesting that a cement mixer
may have PTO fuel burn in the range of 35%-49%. After consideration of this comment, for the
final rule we have updated the cement mixer/pumper PTO rate to 42%, the midpoint of the range
suggested by the commenter to more accurately reflect the industry average PTO energy
consumption for concrete mixers.
The percent PTO energy use for specific vehicle types in HD TRUCS are shown in Table
2-18.
Table 2-17 PTO Energy Use as a Function of Total Energy Consumed from CA Regulation 1432945
Type
PTO Percent (%) from
PTO Percent (%) as
CA Regulation 1432
Used in HD TRUCS
None
0
0
Boom truck/block boom
15
15
Cement mixer
25
42
Cement pumper
40
42
Dump truck
15
15
Fire truck
25
25
Garbage truck
35
35
Snow plow
15
15
Sweeper truck
20
20
Tank truck
15
15
Wrecker
15
15
943 See Cal. Code Regs. tit. 18, § 1432, "Other Nontaxable Uses of Diesel Fuel in a Motor Vehicle," available at
https://www.cdtfa.ca.gov/lawguides/vol3/dftr/dftr-regl432.html.
944 Ibid.
945 California Department of Tax and Fee Administration. Regulation 1432. Other Nontaxable Uses of Diesel Fuel in
a Motor Vehicle. Accessed October 2022. Available online: https://www.cdtfa.ca.gov/lawguides/vol3/dftr/dftr-
regl432.html#:~:text=in%20these%20percentages%3A-.Boom%20truck/block%20boom.l0%25.-
(3)%20For%20transactions.
211
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Table 2-18 PTO Assignment in HD TRUCS
Vehicle ID
PTO Percent Energy
Consumption (%)
19C Mix C18 MP
42%
20T Dump C18 U
15%
2IT Dump C18 MP
15%
22T Dump C16-7 MP
15%
23T Dump C18 U
15%
24T Dump C16-7 U
15%
25T Fire C18 MP
25%
26T Fire C18 U
25%
34T Ref C18 MP
35%
35T Ref C16-7 MP
35%
36T Ref C18 U
35%
37T Ref C16-7 U
35%
60S Plow C16-7 MP
15%
61S Plow C18 MP
15%
62S Plow C16-7 U
15%
63 S Plow C18 U
15%
70S Sweep C16-7 U
20%
7IT Tanker C18 R
15%
72T Tanker C18 MP
15%
73T Tanker C18 U
15%
74T Tow C18 R
15%
75T Tow C16-7 R
15%
76T Tow C18 U
15%
77T Tow C16-7 U
15%
89T Utility C18 MP
15%
90T Utility C18 R
15%
9IT Utility C16-7 MP
15%
92T Utility C16-7 R
15%
93T Utility C14-5 MP
15%
94T Utility C12b-3 MP
15%
95T Utility C14-5 R
15%
96T Utility C12b-3 R
15%
97T Utility C18 U
15%
98T Utility C16-7 U
15%
99T Utility C14-5 U
15%
100T Utility C12b-3 U
15%
Table 2-17 shows the PTO energy as a percent of total energy consumed. We assumed the
fuel is consumed while operating a diesel-powered vehicle on an annual basis. To incorporate the
value into the ZEV baseline energy consumption on a kWh/mi basis, we converted the fuel
consumption of vehicles listed in Table 2-18 from the fuel economy (MPG) of the comparable
ICE vehicle into annual diesel fuel consumption using 250 operating days in a year. Since GEM
does not include PTO of these vehicles, the PTO fuel consumption is the PTO percent multiplied
by the annual fuel consumption projected for the vehicles due to driving operation only. This is
then converted back to a daily value by dividing by 250 operating days per year, and then to an
axle and per-mile value by applying the diesel energy content and losses from the ICE
212
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powertrain system. A detailed description of PTO calculations can be found in RIA Chapter
2.3.3.
2.2.2.2 Heating, Ventilation, and Air Conditioning (HVAC) Energy Consumption
Heating, ventilation, and air conditioning (HVAC) energy requirements vary by vehicle type,
vocation, and duty cycle. The HVAC energy required to heat and cool interior cabins is
considered separately from the baseline energy, since these energy loads are not required year-
round or in all regions of the country and most vehicles are equipped with air conditioning
(A/C). Nearly all commercial vehicles are equipped with heat and basic ventilation. In ICE
vehicles, traditional cabin heating makes use of excess thermal energy produced by the main
ICE. This is the only source of cabin heating for many vehicle types. Additionally, on ICE
vehicles, cabin A/C uses a mechanical refrigerant compressor that is engine belt driven. A/C
utilizes a thermodynamic cycle to move thermal energy from the cabin to the ambient air outside
the vehicle, cooling and dehumidifying the cabin. Compressors can also be driven by an electric
motor.
Energy consumption associated with vehicle heating and cooling is dependent on passenger
comfort requirements, cabin size and materials, ambient air temperature, relative humidity,
number of occupants, number of door openings and closings, and the HVAC system technology
type and efficiency.
Cabin heating utilizing engine waste heat requires electrical power to run the controls and
blower motors. A/C operation adds mechanical load on the engine to run the compressor and
requires electric power to operate the HVAC blower motor.
As described in RIA Chapter 2.2.2.1.2, although GEM already includes HVAC load in its
power consumption, because of the unique and different nature of BEVs and FCEVs, this
incorporated load is removed from the calculated GEM energy consumption at the axle for ZEV
baseline energy. Then, a separate HVAC calculation is performed to calculate the "axle" level
HVAC consumption of BEVs and FCEVs irrespective of the energy source (i.e., the battery or
hydrogen). We describe how HVAC is considered for BEVs and FCEVs in RIA Chapters
2.4.1.1.1 and 2.5.1.2.2. For ICE vehicles, the GEM results (including the HVAC energy demand)
are used.
2.2.3 HD Vehicle Sales
At proposal, EPA calculated sales percentages for each vehicle application using certification
data from MY 2019 and MOVES 3.R1 new vehicle sales data. DRIA at p. 134. For the final rule
we have updated our approach for calculating the sales percentages for each vehicle application
to use the most recent available data: MY 2021 sales of new vehicles in the latest version of
MOVES that is being used in conjunction with the final rule.
We started by updating all HD TRUCS vehicles that were previously categorized as
regClassID 41 with regClassID 42. MOVES defines regClassID 41 as chassis certified Class 2b-
3 vehicles with a gross vehicle weight rating (GVWR) between 8,500 pounds and 14,000
pounds. Chassis certified vehicles are not included in this rulemaking. However, the vehicles
modeled in the NPRM version of HD TRUCS as regClassID 41 do exist in the marketplace as
engine certified vehicles with lower sales volumes. We therefore changed the regClassID of
those vehicles to regClassID 42 which MOVES defines as Class 4-5 vehicles and engine-
213
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certified Class 3 vehicles between 14,000 lbs and 19,500 pounds GVWR. Engine certified LHD
vehicles are included in this rulemaking and have lower sales in MOVES which reflects a more
appropriate approach to approximating vehicle sales in HD TRUCS.
We then checked that HD TRUCS contained the same MOVES sourceTypelDs and
regClassIDs present in the latest version of MOVES. Table 2-19 contains that analysis as well as
the total number of new vehicle sales for each sourceTypelD and regClassID. However, based on
consideration of comments received on the proposal, we modified the total number of sales for
sourceTypelD 41 and regClassID 47 to a maximum value of 2,500 sales. We were using the
sales in this source type and reg class to represent coach buses exclusively and comments
pointed out that sales of Class 8 coach buses do not exceed 2,500 sales. In response, we moved
the remainder of sales of sourceTypelD 41 and regClassID 47 to sourceTypelD 42 and
regClassID 47 to represent sales of Class 8 transit buses which had no sales in MOVES before
this change. These changes are reflected in Table 2-19.
Table 2-19 MY 2021 MOVES New Vehicle Sales by sourceTypelD and regClassID
sourceTypelD
sourceTypeName
regClassID
regClassName
newSales
In HD
TRUCS?
41
Other Buses
42
LHD45
6386
Yes
41
Other Buses
46
MHD67
394
Yes
41
Other Buses
47
HHD8
2500
Yes
42
Transit Bus
42
LHD45
1897
Yes
42
Transit Bus
46
MHD67
117
Yes
42
Transit Bus
47
HHD8
13738
Yes
42
Transit Bus
48
Urban Bus
4823
Yes
43
School Bus
42
LHD45
1746
Yes
43
School Bus
46
MHD67
23977
Yes
43
School Bus
47
HHD8
1787
Yes
51
Refuse Truck
42
LHD45
0
No
51
Refuse Truck
46
MHD67
468
Yes
51
Refuse Truck
47
HHD8
2544
Yes
52
Single Unit Short-haul Truck
42
LHD45
163889
Yes
52
Single Unit Short-haul Truck
46
MHD67
78860
Yes
52
Single Unit Short-haul Truck
47
HHD8
39435
Yes
53
Single Unit Long-haul Truck
42
LHD45
7228
Yes
53
Single Unit Long-haul Truck
46
MHD67
3478
Yes
53
Single Unit Long-haul Truck
47
HHD8
1739
Yes
54
Motor Home
42
LHD45
16877
Yes
54
Motor Home
46
MHD67
7969
Yes
54
Motor Home
47
HHD8
4618
Yes
61
Combination Short-haul Truck
46
MHD67
28746
Yes
61
Combination Short-haul Truck
47
HHD8
72193
Yes
61
Combination Short-haul Truck
49
Gliders
0
No
62
Combination Long-haul Truck
46
MHD67
4416
No
62
Combination Long-haul Truck
47
HHD8
114523
Yes
62
Combination Long-haul Truck
49
Gliders
0
No
We found that there were four MOVES sourceTypelD and regClassID combinations that did
not exist in HD TRUCS. Three of those four combinations contained zero sales and they are
summarized in Table 2-20.
214
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Table 2-20 MY 2021 MOVES New Vehicle Sales with Zero Sales Not in HD TRUCS
sourceTypelD
sourceTypeName
regClassID
regClassName
newSales
In HD
TRUCS?
51
Refuse Truck
42
LHD45
0
No
61
Combination Short-haul Truck
49
Gliders
0
No
62
Combination Long-haul Truck
49
Gliders
0
No
The fourth combination of MOVES sourceTypelD and regClassID that did contain sales is
summarized in Table 2-21 as well as the number of sales.
Table 2-21 MY 2021 MOVES New Vehicle Sales Not in HD TRUCS With Sales
sourceTypelD
sourceT ypeN ame
regClassID
regClassName
newSales
In HD
TRUCS?
62
Combination Long-haul Truck
46
MHD67
4416
No
Since the CO2 emission standards for Class 7 tractors apply for all cab types (see 40 CFR
1037.106(b)), we determined it was appropriate to move the sales from sourceTypelD 62 and
regClassID 46 to sourceTypelD 61 regClassID 46 which are the Class 6 and 7 combination short
haul trucks (day cab tractors). This allowed us to retain the same number of sales in HD TRUCS
as in MOVES. We determined that keeping the sales in a GHG regulatory subcategory that was
in the same weight class so that the additional sales in the combination short haul would still
describe a physically similar vehicle by payload and energy consumption, albeit with fewer miles
travelled per day.
We then calculated the number of vehicle types in HD TRUCS for each MOVES
sourceTypelD and regClassID combination. The results are in Table 2-22.
215
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Table 2-22 Number of HD TRUCS Vehicle Types for each Combination of MOVES sourceTypelD and
regClass ID
MOVES source TypelD
MOVES regClassID
# of HD TRUCS Vehicle Types
41
42
2
41
46
1
41
47
2
42
42
1
42
46
3
42
47
1
42
48
1
43
42
4
43
46
2
43
47
2
51
46
2
51
47
2
52
42
16
52
46
17
52
47
19
53
42
4
53
46
1
53
47
1
54
42
2
54
46
2
54
47
2
61
46
4
61
47
6
62
47
4
51
42
0
61
49
0
62
46
0
62
49
0
We then calculated the number of new vehicle sales for each HD TRUCS vehicle types by
dividing the sales of each MOVES sourceTypelD and regClassID by the number of HD TRUCS
vehicle types. The results are in Table 2-23. However, we did not distribute sales evenly for
certain vehicle applications. For tractors, we have left the last column of Table 2-23 blank for
combinations of MOVES sourceTypelD/regClassID combinations 61/46, 61/47, and 62/47 to
reflect that the sales in these combinations were not evenly divided into the HD TRUCS
vehicles; the sales fractions for tractors are described below Table 2-23. For MOVES
sourceTypelD/ regClassID combinations 52/64, 52/47, 61/46, 61/47, and 62/47 most vehicle
applications are assigned an evenly divided share of sales; however, dump trucks and snow
plows have been assigned distinct sales shares, as described below. Final sales for each vehicle
in HD TRUCS can be found in Table 2-24.
216
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Table 2-23 Number of Sales of MY2021 MOVES New Vehicle Sales for each HD TRUCS Vehicle Type
MOVES
MOVES
regClassID
# of HD
# of MOVES
Sales for Each HD
source
TRUCS
MY 2021
TRUCS Vehicle
TypelD
Vehicle Types
Sales
Type
41
42
2
6386
3193
41
46
1
394
394
41
47
2
2500
1250
42
42
1
1897
1897
42
46
3
117
39
42
47
1
13738
13738
42
48
1
4823
4823
43
42
4
1746
437
43
46
2
23977
11988
43
47
2
1787
894
51
46
2
468
234
51
47
2
2544
1272
52
42
16
163889
10243
52
46
17
78860
4639
52
47
19
39435
2076
53
42
4
7228
1807
53
46
1
3478
3478
53
47
1
1739
1739
54
42
2
16877
8439
54
46
2
7969
3985
54
47
2
4618
2309
61
46
4
33162
61
47
6
72193
62
47
4
114523
51
42
0
0
0
61
49
0
0
0
62
46
0
0
0
62
49
0
0
0
Next, we applied the values from the last column of Table 2-23 to each vehicle in HD
TRUCS, using the appropriate MOVES sourceTypelD and regClassID. We updated the sales
shares for tractors, snow plows, and dump trucks, as described below, to ensure that the sales
shares were representative of technology types that are being assessed for tractors and after
consideration of a comment that snow plows and dump trucks are often the same vehicles that
have different implements applied in different seasons.
For the final rule, the sales allocation for sleeper cabs (MOVES SourceTypelD = 62) were
split along different technology pathways. The four sleeper cab tractors included in HD TRUCS
are the following: 32Tractor_SC_C18 which is a BEV with a range of 420 miles that represents
an aerodynamically optimized tractor; 54Tractor_SC_C18 which is a BEV with a range of 420
miles and represents a BEV that is designed with the same aerodynamic drag as the ICE sleeper
cab tractor; 78Tractor_SC_C19 which is a BEV with a range of 300 miles; and
79Tractor_SC_C18 which is a FCEV with 420 miles of range. 78Tractor_SC_C18 was assigned a
sales percentage of 28 percent as explained in Chapter 2.2.1.2 of this RIA, leaving 72 percent of
the sales fraction to split among the remaining three vehicles. We assigned 20 percent of the
remaining sales to 32Tractor_SC_C18, as a conservative estimate of vehicles that may be
217
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designed with a BEV-specific aerodynamic improvements in the MY 2027-2032 timeframe. The
remaining sales are attributed to the FCEV tractor, 79Tractor_SC_C18. The BEV long-range
sleeper cab, 54Tractor_SC_C18, has a sales allocation of 0 percent because our assessment is that
fuel cells are likely to be the dominant long-range sleeper cab technology until (1) a greater
percentage of BEV sleeper cabs are redesigned with the type of aerodynamic improvements that
are feasible without an internal combustion engine, and (2) the energy density of batteries has
further improved beyond the projections in this final rule, such that the potential impacts on
payload mass are reduced.946
For the final rule, we allocated the day cab sales allocations using the sales shares from Table
18 of CARB's "Large Entity Fleet Reporting."947 We assigned the Class 7 short-range day cab,
3 lTractor_DC_C16-7, with a daily operational VMT of 97 miles, 31 percent of the Class 7 day
cab sales, consistent with the percent of day cabs that operate up to 100 miles per day in the
Large Entity Fleet Reporting table. We assigned the Class 7 mid-range day cab,
83Tractor_DC_C17, with a daily operational VMT of 120 miles, 31 percent of the Class 7 day
cab sales, consistent with the sum of the percent of day cabs that operate in the 101-150 miles
and 151-200 miles per day categories in the Large Entity Fleet Reporting table. We assigned the
Class 7 long-range day cabs, 41Tractor_DC_C17 and 81Tractor_DC_C17, with a daily
operational VMT of 216 miles, half of 38 percent of the Class 7 day cab sales, consistent with
splitting the sales evenly after summing the percent of day cabs that operate in the 201-300 miles
and over 300 miles per day categories in the Large Entity Fleet Reporting table.
We assigned the Class 8 day cabs sales shares using a process that is similar to the Class 7 day
cabs; with the exception of the vehicle 101Tractor_DC_C18 which represents a yard tractor that
is road legal. We assigned the Class 8 short range day cab, 30Tractor_DC_C18, with a daily
operational VMT of 97 miles, 90 percent of 31 percent (= 27.9%) of the Class 8 day cab sales.
As described for Class 7 day cabs above, 31 percent is consistent with the percent of day cabs
that operate up to 100 miles per day in the Large Entity Fleet Reporting table. The reason that
only 90 percent of the fraction of short-range day cabs were assigned to vehicle
30Tractor_DC_C18 is that 10 percent of the short-range day cab sales were assigned to the road-
legal yard tractor, 101Tractor_DC_C18. Only a small fraction of tractors that are used as yard
tractors are certified as on-road vehicles; therefore, the number of sales is a small fraction (about
3%) of the total Class 8 day cab sales. We assigned the Class 8 mid-range day cab similarly to
the Class 7 mid-range day cabs, where vehicle 84Tractor_DC_C18 is assigned 31 percent of the
Class 8 day cab sales. We also assigned the Class 8 long-range day cabs, similar to the Class 7
long-range day cabs; we split 38 percent of the Class 8 day cab sales evenly among
33Tractor_DC_C18, 45Tractor_DC_C18, and 82Tractor_DC_C18.
For the final rule, we have determined that snow plows should represent a much smaller
portion of the snow plow and dump truck sales. To represent this in HD TRUCS we combined
the sales of snow plows and dump trucks respective to their weight classes and ratioed the sales
by the temperature weighted VMT value for cold temperatures which is 5.3%. For further
discussion on this topic, see RTC Section 4.
946 See Chapter 2.9.1 for an assessment of potential impacts on payload.
947CARB. Large Entity Fleet Reporting. Available online https://ww2.arb.ca.gov/sites/default/files/2022-
02/Large Entity Reporting Aggregated Data ADA.pdf
218
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The final HD TRUCS sales shares are summarized in Table 2-24.
Table 2-24 Final HD TRUCS Sales Shares
Vehicle ID
MOVES source TypelD
MOVES regClassID
Sales %
01V Amb C14-5 MP
52
42
1.7%
02V Amb C12b-3 MP
52
42
1.7%
03V Amb C14-5 U
52
42
1.7%
04V Amb C12b-3 U
52
42
1.7%
05T Box C18 MP
52
47
0.3%
06T Box C18 R
53
47
0.3%
07T Box C16-7 MP
52
46
0.8%
08T Box C16-7 R
53
46
0.6%
09T Box C18 U
52
47
0.3%
10T Box C16-7 U
52
46
0.8%
11T Box C12b-3 U
52
42
1.7%
12T Box C12b-3 R
52
42
1.7%
13T Box C12b-3 MP
52
42
1.7%
14T Box C14-5 U
52
42
1.7%
15T Box C14-5 R
52
42
1.7%
16T Box C14-5 MP
52
42
1.7%
17B Coach C18 R
41
47
0.2%
18B Coach C18 MP
41
47
0.2%
19C Mix C18 MP
52
47
0.3%
20T Dump C18 U
52
47
0.5%
21T Dump C18 MP
52
47
0.5%
22T Dump C16-7 MP
52
46
1.5%
23T Dump C18 U
52
47
0.5%
24T Dump C16-7 U
52
46
1.5%
25T Fire C18 MP
52
47
0.3%
26T Fire C18 U
52
47
0.3%
27T Flat C16-7 MP
52
46
0.8%
28T Flat C16-7 R
52
46
0.8%
29T Flat C16-7 U
52
46
0.8%
30Tractor DC C18 MP
61
47
3.3%
31 Tractor DC C16-7 MP
61
46
1.7%
32Tractor SC C18 U
62
47
2.7%
33Tractor DC C18 U
61
47
1.5%
34T Ref C18 MP
51
47
0.2%
35T Ref C16-7 MP
51
46
0.0%
36T Ref C18 U
51
47
0.2%
37T Ref C16-7 U
51
46
0.0%
38RV C18 R
54
47
0.4%
39RV C16-7 R
54
46
0.7%
40RV C14-5 R
54
42
1.4%
41Tractor DC C17 R
61
46
1.0%
42RV C18 MP
54
47
0.4%
43RV C16-7 MP
54
46
0.7%
44RV C14-5 MP
54
42
1.4%
45Tractor DC C18 R
61
47
1.5%
46B School C18 MP
43
47
0.1%
47B School C16-7 MP
43
46
2.0%
48B School C14-5 MP
43
42
0.1%
219
-------
49B School C12b-3 MP
43
42
0.1%
50B School C18 U
43
47
0.1%
5 IB School C16-7 U
43
46
2.0%
52B School C14-5 U
43
42
0.1%
53B School C12b-3 U
43
42
0.1%
54Tractor SC C18 R
62
47
0.0%
55B Shuttle C12b-3 MP
42
42
0.3%
56B Shuttle C14-5 U
41
42
0.5%
57B Shuttle C12b-3 U
41
42
0.5%
58B Shuttle C16-7 MP
42
46
0.0%
59B Shuttle C16-7 U
41
46
0.1%
60S Plow C16-7 MP
52
46
0.1%
61S Plow C18 MP
52
47
0.0%
62 S Plow C16-7 U
52
46
0.1%
63 S Plow C18 U
52
47
0.0%
64V Step C16-7 MP
52
46
0.8%
65V Step C14-5 MP
52
42
1.7%
66V Step C12b-3 MP
53
42
0.3%
67V Step C16-7 U
52
46
0.8%
68V Step C14-5 U
52
42
1.7%
69V Step C12b-3 U
53
42
0.3%
70S Sweep C16-7 U
52
46
0.8%
71T Tanker C18 R
52
47
0.3%
72T Tanker C18 MP
52
47
0.3%
73T Tanker C18 U
52
47
0.3%
74T Tow C18 R
52
47
0.3%
75T Tow C16-7 R
52
46
0.8%
76T Tow C18 U
52
47
0.3%
77T Tow C16-7 U
52
46
0.8%
78Tractor SC C18 MP
62
47
5.3%
79Tractor SC C18 R
62
47
10.9%
80Tractor DC C18 HH
52
47
0.3%
81Tractor DC C17 R
61
46
1.0%
82Tractor DC C18 R
61
47
1.5%
83Tractor DC C17 U
61
46
1.7%
84Tractor DC C18 U
61
47
3.7%
85B Transit C18 MP
42
47
2.3%
86B Transit C16-7 MP
42
46
0.0%
87B Transit C18 U
42
48
0.8%
88B Transit C16-7 U
42
46
0.0%
89T Utility C18 MP
52
47
0.3%
90T Utility C18 R
52
47
0.3%
91T Utility C16-7 MP
52
46
0.8%
92T Utility C16-7 R
52
46
0.8%
93T Utility C14-5 MP
52
42
1.7%
94T Utility C12b-3 MP
52
42
1.7%
95T Utility C14-5 R
53
42
0.3%
96T Utility C12b-3 R
53
42
0.3%
97T Utility C18 U
52
47
0.3%
98T Utility C16-7 U
52
46
0.8%
99T Utility C14-5 U
52
42
1.7%
100T Utility C12b-3 U
52
42
1.7%
lOlTractor DC C18 U
61
47
0.4%
220
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2.3 ICE Vehicle Technology
As previously discussed, a goal of EPA's HD TRUCS analysis is to ensure that we evaluate
ZEVs that can perform the same work as comparable ICE vehicles. HD TRUCS only considers
powertrain or propulsion technologies and operational costs that are the incremental differences
between a ZEV and a comparable ICE vehicle; this RIA chapter thus does not include total
manufacturing or total operating costs.
RIA Chapter 2.2 introduced how we estimated the baseline amount of energy required to
move each benchmark HD vehicle type, considering regenerative braking and additional work
required for PTO operations, independent of the powertrain. RIA Chapter 2.3 explains how we
applied the values in RIA Chapter 2.2 to ICE vehicles and then considered HVAC and other
powertrain-specific energy consumption. First, we defined the vehicle size and powertrain for
each of the 101 vehicles in HD TRUCS, and then estimated upfront DMC and RPE of the ICE
vehicle powertrain components that are different from ZEV components.948 We also then
assessed the sales tax and FET costs. Lastly, we projected ICE vehicle fuel use, diesel engine
fluid (DEF) consumption, maintenance and repair costs, and insurance costs for each vehicle
type for the first ten years of vehicle operation.
2.3.1 ICE Vehicle Attributes
To understand the physical size and powertrain mass of current heavy-duty trucks, we looked
at basic powertrain properties and performance criteria of 76 existing diesel vehicles (see RIA
Chapter 1) to find averages of the wheelbase and powertrain mass based on weight class and
vehicle type. The mass of the powertrain includes the weight of the engine including the
aftertreatment system, transmission, fuel, and DEF. Note that the 76 existing vehicles cover all
101 vehicle types used in HD TRUCS because some of the 76 vehicles are further differentiated
by duty cycles. We then applied the results of this analysis to the 101 vehicles in HD TRUCS
based on the same division of weight class and vehicle type used for averaging the benchmark
vehicles. The results of this analysis are in Table 2-25.
Table 2-25 Benchmark ICE Vehicle Dimensions and Weight
Vehicle ID
Vehicle
ICE Powertrain
Wheelbase [in]
Weight fkgl
01V Amb C14-5 MP
141
788
02V Amb C12b-3 MP
148
462
03V Amb C14-5 U
141
788
04V Amb C12b-3 U
148
462
05T Box C18 MP
125
1370
06T Box C18 R
125
1370
07T Box C16-7 MP
146
879
08T Box C16-7 R
146
879
09T Box C18 U
125
1370
948 In our analysis, the ICE vehicles include a suite of technologies that represent a vehicle that meets the MY 2027
Phase 2 CO2 emission standards and an engine that meets the MY 2027 Low NOx emission standards. The direct
manufacturing costs for the vehicle components beyond the powertrain are considered to be $0 because our
projected technology package did not add additional CCh-reducing technologies to the ICE vehicles beyond those in
the baseline vehicle.
221
-------
Vehicle ID
Vehicle
Wheelbase fin]
ICE Powertrain
Weight fkgl
10T Box C16-7 U
146
879
11T Box C12b-3 U
141
462
12T Box C12b-3 R
141
462
13T Box C12b-3 MP
141
462
14T Box C14-5 U
148
788
15T Box C14-5 R
148
788
16T Box C14-5 MP
148
788
17B Coach C18 R
315
2302
18B Coach C18 MP
315
2302
19C Mix C18 MP
143
1805
20T Dump C18 U
125
1370
21T Dump C18 MP
125
1370
22T Dump C16-7 MP
146
879
23T Dump C18 U
125
1370
24T Dump C16-7 U
146
879
25T Fire C18 MP
125
1370
26T Fire C18 U
125
1370
27T Flat C16-7 MP
146
879
28T Flat C16-7 R
146
879
29T Flat C16-7 U
146
879
30Tractor DC C18
143
1805
31Tractor DC C17
143
1805
32Tractor SC C18
143
1805
33Tractor DC C18
143
1805
34T Ref C18 MP
173
1762
35T Ref C16-7 MP
146
879
36T Ref C18 U
173
1762
37T Ref C16-7 U
146
879
38RV C18 R
148
879
39RV C16-7 R
169
593
40RV C14-5 R
141
528
41Tractor DC C17
143
1805
42RV C18 MP
148
879
43RV C16-7 MP
169
593
44RV C14-5 MP
141
528
45Tractor DC C18
143
1805
46B School C18 MP
145
1209
47B School C16-7 MP
169
1209
48B School C14-5 MP
139
536
49B School C12b-3 MP
138
536
5OB School C18 U
145
1209
5 IB School C16-7 U
169
1209
52B School C14-5 U
139
536
53B School C12b-3 U
139
536
54Tractor SC C18
143
1805
55B Shuttle C12b-3 MP
133
572
56B Shuttle C14-5 U
139
788
57B Shuttle C12b-3 U
133
572
58B Shuttle C16-7 MP
169
1209
59B Shuttle C16-7 U
169
1209
60S Plow C16-7 MP
146
879
6IS Plow C18 MP
125
1370
222
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Vehicle ID
Vehicle
Wheelbase fin]
ICE Powertrain
Weight fkgl
62S Plow C16-7 U
146
879
63 S Plow C18 U
125
1370
64V Step C16-7 MP
158
593
65V Step C14-5 MP
134
788
66V Step C12b-3 MP
133
462
67V Step C16-7 U
158
593
68V Step C14-5 U
134
593
69V Step C12b-3 U
133
462
70S Sweep C16-7 U
169
1209
71T Tanker C18 R
125
1370
72T Tanker C18 MP
125
1370
73T Tanker C18 U
125
1370
74T Tow C18 R
125
1370
75T Tow C16-7 R
146
879
76T Tow C18 U
125
1370
77T Tow C16-7 U
146
879
78Tractor SC C18
143
1805
79Tractor SC C18
143
1805
80Tractor DC C18
143
1805
81Tractor DC C17
143
1805
82Tractor DC C18
143
1805
83Tractor DC C17
143
1805
84Tractor DC C18
143
1805
85B Transit C18 MP
202
1217
86B Transit C16-7 MP
169
790
87B Transit C18 U
202
1217
88B Transit C16-7 U
169
790
89T Utility C18 MP
125.1
1370
90T Utility C18 R
125.1
1370
91T Utility C16-7 MP
146
879
92T Utility C16-7 R
146
879
93T Utility C14-5 MP
148
788
94T Utility C12b-3 MP
149
775
95T Utility C14-5 R
148
788
96T Utility C12b-3 R
149
775
97T Utility C18 U
125.1
1370
98T Utility C16-7 U
146
879
99T Utility C14-5 U
148
788
100T Utility C12b-3 U
149
775
lOlTractor DC C18
116
1036
2.3.2 ICE Vehicle Components and Other Upfront Costs
The purpose of this analysis is to determine the incremental cost differences between ZEV
technologies and a comparable ICE vehicle; therefore, in this RIA Chapter 2.3.2, we are focusing
on the ICE powertrain components and costs that would differ between a ZEV and a comparable
ICE vehicle. These upfront costs are described in the following sections and include powertrain
component costs and costs that are assessed when a vehicle is purchased, such as state sales tax
and the federal excise tax (FET). Table 2-26 is a summary of these results for MY 2032. The
223
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sum of the ICE powertrain RPE, FET, and state sales taxes for MYs 2027, 2030, and 2032 are
shown in Chapter 2.9.2.
Table 2-26 ICE Powertrain (PT) RPE, Sales Tax and FET for MY 2032 (2022$)
Vehicle ID
PT DMC
PT RPE
FET
State Sales Tax
01V_Amb_C14-5_MP
30011
42616
0
2139
02V_Amb_C12b-3_MP
28653
40688
0
2043
03V_Amb_C14-5_U
30011
42616
0
2139
04V_Amb_C12b-3_U
28653
40688
0
2043
05T_Box_C18_MP
57170
81181
9742
4075
06T_Box_C18_R
57170
81181
9742
4075
07T_Box_C16 -7MP
32183
45699
0
2294
08T_Box_C16 -7_R
32183
45699
0
2294
09T_Box_C18_U
50533
71758
8611
3602
10T_Box_C16-7_U
32183
45699
0
2294
1 lT_Box_C12b-3_U
28188
40026
0
2009
12T_Box_C12b-3_R
28188
40026
0
2009
13T_Box_C12b-3_MP
28188
40026
0
2009
14T_Box_C14-5_U
28284
40163
0
2016
15T_Box_C14-5_R
28284
40163
0
2016
16T_Box_C14-5_MP
28284
40163
0
2016
17B_Coach_C18_R
44988
63882
7666
3207
18B_Coach_C18_MP
44988
63882
7666
3207
19 C_Mix_C18_MP
50533
71758
8611
3602
20T_Dump_C18_U
57170
81181
9742
4075
21 T_Dump_C18_MP
57170
81181
9742
4075
22T_Dump_C16-7_MP
32002
45443
0
2281
23 T_Dump_C18_U
50533
71758
8611
3602
24T_Dump_C16-7_U
32002
45443
0
2281
25T_Fire_C18_MP
57170
81181
9742
4075
26T_Fire_C18_U
50533
71758
8611
3602
27T_Flat_C16 -7MP
32002
45443
0
2281
28T_Flat_C16 -7_R
32002
45443
0
2281
29T_Flat_C16 -7_U
32002
45443
0
2281
30Tractor_DC_C18
60231
85528
10263
4294
3 lTractor_DC_C17
47365
67258
8071
3376
32Tractor_SC_C18
62481
88723
10647
4454
3 3 T ractorD CC18
47942
68078
8169
3418
34T_Ref_C18_MP
47568
67547
8106
3391
3 5 T_Ref_C16 -7MP
32002
45443
0
2281
36T_Ref_C18_U
47568
67547
8106
3391
37T_Ref_C16-7_U
32002
45443
0
2281
38RV_C18_R
33440
47485
5698
2384
39RV_C16-7_R
32083
45558
0
2287
40RV_C14-5_R
27686
39314
0
1974
41T ractorD CC17
47365
67258
8071
3376
42RV_C18_MP
33440
47485
5698
2384
224
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Vehicle ID
PT DMC
PT RPE
FET
State Sales Tax
43RVC16-7MP
32083
45558
0
2287
44RVC14-5MP
27686
39314
0
1974
45Tractor_DC_C18
62481
88723
10647
4454
46B_School_C18_MP
33440
47485
5698
2384
47B_School_C16-7_MP
32083
45558
0
2287
48B_School_C14-5_MP
27686
39314
0
1974
49B_School_C12b-3_MP
29015
41201
0
2068
50B_School_C18_U
33440
47485
5698
2384
5 lB_School_C16-7_U
32083
45558
0
2287
52B_School_C14-5_U
27686
39314
0
1974
53B_School_C12b-3_U
29015
41201
0
2068
54Tractor_SC_C18
62481
88723
10647
4454
55B_Shuttle_C12b-3_MP
29015
41201
0
2068
56B_Shuttle_C14-5_U
27686
39314
0
1974
57B_Shuttle_C12b-3_U
29015
41201
0
2068
58B_Shuttle_C16-7_MP
32083
45558
0
2287
59B_Shuttle_C16-7_U
32083
45558
0
2287
60 SPlo w_C16 -7MP
32002
45443
0
2281
61 S_Plow_C18_MP
57170
81181
9742
4075
62 SPlo w_C16 -7_U
32002
45443
0
2281
63 S_Plow_C18_U
50533
71758
8611
3602
64 V_Step_C16 -7MP
31933
45345
0
2276
65V_Step_C14-5_MP
27686
39314
0
1974
66 V_Step_C12b -3MP
28653
40688
0
2043
67 V_Step_C16 -7_U
31933
45345
0
2276
68V_Step_C14-5_U
27686
39314
0
1974
69V_Step_C12b-3_U
28653
40688
0
2043
70 S_Sweep_C16 -7_U
32002
45443
0
2281
71T_Tanker_C18_R
57170
81181
9742
4075
72TT ankerCI 8_MP
50533
71758
8611
3602
73T_Tanker_C18_U
50533
71758
8611
3602
74T_Tow_C18_R
58957
83719
10046
4203
7 5 T_T o w_C16 -7_R
32002
45443
0
2281
76T_Tow_C18_U
50533
71758
8611
3602
77T_Tow_C16-7_U
32002
45443
0
2281
78Tractor_SC_C18
62481
88723
10647
4454
79Tractor_SC_C18
62481
88723
10647
4454
80Tractor_DC_C18
63190
89730
10768
4504
81T ractorD CC17
47365
67258
8071
3376
82Tractor_DC_C18
62481
88723
10647
4454
83 T ractor_DC_C17
47365
67258
8071
3376
84Tractor_DC_C18
58640
83269
9992
4180
85B_Transit_C18_MP
44988
63882
7666
3207
86BT ransit_C16 -7MP
32083
45558
0
2287
87B_Transit_C18_U
44448
63117
7574
3168
88B_Transit_C16-7_U
32083
45558
0
2287
225
-------
Vehicle ID
PT DMC
PT RPE
FET
State Sales Tax
89T_Utility_C18_MP
57170
81181
9742
4075
90T_Utility_C18_R
57170
81181
9742
4075
91 T_Utility_C16 -7MP
32002
45443
0
2281
92 TUtility _C16 -7_R
32002
45443
0
2281
93 T_Utility_C14 -5MP
30011
42616
0
2139
94T_Utility_C12b-3_MP
28653
40688
0
2043
95 T_Utility_C14 -5_R
30011
42616
0
2139
96T_Utility_C12b-3_R
28653
40688
0
2043
97T_Utility_C18_U
50533
71758
8611
3602
98T_Utility_C16-7_U
32002
45443
0
2281
99T_Utility_C14-5_U
30011
42616
0
2139
100T_Utility_C12b-3_U
28653
40688
0
2043
10 lTractor_DC_C18
58640
83269
9992
4180
2.3.2.1 Powertrain Component Costs
The following ICE vehicle components were included in the cost analysis as primary
components of the ICE powertrain: engine including exhaust aftertreatment,
transmission/gearbox, starter, mechanical accessories, torque converter/clutch, final drive, and
generator/alternator. The cost of each component was added to the incremental component cost
used in EPA's technology package to meet the new NOx emissions standards in the Control of
Air Pollution from New Motor Vehicles: Heavy-Duty Engine and Vehicle Standard Rule (called
the "2027 Rule Costs" in Table 2-29).949 This method was used to estimate a total ICE
powertrain cost per vehicle type.
The cost of the engine and transmission/gearbox are two of the most expensive powertrain
components in an ICE HD vehicle. The cost of the diesel engine is calculated as a function of
engine power. To calculate engine costs, we used data from an ANL report where cost of the
engine increases with the power output of the engine, as shown in Figure 2-2.950>951 It should be
noted the aftertreatment cost is incorporated as a part of the engine cost. The power requirements
for each vehicle are based on the power requirements that were used to determine GEM energy
consumption, as shown in Table 2-27.952 We used the gearbox costs from the Autonomie Out
949 U.S. Environmental Protection Agency. Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine
and Vehicle Standards Regulatory Impact Analysis. See Table 7-5. Available at
https://nepis.epa.gov/Exe/ZvPDF.cgi?Dockev=P1016A9N.pdf.
950 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6. October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
951 Islam, Ehsan Sabri, Daniela Nieto Prada, Ram Vijayagopal, Charbel Mansour, Paul Phillips, Namdoo Kim,
Michel Alhajjar, Aymeric Rousseau. "Detailed Simulation Study to Evaluate Future Transportation Decarbonization
Potential", Report to the US Department of Energy, Contract ANL/TAPS-2 3/3, October 2023. Available
online:https://anl.app.box.com/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1429036831008.
952 For the final rule, we have calculated engine costs for all Class 8 vocational vehicles using a maximum of 350 hp
(261 kW). This is done in order to ensure that we do not overestimate the upfront costs of Class 8 vocational vehicle
powertrain systems.
226
-------
Import tab in the 2022 version of ANL's BEAN tool, as shown in Table 2-28.953 Since the tool
presents values for 2025 and 2030, the 2027 values were determined by interpolating between
the 2025 and 2030 high costs and then interpolating between the 2025 and 2030 low costs. Then,
the low and high MY 2027 values were averaged and converted to 2022$, and MY 2028-MY
2032 costs were calculated using ICE learning scalars as shown in RIA Chapter 3.2.1. ANL
vehicle IDs were then mapped to similar vehicles in HD TRUCS as shown in Table 2-2. The
remainder of the powertrain cost, including starter, mechanical accessories954, torque
converter/clutch, final drive, and generator/alternator, are binned to vehicle classes according to
Table 2-29. They are based on costs from the same Autonomie Out Import tab in the 2022
version of ANL's BEAN tool.955 These costs are not a major portion of the costs of the ICE
powertrain. Costs of all components used for ICE vehicles are shown in Table 2-30 for MY
2032.
x 104
3
-
2.5
baseline engine cost
S? 2
emission device cost
1 1-5
Q
1
¦
0.5
. . „ _ ——
0
.
.
250 300 350
Engine Power (kW)
Figure 2-2 Direct Manufacturing Cost of a Diesel Engine as a Function of Engine Power in 2020$ (these costs
are adjusted to 2022$ in HD TRUCS)956
Table 2-27 Engine Power used as GEM Inputs and to Determine Engine Cost
Vehicle ID
GEM Engine Power (kW)
01V Amb C14-5 MP
149
953 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
954 Mechanical accessory costs in HD TRUCS include BEAN costs for mechanical accessories, 12 volt batteries, and
vehicle propulsion architecture (VPA).
955 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
956 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6, October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1406494585829.
227
-------
Vehicle ID
GEM Engine Power (kW)
02V Amb C12b-3 MP
149
03V Amb C14-5 U
149
04V Amb C12b-3 U
149
05T Box C18 MP
265
06T Box C18 R
265
07T Box C16-7 MP
201
08T Box C16-7 R
201
09T Box C18 U
261
10T Box C16-7 U
201
11T Box C12b-3 U
149
12T Box C12b-3 R
149
13T Box C12b-3 MP
149
14T Box C14-5 U
149
15T Box C14-5 R
149
16T Box C14-5 MP
149
17B Coach C18 R
261
18B Coach C18 MP
261
19C Mix C18 MP
261
20T Dump C18 U
265
2IT Dump C18 MP
265
22T Dump C16-7 MP
201
23T Dump C18 U
261
24T Dump C16-7 U
201
25T Fire C18 MP
265
26T Fire C18 U
261
27T Flat C16-7 MP
201
28T Flat C16-7 R
201
29T Flat C16-7 U
201
30Tractor DC C18
339
31Tractor DC C17
261
32Tractor SC C18
339
33Tractor DC C18
261
34T Ref C18 MP
261
35T Ref C16-7 MP
201
36T Ref C18 U
261
37T Ref C16-7 U
201
38RV C18 R
201
39RV C16-7 R
201
40RV C14-5 R
149
41Tractor DC C17
261
42RV C18 MP
201
43RV C16-7 MP
201
44RV C14-5 MP
149
45Tractor DC C18
339
46B School C18 MP
201
47B School C16-7 MP
201
48B School C14-5 MP
149
49B School C12b-3 MP
149
5OB School C18 U
201
5 IB School C16-7 U
201
52B School C14-5 U
149
53B School C12b-3 U
149
228
-------
Vehicle ID
GEM Engine Power (kW)
54Tractor SC C18
339
55B Shuttle C12b-3 MP
149
56B Shuttle C14-5 U
149
57B Shuttle C12b-3 U
149
58B Shuttle C16-7 MP
201
59B Shuttle C16-7 U
201
60S Plow C16-7 MP
201
61S Plow C18 MP
265
62S Plow C16-7 U
201
63 S Plow C18 U
261
64V Step C16-7 MP
201
65V Step C14-5 MP
149
66V Step C12b-3 MP
149
67V Step C16-7 U
201
68V Step C14-5 U
149
69V Step C12b-3 U
149
70S Sweep C16-7 U
201
7IT Tanker C18 R
265
72T Tanker C18 MP
261
73T Tanker C18 U
261
74T Tow C18 R
339
75T Tow C16-7 R
201
76T Tow C18 U
261
77T Tow C16-7 U
201
78Tractor SC C18
339
79Tractor SC C18
339
80Tractor DC C18
447
81Tractor DC C17
261
82Tractor DC C18
339
83Tractor DC C17
261
84Tractor DC C18
339
85B Transit C18 MP
261
86B Transit C16-7 MP
201
87B Transit C18 U
261
88B Transit C16-7 U
201
89T Utility C18 MP
265
90T Utility C18 R
265
9IT Utility C16-7 MP
201
92T Utility C16-7 R
201
93T Utility C14-5 MP
149
94T Utility C12b-3 MP
149
95T Utility C14-5 R
149
96T Utility C12b-3 R
149
97T Utility C18 U
261
98T Utility C16-7 U
201
99T Utility C14-5 U
149
100T Utility C12b-3 U
149
lOlTractor DC C18
339
229
-------
Table 2-28 MY 2027, MY 2030, and MY 2032 ICE Gearbox Costs in HD TRUCS (2022$)
ANLID
MY 2027
MY 2030
MY 2032
Box Medium 3
4698
4651
4604
Van Medium 3
5173
5121
5069
School Medium 3
5542
5487
5431
Box Medium 4
4796
4748
4700
StepVan Medium 4
4186
4144
4102
Service Medium 4
6559
6493
6427
StepVan Medium 6
5331
5277
5224
Box Medium 6
5585
5529
5473
Tractor DayCab 7
7452
7377
7303
Vocational Medium 7
5401
5347
5293
School Medium 7
5483
5428
5374
Longhaul Sleeper 8
13692
13555
13418
Beverage DayCab 8
9772
9675
9577
Drayage DayCab 8
11396
11282
11168
Vocational Heavy 8
11771
11653
11535
Transit Heavy 8
6112
6051
5989
Refuse Heavy 8
8745
8657
8570
Regional DayCab 8
13692
13555
13418
Table 2-29 Binned Direct Manufacturing Costs for ICE Powertrain Components for MY 2032 (2022$)
Vehicle
Class
Starter Cost
($/unit)a
Torque Converter/
Clutch Cost
($/unit)b
Mech Acc Cost
($/unit)
Generator Cost
($/unit)c
2027 Rule
Cost
($/unit)d
Final
Drive Cost
($/unit)e
2b-5
164
554
2439
82
2265
1644
6-7
164
554
2439
82
2103
1644
8
329
554
2439
82
2680
1644
a The starter cost in MY 2032 is $329 for all Class 8 vehicles and all tractors, including Class 7 day cabs.
b The torque converter/clutch cost in MY 2032 is $430 for all tractors.
0 The generator cost in MY 2032 is $204 for all tractors.
d 2027 Rule Cost for Class 8 transit bus is $2,141 for MY 2032
eNote that for tractors, the final drive cost is doubled to account for tandem axles (e.g., one per axle) so is $3,287
for MY 2032.
Table 2-30 ICE Powertrain (PT) Direct Manufacturing Cost (DMC) for MY 2032 (2022$)
Vehicle ID
Engine
Cost
($/unit)
Gearbox
($/unit)
2027
Rule
Cost
($/unit)
Starter
Cost
($/unit)
Mech
Acc.
Cost
($/unit)
Torque
Converter
Clutch
Cost
($/unit)
Final
Drive
Cost
($/unit)
Generator
Cost
($/unit)
ICE
PT
DMC
($/unit)
01V Amb C14-5 MP
16436
6427
2265
164
2439
554
1644
82
30011
02V Amb C12b-3 MP
16436
5069
2265
164
2439
554
1644
82
28653
03V Amb C14-5 U
16436
6427
2265
164
2439
554
1644
82
30011
04V Amb C12b-3 U
16436
5069
2265
164
2439
554
1644
82
28653
05T Box C18 MP
37907
11535
2680
329
2439
554
1644
82
57170
06T Box C18 R
37907
11535
2680
329
2439
554
1644
82
57170
07T Box C16-7 MP
19724
5473
2103
164
2439
554
1644
82
32183
08T Box C16-7 R
19724
5473
2103
164
2439
554
1644
82
32183
09T Box C18 U
31271
11535
2680
329
2439
554
1644
82
50533
230
-------
Vehicle ID
Engine
Cost
($/unit)
Gearbox
($/unit)
2027
Rule
Cost
($/unit)
Starter
Cost
($/unit)
Mech
Acc.
Cost
($/unit)
Torque
Converter
Clutch
Cost
($/unit)
Final
Drive
Cost
($/unit)
Generator
Cost
($/unit)
ICE
PT
DMC
($/unit)
10T Box C16-7 U
19724
5473
2103
164
2439
554
1644
82
32183
11T Box C12b-3 U
16436
4604
2265
164
2439
554
1644
82
28188
12T Box C12b-3 R
16436
4604
2265
164
2439
554
1644
82
28188
13T Box C12b-3 MP
16436
4604
2265
164
2439
554
1644
82
28188
14T Box C14-5 U
16436
4700
2265
164
2439
554
1644
82
28284
15T Box C14-5 R
16436
4700
2265
164
2439
554
1644
82
28284
16T Box C14-5 MP
16436
4700
2265
164
2439
554
1644
82
28284
17B Coach C18 R
31271
5989
2680
329
2439
554
1644
82
44988
18B Coach C18 MP
31271
5989
2680
329
2439
554
1644
82
44988
19C Mix C18 MP
31271
11535
2680
329
2439
554
1644
82
50533
20T Dump C18 U
37907
11535
2680
329
2439
554
1644
82
57170
21T Dump C18 MP
37907
11535
2680
329
2439
554
1644
82
57170
22T Dump C16-7 MP
19724
5293
2103
164
2439
554
1644
82
32002
23T Dump C18 U
31271
11535
2680
329
2439
554
1644
82
50533
24T Dump C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
25T Fire C18 MP
37907
11535
2680
329
2439
554
1644
82
57170
26T Fire C18 U
31271
11535
2680
329
2439
554
1644
82
50533
27T Flat C16-7 MP
19724
5293
2103
164
2439
554
1644
82
32002
28T Flat C16-7 R
19724
5293
2103
164
2439
554
1644
82
32002
29T Flat C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
30Tractor DC C18
39695
11168
2680
329
2439
430
3287
204
60231
31 Tractor DC C17
31271
7303
2103
329
2439
430
3287
204
47365
32Tractor SC C18
39695
13418
2680
329
2439
430
3287
204
62481
33Tractor DC C18
31271
7303
2680
329
2439
430
3287
204
47942
34T Ref C18 MP
31271
8570
2680
329
2439
554
1644
82
47568
35T Ref C16-7 MP
19724
5293
2103
164
2439
554
1644
82
32002
36T Ref C18 U
31271
8570
2680
329
2439
554
1644
82
47568
37T Ref C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
38RV C18 R
19724
5989
2680
329
2439
554
1644
82
33440
39RV C16-7 R
19724
5374
2103
164
2439
554
1644
82
32083
40RV C14-5 R
16436
4102
2265
164
2439
554
1644
82
27686
41 Tractor DC C17
31271
7303
2103
329
2439
430
3287
204
47365
42RV C18 MP
19724
5989
2680
329
2439
554
1644
82
33440
43RV C16-7 MP
19724
5374
2103
164
2439
554
1644
82
32083
44RV C14-5 MP
16436
4102
2265
164
2439
554
1644
82
27686
45Tractor DC C18
39695
13418
2680
329
2439
430
3287
204
62481
46B School C18 MP
19724
5989
2680
329
2439
554
1644
82
33440
47B School C16-7 MP
19724
5374
2103
164
2439
554
1644
82
32083
48B School C14-5 MP
16436
4102
2265
164
2439
554
1644
82
27686
49B School C12b-3 MP
16436
5431
2265
164
2439
554
1644
82
29015
50B School C18 U
19724
5989
2680
329
2439
554
1644
82
33440
5 IB School C16-7 U
19724
5374
2103
164
2439
554
1644
82
32083
52B School C14-5 U
16436
4102
2265
164
2439
554
1644
82
27686
53B School C12b-3 U
16436
5431
2265
164
2439
554
1644
82
29015
54Tractor SC C18
39695
13418
2680
329
2439
430
3287
204
62481
55B Shuttle C12b-3 MP
16436
5431
2265
164
2439
554
1644
82
29015
56B Shuttle C14-5 U
16436
4102
2265
164
2439
554
1644
82
27686
57B Shuttle C12b-3 U
16436
5431
2265
164
2439
554
1644
82
29015
58B Shuttle C16-7 MP
19724
5374
2103
164
2439
554
1644
82
32083
231
-------
Vehicle ID
Engine
Cost
($/unit)
Gearbox
($/unit)
2027
Rule
Cost
($/unit)
Starter
Cost
($/unit)
Mech
Acc.
Cost
($/unit)
Torque
Converter
Clutch
Cost
($/unit)
Final
Drive
Cost
($/unit)
Generator
Cost
($/unit)
ICE
PT
DMC
($/unit)
59B Shuttle C16-7 U
19724
5374
2103
164
2439
554
1644
82
32083
60S Plow C16-7 MP
19724
5293
2103
164
2439
554
1644
82
32002
61S Plow C18 MP
37907
11535
2680
329
2439
554
1644
82
57170
62 S Plow C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
63 S Plow C18 U
31271
11535
2680
329
2439
554
1644
82
50533
64V Step C16-7 MP
19724
5224
2103
164
2439
554
1644
82
31933
65V Step C14-5 MP
16436
4102
2265
164
2439
554
1644
82
27686
66V Step C12b-3 MP
16436
5069
2265
164
2439
554
1644
82
28653
67V Step C16-7 U
19724
5224
2103
164
2439
554
1644
82
31933
68V Step C14-5 U
16436
4102
2265
164
2439
554
1644
82
27686
69V Step C12b-3 U
16436
5069
2265
164
2439
554
1644
82
28653
70S Sweep C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
71T Tanker C18 R
37907
11535
2680
329
2439
554
1644
82
57170
72T Tanker C18 MP
31271
11535
2680
329
2439
554
1644
82
50533
73T Tanker C18 U
31271
11535
2680
329
2439
554
1644
82
50533
74T Tow C18 R
39695
11535
2680
329
2439
554
1644
82
58957
75T Tow C16-7 R
19724
5293
2103
164
2439
554
1644
82
32002
76T Tow C18 U
31271
11535
2680
329
2439
554
1644
82
50533
77T Tow C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
78Tractor SC C18
39695
13418
2680
329
2439
430
3287
204
62481
79Tractor SC C18
39695
13418
2680
329
2439
430
3287
204
62481
80Tractor DC C18
42286
11535
2680
329
2439
430
3287
204
63190
81 Tractor DC C17
31271
7303
2103
329
2439
430
3287
204
47365
82Tractor DC C18
39695
13418
2680
329
2439
430
3287
204
62481
83Tractor DC C17
31271
7303
2103
329
2439
430
3287
204
47365
84Tractor DC C18
39695
9577
2680
329
2439
430
3287
204
58640
85B Transit C18 MP
31271
5989
2680
329
2439
554
1644
82
44988
86B Transit C16-7 MP
19724
5374
2103
164
2439
554
1644
82
32083
87B Transit C18 U
31271
5989
2141
329
2439
554
1644
82
44448
88B Transit C16-7 U
19724
5374
2103
164
2439
554
1644
82
32083
89T Utility C18 MP
37907
11535
2680
329
2439
554
1644
82
57170
90T Utility C18 R
37907
11535
2680
329
2439
554
1644
82
57170
91T Utility C16-7 MP
19724
5293
2103
164
2439
554
1644
82
32002
92T Utility C16-7 R
19724
5293
2103
164
2439
554
1644
82
32002
93T Utility C14-5 MP
16436
6427
2265
164
2439
554
1644
82
30011
94T Utility C12b-3 MP
16436
5069
2265
164
2439
554
1644
82
28653
95T Utility C14-5 R
16436
6427
2265
164
2439
554
1644
82
30011
96T Utility C12b-3 R
16436
5069
2265
164
2439
554
1644
82
28653
97T Utility C18 U
31271
11535
2680
329
2439
554
1644
82
50533
98T Utility C16-7 U
19724
5293
2103
164
2439
554
1644
82
32002
99T Utility C14-5 U
16436
6427
2265
164
2439
554
1644
82
30011
100T Utility C12b-3 U
16436
5069
2265
164
2439
554
1644
82
28653
lOlTractor DC C18
39695
9577
2680
329
2439
430
3287
204
58640
2.3.2.2 State Sales Tax and Federal Excise Tax
The NPRM version of HD TRUCS did not include estimates for state sales taxes on the
purchase of a vehicle or Federal Excise Tax (FET) where applicable. After consideration of
232
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comments, we have added these values to the final version of HD TRUCS to better assess
incremental upfront purchaser costs. Sales tax and FET are calculated by first applying a retail
price equivalent (RPE) factor957 to the upfront powertrain DMC costs. One industry commenter
recommended using a state sales tax rate of 5.02%, an average of the 50 state sales tax values,
which we assessed and confirmed was appropriate.958 This rate was applied to the upfront costs
(RPE) for all HD TRUCS vehicles for the final rule. A Federal Excise tax of 12% was applied to
the upfront costs (RPE) for all Class 8 (heavy heavy-duty) vehicles and all tractors.959
2.3.3 ICE Vehicle Fuel Consumption
To estimate fuel consumption for a diesel version of each vehicle type in HD TRUCS, we
assigned the GEM Energy ID fuel consumption value to the appropriate vehicle segment in HD
TRUCS to get the GEM-weighted fuel consumption by vehicle type. As previously noted,
HVAC is already incorporated into the GEM runs and thus we did not need to determine HVAC
separately for ICE vehicles.
For each regulatory subcategory, grams of CO2 emissions from our GEM simulations were
converted to gallons of diesel fuel consumed using a CO2 conversion of 10,180 grams of CO2 per
gallon of diesel.960'961 The gallons of diesel were then divided by the distance of each driving
cycle and weighted appropriately for their respective regulatory subcategories. The results of
these calculations are shown in Table 2-31.
There are two tractors, 33Tractor_DC_C18 and 32Tractor_SC_C18, which when assessed as
BEVs were simulated in GEM with lower aerodynamic drag than their diesel counterparts. This
is because typical engine packaging precludes the type of aerodynamic reductions that are
available to BEVs; therefore, when these two tractors are assessed as diesel vehicles, the fuel
consumption (MPGD) values used are C8 DC HR. and C8 SC HR, from Table 2-31.
957 See Chapter 3.2 for a discussion of RPE.
958See page 38 of docket number EPA-HQ-OAR-2022-0985-2668-A1.
959 U.S. Internal Revenue Service. 26 USC 4051. Available at
http://uscode.house.gov/view.xhtml?req=granuleid:USC-prelim-title26-section4051&num=0&edition=prelim
960 A value of 10,180 grams of CO2 per gallon of diesel was used as our conversion factor as it was agreed upon as a
common conversion factor between the EPA and Department of Transportation (DOT) in a rulemaking that
established the initial National Program fuel economy standards for model years 2012-2016 (75 FR 25324, May 7,
2010). Available at https://www.epa.gov/energy/greenhouse-gases-equivalencies-calculator-calculations-and-
references
961 U.S. Environmental Protection Agency. "Greenhouse Gas Equivalencies Calculator—Calculations and
References. Accessed December 2022. Available online: https://www.epa.gov/energy/greenhouse-gases-
eauivalencies-calculator-calculations-and-
references#:~:text=of%20diesel%20consumed.In%20the%20preamble%20to%20the%20ioint%20EPA%2FDepartm
ent%20of%20Transportation.emissions%20per%20gallon%20of%20diesel.
233
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Table 2-31 GEM Fuel Consumption in Miles per Gallon Diesel (MPGD)
GEM Energy ID
Fuel Consumption (MPGD)
C8 SC HR
8.5
C8 DC HR
7.5
C7 DC HR
8.6
C8 HH
5.3
HHD R
7.2
HHD M
6.4
HHD U
5.2
MHD R
8.2
MHD M
8.0
MHD U
7.3
LHD R
12.2
LHD M
11.4
LHD U
10.2
RV
8.4
School Bus
7.2
Coach Bus
6.9
Emergency
5.0
Mixer
5.0
Transit Bus
5.2
Refuse Truck
5.0
We then assigned the GEM fuel consumption value to the appropriate vehicle segment in HD
TRUCS to obtain the GEM-weighted fuel consumption by vehicle type. We also took fuel
consumption due to PTO loads into account, as some of the vehicles in HD TRUCS have
auxiliary loads supplied by a PTO. If a vehicle was equipped with a PTO, we calculated the
additional fuel used when operating the PTO. These percent PTO values are a function of the
propulsion ICE values as determined from GEM, where the MPG value for each Vehicle ID can
be found in Table 2-32 (see discussion of PTO loads as a percentage of diesel fuel consumption
in Chapter 2.2.2.1.4). For vehicles without a PTO unit, the percent PTO is zero. The PTO fuel
consumption in terms of MPG was then converted into annual PTO fuel requirement for each
vehicle using the annual operational VMT. Table 2-32 shows the GEM-weighted fuel
consumption, gallons of diesel consumed per year by driving, and gallons of diesel consumed per
year by PTO operation. As discussed in Chapter 2.2.1.1.3, for the final version for HD TRUCS,
we have assessed each year of operation using the appropriate changes that occur with the age of
the vehicle for inputs such as VMT and maintenance and repair costs or vary by calendar year
such as fuel costs; however, we are continuing to show 10-year average values in tables such as
the one below, as a single value point of comparison. Appendix A to this RIA includes each year
of a 10-year schedule for VMT, which can be used to calculate the diesel and DEF gallons
consumed for each year of the 10-year schedule.
Table 2-32 Annual Diesel Fuel Consumption from Driving and PTO Use (MY 2032), 10 Year Average
Vehicle ID
GEM Weighted
Fuel
Consumption
(MPGD)
Annual Average
Gallons of Diesel
Consumed -
Driving
Annual Average
Gallons of Diesel
Consumed - PTO
Annual Average
Gallons of DEF
Consumed
01V Amb C14-5 MP
11.36
662
0
34
02V Amb C12b-3 MP
11.36
965
0
50
234
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Vehicle ID
GEM Weighted
Fuel
Consumption
(MPGD)
Annual Average
Gallons of Diesel
Consumed -
Driving
Annual Average
Gallons of Diesel
Consumed - PTO
Annual Average
Gallons of DEF
Consumed
03V Amb C14-5 U
10.24
846
0
44
04V Amb C12b-3 U
10.24
861
0
45
05T Box C18 MP
6.39
2292
0
119
06T Box C18 R
7.24
1982
0
103
07T Box C16-7 MP
8.01
1104
0
57
08T Box C16-7 R
8.23
1053
0
55
09T Box C18 U
5.15
2844
0
147
10T Box C16-7 U
7.27
1186
0
61
11T Box C12b-3 U
10.24
1285
0
67
12T Box C12b-3 R
12.15
1084
0
56
13T Box C12b-3 MP
11.36
1159
0
60
14T Box C14-5 U
10.24
825
0
43
15T Box C14-5 R
12.15
696
0
36
16T Box C14-5 MP
11.36
744
0
39
17B Coach C18 R
6.92
4955
0
257
18B Coach C18 MP
6.92
4955
0
257
19C Mix C18 MP
5.02
3952
2861
353
20T Dump C18 U
5.15
1724
304
105
21T Dump C18 MP
6.39
1389
245
85
22T Dump C16-7 MP
8.01
1557
275
95
23T Dump C18 U
5.15
1724
304
105
24T Dump C16-7 U
7.27
1715
303
104
25T Fire C18 MP
6.39
1389
463
96
26T Fire C18 U
5.15
1724
575
119
27T Flat C16-7 MP
8.01
1104
0
57
28T Flat C16-7 R
8.23
1074
0
56
29T Flat C16-7 U
7.27
1216
0
63
30Tractor DC C18
7.53
2767
0
143
31 Tractor DC C17
8.60
2426
0
126
32Tractor SC C18
8.51
10969
0
568
33Tractor DC C18
7.53
6153
0
319
34T Ref C18 MP
5.05
2332
1256
186
35T Ref C16-7 MP
8.01
2648
1426
211
36T Ref C18 U
5.05
2332
1256
186
37T Ref C16-7 U
7.27
2917
1571
232
38RV C18 R
8.39
313
0
16
39RV C16-7 R
8.23
319
0
17
40RV C14-5 R
12.15
216
0
11
41 Tractor DC C17
8.60
5392
0
279
42RV C18 MP
8.39
313
0
16
43RV C16-7 MP
8.01
328
0
17
44RV C14-5 MP
11.36
231
0
12
45Tractor DC C18
7.53
6152
0
319
46B School C18 MP
6.39
1630
0
84
47B School C16-7 MP
7.19
1541
0
80
48B School C14-5 MP
11.36
917
0
47
49B School C12b-3 MP
11.36
917
0
47
50B School C18 U
5.15
2023
0
105
5 IB School C16-7 U
7.19
1541
0
80
52B School C14-5 U
10.24
1017
0
53
235
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Vehicle ID
GEM Weighted
Fuel
Consumption
(MPGD)
Annual Average
Gallons of Diesel
Consumed -
Driving
Annual Average
Gallons of Diesel
Consumed - PTO
Annual Average
Gallons of DEF
Consumed
53B School C12b-3 U
10.24
1017
0
53
54Tractor SC C18
8.51
10969
0
568
55B Shuttle C12b-3 MP
11.36
2248
0
116
56B Shuttle C14-5 U
10.24
2493
0
129
57B Shuttle C12b-3 U
10.24
2493
0
129
58B Shuttle C16-7 MP
8.01
3190
0
165
59B Shuttle C16-7 U
7.27
3514
0
182
60S Plow C16-7 MP
8.01
1104
195
67
61S Plow C18 MP
6.39
1536
271
94
62 S Plow C16-7 U
7.27
1216
215
74
63 S Plow C18 U
5.15
1907
336
116
64V Step C16-7 MP
8.01
1687
0
87
65V Step C14-5 MP
11.36
744
0
39
66V Step C12b-3 MP
11.36
1136
0
59
67V Step C16-7 U
7.27
1859
0
96
68V Step C14-5 U
10.24
825
0
43
69V Step C12b-3 U
10.24
1260
0
65
70S Sweep C16-7 U
7.27
1538
385
100
71T Tanker C18 R
7.24
1581
279
96
72T Tanker C18 MP
6.39
1792
316
109
73T Tanker C18 U
5.15
2224
392
136
74T Tow C18 R
7.24
1973
348
120
75T Tow C16-7 R
8.23
1511
267
92
76T Tow C18 U
5.15
2775
490
169
77T Tow C16-7 U
7.27
1712
302
104
78Tractor SC C18
8.51
7835
0
406
79Tractor SC C18
8.51
10969
0
568
80Tractor DC C18
5.34
4403
0
228
81 Tractor DC C17
8.60
5392
0
279
82Tractor DC C18
7.53
6152
0
319
83Tractor DC C17
8.60
3008
0
156
84Tractor DC C18
7.53
3423
0
177
85B Transit C18 MP
5.15
5715
0
296
86B Transit C16-7 MP
8.01
2170
0
112
87B Transit C18 U
5.15
5715
0
296
88B Transit C16-7 U
7.27
2391
0
124
89T Utility C18 MP
6.39
927
164
56
90T Utility C18 R
7.24
818
144
50
91T Utility C16-7 MP
8.01
1363
241
83
92T Utility C16-7 R
8.23
1326
234
81
93T Utility C14-5 MP
11.36
961
170
59
94T Utility C12b-3 MP
11.36
440
78
27
95T Utility C14-5 R
12.15
881
155
54
96T Utility C12b-3 R
12.15
881
155
54
97T Utility C18 U
5.15
1150
203
70
98T Utility C16-7 U
7.27
1502
265
92
99T Utility C14-5 U
10.24
1066
188
65
100T Utility C12b-3 U
10.24
488
86
30
lOlTractor DC C18
7.53
1723
0
89
236
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2.3.4 ICE Vehicle Operating Costs
Operating costs for HD vehicles encompass a variety of costs, such as labor, insurance,
registration fees, fueling, maintenance and repair (M&R), and other costs. For this analysis, we
are primarily interested in costs that differ for a comparable ICE vehicle and a ZEV because
these costs will be used to calculate the year that a ZEV is estimated to pay back relative to a
comparable ICE vehicle (see RIA Chapter 2.8.8 and 2.9.2). We focus on fueling costs, M&R
costs, and insurance costs962 because we expect these costs to be different for ZEVs than for
comparable diesel vehicles, but we do not anticipate other operating costs, such as labor,963 to
differ meaningfully. For ICE vehicles, we also estimated the cost of the diesel exhaust fluid
(DEF) required for the selective catalytic reduction aftertreatment system.
For each vehicle in HD TRUCS, the 10-year average annual operating costs are as shown in
Table 2-33 and described in the sections below. As discussed in RIA Chapter 2.2.1.1.3, for the
final rule version of HD TRUCS, we have assessed each year of operation using the appropriate
changes that occur over time for inputs such as VMT, maintenance and repair, and fuel costs;
however, we are continuing to show a 10-year average value in tables such as the one below, as a
single value point of comparison. Appendix A to this RIA includes each year of a 10-year
schedule for VMT, which, with the M&R cost per mile (by vehicle age), the cost of diesel and
DEF per gallon (by calendar year), and the cost of insurance can be used to calculate the
operating costs for each year of a 10-year schedule.
Table 2-33 ICE Operating Costs for a MY 2032 Vehicle (2022$, 10-Year Average)
Vehicle ID
Average Annual Cost ($/year)
DEF
ICE Vehicle
M&R
Diesel
Powertrain
Insurance
01V Amb C14-5 MP
148
1997
2481
1278
02V Amb C12b-3 MP
216
2909
3781
1221
03V Amb C14-5 U
189
2301
3317
1278
04V Amb C12b-3 U
193
2341
3375
1221
05T Box C18 MP
512
3886
8981
2435
06T Box C18 R
443
3779
7766
2435
07T Box C16-7 MP
247
2346
4326
1371
08T Box C16-7 R
235
2281
4125
1371
09T Box C18 U
636
3886
11147
2153
10T Box C16-7 U
265
2289
4650
1371
11T Box C12b-3 U
287
3494
5037
1201
12T Box C12b-3 R
242
3494
4246
1201
13T Box C12b-3 MP
259
3494
4541
1201
14T Box C14-5 U
184
2243
3234
1205
15T Box C14-5 R
156
2243
2726
1205
16T Box C14-5 MP
166
2243
2915
1205
962 Insurance costs were not included in the proposal; however, EPA added these incremental costs to the final
version of HD TRUCS after consideration of comments. See RIA Chapter 2.3.4.4
963 We do not expect the labor costs for drivers to differ between ICE and ZEV vehicles. After consideration of
comments stating that ZEV technicians may initially require additional training, EPA has phased in the ZEV
maintenance and repair scaling factors to address this potential transition period. See RIA Chapters 2.4.4.1 and
2.5.3.2 and RTC Section 3.6 for more information.
237
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Vehicle ID
Average Annual Cost ($/year)
DEF
ICE Vehicle
M&R
Diesel
Powertrain
Insurance
17B Coach C18 R
1109
9203
19420
1916
18B Coach C18 MP
1109
9203
19420
1916
19C Mix C18 MP
1523
5261
26700
2153
20T Dump C18 U
453
2355
7948
2435
21T Dump C18 MP
365
2355
6404
2435
22T Dump C16-7 MP
409
3307
7176
1363
23T Dump C18 U
453
2355
7948
2153
24T Dump C16-7 U
451
3307
7905
1363
25T Fire C18 MP
414
2355
7257
2435
26T Fire C18 U
514
2355
9007
2153
27T Flat C16-7 MP
247
2346
4326
1363
28T Flat C16-7 R
240
2346
4208
1363
29T Flat C16-7 U
272
2346
4766
1363
30Tractor DC C18
618
5458
10839
2566
31 Tractor DC C17
542
5459
9501
2018
32Tractor SC C18
2452
24793
42985
2662
33Tractor DC C18
1374
12137
24102
2042
34T Ref C18 MP
803
3150
14067
2026
35T Ref C16-7 MP
911
5673
15972
1363
36T Ref C18 U
803
3150
14067
2026
37T Ref C16-7 U
1004
5673
17594
1363
38RV C18 R
70
722
1227
1425
39RV C16-7 R
72
722
1251
1367
40RV C14-5 R
48
722
848
1179
41 Tractor DC C17
1204
12134
21119
2018
42RV C18 MP
70
722
1227
1425
43RV C16-7 MP
74
722
1286
1367
44RV C14-5 MP
52
722
906
1179
45Tractor DC C18
1373
12134
24097
2662
46B School C18 MP
365
2795
6389
1425
47B School C16-7 MP
345
2976
6042
1367
48B School C14-5 MP
205
2795
3592
1179
49B School C12b-3 MP
205
2795
3592
1236
50B School C18 U
453
2795
7929
1425
5 IB School C16-7 U
345
2976
6042
1367
52B School C14-5 U
228
2795
3985
1179
53B School C12b-3 U
228
2795
3985
1236
54Tractor SC C18
2452
24793
42985
2662
55B Shuttle C12b-3 MP
503
6856
8810
1236
56B Shuttle C14-5 U
558
6856
9773
1179
57B Shuttle C12b-3 U
558
6856
9773
1236
58B Shuttle C16-7 MP
714
6856
12503
1367
59B Shuttle C16-7 U
786
6856
13773
1367
60S Plow C16-7 MP
290
2346
5091
1363
61S Plow C18 MP
404
2605
7083
2435
62 S Plow C16-7 U
320
2346
5608
1363
63 S Plow C18 U
501
2605
8790
2153
64V Step C16-7 MP
377
3585
6612
1360
65V Step C14-5 MP
166
2243
2915
1179
66V Step C12b-3 MP
254
3398
4451
1221
67V Step C16-7 U
415
3585
7284
1360
238
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Vehicle ID
Average Annual Cost ($/year)
DEF
ICE Vehicle
M&R
Diesel
Powertrain
Insurance
68V Step C14-5 U
184
2243
3234
1179
69V Step C12b-3 U
281
3398
4937
1221
70S Sweep C16-7 U
430
2967
7536
1363
71T Tanker C18 R
416
3038
7287
2435
72T Tanker C18 MP
471
3038
8261
2153
73T Tanker C18 U
585
3038
10252
2153
74T Tow C18 R
519
3792
9095
2512
75T Tow C16-7 R
397
3302
6968
1363
76T Tow C18 U
730
3792
12796
2153
77T Tow C16-7 U
450
3302
7892
1363
78Tractor SC C18
1751
17709
30704
2662
79Tractor SC C18
2452
24793
42985
2662
80Tractor DC C18
984
6241
17256
2692
81 Tractor DC C17
1204
12134
21119
2018
82Tractor DC C18
1373
12134
24097
2662
83Tractor DC C17
672
6770
11783
2018
84Tractor DC C18
764
6752
13408
2498
85B Transit C18 MP
1279
7904
22400
1916
86B Transit C16-7 MP
486
4664
8507
1367
87B Transit C18 U
1279
7904
22400
1893
88B Transit C16-7 U
535
4664
9371
1367
89T Utility C18 MP
244
1571
4273
2435
90T Utility C18 R
215
1571
3769
2435
91T Utility C16-7 MP
359
2897
6285
1363
92T Utility C16-7 R
349
2897
6113
1363
93T Utility C14-5 MP
253
2897
4429
1278
94T Utility C12b-3 MP
116
1326
2027
1221
95T Utility C14-5 R
231
2817
4060
1278
96T Utility C12b-3 R
231
2817
4060
1221
97T Utility C18 U
302
1571
5303
2153
98T Utility C16-7 U
395
2897
6924
1363
99T Utility C14-5 U
280
2897
4913
1278
100T Utility C12b-3 U
128
1326
2248
1221
lOlTractor DC C18
385
3397
6747
2498
2.3.4.1 Diesel Exhaust Fluid Costs
To estimate DEF consumption for a diesel version of each vehicle type in HD TRUCS, we
referenced the work in the final rulemaking, Control of Air Pollution From New Motor Vehicles:
Heavy-Duty Engine and Vehicle Standards964 (HD2027 Low NOx Rule). The HD 2027 Final
Rule defined the consumption of DEF as a function of NOx reduction over the Selective Catalyst
Reduction (SCR) system considering Federal Test Procedure (FTP) emissions.965 The engine out
964 88 FR 4412 (January 24, 2023).
965 The relationship between DEF dose rate and NOx reduction across the SCR catalyst is based on methodology
presented in the Technical Support Document to the 2012 Non-conformance Penalties for On-highway Heavy-duty
Diesel Engines rule (the NCP Technical Support Document, or NCP TSD).
239
-------
and tailpipe NOx emissions as well as the DEF dosing rate from the HD 2027 Final Rule are
summarized below in Table 2-34.
Table 2-34 DEF Consumption Rates for Diesel Vehicles in HD TRUCS
Value
Engine-out NOx
(FTP g/hp-hr)
4.0
Tailpipe NOx
(FTP g/hp-hr)
0.2
DEF Dose Rate
(% of fuel consumed)
5.18%
The percentage of DEF dosing as a function of diesel fuel consumed was then multiplied by
the sum of Annual Gallons of Diesel Consumed - Driving and Annual Gallons of Diesel
Consumed - PTO (see Table 2-32), and the results are shown in Table 2-35. As discussed in RIA
Chapter 2.2.1.1.3, for the final version for HD TRUCS, we have assessed each year of operation
using the appropriate changes that occur over time for inputs such as VMT, maintenance and
repair, and fuel costs; however, we are continuing to show a 10-year average value in tables such
as the one below, as a single value point of comparison. Appendix A to this RIA includes each
year of a 10-year schedule for VMT.
Table 2-35 Annual DEF Consumption, 10 Year Average
Vehicle ID
Average Annual
Gallons of DEF
Consumed
01V Amb C14-5 MP
34
02V Amb C12b-3 MP
50
03V Amb C14-5 U
44
04V Amb C12b-3 U
45
05T Box C18 MP
119
06T Box C18 R
103
07T Box C16-7 MP
57
08T Box C16-7 R
55
09T Box C18 U
147
10T Box C16-7 U
61
11T Box C12b-3 U
67
12T Box C12b-3 R
56
13T Box C12b-3 MP
60
14T Box C14-5 U
43
15T Box C14-5 R
36
16T Box C14-5 MP
39
17B Coach C18 R
257
18B Coach C18 MP
257
19C Mix C18 MP
353
20T Dump C18 U
105
2IT Dump C18 MP
85
22T Dump C16-7 MP
95
23T Dump C18 U
105
24T Dump C16-7 U
104
25T Fire C18 MP
96
240
-------
Average Annual
Vehicle ID
Gallons of DEF
Consumed
26T Fire C18 U
119
27T Flat C16-7 MP
57
28T Flat C16-7 R
56
29T Flat C16-7 U
63
30Tractor DC C18
143
31Tractor DC C17
126
32Tractor SC C18
568
33Tractor DC C18
319
34T Ref C18 MP
186
35T Ref C16-7 MP
211
36T Ref C18 U
186
37T Ref C16-7 U
232
38RV C18 R
16
39RV C16-7 R
17
40RV C14-5 R
11
41Tractor DC C17
279
42RV C18 MP
16
43RV C16-7 MP
17
44RV C14-5 MP
12
45Tractor DC C18
319
46B School C18 MP
84
47B School C16-7 MP
80
48B School C14-5 MP
47
49B School C12b-3 MP
47
5OB School C18 U
105
5 IB School C16-7 U
80
52B School C14-5 U
53
53B School C12b-3 U
53
54Tractor SC C18
568
55B Shuttle C12b-3 MP
116
56B Shuttle C14-5 U
129
57B Shuttle C12b-3 U
129
58B Shuttle C16-7 MP
165
59B Shuttle C16-7 U
182
60S Plow C16-7 MP
67
6IS Plow C18 MP
94
62S Plow C16-7 U
74
63 S Plow C18 U
116
64V Step C16-7 MP
87
65V Step C14-5 MP
39
66V Step C12b-3 MP
59
67V Step C16-7 U
96
68V Step C14-5 U
43
69V Step C12b-3 U
65
70S Sweep C16-7 U
100
7 IT Tanker C18 R
96
72T Tanker C18 MP
109
73T Tanker C18 U
136
74T Tow C18 R
120
75T Tow C16-7 R
92
76T Tow C18 U
169
241
-------
Vehicle ID
Average Annual
Gallons of DEF
Consumed
77T Tow C16-7 U
104
78Tractor SC C18
406
79Tractor SC C18
568
80Tractor DC C18
228
81Tractor DC C17
279
82Tractor DC C18
319
83Tractor DC C17
156
84Tractor DC C18
177
85B Transit C18 MP
296
86B Transit C16-7 MP
112
87B Transit C18 U
296
88B Transit C16-7 U
124
89T Utility C18 MP
56
90T Utility C18 R
50
9IT Utility C16-7 MP
83
92T Utility C16-7 R
81
93T Utility C14-5 MP
59
94T Utility C12b-3 MP
27
95T Utility C14-5 R
54
96T Utility C12b-3 R
54
97T Utility C18 U
70
98T Utility C16-7 U
92
99T Utility C14-5 U
65
100T Utility C12b-3 U
30
lOlTractor DC C18
89
DEF costs were based on Table 7-31 in the RIA for the Control of Air Pollution from New
Motor Vehicles: Heavy-Duty Engine and Vehicle Standards,966 then adjusted from 2017$ to
2022$.
966 U.S. Environmental Protection Agency. Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine
and Vehicle Standards Regulatory Impact Analysis. See Table 7-31. Available at
https://nepis.epa.gov/Exe/ZvPDF.cgi?Dockev=P1016A9N.t)df
242
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Table 2-36 DEF Price per Gallon (2022$)
Calendar Year
DEF $/Gallon
2027
3.84
2028
3.89
2029
3.93
2030
3.98
2031
4.03
2032
4.08
2033
4.15
2034
4.20
2035
4.25
2036
4.30
2037
4.35
2038
4.42
2039
4.47
2040
4.54
2041
4.59
2.3.4.2 Maintenance and Repair Cost
Maintenance and repair costs contribute to the overall operating costs for HD vehicles. To
establish a baseline cost for maintenance and repair of diesel-fueled ICE vehicles, we relied on
the research compiled by Burnham et al. in Chapter 3.5.5 of "Comprehensive Total Cost of
Ownership Quantification for Vehicles with Different Size Classes and Powertrains"967'968 and
used equations found in the 2022 BEAN tool (see the "TCO" tab).969 Burnham et al. used data
from Utilimarc and American Transportation Research Institute (ATRI) to estimate maintenance
and repair costs per mile for multiple heavy-duty vehicle categories over time. In the proposal we
selected the box truck curve to represent vocational vehicles and short-haul tractors970, and the
semi-tractor curve to represent long-haul tractors. The box truck equation has a higher slope and
intercept than the semi-tractor equation which means that in the NPRM version of HD TRUCS,
vocational vehicle and short haul tractor diesel maintenance costs per mile (and therefore also the
ZEV M&R savings per mile) were much higher than the long-haul tractors' M&R costs (and
savings) per mile. Even though EPA did not receive any comments that specifically challenged
the underlying diesel M&R estimates, after consideration of comments more generally asserting
that M&R savings in our analysis were high, EPA is updating our approach for the final rule HD
TRUCS M&R analysis to be more conservative by using the semi-tractor equation for
calculating ICE vehicle maintenance and repair costs per mile for all vehicles. This change
reduces the overall maintenance cost estimates for ICE vehicles, which in turn reduces the
967 Burnham, Andrew, David Gohlke, Luke Rush, Thomas Stephens, Yan Zhou, Mark A. Delucchi, Alicia Birky,
Chad Hunter, Zhenhong Lin, Shiqi Ou, Fei Xie, Camron Proctor, Steven Wiryadinata, Nawei Liu, and Madhur
Boloor. "Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and
Powertrains". April 2021. Accessible online: https://publications.anl.gov/anlpubs/202l/05/167399.pdf.
968 Burnham, et al uses 2019$ in this report. See page 22 of
https://publications.anl.gov/anlpubs/2021/05/167399.pdf.
969 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
970 Short haul tractors and vocational vehicles were represented by the same M&R equation because they have duty
cycles and annual VMT that are similar.
243
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overall savings from ZEV M&R, since the savings values are estimated as a cost reduction from
the ICE vehicle maintenance and repair values. M&R cost per mile (2022$/mi) are shown in
Figure 2-3.
0.50
f 0.45
^ 0.40
CM
^ 0.35
M 0.30
^ 0.25
-------
Table 2-37 AEO 2023 Reference Case Diesel Price (2022$)
Calendar
Year
Diesel
Price
($/gal)
2027
3.74
2028
3.63
2029
3.65
2030
3.65
2031
3.67
2032
3.69
2033
3.71
2034
3.71
2035
3.74
2036
3.74
2037
3.76
2038
3.78
2039
3.78
2040
3.79
2041
3.81
2.3.4.4 Insurance cost
One commenter recommended using an insurance rate of 3%, based originally on an ICCT
April 2023 paper on ZEV TCO.972 We have considered these sources and found them
reasonable. Similar to State sales tax and the FET, insurance costs are calculated as a percentage,
after applying the RPE to the upfront technology costs shown in Table 2-26; however, unlike the
state sales tax and FET, the insurance costs are added to operating costs each year in HD
TRUCS, as part of the payback calculation. See Table 2-33 for MY 2032 ICE powertrain
insurance costs.
2.4 Battery Electric Vehicle Technology
For the purposes of comparing ICE and BEV technology costs and performance, this section
explains how we assessed heavy-duty BEVs based on the performance and use criteria in
Chapter 2.2. First, we determined BEV battery pack size,973 range, and peak motor power
requirements to meet energy and daily operational needs of each vehicle, and we projected
energy and fuel use for each vehicle type (kWh/mi) on an annual basis. Then, we projected the
DMC and RPE of BEV components and considered the impacts of the IRA battery and vehicle
tax credits for heavy-duty electric vehicles. We also then assessed the sales tax and FET cost of
the BEVs. Next, we determined the weight and physical volume of the battery pack for each of
the vehicles to evaluate the impact on payload capability. Lastly, we projected charging costs,
maintenance and repair costs, insurance costs, and an annual ZEV registration fee for each
972 Basma, Hussein, et.al. "Total Cost of Ownership of Alternative Powertrain Technologies for Class 8 Long-Haul
Trucks in the United States." April 2023. Page 17. Available online: https://theicct.org/wp-
content/uploads/2023/04/tco-alt-powertrain-long-haul-trucks-us-apr23.pdf
973 Please note that HD TRUCS focuses on the traction battery, which is the rechargeable battery that supplies power
to the electric motor.
245
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vehicle type for the first ten years of vehicle operation. Finally, we projected relevant operational
costs, for each year, for the first ten years of operation.
2.4.1 BEV Component Sizing
Two of the major components in a BEV are the battery and the motor. The size of these
components is determined by the needs of the specific vehicle. In HD TRUCS, we determined
the battery storage capacity, projected range of the vehicle, and peak motor power requirement
for each of the 101 vehicles represented in HD TRUCS, as described in the following two
subsections. The resulting values are shown in Table 2-38.
Table 2-38 Battery and Motor Sizes (MY 2032)
Vehicle ID
Battery Size (kWh))
Projected Electric
Range (mi)
Motor Peak Power
(kW)
01V Amb C14-5 MP
120
100
245
02V Amb C12b-3 MP
113
100
245
03V Amb C14-5 U
111
100
245
04V Amb C12b-3 U
104
100
245
05T Box C18 MP
244
100
322
06T Box C18 R
252
100
322
07T Box C16-7 MP
168
100
203
08T Box C16-7 R
183
100
203
09T Box C18 U
236
100
322
10T Box C16-7 U
162
105
203
11T Box C12b-3 U
100
100
245
12T Box C12b-3 R
118
100
245
13T Box C12b-3 MP
109
100
245
14T Box C14-5 U
100
100
245
15T Box C14-5 R
118
100
245
16T Box C14-5 MP
109
100
245
17B Coach C18 R
710
300
322
18B Coach C18 MP
1052
450
322
19C Mix C18 MP
428
100
322
20T Dump C18 U
283
111
322
2IT Dump C18 MP
286
111
322
22T Dump C16-7 MP
277
156
203
23T Dump C18 U
283
111
322
24T Dump C16-7 U
259
156
203
25T Fire C18 MP
300
111
322
26T Fire C18 U
301
111
322
27T Flat C16-7 MP
168
100
203
28T Flat C16-7 R
183
100
203
29T Flat C16-7 U
155
100
203
30Tractor DC C18
351
136
528
31Tractor DC C17
317
147
367
32Tractor SC C18
973
420
400
33Tractor DC C18
531
216
551
34T Ref C18 MP
355
118
322
35T Ref C16-7 MP
290
118
203
36T Ref C18 U
355
118
322
37T Ref C16-7 U
286
118
203
38RV C18 R
564
335
322
39RV C16-7 R
599
335
203
246
-------
Vehicle ID
Battery Size (kWh))
Projected Electric
Range (mi)
Motor Peak Power
(kW)
40RV C14-5 R
381
335
245
41Tractor DC C17
744
349
367
42RV C18 MP
564
335
322
43RV C16-7 MP
550
335
203
44RV C14-5 MP
350
335
245
45Tractor DC C18
891
349
528
46B School C18 MP
266
100
322
47B School C16-7 MP
160
100
203
48B School C14-5 MP
120
100
245
49B School C12b-3 MP
113
100
245
5OB School C18 U
252
100
322
5 IB School C16-7 U
160
100
203
52B School C14-5 U
111
100
245
53B School C12b-3 U
104
100
245
54Tractor SC C18
1164
420
400
55B Shuttle C12b-3 MP
164
150
245
56B Shuttle C14-5 U
158
150
245
57B Shuttle C12b-3 U
151
150
245
58B Shuttle C16-7 MP
264
150
203
59B Shuttle C16-7 U
245
150
203
60S Plow C16-7 MP
199
111
203
61S Plow C18 MP
394
156
322
62S Plow C16-7 U
187
111
203
63 S Plow C18 U
388
156
322
64V Step C16-7 MP
169
101
203
65V Step C14-5 MP
109
100
245
66V Step C12b-3 MP
109
100
245
67V Step C16-7 U
156
101
203
68V Step C14-5 U
100
100
245
69V Step C12b-3 U
100
100
245
70S Sweep C16-7 U
182
100
203
7IT Tanker C18 R
269
100
322
72T Tanker C18 MP
264
100
322
73T Tanker C18 U
263
100
322
74T Tow C18 R
413
157
322
75T Tow C16-7 R
300
157
203
76T Tow C18 U
400
157
322
77T Tow C16-7 U
261
157
203
78Tractor SC C18
834
300
400
79Tractor SC C18
1164
420
400
80Tractor DC C18
647
180
450
81Tractor DC C17
531
216
367
82Tractor DC C18
635
216
528
83Tractor DC C17
459
214
367
84Tractor DC C18
356
120
528
85B Transit C18 MP
472
203
322
86B Transit C16-7 MP
373
219
203
87B Transit C18 U
472
203
322
88B Transit C16-7 U
341
219
203
89T Utility C18 MP
254
100
322
90T Utility C18 R
261
100
322
9IT Utility C16-7 MP
184
100
203
247
-------
Vehicle ID
Battery Size (kWh))
Projected Electric
Range (mi)
Motor Peak Power
(kW)
92T Utility C16-7 R
198
100
203
93T Utility C14-5 MP
120
100
245
94T Utility C12b-3 MP
114
100
245
95T Utility C14-5 R
128
100
245
96T Utility C12b-3 R
128
100
245
97T Utility C18 U
250
100
322
98T Utility C16-7 U
174
100
203
99T Utility C14-5 U
113
100
245
100T Utility C12b-3 U
106
100
245
lOlTractor DC C18
279
108
528
2.4.1.1 Battery Pack Energy
In HD TRUCS, we sized the battery based on the expected energy required for the vehicle to
complete operations (i.e., based on the daily sizing VMT). This daily energy consumption is a
function of miles the vehicle is driven and the energy it consumes because of: (1) energy at the
axle used to move the vehicle per unit mile, including the impact of regenerative braking, and
operational PTO974 energy requirements (together this energy required to perform required work
is the "ZEV baseline energy"), (2) battery conditioning and HVAC energy requirements, and (3)
BEV efficiency, depth of discharge, and deterioration.
The ZEV baseline energy loads are described in RIA Chapter 2.2.2 and are reported in terms
of kWh/mi, which are then converted into kWh/day using the daily sizing VMT as previously
described in RIA Chapter 2.2.1.2.2.
The energy required to maintain the battery at a constant temperature (battery conditioning)
and to heat and cool interior cabins (HVAC) are considered separately from the baseline energy,
since these energy loads are not required year-round or in all regions of the country. The HVAC
energy is calculated as a power requirement, which is converted into an energy requirement by
multiplying the HVAC power by the 8-hour operational day. The battery conditioning energy
requirements are determined as a percent of total battery size; a detailed explanation of battery
conditioning may be found in RIA Chapters 2.4.1.1.1 and 2.5.1.2.2.
The total daily battery demand is assumed to be the sum of the daily ZEV baseline energy
(including regenerative braking and PTO) as well as battery conditioning and HVAC. The
appropriate losses from the BEV powertrain system are applied to the battery size. Also, the
battery is oversized based on the level of depth of discharge for an EV battery and to compensate
for deterioration of the battery over time if the battery is expected to exceed 2000 cycles before
the tenth year of operation. A detailed explanation of the oversizing parameters may be found in
RIA Chapter 2.4.1.1.3 and RIA Chapter 2.4.1.1.4. The battery pack size for MY 2032 is shown
in Table 2-38 for each of the 101 vehicle types.
974 PTO energy consumption is calculated from the benchmark diesel operational fuel consumption (operational
VMT), rather than the sizing energy consumption (sizing VMT). While batteries are sized using the sizing VMT to
calculate the daily propulsion energy, we think that PTO usage per day is unlikely to vary proportionally with the
high mileage activity of the sizing VMT.
248
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2.4.1.1.1 HVAC Considerations in a BEV
In this subsection, we describe the HVAC energy requirements, which vary by the cabin size
of the vehicle, and our approach to considering different HVAC requirements across the U.S.
For BEVs, the energy required for cabin thermal management is different than for ICE
vehicles because the vehicle is not able to utilize excess (waste) heat from an engine. BEVs
could be equipped with either a positive temperature coefficient (PTC) heater with a traditional
A/C, or a full heat pump system. (See RIA Chapter 1 for a description of both). Because heat
pumps are many times more efficient than a PTC heater, a smaller battery is required for the
same duty cycle. This will likely make heat pumps a cost-effective solution in the heavy-duty
sector, considering the avoided upfront costs of a sufficiently larger battery and reduced
electricity costs during operation. Given the success and increasing adoption of heat pumps in
light-duty EVs, we project the use of heat pumps for heavy-duty vehicles in our HD TRUCS
analysis.
To estimate HVAC energy consumption of ZEVs in HD TRUCS, we performed a literature
and market review. Even though there are limited real-world studies, we agreed with the HVAC
modeling approach described in Basma et. al.975 This physics-based cabin thermal model
considers four vehicle characteristics: the cabin interior, walls, and materials, as well as the
number of passengers. The authors modelled a Class 8 electric transit bus with an HVAC system
consisting of two 20 kW-rated reversible heat pumps, an air circulation system, and a battery
thermal management system. The HVAC control strategy is a traditional on-off controller. The
modeled power demand as a function of ambient temperature for the Class 8 transit bus is shown
in Figure 2-4. In response to our request for data in the NPRM on HVAC loads for BEVs, we
received additional modeling data from one commenter that included HVAC loads for European
long-haul tractors. We found the new data to be corroborative with our HVAC loads and the
sleeper cab scaling factor; therefore, we continued to use the same HVAC power demand model
in the final rule version of HD TRUCS.
975 Basma, Hussein, Charbel Mansour, Marc Haddad, Maroun Nemer, Pascal Stabat. "Comprehensive energy
modeling methodology for battery electric buses". Energy: Volume 207, 15 September 2020, 118241. Available
online: https://www.sciencedirect.com/science/article/pii/S0360544220313487.
249
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Figure 2-4 Modeled HVAC Power Demand of a Class 8 Transit Bus as a Function of Ambient Temperature
We recognize that HVAC is not evenly used across the nation. For example, some regions
will be more reliant on heater use while others may depend more on air conditioning. The energy
used for HVAC consumption in HD TRUCS is HVAC energy consumption using Basma for
power demand at a specific temperature and weighted by the percent HD VMT traveled at a
specific temperature range.976 To properly account for the temperature variation throughout the
nation and throughout the year, we calculated the percent of HD VMT for several temperature
bins as available from MOVES; this national distribution of VMT as a function of temperature is
shown in Figure 2-5. For example, if power demand from HVAC at 75 °F is 1 kW and 9.3
percent of HD VMT percent occurs at 75 °F, then the VMT-weighted energy demand is equal to
0.093 kW. Once multiplied, we summed the values that are less than 55 °F and divided by the
percent VMT for temperatures below 55 °F. However, for the final rule analysis, considering
Figure 2-4 and Figure 2-5, HVAC loads are the highest for temperatures less than 55 °F and for
greater than 75 °F, so we made an adjustment to HD TRUCS to reflect a wider range of cooling
temperatures (as compared to the proposed greater than 80 °F). This creates three separate bins -
one for heating (<55 °F), one for cooling (>75 °F), and one for a temperature range that requires
only ventilation (55-75 °F), so we simplified the temperature bins further in HD TRUCS to only
include three bins (<55 °F, 55-75 °F, >75 °F). The results of the VMT-weighted HVAC power
demand for a Class 8 Transit Bus for each of the HVAC temperature bins are shown in Table
2-39. In HD TRUCS, we already accounted for the energy loads due to ventilation in the axle
loads, so no additional energy consumption is applied here for the ventilation-only operation. We
then weighted the power demands by the percent HD VMT traveled at each specific temperature
range, as shown in Table 2-40.
976 It should be noted that Basma model has discrete values in Celsius and MOVES data has discrete values in
Fahrenheit. The Basma discrete values in the Basma model is fitted to a parabolic curve and converted into
Fahrenheit to best fit the VMT distribution that is available in MOVES.
250
-------
00
>
Q
1
~ra
i—
£
H
>
<30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 >90
Temperature (F)
Figure 2-5 MOVES National VMT Distribution as a Function of Temperature for 2b-8 HD Vehicles
Table 2-39 HD TRUCS HVAC Power Consumption of a Class 8 Transit Bus
Temperature (°F)
Consumption (kW)
Heating
<55
5.06
Ventilation
55-75
0.00
Cooling
>75
2.01
Table 2-40 Distribution of VMT for HD TRUCS Temperature Bins
Temperature Bins
Heating
<55 °F
55-75 °F
Cooling
>75 °F
% VMT
37%
16%
47%
HVAC load is dependent on cabin size—the larger the size of the cabin, the greater the
HVAC demand. The values for HVAC power demand shown in Table 2-39 represent the power
demand to heat or cool the interior of a Class 8 transit bus. However, HD vehicles have a range
of cabin sizes; therefore, we developed scaling ratios relative to the cabin size of a Class 8 bus as
derived from Equation 2-20 discussed in Chapter 2.8.5.1 with the results shown in Table 2-41.
Each vehicle's scaling factor is based on the surface area of the vehicle compared to the surface
area of the Class 8 bus. Cabin sizes for most HD vehicle types have a similar cabin to a mid-size
light duty vehicle and therefore, an average scaling factor of 0.2 was applied to all of those
vehicle types.977 The buses and sleeper cab tractors have cabin sizes similar to the transit bus or
977 The interior cabin where the driver and passengers sit are heated while where the cargo is stored is not heated.
251
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scaled down to reflect its cabin size. For example, a Class 4-5 shuttle bus has a cabin size ratio
0.6; in this case, the heating demand for the vehicle will be 3.04 kW (equal to 5.06 kW
multiplied by 0.6) and the cooling demand would be 1.21 kW (2.01 kW multiplied by 0.6).
Table 2-41 Vehicle Surface Area as a Function of a Class 8 Transit Bus Surface Area
Vehicle ID
Cabin Size ratio
01V Amb C14-5 MP
0.6
02V Amb C12b-3 MP
0.4
03V Amb C14-5 U
0.6
04V Amb C12b-3 U
0.4
05T Box C18 MP
0.2
06T Box C18 R
0.2
07T Box C16-7 MP
0.2
08T Box C16-7 R
0.2
09T Box C18 U
0.2
10T Box C16-7 U
0.2
11T Box C12b-3 U
0.2
12T Box C12b-3 R
0.2
13T Box C12b-3 MP
0.2
14T Box C14-5 U
0.2
15T Box C14-5 R
0.2
16T Box C14-5 MP
0.2
17B Coach C18 R
1.0
18B Coach C18 MP
1.0
19C Mix C18 MP
0.2
20T Dump C18 U
0.2
2IT Dump C18 MP
0.2
22T Dump C16-7 MP
0.2
23T Dump C18 U
0.2
24T Dump C16-7 U
0.2
25T Fire C18 MP
0.2
26T Fire C18 U
0.2
27T Flat C16-7 MP
0.2
28T Flat C16-7 R
0.2
29T Flat C16-7 U
0.2
30Tractor DC C18 MP
0.2
31Tractor DC C16-7 MP
0.2
32Tractor SC C18 U
0.3
33Tractor DC C18 U
0.2
34T Ref C18 MP
0.2
35T Ref C16-7 MP
0.2
36T Ref C18 U
0.2
37T Ref C16-7 U
0.2
38RV C18 R
0.2
39RV C16-7 R
0.2
40RV C14-5 R
0.2
41Tractor DC C17 R
0.2
42RV C18 MP
0.2
43RV C16-7 MP
0.2
44RV C14-5 MP
0.2
45Tractor DC C18 R
0.2
46B School C18 MP
1.0
47B School C16-7 MP
0.7
252
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Vehicle ID
Cabin Size ratio
48B School C14-5 MP
0.6
49B School C12b-3 MP
0.4
5OB School C18 U
0.7
5 IB School C16-7 U
0.7
52B School C14-5 U
0.6
53B School C12b-3 U
0.4
54Tractor SC C18 R
0.3
55B Shuttle C12b-3 MP
0.4
56B Shuttle C14-5 U
0.6
57B Shuttle C12b-3 U
0.4
58B Shuttle C16-7 MP
0.7
59B Shuttle C16-7 U
0.7
60S Plow C16-7 MP
0.2
6IS Plow C18 MP
0.2
62S Plow C16-7 U
0.2
63 S Plow C18 U
0.2
64V Step C16-7 MP
0.2
65V Step C14-5 MP
0.2
66V Step C12b-3 MP
0.2
67V Step C16-7 U
0.2
68V Step C14-5 U
0.2
69V Step C12b-3 U
0.2
70S Sweep C16-7 U
0.2
7 IT Tanker C18 R
0.2
72T Tanker C18 MP
0.2
73T Tanker C18 U
0.2
74T Tow C18 R
0.2
75T Tow C16-7 R
0.2
76T Tow C18 U
0.2
77T Tow C16-7 U
0.2
78Tractor SC C18 MP
0.3
79Tractor SC C18 R
0.3
80Tractor DC C18 HH
0.2
81Tractor DC C17 R
0.2
82Tractor DC C18 R
0.2
83Tractor DC C17 U
0.2
84Tractor DC C18 U
0.2
85B Transit C18 MP
0.7
86B Transit C16-7 MP
0.7
87B Transit C18 U
0.7
88B Transit C16-7 U
0.7
89T Utility C18 MP
0.2
90T Utility C18 R
0.2
9IT Utility C16-7 MP
0.2
92T Utility C16-7 R
0.2
93T Utility C14-5 MP
0.2
94T Utility C12b-3 MP
0.2
95T Utility C14-5 R
0.2
96T Utility C12b-3 R
0.2
97T Utility C18 U
0.2
98T Utility C16-7 U
0.2
99T Utility C14-5 U
0.2
253
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Vehicle ID
Cabin Size ratio
100T Utility C12b-3 U
0.2
lOlTractor DC C18 U
0.2
2.4.1.1.2 Effects of Temperature on the Battery
Battery range and life can be impacted by ambient temperatures, as described in Chapter 1.
Therefore, BEVs have thermal management systems to maintain battery core temperatures
within an optimal range of approximately 68 to 95 degrees Fahrenheit (F) (20 to 35 degrees
Celsius).978 Since BEVs may not have an additional energy source beyond what is stored inside
the battery, some stored energy in the battery is used to maintain a constant battery temperature.
The Basma et al. report discusses the battery conditioning power requirements at various
temperatures. Figure 2-6, based on Basma et. al, shows the power demand for battery
conditioning as a function of ambient temperature.979
Figure 2-6 Modeled Power Demand for Battery Conditioning for Class 8 Transit Bus with a 300 kWh Battery
For this we determined the energy consumed to maintain a constant battery temperature for
ambient temperature ranges presented in the Basma et. al paper as well as the HD VMT
distribution by temperature in MOVES Similar to the methods used for HVAC in RIA Chapter
2.4.1.1.1, we determined the VMT-weighted battery conditioning loads associated with
requirements to heat the battery in cold operating temperatures (below 55 °F) and cool the
battery during operations in warm temperatures (over 75 °F for the final version of HD TRUCS).
For the ambient temperatures between these two regimes, we agreed with Basma, et. al that only
ambient air cooling is required for the batteries, which requires no additional load. We
978 Ibid.
979 Basma, Hussein, Charbel Mansour, Marc Haddad, Maroun Nemer, Pascal Stabat. "Comprehensive energy
modeling methodology for battery electric buses". Energy: Volume 207, 15 September 2020, 118241. Available
online: https://www.sciencedirect.com/science/article/pii/S0360544220313487.
254
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determined a VMT-weighted power consumption value for battery heating and cooling based on
the MOVES HD VMT distribution. Then, we determined the energy required for battery
conditioning required for eight hours of daily operation and expressed it in terms of percent of
total battery size. Table 2-42 shows the energy consumption for battery conditioning for both hot
and cold ambient temperatures, expressed as a percentage of battery capacity, used in HD
TRUCS. Some commenters noted heavy-duty vehicles operate in temperatures less than 30 °F,
and we recognize heavy-duty vehicles are used in extreme temperatures. The battery heating
energy needs shown in Table 2-42 are weighted using the MOVES HD VMT distribution as a
function of temperature shown in Figure 2-5, which accounts for operation at temperature less
than 30°F.Our assessment is that the battery heating requirements for operations under 30 °F
would require approximately 10% of the battery energy consumption and therefore the daily
operating VMT could still be met for the BEVs. Furthermore, during the timeframe of this final
rule ICE vehicles will be available and could also be used in those circumstances.
Table 2-42 VMT Weighted Battery Conditioning Energy Consumption
Ambient Temperature (°F)
Energy Consumption (%)
Battery Heating
<55
1.9%
Battery Cooling
>75
3.0%
2.4.1.1.3 Determining BEV Battery Size
In HD TRUCS, the ZEV baseline energy, HVAC, and battery conditioning demands are
summed for one operational day. The HVAC and battery conditioning demands are added using
a weighted average of these demands by the temperature bins in Table 2-40. These values are
used to determine BEV battery size.
We determined the axle energy required to move the vehicle over its drive cycle at the
specified payload, as described in RIA Chapter 2.2.2.1. Then, to determine the energy required at
the battery, we account for losses in the inverter, gearbox, and electric motor (e-motor). These
losses for the inverter, gearbox, and e-motor are calculated using loss maps of each
component.980'981 Table 2-43 includes a summary of the data used for the analysis. As outlined in
Table 2-43, we evaluated different components for Light and Medium HDVs (iDM HVH250-
115 and iDM 190) than for Heavy HDVs (HVH320-216 and the 3 Speed BorgWarner gear box).
This was because the iDM HVH250-115 and iDM 190 are representative of an e-motor and
gearbox that would be installed in a Class 5 vehicle, and HVH320-216 and the 3 Speed
BorgWarner gear box are representative of components that would be installed in a Class 8
tractor. Since we did not have data for each of the 101 vehicle IDs in HD TRUCS, vehicle data
from representative Vehicle IDs was used to determine system efficiency for each GEM duty
cycle and then we weighted the efficiency for each duty cycle based on the specific weighting
factors for each regulatory subcategory.
980 The loss maps for the inverter, gearbox, and e-motor were provided to the agency as claimed confidential
business information from BorgWarner. We examined the loss maps carefully and find the information reliable.
981 Sanchez, James. Memorandum to Docket EPA-HQ-OAR-2022-0985. "Estimating Electric Powertrain Efficiency
with CBI Data Provided by BorgWarner" February 28, 2024.
255
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Table 2-43 Summary of Inverter, Gearbox, and E-motor Data Used for Each Vehicle ID
Vehicle ID Data was
used for
Light Heavy and Medium
Heavy Vocational
Vehicles
Heavy Heavy Vocational
Vehicles and Tractors
E-motor
iDM HVH250-115
HVH320-216
Gearbox
iDM 190
3 speed BorgWarner
Inverter technology
Silicon Carbide
Silicon Carbide
GEM Energy ID
16T_Box_CI4-5_MP
78T ractor_SC_C18_MP
To determine the efficiency for each component, the loss maps were interpolated for each
duty cycle based on the axle speed and torque. The axle speed and torque were determined using
the vehicle parameters for GEM vehicle ID 16 and 78 as show in Table 2-43. For the inverter, we
used a silicon carbide (SiC) based inverter for both sets of vehicles. For the heavy heavy-duty
vocational and tractors this was done by using a loss map from a SiC inverter. For the light and
medium heavy-duty vocational vehicles, the provided data was from a silicon (Si) based inverter,
so we modified the efficiency of the inverter to be representative of a SiC based inverter. This
was done using data from a mid-size SUV where we had loss maps for both Si and SiC based
inverters. The absolute efficiency improvement for the SiC versus the Si inverter was 4 percent,
0.5 percent, and 0.5 percent for the transient, 55mph cruise, and 65mph cruise cycles. The
absolute efficiencies were then added to the efficiencies of the Class 5 Si based inverter. The
combined efficiency values of the components are shown in Table 2-44.
256
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Table 2-44 Combined Inverter, Gearbox, and E-motor Efficiency for each GEM Energy ID
GEM Energy ID
Combined inverter, gearbox,
and e-motor efficiency
C7 DC HR
91%
C8 DC HR
91%
C8 HH
91%
C8 SC HR
93%
C8 SC HR CdA036
93%
C8 DC HR CdA036
91%
HHD R
91%
HHD M
88%
HHD U
84%
MHD R
89%
MHD M
86%
MHD U
83%
LHD R
89%
LHD M
86%
LHD U
83%
RV
89%
School Bus
83%
Coach Bus
91%
Emergency
84%
Concrete Mixer
84%
Transit Bus
84%
Refuse Truck
84%
When sizing the battery, we also accounted for the battery depth of discharge, or the amount
of charge or discharge level during a charge or discharging cycle, and battery deterioration over
time. We received numerous comments about limiting depth of discharge to 80 percent as well as
20 percent extra battery capacity to account for battery deterioration over time, as described in
RTC Section 3.3.3. Some of these commenters said we should reduce or remove the additional
20 percent of extra battery capacity for degradation and the 80 percent depth of discharge. Others
pointed out that batteries degrade over time and will reduce in capacity, up to 3 percent annual
capacity loss.
One commenter cited a February 2022 Roush report on the electrification of tractors where
Roush had set the depth of discharge to 90 percent and a 10 percent battery degradation value
and suggested using those values. They also pointed out that the decrease in VMT over time used
in the proposal's version of HD TRUCS for calculating operating costs meets or exceeds the 20
percent reduction in battery capacity over that same time. They argued that the decrease in VMT
already accounts for 20 percent battery deterioration and that it should not be included, or that
EPA should adopt the 10 percent value that Roush used in their report. Another commenter
questioned the source for a 20 percent battery capacity fade. They agreed that batteries will
degrade over time but stated that data is scarce for HD applications and that recent developments
in battery technology have resulted in prolonged battery life with long-distance BEVs reaching
over 900,000 miles. Another commenter stated that the additional 20 percent battery sizing for
deterioration was an overly conservative estimate and that fleets would adjust the mileage and
routes used for a vehicle over time as they currently do with ICE vehicles from the secondary
market. They stated that fleets would not pay for the additional unused battery capacity. This
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commenter also raised concerns about using an 80 percent depth of discharge value saying that it
would be more appropriate to model battery usage and mileage based on capacity fade and citing
a demonstration by Yang et al. and Dunn et al. Another commenter stated that oversizing the
battery harms the projected rate of BEV adoption due to increased costs attributable to the extra
battery capacity. Relatedly, a few commenters raised concerns about the cost of replacing a
vehicle battery. They stated that is a very large cost that should be accounted for.
After considering these comments, and further supported by the depth of discharge window
value used in the 2022 Autonomie tool from ANL, we revised the battery depth of discharge
window to 90 percent in HD TRUCS.982'983 We separately address the battery deterioration as
discussed in the following subsection.
2.4.1.1.4 Battery Cycling and Deterioration Addition
As at proposal, we continue to account for battery deterioration in our analysis. However,
after consideration of comments, including comments that the proposal was overly conservative
and other comments that EPA had failed to account for battery replacement, we updated our
methodology to do so. Rather than oversize the battery (analytically) by a constant factor of 20%
as at proposal (see DRIA at p. 165), in the final rule, we determined the battery deterioration
factor for each of the 101 vehicle applications based on the number of charging cycles the battery
would require during its first ten years of operation. Ten years represents the longest payback
period we consider for the technologies in our HD TRUCS analysis for MYs 2027-2032.
To better assess the number of cycles a battery will go through in a 10-year time frame, we
modeled the number of charge and discharge cycles in HD TRUCS, based on the operating
VMT. Here, a single full cycle is considered to be when a battery is completely discharged of
energy and fully recharged of energy. Since the daily use of energy is less than the total amount
of energy stored in the battery, one full cycle can be extended to more than one day. Annual
number of cycles is computed using the number of cycles per day and the number of operating
days.
For example, a battery with an operating VMT of 50 miles and operating energy consumption
of 2 kWh/mi will use 100 kWh per day. If the battery has a usable energy of 200 kWh, this
battery will go through half a cycle per day or one full cycle every two days. For this example,
the annual number of cycles would be 125 cycles using 250 operating days in year one of
operation.
The cumulative number of cycles is then summed over 10 years using this same method.
Since the operating VMT changes each year based on the MOVES schedule for each source type
ID as described in RIA Chapter 2.2.1.2.3, the annual number of cycles will change each year.
We selected 2,000 cycles as our number of cycles target at 10 years of age while recognizing
this value depends on a number of internal and external parameters including battery chemistry,
the discharge window while cycling, power output of the battery, and how the battery is
982 In the "Battery" tab, we calculated the difference between the "SOC Max" and "SOC Min" columns for BEVs
and chose the lowest depth of discharge as a conservative value.
983 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - MD HD Truck
- Autonomie Assumptions.xlsx". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
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managed while in and not in use. A study shows LFP batteries can maintain 80 to 95 percent
state of charge at 3,000 cycles and NMC batteries can retain 80 percent state of charge at 2,000
cycles under some test conditions.984'985 c Using this method for the final version of HD TRUCS,
there is not a need for battery replacement during the first 10 years of vehicle operation, which
would otherwise be an additional cost. We note that only eight vehicles of the 101 in HD
TRUCS required a 15 percent increase in battery size to meet the 2,000-cycle limit over a 10-
year period. Most of the 101 vehicle types would experience less than 1,500 cycles over the 10-
year period.
Outside of HD TRUCS, we accounted for the cost of battery replacements (and parallel
engine rebuilding costs for ICE vehicles) in the program cost analysis as a purchaser cost, as
discussed in RIA Chapter 3.4.6.5.
2.4.1.2 E-Motor Sizing Based on Power Needs
The electric motor (e-motor) is part of the electric drive system that converts the electric
power from the battery or fuel cell into mechanical or motive power to move the wheels of the
vehicle. In the case of a BEV, there are losses associated with converting current and voltage
output from the electric motor into mechanical power at any given time. The e-motor is sized to
meet the peak power requirements of each vehicle in HD TRUCS.
BEVs operate at peak power to accelerate up to a driving speed and to climb steep inclines at
a reasonable pace. Peak power requirements are important to ensure that BEVs can match the
speed-related performance of comparable ICE vehicles. Peak power is the maximum power
required to perform the work of an HD vehicle. To estimate peak power needs to size the e-
motor, we used the maximum power among the peak power requirement generated from the
following performance targets: the peak required during the ARB transient cycle986 and
performance targets included in ANL's 2021 Autonomie model987 (see "0-30mph", "0-60mph"
in the Performance Sizing tab) and in Islam et al988 (for 6 percent Grade Speed), as indicated in
Table 2-45. We assigned the target maximum time to accelerate a vehicle from stop to 30 mph
and 60 mph based on weight class of each vehicle. We also used the criteria that the vehicle must
984 Preger, Yuliya, et. al. "Degradation of Commercial Lithium-Ion Cells as a Function of Chemistry and Cycling
Conditions". Journal of The Electrochemical Society. September 2, 2020. Available online:
https://iopscience.iop.org/article/10.1149/1945-71 ll/abae37.
985 Tankou, Alexander, Georg Bieker, and Dale Hall. "White Paper—Scaling Up Reuse and Recycling of Electric
Vehicle Batteries: Assessing Challenges and Policy Approaches". International Council on Clean Transportation.
February 2023. Available online: https://theicct.org/wp-content/uploads/2023/02/recycling-electric-vehicle-
batteries-feb-23 .pdf.
986 EPA uses three representative duty cycles for calculating Carbon Dioxide (CO2) emissions in GEM: transient
cycle and two highway cruise cycles. The ARB transient duty cycle was developed by the California Air Resources
Board (CARB) and includes no grade—just stops and starts. The highway cruise duty cycles represent 55-mph and
65-mph vehicle speeds on a representative highway. They use the same drive cycle profile but at different vehicle
speeds, along with a percent grade ranging from -5 percent to +5 percent.
987 Argonne National Laboratory. VTO HFTO Analysis Reports - 2021. "ANL - ESD-2110 Report - BEAN Tool -
Heavy Duty Vehicle Techno-Economic Analysis.xlsx". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4ilhk/folder/177858439896.
988 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6, October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1406494585829.
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be able to maintain a specified cruise speed while traveling up a road with a 6 percent grade, as
shown in Table 2-45. In the case of cruising at 6 percent grade, the road load calculation is set at
a constant speed for each weight class bin on a hill with a 6 percent incline. We determined the
required power rating of the motor as the greatest power required to drive the vehicle over the
ARB transient test cycle, at 55 mph and 65 mph constant cruise speeds, or at constant speed at 6
percent grade, for all vehicles except sleeper cab and heavy haul tractors. For sleeper cabs, the
motor size was determined to be 400 kW based on the comparable ICE sleeper cab tractor engine
power and the continuous motor power of existing HD BEV tractors.989 For heavy haul tractors,
the BEV motor power is set at 450 kW to reflect the maximum engine power of a heavy heavy-
duty engine.990 The NPRM version of HD TRUCS included a motor efficiency loss; however,
we have corrected this for the final rule, as motors are generally sold using their delivered power.
Because HD TRUCS motor sizing is largely used to estimate the cost of motors, the application
of an efficiency loss is not appropriate for purposes of estimating costs.
Table 2-45 ANL Performance Targets
Vocational
Tractors
Weight Class Bin
2b-3
4-5
6-7
8
7
8
0-30 mph Time (s)
7
8
16
20
18
20
0-60 mph Time (s)
25
25
50
100
60
100
Cruise Speed (mph) a 6 % grade
65
55
45
25
35
25
Consistent with the NPRM, for the final version of HD TRUCS, we calculated the motor
mass using a kg/kW factor derived from ANL's 2021 BEAN tool.991 This factor is calculated
from the "Autonomie Out Import" tab for MY 2027 by averaging the low and high results of
Motor l kg divided by MotorPeakkW for BEV vehicles. This factor is then used in HD
TRUCS by multiplying the factor by the HD TRUCS motor peak power, as shown in Table 2-38.
2.4.2 Battery Weight and Volume
Performance needs of a BEV could result in a battery that is so large or heavy that it
negatively impacts payload and, thus, potential work accomplished relative to a comparable ICE
vehicle. We determined the battery weight and physical volume for each vehicle application in
HD TRUCS using the specific energy and energy density of the battery for each battery capacity.
The resulting values for 101 HD TRUCS vehicle types are shown in Table 2-46 and the detailed
descriptions for weight and volume determinations, as well as descriptions of specific energy
(Wh/kg) and energy density (Wh/L), are described in RIA Chapters 2.4.2.1 and 2.4.2.2. Here, the
battery size in kWh is converted into liters (L) and cubic meters (m3) using the energy density of
the battery. For further discussion on battery volume and the packaging assessments, see RIA
Chapter 2.9.1.
989 Peterbilt. 579EV. Available online: https://www.peterbilt.com/trucks/electric/579EV.
990 Detroit Diesel Engines. Available online: https://www.demanddetroit.com/engines/ddl6/.
991 Argonne National Laboratory. VTO HFTO Analysis Reports - 2021. "ANL - ESD-2110 Report - BEAN Tool -
Heavy Duty Vehicle Techno-Economic Analyisis". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4ilhk/folder/177858439896.
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Table 2-46 Battery Size, Weight, and Volume in HD TRUCS
Vehicle ID
Battery Size
(kWh)
Battery
Weight (kg)
Battery Volume
(mA3)
01V Amb C14-5 MP
120
604
0.30
02V Amb C12b-3 MP
113
570
0.28
03V Amb C14-5 U
111
563
0.28
04V Amb C12b-3 U
104
528
0.26
05T Box C18 MP
244
1231
0.62
06T Box C18 R
252
1272
0.64
07T Box C16-7 MP
168
850
0.42
08T Box C16-7 R
183
924
0.46
09T Box C18 U
236
1193
0.60
10T Box C16-7 U
162
819
0.41
11T Box C12b-3 U
100
505
0.25
12T Box C12b-3 R
118
596
0.30
13T Box C12b-3 MP
109
548
0.27
14T Box C14-5 U
100
505
0.25
15T Box C14-5 R
118
596
0.30
16T Box C14-5 MP
109
548
0.27
17B Coach C18 R
710
3588
1.79
19C Mix C18 MP
428
2160
1.08
20T Dump C18 U
283
1427
0.71
2IT Dump C18 MP
286
1446
0.72
22T Dump C16-7 MP
277
1400
0.70
23T Dump C18 U
283
1427
0.71
24T Dump C16-7 U
259
1310
0.66
25T Fire C18 MP
300
1518
0.76
26T Fire C18 U
301
1521
0.76
27T Flat C16-7 MP
168
850
0.42
28T Flat C16-7 R
183
924
0.46
29T Flat C16-7 U
155
784
0.39
30Tractor DC C18
351
1773
0.89
31Tractor DC C17
317
1603
0.80
32Tractor SC C18
973
4914
2.46
33Tractor DC C18
531
2682
1.34
34T Ref C18 MP
355
1791
0.90
35T Ref C16-7 MP
290
1462
0.73
36T Ref C18 U
355
1791
0.90
37T Ref C16-7 U
286
1443
0.72
38RV C18 R
564
2847
1.42
39RV C16-7 R
599
3027
1.51
40RV C14-5 R
381
1926
0.96
42RV C18 MP
564
2847
1.42
43RV C16-7 MP
550
2775
1.39
44RV C14-5 MP
350
1765
0.88
46B School C18 MP
266
1345
0.67
47B School C16-7 MP
160
810
0.41
48B School C14-5 MP
120
604
0.30
49B School C12b-3 MP
113
570
0.28
5OB School C18 U
252
1274
0.64
5 IB School C16-7 U
160
810
0.41
52B School C14-5 U
111
563
0.28
53B School C12b-3 U
104
528
0.26
261
-------
Vehicle ID
Battery Size
(kWh)
Battery
Weight (kg)
Battery Volume
(mA3)
54Tractor SC C18
1164
5877
2.94
55B Shuttle C12b-3 MP
164
829
0.41
56B Shuttle C14-5 U
158
799
0.40
57B Shuttle C12b-3 U
151
764
0.38
58B Shuttle C16-7 MP
264
1332
0.67
59B Shuttle C16-7 U
245
1236
0.62
60S Plow C16-7 MP
199
1007
0.50
61S Plow C18 MP
394
1991
1.00
62S Plow C16-7 U
187
943
0.47
63 S Plow C18 U
388
1957
0.98
64V Step C16-7 MP
169
856
0.43
65V Step C14-5 MP
109
548
0.27
66V Step C12b-3 MP
109
548
0.27
67V Step C16-7 U
156
790
0.39
68V Step C14-5 U
100
505
0.25
69V Step C12b-3 U
100
505
0.25
70S Sweep C16-7 U
182
919
0.46
7IT Tanker C18 R
269
1361
0.68
72T Tanker C18 MP
264
1336
0.67
73T Tanker C18 U
263
1329
0.66
74T Tow C18 R
413
2086
1.04
75T Tow C16-7 R
300
1518
0.76
76T Tow C18 U
400
2019
1.01
77T Tow C16-7 U
261
1316
0.66
78Tractor SC C18
834
4211
2.11
80Tractor DC C18
647
3267
1.63
81Tractor DC C17
531
2682
1.34
82Tractor DC C18
635
3207
1.60
83Tractor DC C17
459
2319
1.16
84Tractor DC C18
356
1799
0.90
85B Transit C18 MP
472
2383
1.19
86B Transit C16-7 MP
373
1882
0.94
87B Transit C18 U
472
2383
1.19
88B Transit C16-7 U
341
1724
0.86
89T Utility C18 MP
254
1285
0.64
90T Utility C18 R
261
1318
0.66
9IT Utility C16-7 MP
184
931
0.47
92T Utility C16-7 R
198
1001
0.50
93T Utility C14-5 MP
120
606
0.30
94T Utility C12b-3 MP
114
575
0.29
95T Utility C14-5 R
128
647
0.32
96T Utility C12b-3 R
128
647
0.32
97T Utility C18 U
250
1263
0.63
98T Utility C16-7 U
174
877
0.44
99T Utility C14-5 U
113
571
0.29
100T Utility C12b-3 U
106
535
0.27
lOlTractor DC C18
279
1411
0.71
262
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2.4.2.1 Battery Weight
Battery specific energy (also referred to as gravimetric energy density) is a measure of battery
energy per unit of mass (e.g., watt-hours or Wh per kg). While there have been tremendous
advancements in battery chemistries, materials, and pack design in recent years, current ZEV
batteries add mass to the vehicle. Battery specific energy is expected to continue to improve as
next generation battery technologies are developed.992
To determine the weight impact, we used the specific energy of battery packs with lithium-ion
cell chemistries. For the final rule, instead of relying on the 2021 version of Autonomie as we
did at proposal,993 we utilized energy density values from DOE as provided by a recent
comprehensive ANL study.994 This ANL study aligns with our analysis requirements as it covers
the period of 2023 - 2035. The results are in line with studies previously reviewed and are given
merit due to DOE/ANL expertise. The study applies the Argonne National Laboratory's Battery
Performance and Cost (BatPaC) model. Prior to establishing this direction, we reviewed the
specific energy of the battery based on consideration of the comments received on the proposal
and ANL BEAN values. ANL's 2022 BEAN tool includes values of 216 Wh/kg for the "low"
technology scenario and 267 Wh/kg for the "high" technology scenario in 2027 (interpolated
from 2025 and 2030 values).995 For a complete discussion of information provided by
commenters on battery specific energy, see RTC Section 3.2.3.
We calculated the pack specific energy of 2027 batteries by using the correlation provided by
ANL in their January 2024 report.996 The constants provided by ANL for NiMn and LFP battery
packs were applied, using the 2027 values. Since specific energy is a function of the total battery
energy required, the specific energy was calculated for battery energy ranging from 50 to 1200
kWh to cover the probable range for HD BEV battery sizes (pack energy). The corresponding
pack specific energy is 217 to 236 Wh/kg for NiMn and 164 to 177 Wh/kg for LFP.997 Since our
minimum pack size is 100 kWh (per HD TRUCS analysis), and the specific energy changes little
(4%) for both battery types as energy is increased from 100 to 1200 kWh, the value at 100 kWh
was chosen, as a conservative estimate. As with battery cost, a 50/50 mix of NiMn and LFP
batteries are applied. With 100 kWh NiMn batteries at 226 Wh/kg and LFP at 170 Wh/kg, the
resulting value, used in our analysis, is 198 Wh/kg.
992 Mitchell, George. Memorandum to docket EPA-HQ-OAR-2022-0985. " ACT Research Co. LLC. "Charging
Forward" 2020-2040 BEV & FCEV Forecast & Analysis, updated December 2021.
993 Argonne National Laboratory. VTO HFTO Analysis Reports - 2021. "ANL - ESD-2110 Report - MD HD Truck
- Autonomie Assumptions.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/folder/177858439896.
994 Kevin Knehr, Joseph Kubal, Shabbir Ahmed, "Cost Analysis and Projections for U.S.-Manufactured Automotive
Lithium-ion Batteries", Argonne National Laboratory report ANL/CSE-24/1 for US Department of Energy. January
2024. Available online: https://www.osti.gov/biblio/2280913.
995 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
996 Kner, Kevin et al. "Cost Analysis and Projections for U.S.-Manufactured Automotive Lithium-ion Batteries",
Argonne National Laboratory report ANL/CSE-24/1 for US Department of Energy. January 2024. Available online:
https://www.osti.gov/biblio/2280913
997 Ibid.
263
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Table 2-47 Pack Energy Density998
2027 Pack Energy Density (Wh/kg)
Pack Energy
(kWh)
NiMn
LFP
Average
50
217
164
190
100
226
170
198
150
230
173
201
200
231
174
202
1200
236
177
206
Although the ANL study suggests increasing battery specific energy over time, we maintained
the 2027 value in our analysis as a conservative technology assumption in case manufacturers
choose to focus on cost reductions rather than improved energy density.
We recognize that there likely will be improvements made between 2027 and 2032, as
predicted by ANL. It is difficult to determine if the degree of improvements during that time
will be as rapid as between 2020 and 2027, especially considering that manufacturers will have
to balance the cost of additional weight reduction and overall costs of the BEV. Therefore, for
the final rule we reasonably, and arguably conservatively, held the battery specific energy
constant for MYs 2027 through 2032.
For additional discussion on the impact of battery weight see RIA Chapter 2.9.1.1.
2.4.2.2 Battery Volume
To evaluate battery volume and determine the packaging space required for each HD vehicle
type, we used battery energy density. In the proposal, we also estimated the battery's width using
the wheelbase and frame depths.
Battery energy density (also referred to as volumetric energy density) is a measure of battery
energy per unit of volume, (e.g., Wh/L). This value was not available as a part of the Autonomie,
nor did we find many projections for battery pack-level specific energy or energy density
specifically for heavy-duty vehicles in the literature. For the foreseeable future, battery packs
likely will consist of numerous battery cells where the pack-level energies are lower than that of
the cell-level energies because of added mass or volume from the creation of the module or pack.
In response to our request for data in the NPRM, one commenter provided data from a study
that included battery properties of specific energy and energy density. For more details on the
comment and our response, see RTC Section 3.2.3. The average energy density calculated from
the data provided was 2.2.
For the final rule, we used a ratio of 2.0 as a conservative estimate because the properties
cited by the initial commenter discussed here are on a cell level, not a pack level. Based on our
update to battery pack specific energy, we used an energy density value of 396 Wh/L for MYs
2027 through 2032 in HD TRUCS.
998 Ibid.
264
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Battery volume for each vehicle type in each model year is calculated by dividing the battery
size (kWh) by the energy density as shown in Table 2-46. For additional discussion on battery
packaging, see RIA Chapter 2.9.1.2.
2.4.3 BEV Component Costs
A BEV powertrain system has different components than an ICE powertrain system. To
account for differences in powertrain system costs between BEVs and ICEs, we considered the
following HD BEV powertrain systems in HD TRUCS: battery, electric motor, inverter,
converter, onboard charger, power converter and electric accessories, transmission or gearbox,
and final drive.
Although there are many components in a BEV, two components play an outsized role in the
cost of the BEV: the battery and the motor. The cost of these components varies depending on
the size of these components which is determined by the requirements of the HD BEV; the sizing
aspect of these components are explained in RIA Chapter 2.4.1. The remaining components,
including the power converter and electric accessories, gearbox, and final drive impart some cost
on the BEV total cost, but to a much lesser degree.
In HD TRUCS, BEV component DMC are generally estimated from literature values, as
discussed in following sections, for MY 2027 and then extrapolated through MY 2032 using an
EPA learning curve that is described in RIA Chapter 3.2.1.999
As described in RIA Chapter 1.3.2, the IRA provides a tax credit to reduce the cost of
producing qualified batteries (battery tax credit) and to reduce the cost of purchasing qualified
ZEVs (vehicle tax credit).1000 The battery tax credit is considered in HD TRUCS before
determining the total incremental cost, as described in RIA Chapter 2.4.3.1. The vehicle tax
credit is considered after determining the total incremental cost (i.e., increase in purchase cost) of
a BEV relative to a comparable ICE vehicle, effectively reducing the cost of the BEV for the
purchaser. This vehicle tax credit does not affect the cost of BEVs for the manufacturers, as
reflected in our accounting described in RIA Chapter 3. Please see RIA Chapter 2.4.3.5 for
further discussion of this IRA vehicle tax credit.
2.4.3.1 EV Battery Cost
Battery costs are an important component of BEV costs. Battery costs are widely discussed in
the literature because they are a key driver of the cost of a heavy-duty BEV. The per unit cost of
the battery, in terms of $/kWh, is the most common metric in determining the cost of the battery
as the final size of the battery may vary significantly between different applications. The total
battery pack cost is a function of the per-unit-kWh cost and the size (in terms of kWh) of the
battery pack.
We received many comments regarding the values we used for the battery costs in the NPRM,
as well as comments regarding when and how learning should be applied in assessing those
costs. Comments addressing battery cost projections advocated for costs both higher and lower
999 For the final rule, we updated the learning curve for BEV (and FCEV) final drive costs to be consistent with the
ICE learning curve since we are basing final drive costs on a component that is similar to an ICE vehicle final drive.
1000 Inflation Reduction Act of 2022, Pub. L. No. 117-169, 136 Stat. 1818 (2022), available at
https://www.congress.gOv/l 17/bills/hr5376/BILLS-l 17hr5376enr.pdf.
265
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than the costs EPA used at proposal. Comments supporting higher (more expensive) values cited
reasons including volatility in the minerals market, adjustment to rate of learning, inability to
capture some or all of BIL and IRA incentives and pass those through to the vehicle purchaser,
as well as general uncertainty within the sector. Commenters supporting lower values cited
reasons including incentives from BIL and IRA, rapid development in the EV sector including
the light-duty market, cheaper chemistries including LFP and sodium-ion batteries, and (more)
recent stabilization within the lithium market.
One industry commenter recommended that EPA use a figure roughly 26 percent greater than
estimated at proposal: $183/kWh in MY 2027. Two industry commenters echoed these
comments. Another industry commenter shared four CBI battery pack costs for 2029 under four
scenarios; these scenarios include smaller and larger battery packs, and with low and high
lithium raw material costs. Another commenter questioned EPA's reliance on the ICCT Working
Paper 2022-09 value for battery pack cost given ICCT's caution about uncertainty within the
market for this sector. This commenter further maintained that the ICCT Paper did not
adequately explain or cite empirical support for averaging of the values, and that upper and lower
bounds should be adopted instead.
Other commenters believe the battery costs used for the NPRM were too high. One of these
commenters referenced a Roush report of HDV battery cost of $98/kWh in MY 2030 and
$88/kWh in MY 2032 without IRA adjustment. Another of these commenters believes the
battery used for HDV will be less conservative than the one modeled by EPA in terms of both
specific energy and energy density, and that these inappropriately conservative parameters
resulted in an overly high estimated battery pack price. Their estimates align with those of
BloombergNEF projecting that battery cost will decline to $100/kWh by 2026 as a result of
mineral price stabilization.1001 Another of these commenters referenced an ICCT report where
batteries would reach a cost of $120/kWh at the pack level by 2030 but did not produce a battery
pack cost of their own.1002
For the final rule, we re-evaluated our values used for battery cost in MY 2027 based on
consideration of comments provided by stakeholders, as well as additional studies provided by
the FEV and the Department of Energy BatPaC model.
FEV conducted a technology and cost study for a variety of powertrains as applicable to Class
4, 5, 7, and 8 heavy-duty vehicles.1003'1004 Powertrains included BEVs and FCEVs, in addition to
other ICE technologies. Vehicles studied include Class 4-8 box trucks, step vans, buses,
vocational vehicles, and tractors. FEV also costed three (15L (Class 8), 10L (Class 7), 6.6L
(Class 4/5)) diesel ICE powertrains that would meet the emission standards as required by the
HD2027 Low NOx Rule and the Phase 2 CO2 emission standards in MY 2027. These are used to
calculate the incremental cost of the alternative powertrain to the current day powertrain. The
1001 BloombergNEF 2022 Lithium-Ion Battery Price Survey (subscription required).
1002 Xie, Yihao, Hussein Basma, and Felipe Rodriguez, "Purchase Costs of Zero-Emission Trucks In The United
States To Meet Future Phase 3 GHG Standards." International Council on Clean Transportation. March 2, 2023.
Available online: https://theicct.org/publication/cost-zero-emission-trucks-us-phase-3-mar23/
1003 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
1004 Daniels, Jessica and Alex Wang. Memorandum to Docket EPA-HQ-OAR-2022-0985. FEV Component Cost
Estimates. March 2024.
266
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direct manufacturing costs for the battery packs ranged between $128 and $143/kWh for MY
2027. We used an average value of $135.50/kWh as the representative cost projected by FEV.
To support the final rulemaking analysis, Argonne National Laboratory (ANL) conducted
modeling of light, medium-, and heavy-duty battery costs using their BatPaC model.1005 ANL
conducted a detailed analysis of battery costs in which they utilized the current version of
BatPaC to estimate future battery pack costs by taking into account mineral price forecasts from
leading analyst firms, and a technology roadmap of production and chemistry improvements
likely to occur over the time frame of the rule.
To update our estimate of current and future battery pack costs, we worked with the
Department of Energy and Argonne National Laboratory to develop a year-by-year projection of
battery costs from 2023 to 2035, using specific inputs that represent ANL's expert view of the
current state-of-the-art and of the path of future battery chemistries and the battery
manufacturing industry. By default, BatPaC estimates only a current-year battery production cost
and does not support the specification of a future year for cost estimation purposes. However,
some parameters can be modified within BatPaC to represent anticipated improvements in
specific aspects of cell and pack production. For example, cell yield is controlled by an input
parameter that can be modified to represent higher cell yields likely to result from learning-by-
doing and improved manufacturing processes. ANL identified several parameters that could
similarly represent future improvements. This allowed ANL to estimate future pack costs in each
of several specific future years from 2023 to 2035, allowing cost trends over time to be
characterized by a mathematical regression.
A major element of the approach was to select BatPaC input parameters to reflect current and
future technology advances and calculate the cost of batteries for different classes of vehicles at
their anticipated production volumes. Material cost inputs to the BatPaC simulations were based
on forecasted material prices by Benchmark Mineral Intelligence. That is, pack costs were
estimated from current and anticipated future battery materials, cell and pack design parameters,
and market prices and vehicle penetration. Pack cost improvements in future years were
represented at three levels: manufacturing (increasing cell yield and plant capacity), pack
(reducing cell and module numbers and increasing cell capacity), and cell (changing active
material compositions and increasing electrode thickness). The simulations yielded battery pack
cost estimates that can be represented by correlations for model years 2023 to 2035.
The ANL battery cost explicitly represents the most recent trends and forecasts of future
mineral costs and also are an outcome of basing the future costs on a specific set of technology
pathways instead of applying a year-over-year cost reduction rate. Most other forecasts of future
battery costs, including those that we cited in the proposal, are based largely on application of a
historical year-over-year cost reduction rate (i.e., learning rate), without reference to the specific
technology pathways that might lead to those cost reductions. ANL's approach is consistent with
that of the Mauler paper,111 which also identified and modeled a specific set of technology
pathways. EPA acknowledges one potential criticism of such an approach is that it may lead to
conservative results, because it excludes the potential effect of currently unanticipated or highly
uncertain developments that may nonetheless come to fruition. On the other hand, basing the
1005 Kevin Knehr, Joseph Kubal, Shabbir Ahmed, "Cost Analysis and Projections for U.S.-Manufactured
Automotive Lithium-ion Batteries", Argonne National Laboratory report ANL/CSE-24/1 for US Department of
Energy. January 2024. Available online: https://www.osti.gov/biblio/2280913.
267
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costs on specific high confidence pathways allows the basis of the projections to have greater
transparency.
Accordingly, the ANL battery costs are responsive to many of the comments. First, the ANL
work accounts more explicitly for the potential effect of critical mineral prices on the cost of
batteries over time. We worked with ANL to make available medium- and long-term mineral
price forecasts from Benchmark Mineral Intelligence, a leading minerals analysis firm. These
were then used to estimate electrode material prices over the years of the ANL analysis. Second,
as one outcome of this change, in the early years of the program, our battery cost inputs are now
in closer agreement with the 2022 BNEF battery price survey, which commenters mentioned.
Additionally, the 5.1 version of BatPaC used in this analysis includes several significant
feature updates that improve its ability to estimate pack manufacturing costs in realistic
production scenarios. This version accounts for cell production volume and pack production
volume separately, allowing economy of scale for cells and packs to be considered
independently. This allows the analysis to use pack production volumes that are more
representative of the annual production of a single pack design, while continuing to operate cell
production at full plant capacity to provide cells for other product lines.
The ANL analysis provided EPA with several battery pack direct manufacturing costs as a
function of model year and battery capacity (kWh), for both nickel-based (NMC) chemistry and
iron-phosphate based (LFP) chemistry. We used a weighted average of ANL's costs for LFP and
NMC batteries, with a 50/50 weighting. LFP is expected to increase in the future, due to its lower
cost and absence of the critical minerals such as cobalt, manganese, and nickel. Our assessment
is that on average the battery pack costs from the ANL study most representative of our average
HD TRUCS vehicle types is an average of the heavy-duty 190, 220, and 250 kWh battery packs.
Based on a linear interpolation of ANL's 2026 and 2030 costs, we used a value of $101.75 as the
ANL battery pack direct manufacturing cost for MY 2027.1006
We considered a wide range of MY 2027 battery pack costs ranging from the $183/kWh cited
by manufacturers in comments to $101.75/kWh projected in ANL's BatPaC model for HD
battery packs for the final rule. In our analysis, we primarily relied on ANL's BatPaC model
results. However, we also accounted for the data provided in comments and the recent FEV cost
study. Based on our engineering judgement, we applied a weighting of 60% for the BatPac
results in our assessment. We then attributed a 10% weighting to the FEV value of $135.50/kWh,
10%) weighting to the EMA value of $183/kWh, 10%> weighting of MFN's value of
$148.74/kWh (converted from 2021$ supplied in comments to 2022$), and 10%> weighting to a
value of $123.42/kWh based on EDF's comment citing a study conducted by Roush (which
provided a 2030 value of $106/kWh, which we back-learned using the learning scalars shown in
RIA Chapter 3.2). Based on this assessment, we project a battery pack cost value for MY 2027 of
$120/kWh (2022$).
We calculated MYs 2028-2032 battery costs using learning scalars as shown in RIA Chapter
3.2.1, resulting in the values shown in Table 2-48. Per-unit battery pack cost for each of the 101
vehicles can be seen in Table 2-57 through Table 2-59 for MYs 2027, 2030, and 2032,
respectively.
1006 Ibid. Appendix Al, Page 35.
268
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Table 2-48 Pack-Level Battery Pack Direct Manufacturing Costs in HD TRUCS (2022$)
$/kWh
MY
2027
MY
2028
MY
2029
MY
2030
MY
2031
MY
2032
Battery Pack Cost
120
113
107
103
100
97
The battery pack cost estimates discussed thus far do not include the effect of tax credits
available to battery manufacturers under the Inflation Reduction Act. As discussed in RIA
Chapter 1.3.2, Section 13502 of the IRA1007 (Section 45X of the Internal Revenue Code, or
"45X") provides tax credits from CY 2023 through CY 2032 for the production and sale of
battery cells and modules. These include the cell and module production tax credit of up to $45
per kWh available to manufacturers under 45X, and the additional tax credit for 10 percent of
the production cost of (a) critical minerals and (b) electrode active materials available to
manufacturers under 45X. The 45X credit provides a $35 per kWh tax credit for U.S.
manufacture of battery cells, and an additional $10 per kWh for U.S. manufacture of battery
modules. 45X also provides a credit equal to 10 percent of the manufacturing cost of electrode
active materials and another 10 percent for the manufacturing cost of critical minerals if
produced in the U.S. The credits phase out from 2030 to 2032 (with the exception of the 10
percent for critical minerals, which continues indefinitely).
In the proposal, EPA estimated potential future uptake of the IRA credits and how they would
impact manufacturing costs for batteries over the time frame of the rule. In the proposal, we
assumed that manufacturers would be able to take advantage of the full module credit in 2027
through 2032 and that the cell credit would ramp up from 25 percent of total cells in 2027 to 100
percent in 2030 through 2032. We requested comment on all aspects of our accounting for the
IRA credits, including not only the values used for the credits but also whether or not we should
also account for the additional 10 percent provisions for electrode active materials and critical
mineral production, which we did not estimate for the proposal.
Comments received on our modeling of the 45X cell and module credit led us to further
investigate our inputs for the phase-in schedule and average amount realized. Specifically, we
received comment questioning the ability of U.S. battery manufacturing facilities currently
planned or under construction to ramp up quickly enough; the lack of accounting for the 10
percent electrode active material and critical mineral credit; and the assumption that all of the
value of the 45X credit would be realized as a cost reduction by OEMs when purchasing cells or
packs from suppliers.
To address the comments related to the ramp up of battery manufacturing facilities, we
worked with the Department of Energy and Argonne National Lab (ANL) to update our
assessment of U.S. battery manufacturing facilities and to account for gradual ramp-up of these
facilities over time. As discussed in preamble Section II.D.2.ii.c, the updated analysis projects
that the currently planned U.S. battery cell manufacturing capacity is poised to meet projected
U.S. demand during the time frame of the rule. For example, a new joint venture between
Daimler Trucks, Cummins, and PACCAR recently announced a 21 GWh factory to be built in
the U.S. to manufacture cells and packs initially focusing on lithium iron phosphate (LFP)
1007 Inflation Reduction Act of 2022, Pub. L. No. 117-169, 136 Stat. 1818 (2022). Available online:
https://www.congress.gOv/l 17/bills/hr5376/BILLS-l 17hr5376enr.pdf.
269
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batteries for heavy-duty and industrial applications.1008 Tesla is expanding its facilities in Nevada
to produce its Semi BEV tractor and battery cells,1009 and Cummins has entered into an
agreement with Arizona-based Sion Power to design and supply battery cells for commercial
electric vehicle applications.1010 In addition, DOE is funding through the BIL battery materials
processing and manufacturing projects to "support new and expanded commercial-scale
domestic facilities to process lithium, graphite and other battery materials, manufacture
components, and demonstrate new approaches, including manufacturing components from
recycled materials."1011 See also Preamble Section II.D.2.ii.b and RTC section 17.2 documenting
additional current and projected North American battery production, and discussing facility
startup times as being within the timeframe of the Phase 3 rule.
We also received comment that the 10 percent credit for electrode active materials and critical
minerals (CM) under 45X could be significant, and therefore should be included in the analysis.
To investigate this possibility, we consulted with the Department of Energy and ANL to
characterize the potential value of the 10 percent provisions of 45X on a dollar per kWh basis.
ANL determined that the maximum value of the credits would change over time, as CM become
a larger share of battery manufacturing cost due to efficiencies in other material and
manufacturing costs.1012 As shown in Table 2-49, the maximum value for the cathode active
materials (CAM) credit, anode active materials (AAM) credit, CM credit, or the CAM, AAM,
and CM credits combined would range from $0.60 to $8.40 per kWh in 2026 and decline to
$0.40 to $6.20 per kWh in 2030, depending on chemistry. The decline is a result of ANL's
projection that the amount (and hence manufacturing cost) of critical mineral content will decline
over time due to improved cell chemistries for which minerals comprise a diminishing portion of
total cost.
1008 Daimler Trucks North America. "Accelera by Cummins, Daimler Truck and PACCAR form a joint venture to
advance battery cell production in the United States." September 6, 2023. Available online:
https://media.daimlertruck.com/marsMediaSite/en/instance/ko/Accelera-bv-Cummins-Daimler-Truck-and-
PACCAR-form-a-ioint-venture-to-advance-batterv-cell-production-in-the-United-States.xhtml?oid=52385590 (last
accessed October 23, 2023).
1009 Sriram, Akash, Aditya Soni, and Hyunjoo Jin. "Tesla plans $3.6 bin Nevada expansion to make Semi truck,
battery cells." Reuters. January 25, 2023. Last accessed on March 31, 2023. Available online:
https://www.reuters.com/markets/deals/tesla-invest-over-36-bln-nevada-build-two-new-factories-2Q23-01-24/
1010 Sion Power. "Cummins Invests in Sion Power to Develop Licerion® Lithium Metal Battery Technology for
Commercial Electric Vehicle Applications". November 30, 2021. Available online:
https://sionpower.com/2021/cummins-invests-in-sion-power-to-develop-licerion-lithium-metal-batterv-technology-
for-commercial-electric-vehicle-applications/.
1011 U.S. Department of Energy. "Bipartisan Infrastructure Law: Battery Materials Processing and Battery
Manufacturing & Recycling Funding Opportunity Announcement—Fact sheets". October 19, 2022. Available
online: https://www.energy.gov/sites/default/files/2022-10/DOE%20BIL%20Batterv%20FQA-
2678%20Selectee%20Fact%20Sheets%20-%201 2.pdf.
1012 Kevin Knehr, Joseph Kubal, Shabbir Ahmed, "Cost Analysis and Projections for U.S.-Manufactured
Automotive Lithium-ion Batteries", Argonne National Laboratory report ANL/CSE-24/1 for US Department of
Energy. January 2024. Available online: https://www.osti.gov/biblio/2280913.
270
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Table 2-49 Potential value of 45X 10 percent CAM, AAM, and CM credits for a 75-kWh battery
Ni/Mn
LFP
2026
2030
2035
2026
2030
2035
CAM only, $/kWh
4.4
2.9
-
2.2
1.5
-
AAM only, $/kWh
0.7
0.4
-
0.6
0.4
-
CM only, $/kWh
3.3
2.9
1.6
1.0
0.7
0.4
CAM + AAM + CM,
$/kWh
8.4
6.2
1.6
3.9
2.6
0.4
While these tax credits will be significant to manufacturers that produce CAM and AAM in
the U.S., their effect on average battery manufacturing cost across the fleet depends on the
degree to which the average battery uses U.S.-produced CAM and AAM. ANL found that there
are means for satisfying domestic AAM and CAM demand.1013 Because of the uncertainty in
predicting the degree of utilization across the industry, and the relatively small average value of
the resulting credit, we have chosen to not include an estimate of the 10 percent credits in this
analysis. Because some manufacturers will likely be in a position to qualify for some portion of
the credit, this is a conservative assumption.
Regarding the passing of 45X credit savings realized by cell and module suppliers to
manufacturers via the selling price of the cells or modules, we continue to expect that many
suppliers and manufacturers will work closely together as they currently do through contractual
agreements and partnerships and that these close connections will promote fair pricing
arrangements. The large U.S. production capacity that is projected for the time frame of the rule
also suggests that the market will be competitive and that suppliers will be motivated to pass
credit savings along to customers in order to compete on price. Thus, we have continued to
model a full pass through of the 45X credit savings we project in the final rule to the
manufacturers. See RTC Section 2.7 for further discussion of the 45X tax credit pass through.
The tax credits under 45X effectively reduce the costs for batteries via tax credits for cells and
modules, but the indirect costs associated with the batteries should persist even with the tax
credit.1014 As we did in the proposal, we applied the 45X credits after the RPE markup. Because
RPE is meant to be a multiplier against the direct manufacturing cost, and the 45X credit does
not reduce the actual direct manufacturing cost at the factory but only compensates the cost after
the fact, it was most appropriate to apply the 45X credit to the marked-up cost. As discussed in
Chapter 3, our RPE markup factor estimates these indirect costs and is based on the DMC
without tax credits. The 45X cell and module credits per kWh were applied by first marking up
1013 David Gohlke et al., "Quantification of Commercially Planned Battery Component Supply in North America
through 2035", Argonne National Laboratory report ANL-24/14. March 2024. Available online:
https://publications.anl.gov/anlpubs/2024/03/187735.pdf. See pp. 30-35 and 62-63..
1014 As discussed further in Chapter 3.2, indirect costs are all the costs associated with producing the unit of output
that are not direct manufacturing costs - for example, they may be related to research and development (R&D),
warranty, corporate operations (such as salaries, pensions, health care costs, dealer support, and marketing) and
profits. We expect the tax credits under 45X to offset costs for the manufacturers by reducing tax liability, which
reduces the amount of costs that we anticipate manufacturers will recover by selling their products; the tax credits
result in a lower RPE, but we do not expect them to reduce DMC or indirect costs.
271
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the direct manufacturing cost by the RPE factor to determine the indirect cost, then deducting the
credit amount from the marked-up cost to create a post-credit marked-up cost.
Taking into account each of these considerations, we model this tax credit in HD TRUCS in
the final rule such that HD BEV and FCEV manufacturers fully utilize the module tax credit and
gradually increase their utilization of the cell tax credit for MY 2027-2029 until MY 2030 and
beyond, when they earn 100 percent of the available cell and module tax credits.
To estimate the price of the battery packs to the purchaser, we projected that the full value of
the tax credit earned by the manufacturer is passed through to the purchaser because market
competition would drive manufacturers to minimize their prices. See RTC Section 2.7 for further
discussion of this projection.
The battery pack cost and battery tax credits are summarized in Table 2-50. As discussed
above and in RTC Section 2.7, the literature indicates that there will be sufficient manufacturing
capacity for the HDV industry to receive more 45X tax credits than our conservative projections
in Table 2-50. Should the HDV industry's use of the 45X tax credit exceed these conservative
projections, our cost estimates of BEVs and FCEVs would be overestimated.
Table 2-50 Pack-Level Battery Direct Manufacturing Costs and IRA Tax Credits in HD TRUCS (2022$)
$/kWh
MY
MY
MY
MY
MY
MY
2027
2028
2029
2030
2031
2032
Battery Pack Cost (no Credit)
120
113
107
103
100
97
IRA Cell Credit
8.75
17.50
26.25
26.25
17.50
8.75
IRA Module Credit
10.00
10.00
10.00
7.50
5.00
2.50
IRA Total Battery Credit
18.75
27.50
36.25
33.75
22.50
11.25
Battery Pack Cost Less IRA Total Battery Credit
101
85
71
69
77
85
ICCT and Energy Innovation assessed the impact of the IRA on electric vehicle uptake in the
United States and analyzed three scenarios differentiated by how much of the tax credit value is
passed through to vehicle purchasers: "From 2024 through 2029, the assumed percentage of the
tax credit value passed to consumers is 0 percent in the Low scenario, 50 percent in the Moderate
scenario, and 100 percent in the High scenario. For 2023, these values are reduced by a factor of
two. By 2030, the 45X production tax credit begins to phase out, and the percentage passed
through is reduced by 25 percent per year until fully expiring in 2033."1015 In comparison with
this ICCT and Energy Innovation study, our analysis falls between the Low and High scenarios
for 2027-2029 and matches the High scenario for 2030-2032, reflecting our expectation that
domestic battery manufacturing capacity will increase over time to capture this incentive and that
competition in the market will lead manufacturers to reduce prices in accordance with the tax
credits earned.
1015 Slowik, Peter, et al. "Analyzing the Impact of the Inflation Reduction Act on Electric Vehicle Uptake in the
United States". The International Council on Clean Transportation and Energy Innovation: Policy and Technology.
January 31, 2023. Available online: https://energvinnovation.org/wp-content/uploads/2023/01/Analvzing-the-
Impact-of-the-Inflation-Reduction-Act-on-EV-Uptake-in-the-U.S..pdf
272
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These lower battery prices have the potential to accelerate ZEV technology adoption. For
example, the Rocky Mountain Institute found that because of the IRA, the TCO of electric trucks
will be lower than the TCO of diesel trucks about five years faster than without the law.1016
2.4.3.2 E-Drive
The electric drive in a BEV includes the electric motor (e-motor), power electronics and
electrical accessories, and a driveshaft that can include a transmission system or gearbox. The
electric energy in the form of DC current is provided from the battery; an inverter is used to
change the DC current into AC current for use by the motor. The motor1017 then converts the
electric power into mechanical or motive power to move the vehicle. Conversely, the motor also
receives AC current from the regenerative braking, whereby the inverter changes it to DC current
to be stored in the battery. Lastly, the transmission or gearbox and final drive reduces the speed
of the motor through a set of gears to an appropriate speed at the axle. Although there is an
emerging trend of replacing the transmission and driveline with an e-axle, which is an electric
motor integrated into the axle, e-axles are not explicitly covered in our cost analysis.1018
Like the battery cost described above, there are disparate electric drive cost projections. One
reason for the differences is what is included in the definition of "electric drive"; some values
include only the electric motor and other values present a more integrated e-
motor/inverter/gearbox (or transmission) combination. For example, Sharpe and Basma et al.
found the average reported e-drive costs—defined as the e-motor, inverter, and transmission
system—to be around $60/kW in 2020, expected to drop to roughly $25/kW by 2030.1019 But
this is difficult to compare to values in Nair et. al,1020 which include total component costs,
where the motor and inverter costs vary by duty cycle, as shown in Figure 2-7.
1016 Kahn, Ari, et. al. "The Inflation Reduction Act Will Help Electrify Heavy-Duty Trucking". Rocky Mountain
Institute. August 25, 2022. Available online: https://rmi.org/inflation-reduction-act-will-help-electrifV-heaw-dutv-
trucking/.
1017 BEVs and FCEVs with e-motors have high torque at low motor speeds (i.e., low-end torque), which can provide
performance benefits for HD ZEVs compared to comparable ICE vehicles, especially for heavy vehicles at low
speed in terms of gradeability and acceleration. We did not quantify the potential performance improvements
associated with the increase in low-end torque due to e-motors in the HD TRUCS analysis as we focused on
matching ICE vehicle performance rather than exceeding it.
1018 E-axles are an emerging technology that have potential to realize efficiency gains because they have fewer
moving parts. Though we did not quantify their impact explicitly due to a lack of data and information at the time of
our analysis and to remain technology-neutral, the technology can be used to comply with this regulation.
1019 Sharpe, Ben and Hussein Basma. "A meta-study of purchase costs for zero-emission trucks". The International
Council on Clean Transportation, Working Paper 2022-09 (February 2022). Available online:
https://theicct.org/publication/pnrchase-cost-ze-trucks-feb22/. Costs are prior to integration markups.
1020 Nair et. al "Technical Review of: Medium and Heavy-Duty Electrification Costs for MY 2027-30—Final
Report". Environmental Defense Fund and Roush. February 2, 2022. Available online:
https://blogs.edf.Org/climate411/files/2022/02/EDF-MDHD-Electrification-vl.6 20220209.pdf.
273
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E-Drive Component Costs
(HD Motor Reference & High Case)
$1,800.00
$1,600.00
$1,400.00
$1,200.00
$1,000.00
$eoo.oo
$600.00
$400.00
$200.00
$0.00
lii hi lii lii lii
lilt
Class 3 Class 5 Class 5 Class 7 Class 7 Class 8 Class 8
Delivery Delivery ShLrttleBus Delivery School Bus Refuse Transit Bus
Van Truck Truck Truck
¦ Motor Costs ¦ Inverter Costs ¦ Gearbox Costs
Figure 2-7 Electric Drive Component Costs from (Nair et al. 2022)
Both references cite inverter cost rather than power electronics and electronic accessories
costs, which are considered in HD TRUCS. Burke et. al includes electric powertrain costs that
represent the motor, power electronics, and DC-DC converters, but not individual component
costs.1021
To remain consistent with other aspects of HD TRUCS and based on the structure of ANL's
2022 BEAN tool,1022 our analysis included cost values of individual e-drive components: the e-
motor, power electronics and electronic accessories, and gearbox. We primarily used the
"Autonomie Out Import" tab, though there are exceptions as described below. Since the tool
presents values for 2025 and 2030, the 2027 values were determined by interpolating between
the 2025 and 2030 high costs and then interpolating between the 2025 and 2030 low costs. Then,
the low and high MY 2027 values were averaged, converted to 2022$, and a learning factor was
applied. See RIA Chapter 3.2 for an explanation of BEV learning. ANL vehicle IDs were then
mapped to similar vehicles in HD TRUCS as shown in Table 2-2.
2.4.3.2.1 E-Motor
An e-motor—which is another major component of a BEV vehicle1023—converts electric
energy from the battery into mechanical energy. We did not find sole $ per kW e-motor costs in
the literature. A few commenters disagreed with the cost used by EPA at proposal for the electric
motor, providing values that were lower and higher than those proposed. One commenter
referenced Roush reports of $8/kW for 2030 and 2032, much lower than EPA's value. One
industry commenter provided CBI values of the combined costs of e-motor, gearbox, inverter,
11121 Burke, Andrew, Marshall Miller, Anish Sinlia, et. al. "Evaluation of the Economics of Battery-Electric and Fuel
Cell Trucks and Buses: Methods, Issues, and Results". August 1, 2022. Available online:
https://escholarsliip.org/uc/itein/lg89p8dn.
11122 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.coin/s/an4n\0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
11123 Alternative Fuels Data Center. "How Do All-Electric Cars Work". U.S. Department of Energy. Available online:
https://afdc.energv.gov/veliicles/how-do-all-electric-cars-work.
274
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and e-axle. Another industry commenter cited an ICCT report that projected cost reductions of
60 percent by 2030 and that further projected that the price of electric powertrain systems,
including the transmission, motor, and inverter, would reach $23/kW. One commenter is
concerned that the market will demand different ZEV architectures depending on the application
(direct drive, e-axle, and portal axle) and that each of these technologies will have a different $
per kW value due to differences in component costs and their respective manufacturing process.
For the final rule, we maintained the direct manufacturing cost for the e-motor (including the
inverter) in HD TRUCS that we used for the proposal but converted it to 2022$. The e-motor
costs in HD TRUCS come from ANL's 2022 BEAN tool1024 as "Integrated Traction Drive Cost"
values in the Vehicle Assumptions tab. 1025>1026 The MY 2027 value is a linear interpolation of the
average of the high- and low-tech scenarios for 2025 and 2030, adjusted to 2022$. MY 2028-
2032 values were then calculated using the BEV learning effects in RIA Chapter 3.2.1. The per-
unit cost was calculated from the power of the motor (RIA Chapter 2.4.1.2) and $/kW of the e-
motor (shown in Table 2-51). Per-unit e-motor cost for each of the 101 vehicles can be seen in
Table 2-57 for MY 2027.
Table 2-51 E-Motor Direct Manufacturing Costs in HD TRUCS (2022$)
MY
2027
2028
2029
2030
2031
2032
E-Motor Cost ($/kW)
21
20
19
18
17
17
2.4.3.2.2 Power Converter and Electric Accessories
Power converter and electric accessories are components that include DC-DC converters,
electric accessories, and vehicle propulsion architecture (VPA).
One NREL report includes a cost assumption used in FASTSim Powertrain Modeling for
"power electronics with boost and motor" of $41.70/kW (in 2016 dollars) for medium- and
heavy-duty trucks by 2025.1027 EDF/Roush suggest that DC-DC converters, which includes the
cost of the motor, in medium- and heavy-duty vehicles could cost $45.31/kW in 2027.1028 We
did not receive additional comments on the power electronics and electric accessories.
The power converter and electric accessories costs in HD TRUCS for both the proposal and
final rule came from the "Autonomie Out Import" tab of ANL's 2022 BEAN tool.1029 For the
1024 These values did not come directly from the "Autonomie Out Import" tab but can be calculated from fields on
the "Autonomie Out Import" tab.
1025 Our assumption is that ANL's integrated cost includes the inverter and the motor.
1026 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
1027 Hunter et. al. "Spatial and Temporal Analysis of the Total Cost of Ownership for Class 8 Tractors and Class 4
Parcel Delivery Trucks". National Renewable Energy Laboratory. September 2021. Available online:
https://www.nrel.gov/docs/IV21osti/71796.pdf.
1028 Nair et. al "Technical Review of: Medium and Heavy-Duty Electrification Costs for MY 2027-30—Final
Report". Environmental Defense Fund and Roush. February 2, 2022. Available online:
https://blogs.edf.Org/climate411/files/2022/02/EDF-MDHD-Electrification-vl.6 20220209.pdf.
1029 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
275
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final rulemaking version of HD TRUCS, we updated the term Power Electronics to Power
Converter, which represents the cost of a DC-DC converter ($1500 in 2020$).1030 DC-DC
converters transfer energy (i.e., they "step up" or "step down" voltage) between higher- and
lower-voltage systems, such as from a high-voltage battery to a common 12V level for auxiliary
uses.1031 We identified an additional cost in BEAN that we added as a second DC-DC converter,
which we call an Auxiliary Converter.1032 This costs is shown by ANL ID in Table 2-53.1033 We
also revised the Electric Accessories costs to include both "ElecAccessory" ($4500 in 2020$)
and vehicle propulsion architecture (VPA) costs ($186 in 2020$) from ANL's 2022 BEAN.
These values, as shown below in Table 2-52, were converted to 2022$ and include the BEV
learning effects included in RIA Chapter 3.2.
Table 2-52 Power Converter and Electric Accessories Direct Manufacturing Costs in HD TRUCS (2022$)
MY
2027
2028
2029
2030
2031
2032
Power Converter ($)
1677
1577
1501
1440
1391
1349
VPA
208
196
186
179
173
167
Electric Accessories ($)
5032
4731
4502
4321
4174
4048
Table 2-53 Auxiliary Converter Direct Manufacturing Costs in HD TRUCS (2022$)
ANL ID
MY 2027
MY 2030
MY 2032
Box Medium 3
134
115
108
Van Medium 3
90
77
72
School Medium 3
224
192
180
Box Medium 4
134
115
108
StepVan Medium 4
134
115
108
Service Medium 4
134
115
108
StepVan Medium 6
224
192
180
Box Medium 6
224
192
180
Tractor DayCab 7
224
192
180
Vocational Medium 7
224
192
180
School Medium 7
448
385
360
Longhaul Sleeper 8
358
308
288
Beverage DayCab 8
313
269
252
Drayage DayCab 8
313
269
252
Vocational Heavy 8
313
269
252
Transit Heavy 8
537
461
432
Refuse Heavy 8
358
308
288
Regional DayCab 8
304
262
245
1030 In the 2022 version of BEAN, the "BEAN results" tab, this is also represented as "pc2 DC/DC booster".
1031 Smith, David et. al. "Medium- and Heavy-Duty Vehicle Electrification: An Assessment of Technology and
Knowledge Gaps". U.S. Department of Energy: Oak Ridge National Laboratory and National Renewable Energy
Laboratory. December 2019. ORNL/SPR-2020/7. Available online:
https://info.ornl.gov/sites/publications/Files/Publ36575.pdf..
1032 In the 2022 version of BEAN, the "Cost & LCOD & CCM" tab, this is called a "pel DC/DC ESS". In the
"Autonomie Out" tab, this is linked to a DC/DC buck converter cost.
1033 See Table 2-2 for HD TRUCS Vehicle ID mapping to ANL IDs.
276
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2.4.3.2.3 Gearbox and Final Drive
Gearbox and final drive units are used to reduce the speed of the motor and transmit torque to
the axle of the vehicle. In HD TRUCS for the proposal, we set the MY 2027 final drive DMC at
$l,500/unit, based on the "Final Drive Costs" column in the "Autonomie Out Import" tab of
ANL's 2022 BEAN model for vocational vehicles.1034 For tractors, the final drive cost is doubled
the cost of vocational vehicles. We did not receive any data to support different values, therefore,
we adjusted the values used in the proposal to 2022$ and then calculated the MY 2028-2032
costs using the ICE learning curve shown in RIA Chapter 3.2.1.1035 Final drive costs in HD
TRUCS for BEVs are in Table 2-54.
The cost of the gearbox varies depends on the vehicle weight class and duty cycle. In our
assessment, all light heavy-duty BEVs will be direct drive and have no transmission and no cost,
in keeping with ANL's 2022 BEAN model. We then mapped BEAN gearbox costs for BEVs
from the same "Autonomie Out Import" tab to the appropriate medium heavy-duty and heavy
heavy-duty vehicles in HD TRUCS by calculating MY 2027 values using linear interpolation of
the average of the high- and low-tech scenarios for 2025 and 2030, and then adjusting to
2022$.1036 We then calculated the MY 2028-2032 costs using the BEV learning curve shown in
RIA Chapter 3.2.1. BEV Gearbox costs are shown according to their ANL ID in Table 2-55.
Table 2-57, Table 2-58, and Table 2-59 show the final drive and gearbox costs, as assigned to the
101 HD TRUCs vehicle types for model years 2027, 2030, and 2032, respectively. For vehicle
Classes 5 and below, the gearbox cost is $0 in BEAN. This is consistent with the NPRM.
Table 2-54 Final Drive Costs in HD TRUCS (2022$)
MY
2027
2028
2029
2030
2031
2032
Vocational Vehicle Final Drive ($)
1677
1660
1660
1660
1644
1644
Tractor Final Drive ($)
3354
3321
3321
3321
3287
3287
Table 2-55 MY 2027, MY 2030, and MY 2032 BEV Gearbox Costs in HD TRUCS (2022$)
ANL ID
MY 2027
MY 2030
MY 2032
Box Medium 3
-
-
-
Van Medium 3
-
-
-
School Medium 3
-
-
-
Box Medium 4
-
-
-
StepVan Medium 4
-
-
-
Service Medium 4
-
-
-
StepVan Medium 6
2421
2079
1948
Box Medium 6
2587
2222
2082
Tractor Day Cab 7
2459
2112
1978
Vocational Medium 7
2489
2138
2003
1034 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
1035 For the final rule, we updated the learning curve for BEV (and FCEV) final drive costs to be consistent with the
ICE learning curve since we are basing final drive costs on a component that is similar to an ICE vehicle final drive.
1036 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
277
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School Medium 7
2426
2084
1952
Longhaul Sleeper 8
5450
4681
4385
Beverage Day Cab 8
3858
3313
3104
Drayage Day Cab 8
4525
3887
3641
Vocational Heavy 8
4674
4014
3761
Transit Heavy 8
2666
2290
2145
Refuse Heavy 8
3626
3114
2917
Regional Day Cab 8
5460
4689
4393
2.4.3.3 Onboard Chargers
When using a Level 2 charging plug, an on-board charger converts AC power from the grid to
usable DC power via an AC-DC converter. When using a DC fast charger (DCFC), any AC-DC
converter is bypassed, and the high-voltage battery is charged directly. We included on-board
chargers for all vehicles, even those that we predict will use DC fast chargers at the depot, as a
conservative assumption. EPA's on-board charger costs are shown in Table 2-56. These values
are significantly higher than the values we used in the NPRM, where we used a value of $38 in
MY 2027, based on ANL's BEAN model. In the peer review of HD TRUCS, one reviewer noted
that the value used in the NPRM was unrepresentative of the actual costs and suggested a cost of
$600. In light of this critique, EPA has increased the on-board charger costs to $600 in MY 2027,
We then calculated the MY 2028-2032 costs using the BEV learning curve shown in RIA
Chapter 3.2.1.
Table 2-56 Onboard Charger Direct Manufacturing Costs in HD TRUCS (2022$)
Model Year
2027
2028
2029
2030
2031
2032
On-Board Charger Cost ($/unit)
600
564
537
515
498
483
2.4.3.4 Total Upfront BEV Costs
The total upfront BEV DMC is the summation of the per-unit cost of the battery, motor,
power converter and electric accessories, on-board charger, gearbox, and final drive. The total
BEV technology DMC and associated IRA battery tax credit for each of the 101 vehicle types
can be found in Table 2-57 for MY 2027, Table 2-58 for MY 2030, and Table 2-59 for MY
2032.
Table 2-57 Direct Manufacturing BEV Costs Including IRA Tax Credit for MY 2027 (2022$)
Battery
Cost
Power
BEV PT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
01V Amb C14-5 MP
14,345
5,093
7,051
600
-
1,677
28,766
2,241
02V Amb C12b-3 MP
13,542
5,093
7,006
600
-
1,677
27,918
2,116
03V Amb C14-5 U
13,366
5,093
7,051
600
-
1,677
27,787
2,088
04V Amb C12b-3 U
12,534
5,093
7,006
600
-
1,677
26,910
1,958
05T Box C18 MP
29,250
6,700
7,230
600
4,674
1,677
50,132
4,570
278
-------
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
06T Box C18 R
30,213
6,700
7,230
600
4,674
1,677
51,095
4,721
07T Box C16-7 MP
20,192
4,236
7,141
600
2,587
1,677
36,433
3,155
08T Box C16-7 R
21,962
4,236
7,141
600
2,587
1,677
38,202
3,432
09T Box C18 U
28,339
6,700
7,230
600
4,674
1,677
49,221
4,428
10T Box C16-7 U
19,458
4,236
7,141
600
2,587
1,677
35,699
3,040
11T Box C12b-3 U
12,001
5,093
7,051
600
-
1,677
26,422
1,875
12T Box C12b-3 R
14,150
5,093
7,051
600
-
1,677
28,571
2,211
13T Box C12b-3 MP
13,028
5,093
7,051
600
-
1,677
27,449
2,036
14T Box C14-5 U
12,001
5,093
7,051
600
-
1,677
26,422
1,875
15T Box C14-5 R
14,150
5,093
7,051
600
-
1,677
28,571
2,211
16T Box C14-5 MP
13,028
5,093
7,051
600
-
1,677
27,449
2,036
17B Coach C18 R
85,254
6,700
7,454
600
2,666
1,677
104,352
13,321
19C Mix C18 MP
51,317
6,700
7,230
600
4,674
1,677
72,199
8,018
20T Dump C18 U
33,909
6,700
7,230
600
4,674
1,677
54,791
5,298
21T Dump C18 MP
34,347
6,700
7,230
600
4,674
1,677
55,229
5,367
22T Dump C16-7 MP
33,258
4,236
7,141
600
2,489
1,677
49,400
5,197
23T Dump C18 U
33,909
6,700
7,230
600
4,674
1,677
54,791
5,298
24T Dump C16-7 U
31,128
4,236
7,141
600
2,489
1,677
47,271
4,864
25T Fire C18 MP
36,059
6,700
7,230
600
4,674
1,677
56,941
5,634
26T Fire C18 U
36,134
6,700
7,230
600
4,674
1,677
57,016
5,646
27T Flat C16-7 MP
20,192
4,236
7,141
600
2,489
1,677
36,334
3,155
28T Flat C16-7 R
21,962
4,236
7,141
600
2,489
1,677
38,104
3,432
29T Flat C16-7 U
18,634
4,236
7,141
600
2,489
1,677
34,776
2,912
30Tractor DC C18
42,133
10,997
7,230
600
4,525
3,354
68,840
6,583
31 Tractor DC C17
38,077
7,642
7,141
600
2,459
3,354
59,273
5,950
32Tractor SC C18
116,748
8,328
7,275
600
5,450
3,354
141,755
18,242
33Tractor DC C18
63,736
11,477
7,141
600
2,459
3,354
88,766
9,959
34T Ref C18 MP
42,564
6,700
7,275
600
3,626
1,677
62,442
6,651
35T Ref C16-7 MP
34,744
4,236
7,141
600
2,489
1,677
50,886
5,429
36T Ref C18 U
42,564
6,700
7,275
600
3,626
1,677
62,442
6,651
37T Ref C16-7 U
34,284
4,236
7,141
600
2,489
1,677
50,426
5,357
38RV C18 R
67,652
6,700
7,454
600
2,666
1,677
86,750
10,571
39RV C16-7 R
71,928
4,236
7,364
600
2,426
1,677
88,232
11,239
40RV C14-5 R
45,760
5,093
7,051
600
-
1,677
60,181
7,150
42RV C18 MP
67,652
6,700
7,454
600
2,666
1,677
86,750
10,571
43RV C16-7 MP
65,942
4,236
7,364
600
2,426
1,677
82,245
10,303
44RV C14-5 MP
41,941
5,093
7,051
600
-
1,677
56,362
6,553
46B School C18 MP
31,950
6,700
7,454
600
2,666
1,677
51,048
4,992
47B School C16-7 MP
19,251
4,236
7,364
600
2,426
1,677
35,555
3,008
48B School C14-5 MP
14,345
5,093
7,051
600
-
1,677
28,766
2,241
49B School C12b-3 MP
13,542
5,093
7,141
600
-
1,677
28,053
2,116
50B School C18 U
30,263
6,700
7,454
600
2,666
1,677
49,361
4,729
5 IB School C16-7 U
19,251
4,236
7,364
600
2,426
1,677
35,555
3,008
52B School C14-5 U
13,366
5,093
7,051
600
-
1,677
27,787
2,088
53B School C12b-3 U
12,534
5,093
7,141
600
-
1,677
27,044
1,958
54Tractor SC C18
139,631
8,328
7,275
600
5,450
3,354
164,638
21,817
279
-------
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
55B Shuttle C12b-3 MP
19,694
5,093
7,141
600
-
1,677
34,205
3,077
56B Shuttle C14-5 U
18,991
5,093
7,051
600
-
1,677
33,412
2,967
57B Shuttle C12b-3 U
18,159
5,093
7,141
600
-
1,677
32,670
2,837
58B Shuttle C16-7 MP
31,645
4,236
7,364
600
2,426
1,677
47,948
4,945
59B Shuttle C16-7 U
29,357
4,236
7,364
600
2,426
1,677
45,660
4,587
60S Plow C16-7 MP
23,919
4,236
7,141
600
2,489
1,677
40,062
3,737
61S Plow C18 MP
47,307
6,700
7,230
600
4,674
1,677
68,189
7,392
62 S Plow C16-7 U
22,407
4,236
7,141
600
2,489
1,677
38,549
3,501
63 S Plow C18 U
46,507
6,700
7,230
600
4,674
1,677
67,389
7,267
64V Step C16-7 MP
20,339
4,236
7,141
600
2,421
1,677
36,414
3,178
65V Step C14-5 MP
13,028
5,093
7,051
600
-
1,677
27,449
2,036
66V Step C12b-3 MP
13,028
5,093
7,006
600
-
1,677
27,404
2,036
67V Step C16-7 U
18,769
4,236
7,141
600
2,421
1,677
34,844
2,933
68V Step C14-5 U
12,001
5,093
7,051
600
-
1,677
26,422
1,875
69V Step C12b-3 U
12,001
5,093
7,006
600
-
1,677
26,377
1,875
70S Sweep C16-7 U
21,837
4,236
7,141
600
2,489
1,677
37,980
3,412
71T Tanker C18 R
32,332
6,700
7,230
600
4,674
1,677
53,214
5,052
72T Tanker C18 MP
31,734
6,700
7,230
600
4,674
1,677
52,616
4,958
73T Tanker C18 U
31,568
6,700
7,230
600
4,674
1,677
52,450
4,933
74T Tow C18 R
49,558
6,700
7,230
600
4,674
1,677
70,440
7,743
75T Tow C16-7 R
36,058
4,236
7,141
600
2,489
1,677
52,201
5,634
76T Tow C18 U
47,977
6,700
7,230
600
4,674
1,677
68,859
7,496
77T Tow C16-7 U
31,264
4,236
7,141
600
2,489
1,677
47,407
4,885
78Tractor SC C18
100,054
8,328
7,275
600
5,450
3,354
125,061
15,633
80Tractor DC C18
77,624
9,369
7,230
600
4,674
3,354
102,852
12,129
81 Tractor DC C17
63,732
7,642
7,141
600
2,459
3,354
84,928
9,958
82Tractor DC C18
76,208
10,997
7,221
600
5,460
3,354
103,840
11,907
83Tractor DC C17
55,097
7,642
7,141
600
2,459
3,354
76,292
8,609
84Tractor DC C18
42,754
10,997
7,230
600
3,858
3,354
68,794
6,680
85B Transit C18 MP
56,627
6,700
7,454
600
2,666
1,677
75,725
8,848
86B Transit C16-7 MP
44,724
4,236
7,364
600
2,426
1,677
61,027
6,988
87B Transit C18 U
56,627
6,700
7,454
600
2,666
1,677
75,725
8,848
88B Transit C16-7 U
40,967
4,236
7,364
600
2,426
1,677
57,270
6,401
89T Utility C18 MP
30,535
6,700
7,230
600
4,674
1,677
51,417
4,771
90T Utility C18 R
31,310
6,700
7,230
600
4,674
1,677
52,191
4,892
91T Utility C16-7 MP
22,126
4,236
7,141
600
2,489
1,677
38,268
3,457
92T Utility C16-7 R
23,779
4,236
7,141
600
2,489
1,677
39,922
3,716
93T Utility C14-5 MP
14,390
5,093
7,051
600
-
1,677
28,811
2,248
94T Utility C12b-3 MP
13,651
5,093
7,006
600
-
1,677
28,027
2,133
95T Utility C14-5 R
15,382
5,093
7,051
600
-
1,677
29,803
2,403
96T Utility C12b-3 R
15,382
5,093
7,006
600
-
1,677
29,758
2,403
97T Utility C18 U
30,009
6,700
7,230
600
4,674
1,677
50,891
4,689
98T Utility C16-7 U
20,841
4,236
7,141
600
2,489
1,677
36,984
3,256
99T Utility C14-5 U
13,567
5,093
7,051
600
-
1,677
27,988
2,120
100T Utility C12b-3 U
12,718
5,093
7,006
600
-
1,677
27,094
1,987
lOlTractor DC C18
33,513
10,997
7,230
600
3,858
3,354
59,553
5,236
280
-------
Table 2-58 Direct Manufacturing BEV Costs Including IRA Tax Credit for MY 2030 (2022$)
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
01V Amb C14-5 MP
12,320
4,374
6,056
515
-
1,660
24,926
4,035
02V Amb C12b-3 MP
11,631
4,374
6,017
515
-
1,660
24,198
3,809
03V Amb C14-5 U
11,479
4,374
6,056
515
-
1,660
24,085
3,759
04V Amb C12b-3 U
10,765
4,374
6,017
515
-
1,660
23,332
3,525
05T Box C18 MP
25,121
5,755
6,210
515
4,014
1,660
43,276
8,227
06T Box C18 R
25,949
5,755
6,210
515
4,014
1,660
44,103
8,498
07T Box C16-7 MP
17,342
3,638
6,133
515
2,222
1,660
31,510
5,679
08T Box C16-7 R
18,862
3,638
6,133
515
2,222
1,660
33,030
6,177
09T Box C18 U
24,339
5,755
6,210
515
4,014
1,660
42,493
7,970
10T Box C16-7 U
16,711
3,638
6,133
515
2,222
1,660
30,880
5,473
11T Box C12b-3 U
10,307
4,374
6,056
515
-
1,660
22,912
3,375
12T Box C12b-3 R
12,153
4,374
6,056
515
-
1,660
24,758
3,980
13T Box C12b-3 MP
11,189
4,374
6,056
515
-
1,660
23,794
3,664
14T Box C14-5 U
10,307
4,374
6,056
515
-
1,660
22,912
3,375
15T Box C14-5 R
12,153
4,374
6,056
515
-
1,660
24,758
3,980
16T Box C14-5 MP
11,189
4,374
6,056
515
-
1,660
23,794
3,664
17B Coach C18 R
73,221
5,755
6,402
515
2,290
1,660
89,843
23,978
19C Mix C18 MP
44,074
5,755
6,210
515
4,014
1,660
62,228
14,433
20T Dump C18 U
29,123
5,755
6,210
515
4,014
1,660
47,277
9,537
2IT Dump C18 MP
29,499
5,755
6,210
515
4,014
1,660
47,653
9,660
22T Dump C16-7 MP
28,563
3,638
6,133
515
2,138
1,660
42,647
9,354
23T Dump C18 U
29,123
5,755
6,210
515
4,014
1,660
47,277
9,537
24T Dump C16-7 U
26,735
3,638
6,133
515
2,138
1,660
40,818
8,755
25T Fire C18 MP
30,969
5,755
6,210
515
4,014
1,660
49,123
10,141
26T Fire C18 U
31,034
5,755
6,210
515
4,014
1,660
49,188
10,163
27T Flat C16-7 MP
17,342
3,638
6,133
515
2,138
1,660
31,426
5,679
28T Flat C16-7 R
18,862
3,638
6,133
515
2,138
1,660
32,946
6,177
29T Flat C16-7 U
16,004
3,638
6,133
515
2,138
1,660
30,088
5,241
30Tractor DC C18
36,186
9,445
6,210
515
3,887
3,321
59,563
11,850
31Tractor DC C17
32,703
6,563
6,133
515
2,112
3,321
51,346
10,709
32Tractor SC C18
100,269
7,152
6,248
515
4,681
3,321
122,186
32,835
33Tractor DC C18
54,739
9,857
6,133
515
2,112
3,321
76,676
17,926
34T Ref C18 MP
36,556
5,755
6,248
515
3,114
1,660
53,849
11,971
35T Ref C16-7 MP
29,839
3,638
6,133
515
2,138
1,660
43,923
9,772
36T Ref C18 U
36,556
5,755
6,248
515
3,114
1,660
53,849
11,971
37T Ref C16-7 U
29,445
3,638
6,133
515
2,138
1,660
43,529
9,642
38RV C18 R
58,103
5,755
6,402
515
2,290
1,660
74,725
19,027
39RV C16-7 R
61,775
3,638
6,325
515
2,084
1,660
75,998
20,230
40RV C14-5 R
39,301
4,374
6,056
515
-
1,660
51,906
12,870
42RV C18 MP
58,103
5,755
6,402
515
2,290
1,660
74,725
19,027
281
-------
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
43RV C16-7 MP
56,634
3,638
6,325
515
2,084
1,660
70,856
18,546
44RV C14-5 MP
36,021
4,374
6,056
515
-
1,660
48,627
11,796
46B School C18 MP
27,440
5,755
6,402
515
2,290
1,660
44,063
8,986
47B School C16-7 MP
16,534
3,638
6,325
515
2,084
1,660
30,756
5,414
48B School C14-5 MP
12,320
4,374
6,056
515
-
1,660
24,926
4,035
49B School C12b-
3 MP
11,631
4,374
6,133
515
-
1,660
24,313
3,809
5OB School C18 U
25,991
5,755
6,402
515
2,290
1,660
42,614
8,512
5 IB School C16-7 U
16,534
3,638
6,325
515
2,084
1,660
30,756
5,414
52B School C14-5 U
11,479
4,374
6,056
515
-
1,660
24,085
3,759
53B School C12b-3 U
10,765
4,374
6,133
515
-
1,660
23,447
3,525
54Tractor SC C18
119,922
7,152
6,248
515
4,681
3,321
141,839
39,271
55B Shuttle C12b-
3 MP
16,914
4,374
6,133
515
-
1,660
29,596
5,539
56B Shuttle C14-5 U
16,311
4,374
6,056
515
-
1,660
28,916
5,341
57B Shuttle C12b-3 U
15,596
4,374
6,133
515
-
1,660
28,278
5,107
58B Shuttle C16-7 MP
27,178
3,638
6,325
515
2,084
1,660
41,400
8,900
59B Shuttle C16-7 U
25,213
3,638
6,325
515
2,084
1,660
39,435
8,257
60S Plow C16-7 MP
20,543
3,638
6,133
515
2,138
1,660
34,627
6,727
61S Plow C18 MP
40,629
5,755
6,210
515
4,014
1,660
58,784
13,305
62S Plow C16-7 U
19,244
3,638
6,133
515
2,138
1,660
33,328
6,302
63 S Plow C18 U
39,943
5,755
6,210
515
4,014
1,660
58,097
13,080
64V Step C16-7 MP
17,468
3,638
6,133
515
2,079
1,660
31,494
5,720
65V Step C14-5 MP
11,189
4,374
6,056
515
-
1,660
23,794
3,664
66V Step C12b-3 MP
11,189
4,374
6,017
515
-
1,660
23,756
3,664
67V Step C16-7 U
16,120
3,638
6,133
515
2,079
1,660
30,145
5,279
68V Step C14-5 U
10,307
4,374
6,056
515
-
1,660
22,912
3,375
69V Step C12b-3 U
10,307
4,374
6,017
515
-
1,660
22,874
3,375
70S Sweep C16-7 U
18,755
3,638
6,133
515
2,138
1,660
32,839
6,142
7IT Tanker C18 R
27,769
5,755
6,210
515
4,014
1,660
45,923
9,094
72T Tanker C18 MP
27,255
5,755
6,210
515
4,014
1,660
45,409
8,925
73T Tanker C18 U
27,113
5,755
6,210
515
4,014
1,660
45,267
8,879
74T Tow C18 R
42,563
5,755
6,210
515
4,014
1,660
60,718
13,938
75T Tow C16-7 R
30,969
3,638
6,133
515
2,138
1,660
45,053
10,141
76T Tow C18 U
41,205
5,755
6,210
515
4,014
1,660
59,360
13,494
77T Tow C16-7 U
26,851
3,638
6,133
515
2,138
1,660
40,935
8,793
78Tractor SC C18
85,931
7,152
6,248
515
4,681
3,321
107,848
28,140
80Tractor DC C18
66,668
8,046
6,210
515
4,014
3,321
88,774
21,832
81Tractor DC C17
54,736
6,563
6,133
515
2,112
3,321
73,380
17,925
82Tractor DC C18
65,451
9,445
6,202
515
4,689
3,321
89,623
21,433
83Tractor DC C17
47,320
6,563
6,133
515
2,112
3,321
65,963
15,496
84Tractor DC C18
36,719
9,445
6,210
515
3,313
3,321
59,523
12,025
85B Transit C18 MP
48,634
5,755
6,402
515
2,290
1,660
65,256
15,926
86B Transit C16-7 MP
38,411
3,638
6,325
515
2,084
1,660
52,633
12,579
87B Transit C18 U
48,634
5,755
6,402
515
2,290
1,660
65,256
15,926
88B Transit C16-7 U
35,184
3,638
6,325
515
2,084
1,660
49,406
11,522
282
-------
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
89T Utility C18 MP
26,225
5,755
6,210
515
4,014
1,660
44,379
8,588
90T Utility C18 R
26,890
5,755
6,210
515
4,014
1,660
45,045
8,806
9IT Utility C16-7 MP
19,003
3,638
6,133
515
2,138
1,660
33,087
6,223
92T Utility C16-7 R
20,423
3,638
6,133
515
2,138
1,660
34,507
6,688
93T Utility C14-5 MP
12,359
4,374
6,056
515
-
1,660
24,964
4,047
94T Utility C12b-3 MP
11,724
4,374
6,017
515
-
1,660
24,291
3,839
95T Utility C14-5 R
13,211
4,374
6,056
515
-
1,660
25,816
4,326
96T Utility C12b-3 R
13,211
4,374
6,017
515
-
1,660
25,778
4,326
97T Utility C18 U
25,773
5,755
6,210
515
4,014
1,660
43,928
8,440
98T Utility C16-7 U
17,900
3,638
6,133
515
2,138
1,660
31,983
5,862
99T Utility C14-5 U
11,652
4,374
6,056
515
-
1,660
24,257
3,816
100T Utility C12b-3 U
10,922
4,374
6,017
515
-
1,660
23,489
3,577
lOlTractor DC C18
28,783
9,445
6,210
515
3,313
3,321
51,587
9,426
Table 2-59 Direct Manufacturing BEV Costs and IRA Tax Credit for MY 2032 (2022$)
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
01V Amb C14-5 MP
11,542
4,097
5,673
483
-
1,644
23,438
1,345
02V Amb C12b-
3 MP
10,896
4,097
5,637
483
-
1,644
22,756
1,270
03V Amb C14-5 U
10,754
4,097
5,673
483
-
1,644
22,650
1,253
04V Amb C12b-3 U
10,084
4,097
5,637
483
-
1,644
21,945
1,175
05T Box C18 MP
23,533
5,391
5,817
483
3,761
1,644
40,628
2,742
06T Box C18 R
24,309
5,391
5,817
483
3,761
1,644
41,404
2,833
07T Box C16-7 MP
16,246
3,408
5,745
483
2,082
1,644
29,606
1,893
08T Box C16-7 R
17,670
3,408
5,745
483
2,082
1,644
31,030
2,059
09T Box C18 U
22,800
5,391
5,817
483
3,761
1,644
39,895
2,657
10T Box C16-7 U
15,655
3,408
5,745
483
2,082
1,644
29,016
1,824
11T Box C12b-3 U
9,655
4,097
5,673
483
-
1,644
21,552
1,125
12T Box C12b-3 R
11,385
4,097
5,673
483
-
1,644
23,282
1,327
13T Box C12b-3 MP
10,481
4,097
5,673
483
-
1,644
22,378
1,221
14T Box C14-5 U
9,655
4,097
5,673
483
-
1,644
21,552
1,125
15T Box C14-5 R
11,385
4,097
5,673
483
-
1,644
23,282
1,327
16T Box C14-5 MP
10,481
4,097
5,673
483
-
1,644
22,378
1,221
17B Coach C18 R
68,592
5,391
5,997
483
2,145
1,644
84,252
7,993
19C Mix C18 MP
41,288
5,391
5,817
483
3,761
1,644
58,383
4,811
20T Dump C18 U
27,282
5,391
5,817
483
3,761
1,644
44,377
3,179
2IT Dump C18 MP
27,634
5,391
5,817
483
3,761
1,644
44,729
3,220
283
-------
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
22T Dump C16-
7 MP
26,758
3,408
5,745
483
2,003
1,644
40,040
3,118
23T Dump C18 U
27,282
5,391
5,817
483
3,761
1,644
44,377
3,179
24T Dump C16-7 U
25,045
3,408
5,745
483
2,003
1,644
38,326
2,918
25T Fire C18 MP
29,011
5,391
5,817
483
3,761
1,644
46,106
3,380
26T Fire C18 U
29,072
5,391
5,817
483
3,761
1,644
46,167
3,388
27T Flat C16-7 MP
16,246
3,408
5,745
483
2,003
1,644
29,527
1,893
28T Flat C16-7 R
17,670
3,408
5,745
483
2,003
1,644
30,951
2,059
29T Flat C16-7 U
14,992
3,408
5,745
483
2,003
1,644
28,274
1,747
30Tractor DC C18
33,898
8,848
5,817
483
3,641
3,287
55,974
3,950
31Tractor DC C17
30,636
6,148
5,745
483
1,978
3,287
48,277
3,570
32Tractor SC C18
93,931
6,700
5,853
483
4,385
3,287
114,639
10,945
33Tractor DC C18
51,279
9,234
5,745
483
1,978
3,287
72,006
5,975
34T Ref C18 MP
34,246
5,391
5,853
483
2,917
1,644
50,533
3,990
35T Ref C16-7 MP
27,953
3,408
5,745
483
2,003
1,644
41,235
3,257
36T Ref C18 U
34,246
5,391
5,853
483
2,917
1,644
50,533
3,990
37T Ref C16-7 U
27,584
3,408
5,745
483
2,003
1,644
40,865
3,214
38RV C18 R
54,430
5,391
5,997
483
2,145
1,644
70,090
6,342
39RV C16-7 R
57,871
3,408
5,925
483
1,952
1,644
71,282
6,743
40RV C14-5 R
36,817
4,097
5,673
483
-
1,644
48,713
4,290
42RV C18 MP
54,430
5,391
5,997
483
2,145
1,644
70,090
6,342
43RV C16-7 MP
53,054
3,408
5,925
483
1,952
1,644
66,465
6,182
44RV C14-5 MP
33,744
4,097
5,673
483
-
1,644
45,641
3,932
46B School C18 MP
25,706
5,391
5,997
483
2,145
1,644
41,366
2,995
47B School C16-
7 MP
15,489
3,408
5,925
483
1,952
1,644
28,900
1,805
48B School C14-
5 MP
11,542
4,097
5,673
483
-
1,644
23,438
1,345
49B School C12b-
3 MP
10,896
4,097
5,745
483
-
1,644
22,864
1,270
5OB School C18 U
24,348
5,391
5,997
483
2,145
1,644
40,008
2,837
5 IB School C16-7 U
15,489
3,408
5,925
483
1,952
1,644
28,900
1,805
52B School C14-5 U
10,754
4,097
5,673
483
-
1,644
22,650
1,253
53B School C12b-
3 U
10,084
4,097
5,745
483
-
1,644
22,053
1,175
54Tractor SC C18
112,341
6,700
5,853
483
4,385
3,287
133,049
13,090
55B Shuttle C12b-
3 MP
15,845
4,097
5,745
483
-
1,644
27,814
1,846
56B Shuttle C14-5 U
15,280
4,097
5,673
483
-
1,644
27,176
1,780
57B Shuttle C12b-
3 U
14,610
4,097
5,745
483
-
1,644
26,579
1,702
58B Shuttle C16-
7 MP
25,460
3,408
5,925
483
1,952
1,644
38,872
2,967
59B Shuttle C16-7 U
23,620
3,408
5,925
483
1,952
1,644
37,031
2,752
60S Plow C16-7 MP
19,245
3,408
5,745
483
2,003
1,644
32,526
2,242
61S Plow C18 MP
38,061
5,391
5,817
483
3,761
1,644
55,156
4,435
284
-------
Battery
Cost
Power
BEVPT
DMC
without
Motor
Cost
($/unit)
Converter
Final
Drive
($/unit)
without
Battery
Vehicle ID
IRA
Battery
Tax
Credit
($/unit)
and
Electric
Accessories
($/unit)
Charger
($/unit)
Gearbox
($/unit)
IRA
Battery
Tax
Credit
($/veh)
Tax
Credit
($/veh)
62S Plow C16-7 U
18,028
3,408
5,745
483
2,003
1,644
31,310
2,101
63 S Plow C18 U
37,418
5,391
5,817
483
3,761
1,644
54,513
4,360
64V Step C16-7 MP
16,364
3,408
5,745
483
1,948
1,644
29,591
1,907
65V Step C14-5 MP
10,481
4,097
5,673
483
-
1,644
22,378
1,221
66V Step C12b-
3 MP
10,481
4,097
5,637
483
-
1,644
22,342
1,221
67V Step C16-7 U
15,101
3,408
5,745
483
1,948
1,644
28,328
1,760
68V Step C14-5 U
9,655
4,097
5,673
483
-
1,644
21,552
1,125
69V Step C12b-3 U
9,655
4,097
5,637
483
-
1,644
21,516
1,125
70S Sweep C16-7 U
17,569
3,408
5,745
483
2,003
1,644
30,851
2,047
7IT Tanker C18 R
26,013
5,391
5,817
483
3,761
1,644
43,108
3,031
72T Tanker C18 MP
25,532
5,391
5,817
483
3,761
1,644
42,627
2,975
73T Tanker C18 U
25,399
5,391
5,817
483
3,761
1,644
42,494
2,960
74T Tow C18 R
39,873
5,391
5,817
483
3,761
1,644
56,968
4,646
75T Tow C16-7 R
29,011
3,408
5,745
483
2,003
1,644
42,293
3,380
76T Tow C18 U
38,601
5,391
5,817
483
3,761
1,644
55,696
4,498
77T Tow C16-7 U
25,154
3,408
5,745
483
2,003
1,644
38,436
2,931
78Tractor SC C18
80,499
6,700
5,853
483
4,385
3,287
101,208
9,380
80Tractor DC C18
62,454
7,538
5,817
483
3,761
3,287
83,339
7,277
81Tractor DC C17
51,277
6,148
5,745
483
1,978
3,287
68,918
5,975
82Tractor DC C18
61,314
8,848
5,810
483
4,393
3,287
84,134
7,144
83Tractor DC C17
44,329
6,148
5,745
483
1,978
3,287
61,970
5,165
84Tractor DC C18
34,398
8,848
5,817
483
3,104
3,287
55,937
4,008
85B Transit C18 MP
45,560
5,391
5,997
483
2,145
1,644
61,220
5,309
86B Transit C16-
7 MP
35,983
3,408
5,925
483
1,952
1,644
49,394
4,193
87B Transit C18 U
45,560
5,391
5,997
483
2,145
1,644
61,220
5,309
88B Transit C16-7 U
32,960
3,408
5,925
483
1,952
1,644
46,372
3,841
89T Utility C18 MP
24,567
5,391
5,817
483
3,761
1,644
41,662
2,863
90T Utility C18 R
25,190
5,391
5,817
483
3,761
1,644
42,285
2,935
9IT Utility C16-
7 MP
17,802
3,408
5,745
483
2,003
1,644
31,083
2,074
92T Utility C16-7 R
19,132
3,408
5,745
483
2,003
1,644
32,414
2,229
93T Utility C14-
5 MP
11,578
4,097
5,673
483
1,644
23,475
1,349
94T Utility C12b-
3 MP
10,983
4,097
5,637
483
1,644
22,844
1,280
95T Utility C14-5 R
12,376
4,097
5,673
483
-
1,644
24,272
1,442
96T Utility C12b-
3 R
12,376
4,097
5,637
483
1,644
24,236
1,442
97T Utility C18 U
24,144
5,391
5,817
483
3,761
1,644
41,239
2,813
98T Utility C16-7 U
16,768
3,408
5,745
483
2,003
1,644
30,050
1,954
99T Utility C14-5 U
10,916
4,097
5,673
483
-
1,644
22,812
1,272
100T Utility C12b-
3 U
10,232
4,097
5,637
483
1,644
22,093
1,192
lOlTractor DC C18
26,964
8,848
5,817
483
3,104
3,287
48,503
3,142
285
-------
2.4.3.5 Qualified Commercial Clean Vehicle Tax Credits
IRA section 13403, "Qualified Commercial Clean Vehicles," (codified in the Internal
Revenue Code as section 45W) creates a tax credit for the purchase or lease of a qualified
commercial clean vehicle.1037 In our HD TRUCS analysis, we included in our quantitative
analysis the IRA battery tax credit described in RIA Chapter 2.4.3.1 and this vehicle tax credit.
As described in Section II.E.4 of the preamble, RIA Chapter 1, RIA Chapter 2.4.3.1, and RIA
Chapter 2.6.2.1.2, there are several other provisions in the IRA that we expect will support
electrification of the HD vehicle fleet.
IRA section 13403 creates a tax credit applicable to each purchase of a qualified commercial
clean vehicle. These vehicles must be on-road vehicles (or mobile machinery) that are propelled
to a significant extent by a battery-powered electric motor. The battery must have a capacity of at
least 15 kWh (or 7 kWh if it is Class 3 or below) and must be rechargeable from an external
source of electricity. This limits the qualified vehicles to BEVs, plug-in hybrid electric vehicles
(PHEVs) and FCEVs (see RIA Chapter 2.5.2.3).
The credit is available from CY 2023 through 2032, which overlaps with the model years for
which we are finalizing standards (MYs 2027-2032), so we included the tax credit in our
calculations for each of those years in HD TRUCS. For BEVs, the tax credit is equal to the lesser
of: (A) 30 percent of the BEV cost, or (B) the incremental cost of a BEV when compared to a
comparable ICE vehicle. The limit of this tax credit is $40,000 for Class 4-8 commercial
vehicles and $7,500 for commercial vehicles Class 3 and below. For example, if a BEV costs
$350,000 and a comparable ICE vehicle costs $150,0001038 the tax credit would be the lesser of:
(A) 30 percent x $350,000 = $105,000 or (B) $350,000 - $150,000 = $200,000. (A) is less than
(B), but (A) exceeds the limit of $40,000, so the tax credit would be $40,000.
In order to estimate the impact of this tax credit in our feasibility analysis for BEVs, we first
applied a retail price equivalent to our direct manufacturing costs for BEVs, FCEVs, and ICE
vehicles. Note that the direct manufacturing costs of BEVs were reduced by the amount of the
battery tax credit in IRA section 13502, as described previously and in Chapter 2.4.3.1. We
calculated the purchaser's incremental cost of BEVs compared to ICE vehicles and not the full
cost of vehicles in our analysis. We based our calculation of the tax credit on this incremental
cost. When the incremental cost exceeded the tax credit limitation (determined by gross vehicle
weight rating as described in the previous paragraph), we decreased the incremental cost by the
tax credit limitation. When the incremental cost was between $0 and the tax credit limitation, we
reduced the incremental cost to $0 (i.e., the tax credit received by the purchaser was equal to the
incremental cost). When the incremental cost was negative (i.e., the BEV was cheaper to
purchase than the ICE vehicle), no tax credit was given. In order for this calculation to be
appropriate, we determined that all Class 4-8 BEVs must cost more than $133,333 such that 30
percent of the cost is at least $40,000 (or $25,000 and $7,500, respectively, for BEVs Class 3 and
1037 Inflation Reduction Act of 2022, Pub. L. No. 117-169, 136 Stat. 1818 (2022). Available online:
https://www.congress.gov/l 17/bills/hr5376/BILLS-l 17hr5376enr.pdf.
1038 Sharpe, B., Basma, H. "A meta-study of purchase costs for zero-emission trucks". International Council on
Clean Transportation. February 17, 2022. Available online: https://theicct.org/wp-
content/uploads/2022/02/purchase-cost-ze-trucks-feb22-1 .pdf.
286
-------
below), and determined that this assumption is reasonable based on our review of the literature
on the costs of BEVs.1039
2.4.3.6 State Sales Tax and Federal Excise Tax
As explained in RIA Chapter 2.3.2.2 above, the NPRM version of HD TRUCS did not
include estimates for state sales taxes on the purchase of a vehicle or Federal Excise Tax (FET).
In response to comments, we have added these values to the final version of HD TRUCS. Sales
tax and FET are calculated by first applying a retail price equivalent (RPE) factor1040 to the BEV
powertrain DMC costs. One industry commenter recommended using a state sales tax rate of
5.02%, an average of the 50 state sales tax values, which we assessed and confirmed was
appropriate.1041 This rate was applied to the upfront costs (RPE) for all HD TRUCS vehicles for
the final rule analysis. A Federal Excise tax of 12% was applied to the upfront costs (RPE) for all
Class 8 (heavy heavy-duty) vehicles and all tractors.1042 The results of this analysis for MY
2032 as an example year are shown in Table 2-60.
Table 2-60 BEV Powertrain (PT) RPE, Sales Tax and FET for MY 2032 (2022$)
PT DMC
PT RPE
State Sales
Tax
($/veh)
Vehicle ID
without Battery
Tax Credit
($/veh)
with Battery
Tax Credit
($/veh)
FET
($/veh)
01V Amb C14-5 MP
23,438
31,938
-
1,603
02V Amb C12b-3 MP
22,756
31,044
-
1,558
03V Amb C14-5 U
22,650
30,911
-
1,552
04V Amb C12b-3 U
21,945
29,987
-
1,505
05T Box C18 MP
40,628
54,950
6,594
2,759
06T Box C18 R
41,404
55,961
6,715
2,809
07T Box C16-7 MP
29,606
40,148
-
2,015
08T Box C16-7 R
31,030
42,004
-
2,109
09T Box C18 U
39,895
53,995
6,479
2,711
10T Box C16-7 U
29,016
39,378
-
1,977
11T Box C12b-3 U
21,552
29,479
-
1,480
12T Box C12b-3 R
23,282
31,733
-
1,593
13T Box C12b-3 MP
22,378
30,556
-
1,534
14T Box C14-5 U
21,552
29,479
-
1,480
15T Box C14-5 R
23,282
31,733
-
1,593
16T Box C14-5 MP
22,378
30,556
-
1,534
17B Coach C18 R
84,252
111,645
13,397
5,605
19C Mix C18 MP
58,383
78,093
9,371
3,920
20T Dump C18 U
44,377
59,836
7,180
3,004
21T Dump C18 MP
44,729
60,296
7,235
3,027
22T Dump C16-7 MP
40,040
53,738
-
2,698
23T Dump C18 U
44,377
59,836
7,180
3,004
1039 Burnham, A., Gohlke, D., Rush, L., Stephens, T., Zhou, Y., Delucchi, M. A., Birky, A., Hunter, C., Lin, Z., Ou,
S., Xie, F., Proctor, C., Wiryadinata, S., Liu, N., Boloor, M. "Comprehensive Total Cost of Ownership
Quantification for Vehicles with Different Size Classes and Powertrains". Argonne National Laboratory. April 1,
2021. Available at https://publications.anl.gov/anlpubs/2021/05/167399.pdf.
1040 See Chapter 3.2 for a discussion of RPE.
1041 See page 38 of docket number EPA-HQ-OAR-2022-0985-2668-A1.
1042 U.S. Internal Revenue Service. 26 USC 4051. Available at
http://uscode.house.gov/view.xhtml?req=granuleid:USC-prelim-title26-section4051&num=0&edition=prelim
287
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PT DMC
PT RPE
State Sales
Tax
($/veh)
Vehicle ID
without Battery
Tax Credit
($/veh)
with Battery
Tax Credit
($/veh)
FET
($/veh)
24T Dump C16-7 U
38,326
51,505
-
2,586
25T Fire C18 MP
46,106
62,091
7,451
3,117
26T Fire C18 U
46,167
62,170
7,460
3,121
27T Flat C16-7 MP
29,527
40,036
-
2,010
28T Flat C16-7 R
30,951
41,892
-
2,103
29T Flat C16-7 U
28,274
38,402
-
1,928
30Tractor DC C18
55,974
75,533
9,064
3,792
31 Tractor DC C17
48,277
64,983
7,798
3,262
32Tractor SC C18
114,639
151,842
18,221
7,622
33Tractor DC C18
72,006
96,273
11,553
4,833
34T Ref C18 MP
50,533
67,766
8,132
3,402
35T Ref C16-7 MP
41,235
55,297
-
2,776
36T Ref C18 U
50,533
67,766
8,132
3,402
37T Ref C16-7 U
40,865
54,815
-
2,752
38RV C18 R
70,090
93,186
11,182
4,678
39RV C16-7 R
71,282
94,477
-
4,743
40RV C14-5 R
48,713
64,883
-
3,257
42RV C18 MP
70,090
93,186
11,182
4,678
43RV C16-7 MP
66,465
88,199
-
4,428
44RV C14-5 MP
45,641
60,878
-
3,056
46B School C18 MP
41,366
55,744
6,689
2,798
47B School C16-7 MP
28,900
39,233
-
1,970
48B School C14-5 MP
23,438
31,938
-
1,603
49B School C12b-3 MP
22,864
31,198
-
1,566
50B School C18 U
40,008
53,974
6,477
2,710
5 IB School C16-7 U
28,900
39,233
-
1,970
52B School C14-5 U
22,650
30,911
-
1,552
53B School C12b-3 U
22,053
30,140
-
1,513
54Tractor SC C18
133,049
175,840
21,101
8,827
55B Shuttle C12b-3 MP
27,814
37,649
-
1,890
56B Shuttle C14-5 U
27,176
36,810
-
1,848
57B Shuttle C12b-3 U
26,579
36,040
-
1,809
58B Shuttle C16-7 MP
38,872
52,231
-
2,622
59B Shuttle C16-7 U
37,031
49,832
-
2,502
60S Plow C16-7 MP
32,526
43,945
-
2,206
61S Plow C18 MP
55,156
73,887
8,866
3,709
62 S Plow C16-7 U
31,310
42,359
-
2,126
63 S Plow C18 U
54,513
73,048
8,766
3,667
64V Step C16-7 MP
29,591
40,113
-
2,014
65V Step C14-5 MP
22,378
30,556
-
1,534
66V Step C12b-3 MP
22,342
30,505
-
1,531
67V Step C16-7 U
28,328
38,466
-
1,931
68V Step C14-5 U
21,552
29,479
-
1,480
69V Step C12b-3 U
21,516
29,428
-
1,477
70S Sweep C16-7 U
30,851
41,761
-
2,096
71T Tanker C18 R
43,108
58,183
6,982
2,921
72T Tanker C18 MP
42,627
57,555
6,907
2,889
73T Tanker C18 U
42,494
57,382
6,886
2,881
74T Tow C18 R
56,968
76,248
9,150
3,828
75T Tow C16-7 R
42,293
56,675
-
2,845
288
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PT DMC
PT RPE
State Sales
Tax
($/veh)
Vehicle ID
without Battery
Tax Credit
($/veh)
with Battery
Tax Credit
($/veh)
FET
($/veh)
76T Tow C18 U
55,696
74,590
8,951
3,744
77T Tow C16-7 U
38,436
51,648
-
2,593
78Tractor SC C18
101,208
134,335
16,120
6,744
80Tractor DC C18
83,339
111,064
13,328
5,575
81 Tractor DC C17
68,918
91,888
11,027
4,613
82Tractor DC C18
84,134
112,326
13,479
5,639
83Tractor DC C17
61,970
82,832
9,940
4,158
84Tractor DC C18
55,937
75,423
9,051
3,786
85B Transit C18 MP
61,220
81,623
9,795
4,097
86B Transit C16-7 MP
49,394
65,947
-
3,311
87B Transit C18 U
61,220
81,623
9,795
4,097
88B Transit C16-7 U
46,372
62,007
-
3,113
89T Utility C18 MP
41,662
56,298
6,756
2,826
90T Utility C18 R
42,285
57,110
6,853
2,867
91T Utility C16-7 MP
31,083
42,064
-
2,112
92T Utility C16-7 R
32,414
43,798
-
2,199
93T Utility C14-5 MP
23,475
31,985
-
1,606
94T Utility C12b-3 MP
22,844
31,159
-
1,564
95T Utility C14-5 R
24,272
33,025
-
1,658
96T Utility C12b-3 R
24,236
32,974
-
1,655
97T Utility C18 U
41,239
55,746
6,690
2,798
98T Utility C16-7 U
30,050
40,717
-
2,044
99T Utility C14-5 U
22,812
31,122
-
1,562
100T Utility C12b-3 U
22,093
30,179
-
1,515
lOlTractor DC C18
48,503
65,732
7,888
3,300
2.4.4 BEV Operating Costs
Operating costs for HD vehicles encompass a variety of costs, such as labor, insurance,
registration fees, charging, maintenance and repair (M&R), and other costs. For this analysis, we
are primarily interested in costs that could differ for a comparable diesel-powered ICE vehicle
and a ZEV. These operational cost differences are used to calculate an estimated payback period
in HD TRUCS. We focus on charging costs, M&R costs, insurance costs, and ZEV state
registration fees1043 because we expect these costs to be different for ZEVs than for comparable
ICE vehicles.
For each BEV in HD TRUCS, the 10-year average annual operating costs are as shown in
Table 2-61 and described in the sections below. As discussed in Chapter 2.2.1.1.3, for the final
version for HD TRUCS, we have assessed each year of operation using the appropriate changes
that occur over time for inputs such as VMT, maintenance and repair, and fuel costs; however,
we are continuing to show a 10-year average values in tables such as the one below, as a single
value point of comparison. Note that the annual insurance cost represents the incremental
1043 Insurance costs and ZEV registration fees were not included in the proposal; EPA added these costs to the final
version of HD TRUCS after consideration of comments. See RIA Chapter 2.4.4.3 and 2.4.4.4.
289
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insurance cost of the BEV powertrain only, not the total insurance cost for the complete BEV.
Appendix A to this RIA includes each year of a 10-year schedule for VMT.
Table 2-61 BEV Operating Costs for a MY 2032 Vehicle (2022$, 10-Year Average)
Vehicle ID
Annual BEV
M&R ($/year)
Annual Charging
Cost ($/year)
Annual Powertrain Insurance Cost1044 +
$100 annual ZEV Reg. Fee ($/year)
01V Amb C14-5 MP
1418
1063
1378
02V Amb C12b-3 MP
2065
1461
1321
03V Amb C14-5 U
1634
1141
1378
04V Amb C12b-3 U
1662
1088
1321
05T Box C18 MP
2759
4216
2535
06T Box C18 R
2683
4271
2535
07T Box C16-7 MP
1666
1757
1471
08T Box C16-7 R
1620
1874
1471
09T Box C18 U
2759
4085
2253
10T Box C16-7 U
1625
1579
1471
11T Box C12b-3 U
2481
1555
1301
12T Box C12b-3 R
2481
1834
1301
13T Box C12b-3 MP
2481
1688
1301
14T Box C14-5 U
1593
999
1305
15T Box C14-5 R
1593
1178
1305
16T Box C14-5 MP
1593
1084
1305
17B Coach C18 R
6534
15516
2016
19C Mix C18 MP
3735
10014
2253
20T Dump C18 U
1672
2666
2535
2IT Dump C18 MP
1672
2700
2535
22T Dump C16-7 MP
2348
2619
1463
23T Dump C18 U
1672
2666
2253
24T Dump C16-7 U
2348
2452
1463
25T Fire C18 MP
1672
2835
2535
26T Fire C18 U
1672
2841
2253
27T Flat C16-7 MP
1666
1757
1463
28T Flat C16-7 R
1666
1911
1463
29T Flat C16-7 U
1666
1621
1463
30Tractor DC C18
3875
6345
2666
31Tractor DC C17
3876
5306
2118
32Tractor SC C18
17603
35944
2762
33Tractor DC C18
8617
18972
2142
34T Ref C18 MP
2237
4170
2126
35T Ref C16-7 MP
4028
6129
1463
36T Ref C18 U
2237
4170
2126
37T Ref C16-7 U
4028
6048
1463
38RV C18 R
513
521
1525
39RV C16-7 R
513
554
1467
40RV C14-5 R
513
353
1279
42RV C18 MP
513
521
1525
43RV C16-7 MP
513
508
1467
44RV C14-5 MP
513
323
1279
46B School C18 MP
1985
3275
1525
1044 As described at the beginning of Chapter 2.3, this analysis is examining the incremental cost differences
between a comparable ICE vehicle and ZEV technologies; therefore, insurance costs are estimated based on the
upfront cost of powertrain components that are expected to differ for a comparable ICE vehicle and ZEV.s.
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Vehicle ID
Annual BEV
M&R ($/year)
Annual Charging
Cost ($/year)
Annual Powertrain Insurance Cost1044 +
$100 annual ZEV Reg. Fee ($/year)
47B School C16-7 MP
2113
2101
1467
48B School C14-5 MP
1985
1471
1279
49B School C12b-3 MP
1985
1388
1336
5OB School C18 U
1985
3102
1525
5 IB School C16-7 U
2113
2101
1467
52B School C14-5 U
1985
1370
1279
53B School C12b-3 U
1985
1285
1336
54Tractor SC C18
17603
42990
2762
55B Shuttle C12b-3 MP
4868
3301
1336
56B Shuttle C14-5 U
4868
3183
1279
57B Shuttle C12b-3 U
4868
3043
1336
58B Shuttle C16-7 MP
4868
5304
1467
59B Shuttle C16-7 U
4868
4920
1467
60S Plow C16-7 MP
1666
1874
1463
61S Plow C18 MP
1849
2934
2535
62S Plow C16-7 U
1666
1755
1463
63 S Plow C18 U
1849
2884
2253
64V Step C16-7 MP
2546
2685
1460
65V Step C14-5 MP
1593
1084
1279
66V Step C12b-3 MP
2412
1656
1321
67V Step C16-7 U
2546
2477
1460
68V Step C14-5 U
1593
999
1279
69V Step C12b-3 U
2412
1525
1321
70S Sweep C16-7 U
2107
2404
1463
7IT Tanker C18 R
2157
3644
2535
72T Tanker C18 MP
2157
3576
2253
73T Tanker C18 U
2157
3558
2253
74T Tow C18 R
2692
4452
2612
75T Tow C16-7 R
2344
2821
1463
76T Tow C18 U
2692
4310
2253
77T Tow C16-7 U
2344
2446
1463
78Tractor SC C18
12573
30805
2762
80Tractor DC C18
4431
10002
2792
81Tractor DC C17
8615
18971
2118
82Tractor DC C18
8615
22685
2762
83Tractor DC C17
4807
6544
2118
84Tractor DC C18
4794
12727
2598
85B Transit C18 MP
5612
8078
2016
86B Transit C16-7 MP
3312
3486
1467
87B Transit C18 U
5612
8078
1993
88B Transit C16-7 U
3312
3193
1467
89T Utility C18 MP
1116
1780
2535
90T Utility C18 R
1116
1825
2535
9IT Utility C16-7 MP
2057
2377
1463
92T Utility C16-7 R
2057
2555
1463
93T Utility C14-5 MP
2057
1546
1378
94T Utility C12b-3 MP
941
671
1321
95T Utility C14-5 R
2000
1621
1378
96T Utility C12b-3 R
2000
1621
1321
97T Utility C18 U
1116
1749
2253
98T Utility C16-7 U
2057
2239
1463
99T Utility C14-5 U
2057
1458
1378
291
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Vehicle ID
Annual BEV
M&R ($/year)
Annual Charging
Cost ($/year)
Annual Powertrain Insurance Cost1044 +
$100 annual ZEV Reg. Fee ($/year)
100T Utility C12b-3 U
941
625
1321
lOlTractor DC C18
2412
3954
2598
2.4.4.1 Maintenance and Repair
Data on real-world maintenance and repair costs for heavy-duty BEVs is sparse due to limited
heavy-duty BEV technology adoption today. We expect the overall maintenance costs to be
lower for heavy-duty BEVs than for a comparable ICE vehicle for several reasons. First, an
electric powertrain has fewer moving parts that accrue wear or need regular adjustments. Second,
BEVs do not require fluids such as engine oil or DEF, nor do they require exhaust filters to
reduce particulate matter or other pollutants. Third, the per-mile rate of brake wear is expected to
be lower for BEVs due to regenerative braking systems. Several literature sources apply a
scaling factor to diesel vehicle maintenance costs to estimate BEV maintenance costs.1045'1046'1047
We followed this approach and, for the proposal, applied a repair cost scaling factor of 0.71 to
the maintenance and repair costs for diesel-fueled ICE vehicles. The 0.71 scaling factor was
based on an analysis from Wang et al. 2022, that estimates a future BEV HD vehicle would have
a 29 percent reduction compared to a diesel-powered HD vehicle.1048
Commenters noted the potential need to retrain technicians to work on BEVs. We agree that
there may be a transition period during which costs for maintaining and repairing BEVs will not
be at their full savings potential due to the need to train more of the workforce to maintain and
repair BEVs. To account for this period, in this final rule EPA has phased in the BEV scaling
factors for maintenance and repair. Specifically, instead of applying a single scaling factor for
every year commencing in 2027 as at proposal, EPA is starting with a higher scaling factor and
gradually decreasing it (i.e., gradually increasing the projected cost savings) from calendar year
2027-2032. The initial higher scaling factor (0.88) also comes from Wang et al. and reflects
estimates for 2022. EPA's approach of applying this factor commencing in 2027 is consequently
conservative given that technicians in those later years will be more experienced than they were
in 2022. These values, shown in Table 2-62, are multiplied by the annual diesel maintenance and
repair costs by calendar year in order to assess the costs for BEV vehicle maintenance and repair.
1045 Burnham, A., Gohlke, D., Rush, L., Stephens, T., Zhou, Y., Delucchi, M. A., Birky, A., Hunter, C., Lin, Z., Ou,
S., Xie, F., Proctor, C., Wiryadinata, S., Liu, N., Boloor, M. "Comprehensive Total Cost of Ownership
Quantification for Vehicles with Different Size Classes and Powertrains". Argonne National Laboratory. April 1,
2021. Available online: https://publications.anl.gov/anlpubs/2021/05/167399.pdf.
1046 Hunter, Chad, Michael Penev, Evan Reznicek, Jason Lustbader, Alicia Birkby, and Chen Zhang. "Spatial and
Temporal Analysis of the Total Cost of Ownership for Class 8 Tractors and Class 4 Parcel Delivery Trucks".
National Renewable Energy Lab. September 2021. Available online: https://www.nrel.gov/docs/fV2losti/71796.pdf.
1047 Burke, Andrew, Marshall Miller, Anish Sinha, et. al. "Evaluation of the Economics of Battery-Electric and Fuel
Cell Trucks and Buses: Methods, Issues, and Results". August 1, 2022. Available online:
https://escholarship.org/uc/item/lg89p8dn.
1048 Wang, G., Miller, M., and Fulton, L." Estimating Maintenance and Repair Costs for Battery Electric and Fuel
Cell Heavy Duty Trucks, 2022. Available online:
https://escholarship.org/content/at36c08395/qt36c08395 noSplash 589098e470b036b3010eae00f3b7b618.pdf?t=r6
zwib.
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Table 2-62 Maintenance and Repair Scaling Factors for BEV CY 2027 - 2032+
CY
2027
2028
2029
2030
2031
2032+
Factor
0.88
0.846
0.812
0.778
0.744
0.71
In our payback analysis in HD TRUCS, we did not account for potential diesel engine rebuild
costs for ICE vehicles, potential replacement battery costs for BEVs, or potential replacement
fuel cell stack costs for FCEVs because our payback analysis typically covers a shorter period of
time than the expected life of these components. Typical battery warranties being offered by HD
BEV manufacturers range between 8 and 15 years today.1049 A BEV battery replacement may be
practically necessary over the life of a vehicle if the battery deteriorates to a point where the
vehicle range no longer meets the vehicle's operational needs. We believe that proper vehicle
and battery maintenance and management can extend battery life, and our use of 2,000 cycles for
battery sizing in HD TRUCS is a conservative means of assuring that no battery replacement is
needed for the first 10 years of a vehicle at issue in our HD TRUCS analysis. See RIA Chapter
2.4.1.1.4. For example, manufacturers can utilize battery management system to maintain the
temperature of the battery1050 as well active battery balancing to extend the life of the
battery.1051'1052 Likewise, pre-conditioning has also shown to extend the life of the battery as
well.1053 Furthermore, research suggests that battery life is expected to improve with new
batteries over time as battery chemistry and battery charging strategies improve, such that newer
MY BEVs will have longer battery life.
2.4.4.2 Charging Costs
The annual charging cost is a function of the electricity price, daily energy consumption of a
BEV, and number of operating days in a year. There are energy losses between the meter and the
battery associated with the AC/DC converter and battery charge and discharge that are in
addition to the losses accounted for in the electrified powertrain (as described in RIA Chapter
2.4.1.1.3) so the electrical power purchased (as measured at the meter) is greater than the
electrical power applied at the axle. For the AC/DC converter we used an efficiency value of
94% and a value of 95% for battery charge and discharge efficiency, consistent with the values
used in MOVES.
For the final rule, we differentiate between depot charging and public charging when
assigning charging costs. We have also expanded the scope of what is covered in these costs to
more accurately capture the cost of charging. The charging costs we use for both charging types
1049 Type C BEV school bus battery warranty range five to fifteen years according to
https://www.nYapt.org/resources/DocumentsAVRI ESB-Buvers-Guide US-Market 2022.pdf. The Freightliner
electric walk-in van includes an eight year battery warranty according to https://www.electricwalkinvan.com/wp-
content/uploads/2022/05/MT50e-specifications-2022.pdf.
1050 Basma, Hussein, Charbel Mansour, Marc Haddad, MarounNemer, Pascal Stabat. "Comprehensive energy
modeling methodology for battery electric buses". Energy: Volume 207, 15 September 2020, 118241. Available
online: https://www.sciencedirect.com/science/article/pii/S036054422Q313487.
1051 Bae, SH., Park, J.W., Lee, S.H. "Optimal SOC Reference Based Active Cell Balancing on a Common
Energy Bus of Battery" Available online: http://koreascience.or.kr/article/JAK0201709641401357.pdf.
1052 Azad, F.S., AhasanHabib, A.K.M., Rahman, A., Ahmed I. "Active cell balancing of Li-Ion batteries using
single capacitor and single LC series resonant circuit." https://beei.org/index.php/EEI/article/viewFile/1944/1491.
1053 Prejean, Louis. "How to Improve EV Battery Performance in Cold Weather" Accessed on March 31, 2023.
https://www.worktruckonline.com/10176367/how-to-improve-ev-batterv-performance-in-cold-weather.
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include the cost of electricity as charged by the utility (cents/kWh) as well as costs for EVSE
maintenance and grid distribution upgrades (expressed in cents/kWh).1054 Our public charging
price additionally includes the amortized cost of public charging equipment, land costs for the
station and other costs described below; we project that third parties may install and operate
these stations and pass costs onto BEV owners via charging costs.
To estimate charging costs, we start by modeling future electricity prices, as charged by
utilities, that account for the costs of BEV charging demand and the associated distribution
system upgrade costs. We do this in three steps: 1) we model future power generation using the
Integrated Planning Model (IPM), 2) we estimate the cost of distribution system upgrades
associated with charging demand through the DOE Transportation Electrification Impact Study
(TEIS), 1055 and 3) we use the Retail Price Model to project electricity prices accounting for both
(1) and (2).
As described in RIA Chapter 4.2, IPM models the power sector, including changes to power
generation based on future demand scenarios. In order to capture the potential future impacts on
the power sector from ZEVs, we ran IPM for a scenario that combined electricity demand from
an interim version of the final standards case and EPA's proposed rulemaking "Multi-Pollutant
Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty
Vehicles."1056 >1057 The same demand scenario was used as the action case for the TEIS.1058 The
TEIS research team modeled how many new or upgraded substations, feeders, and transformers
would be needed to meet projected electricity demand from transportation, including demand
from residential workplace, depot, and public charging to support projected light-, medium-, and
heavy-duty plug-in electric vehicles. For all public and workplace charging, vehicles were
assumed to charge at full power upon arrival. At homes and depot charging stations—where
vehicles have longer dwell times—a conservative managed charging scenario was developed to
spread out charging and reduce peak power (vehicles arriving at charging locations minimize
charging power such that the session is completed when the vehicle departs).1059 (See RIA
Chapter 1.6.5 for a discussion of the potential benefits of managed charging to fleet owners.)
1054 While EVSE maintenance costs associated with depot charging infrastructure may be borne directly by the fleet
owner, it will occur over the lifetime of the EVSE rather than as an upfront capital cost. Therefore, we have
accounted for it as part of our operating cost analysis rather than as part of the upfront depot EVSE costs discussed
in RIA Chapter 2.6.2.
1055 National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, Kevala Inc., and U.S.
Department of Energy. "Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-,
Medium-, and Heavy-Duty Electric Vehicles". DOE/EE-2818. U.S. Department of Energy. March 2024.
1056 Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles
(88 FR 29184, May 5, 2023)
1057 Electricity demand for heavy-duty ZEVs was based on the interim control case described in RIA Chapter 4.2.4
and for light- and medium-duty vehicles was based Alternative 3 from the proposed "Multipollutant Emissions
Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles." See the TEIS report for more
information on the modeled ('Action', 'Managed') scenario, and how demand was allocated by region and time of
day.
1058 National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, Kevala Inc., and U.S.
Department of Energy. "Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-,
Medium-, and Heavy-Duty Electric Vehicles". DOE/EE-2818. U.S. Department of Energy. March 2024 at 3.
1059 TEIS at 4.
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The changes to power generation in our modeled IPM scenario and the distribution cost
estimates from TEIS1060 were then input to the Retail Price Model (RPM).1061 The RPM
developed by ICF generates estimates for average electricity prices over consumer classes
accounting for the regional distribution of electricity demand. The resulting national average
retail prices, which include distribution upgrade costs, were used as a basis for the charging costs
in HD TRUCS and are shown in Table 2-63. For comparison purposes, we also estimated retail
prices for the same demand scenario without including the distribution upgrades costs associated
with charging demand. We find that electricity prices would be 11.1 (rather than 11.3)
cents/kWh in 2030 and 9.8 (rather than 10.4) cents/kWh in 2050 showing the cost of distribution
upgrades increased electricity prices between about two percent and six percent over this
timeframe. As described in RTC Section 7, for comparison purposes, we also ran IPM and RPM
for a no action case with unmanaged charging.1062 We think this is a reasonable comparison to
make given the considerable economic benefits of managed charging, particularly in light of the
increased EV adoption associated with the modeled potential compliance pathway of the final
rule, which provides an extremely strong economic incentive for market actors to adopt managed
charging practices. Our analysis projects that there is almost no difference in retail electricity
prices in 2030 and the difference in 2050 is only about 2.5 percent.
Table 2-63 Retail Electricity Prices for select years (2022 cents/kWh) 1063 1064
2027
2028
2030
2035
2040
2045
2050
2055
11.8
11.8
11.3
11.2
11.1
10.8
10.4
10.4
To estimate depot charging costs in HD TRUCS, we add 0.52 cents/kWh to the RPM results
in Table 2-63 (and for intermediate years) to account for EVSE maintenance costs. This value is
from a recent ICCT study1065 which was suggested in public comments (see RTC Section 6). For
public charging, we project an electricity price of 19.6 cents/kWh for 2027 and adjust it for
future years according to the results of the IPM Retail Price Model discussed above. The initial
value from the same ICCT study1066 reflects costs for public charging at stations designed for
1060 Electricity demand for heavy-duty ZEVs was based on the interim control case described in RIA Chapter 4.2.4
and for light- and medium-duty vehicles was based Alternative 3 from the proposed "Multipollutant Emissions
Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles." See the TEIS report for more
information on the modeled ('Action', 'Managed') scenario, and how demand was allocated by region and time of
day.
1061 ICF. "Documentation of the Retail Price Model. Draft." 2019. Available online:
https://www.epa.gov/sites/default/files/2019-06/documents/rpm_documentationjune2019.pdf.
1062 This scenario is the TEIS 'No Action', 'Unmanaged' scenario, see TEIS 2-4 for details.
i°63IPM and the RPM were run for select years between 2028 and 2050. We used linear interpolation for electricity
prices between model run years from 2028-2050. We kept electricity prices constant for 2050+ and assumed the
2027 price was the same as 2028. We converted outputs of the RPM from 2019$ to 2022$.
1064 The results from the RPM (along with input files used for power sector modeling) discussed here are available in
the docket. (See Evan Murray. Memorandum to Docket EPA-HQ-OAR-2022-0985. "Files from IPM Runs
Supporting FRM Modeling." March 2024.)
1065 Hussein Basma, Claire Buy see, Yuanrong Zhou, and Felipe Rodriguez. "Total Cost of Ownership of Alternative
Powertrain Technologies for Class 8 Long-haul Trucks in the United States." April 2023. Available online:
https://theicct.org/wp-content/uploads/2023/04/tco-alt-powertrain-long-haul-trucks-us-apr23.pdf.
1066 Hussein Basma, Claire Buysee, Yuanrong Zhou, and Felipe Rodriguez. "Total Cost of Ownership of Alternative
Powertrain Technologies for Class 8 Long-haul Trucks in the United States." April 2023. Available online:
https://theicct.org/wp-content/uploads/2023/04/tco-alt-powertrain-long-haul-trucks-us-apr23.pdf.
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long-haul vehicles. Stations are assumed to have seventeen 1 MW EVSE ports and twenty 150
kW EVSE ports for a total peak power capacity of 20 MW. The 19.6 cents/kWh price includes
the amortized cost of this charging equipment, land costs, both electricity prices (cents/kWh) and
demand charges (cents/kW) associated with high peak power, distribution upgrade costs for
substations, feeders, and transformers, and EVSE maintenance costs. As discussed in Chapter
2.6.2.1.2, we expect the 30C tax credit1067 to significantly reduce the costs for procuring and
installing EVSE where applicable. DOE assessed the average value of this tax credit for both
depot and public charging infrastructure serving HD BEVs taking into account the potential
share of EVSE in eligible census tracts, 30C prevailing wage and apprenticeship requirements
and the $100,000 per item cap.1068 DOE estimated average value of this tax credit for public
charging infrastructure to be 27 percent of the installed costs for EVSE under 1 MW, and 19
percent for 1 MW or higher EVSE. However, we did not reduce the amortized cost of public
charging infrastructure (which was sourced from the ICCT study) to account for this tax credit,
and therefore, these costs may be considered conservative.
We apply public electricity prices to long-haul vehicles, some longer-range day cab tractors
and coach buses. Overall, our charging costs used in the final rule analysis are higher than those
used in the NPRM analysis, particularly since those costs now reflect maintenance, grid
distribution upgrades, and public charging costs.
Table 2-64 Charging Costs (2022$)
CY
Depot
(cents/kWh)
Public
(cents/kWh)
2027
12.36
19.60
2028
12.36
19.60
2029
12.09
19.33
2030
11.83
19.07
2031
11.81
19.05
2032
11.79
19.03
2033
11.77
19.02
2034
11.76
19.00
2035
11.74
18.98
2036
11.72
18.97
2037
11.71
18.95
2038
11.70
18.94
2039
11.68
18.92
2040
11.67
18.91
2041
11.61
18.85
2.4.4.3 Insurance Cost
In the NPRM analysis, we did not take into account the cost of insurance on the ZEV
purchaser. A few commenters suggested we should consider the addition of insurance cost
because the incremental cost of insurance for the ZEVs will be higher than for ICE vehicles. We
1067 IRA Section 13404, "Alternative Fuel Refueling Property Credit" under section 26 U.S. Code §30C, referred to
as 30C in this document.
1068 U.S. DOE, "Estimating Federal Tax Incentives for Heavy Duty Electric Vehicle Infrastructure and for Acquiring
Electric Vehicles Weighing Less Than 14,000 Pounds," Memorandum, March 2024.
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agree that insurance costs may differ between these vehicle types and that this is a cost that will
be seen by the operator. Therefore, for the final rule analysis in HD TRUCS, we included the
incremental insurance costs of a ZEV relative to an ICE vehicle by incorporating an annual
insurance cost. A commenter recommended using an insurance rate of 3%, based originally on
an ICCT April 2023 paper on ZEV TCO.1069 We have reviewed the comment and the ICCT
White Paper and consider the 3% insurance rate to be reasonable. Similar to sales tax and the
FET, insurance costs are calculated as a percentage, after applying the RPE, to the upfront costs
shown in Table 2-60; however, unlike the sales tax and FET, the insurance costs are added to
operating costs each year in HD TRUCS, as part of the payback calculation. See Table 2-61 for
MY 2032 BEV insurance costs.
2.4.4.4 ZEV Registration Fee
Some states have adopted ZEV registration fees. Though 18 states do not have an additional
ZEV registration fee, of the 32 states that do, the registration fees are generally between $50 and
$225 per year.1070 While EPA cannot predict whether and to what extent other states will enact
ZEV registration fees, we have nonetheless conservatively added an annual registration fee of
$100 to all ZEV vehicles in our final HD TRUCS analysis. See RTC Section 3 for further
discussion.
2.5 Fuel Cell Electric Vehicle Technology
We considered HD FCEVs for select applications that travel long distances and/or have heavy
loads. Our analysis in HD TRUCS evaluates a FCEV as having similar components as a BEV
plus a fuel cell and an onboard hydrogen storage tank, with variations in the sizing of key
components. Rather than focusing on depot hydrogen fueling infrastructure costs that would be
incurred upfront, we included infrastructure costs in our per-kilogram retail price of
hydrogen.1071 This approach is consistent with the method we use in HD TRUCS for ICE
vehicles, where the equivalent diesel fuel costs are included in the diesel fuel price instead of
accounting for the costs of fuel stations separately, and consistent as well with our inclusion of
public charging infrastructure costs within the price of charging (see RIA Chapter 2.4.4.2 above).
To compare ICE and heavy-duty FCEV technology costs and performance, this section
explains how we characterize heavy-duty FCEVs based on the performance and use criteria in
RIA Chapter 2.2. First, we determined the size of key FCEV components based on power
requirements and the hydrogen fuel amount required to meet the energy and daily operational
needs of each vehicle, and projected energy and fuel use for each FCEV application (kWh/mi) on
an annual basis. Then, we estimated upfront DMC of FCEV components. Next, the upfront DMC
costs are presented as RPE costs, and state sales tax and excise taxes are added, where
applicable. Lastly, we projected the hydrogen fueling costs, maintenance and repair costs,
insurance costs, and an annual ZEV registration fee for each vehicle type for the first ten years of
vehicle operation. Table 2-65 shows the technical properties for four vehicle types that travel
1069 Basma, Hussein, et.al. "Total Cost of Ownership of Alternative Powertrain Technologies for Class 8 Long-Haul
Trucks in the United States." April 2023. Page 17. Available online: https://theicct.org/wp-
content/uploads/2023/04/tco-alt-powertrain-long-haul-trucks-us-apr23.pdf
1070 National Conference of State Legislatures. "Special Fees on Plug-In Hybrid and Electric Vehicles" March 2023,
Available at: https://www.ncsl.org/energy/special-fees-on-plug-in-hybrid-and-electric-vehicles..
1071 Retail price of hydrogen is the total price of hydrogen when it becomes available to the end user, including the
costs of production, distribution, storage, and dispensing at a fueling station.
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long distances (e.g., for duty cycles where the volume or weight of a BEV battery may impact
payload).1072 The FCEV properties analyzed in HD TRUCS as part of the compliance pathway to
support the final standards include power output of the fuel cell and e-motor, battery energy,
hydrogen fuel tank capacity, and daily hydrogen fuel use.
Table 2-65 Technical Properties of the FCEV for MY 2032
Vehicle ID
Fuel Cell
Size (kW)
E-Motor Peak
Power (kW)
Battery
Energy (kWh)
H2 Fuel Tank
Capacity (kg)
Daily H2 Fuel
Use (kg)
18B Coach C18 MP
182
322
33
53
16
41Tractor DC C17 R
190
367
67
38
20
45Tractor DC C18 R
265
528
98
45
24
79Tractor SC C18 R
285
400
58
51
44
2.5.1 Fuel Cell Electric Vehicle Component Sizing
To compare HD FCEV technology costs and performance to a comparable ICE vehicle in HD
TRUCS, this section explains how we define HD FCEVs based on the performance and use
criteria. We determined the e-motor, fuel cell system, and battery pack sizes to meet the power
requirements for each of the four FCEVs represented in HD TRUCS, as described in the
following subsections. We also estimated the size of the onboard fuel tank needed to store the
fuel, in the form of hydrogen, required to meet typical range and duty cycle needs. Finally, based
on component sizing, we determined the cost of these vehicles.
2.5.1.1 Component Sizing Based on Power Needs
2.5.1.1.1 E-Motor
As discussed in Chapter 2.4.1.2, the e-motor is part of the electric drive system that converts
the electric power from the battery or fuel cell into mechanical power to move the wheels of the
vehicle. In HD TRUCS, the e-motor was sized for a FCEV like it was sized for a BEV (see RIA
Chapter 2.4.1.2) - to meet peak power needs of a vehicle, which is the maximum requirement to
drive the ARB transient cycle, meet the maximum time to accelerate from 0 to 30 mph, meet the
maximum time to accelerate from 0 to 60 mph, and maintain a set speed up a six-percent grade.
2.5.1.1.2 Fuel Cell System
Vehicle power in a FCEV comes from a combination of the fuel cell stack and the battery
pack. The fuel cell converts chemical energy stored in the hydrogen fuel into electrical energy.
The battery is charged by power derived from regenerative braking, as well as excess power
from the fuel cell. Some FCEVs are designed to rely on the fuel cell stack to produce the
necessary power, with the battery primarily used to capture energy from regenerative braking.
This is the type of HD FCEV that we modeled in HD TRUCS for the MY 2030 to 2032
1072 This does not mean that a BEV with large battery weight and volume is not technically feasible. Rather, this is
an acknowledgement that as battery size increases, cost is likely to increase, which can affect purchase price and
payback.
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timeframe in order to meet the longer distance requirements of select vehicle
applications. 1073>1074>1075
While much of FCEV design is dependent on the use case of the vehicle, manufacturers also
balance the cost of components such as the FC stack, the battery, and the hydrogen fuel storage
tanks. For the purposes of this HD TRUCS analysis, we focused on proton-exchange membrane
(PEM) fuel cells that use batteries with energy cells (described in RIA Chapter 1.7.2), where the
fuel cell and the battery were sized based on the demands of the vehicle. In HD TRUCS, the fuel
cell system (i.e., fuel cell stacks plus balance of plant, or BOP) was sized at either the 90th
percentile of power required for driving the ARB transient cycle or to maintain a constant
highway speed of 75 mph with 80,000-pound gross combined vehicle weight (GCVW). The 90th
percentile power requirement was used to size the fuel cells of vocational vehicles and day cab
tractors, and the 75-mph power requirement was used to size the fuel cells of sleeper cab
tractors.1076
As explained below, we revised our sizing methodology for the fuel cell system in the final
rule version of HD TRUCS.
To avoid undersizing the fuel cell system, we oversized the fuel cell stack by an additional 25
percent to allow for occasional scenarios where the vehicle requires more power (e.g., to
accelerate when the battery state of charge is low, to meet unusually long grade requirements, or
to meet other infrequent extended high loads like a strong headwind) and so the fuel cell can
operate within an efficient region. This size increase we included in the final rule version of HD
TRUCS can also improve fuel cell stack durability and ensure the fuel cell stack can meet the
power needs throughout the useful life. This is the system's net peak power, or the amount
available to power the wheels.1077 The fuel cell stack generates power, but some power is
consumed to operate the fuel cell system before it gets to the e-motor. Therefore, we increased
1073 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential",Report to the U.S. Department of Energy, Contract
ANL/ESD-22.6, October 2022. See Full report. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4ilhk/file/1406494585829.
1074 Note that ANL's analysis defines a fuel cell hybrid EV (FCHEV) as a battery-dominant vehicle with a large
energy battery pack and a small fuel cell, and a fuel cell EV (FCEV) as a fuel cell-dominant vehicle with a large fuel
cell and a smaller power battery. Ours is a slightly different approach because we consider a fuel cell-dominant
vehicle with a large battery with energy cells. The approach we took is intended to cover a wide range of vehicle
applications however it results in a conservative design, as it relies on a large fuel cell and a larger energy battery.
As manufacturers design FCEV for specific HD applications, they will likely end up with a more optimized lower
cost designs. Battery-dominant FCHEVs and fuel cell-dominant technologies with power batteries may also be
feasible in this timeframe but were not evaluated for the FRM.
1075 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
1076 In the NPRM version of HD TRUCS, we inadvertently used the 90th percentile of the ARB transient cycle to size
the sleeper and day cab tractors and the power required to drive at 75 mph to size the vocational vehicles. This error
is corrected in the final version of HD TRUCS.
1077 Net system power is the gross stack power minus balance of plant losses. This value can be called the rated
power.
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the size of the system by an additional 20 percent1078 to account for operation of balance of plant
components that ensure that gases entering the system are at the appropriate temperature,
pressure, and humidity and remove heat generated by the stack. This is the fuel cell stack gross
power.
The larger fuel cell can allow the system to operate more efficiently based on its daily needs,
which results in less wasted energy and lower fuel consumption. This additional size also adds
durability, which is important for commercial vehicles, by allowing for some degradation over
time. We determined that with this upsizing, there is no need for a fuel cell system replacement
within the 10-year period at issue in the HD TRUCS analysis.
2.5.1.1.3 Battery Pack
In HD TRUCS, the battery power accounts for the difference between the peak power of the
e-motor and the continuous power output of the fuel cell system. We sized the battery to meet
these power needs in excess of the fuel cell's capability only when the fuel cell cannot provide
sufficient power. In our analysis, the remaining power needs are sustained for a duration of 10
minutes (e.g., to assist with a climb up a steep hill).
Since a FCEV operates like a hybrid vehicle, where instantaneous power comes from a
combination of the fuel cell stack and the battery, the battery is sized smaller than a battery in a
BEV, which can result in more cycling of the FCEV battery. Thus, we reduced the FCEV
battery's depth of discharge from 80 percent in the NPRM to 60 percent in the final rule version
of HD TRUCS to reflect the usage of a hybrid battery more accurately. This means the battery is
oversized by in HD TRUCS to account for potential battery degradation over time.1079
2.5.1.2 Onboard Hydrogen Storage Tank Sizing Based on Energy Needs
A FCEV is re-fueled like a gasoline or diesel-fueled ICE vehicle. We determined the capacity
of the onboard hydrogen energy storage system using an approach like the BEV methodology for
battery pack sizing in RIA Chapter 2.4.1.1, but we based the amount of hydrogen needed on the
daily energy consumption needs of a FCEV.
Daily energy consumption is a summation of ZEV baseline energy and powertrain-specific
energy. A detailed description of ZEV baseline energy, which includes the energy used at the
axle to move the vehicle, regenerative braking, and PTO load, can be found in RIA Chapter
2.2.2.1. The powertrain-specific energy demand includes energy losses associated with the fuel
cell system (based on fuel cycle efficiency) as well as energy used for HVAC and battery
conditioning.
Hydrogen fuel in the tank enters the fuel cell stacks, where an electrochemical reaction
converts the hydrogen into electricity. During the conversion process, energy from the hydrogen
fuel is lost as heat or otherwise does not go towards producing electricity. The remaining energy
is used to operate the fuel cell system. Based on consideration of comments, we agree the fuel
1078 Huya-Kouadio, Jennie and Brian D. James. "Fuel Cell Cost and Performance Analysis: Presentation for the
DOE Hydrogen Program; 2023 Annual Merit Review and Peer Evaluation Meeting". Strategic Analysis. June 6,
2023. Available online:
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/review23/fc353James_2023_o-pdf.pdf.
1079 Ceschia, et. al. "Optimal Sizing of Fuel Cell Hybrid Power Sources with Reliability Consideration". Energies,
Volume 13, Issue 13. 2020. Available online: https://www.mdpi.com/1996-1073/13/13/3510.
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cell efficiency values used in the NPRM were too high and therefore reduced them, as described
in RIA Chapter 2.5.1.2.1.
For the final rule, we combined the revised fuel cell system efficiency value with the BEV
powertrain efficiencies (i.e., the combined inverter, gearbox, and e-motor efficiencies from Table
2-44). Table 2-66 includes the estimated total FCEV powertrain efficiencies to account for losses
that take place before the remaining energy arrives at the axle. The final FCEV powertrain
efficiencies were used to size the hydrogen storage tanks and to determine the hydrogen usage
and related costs.
The ZEV baseline energy loads from RIA Chapter 2.2.2 and the powertrain-specific energy
loads are reported in terms of kWh/mi, which we converted into kWh/day using the daily sizing
VMT. This daily energy consumption was then used to size the hydrogen fuel tank and
eventually to estimate its cost. Since literature frequently provides cost of a hydrogen fuel tank in
terms of $ per kg of hydrogen, to determine the hydrogen tank size, we converted the energy
demand of each vehicle in HD TRUCS (kWh) into) into hydrogen weight using an energy
content of 33.33 kWh per kg of hydrogen. In our analysis, 95 percent of the hydrogen in the tank
("usable H2") can be accessed. This is based on targets for light-duty vehicles, where a 700-bar
hydrogen fuel tank with a capacity of 5.9 kg has 5.6 kg of usable hydrogen.1080 Furthermore, we
added 10 percent to the tank to avoid complete depletion of hydrogen from the tank.
2.5.1.2.1 Fuel Cell System Efficiency
Fuel cell system efficiency is an important factor for sizing the hydrogen tank. For the NPRM,
we used the DOE fuel cell efficiency target values that ranged between 64.5 and 66 percent and
requested comment on these values. We received comments suggesting that the NPRM did not
accurately reflect how a fuel cell operates because we relied on peak fuel cell efficiency rather
than average operating efficiency. One commenter noted that FCEVs would benefit from BEV
component efficiency gains and observed that we did not utilize the DOE targets for peak fuel
cell efficiency in HD TRUCS, implying that fuel cells could be more efficient than we assumed
in the NPRM because a more efficient stack would require less cooling, which could lead to
compounded gains over time. Three commenters suggested that the fuel cell efficiency values
used in the NPRM were too high. One commenter pointed out that we considered peak efficiency
estimates in error rather than average operating efficiencies. The same commenter and another
offered ranges for operating efficiency at power levels typical for commercial vehicles and
suggested that we revise our fuel cell efficiency estimates. One of the same commenters noted
that fuel cell performance degrades over time, generally due to impurities in hydrogen fuel that
cause efficiencies to drop significantly from beginning of life to end of life. We evaluated these
comments and find those about considering fuel cell efficiencies at more average rather than
peak operating conditions to be persuasive. Accordingly, we have made revisions consistent with
the commenters' suggestions.
1080 U.S. DRIVE Partnership. "Target Explanation Document: Onboard Hydrogen Storage for Light-Duty Fuel Cell
Vehicles". U.S. Department of Energy. 2017. Available online:
https://www.energy.gov/sites/prod/files/2017/05/f34/fcto targets onboard hydro storage explanation.pdf.
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Figure 2-8 (which is shared to be illustrative) shows the shape of an efficiency curve for a fuel
cell system in a HD FCEV in terms of normalized net power. A typical fuel cell system operates
most efficiently at lower or partial power loads. For example, the figure demonstrates a peak
efficiency of about 65 percent at roughly 10 percent power load compared to an efficiency of
around 55 percent at full power on a normalized scale.
Power (normalized)
FIGURE 2-11 Operating efficiency of the fuel cell plotted against the normalized net power output
Figure 2-8: Operating Efficiency of a Fuel Cell1081
Based on a review of comments, we agree that the fuel cell system efficiency values used in
the NPRM were too high and should not be based on peak performance at low power, since fuel
cells typically do not operate long in that range. We therefore reduced them by eight percent to
reflect an average operating efficiency instead of peak efficiency. This was based on a review of
DOE's 2019 Class 8 Fuel Cell Targets. DOE has an ultimate target for peak efficiency of 72
percent, which corresponds to an ultimate fuel cell drive cycle efficiency of 66 percent. This
equates to an 8 percent difference between peak efficiency and drive cycle efficiency at a more
typical operating power. Therefore, to reflect system efficiency more accurately at a typical
operating power, we applied the 8 percent difference to the peak efficiency estimate in the
NPRM. For the final rule, the operational efficiency of the fuel cell system (i.e., represented by
drive cycle efficiency) is about 61 percent.
11181 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22.6, October 2022. Available online:
https://anl.app.box.com/s/an4n\0v2\pud\tpsnkhd5 peim/u4i 1 hk/File/1406494585829.
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Table 2-66 Powertrain Efficiencies for FCEV
Combined inverter,
GEM Energy ID
gearbox, e-motor and
FC system efficiency
C7 DC HR
56%
C8 DC HR
56%
C8 HH
56%
C8 SC HR
57%
C8 SC HR CdA036
57%
C8 DC HR CdA036
56%
C7 DC HR CdA036
56%
HHD R
56%
HHD M
54%
HHD U
51%
MHD R
54%
MHD M
52%
MHD U
51%
LHD R
54%
LHD M
52%
LHD U
51%
RV
54%
School Bus
51%
Coach Bus
56%
Emergency
51%
Concrete Mixer
51%
Transit Bus
51%
Refuse Truck
51%
More information on ambient temperature impact on powertrain-specific energy demand can
be found in the following section.
2.5.1.2.2 HVAC and Battery Conditioning
Fuel cell stacks produce excess heat during the conversion of hydrogen to electricity, like an
engine during combustion. This excess heat can be used to heat the interior cabin of the vehicle.
In HD TRUCS, no additional energy consumption is applied to FCEVs for heating operation,
and we already accounted for the energy loads due to ventilation in the axle loads. Therefore, for
FCEV energy consumption, we only include additional energy requirements for air
conditioning.1082 As described in RIA Chapter 2.4.1.1.1, we assigned a power demand of 3.32
kW for powering the air conditioner on a Class 8 bus. The HVAC loads are then scaled by the
cabin volume for other vehicle applications in HD TRUCS and applied to the VMT fraction that
requires cooling.
Since the batteries in FCEVs have the same characteristics as batteries for BEVs, for battery
conditioning, we used the methodology described in RIA Chapter 2.4.1.1.2 for BEVs to estimate
the energy consumption of the battery.
1082 We assume that FCEVs use waste heat from the fuel cell for heating, and that ventilation operates the same as it
does for an ICE vehicle.
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2.5.2 FCEV Components Costs
FCEVs and BEVs include many of the same components such as a battery pack, e-motor,
power converter and electric accessories, gearbox unit, and final drive. Therefore, we used the
same costs across vehicles for the same applications; for detailed descriptions of these
components, see RIA Chapter 2.4.3. In this subsection, we present the costs for components for
FCEVs that are different from a BEV. These components include the fuel cell system and
hydrogen fuel tank. The same energy cell battery costs used for BEVs are used for FCEVs, but
the battery size of a comparable FCEV is smaller.1083 Table 2-67 shows the component level and
total powertrain direct manufacturing costs for the eight FCEVs for MY 2032, which are
described in more detail in the following subsections.
As described in Chapter 1.3.2, the IRA provides a tax credit to reduce the cost of producing
qualified batteries (battery tax credit) and to reduce the cost of purchasing qualified ZEVs
(vehicle tax credit).1084 The battery tax credit is considered in HD TRUCS before determining
the total incremental RPE, as described in RIA Chapter 2.4.3.1.
Table 2-67 FCEV Direct Manufacturing Costs and IRA Tax Credit for MY 2032 (2022$)
Vehicle ID
FC Stack
($/unit)
E-Motor
($/unit)
H2 Fuel
Tank
($/unit)
Battery
without
IRA
Battery
Tax
Credit
($/unit)
Power
Converter
and
Electric
Accessorie
s($/unit)
Gearb
ox
($/unit)
Final
Drive
($/unit)
FCEV PT
Cost
($/veh)
IRA
Tax
Credit
($/unit)
18B Coach C18 MP
$29,096
$5,391
$32,525
$3,158
$5,997
$2,415
$1,644
$79,956
$368
41Tractor DC C17
$30,381
$6,148
$23,310
$6,442
$5,745
$1,978
$3,287
$77,291
$751
45Tractor_DC_C18
$42,353
$8,848
$27,919
$9,423
$5,810
$4,393
$3,287
$102,033
$1,098
79Tractor_SC_C18
$45,497
$6,700
$31,675
$5,633
$5,853
$4,385
$3,287
$103,030
$656
It is important to note that, as described in the subsequent sections, the cost of FCEV
components will depend heavily on manufacturing volumes and economies of scale. Modeling of
compliance pathways for this rulemaking conducted using HD TRUCS yielded estimates of
roughly 10,000 FCEVs per year by 2032. This manufacturing volume informed estimates of
component costs, but may be conservative, particularly if research and development (R&D)
success toward DOE targets is achieved or if large-scale infrastructure deployments occur faster
than assumed. Analysis that informed DOE's National Clean Hydrogen Strategy and Roadmap
identified scenarios where 10 to 14 percent of the truck stock in 2050 could utilize hydrogen and
1083 Sharpe, Ben and Hussein Basma. "A Meta-Study of Purchase Costs for Zero-Emission Trucks". The
International Council on Clean Transportation. February 2022. Available online:
https://theicct.org/publication/purchase-cost-ze-trucks-feb22/.
1084 Inflation Reduction Act of 2022, Pub. L. No. 117-169, 136 Stat. 1818 (2022). Available online:
https://www.congress.gOv/l 17/bills/hr5376/BILLS-l 17hr5376enr.pdf.
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fuel cells (representing annual sales of-40,000 trucks per year in 2032), if hydrogen fuel is
available at $4 per kg and DOE's targets for technology cost are achieved. I0X5-I0X6-I0X7
2.5.2.1 Fuel Cell System Costs
The fuel cell stack is the most expensive component of a fuel cell system,1088 which is the
most expensive part of a heavy-duty FCEV, primarily due to the technological requirements of
manufacturing rather than raw material costs.1089 Fuel cells for the heavy-duty sector are
expected to be more expensive than fuel cells for the light-duty sector because they operate at
higher average continuous power over their lifespan, which requires a larger fuel cell stack size,
and because they have more stringent durability requirements (i.e., to travel more hours and go
longer distances).1090
Projected costs vary widely in the literature. They are expected to decrease as manufacturing
matures. Larger production volumes are anticipated as global demand increases for fuel cell
systems for HD vehicles, which could improve economies of scale.1091 Costs are also anticipated
to decline as durability improves.1092
For the NPRM, we relied on an average of costs from an ICCT meta-study that found a wide
variation in fuel cell costs in the literature.1093 The costs we used in the NPRM ranged from $200
1085 U.S. Department of Energy. "U.S. National Clean Hydrogen Strategy and Roadmap". June 2023. Available
online: https ://www. hydro gen, energy. gov/librarv/roadmaps-vision/clean-hvdro gen-strate ev -roadmap.
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/us-national-clean-hydrogen-strategy-
roadmap.pdf.
1086 Marcinkoski, Jason et. al. "Hydrogen Class 8 Long Haul Truck Targets". U.S. Department of Energy. October
31, 2019. Available online:
https://www.hydrogen.energy.gov/pdfs/19006_hydrogen_class8_long_haul_truck_targets.pdf.
1087 Ledna, et. al. "Decarbonizing Medium- & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost
Analysis". National Renewable Energy Laboratory. March 2022. Available online:
https://www.nrel.gov/docs/fy22osti/82081.pdf.
1088 Papageorgopoulos, Dimitrios. "Fuel Cell Technologies Overview". U.S. Department of Energy. June 6, 2023.
Available online:
https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/review23/fc000_papageorgopoulos_2023_o.
pdf.
1089 Deloitte China and Ballard. "Fueling the Future of Mobility: Hydrogen and fuel cell solutions for transportation,
Volume 1". 2020. Available online:
https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/finance/deloitte-cn-fueling-the-future-of-mobility-
en-200101.pdf.
1090 Marcinkoski, Jason et. al. "Hydrogen Class 8 Long Haul Truck Targets". U.S. Department of Energy. October,
31, 2019. Available online:
https://www.hydrogen.energv.gov/pdfs/19006 hydrogen class8 long haul truck targets.pdf.
1091 Deloitte China and Ballard. "Fueling the Future of Mobility: Hydrogen and fuel cell solutions for transportation,
Volume 1". 2020. Available online:
https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/finance/deloitte-cn-fueling-the-future-of-mobilitv-
en-200101.pdf.
1092 Deloitte China and Ballard. "Fueling the Future of Mobility: Hydrogen and fuel cell solutions for transportation,
Volume 1". 2020. Available online:
https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/finance/deloitte-cn-fueling-the-future-of-mobilitv-
en-200101.pdf.
1093 Sharpe, Ben and Hussein Basma. "A meta-study of purchase costs for zero-emission trucks". International
Council on Clean Transportation, Working Paper 2022-09. February 2022. Available online:
https://theicct.org/publication/purchase-cost-ze-trucks-feb22/.
305
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per kW in MY 2030 to $185 per kW in MY 2032. We requested comment and cost data
projections in the proposal.
Several commenters addressed EPA's estimates for fuel cell costs. CARB agreed with EPA's
estimates, noting they used similar estimated values in their Advanced Clean Fleets rule
proceeding. One commenter thought the NPRM fuel cell cost estimates were too high,
particularly if they represent the fuel cell stack alone, based on targets published by the European
Joint Undertaking. Another commenter stated that fuel stack technology is too nascent to make
any type of realistic cost estimate. They noted that existing component technologies still need to
be adapted for the HD market and that fuel cell stacks are not being produced now, and they
stated that they do not believe accurate HD FCEV technology costs can be predicted now.
Several commenters said that EPA's estimates were too low and referred to fuel cell costs from a
more recent (2023) ICCT White Paper1094 that updated the ICCT meta-study referenced in the
NPRM.1095 See RTC Section 3.4.3 for additional details.
We reviewed the ICCT paper that several commenters referenced. Also, due to the wide range
of projected costs in the literature, EPA contracted with FEV1096 to independently evaluate direct
manufacturing costs of heavy-duty vehicles with alternative powertrain technologies and EPA
conducted an external peer review of the final FEV report.1097 In the report, FEV estimated costs
associated with a Class 8 FCEV-dominated long-haul tractor with graphite fuel cell stacks, which
are more durable than stainless steel stacks typically used in light-duty vehicle applications. FEV
leveraged a benchmark study of a commercial vehicle fuel cell stack from a supplier that serves
the Class 8 market. They also built prototype vehicles in-house and relied on existing expertise to
validate their sizing of tanks and stacks.1098 Please see RTC Section 3.4.3 for additional detail.
For the final rule, we established MY 2032 fuel cell system DMCs using cost projections
from FEV and ICCT. We weighted FEV's work twice as much as ICCT's because it was
primary research and because some of the volumes associated with the costs in ICCT's analysis
were not transparent. We note that this method of weighting primary research more heavily than
secondary research is generally appropriate for assessing predictive studies of this nature; indeed,
it is consistent with what ICCT itself did. For FEV's work, we selected costs that align with the
HD FCEV production volume that we project in our modeled potential compliance pathway's
technology packages developed for this final rule, which is roughly 10,000 units per year in MY
2032, for a DMC of $89 per kW. For ICCT's work, we used the 2030 value of $301 per kW for
1094 Xie, et. al. "Purchase costs of zero-emission trucks in the United States to meet future Phase 3 GHG standards".
International Council of Clean Transportation, Working Paper 2023-10. March 2023. Available online:
https://theicct.org/wp-content/uploads/2023/03/cost-zero-emission-trucks-us-phase-3-mar23.pdf.
1095 Sharpe, Ben and Hussein Basma. "A meta-study of purchase costs for zero-emission trucks". International
Council on Clean Transportation, Working Paper 2022-09. February 2022. Available online:
https://theicct.org/publication/purchase-cost-ze-trucks-feb22/.
1096 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
1097 ICF. "Peer Review of HD Vehicles, Industry Characterization, Technology Assessment and Costing Report".
September 15, 2023
1098 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
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MY 2032, since 2030 was the latest year of values referenced by ICCT from literature. Our
weighted average yielded a MY 2032 fuel cell system DMC of $160 per kW. In order to project
DMCs from MY 2032 for earlier MYs, we used our learning rates shown in RIA Chapter 3.2.1.
This yielded the MYs 2030 and 2031 DMCs shown in Table 2-68.
Table 2-68 Fuel Cell System Direct Manufacturing Costs (2022$)
Year
MY 2030
MY 2031
MY 2032
FC System
$170/kW
$165/kW
$160/kW
2.5.2.2 Onboard Hydrogen Fuel Tank Costs
Onboard hydrogen storage cost projections also vary widely in the literature. For the NPRM,
we relied on an average of costs from the same ICCT meta-study that we used for fuel cell
costs.1099 The values we used in the NPRM analysis ranged between $660/kg in MY 2030 and
$612/kg in MY 2032. We requested comment and cost data projections in the proposal.
There were few comments on hydrogen fuel tank costs. Two commenters referred to ICCT's
revised meta-study.1100 One commenter suggested that onboard liquid hydrogen will be required
for long-distance ranges of over 500 miles in the longer-term and suggested that it is too soon to
offer cost estimates for liquid tanks. See RTC Section 3.4.3 for details about the meta-study.
Given our assessment of technology readiness for the NPRM, liquid storage tanks were not
included in the potential compliance pathway that supports the feasibility and appropriateness of
our standards.
Like fuel cell costs, onboard gaseous hydrogen tank costs are dependent on manufacturing
volume. We reviewed the ICCT paper that several commenters referenced and contracted with
FEV1101 to independently evaluate onboard hydrogen storage tanks costs for 2027 (2022$) based
on manufacturing volume, and EPA conducted an external peer review of the final FEV
report.1102 Please see RTC Section 3.4.3 for additional detail.
Using the same approach taken for fuel cell system costs, as described in RIA Chapter 2.5.2.2,
we established MY 2032 onboard storage tank DMCs using cost projections from FEV and
ICCT. We weighted FEV's work twice as much as ICCT's because it was primary research and
because some of the volumes associated with the costs in ICCT's analysis were not transparent.
We note that this method of weighting primary research more heavily than secondary research is
generally appropriate for assessing predictive studies of this nature; indeed, it is consistent with
1099 Sharpe, Ben and Hussein Basma. "A meta-study of purchase costs for zero-emission trucks". International
Council on Clean Transportation, Working Paper 2022-09. February 2022. Available online:
https://theicct.org/publication/purchase-cost-ze-trucks-feb22/.
1100 Xie, et. al. "Purchase costs of zero-emission trucks in the United States to meet future Phase 3 GHG standards".
International Council of Clean Transportation, Working Paper 2023-10. March 2023. Available online:
https://theicct.org/wp-content/uploads/2023/03/cost-zero-emission-trucks-us-phase-3-mar23.pdf.
ii°i FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
1102ICF. "Peer Review of HD Vehicles, Industry Characterization, Technology Assessment and Costing Report".
September 15, 2023
307
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what ICCT itself did. For FEV's work, we selected costs for approximately 10,000 units per year
in MY 2032, for a DMC of $504 per kg. For ICCT's work, we used the 2030 value of $844 per
kW for MY 2032, since 2030 was the latest year of values referenced by ICCT from literature.
Our weighted average yielded a MY 2032 fuel cell system DMC of $617 per kW. Please see
RTC Section 3.4.3 for additional detail. In order to project DMCs for earlier MYs, we used our
learning rates shown in RIA Chapter 3.2.1. This yielded the MYs 2030 and 2031 DMCs shown
in Table 2-69.
Table 2-69: Onboard Hydrogen Tank Direct Manufacturing Costs (2022$)
Year
MY 2030
MY 2031
MY 2032
Onboard H2 Tank
$659/kg
$636/kg
$617/kg
2.5.2.3 Vehicle Tax Credits
We applied the IRA section 13403 vehicle tax credit to FCEVs in HD TRUCS exactly how
we applied it to BEVs, as described in RIA Chapter 2.4.3.5.
2.5.2.4 State Sales Tax and Federal Excise Tax
As explained in RIA Chapter 2.3.2.2, the NPRM version of HD TRUCS did not include
estimates for state sales taxes on the purchase of a vehicle or Federal Excise Tax (FET). After
consideration of comments, we have added these values to the final version of HD TRUCS.
Sales tax and FET are calculated by first applying a retail price equivalent (RPE) factor1103 to the
upfront powertrain DMC costs. One industry commenter recommended using a state sales tax
rate of 5.02%, an average of the 50 state sales tax values, which we assessed and confirmed was
appropriate.1104 This rate was applied to the upfront costs (RPE) for all HD TRUCS vehicles for
the final rule analysis. A Federal Excise tax of 12% was applied to the upfront costs (RPE) for all
Class 8 (heavy heavy-duty) vehicles and all tractors.1105 The results of this analysis for MY 2032
as an example year are shown in Table 2-70.
Table 2-70 FCEV Powertrain (PT) RPE, Sales Tax and FET for MY 2032 (2022$)
Vehicle ID
PT DMC
Battery
PT RPE
FET
State Sales Tax
($/unit)
Tax
Credit
($/unit)
($/unit)
($/unit)
($/unit)
18B Coach C18 MP
$ 79,956
$368
$113,169
$13,580
$5,681
41 Tractor DC C17
$77,291
$751
$109,002
$13,080
$5,472
45Tractor DC C18
$102,033
$1,098
$143,789
$17,255
$7,218
79Tractor SC C18
$103,030
$656
$145,647
$17,478
$7,311
1103 See Chapter 3.2 for a discussion of RPE.
1104See page 38 of docket number EPA-HQ-OAR-2022-0985-2668-A1.
1105 U.S. Internal Revenue Service. 26 USC 4051. Available at
http://uscode.house.gov/view.xhtml?req=granuleid:USC-prelim-title26-section4051&num=0&edition=prelim
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2.5.3 FCEV Operating Costs
The annual operating cost for FCEVs is the annual hydrogen fuel cost plus the maintenance
and repair cost, powertrain insurance cost, and annual ZEV registration fee.1106 RIA Chapter
2.5.3.1 discusses hydrogen fuel price and how the annual hydrogen cost of operating a FCEV is
computed, and RIA Chapter 2.5.3.2 discusses maintenance and repair costs for FCEVs. RIA
Chapter 2.5.3.3 describes the insurance cost for FCEV vehicles, and RIA Chapter 2.5.3.4
describes an annual ZEV registration fee. For each FCEV in HD TRUCS, the 10-year average
annual operating costs are as shown in Table 2-71 and described in the sections below. As
discussed in RIA Chapter 2.2.1.1.3, for the final version for HD TRUCS, we have assessed each
year of operation using the appropriate changes that occur over time for inputs such as VMT,
maintenance and repair, and fuel costs; however, we are continuing to show a 10-year average
values in tables such as the one below, as a single value point of comparison. Appendix A to this
RIA includes each year of a 10-year schedule for VMT.
Table 2-71 FCEV Operating Costs for a MY 2032 Vehicle (2022$), 10 Year Average
Vehicle ID
Annual
FCEV M&R
(S/ycar)
Annual Hydrogen Cost ($/year)
Annual Powertrain
Insurance Cost1107 + $100
Annual ZEV Reg. Fee
($/year)
18B Coach C18 MP
7073
14593
3395
41 Tractor DC C17
9339
18252
3370
45Tractor DC C18
9339
21865
4414
79Tractor SC C18
19058
41425
4469
2.5.3.1 Annual Hydrogen Fuel Cost
The annual hydrogen cost is a function of the hydrogen price, daily energy consumption of a
FCEV (which includes the efficiency of the powertrain), and number of operating days in a year.
For the purposes of the HD TRUCS analysis, rather than focusing on depot hydrogen fueling
infrastructure costs that would be incurred upfront, we included infrastructure costs in our per-
kilogram retail price of hydrogen. The retail price of hydrogen is the total price of hydrogen
when it becomes available to the end user, including the costs of production, distribution,
storage, and dispensing at a fueling station. This price per kilogram of hydrogen includes the
amortization of the station capital costs. This approach is consistent with the method we use in
HD TRUCS for ICE vehicles, where the equivalent diesel fuel costs are included in the diesel
fuel price instead of accounting for the costs of fuel stations separately, as well as for BEVs with
public charging infrastructure costs within the price of charging.
We acknowledge that this market is still emerging and that hydrogen fuel providers will likely
pursue a diverse range of business models. For example, some businesses may sell hydrogen to
fleets through a negotiated contract rather than at a flat market rate on a given day. Others may
1106 Insurance costs and an annual ZEV registration fee were not included in the proposal; EPA added these costs to
the final version of HD TRUCS after consideration of comments. See RIA Chapter 2.5.3.3 and 2.5.3.4.
1107 As described at the beginning of Chapter 2.3, this analysis is examining the incremental cost differences
between a comparable ICE vehicle and ZEV technologies; therefore, insurance costs are estimated based on the
upfront cost of powertrain components that are expected to differ for a comparable ICE vehicle and ZEV.
309
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offer to absorb the infrastructure development risk for the consumer, in exchange for the ability
to sell excess hydrogen to other customers and more quickly amortize the cost of building a
fueling station. FCEV manufacturers may offer a "turnkey" solution to fleets, where they provide
a vehicle with fuel as a package deal. This level of granularity is not reflected in our hydrogen
price estimates presented in the RIA.
As discussed in RIA Chapters 1.3.2 and 1.8, large federal incentives are in place that could
impact the price of hydrogen. In June 2021, DOE launched a Hydrogen Shot goal to reduce the
cost of clean hydrogen production by 80 percent to $1 per kilogram in one decade.1108 The BIL
and IRA included funding for several hydrogen programs to accelerate progress towards the
Hydrogen Shot and jumpstart the hydrogen market in the U.S.
For the NPRM analysis, we included a hydrogen price based on analysis from ANL using
BEAN. One commenter highlighted several reports that indicate large potential for the hydrogen
price to rapidly drop, particularly on the production side. Several commenters expressed concern
about the hydrogen price assumption in the NPRM or said that prices cannot be predicted at this
time and urged that EPA's projection be regularly evaluated as the market develops. Some
commenters referred to an ICCT analysis of hydrogen pricing that indicated a lack of cost-
competitiveness for hydrogen-fueled trucks before 2035. Another commenter noted that the price
of $4 to 5 per kg (that EPA referenced) is described by DOE as a "willingness to pay" that
reflects the total price at which hydrogen must be available to the HD vehicle end user for uptake
to occur, or the point at which FCEVs could reach cost parity with diesel vehicles. They stated
that it cannot represent the real market and offered a bottom-up analysis to understand what fleet
owners would pay at the hydrogen refueling stations.
For the final rule HD TRUCS analysis, in consideration of the comments, we re-evaluated our
assumption about the retail price of hydrogen, in consultation with DOE. We determined the
estimates for hydrogen price based on 2030 cost scenarios for hydrogen from DOE's Pathways
to Commercial Liftoff report1109 that are in line with estimates from a previous DOE analysis of
market uptake of HD ZEVs, including FCEVs.1110 Several cost trajectories in the report
identified paths for around $6 per kg in 2030, depending on the method of hydrogen production
and cost of the station. For 2030, we looked at the average of the sums of low and high pathway
estimates for hydrogen produced using steam methane reforming (SMR) with carbon capture and
sequestration (CCS) and water electrolysis, considering varying incentives from the IRA
hydrogen production tax credit (PTC). Distribution, storage, and dispensing costs are based on
DOE estimates if advances in distribution and storage technology are commercialized and at
scale. Our scenario selections presume that in the near-term, delivery of hydrogen in liquid form
1108 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Hydrogen Shot". Available online:
https://www.energy.gov/eere/fuelcells/hydrogen-shot.
1109 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energv.gOv/wp-content/uploads/2023/05/20230523-Pathwavs-to-Commercial-Liftoff-Clean-
Hydrogen.pdf. See Figure 10.
1110 Ledna, et. al. "Decarbonizing Medium- & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost
Analysis". National Renewable Energy Laboratory. March 2022. Available online:
https://www.nrel.gov/docs/fy22osti/82081.pdf.
310
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is likely, due to the limited capacity of gaseous tube trailers and limited availability of pipelines.
Table 2-72 shows the range of costs presented in Figure 10 of the Liftoff Report.1111
Table 2-72 Projected Hydrogen Costs from DOE's Liftoff Report
DOI'l l.iflnIT Report (2030 S/k»)
S\1k u so "5 kg lJTC (including a»sl nf CCS)
l.k|uefaclkni
I ,K|iikl 112 siorage
I.k|iud 112 Mucking
\e\l no11 fuel dispensing ;il high nse:;:
Low High
()4 () X5
SI M
Wilier eleeliiils sis w Si kg I'TC
l.k|iief;ielk
7 ?
"» -
SI M
M 4.5
**Greater than or equal to 70% utilization, assumes line fill at high pressure
Cost reductions to $4 per kg are considered feasible by 2035 with next generation fuel
dispensing technologies, reductions in the cost of hydrogen production due to IRA incentives,
and possibly the use of pipelines for hydrogen delivery.1112
To evaluate our estimates further, and in response to comments, the National Renewable
Energy Laboratory (NREL) conducted a bottom-up analysis that explores the potential range of
levelized costs of dispensed hydrogen (LCOH)1113 from hydrogen refueling stations for HD
FCEVs in 2030. Bracci et. al1114 evaluates breakeven costs along the full supply chain from
hydrogen production to dispensing, including station costs by technology component and
delivery costs by distance delivered. The authors vary hydrogen delivery distances, station sizes,
station utilization rates, and economies of scale. They assume that hydrogen is dispensed in
gaseous form at 700 bar pressure and is either delivered via liquid tanker trucks or produced
onsite in gaseous form. The assumed production cost of $1.50 per kg is based on costs of
production today using steam methane reforming (SMR), though the paper acknowledges that
many factors are at play that could impact the cost and method of hydrogen production in 2030
such as the rate of economies of scale; the impacts of policy incentives (e.g, the 45 V production
1111 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energv.gOv/wp-content/uploads/2023/05/20230523-PathwaYS-to-Commercial-Liftoff-Clean-
Hydrogen.pdf. See Figure 10.
1112 Ledna, et. al. "Decarbonizing Medium- & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost
Analysis". National Renewable Energy Laboratory. March 2022. Available online:
https://www.nrel.gov/docs/fy22osti/82081.pdf.
1113 LCOH is described as the total annualized capital costs plus annual feedstock, variable, and fixed operating
costs, divided by the annual hydrogen flow through the supply chain.
1114 Bracci, Justin, Mariya Koleva, and Mark Chung. "Levelized Cost of Dispensed Hydrogen for Heavy-Duty
Vehicles". National Renewable Energy Laboratory. NREL/TP-5400-88818. March 2024. Available online:
https://www.nrel.gov/docs/fy24osti/88818.pdf.
311
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tax credit);1115 and the success of research, development, and deployment efforts. Most capital
and operating costs are derived from Argonne National Laboratory's Hydrogen Delivery
Scenario Analysis Model (HDSAM) Version 4.5.1116
The authors conclude that the overall system LCOH for stations in 2030 is estimated to range
from ~$3.80/kg-H2 to ~$12.60/kg-H2, depending on the size of stations and method of hydrogen
supply.1117 This cost range is not the same as a retail price, but we assume that any retail markup
at the station is minimal.1118'1119 Importantly, it does not consider any tax incentives or other state
or federal incentive policies that may further reduce the retail price that consumers see at a
fueling station in 2030.1120>1121 Therefore, we conclude that our retail price of hydrogen is within
a reasonable range of anticipated values.
We took a closer look at the ICCT analysis referenced by several commenters.1122ICCT
assessed near-term charging and refueling needs for Class 4 to 8 vehicles for scenarios before
and after IRA tax incentives are in place, including incentives for renewable electricity (45 and
45Y) and clean hydrogen (45 V). They assumed that hydrogen fuel is green, meaning that it is
produced onsite using electrolysis powered by renewable energy. Thus, their retail price includes
production and refueling station costs but not distribution costs. ICCT's study found that HD
FCEVs would account for less than one percent of total sales overall through 2035,1123 and that
neither HD FCEVs nor H2-ICEVs would be cost-competitive due to hydrogen prices, despite
1115 The authors indicate that relevant incentives include but are not limited to the Alternative Fuel Refueling
Property Credit (30C), the Credit of Production of Clean Hydrogen (45 V), the Qualified Advanced Energy Project
Credit (48C), and the Credit for Qualified Commercial Clean Vehicles (45W).
1116 Bracci, Justin, Mariya Koleva, and Mark Chung. "Levelized Cost of Dispensed Hydrogen for Heavy-Duty
Vehicles". National Renewable Energy Laboratory. NREL/TP-5400-88818. March 2024. Available online:
https://www.nrel.gov/docs/fy24osti/88818.pdf.
1117 Bracci, Justin, Mariya Koleva, and Mark Chung. "Levelized Cost of Dispensed Hydrogen for Heavy-Duty
Vehicles". National Renewable Energy Laboratory. NREL/TP-5400-88818. March 2024. Available online:
https://www.nrel.gov/docs/fy24osti/88818.pdf.
1118 West Virginia Oil Marketers and Grocers Association. "How Much Money Do Businesses Make on Fuel
Purchases?" Available online: https://www.omegawv.com/faq/140-how-much-money-do-businesses-make-on-fuel-
purchases.html#:~:text=Retailers%20Make%20Very%20Little%20Selling,cents%20per%20gallon%20in%20profit.
1119 Kinnier, Alex. "I've analyzed the profit margins of 30,000 gas stations. Here's the proof fuel retailers are not to
blame for high gas prices". Fortune. August 9, 2022. Available online: https://fortune.com/2022/08/09/energy-
profit-margins-gas-stations-proof-fuel-retailers-high-gas-prices-alex-kinnier/.
1120 The authors indicate that relevant incentives include but are not limited to the Alternative Fuel Refueling
Property Credit (30C), the Credit of Production of Clean Hydrogen (45 V), the Qualified Advanced Energy Project
Credit (48C), and the Credit for Qualified Commercial Clean Vehicles (45W).
1121 U.S. Department of Energy, Hydrogen and Fuel Cell Technologies Office. "Financial Incentives for Hydrogen
and Fuel Cell Projects". Available online: https://www.energy.gov/eere/fuelcells/financial-incentives-hydrogen-and-
fuel-cell-projects.
1122 Slowik, Peter, et. al. "White Paper: Analyzing the Impact of the Inflation Reduction Act on Electric Vehicle
Uptake in the United States". International Council on Clean Transportation and Energy Innovation Policy &
Technology LLC. January 2023. Available online: https://theicct.org/wp-content/uploads/2023/01/ira-impact-evs-us-
jan23-2.pdf.
1123 The HD FCEV component costs used in this ICCT study are from Xie et. al, which we also considered in RIA
Chapter 2.5.2.
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IRA incentives.1124 Their levelized costs for new green hydrogen production plants started at
$5.59 per kg in 2020 and did not go below $4.50 through 2035 with or without tax credits. This
cost is higher than the clean hydrogen production costs in DOE's Liftoff Report and the
production cost in Bracci et. al, which assumed $1.50 per kg based on the cost of hydrogen
production today. ICCT's production costs are from a paper on hydrogen production in Europe,
where about 500 kg of hydrogen is produced onsite at a station per day to meet the needs of a
station.1125 This is a smaller station size than used in the bottom-up analysis conducted in support
of this rule. For example, Bracci et. al evaluated hydrogen refueling stations in the U.S.—
considering gaseous stations that produce hydrogen onsite, but also centralized production
pathways—that would dispense between 2 and 18 million tons of hydrogen per day per station.
The larger station size is based on the size of operating and planned hydrogen refueling stations
for HD FCEVs in the U.S.1126
Then, ICCT relied on a 2017 study for a refueling station cost of $6 per kg in 2020,
decreasing linearly to $2.30 per kg by 2050. This equates to about $4.77 in 2030. Their station
costs are closer to the range of costs for refueling stations with onsite production in Bracci et. al,
which vary depending on the rate of utilization. We note that Bracci et. al also considers the cost
of liquid hydrogen delivery to stations in the LCOH.
The ICCT authors reduced the station costs by four percent due to the IRA tax credit for
eligible hydrogen refueling stations of up to $100,000 (30C), which we did not quantify.
Applying this four percent to the LCOH range in Bracci et. al would drop their estimated LCOH
costs to between ~$3.65 to $12.10 per kg. ICCT also accounted for competition between
hydrogen suppliers to estimate a total market price "at-the-pump" that includes a retail markup.
We did not add a retail markup to the LCOH, given that gas and diesel fuel retailers generally
make very little selling fuel.1127'1128
1124 ICCT used a discounted cash flow model, which they said is necessary to estimate annual tax liability and
accurately reflect the impact of the PTC. For example, since the PTC ends in 2030, they used the model to account
for the impact of the credit for a limited time during the life of a plant (e.g., only for two years for a plant that starts
producing hydrogen in 2030 and then operates for 30 years). They included additional effects of IRA policies (i.e., a
separate PTC for renewable electricity, "direct pay", and tax transferability provisions).
1125 Zhou, Yuanrong and Stephanie Searle. "White Paper: Cost of Renewable Hydrogen Produced Onsite at
Hydrogen Refueling Stations in Europe". International Council on Clean Transportation. February 2022. Available
online: https://theicct.org/wp-content/uploads/2022/02/fuels-eu-cost-renew-H-produced-onsite-H-refueling-stations-
europe-feb22.pdf.
1126 Bracci, Justin, Mariya Koleva, and Mark Chung. "Levelized Cost of Dispensed Hydrogen for Heavy-Duty
Vehicles". National Renewable Energy Laboratory. NREL/TP-5400-88818. March 2024. Available online:
https://www.nrel.gov/docs/fy24osti/88818.pdf.
1127 West Virginia Oil Marketers and Grocers Association. "How Much Money Do Businesses Make on Fuel
Purchases?" Available online: https://www.omegawv.com/faq/140-how-much-money-do-businesses-make-on-fuel-
purchases.html#:~:text=Retailers%20Make%20Very%20Little%20Selling,cents%20per%20gallon%20in%20profit.
1128 Kinnier, Alex. "I've analyzed the profit margins of 30,000 gas stations. Here's the proof fuel retailers are not to
blame for high gas prices". Fortune. August 9, 2022. Available online: https://fortune.com/2022/08/09/energy-
profit-margins-gas-stations-proof-fuel-retailers-high-gas-prices-alex-kinnier/.
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The high green hydrogen production cost assumed by ICCT is a main driver of their estimated
retail price in 2030 of $9.50 per kg.1129 We recognize that ICCT's results are also within the
range of values presented in Bracci et al's analysis of the LCOH in 2030, but our approach for
the FRM is based on projections about a U.S. clean hydrogen market that may or may not be
"green" during the 2030 to 2032 timeframe but is incentived to reduce emissions over time. (See
RIA Chapter 4.8 for a comparative emissions analysis of potential hydrogen production methods
in this timeframe.) As indicated in RIA Chapter 1.8.3, there is $9.5 billion in BIL and IRA
investment to quickly ramp up production and reduce the cost of hydrogen. Our retail price
estimates are lower than ICCT's without directly accounting for these incentives, so any
potential beneficial impact from them would be additional.
We identified few other bottom-up assessments of hydrogen price available since the NPRM.
The authors used differing analytical approaches and assumptions and only two included
production, delivery, and dispensing costs. For example, Fulton et. al evaluated hydrogen end
use scenarios in the state of California, aligned with the state's vision for a hydrogen hub (the
"ARCH2ES" or Alliance for Renewable Clean Hydrogen Energy Systems) that was awarded
$1.2 billion from DOE. They considered eight approaches to producing electrolytic hydrogen
and delivering it to refueling stations in California and determined that, given strong
transportation demand growth, a levelized cost of $5 to 6.25 per kg could be achievable for a
scaled system by 2030.1130 Their analysis of longer-term (e.g., 2030-35) costs included reduced
operating and capital costs due to scale and learning. They assumed electricity generation from
low-cost renewables in this timeframe. Hydrogen production costs ranged from roughly $2.60 to
3.70 per kg; distribution and storage costs ranged widely based on volumes and distance moved;
and refueling station costs ranged from just $1 to 2 per kg to about $3.80 per kg, with lower costs
for larger liquid hydrogen stations.1131 Their analysis represents potential cost ranges for a single
H2Hub region.
A Ricardo study for the Truck and Engine Manufacturers Association investigated the
feasibility of the EPA NPRM Phase 3 GHG standards for Medium Heavy-Duty Vehicles, so
their hydrogen demand levels were higher than we are including in the final FRM. Their
hydrogen price projections were based on a review of costs for production, delivery, and
dispensing from various literature sources. They chose the costs in Table 2-73 for their analysis
and applied an annual reduction rate of three percent:
Table 2-73 EMA H2 Cost Projections
Type
Option
Cost (2030)
Production
Blue hydrogen
$1.50/kg
Green hydrogen
$5/kg
1129 Slowik, Peter, et. al. "White Paper: Analyzing the Impact of the Inflation Reduction Act on Electric Vehicle
Uptake in the United States". International Council on Clean Transportation and Energy Innovation Policy &
Technology LLC. January 2023. Available online: https://theicct.org/wp-content/uploads/2023/01/ira-impact-evs-us-
jan23-2.pdf.
1130 Fulton, Lew, et. al. "California Hydrogen Analysis Project: The Future Role of Hydrogen in a Carbon-Neutral
California: Final Synthesis Modeling Report". UC Davis Institute of Transportation Studies. April 19, 2023.
Available online: https://escholarship.org/uc/item/27m7g841.
1131 Fulton, Lew, et. al. "California Hydrogen Analysis Project: The Future Role of Hydrogen in a Carbon-Neutral
California: Final Synthesis Modeling Report". UC Davis Institute of Transportation Studies. April 19, 2023.
Available online: https://escholarship.org/uc/item/27m7g841.
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Delivery
Gas tube trailer
$1.50/kg
Liquid tankers
$1.20/kg
Dedicated pipeline
$0.50/kg
Repurposed pipeline
$0.30/kg
Dispensing
Based on 2020 levelized refueling station
cost and 25-30% reduction in green
hydrogen production cost
$3.50/kg
Their assessment of four scenarios (e.g., based on different fuel types and delivery options)
found that hydrogen costs could range from $5.50 to 10 per kg in 2030.1132
After consideration of comments and this assessment, we project the price of hydrogen in
2030 will be $6/kg and fall to $4/kg in 2035 and beyond, as shown in Table 2-74.
Table 2-74 Retail Price of Hydrogen for CYs 2030-2035+ (2022$) used in Final Version of HD TRUCS
2030
2031
2032
2033
2034
2035 and beyond
$/kg H2
6.00
5.60
5.20
4.80
4.40
4.00
2.5.3.2 Maintenance and Repair
Like BEVs, data on real-world maintenance and repair costs for heavy-duty FCEVs is limited.
We expect the overall maintenance costs to be lower for a heavy-duty FCEV than a comparable
diesel- fueled ICE vehicle for several reasons. First, a FCEV powertrain has fewer moving parts
that accrue wear or need regular adjustments. Second, FCEVs do not require regular replacement
of certain fluids such as engine oil, nor do they require exhaust filters to reduce particulate matter
and other pollutants. Third, the per-mile rate of brake wear is expected to be lower for FCEVs
due to regenerative braking systems.
Fuel cell vehicles share many BEV components, with fuel cell vehicles also having fuel cell
stacks and hydrogen tanks; based on this, it is reasonable to assume that, since a FCEV has more
components than a BEV (e.g., a fuel cell and a hydrogen storage tank), a FCEV will have
slightly higher maintenance and repair costs than a BEV. Several literature sources apply a
scaling factor to diesel vehicle maintenance costs to estimate FCEV maintenance
costs.1133,1134,1135 We followed this approach for the proposal and applied a repair cost scaling
factor of 0.75 to the maintenance and repair costs for diesel-fueled ICE vehicles. This scaling
factor is slightly higher than the BEV scaling factor of 0.71. The 0.75 FCEV scaling factor is
1132 Kuhn, et. al. "Feasibility study of EPA NPRM Phase 3 GHG standards for Medium Heavy-Duty Vehicles:
Version 3.0". Ricardo, Prepared for Truck and Engine Manufacturers Association. July 19, 2023.
1133 Burnham, A., Gohlke, D., Rush, L., Stephens, T., Zhou, Y., Delucchi, M. A., Birky, A., Hunter, C., Lin, Z., Ou,
S., Xie, F., Proctor, C., Wiryadinata, S., Liu, N., Boloor, M. "Comprehensive Total Cost of Ownership
Quantification for Vehicles with Different Size Classes and Powertrains". Argonne National Laboratory. April 1,
2021. Available online: https://publications.anl.gov/anlpubs/2021/05/167399.pdf.
1134 Hunter, Chad, Michael Penev, Evan Reznicek, Jason Lustbader, Alicia Birkby, and Chen Zhang. "Spatial and
Temporal Analysis of the Total Cost of Ownership for Class 8 Tractors and Class 4 Parcel Delivery Trucks".
National Renewable Energy Lab. September 2021. Available online: https://www.nrel.gov/docs/fV2losti/71796.pdf.
1135 Burke, Andrew, Marshall Miller, Anish Sinha, et. al. "Evaluation of the Economics of Battery-Electric and Fuel
Cell Trucks and Buses: Methods, Issues, and Results". August 1, 2022. Available online:
https://escholarship.org/uc/item/lg89p8dn.
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based on an analysis from Wang et al. 2022, that estimates a future FCEV HD vehicle would
have a 25 percent reduction compared to a diesel-powered HD vehicle truck.1136
Commenters noted the potential need to retrain technicians to work on ZEVs. As similarly
noted in RIA Chapter 2.4.4.1 above with respect to BEVs, we agree that there may be a
transition period during which costs for maintaining and repairing FCEVs will not be at their full
savings potential due to the need to train more of the workforce to maintain and repair FCEVs.
To account for this period, in this final rule, EPA has phased in the FCEV scaling factors for
maintenance and repair. Specifically, instead of applying a single scaling factor for every year
commencing in 2027 as at proposal, EPA is starting with a higher scaling factor and gradually
decreasing it (i.e., gradually increasing the projected cost savings) from calendar year 2030-
2035. The initial higher scaling factor (1.0) also comes from Wang et al. and reflects estimates
for 2022. EPA's approach of applying this factor commencing in 2030 is consequently
conservative given that technicians in those later years will be more experienced than they were
in 2022. These values, shown in Table 2-75, are multiplied by the annual diesel maintenance and
repair costs by calendar year in order to assess the costs for FCEV vehicle maintenance and
repair.
Table 2-75 Maintenance and Repair Scaling Factors for FCEV CY 2030 - 2035+
CY
2030
2031
2032
2033
2034
2035+
Factor
1.0
0.95
0.90
0.85
0.80
0.75
Consistent with our approach for ICEs and BEVS, we did not include the costs for fuel cell
system replacement within our analysis. We upsized the fuel cell system such that the addition of
cells add durability so that replacement will not be necessary in the 10-year assessment period
considered in the HD TRUCS analysis.1137
2.5.3.3 Insurance cost
In the NPRM analysis, we did not take into account the cost of insurance on the ZEV
purchaser. A few commenters suggested we should consider the addition of insurance cost
because the incremental cost of insurance for the ZEVs will be higher than for ICE vehicles. We
agree that insurance costs may differ between these vehicle types and that this is a cost that will
be seen by the operator. Therefore, for the final rule analysis in HD TRUCS, we included the
incremental insurance costs of a ZEV relative to an ICE vehicle by incorporating an annual
insurance cost. A commenter recommended using an insurance rate of 3%, based originally on
an ICCT April 2023 paper on ZEV TCO.1138 We have reviewed the comment and the ICCT
White Paper and consider the 3% insurance rate to be reasonable. Similar to sales tax and the
FET, insurance costs are calculated as a percentage, after applying the RPE, to the upfront costs
1136 Wang, G., Miller, M., and Fulton, L." Estimating Maintenance and Repair Costs for Battery Electric and Fuel
Cell Heavy Duty Trucks, 2022. Available online:
https://escholarship.org/content/at36c08395/qt36c08395 noSplash 589098e470b036b3010eae00f3b7b618.pdf?t=r6
zwib.
1137 The interim target fuel cell system lifetime for a Class 8 tractor-trailer is 25,000 hours, which is equivalent to
more than 10 years if a vehicle operates for 45 hours a week for 52 weeks a year.
1138 Basma, Hussein, et.al. "Total Cost of Ownership of Alternative Powertrain Technologies for Class 8 Long-Haul
Trucks in the United States." International Council on Clean Transportation. April 2023. Page 17. Available online:
https://theicct.org/wp-content/uploads/2023/04/tco-alt-powertrain-long-haul-trucks-us-apr23.pdf
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shown in Table 2-70; however, unlike the sales tax and FET, the insurance costs are added to
operating costs each year in HD TRUCS, as part of the payback calculation. See Table 2-71 for
MY 2032 FCEV powertrain insurance costs.
2.5.3.4 ZEV Registration Fee
Some states have adopted ZEV registration fees. Though 18 states do not have an additional
ZEV registration fee, of the 32 states that do, the registration fees are generally between $50 and
$225 per year.1139 While EPA cannot predict whether and to what extent other states will enact
ZEV registration fees, we have nonetheless conservatively added an annual registration fee of
$100 to all ZEV vehicles in our final HD TRUCS analysis. See RTC Section 3 for further
discussion.
2.6 BEV Charging Infrastructure
Charging infrastructure will be needed to support the growing fleet of heavy-duty BEVs. This
section describes how we accounted for costs associated with charging infrastructure in our
analysis of heavy-duty BEV technologies for our technology packages to support the feasibility
of the standards and extent of use of HD BEV technologies in the potential compliance pathway
for MYs 2027 through 2032.
2.6.1 Scope
As discussed in Chapter 1, we project future charging infrastructure will include a
combination of (1) depot charging—with infrastructure installed in parking depots, warehouses,
and other private locations where vehicles are parked off-shift (when not in use), and (2) public
charging, which provides additional electricity for vehicles during their operating hours or en-
route.
For this final rule HD TRUCS analysis, we project that most vocational vehicles and certain
day cab tractors—those with return-to-base operations— will rely on depot charging. We
estimate upfront capital hardware and installation costs for depot charging to fulfill each BEV's
daily charging needs off-shift with the appropriately sized EVSE.1140 This approach reflects our
expectation that many heavy-duty BEV owners will opt to purchase and install sufficient EVSE
ports at or near the time of vehicle purchase to ensure that operational needs are met. Starting in
MY 2030 in our final rule HD TRUCS analysis we project en-route charging at public stations
will be used by eight BEV types: long-haul vehicles (both sleeper cab and long-range day cab
tractors) and coach buses. MY 2030 is the year when we project there will be sufficient public
charging infrastructure for HD vehicles for the projected utilization of such technologies under
the modeled potential compliance pathway. See RIA Chapter 1.6. We assign higher charging
costs to vehicles using public charging stations to reflect our expectation that upfront capital
costs and operating expenses for public EVSE1141 will be passed onto customers, in addition to
the electricity prices.
1139 National Conference of State Legislatures. "Special Fees on Plug-In Hybrid and Electric Vehicles". March 27,
2023. Available online: https://www.ncsl.org/energy/special-fees-on-plug-in-hybrid-and-electric-vehicles.
1140 We sized EVSE to meet vehicles' daily electricity consumption (kWh/day) based on the sizing VMT, as
described in RIA Chapter 2.2.1.2.2.
1141 En-route charging could occur at public or private charging stations though, for simplicity, we often refer to en-
route charging as occurring at public stations in the RIA.
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We acknowledge that even vehicles which predominantly rely on depot charging may utilize
some public charging, for example on high travel days. This could allow fleet owners to
purchase lower-power EVSE and reduce upfront depot infrastructure costs. In addition, we
recognize that not all BEV owners may choose to procure and install their own EVSE. Some
fleets may opt for lease agreements or alternative business models such as charging as a service,
in which a third-party provider owns, operates, and maintains the charging equipment for a
monthly (or other recurring) fee. Given the uncertainty around uptake and costs of these
alternatives to depot charging at this early market stage, we chose to account for the hardware
and installation costs of EVSE sized to meet BEV needs upfront in our analysis.
Depot and public charging infrastructure will vary depending on the number of vehicles that
stations are designed to accommodate and their expected duty cycles, site conditions, and the
charging preferences of BEV owners. The subsequent sections describe how we considered these
factors and estimated the associated costs for each vehicle type in our analysis.
2.6.2 Depot Charging Analysis
2.6.2.1 EVSE Costs
Vehicle owners with return-to-base (or "depot") operations who choose to install privately-
owned charging equipment have many equipment options from which to select. This includes
AC or DC charging, power level1142, number of ports and connectors, connector type(s),
communications protocols, and additional features such as vehicle-to-grid capability (which
allows the vehicle to supply energy back to the grid). Many of these selections will impact EVSE
hardware and installation costs. For example, an ICCT paper found that hardware costs more
than doubled between networked and non-networked1143 Level 2 EVSE ports (with networked
equipment costing more).1144 Among networked EVSE with one or two ports per pedestal, ICCT
found a roughly 10 percent difference in per-port hardware costs.1145
Power level of the EVSE is one of the most significant drivers of cost. While specific cost
estimates vary across the literature, higher-power charging equipment is typically more
expensive than lower-power units. For example, ICCT estimated hardware costs for a 350 kW
DCFC port to be five times higher than for a 50 kW port.1146 For this reason, we have evaluated
1142 Charging types are described in RIA Chapter 1.6.1.2.
1143 Networked charging equipment is equipped with communications hardware such as WiFi or cellular.
1144 Nicholas, Michael. "Estimating electric vehicle charging infrastructure costs across major U.S. metropolitan
areas". The International Council on Clean Transportation. 2019. Available online:
https://theicct.org/sites/default/files/publications/ICCT EV Charging Cost 20190813.pdf.
1145 Nicholas, Michael. "Estimating electric vehicle charging infrastructure costs across major U.S. metropolitan
areas". The International Council on Clean Transportation. 2019. Available online:
https://theicct.org/sites/default/files/publications/ICCT EV Charging Cost 20190813.pdf.
1146 Nicholas, Michael. "Estimating electric vehicle charging infrastructure costs across major U.S. metropolitan
areas". The International Council on Clean Transportation. 2019. Available online:
https://theicct.org/sites/default/files/publications/ICCT EV Charging Cost 20190813.pdf.
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infrastructure costs separately for four different, common power levels: AC Level 2 (19.2 kW)
and 50 kW, 150 kW, and 350 kW DCFC.1147
Installation costs typically include labor and supplies, such as wire, conduit, and other
hardware required for installation that is not supplied with the EVSE hardware purchase.
Installation costs may also be incurred for permitting, taxes, and any upgrades or modifications
to the on-site electrical service. These costs, especially those for labor and permitting can vary
widely by region.1148 Costs also vary by site conditions. The amount of land preparation and
trenching needed will depend on the distance from where vehicles are parked (and the charging
equipment is located) and the electrical panel.1149 For example, a recent study found that average
Level 2 installation costs at commercial locations increased by $20 for each extra foot of
distance between the EVSE and power source.1150 Another key factor is how many EVSE ports
are installed. ICCT estimated that on a per-port basis, installation costs for 150 kW ports were
about 2.5 times higher when only one port is installed compared to 6-20 per site.1151 And as with
hardware costs, installation costs may rise with power levels.
To reflect the diversity in anticipated depot infrastructure costs, we consider a range of
hardware and installation costs for each charging type in our analysis. For the NPRM analysis,
we developed the DCFC costs from a 2021 study (Borlaug et al. 2021) specific to heavy-duty
electrification at charging depots. The study estimated the cost for procuring and installing 50
kW EVSE to be $30,000-$82,000 per port, the cost for 150 kW EVSE to be $94,000-$ 148,000
per port, and the cost for 350 kW EVSE to be $154,000-$216,000 per port.1152'1153 In response to
comments received and to reflect more recent literature, we are updating the cost ranges for 150
kW and 350 kW EVSE in the NPRM to those from a 2023 NREL report (Wood et al. 2023),1154
which estimated combined hardware and installation costs to range from $112,200-$ 196,200 per
1147 Level 2 charging is available at a range of power levels. For simplicity, we have selected the upper end of the
range to reflect our expectation that some heavy-duty fleets may opt for this power level. However, we acknowledge
that some fleets may find that lower-power (e.g., 10 kW or 16.6 kW) Level 2 charging meets their needs and such
fleets would therefore be likely to have lower infrastructure costs. Other DCFC power levels between 50 kW and
350 kW may also be available; this list is not intended to be comprehensive but is instead targeted to evaluate the
range of potential costs.
1148 U.S. Department of Energy. "Costs Associated with Non-Residential Electric Vehicle Supply Equipment". 2015.
Available online: https://afdc.energv.gOv/files/u/publication/evse cost report 2015.pdf.
1149 U.S. Department of Energy. "Costs Associated with Non-Residential Electric Vehicle Supply Equipment". 2015.
Available online: https://afdc.energv.gOv/files/u/publication/evse cost report 2015.pdf.
1150 Schey, Stephen, Kang-Ching Chu, and John Smart. "Breakdown of Electric Vehicle Supply Equipment
Installation Costs. Idaho National Laboratory." 2022. Accessed March 13, 2023.
https ://inldigitallibrary. inl.gov/sites/sti/sti/Sort_63124.pdf.
1151 Nicholas, Michael. "Estimating electric vehicle charging infrastructure costs across major U.S. metropolitan
areas". The International Council on Clean Transportation. 2019. Available online:
https://theicct.org/sites/default/files/publications/ICCT EV Charging Cost 20190813.pdf.
1152 Costs are expressed in 2019 dollars. We did not include the cost that may be incurred if a depot owner decides to
install a separate meter for EVSE. These costs ($1,200-5,000) are relatively small compared to EVSE procurement
and installation costs and would be even smaller on a per port basis if spread across multiple EVSE ports.
1153 Borlaug, B., Muratori, M., Gilleran, M. et al. "Heavy-duty truck electrification and the impacts of depot
charging on electricity distribution systems". Nat Energy 6, 673-682 (2021). Available online:
https://www.nature.com/articles/s41560-021-00855-Q.
1154 This report did not include costs for 50 kW EVSE ports.
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150 kW EVSE port and from $180,100-$285,300 per 350 kW EVSE port.1155 Considering the
midpoints of these ranges, the EVSE costs in Wood et al. 2023 are about 25% higher than those
in Borlaug et al. 2021.1156 Most of the literature on Level 2 EVSE costs is for power levels
common for light-duty vehicle charging. For example, the ICCT study previously discussed
estimated hardware costs for networked 6.6 kW ports to be about $3,000 with approximately
another $2,000-$4,000 per port for installation.1157 We expect higher costs for higher-power
Level 2 charging equipment. An RMI study showed a spread of hardware costs from $2,500 for a
7.7 kW charger to $4,900 for a 16.8 kW charger, with one outlier over $7,000 (for 14.4 kW).1158
A guide by the Vermont Energy Investment Corporation (VEIC), which engaged in an electric
school bus pilot, estimates that equipment and installation for high-powered Level 2 EVSE could
range from $4,200 to over $21,000.1159 Consistent with the NPRM analysis, we selected a range
of $10,000 to $20,000 per EVSE port for our FRM final rule HD TRUCS analysis.
Table 2-76 summarizes the range of costs we considered for each charging type, adjusted to
2022 dollars.1160
Table 2-76 Combined Hardware and Installation Costs per EVSE Port (in 2022$)
Power level
Cost range
Level 2 (19.2 kW)
$ll,327-$22,654
DC-50 kW
$33,981-$92,882
DC-150 kW
$112,200-$ 196,200
DC-350 kW
$180,100-$285,300
2.6.2.1.1 Will costs change over time?
The hardware and installation costs shown above generally reflect present day values.
However, both could vary over time. For example, hardware costs could decrease due to
manufacturing learning and economies of scale. Recent studies by ICCT assumed a 3 percent
reduction in hardware costs for EVSE per year to 2030.1161>1162 By contrast, installation costs
1155 Wood, Eric et al. "The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric
Vehicle Charging Infrastructure." 2023. Available online: https://driveelectric.gov/files/2030-charging-network.pdf.
1156 Wood et al. 2023 cites multiple sources for EVSE cost ranges including Borlaug et al. 2021. The difference in
EVSE costs was estimated from values as presented in the papers without adjusting for dollar years. Costs in
Borlaug et al. are expressed in 2019 dollars whereas we treat values from Wood et al. as 2022 dollars.
1157 Nicholas, Michael. "Estimating electric vehicle charging infrastructure costs across major U.S. metropolitan
areas". The International Council on Clean Transportation. 2019. Available online:
https://theicct.org/sites/default/files/publications/ICCT EV Charging Cost 20190813.pdf.
1158 Neider, Chris and Emily Rogers. "Reducing EV Charging Infrastructure Costs". Rocky Mountain Institute.
2019. Available online: https://rmi.org/wp-content/uploads/2020/01/RMI-EV-Charging-Infrastructure-Costs.pdf.
1159 Vermont Energy Investment Corporation. "Electric School Bus Charging Equipment Installation Guide". August
2017. Available online: https://www.veic.org/Media/Default/documents/resources/reports/electric-school-bus-
charging-equipment-installation-guide.pdf.
1160 Values in the literature cited for Level 2 EVSE costs are assumed to be in 2019 dollars.
1161 Bauer, Gordon, Chih-Wei Hsu, Mike Nicholas, and Nic Lutsey. "Charging Up America: Assessing the Growing
Need for U.S. Charging Infrastructure Through 2030". The International Council on Clean Transportation, July
2021. Available online: https://theicct.org/wp-content/uploads/2021/12/charging-up-america-iul2021.pdf.
1162 Minjares, Ray, Felipe Rodriguez, Arijit Sen, and Caleb Braun. "Infrastructure to support a 100% zero-emission
tractor-trailer fleet in the United States by 2040". Working Paper 2021-33. ICCT, September 2021. Available online:
https://theicct.org/sites/default/files/publications/ze-tractor-trailer-fleet-us-hdvs-sept21.pdf.
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could increase due to growth in labor or material costs. As noted above, installation costs are also
highly dependent on the specifics of the site including whether sufficient electric capacity exists
to add charging infrastructure and how much trenching or other construction is required. If fleet
owners choose to install charging stations at easier, and therefore, lower cost sites first, then
installation costs could rise over time as stations are developed at more challenging sites. One of
the ICCT studies discussed above1163 found that these and other countervailing factors could
result in the average cost of a 150 kW EVSE port in 2030 being similar (~3 percent lower) to
that in 2021.
Due to the uncertainty on how costs may change over time, for this analysis we have kept
combined hardware and installation costs per EVSE port constant, which could potentially be a
conservative approach.
2.6.2.1.2 Tax Credit for Charging Infrastructure
As discussed in RIA Chapter 1.3.2, the IRA extends and modifies a federal tax credit under
section 30C of the Internal Revenue Code that could cover up to 30 percent of the costs for
businesses to procure and install EVSE on properties located in low-income or non-urban census
tracts (subject to a total cap of $100,000 per item) if prevailing wage and apprenticeship
requirements are met.1164 The tax credit is available through 2032. To reflect our expectation that
this tax credit—as well as grants, rebates, or other funding available through the IRA—could
significantly reduce the overall infrastructure costs paid by BEV and fleet owners for depot
charging, we used the low end of our EVSE cost ranges in the NPRM infrastructure cost
analysis. After further consideration, including consideration of comments on this issue and
availability of a new DOE analysis1165 of the average value of the 30C tax credit for HD
charging infrastructure, we have updated the depot EVSE costs in our final rule analysis to
reflect a quantitative assessment of average savings from the tax credit.
As noted above, the 30C tax credit could cover up to 30 percent of the costs for fleets or other
businesses to procure and install EVSE on properties located in low-income or non-urban census
tracts if prevailing wage and apprenticeship requirements are met. DOE projects that businesses
will meet prevailing wage and apprenticeship requirements in order to qualify for the full 30
percent tax credit1166 and estimates that 60 percent1167 of depots will be located in qualifying
census tracts based on its assessment of where HD vehicles are currently registered, the location
of warehouses and other transportation facilities that may serve as depots, and the share of the
1163 Bauer, Gordon, Chih-Wei Hsu, Mike Nicholas, and Nic Lutsey. "Charging Up America: Assessing the Growing
Need for U.S. Charging Infrastructure Through 2030". The International Council on Clean Transportation, July
2021. Available online: https://theicct.org/wp-content/uploads/202l/12/charging-up-america-iul2021 .pdf.
1164 IRA Section 13404, "Alternative Fuel Refueling Property Credit" under section 26 U.S. Code §30C, referred to
as 30C in this document.
1165 DOE. "Estimating Federal Tax Incentives for Heavy Duty Electric Vehicle Infrastructure and for Acquiring
Electric Vehicles Weighting Less Than 14,000 Pounds." Memorandum. March 11, 2024.
1166 As noted in DOE's assessment, the "good faith effort" clause applicable to the apprenticeship requirement
suggests that it is unlikely that businesses will not be able to meet it and take advantage of the full 30 percent tax
credit (if otherwise eligible).
1167 This estimate may be conservative as DOE notes that its analysis did not factor in that fleets may choose to site
depots at charging facilities in eligible census tracts to take further advantage of the tax credit. In addition, we note
that DOE estimated 68 percent of heavy-duty vehicles are registered in qualifying census tracts suggesting the share
of EVSE installations at depots that are eligible for the 30C tax credit could be higher.
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population living in eligible census tracts. Taken together, DOE estimates an average value of
this tax credit of 18 percent of the installed EVSE costs at depots. We apply this 18 percent
average reduction to the EVSE costs used in HD TRUCS for the FRM.
As noted above, for the NPRM, we had used the low end of our EVSE cost ranges to reflect
our expectation that the tax credit would significantly reduce EVSE costs to purchasers (i.e. we
used the low end to reflect typical EVSE hardware and installation costs less savings from the
tax credit). Since we explicitly model the tax credit reductions for the FRM analysis, we
determined it was appropriate to switch from using the low to the midpoint of EVSE cost ranges
for all EVSE types to better reflect typical hardware and installation costs before accounting for
the tax credit savings. The resulting hardware and installation costs for EVSE are shown in Table
2-77 before and after applying the tax credit. We use values in the right column in our depot
charging analysis.
Table 2-77 Combined Hardware and Installation EVSE Costs used in HD TRUCS (in 2022$)
Charging Type
Cost Before
Tax Credit
Cost After
Tax Credit
Level 2-19.2 kW
$16,991
$13,932
DCFC-50 kW
$63,432
$52,014
DCFC—150 kW
$154,200
$126,444
DCFC—350 kW
$232,700
$190,814
2.6.2.1.3 EVSE Sizing
In the preceding section, we described infrastructure costs for four different charging types
that we think could be used at depots. To estimate the corresponding costs for each vehicle type,
we considered the type and number of EVSE ports that different BEV owners may buy.
The choice of charging equipment will be based on the needs and preferences of each BEV or
fleet owner. Fleet owners may work with OEMs, dealers, utilities, or charging equipment
suppliers to analyze their charging options based on duty cycle requirements of the fleet and site-
specific conditions of the depot, warehouse, or yard where EVSE will be installed. Some owners
will likely opt for the lowest-power (and lowest-cost) EVSE type that is appropriate for the
application. Other fleets may choose to install higher-power charging options that be shared
among multiple BEVs in their fleet, or to prepare for future or additional vehicle purchases,
resiliency, or evolving business needs.
For our depot charging analysis, we analyzed the scenario where BEV or fleet owners would
opt for the lowest-cost EVSE option1168 that could be used to charge the vehicle battery
conservatively sized based on the 90th percentile VMT (as discussed in RIA Chapter 2.2.1.2.2
and 2.4.1.1) each day. While purchasers may make their own business decisions, we think
analyzing the lowest-cost EVSE option that meets operational needs is a reasonable approach to
estimating costs for the final rule. Two key inputs include (1) the amount of time a vehicle has to
charge at the depot each day, and (2) how many vehicles can share charging equipment.
1168 As discussed in Chapter 2.8.7.1.3, the lowest-cost EVSE option refers to the lowest cost on a per vehicle basis
accounting for both EVSE port price and the number of vehicles that can share a port.
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2.6.2.1.4 Depot Dwell Time
How long a vehicle is off-shift and parked at a depot, warehouse, or other home base each day
is a key factor in determining what type of charging infrastructure could meet its needs. We refer
to this as depot dwell time. This depot dwell time depends on a vehicle's duty cycle. For
example, a school bus or refuse truck may be parked at a depot in the afternoon or early evening
and remain there until the following morning whereas a transit bus may continue to operate
throughout the evening. Even for a specific vehicle, off-shift depot dwell times may vary
between weekends and weekdays, by season, or due to other factors that impact its operation.
The vehicles in our depot charging analysis span a wide range of vehicle types and duty
cycles, and we expect their dwell times to vary accordingly. In the NPRM, we used a dwell time
of 12 hours for every type of HD vehicle informed by our examination of start and idle activity
data1169 for 564 commercial vehicles.1170 In order to better understand how depot dwell times
might vary by vehicle application and class for our final rule analysis, we supported new data
analysis by NREL through an interagency agreement between EPA and the U.S. Department of
Energy. NREL analyzed several data sets for this effort: General Transit Feed Specification
(GTFS) data for about 21,700 transit buses,1171 operating data for nearly 300 school buses from
NREL's FleetDNA database, and a set of fleet telematics data from Geotab's Altitude platform
covering about 13,600 medium- and heavy-duty trucks in seven geographic zones1172 selected to
be nationally representative.1173 The truck dataset includes a variety of classes and vocations. As
described in Bruchon et al. 2024,1174 NREL separately analyzed data for four class combinations
(2b-3, 4-5, 6-7, and 8) and four vocations defined by vehicles' travel patterns (door to door, hub
and spoke, local, and regional). This results in sixteen unique freight vehicle categories.1175
Across all vehicle categories, NREL provided national dwell time distributions that describe
the number of hours vehicles spend at their primary domicile (or depot). For each of the sixteen
freight categories as well as for school buses, these dwell durations reflect the total daily hours
vehicles spent at their depots on operational weekday or weekend days regardless of whether the
vehicles were parked for one continuous period or across multiple stops throughout the day. For
transit buses, NREL estimated the typical time buses spent when parked at their depot overnight,
i.e., the time between the end of the last shift of the day and the first shift the following service
1169 Zhang, Chen; Kotz, Andrew; Kelly, Kenneth "Heavy-Duty Vehicle Activity for EPA MOVES." National
Renewable Energy Laboratory. 2021. Available online: https://data.nrel.gov/submissions/168.
1170 The dataset had been analyzed as a joint effort between EPA and NREL to inform EPA's MOVES model.
1171 Both GTFS schedule and real-time data were utilized along with information from the National Transit
Database.
1172 The seven zones are: San Jose-Sunnyvale-Santa Clara, CA; Pittsburgh, PA; Evansville, IN-KY; Lafayette, LA;
Janesville-Beloit, WI; Southern ID non-Metropolitan Statistical Areas (MSA); Eastern GA non-MSAs. Data used
was collected between September 7 and September 30, 2022. See Bruchon et al. 2024 for details on variables used
to select the seven representative zones.
1173 Bruchon, Matthew, Brennan Borlaug, Bo Liu, Tim Jonas, Jiayun Sun, Nhat Le, and Eric Wood. "Depot-based
Vehicle Data for National Analysis of Medium- and Heavy-Duty Electric Vehicle Charging." NREL/TP-5400-
88241. February 2024. Available online: https://www.nrel.gov/docs/fy24osti/88241.pdf.
1174 Bruchon, Matthew, Brennan Borlaug, Bo Liu, Tim Jonas, Jiayun Sun, Nhat Le, and Eric Wood. "Depot-based
Vehicle Data for National Analysis of Medium- and Heavy-Duty Electric Vehicle Charging." NREL/TP-5400-
88241. February 2024. Available online: https://www.nrel.gov/docs/fy24osti/88241.pdf.
1175 NREL's report also includes information on a long-distance vocation. However, we have excluded these from
our depot charging analysis because, as noted in Bruchon et al. 2024, the long-distance trucks in the sample are less
likely to meet the criteria for depot-based travel.
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day with separate estimates for weekdays, Saturdays, and Sundays. Days on which vehicles were
not operated were excluded from the samples.1176
There is a wide variation of dwell durations across vehicles and operating days. NREL
provided tenth to ninetieth percentile dwell durations for each combination of class and vocation,
where the tenth percentile values can be interpreted as the minimum depot dwell duration
applicable to 90 percent of vehicle operating days in the sample, the twentieth percentile is the
minimum dwell duration applicable to 80 percent of sampled vehicle days and so on. For our
analysis, we selected the thirtieth percentile values for weekdays,1177'1178 which corresponds to a
minimum depot dwell duration applicable to 70 percent of sampled vehicle days. As described in
RIA Chapter 2.7.2, we limited the maximum penetration of the ZEV technologies in HD
TRUCS, and corresponding to our modeled potential compliance pathway, to 20 percent in MY
2027 and 70 percent in MY 2032 for any given vehicle type. Therefore, our use of the thirtieth
percentile dwell times should cover the BEV technology in the projected technology packages
developed to support the final standards and could be considered conservative for vehicle types
or years with lower projected utilization of BEV technology.
We mapped the resulting dwell times1179'1180 for the 18 unique combinations of vocation and
class types (i.e., 16 freight vehicle categories plus transit and school buses) to the applicable
vehicle types in our HD TRUCS model. We applied dwell times from NREL's school bus
category to all eight school bus types in HD TRUCS and NREL's transit bus dwell times to all
four transit buses in HD TRUCS. We mapped the freight vehicles as follows. For vocational
vehicles in HD TRUCS, we assumed that those with an urban duty cycle corresponded to door-
to-door vehicles in NREL's analysis, those with a multipurpose duty cycle corresponded to hub
and spoke vehicles, and those with a regional duty cycle corresponded to either local or regional
depending on whether daily operational VMT was (a) less than or equal to 150 miles or (b)
greater than 150 miles, respectively.1181 For tractors, we assumed all vehicle types in our analysis
were either local or regional depending on the same daily operational VMT limits. There was
one heavy-haul vehicle type that we assumed would use depot charging, but which did not
1176 In addition, total dwell durations for school buses were only considered during the school year and stops at the
depot less than one hour were excluded.
1177 The total time a vehicle spends at the depot on a weekday is typically shorter than on a weekend when some
vehicles may operate for fewer hours. For this reason, we assumed fleet owners would size EVSE based on weekday
driving needs.
1178 NREL provided two sets of dwell durations for freight vehicles: 'fixed' and 'adjusted'. We selected the
'adjusted' values, which were more conservative than the corresponding 'fixed' values for the percentile selected.
See Bruchon et al. 2024 for more details.
1179 In NREL's "MHDVOperationsSummaries.xlsx" data file, in the "Statistics" tab, see column V
('Domicile_Hours_p3 0').
ii8° Bruchon, Matthew, Brennan Borlaug, Bo Liu, Tim Jonas, Jiayun Sun, Nhat Le, and Eric Wood. 2024. "National
Summary Statistics for Depot-Based Medium- and Heavy-Duty Vehicle Operations." NREL Data Catalog. Golden,
CO: National Renewable Energy Laboratory. Last updated: March 8, 2024. Available online:
https://data.nrel.gov/submissions/231. (See spreadsheet "MHDV Operations Summaries.xlsx".)
1181 See Bruchon et al. 2024 for a description of vocations in the truck data set.
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correspond to the vehicle types in NREL's analysis. For that vehicle type we assumed 8 hours
consistent with a recent ICCT report.1182
The final dwell times assigned to each of the vehicle types in our analysis ranged from 7.4
hours to 14.5 hours and are shown in Table 2-78.
2.6.2.1.5 EVSE Sharing
Charging infrastructure can be shared across multiple vehicles in a variety of ways. An EVSE
port with just one connector can be used sequentially by different vehicles. If those vehicles are
parked at the depot at different times of day, drivers may plug in when they park. If vehicles
have overlapping depot dwell times, employees may be tasked with swapping the connector
among vehicles—though this may have tradeoffs in terms of convenience and may not be
practical for all applications. Some EVSE ports are available for purchase with multiple
connectors allowing vehicles to charge sequentially without the need to swap connectors.1183
Rated power can also be shared across EVSE ports by either decreasing the charging rate of
vehicles charging simultaneously or charging vehicles one after another.1184 For example, a dual
port 150 kW DCFC unit could be configured to charge one vehicle at 150 kW or two vehicles at
75 kW. Some residential and commercial Level 2 charging equipment is also capable of power
sharing (e.g., the Tesla Gen 3 Wall Connector).1185 This can be accomplished through either a
multi-connector charging unit, or use of multiple units on the same electrical circuit which
communicate to limit the total power being delivered.
Sharing charging equipment or power may be attractive to fleet owners as it can reduce the
upfront costs associated with procuring and installing EVSE at depots. And by spreading
infrastructure costs across multiple vehicles, per-vehicle EVSE costs can decline. Of course, the
decisions of whether to share EVSE ports and which types of sharing are selected will depend on
the specific situation and operational needs of the fleet. For the NPRM, we assumed that each
vehicle using Level 2 charging would have its own EVSE port, while up to two vehicles could
share DCFC if charging needs could be met within the assumed dwell time. We received several
comments that these constraints were too limiting. In our final rule HD TRUCS analysis, we
updated our approach and project that up to two vocational vehicles can share one EVSE port if
there is sufficient depot dwell time for all vehicles to meet their daily charging needs. For
tractors, which tend to be part of larger fleets, we project up to four vehicles can share one EVSE
port if there is sufficient daily depot dwell time for each vehicle to meet its charging needs. We
note that for some of the vehicle types we evaluated, higher numbers of vehicles could share
EVSE ports and still meet their daily electricity consumption needs. However, in our final rule
HD TRUCS analysis we limit sharing to two vocational vehicles and four tractors per port,
which could potentially be a conservative approach.
1182 Ragon, Pierre-Louis et al "Near-term Infrastructure Deployment to Support Zero-Emission Medium- and
Heavy-Duty Vehicles in the United States," 2023. Available online: https://theicct.org/publication/infrastructure-
deployment-mhdv-may23/.
1183 Proterra. "New Proterra EV Charging Solutions Enable Full Fleet Electrification for Commercial Vehicles".
October 28, 2020. See EPA-HQ-OAR-2022-0985-0705.
1184 Agrawal, Ajay. "Charge More EVs with Power Management". ChargePoint, EV Charging Innovation: July 18,
2017. Available online: https://www.chargepoint.com/blog/charge-more-evs-power-management.
1185 Tesla. "Power Sharing Overview". See EPA-HQ-OAR-2022-0985-0700.
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2.6.2.2 Depot Summary
RIA Chapter 2.8.7 describes how EVSE are sized and per vehicle costs are assigned within
HD TRUCS for each of the vehicle types that we assume use depot charging taking into account
the vehicles' battery size, depot dwell time, and EVSE sharing constraints. The results are
summarized in Table 2-78 which shows the charging type (designated in the table by its power
level) assigned to each vehicle ID, how many vehicles can share the EVSE port, and the final per
vehicle EVSE cost (reflecting upfront hardware and installation costs for depot charging
accounting for the tax credit).1186 The depot dwell time and battery size for each vehicle type are
shown for reference.
Table 2-78 Summary of per vehicle EVSE costs (in 2022$)
Vehicle ID
Battery Size
(kWh)
Dwell
Time
(hrs)
Charging
Type (kW)
Vehicles
per EVSE
Port
EVSE Cost
($/vehicle)
01V Amb C14-5 MP
120
12.2
L2 (19.2 kW)
1
$13,932
02V Amb C12b-3 MP
113
12.5
L2 (19.2 kW)
2
$6,966
03V Amb C14-5 U
111
10.3
L2 (19.2 kW)
1
$13,932
04V Amb C12b-3 U
104
10.6
L2 (19.2 kW)
1
$13,932
05T Box C18 MP
244
11.6
DC - 50 kW
2
$26,007
06T Box C18 R
252
9.2
DC - 50 kW
1
$52,014
07T Box C16-7 MP
168
11.9
L2 (19.2 kW)
1
$13,932
08T Box C16-7 R
183
9.9
L2 (19.2 kW)
1
$13,932
09T Box C18 U
236
9.1
DC - 50 kW
1
$52,014
10T Box C16-7 U
162
10.2
L2 (19.2 kW)
1
$13,932
11T Box C12b-3 U
100
10.6
L2 (19.2 kW)
2
$6,966
12T Box C12b-3 R
118
7.9
L2 (19.2 kW)
1
$13,932
13T Box C12b-3 MP
109
12.5
L2 (19.2 kW)
2
$6,966
14T Box C14-5 U
100
10.3
L2 (19.2 kW)
1
$13,932
15T Box C14-5 R
118
9.7
L2 (19.2 kW)
1
$13,932
16T Box C14-5 MP
109
12.2
L2 (19.2 kW)
2
$6,966
17B Coach C18 R
710
NA
Public
0
$-
18B Coach C18 MP
1052
NA
NA
0
$-
19C Mix C18 MP
428
11.6
DC - 50 kW
1
$52,014
20T Dump C18 U
283
9.1
DC - 50 kW
1
$52,014
2IT Dump C18 MP
286
11.6
DC - 50 kW
2
$26,007
22T Dump C16-7 MP
277
11.9
DC - 50 kW
2
$26,007
23T Dump C18 U
283
9.1
DC - 50 kW
1
$52,014
24T Dump C16-7 U
259
10.2
DC - 50 kW
1
$52,014
25T Fire C18 MP
300
11.6
DC - 50 kW
1
$52,014
26T Fire C18 U
301
9.1
DC - 50 kW
1
$52,014
27T Flat C16-7 MP
168
11.9
L2 (19.2 kW)
1
$13,932
28T Flat C16-7 R
183
9.9
DC - 50 kW
2
$26,007
29T Flat C16-7 U
155
10.2
L2 (19.2 kW)
1
$13,932
30Tractor DC C18
351
9.2
DC - 150 kW
3
$42,148
1186 Note that all RV vehicle types have been assigned L2 EVSE with no sharing of EVSE ports. This was done to
reflect the fact that RVs will generally be charged at residences and are likely to have a very long dwell time
opportunity before the initial part of a trip. This assignment does not impact the HD TRUCS payback results
because we are not setting new Optional Custom Chassis Standards for RVs, and RV vehicle types have zero
percent ZEV adoption in the HD TRUCS results with this assignment.
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Vehicle ID
Battery Size
(kWh)
Dwell
Time
(hrs)
Charging
Type (kW)
Vehicles
per EVSE
Port
EVSE Cost
($/vehicle)
31Tractor DC C17
317
9.9
DC -150 kW
4
$31,611
32Tractor SC C18
973
NA
Public
0
$-
33Tractor DC C18
531
NA
Public
0
$-
34T Ref C18 MP
355
11.6
DC - 50 kW
1
$52,014
35T Ref C16-7 MP
290
11.9
DC - 50 kW
1
$52,014
36T Ref C18 U
355
9.1
DC - 50 kW
1
$52,014
37T Ref C16-7 U
286
10.2
DC - 50 kW
1
$52,014
38RV C18 R
564
7.4
L2 (19.2 kW)
1
$13,932
39RV C16-7 R
599
8.3
L2 (19.2 kW)
1
$13,932
40RV C14-5 R
381
7.8
L2 (19.2 kW)
1
$13,932
41Tractor DC C17
744
NA
NA
0
$-
42RV C18 MP
564
11.6
L2 (19.2 kW)
1
$13,932
43RV C16-7 MP
550
11.9
L2 (19.2 kW)
1
$13,932
44RV C14-5 MP
350
12.2
L2 (19.2 kW)
1
$13,932
45Tractor DC C18
891
NA
NA
0
$-
46B School C18 MP
266
14.5
DC - 50 kW
2
$26,007
47B School C16-7 MP
160
14.5
L2 (19.2 kW)
1
$13,932
48B School C14-5 MP
120
14.5
L2 (19.2 kW)
2
$6,966
49B School C12b-3 MP
113
14.5
L2 (19.2 kW)
2
$6,966
5OB School C18 U
252
14.5
L2 (19.2 kW)
1
$13,932
5 IB School C16-7 U
160
14.5
L2 (19.2 kW)
1
$13,932
52B School C14-5 U
111
14.5
L2 (19.2 kW)
2
$6,966
53B School C12b-3 U
104
14.5
L2 (19.2 kW)
2
$6,966
54Tractor SC C18
1164
NA
Public
0
$-
55B Shuttle C12b-3 MP
164
12.5
L2 (19.2 kW)
1
$13,932
56B Shuttle C14-5 U
158
10.3
L2 (19.2 kW)
1
$13,932
57B Shuttle C12b-3 U
151
10.6
L2 (19.2 kW)
1
$13,932
58B Shuttle C16-7 MP
264
11.9
DC - 50 kW
$26,007
59B Shuttle C16-7 U
245
10.2
DC - 50 kW
1
$52,014
60S Plow C16-7 MP
199
11.9
L2 (19.2 kW)
1
$13,932
61S Plow C18 MP
394
11.6
DC - 50 kW
1
$52,014
62S Plow C16-7 U
187
10.2
DC - 50 kW
$26,007
63 S Plow C18 U
388
9.1
DC - 50 kW
1
$52,014
64V Step C16-7 MP
169
11.9
L2 (19.2 kW)
1
$13,932
65V Step C14-5 MP
109
12.2
L2 (19.2 kW)
$6,966
66V Step C12b-3 MP
109
12.5
L2 (19.2 kW)
$6,966
67V Step C16-7 U
156
10.2
L2 (19.2 kW)
1
$13,932
68V Step C14-5 U
100
10.3
L2 (19.2 kW)
1
$13,932
69V Step C12b-3 U
100
10.6
L2 (19.2 kW)
1
$13,932
70S Sweep C16-7 U
182
10.2
L2 (19.2 kW)
1
$13,932
7IT Tanker C18 R
269
9.2
DC - 50 kW
1
$52,014
72T Tanker C18 MP
264
11.6
DC - 50 kW
$26,007
73T Tanker C18 U
263
9.1
DC - 50 kW
1
$52,014
74T Tow C18 R
413
9.2
DC - 50 kW
1
$52,014
75T Tow C16-7 R
300
9.9
DC - 50 kW
1
$52,014
76T Tow C18 U
400
9.1
DC - 50 kW
1
$52,014
77T Tow C16-7 U
261
10.2
DC - 50 kW
1
$52,014
78Tractor SC C18
834
NA
Public
0
$-
79Tractor SC C18
1164
NA
NA
0
$-
80Tractor DC C18
647
8
DC - 350 kW
4
$47,704
327
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Vehicle ID
Battery Size
(kWh)
Dwell
Time
(hrs)
Charging
Type (kW)
Vehicles
per EVSE
Port
EVSE Cost
($/vehicle)
81Tractor DC C17
531
NA
Public
0
$-
82Tractor DC C18
635
NA
Public
0
$-
83Tractor DC C17
459
9.9
DC -150 kW
3
$42,148
84Tractor DC C18
356
NA
Public
0
$-
85B Transit C18 MP
472
8.1
DC -150 kW
2
$63,222
86B Transit C16-7 MP
373
8.1
DC - 50 kW
1
$52,014
87B Transit C18 U
472
8.1
DC -150 kW
$63,222
88B Transit C16-7 U
341
8.1
DC - 50 kW
1
$52,014
89T Utility C18 MP
254
11.6
DC - 50 kW
$26,007
90T Utility C18 R
261
9.2
DC - 50 kW
1
$52,014
9IT Utility C16-7 MP
184
11.9
L2 (19.2 kW)
1
$13,932
92T Utility C16-7 R
198
9.9
DC - 50 kW
$26,007
93T Utility C14-5 MP
120
12.2
L2 (19.2 kW)
1
$13,932
94T Utility C12b-3 MP
114
12.5
L2 (19.2 kW)
1
$13,932
95T Utility C14-5 R
128
9.7
L2 (19.2 kW)
1
$13,932
96T Utility C12b-3 R
128
7.9
L2 (19.2 kW)
1
$13,932
97T Utility C18 U
250
9.1
DC - 50 kW
1
$52,014
98T Utility C16-7 U
174
10.2
L2 (19.2 kW)
1
$13,932
99T Utility C14-5 U
113
10.3
L2 (19.2 kW)
1
$13,932
100T Utility C12b-3 U
106
10.6
L2 (19.2 kW)
1
$13,932
lOlTractor DC C18
279
9.2
DC - 150 kW
4
$31,611
2.6.3 Public Charging Analysis
As noted above, starting in MY 2030, we project eight BEV types: long-haul vehicles (both
sleeper cab and some long-range day cab tractors) and BEV coach buses utilize public charging.
The per-vehicle costs associated with public charging infrastructure will depend largely on the
hardware and installation costs of the EVSE and station utilization. As discussed in RIA Chapter
1.6, recent studies have assumed different mixes of EVSE ports deployed at public stations,
ranging from 125 kW to 2 MW. For our final rule analysis, we modeled station costs to reflect a
2023 ICCT study that examined public charging costs for Class 8 BEV trucks.1187 The study
assumed that a mix of 1 MW and 150 kW EVSE ports would meet BEV charging needs with
each station capable of 20 MW power1188 and utilization reaching 15% by 2035. The study
estimated the mean levelized cost for trucks to charge at these stations to be 19.6 cents/kWh
accounting for EVSE hardware and installation costs, EVSE maintenance, land costs, upgrades
to the distribution infrastructure (see following section), electricity rates, demand charges, as
well as financial costs and profit margins of station operators.
As discussed in RIA Chapter 2.4.4.2, we used this value as the basis of our public charging
costs, which we then adjusted over time to reflect projected changes to electricity prices. This
approach to incorporating public infrastructure costs reflects our expectation that upfront capital
1187 Hussein Basma, Claire Buysee, Yuanrong Zhou, and Felipe Rodriguez, "Total Cost of Ownership of Alternative
Powertrain Technologies for Class 8 Long-haul Trucks in the United States." April 2023. Available online:
https://theicct.org/wp-content/uploads/2023/04/tco-alt-powertrain-long-haul-trucks-us-apr23.pdf.
1188 Each station was assumed to have 17 one MW EVSE ports and 20 150 kW EVSE ports.
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costs and operating expenses for public charging stations will be passed onto customers through
the charging cost.
We analyzed the feasibility of public charging to meet the daily charging needs for the eight
BEV vehicle types by assessing the time it would take to charge the energy needed for the daily
operating VMT using a maximum of 2C power (up to 1 MW), as discussed in Chapter RIA
2.8.7.3. The results are shown in Table 2-79.1189'1190 All vehicles, except 54Tractor_SC_C18 (is
not part of the technology package in the modeled potential compliance pathway), have
approximate charging times of less than 60 minutes when charging at 2C or 1 MW.
Table 2-79 Time to Charge at 2C or 1 MW for Daily Operating VMT
Vehicle ID
Operating VMT
Time to Charge at 2C or 1 MW
(miles)
(minutes)
17B Coach C18 R
158
26
32Tractor SC C18
420
59
33Tractor DC C18
216
32
54Tractor SC C18
420
70
78Tractor SC C18
300
50
81 Tractor DC C17
216
32
82Tractor DC C18
215
38
84Tractor DC C18
120
30
As discussed in RIA Chapter 2.2.1.2.2 and 2.2.1.2.3 and shown in Table 2-80, we also
calculated the amount of time it would take to charge the battery at 2C or 1 MW to enable the
vehicle to travel the 90th percentile daily VMT, assuming the vehicle has started the day charged
to travel the operating VMT. All of the publicly-charged tractor vehicle types in our analysis
have additional charging times of less than half an hour, which should allow drivers to charge
during a 30 minute break. The BEV coach bus has an approximate additional charging time of
less than an hour; however, since the sizing VMT for 17B_Coach_C18_R is 300 miles, if the
coach bus starts the day with a full battery, an additional charge to reach the 90th percentile daily
VMT would take less than 30 minutes.
1189 The time to charge for operating VMT is based on year 0 of operation. Because VMT declines over time, we
would also expect this time to correspondingly decline over time.
1190 This calculation uses a uniform charging rate; however, charging rates may vary based on the state of charge of
the battery.
329
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Table 2-80 Additional Time to Charge at 2C or 1 MW to Travel the 90th Percentile VMT
Vehicle ID
Operating VMT
90th Percentile VMT
Additional Charging Time
(miles)
(miles)
Needed for 90th Percentile
Daily VMT at 2C or 1 MW
(minutes)
17B Coach C18 R
158
450
48
32Tractor SC C18
420
571
21
33Tractor DC C18
216
349
20
54Tractor SC C18
420
571
25
78Tractor SC C18
300
300
0
81 Tractor DC C17
216
349
20
82Tractor DC C18
215
349
24
84Tractor DC C18
120
120
0
2.6.4 Other considerations
While our depot and public charging analyses described above focus on EVSE needs and
costs, we acknowledge that additional infrastructure costs associated with charging stations could
be incurred. If the electrical grid distribution hosting capacity (power available for new use) is
less than the charging station requires, investment will be needed to upgrade or "build out" that
portion of the grid to enable the depot to draw power. While large BEV fleets or BEVs with high
daily electricity consumption could force significant buildouts and associated expenditures, even
lower power depots could drive some buildout if their need exceeds the grid capacity. As
discussed in RTC section 7 (Distribution), we discuss demand posed by the phase 3 rule,
assuming that the compliance pathway developed in support of the standards is followed. We
see low demand at the national level, at the regional level in the high-volume freight corridors
which are the most likely candidates for initial electrification, and at the localized parcel level.
We also note that most (approximately 88%) of our projected depot ports will be Level 2, again
reducing potential demand occasioning buildout. See RIA Chapter 2.10.3. In addition, as
discussed in Chapter RIA 1.6.5, there are a variety of approaches by both utilities and BEV users
that could reduce the need or scale of such upgrades. Utilities can factor, distribution system
capacity into station siting decisions, and consider alternative charging solutions (e.g., mobile
charging units or standalone charging canopies with integrated solar generation). In addition to
charging at lower levels (as we project), fleets can engage in time of use and other managed
charging to limit the instantaneous demand on the grid.
In the NPRM, we noted that in many cases, costs for distribution system upgrades will be
borne by utilities and we did not model them in our analysis of EVSE or charging costs. In
consideration of comments received (see RTC 7 (Distribution)), information from a new DOE
analysis (described below), and from the literature, we have decided that it is appropriate to
include the cost of distribution upgrades in our FRM analysis. See RIA Chapter 2.4.4.2 for a
description of how we accounted for the costs associated with distribution upgrades for both
depot and public charging in the charging costs used in the final rule analysis.
Our analysis for assessing the cost of potential distribution grid buildout posed by the final
rule is informed by the DOE Multi-State Transportation Electrification Impact Study
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("TEIS").1191 It also provides information we have considered to inform questions of availability
of infrastructure necessary to support the standards under the modeled potential compliance
pathway within the rule's MY 2027-2032 and later time frame. The study focuses on 5 states
(California, New York, Illinois, Oklahoma, and Pennsylvania) selected to capture diversity in
population density (urban and rural areas), freight demand, BEV demand, state EV policies,
utility type (i.e., investor owned, municipality, or cooperative) and distribution grid composition.
The study is the first of its kind with respect to the combination of scale of the analysis, load and
distribution spatial and asset granularity (parcel and feeder-level respectively), scope of the EV
impacts, and time horizon. The study compares parcel level LMHD and HDV demand to parcel
supply by photo-voltaic and grid capacity at each examined parcel. The TEIS used the five states
to extrapolate a national demand for where and when upgrades will be needed to the electricity
distribution system—including substations, feeders, and service transformers—due to BEV load
under the EPA light- and heavy-duty rules (approximated) and under a no action case. The
results from these five-states are extrapolated to the IPM regions that we use to represent the
remaining 48 contiguous states within our power sector analysis. The Study also assesses the
potential impact of simple, conservative limited time charging to reduce the needs and associated
costs of distribution upgrades. This managed charging simply spreads the charging over the
dwell time available rather than apply maximum charging as soon as the vehicle parks (starts
dwell). The system peak power demand may still increase. With more sophisticated managed
charging, the existing system peak would be avoided which suggests that demand and
infrastructure savings could be a lower-end estimate compared to implementing more advanced
control sy stem s.1192
The TEIS evaluates demand from both the light- and heavy-duty sectors. The load profiles
used for this analysis combine, for the first time, the load profiles for a No Action case and for
both the Light- and Medium-Duty Multipollutant Standards rulemaking and this Phase 3 rule1193
into a single power sector analysis. The load profiles from light-, medium- and heavy-duty are
distributed into IPM regions using NREL's EVI-X suite of models for light-duty, LDVs, MDVs,
and heavy-duty buses; and using LBNL's HEVI-LOAD model for all other heavy-duty
applications. The resulting premise-level load profiles were aggregated up to electric utility
service territories. The system-level grid impacts and costs of electricity service were determined
based upon the profiles. Additional scenarios were modeled to evaluate the impact of both
unmanaged charging and managed charging. In the unmanaged case, the study assumes that EVs
are charged immediately when the vehicle returns to a charger. In contrast, managed charging
spreads the charging out more evenly over the period when the vehicle is parked at the charger.
With respect to heavy-duty, the TEIS evaluates charging demand from heavy-duty vehicles
using the Lawrence Berkely National Laboratory HEVI-LOAD modelling tool. HEVI-LOAD
provides granular temporal and geospatial resolutions ranging from the station location level to
traffic analysis zone, county, state, and freight corridors, to national scale. HEVI-LOAD's
1191 National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, Kevala Inc., and U.S.
Department of Energy. "Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-,
Medium-, and Heavy-Duty Electric Vehicles". DOE/EE-2818. U.S. Department of Energy. March 2024.
1192 TEIS at 4, 76.
1193 Electricity demand for heavy-duty ZEVs matches that of the interim control case as described in RIA Chapter
4.2.4 while demand from light- and medium-duty vehicles was based on Alternative 3 from the proposed
"Multipollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles."
331
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workflow consists of three major steps: data preprocess and scenario generation, agent-based
simulation, and resulting output. Data preprocessing and scenario generation takes input data for
travel demand, charging infrastructure, and road networks to create simulation scenarios. The
post-scenario, post-analysis outputs are an energy demand analysis and an infrastructure
assessment. More specifically, energy demand is considered on state/county/charging station
locations. Charging infrastructure planning assesses charger quantity and power determination
based on energy needs, charging session needs and charger utilization rate assumptions. The
Study further sets out its methodology respecting HDC trip synthesis, vehicle and trip behavior,
start time distribution, travel distance distribution, battery starting SOC distribution, charging
infrastructure scenarios, and managed charging.1194
Additional infrastructure costs could also be incurred based on the choices of the fleet owner.
For example, some fleet owners may opt to install battery energy storage or renewable energy
such as solar panels at charging stations. While these choices add upfront costs, fleet owners can
save on electricity costs over time. For example, as discussed in Chapter 1.6, by charging BEVs
from onsite battery energy storage rather than directly from the grid, owners can reduce the
amount of electricity purchased during peak hours (since battery energy storage can be
replenished during off-peak periods). This can help fleet owners take advantage of lower-priced,
time-of-use electricity rates, where applicable. Onsite battery energy storage can also be used to
avoid large power draws from the grid, potentially reducing costly demand charges that are tied
to peak power.1195 ANL's paper on Innovative Charging solutions shares stationary battery
strategies and analysis for Class 1-3 vehicles. While focused on LD and MD BEV, the positive
aspects of the ICS may apply to some HD BEV users. ICS concepts may also allow LD and MD
BEV users to implement stationary batteries and free up grid hardware needed for buildout for
HD BEV users.1196 Installing solar panels or other onsite renewables can support these strategies
while also reducing the overall volume of electricity fleet owners need to purchase from utilities
and potentially reducing the need for distribution upgrades described above. See also TEIS at 62
showing that in three of the five states analyzed, there are outright reductions in peak demand in
2032 between a no action case (reference case) and an action case with time-of-day adjustments,
and significant projected decreases in peak demand in the action case (light-duty and heavy-duty
standards) for the other two states in the study.
There is uncertainty about how many charging depots and public stations will incorporate
these technologies over time, and how the incorporation of these technologies could impact site
costs. The savings fleet owners may expect will also be highly variable based on local electricity
rates and the charging load of the site. However, we generally expect that many fleet owners who
choose to install onsite battery storage and renewables do so with the intent of recouping the
upfront capital costs through electricity cost savings. For these reasons, we do not include these
costs in our charging infrastructure cost estimates. Cost analysis for onsite battery systems is
covered in a study, "Innovative Charging Solutions for Deploying The National Charging
1194 TEIS at 16-25.
1195 National Renewable Energy Laboratory. "When Does Energy Storage Make Sense? It Depends." February 25,
2018. Available online: https://www.nrel.gov/state-local-tribal/blog/posts/when-does-energy-storage-make-sense-it-
depends.html.
1196 Poudel, Sajag, et. al. "Innovative Charging Solutions for Deploying the National Charging Network:
Technoeconomic Analysis". Argonne National Laboratory. March 2024.
332
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Network: Technoeconomic Analysis".1197 This study looks at the levelized cost of charging
(LCOC) to determine when onsite battery use drives net savings. Although the study is focused
on LD Class 1-3 vehicles, the EVSE and BES (battery energy storage) is of sufficient size that it
could apply to smaller HD BEV fleets. Directionally, this analysis supports that there will be
scenarios where HD BEV users benefit from applying BES.
2.7 Technology Adoption
In the transportation sector, new technology adoption rates often follow an S shape. DRIA at
231. That is, the adoption rates for a specific technology are initially slow, followed by a rapid
adoption period, then eventually levelling off as the market saturates. At proposal, we developed
a method to project the rate at which utilization of ZEV technologies in the modeled technology
packages could be accepted into the HD fleet. The schedule used in the NPRM was developed
by EPA based on initial literature searches.1198,1199>1200>1201>1202>1203> 1204>1205 The adoption rate
method used for the final rule includes updates to the proposal developed after considering
methods in the literature to estimate adoption rates of ZEV technologies in the HD vehicle
market as well as comments received after the proposed rule. The methods explored include the
following: (1) the methods described in ACT Research's ChargeForward report,1206 (2) NREL's
Transportation Technology Total Cost of Ownership (T3CO) tool,1207 (3) Oak Ridge National
Laboratory's Market Acceptance of Advanced Automotive Technologies (MA3T) model,1208 (4)
1197 Poudel, Sajag, et. al. "Innovative Charging Solutions for Deploying the National Charging Network:
Technoeconomic Analysis". Argonne National Laboratory. March 2024.
1198 Oak Ridge National Laboratory. "MA3T-TruckChoice." June 2021. Available at:
https://www.energv.gov/sites/default/files/2021-07/van021 lin 2021 o 5-28 1126pm LR FINAL ML.pdf.
1199 Oak Ridge National Laboratory. "Transportation Energy Evolution Modeling (TEEM) Program."
https://www.energy.gov/eere/vehicles/articles/transportation-energy-evolution-modeling-teem-program-l
1200 National Renewable Energy Laboratory. T3CO: Transportation Technology Total Cost of Ownership. Available
at: https://www.nrel.gov/transportation/t3co.html.
1201 Argonne National Laboratory. "ANL - ESD-2206 Report - BEAN Tool - MD HD Vehicle Techno-Economic
Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
1202 Pacific Northwest National Laboratory. GCAM: Global Change Analysis Model.
https://gcims.pnnl.gov/modeling/gcam-global-change-analvsis-model
1203 Robo, Ellen and Dave Seamonds. Technical Memo to Environmental Defense Fund: Analysis of Alternative
Medium- and Heavy-Duty Zero-Emission Vehicle Business-As-Usual Scenarios. ERM. August 19, 2022. Available
online: https://www.erm.com/contentassets/154d08e0d0674752925cd82c66b3e2bl/edf-zev-baseline-technical-
memo-16mav2022.pdf.
1204 ICCT and Energy Innovation. "Analyzing the Impact of the Inflation Reduction Act on Electric Vehicle Uptake
in the United States". January 2023. Available online: https://theicct.org/wp-content/uploads/2Q23/01/ira-impact-
evs-us-i an23 -2 .pdf.
1205 Al-Alawi, Baha M., Owen MacDonnell, Cristiano Facanha. "Global Sales Targets for Zero-Emission Medium-
and Heavy-Duty Vehicles—Methods and Application". February 2022. Available online:
https://globaldrivetozero.org/site/wp-content/uploads/2022/02/CALSTART_Global-Sales_White-Paper.pdf.
1206 Mitchell, George. Memorandum to docket EPA-HQ-OAR-2022-0985. " ACT Research Co. LLC. "Charging
Forward" 2020-2040 BEV & FCEV Forecast & Analysis, updated December 2021.
1207 National Renewable Energy Laboratory. T3CO: Transportation Technology Total Cost of Ownership. Available
at: https://www.nrel.gov/transportation/t3co.html.
1208 Oak Ridge National Laboratory. "MA3T-TruckChoice." June 2021. Available at:
https://www.energv.gov/sites/default/files/2021-07/van021 lin 2021 o 5-28 1126pm LR FINAL ML.pdf
333
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Pacific Northwest National Laboratory's Global Change Analysis Model (GCAM),1209 (5)
ERM's market growth analysis done on behalf of EDF,1210 (6) Energy Innovation's United States
Energy Policy Simulator used in a January 2023 analysis by ICCT and Energy Innovation,1211
and (7) CALSTART's Drive to Zero Market Projection Model.1212
The data we received in comments with respect to technology adoption rates relative to
payback periods are plotted with the payback values we used in the NPRM, as shown in Figure
2-9. DTNA suggested a curve for Class 4-7 ZEVs and one for Class 8 ZEVs.1213 EDF provided
an alternate distribution of adoption rate based on payback period developed from their
assessment of the inputs from a NREL study using the TEMPO Model.1214 Energy Innovation
provided payback versus adoption rate curves by vehicle segment.1215 ICCT recommended a
curve similar to TEMPO with a cap of 90% adoption.1216 As shown in the figure, in general the
adoption rate relative to the payback period follows a similar curve for all of the sources.
1209 Pacific Northwest National Laboratory. GCAM: Global Change Analysis Model.
https://gcims.pnnl.gov/modeling/gcam-global-change-analvsis-model
1210 Robo, Ellen and Dave Seamonds. Technical Memo to Environmental Defense Fund: Analysis of Alternative
Medium- and Heavy-Duty Zero-Emission Vehicle Business-As-Usual Scenarios. ERM. August 19, 2022. Available
online: https://www.erm.com/contentassets/154d08e0d0674752925cd82c66b3e2bl/edf-zev-baseline-technical-
memo-16mav2022.pdf.
1211 ICCT and Energy Innovation. "Analyzing the Impact of the Inflation Reduction Act on Electric Vehicle Uptake
in the United States". January 2023. Available online: https://theicct.org/wp-content/uploads/2023/01/ira-impact-
evs-us-i an23 -2 .pdf.
1212 Al-Alawi, Baha M., Owen MacDonnell, Cristiano Facanha. "Global Sales Targets for Zero-Emission Medium-
and Heavy-Duty Vehicles—Methods and Application". February 2022. Available online:
https://globaldrivetozero.org/site/wp-content/uploads/2022/02/CALSTART Global-Sales White-Paper.pdf.
1213 Appendix E. Zero Emission Truck Market Assessment. CARB Advanced Clean Truck Regulations. October 22,
2019. Accessible at https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2019/act2019/appe.pdf
1214 EDF Comments to Docket. EPA-HQ-OAR-2022-0985-1644-A1, p. 58-59.
1215 See Comments of Energy Innovation. Docket EPA-HQ-OAR-2022-0985-1604 at pages 9-12.
1216 See Comments of ICCT. Docket EPA-HQ-OAR-2022-0985-1553-A1, p. 7.
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100% A
90% ¦
Payback Period
TEMPO
• DTNA Class 4-7
A Energy Innovation; Rigid Truck
NPRM -2032
Payback Period (years)
¦ ICCT
• DTNA class 8
A Energy Innovation; Short-haul Tractor
NPRM -2027
Figure 2-9 Payback Curve Data Provided in Comments
In the final rule, we used data from the NREL's TEMPO model as provided by EOF to inform
our ZEV percentages in the technology packages in MY 2027, MY 2030, and MY 2032 in HD
TRUCS (Rta), using the same methodology we used in the proposal. We describe our reasons
for doing so, and our adaptation of that model, in the following section.
2.7.1 Technology Adoption based on TEMPO
As noted in RTC Sections 2.4 and 3.12.2, commenters criticized EPA's use at proposal of the
ACT Research payback equation. The critique from these commenters was both for lack of
transparency - stating that the equation was proprietary and so did not appear in the DRIA
making comment difficult without getting access - and one commenter obtained the equation
and asserted that they found no substantive basis for it. As just noted, in one commenter's
submitted comment, ACT Research itself reviewed the NPRM and stated that EPA had
misapplied the equation by leaving out various factors, including a consideration of total cost of
ownership in addition to payback period. Some commenters asserted that the total cost of
ownership approach used in NREL's Transportation Energy & Mobility Pathway Options
(TEMPO) Model (Muratori et al„ 2021) was a better way to assess the shape of the payback
335
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relative to adoption rate. One of these commenters stated that the NREL model "overcomes key
deficiencies of the ACT Research-based curve by being based on validated empirical data,
subject to peer-review, and freely available to the public."1217 One commenter also provided an
alternate distribution of adoption rate based on payback period developed from their assessment
of the inputs from a NREL study using the TEMPO Model.1218 This commenter also suggested
standards of significantly increased stringency using the TEMPO model.
The TEMPO model was one of those considered by EPA before proposal, as noted above. We
evaluated it as a part of the T3CO model. At that time, EPA did not use it because the adoption
distribution as a function of payback was not readily available. For the final rule, we further
evaluated NREL's TEMPO model, including discussions with NREL.1219'1220 NREL describes
TEMPO as "a transportation demand model that covers the entire U.S. transportation sector"
including the medium- and heavy-duty market. Inputs to the model include vehicle cost and
performance, fuel costs, charging and refueling availability, and travel behavior. The model
receives this information and applies a technology adoption based on market segment, vehicle
technology, scenario year, and vehicle class as a part of the outputs for TEMPO. The model uses
a logit formulation to describe a relationship between purchaser adoption and aforementioned
inputs, cost coefficients and financial horizon. The TEMPO model specifically evaluates HD
ICE vehicles, BEVs, and FCEVs, which aligns with the technologies we are evaluating with the
payback period curve. We agree with the assessment in comment that the approach developed by
NREL for use in the TEMPO model is more transparent. We also found NREL's TEMPO model
and approach to be robust.
A commenter provided in comments an adoption rate distribution as a function of payback
years using inputs and outputs obtained from NREL's TEMPO model. Using the outputs from
NREL, this commenter then calculated the adoption rates using the payback calculation
methodology we used in the proposal.1221 We evaluated the work conducted by this commenter
in development of their suggested alternative payback curve derived from the TEMPO outputs.
We obtained input and output TEMPO data from NREL, similar to the dataset they provided
to the commenter and analyzed it to obtain the relationship between the adoption rate and
payback period. Our purpose was to assess the reasonableness of utilizing the TEMPO results for
adoption rates and payback period relationships. As explained further below, our evaluation of
the work conducted by the commenter was that we were able to reproduce similar adoption rates
relative to payback periods as those provided by the commenter. Our assessment is that this
indicates that the results are replicable, and validates the use of the TEMPO model outputs as
explained below. Therefore, based on our assessment that NREL's TEMPO model is robust and
the adoption rates to payback period relationship is reproducible, for the final rule, we are
1217ICCT Comments to Docket. EPA-HQ-OAR-2022-0985-1553-A1, p. 2.
1218 EDF Comments to Docket. EPA-HQ-OAR-2022-0985-1644-A1, p. 58-59.
1219 Muratori, M, et.al. "Exploring the future energy-mobility nexus: The transportation energy & mobility pathway
options (TEMPO) model." September 2021. Available online:
https://www.sciencedirect.com/science/article/pii/S13619209210026507via%3Dihub. Also see "The Transportation
Energy and Mobility Pathway Options (TEMPO) Model Overview and Validation of VI.0." 2021. Available online:
https://www.nrel.gov/docs/fy21osti/80819.pdf.
1220 Miller, Neil. Memorandum to docket EPA-HQ-OAR-2022-0985. Summary of Stakeholder Meetings. March
2024.
1221 We note TEMPO normally uses a total cost of ownership method to relate vehicle costs to adoption rates,
however in publications and discussions, they state it is also a reasonable method to relate payback to adoption rates.
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continuing to use the same payback period method we used in the proposal but have revised the
adoption rates that correspond to the payback period bins based on data from NREL's TEMPO
model instead of the use of the ACT Research-based model.
The dataset provided by NREL included primary inputs and outputs as shown in Table 2-81;
these inputs and outputs are further disaggregated based on scenarios, class, market segment, fuel
and technologies for years 2020 to 2050 as shown in Table 2-82. Based on discussions with the
commenter, they only assessed the "central" scenario year and the relationship between adoption
rate was determined for all years from 2020 to 2050, vehicle classes and market segments.1222
The TEMPO model uses a total cost of ownership (TCO) in assessing potential adoption rates
of the technologies. We recognize that TCO is another common approach to address technology
adoption rates, but we believe that showing data in the form of payback years is a more
transparent way of showing an adoption rate. In the case of TCO, the financial horizon is an
input into the calculation rather than an output of the model, thus one has to assume a time
period in which to compare one cost of ownership analysis to another using the TCO method. In
the case of payback calculation, the payback time can be determined based on when operational
savings from a new technology is greater than the initial cost of investing in the technology. We
feel this is an important distinction. The scatter in Figure 2-10 shows that while the payback may
be the same, adoption rates may vary. This variation is not exclusive to the time horizon in which
TCO reaches cost parity; however, it does impart some additional information in that not all
fleets have the same considerations for adoption based on a payback time frame. A 4-year
payback, for example, may yield 7-40% adoption rates based on Figure 2-10. The adoption rate
scatter decreases as the payback period becomes shorter or negative, suggesting less variation in
response to adoption for technologies that immediately payback. Similarly, there is less scatter in
the adoption rates for technologies that pay back in more than six years, suggesting agreement in
reduced adoption rates for longer payback. Therefore, having payback as an output provides
additional information compared to using it as an input. Additional discussion of choice of
payback as a metric can be found at Preamble Section II.F. 1 and RTC Section 3.12. For the final
rule analysis, we also evaluated TCO within the HD TRUCS tool. As shown in Chapter 2.12, the
results of our payback analysis are complemented by the TCO results.
Thus, we need to determine the relationship between technology adoption rate determined in
TEMPO and payback where the payback year is the year when the upfront cost is offset by
operational savings. For EPA's analysis, incremental purchaser upfront cost was equal to the
incremental technology cost of the ZEV compared to the comparable ICE vehicle cost (i.e. the
incremental purchaser upfront vehicle cost) and the associated costs of the EVSE hardware and
installation (for BEVs using depot charging) after accounting for IRA tax credits, sales tax, and
FET. In NREL's TEMPO model, the dataset did not provide the upfront EVSE costs; instead,
this EVSE cost is amortized and combined with the dollar per kWh electricity cost. Therefore,
the cost of the EVSE is included in the operational cost. Thus, we calculated the vehicle cost
delta in TEMPO by subtracting ICEV vehicle cost from ZEV vehicle cost. Operating cost in
TEMPO is the sum of the annual maintenance cost, annual fuel costs and annual charging time
costs where the annual maintenance cost is computed using the dollar per mile cost and annual
VMT, and annual fuel cost is computed using the dollar per content of energy (diesel gallon
equivalent, kWh, or kg H2). The payback period for each technology, class, year and market
1222 Memo to Docket. Evaluation of TEMPO Model. Docket EPA-HQ-OAR-2022-0985.
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segment is then calculated using the upfront cost divided by the operational cost. The adoption
rate was calculated using the vehicle sales of each technology divided by the total vehicle sales.
Since each ZEV (EV-150, EV-300, EV-500 and FCEV)1223 technology may a have different
payback period, the ZEV level payback period was weighted by the sales percent of each ZEV
technology and divided by the sum of ZEV sales percent. The result of our analysis of the
TEMPO data is plotted along with the data from the commenter for payback period and adoption
rates as shown in Figure 2-10 and shows reasonable agreement.
Table 2-81 Primary Inputs and Outputs for TEMPO
Inputs/Outputs
Unit
Input/Output Disaggregation Level
Vehicle Sales
'000 Vehicles
Scenario, Year, Class, Market Segment, Technology
Vehicle Stock
'000 Vehicles
Scenario, Year, Class, Market Segment, Technology
C02 Emissions
MMT
Scenario, Year, Class, Market Segment, Technology, Fuel
Energy Consumption
TBtu
Scenario, Year, Class, Market Segment, Technology, Fuel
TCD
$/mile
Scenario, Year, Class, Market Segment, Technology
Vehicle Cost
$/Vchiclc
Scenario, Year, Class, Technology
Vehicle Fuel Economy
Miles/DGE
Scenario, Year, Class, Technology
Fuel Costs
$/DGE, $/kWh, $/kgH2
Scenario, Year
Maintenance
$/mile
Class, Technology
Charge Speed
kW
Scenario, Year, Class, Market Segment, Technology
Charging Time
Hr/mile
Scenario, Year, Class, Market Segment, Technology
Charging Time cost
$/mile
Scenario, Year, Class, Market Segment, Technology
Financial Horizon
Years
Class
Discount Rate
Percent
Cost Coefficient
Class, Market Segment
Annual VMT
Mile/year
Market Segment
1223 EV-150, EV-300, and EV-500 here are referring to EVs with ranges of 150, 300, and 500 mile ranges,
respectively.
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Table 2-82 Primary TEMPO Input and Output Disaggregation
Parameter
Disaggregation Level
Scenario
Advanced Electricity Price
Advanced Hydrogen Price
Advanced Technology
Central
Conservative Electricity Price
Conservative Hydrogen & Electricity Price
Conservative Hydrogen Price
Conservative Technology
Class
Light Medium (Class 3)
Medium (Class 4-6)
Heavy (Class 7-8)
Bus
Market Segment
Bus
0-99 Miles
100-249 Miles
250-499 Miles
500+ Miles
500-749 Miles
750-999 Miles
1000-1499 Miles
1500-1999 Miles
2000+ Miles
Fuel
Electricity
Hydrogen
Diesel
Technology
EV-150
EV-300
EV-500
FCEV
HEV
ICEV
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Payback Period (Year)
Figure 2-10 Adoption rate as a function of payback period for data received from NREL and the commenter
(EDF).
The adoption rate curve was calculated by the commenter using the adoption rate data as
shown in Figure 2-10 The commenter then averaged the adoption values within a half year
period and smoothed the curve out in the longer payback periods to formulate the curve
presented in another commenter's comment. For example, for payback period of 1 year, all
values of adoption rates of technologies with a payback period between 0.75 to 1.25 years were
averaged into a single value. Likewise, for a payback period of 6.5 years, all values of adoption
rates within a payback period of between 6.25 to 6.75 years were averaged together. While there
is significant data for payback periods before eight years using this approach, there is limited
data for the payback periods longer than eight years. Table 2-83 tabulates the number of adoption
rate data points available for each payback period. Therefore, for some payback periods longer
than 6.25 years, the commenter used an approximate value. Figure 2-12 shows a comparison of
the adoption rate curves developed by the commenter and EPA. As the figure shows, we were
able to reproduce the commenter's results.
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Table 2-83 Number of Data Points within each Payback Period Provided by the commenter (EDF)
Payback
Period
Number of
Data Points
<0
150
0-1
142
1-2
32
2-3
20
3-4
12
4-5
13
5-6
11
6-7
5
7-8
5
8-9
1
9-10
3
10-11
5
11-12
1
12-13
0
13-14
2
14-15
2
15+
2
To determine the adoption rates for each payback bin, we recognized that we need to average
the data presented in Figure 2-10. We evaluated two methods to represent the adoption rates for
each payback bin that is shown in Table 2-84. First, we recognize that there is scatter in adoption
rate response to payback period as presented in Figure 2-10 and that EDF's half-year average
curve captures the shape of this adoption rate response to payback period. Second, while there is
more data for payback periods before one year, most of this data centers around a 95% adoption
rate; however, for payback periods between 0 and 6 years there is less data and significantly
more scatter. In some cases, as noted above, EDF used an approximation to fill in the data gaps
or to replace a non-representative value. As a result of this scatter and lack of data in later years
from more discrete averaging, we determined that it was reasonable to incorporate more years
into the averaging before binning. In this case, we averaged over a one-year period. For example,
for a payback period of 6 years, all values of adoption rates are averaged for payback periods of
between 5.50 to 6.50 years. We found instead of averaging the half-year averaged data as
presented by EDF, averaging over one-year shows similar results as the EDF curve, as shown in
Figure 2-11.
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120%
¦EDF 0.5 Year Averaging
&
-------
120%
Payback Period (Year)
—•—0.5 year — • — 1 year
Figure 2-12 Adoption rate as a function of payback period for different averaging methods
For the final rule, we maintained the same payback period bins used for the NPRM for
payback periods up to 10 years, as shown in Table 2-84. For the final rule analysis, we did not
include payback periods longer than 10 years, as discussed in the next subsection. To determine
the adoption rates for each payback bin for MY 2032, we averaged the data presented in Figure
2-11. For example, we averaged all of the adoption rate datapoints between the two and four
years of payback, as shown in Figure 2-12, to determine the adoption rate for the 2-4 year
payback bin.
Table 2-84 Payback Period Bins for the NPRM and Final Rule
NPRM
FRM
<0
<0
0-1
0-1
1-2
1-2
2-4
2-4
4-7
4-7
7-10
7-10
10-15
N/A
We note that this methodology is applicable to any technology, even though the data from the
TEMPO model used to develop the methodology was focused on ICE vehicle, BEV, and FCEV
technologies. We note again that the standards we have adopted in the final rule can be achieved
by many combinations of technologies, including technology packages not utilizing any ZEV
technologies. See Preamble Section II.F.4.
2.7.2 Payback Schedule for Final Rule
At proposal, we applied an additional constraint within HD TRUCS that limited the maximum
penetration of the BEV and FCEV technologies to 80 percent for any given vehicle type. This
limit was developed after consideration of the actual needs of the purchasers related to two
primary areas of our analysis. First, this limit takes into account that we sized the batteries,
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power electronics, e-motors, and infrastructure for each vehicle type based on the 90th percentile
of the average VMT. We utilize this technical assessment approach because we do not expect
heavy-duty manufacturers to design ZEV models for the 100th percentile VMT daily use case for
vehicle applications, as this could significantly increase the ZEV powertrain size, weight, and
costs for a ZEV application for all users, when only a relatively small part of the market will
need such specifications. Therefore, the ZEVs we analyzed and have used for the feasibility and
cost projections for the proposal and final rule in this timeframe are likely not appropriate for
100 percent of the vehicle applications in the real-world. Our second consideration for including
a limit for BEVs and FCEVs is that we recognize that there are a wide variety of real-world
operations even for the same type of vehicle. For example, some owners may not have the ability
to install charging infrastructure at their facility, or some vehicles may need to be operational 24
hours a day.
The TEMPO model, as shown in Chapter 2.7.1, would attribute 100% adoption to vehicles
that have an immediate payback (payback less than or equal to 0 year). Commenters also
provided ZEV adoption rate caps (or maximum rates of penetration in the adoption rate tables
that were submitted). For example, DTNA suggested that Class 4-7 ZEVs with payback rates of
<0 years would have an adoption rate of 73 percent, and Class 8 ZEVs with payback rates of <0
years would have an adoption rate of 36 percent, noting that these rates are consistent with
CARB's 2019 initial market assessment for the ACT rule1224 for vehicles. Energy Innovation's
payback versus adoption rate curves by vehicle segment1225 allowed for 100 percent adoption for
vehicles with immediate payback. CALSTART stated that EPA's proposed cap of 80% and ACT
Research's value of 86% with immediate payback were too constraining, and further describe
applications that have the potential to reach 100%.1226 ICCT recommended a cap of 90%.1227
After consideration of comments, including concerns raised by manufacturers, we re-evaluated
the maximum penetration constraints in HD TRUCS for the final rule. The constraints discussed
in the proposal, such as the methodology to size the batteries and the recognition of the variety of
real-world applications of heavy-duty trucks, still apply to the final rule analysis. Furthermore,
we are taking a phased-in approach to the constraints to recognize that the development of the
ZEV market will take time to develop. We broadly considered the lead time necessary to
increase heavy-duty battery production, as discussed in preamble Section II.D.2.ii.b, which
shows a growth in the planned battery production capacity from now through 2031 and other
issues like critical minerals, and for manufacturers to design, develop, and manufacture ZEVs (as
discussed in preamble Section II.F.3). We also have generally accounted for the time required for
infrastructure (as discussed in preamble Section II.F.3), including the potential distribution grid
buildout through 2032 as informed by the DOE's TEIS and discussed in RIA Chapter 2.6.4. We
see a similar trend in the growth of the infrastructure to support H2 refueling for FCEVs, as
discussed in RIA Chapter 1.8.3.6.
In recognition of these considerations, for the final rule we applied more conservative
maximum penetration constraints within HD TRUCS than at proposal. We limited the maximum
penetration of the ZEV technologies in HD TRUCS for the final rule to 20 percent in MY 2027
1224 Appendix E. Zero Emission Truck Market Assessment. CARB Advanced Clean Truck Regulations. October 22,
2019. Accessible at https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2019/act2019/appe.pdf
1225 See Comments of Energy Innovation. Docket EPA-HQ-OAR-2022-0985-1604 at pages 9-12.
1226 See Comments of CALSTART. Docket EPA-HQ-OAR-2022-0985-1656-A1 at p. 13.
1227 See Comments of ICCT. Docket EPA-HQ-OAR-2022-0985-1553-A1, p. 7.
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and 70 percent in MY 2032 for any given vehicle type, as shown in Figure 2-13. For payback
bins with payback periods of 4 years or less, the MY 2030 adoption rates were established to
reflect a 33 percent of the increase between the MY 2027 and MY 2032 adoption rates (see
Equation 2-1). This ensures that the adoption rates in MY 2030 are lower than other reasonable
approaches, such as a linear interpolation, allowing for more time for the electric charging and
hydrogen refueling infrastructure to be better established.
Equation 2-1 MY 2030 Payback Schedule Calculation
AdoptRateMY3o = AdoptRateMY27 + [(AdoptRateMr32 — AdoptRateMY27) * 33%]
Maximum Adoption Rates by Model Year
80%
70%
CD
+-»
Sl 60%
c
~ 50%
Q.
5 40%
| 30%
£
X 20%
ro
10%
0%
2026 2027 2028 2029 2030 2031 2032 2033
Model Year
Figure 2-13 Maximum Adoption Rate Caps in Payback Schedules for Final Rule
We received comments suggesting that technology would not be adopted if the payback
period was too long. For example, some commenters stated that an adoption period for payback
exceeding 10 years was unrealistic. Another commenter believes it is not prudent to have a
payback period longer than 10 years because of inherent risk of adopting new technology for
first purchasers. Other commenters said that the financial horizon (or payback period) can be as
long as 12 years depending on vehicle class and type, noting that municipalities may keep
vehicles longer. While the TEMPO data provided by NREL showed adoption for time periods
beyond 10 years, we recognize the available data in that timeframe is limited. Therefore, after
consideration of comments, we did not project any adoption of technologies that had payback
periods greater than 10 years in our analysis. The schedule also utilizes lower rates of technology
acceptance than those used in the proposal for payback periods greater than four years.
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The payback schedules used in HD TRUCS for the final rule are shown in Table 2-85. As
discussed above in this section, the schedule shows that when the payback is immediate, in the
final rule we conservatively project up to 20 percent of that type of vehicle could use BEV
technology in MY 2027, for example, with diminishing adoption as the payback period increases
to more than 4 years. After consideration of comments from some stakeholders, we also set the
adoption rates to zero for payback bins that were greater than 10 years.
The comments raised by manufacturers were thus considered and addressed in our final rule's
approach to HD TRUCS and the projected technology packages: by applying the MY 2027, MY
2030 and MY 2032 "cap" constraints, as discussed above, and through lower ZEV adoption in
the technology packages for payback periods that are longer than 4 years (including setting
adoption to zero for technologies with payback periods longer than 10 years) and higher ZEV
adoption when payback is 4 years or sooner. The relationship between adoption and payback
period that was created from TEMPO outputs differ from the ACT payback schedule used at
proposal and reflects a more typical S-curve, where adoption starts slowly and then speeds up.
(Note, the 70 percent constraint we imposed in MY 2032 and explained in this chapter limits the
adoption of the shortest payback bins).
The schedule shown in Table 2-85 was used in HD TRUCS to evaluate the use of BEV or
FCEV technologies for each of the 101 HD TRUCS vehicle types based on its payback period
forMYs 2027, 2030 and 2032.
Table 2-85: Payback Schedule Used in the Final Rule HD TRUCS
Payback Bins
MY 2027
MY 2030
MY 2032
<0
20%
37%
70%
0-1
20%
37%
70%
1-2
20%
37%
70%
2-4
20%
26%
39%
4-7
14%
14%
14%
7-10
5%
5%
5%
> 10
0%
0%
0%
In Figure 2-14 the payback schedules we developed and used for the final rule analysis for
MYs 2027 and 2032 are shown compared to the values shown previously in Figure 2-9.
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Payback Period
100%
90%
80%
70%
oj 60%
ro
en
o 50%
Q_
O
~C5
<40%
30%
20%
10%
0%
0 2 4 6 8 10 12 14 16
Payback Period (years)
—•— tempo ¦ ICCT
• DTNA Class 4-7 • DTNA Class 8
~ Energy Innovation; Rigid Truck ~ Energy Innovation; Short-haul Tractor
NPRM-2032 FRM-2032
FRM - 2027
Figure 2-14 Adoption Rate to Payback Period Comparison for FRM
2.8 HD TRUCS Functionality
HD TRUCS is an extensive physics-based tool designed to project technology feasibility,
payback, and adoption rates in future model years. In this mlemaking, EPA used HD TRUCS to
evaluate inclusion of ZEV technologies in one potential compliance pathway. This chapter
includes the methodology and formulas used in the tool, with main topics and calculations
organized similarly to the structure of this chapter of the RIA. The ICE Tech tab is covered in
RIA Chapter2.3, the BEV Tech tab in RIA Chapters 2.4 and 2.6, and the FCEV Tech tab in
RIA Chapter 2.5.
2.8.1 Baseline Energy and Fuel Consumption
EPA calculated the required energy consumption for vehicles using GEM with the physical
parameters of an ICE vehicle. (See RIA Chapter2.2 for more information on the GEM runs.) We
converted the GEM output of energy in kWh for each duty cycle to energy consumption per mile
A
¦
A
~
~
A
A
•
•
1
A
¦
A
I \
4
•
\
R "
•
:
i
347
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by dividing the energy consumption for each regulatory type by the distance of each GEM duty
cycle (see Chapter 2.2.2.1.2).
Each of the energy consumption calculations was then weighted by the appropriate drive
cycle weighting factor for their respective regulatory classes and summed to provide us with the
weighted energy consumption of each regulatory class. GEM distance weighting and time
weighting factors as well as average speed during non-idle cycles may be found in Chapter
2.2.2.1.2. Furthermore, GEM axle energy consumption includes air conditioning energy
consumption; this value is subtracted out and considered separately for BEV and FCEV
technologies.
The calculation for weighted energy consumption for tractors of each regulatory class is in
Equation 2-2 and the vocational vehicle weighted energy consumption calculation is in Equation
2-3. Table 2-15 shows the results of the calculations.
Equation 2-2 Weighted Energy Consumption per Mile for Tractors
kWh,
3
axle
mi
-I
kWhc * fc kWh
tract '—i dc mi
c=1
AC
Where:
kWYlaxle
= weighted energy consumption at the axle for tractors.
tract
kWhc = energy consumed during the appropriate test cycle, c.
fc = weighting factor for the appropriate test cycle, c, as shown in Table 2-14.
dc = the total driving distance for the indicated duty cycle, c, as shown in Table 2-13.
c = tractor drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles.
kWh
= weighted energy consumption of air conditioning (AC) load.
AC
Equation 2-3 Weighted Energy Consumption per Mile for Vocational Vehicles
kWh
axle
mi
voc ^moving * (l fdrive fpark)
(i
kWhc *fc _
^ ^moving
fdrive * drive fpark
c=1
* kWpark
kWh
mi
AC
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Where:
kWhaxle
weighted energy consumption at the axle for vocational vehicles.
kWhc = energy consumed during the appropriate test cycle, c.
fc = weighting factor for the appropriate test cycle, c, shown in Table 2-14
dc = the total driving distance for the indicated duty cycle, c, shown in Table 2-13.
c = vocational drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65
MPH cruise cycles
drive-idle and parked-idle fractions
vmoving = mean composite weighted driven vehicle speed, excluding idle operation, as shown
in Table 2-14, for Phase 2 vocational vehicles. For other vehicles, let vm0ving = 1-
AC energy consumption at the axle is converted from AC load and using the appropriate
weighting factors, shown in Equation 2-4.
Equation 2-4 Duty Cycle Weighted Average Air Conditioning Energy Requirement
Where:
kWAC= Air conditioning load; 1.0 for LHD and MHD, and 1.5 for all other vehicles
tc = the total driving time in seconds for the respective cycles as shown in Table 2-13.
fc = the weighting factors for the respective GEM duty cycles, shown in Table 2-14.
dc = the distance in miles, shown in Table 2-13
c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
Regenerative braking plays a large role in energy consumption of electric and fuel cell
vehicles, and we took this into account by calculating the distance-weighted percent of recovered
energy1228 from tractive energy for each regulatory class. To do this, we started with a model
developed in-house for hybrid vehicles and adjusted the input parameters to prevent the battery
capacity and state of charge from limiting the amount of recovered energy. We also limited
braking capacity to 90 percent of total braking power to allow for some use of the traditional
braking system. See Table 2-86 for input parameters.
1228 Recovered energy is amount of energy that is gained while driving an electric vehicle. It is gained in the form of
regenerative braking which is defined in footnote 928.
3
349
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Table 2-86 Input Parameters for Hybrid Vehicle Model
Vehicle Parameters
Input Values
Mass (kg)
Table 2-10 and Table 2-11
CdA (mA2)
Table 2-10 and Table 2-11
Crr (kg/t)
Table 2-10 and Table 2-11
Battery Size (kwh)
200
Pmax Regen (kW)
5001229
Battery SoC Min (%)
10
Battery SoC Max (%)
90
Hybrid System Efficiency (%)
73
Axle Efficiency (%)
92
Accessory Power driven by wheels (kW)
1.5
Hybrid Braking Power (% of total braking power)
90
We then calculated the road load power required for each drive cycle via Equation 2-5 using
positive values for tractive power and negative values for braking power.
Equation 2-5 Road Load Power
, (mveh* g * Crr pair*CdA*vc2
Proadlc ~ I 1000 2 ®~veh * ™veh ™veh * 9
* sin (atari f——* c
\ V100))) 1000
Where:
Proadlc = Road load power for each drive cycle, c
mveh = mass of the vehicle (kg)
g = gravitational constant of 9.81 m/s2
Crr = tire rolling resistance (kN/N)
CdA = drag area, m2
pair = density of air at a constant value of 1.17 (kg/m3)
vc = velocity of the vehicle at each specific point of the drive cycle, c
aveh = acceleration of the vehicle at each specific point of the drive cycle
G = percent slope of the drive cycle
c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
1229 por (]le fjna( raie we retained the use of 500 kW as the maximum regenerative power for all vehicle types in HD
TRUCS, however, this was an error and we should have used the maximum motor power for each vehicle type in
HD TRUCS. We have since performed checks on each regulatory sub-category using the motor power for each
vehicle type in HD TRUCS as Pmax Regen and found that the change in Pmax Regen had no effect on regenerative
braking.
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We were then able to calculate the regenerative braking power in Equation 2-7 using only the
negative values from hybrid available power in Equation 2-6.
Equation 2-6 Negative Road Load Power
Pneg_road\c ~ Proadie * P%brake * Vhyb * Vaxle Pace
Where:
P-negroad |c = available hybrid power for the appropriate cycle (kW).
P"/,brake = percent of braking power available to hybrid system, value is in Table 2-86.
Vhyb = hybrid system efficiency, shown in Table 2-86.
Vaxie = axle efficiency, shown in Table 2-86.
Pace = accessory power driven by the wheels, shown in Table 2-86.
c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
Equation 2-7 Regenerative Braking Power
Pregen\c ~ Pneg_road\c * Vhyb * Vaxle
Where:
Pregen |c = regenerative braking power for each cycle
Pneg_rod \ = available hybrid power for the appropriate cycle (kW).
Vhyb = hybrid system efficiency, value is in Table 2-86.
rjaxie = axle efficiency, value is in Table 2-86.
c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
Equation 2-8 Recovered Energy
kWhrec\c = _3600q^ (Pregen\c)
Where:
kWhrec\c = recovered energy of the appropriate cycle (kWh)
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c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
Equation 2-9 Tractive Energy
kWhtract\cyc ~ ^ppo ^ ^ (Ftract Ic)
Where:
kWhtract\c = tractive energy of the appropriate cycle (kWh)
Ptractlc = tractive power of the appropriate cycle (kW)
c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
The recovered energy percentage was calculated by dividing the recovered energy by the
tractive energy, the final percent was then weighted by the appropriate distance weighting factor
and summed to end up with a final percent of energy recovered during regenerative braking for
each regulatory class based on the GEM duty cycles using Equation 2-10 the results may be
found in Table 2-15.
Equation 2-10 Percent Regenerative Braking
_,nn \"fkWhrec A
/°reSen ^ [kWh^, f>c
Where,
kWhrec= recovery energy of the vehicle for cycle, c
kWhrec= tractive energy of the vehicle for cycle, c
c = GEM drive cycles where 1 = ARB transient cycle, 2 = 55 MPH cruise or 3 = 65 MPH
cruise cycles, shown in Table 2-13.
The percent regen was then multiplied against the energy per mile at the axle to end up with
energy gain due to regenerative braking per mile using Equation 2-11. The results are in Table 2-
16.
Equation 2-11 Energy Recovered from Regenerative Braking
kWhaxie
kWhregen
mi
Where,
%regen = Percent regenerative breaking
— %regen * '
veh
352
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kwhaxie _ wejgjltecj energy consumption per mile at the axle
The ZEV baseline per-mile energy consumed is described in Table 2-12. However, additional
energies are required for both the HVAC unit as well as the conditioning of the battery;
therefore, in this case, the ZEV vehicle level energy consumption is calculated as shown in Table
2-13. The per mile PTO (~~~~) ar|d per mile temperature related energy consumption
(ikwhTemp^ equatjons are described in Chapter 2.2.2.2.
Equation 2-12 ZEV Baseline Line Energy Consumption Per Mile
kWhbasUne
mi veh mi mi mi
kWhaxie kWhregen kWh
PTO
And,
Equation 2-13 ZEV Vehicle Level Energy Consumption Per Mile
kWhTot
mi veh mi mi
kWhfodgHrtg kWhTemp
Where,
kWhaxle
mi
kWh
= weighted energy consumption at the axle
regen
mi
kWhpTo
= regen energy consumption per mile
mi
kWhf emp
= PTO energy consumption per mile
= temperature related energy consumption per mile
2.8.2 Vehicle Miles Traveled
The annual miles driven for any particular vehicle changes with the age of the vehicle. We
therefore used a decrease in operating VMT over time in our payback analysis. The annual
operating VMT for each vehicle (AORveh) for vehicle age (VAi) is calculated using Equation
2-14.
Equation 2-14 VMT for Vehicle Age i
AORyghfVAi) — ORvehtopdayka
Where,
t0pday = number of operational days, 250 days with the exception of RVs where it is 8 days
ORVeh = 50th percentile range for a vehicle (mi/day)
353
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VAt = Vehicle age at year i (where i = 0 is the first year of vehicle ownership and i = 9 is the
tenth year of vehicle ownership)
ka = coefficient A
Here, change in coefficient A over time are shown in Table 2-4 for year 0 to 9. Cumulative
VMT over time (CORveh) is calculated using Equation 2-15.
Equation 2-15 Cumulative VMT over Year i
9
CORveh(Yi) = AORvehi
i=0
2.8.3 Power Take Off Loads
In addition to baseload of moving a vehicle, heavy-duty vehicles also perform additional
functions such as lifting a garbage can or bucket. As explained in RIA Chapter 2.2.2.1.4, PTO
fuel consumption is calculated using the percentage fuel consumption by auxiliary equipment
type for various HD applications from the California Department of Tax and Fee
Administration.1230 The fuel consumption is converted into energy consumption in terms of kWh
using the efficiency of diesel HD vehicles and associated PTO components, the energy content
of diesel fuel, and the operational range and time of the PTO unit, as shown in Equation 2-16.
Equation 2-16 PTO Calculation
kWhPT0 AORveh ( 1 \
— kWhgaL
Diesel pp
— (%PTO) —— (FEice) * tj trans * rjhyd
veh " ^ICE XyKveh^ov-dayJ
Where:
kWhgal DieSei = energy contet of a gallon of diesel fuel (40.5 kWh/gal123 *)1232
AORveh = annual VMT for the vehicle (mi) for vehicle at age 0
FE;ce = GEM2 calculated fuel economy of the ICE vehicle (%), 35%
%PTO = percent fuel consumption from the PTO device
ORVeh = 50th percentile range for a vehicle (mi)
top-day = daily operating hours (hr)
Vtrans = Efficiency of the transmission (%), 95%
Vhyd = Efficiency of the hydraulic pump (%), 85%
1230 See Cal. Code Regs. tit. 18, § 1432, "Other Nontaxable Uses of Diesel Fuel in a Motor Vehicle," available at
https://www.cdtfa.ca.gov/lawguides/vol3/dftr/dftr-regl432.html. .
1231 Alternative Fuels Data Center Fuel Properties Comparison. Accessed November 2023. Available online:
https://afdc.energy.gOv/files/u/publication/fuel_comparison_chart.pdf
1232 Conversion of low sulfur diesel with energy content of 138,490 BTU/gal with conversion factor of 1 kWh per
3412 BTU.
354
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2.8.4 ICE Vehicle Technology
2.8.4.1 ICE Vehicle Fuel Consumption
In the case of ICE vehicles, we calculated fuel consumption by converting the GEM output of
grams of CO2 into gallons of diesel for each regulatory class using Equation 2-17. See RIA
Chapter 2.2.2.1.2 for the CO2 output of each regulatory class and RIA Chapter 2.3.3 for fuel
consumption values.
Where:
MPGice = mile per gallon of ICE vehicle
10,180 = conversion factor for grams of CO2 into gallon of diesel consumed
fc = the weighting factors for the respective GEM duty cycles, shown in Table 2-14.
dc = the distance in miles, shown in Table 2-13.
2.8.4.2 Diesel Exhaust Fluid Consumption
DEF consumption (used in diesel vehicles) is a function of the DEF dosing rate where the
NOx reduction is estimated from the difference between estimated engine-out and tailpipe NOx
emissions, as described in Equation 2-18.
Where
MPGice = mile per gallon of ICE vehicle
x = the DEF dosing rate (5.18%).
2.8.4.3 ICE Powertrain System Cost
The cost of a ZEV powertrain system is calculated to determine the cost difference from the
comparable ICE powertrain as described in Equation 2-19.
Equation 2-19 Cost of the ICE powertrain system
Equation 2-17 ICE Vehicle Fuel Consumption
Equation 2-18 DEF Consumption
DEF = MPGice(-73.679x + 0.0149)
355
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Where,
Cj = Cost of ICE powertrain component i for the following components
i = Engine cost as determined based on engine power (kW) including projected costs to meet
the HD 2027 emission standards, gearbox, starter, torque converter clutch, final drive,
accessories (including 12-volt battery and TP A), and generator.
2.8.5 BEV Technology
To better understand the technical feasibility and paybacks of BEV technologies, several
calculations were performed. For physical parameters, the energy consumption, weight, and
physical volume of battery packs for the 101 vehicle types as defined in the vehicle applications
are sized in the 2_BEV_Tech worksheet in HD TRUCS. Other attributes including motor power,
payload impact, and component costs associated with the BEVs are also incorporated into this
section.
2.8.5.1 Temperature Effects on BEV
BEVs also have added energy requirements for heating and cooling of the vehicles as well as
maintaining a constant temperature (conditioning) of the battery pack. The national average
heating and cooling requirements are determined from the MOVES HD vehicle VMT
distribution as a function of outside temperature, as well as the energy consumptions for HVAC
and battery conditioning, detailed description can be found in Chapter 2.2.2.2. From MOVES,
these values are broadly grouped into temperature ranges in Table 2-40 with average HVAC
(QbusC) in kW and battery conditioning (%BC) as function size of the battery.
Table 2-87 Energy Consumption as a Function of Temperature Bands
Temperature Bins
(°F)
% VMT
Distribution
HVAC Power
Consumption (kW)
Battery Conditioning
(% of Battery)
<55
37%
5.06
1.9%
55-75
16%
-
-
>75
47.3%
2.01
3.0%
The power consumption for HVAC is rescaled for HD TRUCS using the surface area ratio for
each vehicle (SARveh) as in Equation 2-20.
Equation 2-20 SAR for Each Vehicle ID to SA of a Class 8 Bus
= 2 *(L*H + L*W + W*H)[veh]
veh 2 *(L*H+ L*W+ W *H)[bus]
Where,
Lbus> HbUS> Wbus = length, height, and width of the bus, respectively
Lveh> Hveh> Wveh = length, height, and width of the vehicle, respectively
356
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Table 2-88 shows the Lveh, Hveh, and Wveh different buses, ambulances, and for the
remainder of the vehicles.
Table 2-88 HD Vehicle Dimensions
Vehicle Type
W„„h (ft)
Hmh (ft)
(ft)
Class 2b-3
School Bus
7.5
6.3
12
Ambulance
Class 4-5
7.5
6.3
22
School Bus Ambulance
Class 6-7
School Bus
7.5
6.3
27
Transit Bus
Class 8 School Bus
7.5
6.3
29
Class 8 Coach Bus
7.5
6.3
40
All Other vehicles
5.2
6.35
9.7
The HVAC energy consumption for any one particular vehicle ID is then calculated using
Equation 2-21.
1 /
— TJ \SARveh
r)hvac t \
Vbus °P day )
Equation 2-21 Energy Consumption from Heating or Cooling per mile
kWhHVAC
"" veh Rs^
Where,
SAR = Surface area ratio of the vehicle compared to a Class 8 bus
Qbusc =Power requirement to heat or cool the inside of a Class 8 bus
t0pday = Daily operating time, 8 hrs
RSize = Vehicle 90th percentile VMT
Battery conditioning is expressed as a function of energy consumption, as shown in Equation
2-22:
Equation 2-22 Battery Conditioning per mile
kWh
BC
mi
= %BC * ¦
kWh
axle
veh
mi
kWhaxle
= weighted energy consumption at the axle for the vehicle
%BC = percent battery conditioning, Table 2-87
357
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2.8.5.2 BEV Energy Consumption Per Mile
The energy consumption of a vehicle can be considered a function of the per mile energy
consumption, the daily VMT, and losses associated in converting the stored energy into
mechanical energy used to move the vehicle. In the case of BEVs, these losses include the
battery, DC/AC inverter, and e-motor efficiencies; therefore, the baseline energy consumption of
an electric heavy-duty vehicle are calculated using Equation 2-23.
Equation 2-23 BEV Baseline Energy Consumption
kWh
basline
mi
Where,
kWhfjasline
kWhy
Lbasline
¦ *
BEV VePT ml
veh
= ZEV baseline vehicle level energy consumption per mile
veh
r/ePT = efficiency of the electric powertrain system, Table 2-44.
The temperature related energy consumption consists of per mile energy consumption of the
HVAC and battery conditioning, here the same equation can be used for heating or cooling,
Equation 2-24.
Equation 2-24 BEV Temperature Energy Consumption per Mile
kWhTemp
mi
Where,
kWhHVAC
_ (kWhHvAc kWhBC\
bev \ mi mi ) veh
mi
kWhBC
mi
= ZEV HVAC energy consumption per mile
veh
= ZEV battery conditioning energy consumption per mile
veh
2.8.5.3 BEV Battery Pack Sizing
Battery packs are sized to meet the energy requirement for each of the 101 vehicle types as
defined in Chapter 2.4.1.1 based on the vehicle class, duty cycle, and range requirements. The
total energy consumption per mile of BEVs (Equation 2-25) is determined based on the baseline
energy consumption and the temperature-dependent energy consumption. The temperature-
dependent energy is determined by weighting the HVAC loads based on the heavy-duty vehicle
miles traveled requiring heating, ventilation, or cooling using the MOVES VMT distribution in
Table 2-87.
358
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Equation 2-25 Total Energy Consumption Per Mile For BEV
kWh
Tot
mi
fkWhtemp kWhbaseiine\ ci/Trn/fT kWhfoaseline
= %VMT<55F + %VMT55_75F
BEV V 1711 1711 JbEV ml
BEV
+ %vmt>7SF ^ +
kWhf-gmp kWhbaseUne\
'}
Where,
mi mi
BEV
%VMT<55f = percent of VMT at temperature < 55 °F
%VMTSS_7SF = percent of VMT at temperature 55-75 °F
%VMT>7SF = percent of VMT at temperature > 75 °F
kwhte5mv . .
—-= ZEV temperature related energy consumption per mile at temperature <55 F
kWh
>75 F
ZEV temperature related energy consumption per mile at temperature > 75 °F
= Baseline energy consumption per mile of the BEV
mi
kWhfjaseline
mi
BEV
The pack capacity in terms of kWh is calculated using Equation 2-26.
Equation 2-26 Battery Pack Sizing
i kWhTot
kWh-narA — r
pacK \BEV ml
) (1 + Vdet) * Rsiz
\rinnn/
BEV ViDOD
Where
kWhjot
= vehicle level energy consumption for each BEV
BEV
Vdod = depth of discharge (90%)
Vdet = battery capacity increase to account for deterioration over battery life (ranging
between 0 to 15% depending on the vehicle type)
Rsize = Sizing VMT
We adjusted Equation 2-25 to account for the energy efficiency of the BEV's electrical
system, a daily maximum level of battery discharge, and the deterioration of battery capacity
over time as shown in Equation 2-26. The pack size is calculated by the required range for the
vehicle, RSize. This range is set at the sizing VMT, as described in Chapter 2.2.1. The maximum
level of discharge, r/D0D, is equal to 90%.
For the final rule analysis, we applied a deterioration adjustment factor (jjDET) to the sizing of
the battery as determined by the number of cycles the battery goes through over the course of a
10-year period instead of using the constant factor we used for the proposal analysis. A
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deterioration adjustment factor is applied such that the total number of cycles over the first 10
years of operation is less than 2,000 cycles. The total number of cycles is determined by first
calculating the annual throughput energy and the total possible energy throughput for a given
pack size for a given year, and the cycle number for each year is equal to the possible energy
throughput divided by the actual annual throughput energy and the cumulative total cycle is the
addition of each cycle over the 10 year period as show in Equation 2-27 through Equation 2-30.
Equation 2-27 Total number of battery cycles for vehicle age 0 to age 9
9
Cycletot = ^ CycleyX
i=0
Where,
Equation 2-28 Battery single cycle
Whactual
Cycleyi =
^^•possifcie
And,
Equation 2-29 Actual daily energy use
kWhTot
Whactual ~ AORygft i *
mi
BEV
And,
Equation 2-30 Daily possible energy use
kWh
WhpossiMe — Rsize * t0Pday * ^
Tot
Cycletot = Total number of cumulative cycles
Cycley i = The number of cycles for vehicle age i where i = 0 to 9
Whactuai = Actual throughput energy for vehicle age i where i = 0 to 9
WhpossiMe = Total possible throughput energy for a year
AORveh i= Average operating range for a vehicle at vehicle age i (where i = 0 to 9)
In the case where the total cumulative cycles are less than 2,000, the deterioration parameter
(Vdet) m Equation 2-26 is 0%. If the number of total cumulative cycles is greater than 2,000
cycles without a deterioration adjustment, the deterioration parameter is determined through
iterations of r/DET values until the total number of cycles is less than 2,000 cycles. The r/DET for
some vehicles in the final rule analysis is to 15%.
Using HD TRUCS, we also evaluated the payload impact of a BEV. The physical pack weight
and volume are calculated from the kWhpack and the pack level specific energy is 198 Wh/kg
360
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and energy density 396 Wh/L for MY 2027-2032. Furthermore, weight of the motor and gearbox
are included to complete the BEV driveline system.
The weight of the pack (mpack) is calculated using Equation 2-31.
Equation 2-31 Weight of the Battery Pack
mpack\BEy ~ kWhpack \BEy * Epack
Where,
kWhpack \ bev = battery pack energy for each
Epack = battery pack level specific energy
The weight of the motor (mmotor) is calculated using Equation 2-32 Motor Mass.
Equation 2-32 Motor Mass
Hl-motor * P-motor\veh
kw
Where,
Ckg_ = Conversion factor from ANL BEAN (kg/kW)
kw
Pmotorlveh = Power of the motor for each vehicle (kW) (motor power is calculated in
Equation 2-38)
The weight of the BEV powertrain system is calculated using Equation 2-33.
Equation 2-33 Weight of BEV Powertrain
™BEV_Pt\bev ~ ITlpack ITlmotor ^gearbox
Where,
mpack = weight of the battery pack
mmotor = weight of the e-motor
™gearbox = weight of the gearbox
Using the weight of the BEV driveline and the weight of the ICE powertrain components as
calculated in RIA Chapter 2.3.1, we calculated the payload impact (%PL) using Equation 2-34.
Equation 2-34 Payload Impact
TRd£W DT m,ir£
%PL\veh = — * 100
mPL
361
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Where,
mBEV_PT = weight of the BEV powertrain
rriicE = weight of the ICE powertrain system
mPL = the Standard Payload as described in 40 CFR 1037.801, which is less than the
maximum payload of a vehicle
The volume of the pack (Vpack) is calculated using Equation 2-35.
Equation 2-35 Pack Volume
Vpack ~ kWhpack * Ppack
Where,
kWhpack = energy of the battery pack
Ppack = pack level energy density
2.8.5.4 E-Motor Sizing
The e-motor in a BEV is used to convert electric energy into mechanical energy. To
determine the power requirement of the e-motor that required in the BEVs, the power
requirements for four performance metrics were calculated; these performance metrics are the
peak power requirement of the ARB transient cycle, 0-30 MPH vehicle acceleration times, 0-60
MPH vehicle acceleration times, and constant cruise at 6 percent grade as described in RIA
Chapter 2.4.1,2and below.
Power requirements for the transient cycle were calculated using the road load power as
described in Equation 2-5; for motor sizing, the power requirement is determined to be the
absolute peak power requirement.
Power requirements to meet the 0-30 MPH and 0-60 MPH acceleration time targets were
calculated using Equation 2-36. The target times associated with each vehicle class are shown in
Table 2-45.
Equation 2-36 Power Required for Vehicle Acceleration
p _ fVrfass * (X^-veh ^hrot) f^-veh * 9 * Cw Pair * ^class\
acc ~ V tacc\class V iooo 2 J
Vclass
* 1000
Where:
Pacc = Power required to accelerate to specific speed in kW
vdass = Final velocity of the vehicle in the specific weight class in m/s
^acc I class = Time to accelerate to the final speed for the specific weight class in seconds
362
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mveh = mass of the vehicle (kg)
g = gravitational constant of 32.2 m/s2
Crr = tire rolling resistance (kg/ton)
pair = density of air at a constant value of 1.17 (kg/m3)
Power requirements to maintain a constant cruise speed at 6 percent grade were calculated by
applying a grade factor to the road load power in Equation 2-5 and can be seen in Equation
2-37.1233 The vehicle speed for each class of vehicle was taken from ANL and can be seen in
Table 2-45.1234
Equation 2-37 Power Required for 6% Slope
Here:
mveh = mass of the vehicle (kg)
g = gravitational constant of 32.2 m/s2
6 = grade of 6%
vclass = velocity by vehicle weight class as listed in Table 2-45.
Crr = tire rolling resistance in (kg/ton)
Pair = density of air at a constant value of 1.17 (kg/m3)
aveh = acceleration of the vehicle at each specific point of the duty cycle
The maximum value of the power required to perform the ARB transient cycle, accelerate 0-
30 MPH, 0-60 MPH, and of maintaining a specific speed on a 6 percent grade was used for the
power requirement of the electric motor for each vehicle that is not a day cab or heavy haul truck
as shown in Equation 2-38. For a day cab, the power requirement is set at 400 kW and 450 kW
for heavy haul trucks., as described in RIA Chapter 2.4.1.2.
1233 Islam, Ehsan Sabri, Ram Vijayagopal, Aymeric Rousseau. "A Comprehensive Simulation Study to Evaluate
Future Vehicle Energy and Cost Reduction Potential", Report to the U.S. Department of Energy, Contract
ANL/ESD-22/6, October 2022. Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4jlhk/file/1406494585829.
1234 Argonne National Laboratory. VTO HFTO Analysis Reports - 2021. "ANL - ESD-2110 Report - BEAN Tool -
Heavy Duty Vehicle Techno-Economic Analysis.xlsx". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4ilhk/folder/177858439896.
+ Clygfl * TYlyeti
363
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Where:
Pmotor = Power of electric motor in kW for each vehicle
Vmotor = Electric motor efficiency, as defined in RIA Chapter 2.4.1.1.3.
Pr0adARB = peak power requirement for ARB transient cycle
PacCo_30 = peak power requirement for acceleration from 0-30 MPH
PacCo_60 = peak power requirement for acceleration from 0-60 MPH
Pr0ad6% = peak power requirement for maintaining a constant speed at 6 percent grade
2.8.5.5 BEV Powertrain System Cost
The cost of BEV powertrain systems is calculated to determine the cost difference from the
comparable ICE powertrain as described in Equation 2-39.
Equation 2-39 Cost of the BEV powertrain system
Cbevpt
Where,
Cj = Cost of BEV powertrain component i
Here component i includes the battery pack (Cpack), e-motor (Cmotor), power converter
(CpconnX on-board charger (C0nCharger\ gearbox (Cgearbox), final drive (Cfinaidrive) and
accessories (including the auxiliary converter and TP A) (Cacc) costs. The individual component
costs are described in RIA Chapter 2.4.3. Furthermore, Cpack and Cmotor are determined using
Equation 2-40 and Equation 2-41. The cost of the battery pack is determined from the pack size
as sized in RIA Chapter 2.4.1.1.3.
Equation 2-40 Cost of the Battery Pack
Cpack ~ kWhpack * \b]A/h\ ~ kW hpack * ( kW h ~ ^^battery/RPEj
^ 'IRA ^ '
Where,
([l
-------
RPE = Retail Price Equivalent, 1.42
Likewise, the cost of the motor is determined using the size of the motor as sized in RIA
Chapter 2.8.5.4.
Equation 2-41 Cost of the E-Motor
$
r — 7,T/|/
umotor ~ "¦** motor
Where,
kWmotor = E-motor power
$
— = Per kilowatt cost of the electric motor.
kW
For a breakdown of the e-drive component costs for all 101 vehicle types, see Tables 2-57
through 2-59.
2.8.6 FCEV Technology
Several calculations were performed to understand the payback periods of FCEV
technologies. For physical parameters, fuel cell system power output, the hydrogen consumption,
hydrogen fuel tank size, and physical volume of battery packs for the 101 vehicle types as
defined in the vehicle applications are sized in the 2_FCEV_Tech worksheet in HD TRUCS.
Other attributes including motor power and component costs associated with FCEVs are also
incorporated into this section.
2.8.6.1 Fuel Cell System Power Requirement
The power demand for a HD vehicle is calculated using either the continuous power at
constant cruise at 75 MPH or the 90th percentile power for the ARB transient cycle. Equation
2-42 shows that the fuel cell power demand is determined to be the maximum of the two cycles,
plus an additional 50% is added to the system sizing to accommodate occasional performance
scenarios where the vehicle requires more power plus the operation of the system's balance of
plant, using Equation 2-42. A portion of this size increase represents the addition of cells, which
can also add fuel cell stack durability.
Equation 2-42 Power of Fuel Cell Stack
PFc\veh = 75) * T]fcs
Where,
Parb1 = 90th percentile ARB transient cycle power
P75 = Power at 75 MPH cruise
Vfcs = Fuel cell system oversizing, as described in RIA Chapter 2.5.1.1.2
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2.8.6.2 E-Motor Sizing
The e-motors for FCEVs are sized to accommodate peak power needs the same way as BEVs,
as described in RIA Chapter 2.8.5.4.
2.8.6.3 FCEV Battery Pack Sizing
Battery packs are sized to provide 10 minutes of additional power to the HD vehicle when
requirements are not met by the fuel cell stack alone as shown in Equation 2-43.
Equation 2-43 FCEV Battery Pack Sizing
kWhp^fc | — (Pmotor ~ Pfc) * ^discharge ( 1
ven ^IDOD'
Where,
Pmotor = Motor power
PFC = Fuel Cell power
tdischarge = Battery discharge time, here it is assumed to be 10 minutes or 0.167 hour
rjdod = Depth of Discharge (60%)
2.8.6.4 Temperature Effects on FCEVs
While FCEVs can use waste heat from the fuel cell, like vehicles with internal combustion
engines, FCEVs have energy requirements for cooling of the vehicles as well as maintaining a
constant temperature (conditioning) of the battery pack. The considerations for energy required
to cool the interior cabin of the vehicle are similar to those of BEVs as described in RIA Chapter
2.8.5.1, where the HVAC (Q^uT) in kW and battery conditioning (%BC) are shown in Table
2-89. The per-mile energy consumption of HVAC and battery conditioning for FCEVs are
calculated using Equation 2-45.
Table 2-89 Energy Consumption as a Function of Temperature Bands
Temperature Bins
(°F)
% VMT
Distribution
HVAC Power
Consumption (kW)
Battery Conditioning
(% of Battery)
<55
37%
-
1.9%
55-75
16%
-
-
>75
47.3%
2.01
3.0%
2.8.6.5 FCEV Energy Consumption Per Mile
Like ICE vehicles, the energy required of a FCEV is stored in the form of fuel that is
converted into mechanical energy by a powertrain system. In the case of a FCEV, the stored
energy is in the form of hydrogen fuel. RIA Chapter 2.5.1.2describes how the daily energy
366
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consumption of a HD FCEV is considered, which is similar to that of a BEV; briefly these
include the per-mile energy consumption, daily VMT, and losses associated with fuel cell stack,
DC/AC inverter, gearbox, and e-motor efficiencies. The total energy consumption of a FCEV is
calculated using Equation 2-44:
Equation 2-44 FCEV Total Energy Consumption Per Mile
kWh
Tot
kWhbasiine ^ kWhTemp^
= * : +
ml FCEV VFCEV \ ml ml
And,
"HfCEV = "HfC * VePT
Where,
rjfcev = efficiency of the fuel cell powertrain, as shown in Table 2-66.
r/FC = efficiency of the fuel cell system, as described in RIA Chapter 2.5.1.2.1
r/ePT = Electric powertrain system efficiency, Table 2-44.
kWh^lme = baseline per mile energy consumption at the axle, Equation 2-12
The temperature related energy consumption consists of per mile energy consumption of the
HVAC and battery conditioning, here the equation is be used for cooling only for HVAC and
heating and cooling for battery conditioning, see RIA Chapters 2.8.5.1 and Equation 2-45.
mi
Where,
kWhHVAC
Equation 2-45 FCEV Temperature Energy Consumption per Mile
_ 1 ^ (kWhHVAC kWhBc\
FCEV VfCEV ^ mi mi 'veh
kWhTemp
= ZEV HVAC energy consumption per mile, for heating this value is 0
veh
= ZEV battery conditioning energy consumption per mile
veh
Vfcev = efficiency of the FCEV powertrain
kWhgc
2.8.6.6 FCEV Hydrogen Storage and Use
The total energy consumption per mile of FCEVs (Equation 2-46) is determined based on the
baseline energy consumption and the temperature-dependent energy consumption. The
temperature-dependent energy is determined by weighting the HVAC loads based on the heavy-
duty vehicle miles traveled requiring heating, ventilation, or cooling using the MOVES VMT
distribution in Table 2-87.
367
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lTot
Equation 2-46 Total Energy Consumption Per Mile For FCEV
kWhbaseline ^
MAru / L-M/ii >75F
n/ T/i/fT kWhbaSeline
— /oV M155-75f :
FC£V ml
fkWhtemp kWhbaseUne\
+ %VMT>75F 4^ + £££fime »
FCEV \ ml ml
mi
Where,
%VMT55_75f = percent of VMT at temperature 55-75 °F
%VMT>7SF = percent of VMT at temperature > 75 °F
kwhtJAv
ZEV temperature related energy consumption per mile at temperature > 75 °F
FCEV
mi
kWhfjaseline
mi
= Baseline energy consumption per mile of the FCEV
FCEV
The stored energy requirement (kWhs_H2\ ), in the form of hydrogen fuel, is calculated
from the total energy consumption per mile of the FCEV using Equation 2-44 and the daily
sizing VMT (Rsize), as shown in Equation 2-47.
Equation 2-47 Maximum Daily Energy Consumption of a FCEV
(kWhTot
kWHc H? . — Rei?
<*_H2\veh ~ "size { mi
Where,
kwhTot = total energy consumption per mile of FCEV
ml FCEV
RSize= Sizing range of the vehicle
FCEV''
The energy in kWh is converted into amount of hydrogen required, or stored hydrogen, using
the energy content for each kg of hydrogen using Equation 2-48.
Equation 2-48 Required Hydrogen Storage Weight
mSH21 = kWhs H2 (—( 1 ^
s_H2\veh s_H2 \33 33 kwh) \Vh2) \i _ ndeplete)
Where,
kWhs H2 = Daily maximum energy consumption of a FCEV
rjH2 =is the fraction of usable hydrogen (0.95)
Vdepiete = oversizing to avoid complete depletion of usable hydrogen (0.10)
We differentiate the operating energy requirement (kWh0p H2\^h) from the sizing energy
requirement using daily operating VMT, as shown in Equation 2-49.
368
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Equation 2-49 Daily Operational Energy Consumption of a FCEV
¦ (kWhTot
kWh0p H2\vgh = DORveh(-
mi
Where,
DORveh = daily operational range or VMT, Equation 2-14
kWhjot
FCEV'1
= total energy consumption per mile for an FCEV, Equation 2-44
FCEV
The energy in kWh is converted into amount of hydrogen required, or stored hydrogen, using
the energy content for each kg of hydrogen using Equation 2-50.
Equation 2-50 Required Hydrogen Weight for Operating the FCEV
mowraL = kWhopM2 (33 3®^) (^) (x _ ^ J
Where,
kWh0p H2 = Daily operating energy consumption of a FCEV
r/H2 = is the fraction of usable hydrogen (0.95)
Vdepiete = oversizing to avoid complete depletion of usable hydrogen (0.10)
2.8.6.7 FCEV Powertrain System Cost
The cost of FCEV powertrain systems is calculated to determine the cost difference from the
comparable ICE powertrain as described in Equation 2-51.
Equation 2-51 Cost of the FCEV powertrain system
CfceVpT = ^ cj
j
Where,
Cj = Cost of FCEV powertrain component j
Here component j includes the cost of fuel cell system (CFC), hydrogen tank (CH2TankX
battery pack (Cpack), e-motor (Cmotor), power electronics (CP£7ec), gearbox (Cgearbox),
differential (Qj//) and accessories (Cacc). The individual component costs are described in
Chapters 2.4.3 and 2.5.2. Most component costs are calculated the same way as BEVs, while CFC
and CH2Tank are determined using Equation 2-52 and Equation 2-53.
Equation 2-52 Cost of the Fuel Cell System
$
CFc — kWFC * ——
369
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Where,
$
kWFC = Fuel cell stack power— = Per kilowatt cost of the fuel cell
The cost of the hydrogen tank is determined using the mass of the stored hydrogen (mH2),
Equation 2-53 Cost of Hydrogen Tank
$
CmTank-mSH2*-k—jfi
Where,
ms_H2 = weight of stored hydrogen,
$
kg kg H2 = Per kg hydrogen-stored cost of the hydrogen tank
2.8.7 Charging Infrastructure
In the final rule analysis, we project BEVs either charge at depots or en-route at public
charging stops depending on vehicle type (see discussion in RIA Chapter 2.6). For BEVs using
depot charging, we assign an upfront per-vehicle cost associated with hardware and installation
of depot charging infrastructure to each of the vehicle types. For BEVs using public charging,
the upfront capital EVSE cost is assumed to be $0; hardware and installation costs for public
charging equipment are instead passed onto customers through the cost to charge (see Chapter
2.4.4.2).
2.8.7.1 Depot Charging Costs
2.8.7.1.1 Charging Time
We start by estimating in Equation 2-54 how many hours1235 it would take to charge a vehicle
sufficiently to cover its expected daily electricity consumption with each of four EVSE types:
Level 2-19.2 kW, DCFC-50 kW, DCFC-150 kW, DCFC-350 kW.
That is, for each charging type:
Equation 2-54 Hours to Charge by EVSE Type
1 1
tc — kWhBEV * — * TT77 * Vdod
Tjc
Where,
tc = hours to charge for each EVSE type
c = charging (or EVSE) type
kWhBEV = Total energy based on the depth of discharge and the battery size (corresponding
to sizing VMT)
1235 Charging rate may vary based on the state of charge of the battery, e.g., by slowing down when the battery is
nearly full. We have made the simplifying assumption that the charging rate is uniform for this purpose.
370
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7jc = charging efficiency of EVSE type c (89.3%)1236
kWc = power level for each EVSE type c (19.2, 50, 150, 350 kW)
Vdod = depth of discharge (90%)
2.8.7.1.2 EVSE Sharing
In the NPRM analysis, we projected that each vehicle using Level 2 charging had a dedicated
EVSE port while up to two vehicles using DCFC could share a port if there was sufficient dwell
time at the depot for both vehicles to charge. We have modified our approach in the FRM after
consideration of comments that this approach was too conservative and due to the availability of
more refined depot dwell times (discussed in RIA Chapter 2.6.2.1.4). For the final rule analysis,
we allow up to two vocational vehicles and up to four tractors - to share an EVSE port. This is
implemented as follows. We first check how many vehicles could share an EVSE port of a given
power level and meet their charging needs within the assumed depot dwell time. Vehicles are
assumed to have a depot dwell time (td) as shown in Table 2-78 and explained in RIA Chapter
2.6.2.1.4. This value divided by the charge time of the same vehicle type as shown in Equation
2-55. The result is the potential number of vehicles that could share an EVSE port (Sc). Sc is
rounded down to the nearest whole number.
Equation 2-55 Number of vehicles shared per EVSE port
Where,
Sc = potential number of vehicles that could share an EVSE port rounded down to the nearest
integer
tc = hours to recharge for each EVSE type
td = dwell time for each vehicle
The potential number of vehicles that could share an EVSE port within the allotted depot
dwell time is then compared to the cap or maximum allowed number of vehicles sharing an
EVSE port (SM) for that vehicle type. The actual sharing per EVSE type (SEVSE) is assumed to be
the lower of the two values, as shown in Equation 2-56.
Equation 2-56 Actual number of vehicles sharing an EVSE port
Sevse = MIN(Sc,Sm)
Here, SM is two for vocational vehicles and four for tractors. Note that if the dwell time is less
than the charging time using a given EVSE type (i.e. if Sc < 1), we do not consider that EVSE
type viable for the vehicle in our analysis.
1236 \ye adjust the estimated electricity consumption upward to account for charging losses from the wall to the
battery. While these losses may vary by charging type and other factors, as a simplifying assumption, we assign the
same losses for all charging types. The charging efficiency of 89.3 percent is the product of the AC/DC converter
efficiency of 94% and a battery charge and discharge efficiency of 95% from the MOVES model.
371
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2.8.7.1.3 Per Vehicle EVSE Cost
Lastly, the per vehicle EVSE cost depends on the cost of the EVSE and the number of
vehicles sharing the EVSE port. In some cases, a higher power EVSE that is shared by two
vehicles, for example, is a lower cost option than a lower power EVSE that is not shared. The
per vehicle EVSE cost (PVEVSE) is calculated using Equation 2-57.
Equation 2-57 Per vehicle EVSE cost
pv - Cevse
PVEVSE ~ c
JEVSE
Where, PVEVSE = Per vehicle EVSE cost
CEvse = cost of EVSE type
SEvse = number of vehicles sharing an EVSE port
The per vehicle EVSE cost is compared between the different EVSE types and we use the
EVSE type with the lowest per vehicle cost as the EVSE type assigned for that vehicle in HD
TRUCS. Below is an example of this determination.
For a tractor with a 400 kWh battery, the resulting charging time estimates (rounded to the
nearest hour) for each of the four charging types are shown in Table 2-90.
Table 2-90 Example Charging Times (for 400 kWh)
Level 2 -19.2kW
DCFC—50 kW
DCFC—150 kW
DCFC—350 kW
24 hours
9 hours
3 hours
1 hour
If the depot dwell time for this vehicle type is 10 hours, then the potential number of vehicles
that can share an EVSE port is shown in Table 2-91.
Table 2-91 Number of vehicles that can share an EVSE port
Level 2 -19.2kW
DCFC—50 kW
DCFC—150 kW
DCFC—350 kW
NA
1
3
4
Accordingly, the per-vehicle infrastructure costs for each of the viable charging options are
shown in Table 2-92.
Table 2-92 Example per-vehicle EVSE Costs in 2022$
Level 2 -19.2kW
DCFC—50 kW
DCFC—150 kW
DCFC—350 kW
NA
$52,014
$42,418
$47,704
The lowest cost option is for a 150 kW DCFC port shared between three vehicles at about
$42K per vehicle so we would assign that EVSE type and cost for the vehicle category in this
example.
372
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2.8.7.2 EVSE Port Counts at Depots
We estimate the number of new EVSE ports needed to support the MY 2027 through MY
2032 depot-charged BEVs in the modeled potential compliance pathway's technology packages.
For each vehicle type, we calculate the number of new BEV sales each model year as follows:
Equation 2-58 New BEV sales by model year
SABev,my = HSmy * Bmy
Where, SABEVMY = number of new BEV sales for each vehicle type for the specified model
year
HSmy = new vehicle sales for the entire heavy-duty fleet for the specified model year as
estimated in MOVES1237
Bmy = BEV sales share for the specified model year, equal to the BEV adoption rate for that
vehicle type multiplied by the percent of total HD sales for that vehicle type1238'1239
For each depot-based BEV type, we then calculate the number of new EVSE ports needed
each model year as follows:
Equation 2-59 EVSE port counts
SABev,my
PEVSE,MY = ^
J EVSE
Where, Pevse.my = number of EVSE ports needed for the specified model year for each depot-
based BEV type1240
SEvse = number of vehicles sharing an EVSE port for that vehicle type
As described in Chapter 2.8.7.1.3, we assign an EVSE type to each depot-charged BEV. As a
final step, we sum the port counts by EVSE type across all depot-charged BEVs for each model
year between 2027 and 2032. Resulting EVSE port counts are presented in Chapter 2.10.3.
2.8.7.3 Public Charging
For the FRM, we project that sleeper cabs, some day cab tractors, and any BEV coach buses
will use public charging. As described in RIA Chapter 2.6.3, we modeled our public charging
12371237 §aies numbers are from MOVES4.R3. More details on MOVES4.R3 can be found in RIA Chapter 4.
1238 por ilcavy heavy-duty vocational vehicles, we scaled the adoption rates down in MYs 2027 and 2028 because
the Phase 3 standards for these vehicles do not begin until MY 2029. These adoption rates were scaled to match the
reference case ZEV adoption shown in RIA Chapter 4.2.2.
1239 For day cab tractors, since our technology assessment for MYs 2027-2029 is based solely on depot-charged
BEVs (vehicle numbers 30, 31, 83, and 101), we scaled sales of only the depot-charged BEVs (in equal proportion)
to the levels consistent with our technology packages for MYs 2028 and 2029. Similar to the heavy heavy-duty
vocational vehicles, the day cab tractors were scaled to match the reference case in MY 2027 since the Phase 3
standards for these vehicles do not begin until MY 2028. Beginning in MY 2030, our technology assessment
includes BEVs and FCEVs utilizing public infrastructure. Consequently, our projections of sales of depot-charged
BEVs and associated EVSE decrease in MY 2030 from the MY 2029 levels as ZEV tractors designed to rely on
public infrastructure gain market share.
1240 We round up the number of EVSE ports to a whole number.
373
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assumptions after a recent ICCT analysis, which assumed that a mix of 1 MW and 150 kW
DCFC ports would be utilized. Although megawatt EVSE have the capability of 1 MW charging,
BEV batteries may not be able to accept the full power level. In order to ensure that our public
charging assumptions are feasible, in HD TRUCS we constrain the charging power to a c-rate of
2 (or 2C).1241 In our analysis, we calculate the amount of time it takes to charge up to their daily
operational demand (50th percentile VMT) with charging power levels at either 2C or 1
megawatt, whichever is the lower power level.1242 We have calculated this estimate using year 0
of operation (when the vehicle is new); however, since operating miles generally decline over
time as, described in RIA Chapter 2.2.1, the charge time for operating VMT would also be
expected to decline over time. Equation 2-60 shows how the power level for 2C is calculated for
each battery size.
Equation 2-60 Power at 2C charge rate
^ ^ 2 * kWhpack\BEv
20 ~ Tkr
Where,
Pic = charging power at 2C in kW
kWhpack \BEV = size of the battery pack in kWh
If P2c is less than 1 MW, then the P2c power value is used, however, if P2cis greater than 1
MW, 1 MW power is used as charging power.
The daily energy consumption for the BEV is determined using Equation 2-61,
Equation 2-61 Daily Energy Consumption
(kWhTot
kWhriav = 1
day V mi
Here,
kWh day = daily energy consumption
= operating energy of the BEV
AORveh(Yi)
i * ¦
BEV' tOPday
kWhT0t
mi BEV
AORveh(Yi) = Annual operating VMT for each vehicle for vehicle age i where i = year 0
t0pday = number of operating days, 250 days
Time for megawatt charging is calculated using Equation 2-62.
1241 For the same battery size (in kWh), 1C = Fully charged in 1 hour, 2C = Fully charge in 30 min. For example, to
charge a 150 kWh battery using a c-rate of 1, the charging power is 150 kW and the charging time is 1 hr; whereas
to charge it to the same 150 kWh using a c-rate of 2, the charging power is 300 kW and the charging time is 30 min.
1242 This calculation uses a uniform charging rate; however, charging rates may vary based on the state of charge of
the battery.
374
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Equation 2-62 Time for Mega-watt Charging
kWhday
tMW — p * °0
r2 C
Using the same parameters, we also calculated the time required to charge the battery to
enable the vehicle to travel the 90th percentile daily VMT, assuming that the vehicle has started
the day charged to travel the daily operating VMT. Equation 2-63 shows how we determined the
additional daily energy consumption required for a BEV to go from 50th percentile daily VMT to
90th percentile daily VMT.
Equation 2-63 Additional Energy Consumption to Achieve 90th Percentile Daily VMT from 50th Percentile
Daily VMT
/ kWhTnt
kWh90th_S0th = (Rsize — ORveh) * (¦
\ mi
Where,
RSize = Vehicle 90th percentile VMT
ORVeh = 50th percentile range for a vehicle (mi/day)
kWhjot
BEV'
= Operating energy of the BEV
BEV
Time for megawatt (or 2C) charging to go from 50th percentile daily VMT to 90th percentile
daily VMT is calculated using Equation 2-64.
Equation 2-64 Time to Mega-watt Charge from 50th Percentile Daily VMT to 90th Percentile Daily VMT
kWh90th_50th
190th-S0th — n * ^0
r2 C
2.8.8 Payback
We calculate the payback period (PBP) by subtracting cumulative operational savings from
upfront costs until the cumulative savings are greater than the upfront costs; the year when
cumulative savings are greater than the upfront costs is the year that is considered the payback
year as shown in Equation 2-65.
Equation 2-65 Payback period for each vehicle
PBPveh(Y) = Upfront costs delta — Cumulative operational savings < 0
Where the upfront costs delta is described in Equation 2-66,
Equation 2-66 Upfront cost delta between ICE and ZEV
Upfront costs delta = Upfront costs ZEV — Upfront costs ICE
In addition to upfront technology costs as described in RIA Chapters 2.7.4.3, 2.7.5.5 and 2.7.6,
we also incorporated state sales tax and Federal Excise tax into the total upfront cost as shown in
Equation 2-67 and Equation 2-68.
375
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Equation 2-67 Upfront costs for ICE or FCEV
Upfront costs ICE and FCEV = CPT * RPE * (1 + FET + ST)
or,
Equation 2-68 Upfront costs for BEV
Upfront costs BEV = CPT * RPE * (1 + FET + ST) + PVEVSE
Where,
CPT = Powertrain technology costs
RPE = Retail Price Equivalent, 1.42
FET = Federal Excise Tax, 12% for all Class 8 vehicles and all tractors and 0% for all other
vehicles
ST = State sales tax, 5.02%
PVEvse = ?er vehicle cost of the EVSE unit for depot charging BEV vehicles
The annual operating cost is calculated the same way for all technologies in Equation 2-69,
Equation 2-69 Annual operating cost
Annual Operating Cost (OY) = AFC + AMR + AIC + ZF
Where,
OY = Operating year, which starts in with the first year of operation and is calculated through
each of the first 10 years)
AFC = Annual Fuel cost for diesel, electricity and hydrogen fuels (RIA Chapter 2.7.8.1) AMR =
Annual Maintenance and repair cost (RIA Chapter 2.7.8.2)
AIC = Annual Powertrain Insurance cost (RIA Chapter 2.7.8.3)
ZF = $100 Annual ZEV registration fee (only applies to ZEV vehicles)
The cumulative operating cost for a vehicle in that model year (MY) is calculated by
summing the annual operating cost and the cumulative operational savings as the delta between
the annual ICE operational cost and the annual ZEV operating cost using Equation 2-70,
Equation 2-70 Cumulative operational savings
Cumulative operational savings (MY)
MY+l
= ^ [(Annual ICE Operating Cost of MY)cy
OY=MY
— (Annual ZEV Operating Cost of MY)cy]
Where,
MY = Model Year for 2027 to 2032
376
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OY = Operation year, where OY = MY for the first year of operation and increases to year 10
(the maximum payback period in our analysis, see RIA Chapter 2.7) according to Table 2-93,
Table 2-93 Operation years for each model year (MY)
Operational Year (i)
Year 1
Year 2
Year 3
Year 4
Year 5
Year 6
Year 7
Year 8
Year 9
Year 10
MY2027
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
MY2028
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
MY2029
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
MY2030
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
MY2031
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
MY2032
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2.8.8.1 Operational Fuel Consumption Cost
We calculate fuel costs for diesel, charging, and hydrogen using the total energy per mile
consumption of the vehicle as described in RIA Chapters 2.8.4.1, 2.8.5.2 and 2.8.5.3, and 2.8.6.4,
respectively. In the case of ICE vehicles, the GEM fuel economy (FE) values are reported in
miles per gallon instead of kWh per mile. For HD TRUCS computed per-mile energy
consumption, the values are reported in kWh/mi. Equation 2-71 describes the annual diesel fuel
consumption cost.
Equation 2-71 Annual Diesel Fuel Consumption Cost
fA.OR.-neh AO R-nph \
AFPdieselm) = —(1 + %PTO) * Prdiesel{OYd
\ r bicE rhICE J
Where,
AORveh = annual operating VMT (RIA Chapter 2.8.2)
Prdiesei(.OYi) = Price of diesel fuel, $/gal, for operating year (OY) where i can be 1 - 10
according to Table 2-93.
%PTO = Percent PTO use
The annual charging cost for a BEV is calculated using the total per-mile energy
consumption, the operating range and price of charging as shown in Equation 2-72 and described
in RIA Chapter 2.4.4.2.
Equation 2-72 Annual Electricity Fuel Consumption Cost
kWhBEV 1 1
AFPrelec(Yi) = AORveh * * *Preiec(^)
ml VACDC VBatt
Where,
AORveh = annual operating VMT (RIA Chapter 2.8.2)
377
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kW^EV = the total per mile energy consumption for a BEV
= converter efficiency, 94%
Vacdc
1
= battery efficiency, 95%
VBatt
Preiec(Xi) = Price of charging, $/kWh, for operating year (OY) where i can be 1 - 10
according to Table 2-93.
The annual hydrogen consumption price on average during operation of the vehicle is
calculated using the operational energy consumption, the operating VMT, and the price of
hydrogen as shown in Equation 2-73 and described in RIA Chapter 2.5.3.1:
Equation 2-73 Annual Hydrogen Consumption Cost
/kWhprpy\
AFPrelec(Yi) = AORveh ^L) * PrH2(OYt)
\ mi /
Where,
AORveh annual operating VMT (RIA Chapter 2.8.2)
kW^EV = the total per mile energy consumption for a FCEV, RIA Chapter 2.8.6.4
PrH2(OFj) = Price of hydrogen, $/kg, for operating year (OY) where i can be 1 - 10
according to Table 2-93.
2.8.8.2 Maintenance and Repair Cost
Maintenance and repair costs are calculated for ICE vehicles, BEVs, and FCEVs. The costs
maintenance and repair for ICE vehicles is calculated annually using Equation 2-74:
Equation 2-74 Annual Maintenance and Repair of ICE Cost
AMRice(Y{) = AORveh(Yi) * (kaOYt + kb)
Where,
OYt = operating year i where i is between 1 and 10
ka = coefficients a, 0.03
kb = coefficients b, 0.11
AORveh = annual operating VMT (RIA Chapter 2.8.2)
378
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Here, coefficients a and b are as described in RIA Chapter 2.3.4.2. These coefficients are
derived from equations found in the 2022 BEAN tool.1243'1244
The maintenance and repair costs of BEVs and FCEVs are scaled from the maintenance and
repair costs of ICE vehicles for the same vehicle type as in Equation 2-75 and Equation 2-76.
Please see RIA Chapters 2.4.4.land 2.5.3.2for more details on the BEV and FCEV scaling
factors, which have been revised for the final rule analysis.
Equation 2-75 Annual Maintenance and Repair of BEV Cost
AMRbev(OYi) = pBEV(OYi)*AMRICE(OYi)
Equation 2-76 Annual Maintenance and Repair of FCEV Cost
MRfcevAMRFcev(.OY{) = Pfcev(.OYi) * AMRICE(OYj)
Where,
((3) can be found in Table 2-94.
Table 2-94 Maintenance and repair scaling factor for BEV and FCEV
Operating Year
Pbfv
Pfcf.v
2027
0.88
1
2028
0.846
1
2029
0.812
1
2030
0.778
1
2031
0.744
0.95
2032
0.71
0.9
2033
0.71
0.85
2034
0.71
0.8
2035
0.71
0.75
2036
0.71
0.75
2037
0.71
0.75
2038
0.71
0.75
2039
0.71
0.75
2040
0.71
0.75
2041
0.71
0.75
2.8.8.3 Insurance Cost
Annual insurance cost (AIC) of the technology is determined using the upfront technology
RPE and an insurance rate (IR) of 3% using Equation 2-77,
Equation 2-77 Annual insurance cost
AIC = CPT * RPE * (1 + IR)
Where,
1243 See "Coef A" and "Coef B" in the "TCO Assumptions" tab.
1244 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
379
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CPT = Powertrain technology costs
RPE = Retail Price Equivalent, 1.42
IR = Insurance Rate, 3%
In the heavy-duty sector, technology adoption rates often follow an S-shape. See RIA Chapter
2.7 above. As discussed there, the adoption rates are initially slow, followed by a rapid adoption
period, then leveling off as the market saturates.1245 Studies have long used payback period to
inform new technology adoption rates.1246
The payback schedule in Table 2-95 for MY 2027 was used to assign the percentage of BEVs
to each of the 101 HD TRUCS vehicle types based on its payback period for MY 2027. For MY
2030 and MY 2032, the payback schedule was applied to both BEVs and select FCEVs. The
discussion on how we determined this schedule based on the TEMPO model is in Chapter 2.7.
Table 2-95 Payback Schedule in HD TRUCS
Payback Bins
MY 2027
MY 2030
MY 2032
<0
20%
37%
70%
0-1
20%
37%
70%
1-2
20%
37%
70%
2-4
20%
26%
39%
4-7
14%
14%
14%
7-10
5%
5%
5%
> 10
0%
0%
0%
2.8.8.4 Percentage of ZEVs in the Technology Packages
The percentage of ZEVs for each vehicle type is then weighted using the MY 2021 sales
volume from MOVES (see RIA 2.2.3) and 2021 sales volume adjusted maximum for that vehicle
type as shown in Equation 2-78.
Equation 2-78 Sales-Weighted Vehicle Percentage
RTA\veh ~ RTAlveh * $veh
Here,
^TAlveh = Vehicle-level adoption %
Sveh = Sales percent of the vehicle
The ZEV adoption values are aggregated into different levels for various calculations. For
example, aggregation is done for both MOVES sourcetypelD and regclassID as well as
1245 See also a similar discussion in the preamble to EPA's Phase 2 HD rule. U.S. Environmental Protection
Agency. 81 FR at 73558 (Oct 25, 2016).
1246 packey Daniel. National Renewable Energy Laboratory. "Market Penetration of New Technologies." February
1993. Available at: https://www.nrel.gov/docs/legosti/old/4860.pdf.
380
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regulatory classes. Generally, the aggregated technical adoption values are calculated using
Equation 2-79.
Equation 2-79 Aggregated Technical Adoption
(Rta)agg
^TA\agg ~
a-gg c
agg
Here,
R'TA\agg = The aggregated adjusted technical adoption rate where the aggregation can be on
any level
Sagg = Aggregated sales value that is aggregated to the same level as (R^agg
2.8.8.5 Battery Demand
We used HD TRUCS and MOVES to estimate the total annual HD vehicle battery demand for
BEVs and FCEVs in MYs 2027 and 2032. For both BEVs and FCEVs, we multiplied sales-
weighted averages of battery sizes for each MOVES SourceTypelD and RegClass ID
combination by MOVES' projected sales for those vehicle types. The battery size is calculated
from the multiplication of the battery size of the vehicle (as described in RIA Chapter 2.8.5.3 for
BEVs and RIA Chapter 2.8.6.3 for FCEVs) and the sales weighted vehicle adoption rates
(Equation 2-78), shown in Equation 2-80.
Equation 2-80 Sales Weighted Battery Size for each MOVES SourceType ID and RegClass ID
, T... 2 kWhpack * RtaIvbH
kWhM0VESID = —
Zj^ta \veh
Here,
kWhM0VES ID = Sales weighted battery size for each MOVES SourceType ID and
RegClassID for each MY
kWhpack= Battery pack size for BEV, Equation 2-26, or FCEV, Equation 2-43
R'TA\veh =sales weighted vehicle adoption rates, Equation 2-78.
To determine the total battery demand in the analysis, the sales weighted battery size for each
MOVES SourceType ID and RegClass ID is multiplied by the sales value for that MOVES
SourceType ID and RegClass ID as shown in Equation 2-81.
Equation 2-81 Annual Battery Demand for each MY in GWh
GWhMY = 77^6 ^ $ moves jd * kWhM0VESJD
Smovesjd = vehicle sales for each MOVES Source TypelD and RegClassID vehicle for each
MY.
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2.9 HD TRUCS Analysis Results
HD TRUCS is a flexible tool that was used to analyze both the operational characteristics and
costs of ZEV technologies that we used to estimate heavy-duty ZEV technologies feasibility and
payback period.1247 Then we translated the payback period, which is the number of years it takes
to offset any incremental cost increase of a ZEV over a comparable ICE vehicle, into projected
potential technology adoption of BEV or FCEV technologies.
2.9.1 HD TRUCS Technology Analysis
As discussed in RIA Chapter2.1, HD TRUCS evaluates the design features needed to meet the
power and energy demands of various HD vehicle types, in this rule, when using ZEV
technologies. Since BEV technology (and, likewise, FCEV technology) may be more suitable for
some applications compared to others, to assess the technical suitability of ZEVs for specific
vehicle applications, we created 101 representative vehicles in HD TRUCS that cover the full
range of weight classes within the scope of the final standards (Class 2b through 8 vocational
vehicles and tractors). The representative vehicles cover many aspects of work performed by the
industry. This work was translated into total energy and power demands per vehicle type based
on everyday use of HD vehicles, ranging from moving goods and people to mixing cement. We
then identified the technical properties required for a BEV or FCEV to meet the operational
needs of a comparable ICE HD vehicle.
Since batteries can add weight and require space for packaging, we evaluated the battery mass
and physical volume impacts of BEV technology. Similarly, we determined the H2 storage tank
volume required for packaging on FCEVs. If the performance needs of a ZEV resulted in a
battery that was too large or heavy, then we did not include the ZEV for that application in our
modeled potential compliance pathway's technology package because of the potential impact on
payload and, thus, potential work accomplished relative to a comparable ICE vehicle. However,
we also show multiple additional example potential compliance pathways (in Chapter 2.11) that
illustrate it is possible to comply with the final standards without ZEVs (e.g., relative to the
reference case), which further supports our conclusion that the final standards can be met—and
can be achieved through a number of compliance strategies— even if certain ZEVs have payload
impacts.
2.9.1.1 BEV Payload Weight Impact
In the case of HD vehicles, battery mass may impact the overall payload available for use.
The payload mass impact is the difference in weight between an ICE powertrain and a BEV
powertrain. The ICE powertrain mass includes weight of the engine including the aftertreatment
system, transmission, fuel, and DEF (see RIA Chapter 2.3.2). The BEV powertrain mass
includes weight of battery, the motor, and the gearbox. The BEV battery weight is converted
from the battery size (in terms of kWh) and the pack-level specific energy of the battery as
discussed in RIA Chapter 2.4.2.1. The BEV motor mass is discussed in Chapter 2.4.1.2. The
BEV gearbox weights are mapped to the BEAN gearbox weight from the " Autonomie Out
1247 We also show multiple additional example potential compliance pathways (in RIA Chapter 2.11) that illustrate it
is possible to comply with the final standards without the use of ZEVs, which further supports our conclusion that
the final standards can be met and can be achieved through a number of compliance strategies.
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Import" tab to the appropriate medium heavy-duty and heavy heavy-duty vehicles in HD
TRUCS by calculating MY 2027 values using linear interpolation of the average of the high- and
low-tech scenarios for 2025 and 2030.1248 Table 2-96 shows the weight differences calculated in
HD TRUCS of a BEV powertrain compared to its ICE counterpart. Negative values in the
Weight Difference column indicate that the BEV vehicle weighs less than the ICE vehicle.
Table 2-96 Weight Difference between BEV and ICE Vehicles in HD TRUCS
Vehicle ID
ICE Powertrain (lbs)
BEV Powertrain (lbs)
Weight Difference (DEV-
ICE) (lbs)
01V Amb C14-5 MP
1738
1593
-145
02V Amb C12b-3 MP
1019
1518
499
03V Amb C14-5 U
1738
1502
-236
04V Amb C12b-3 U
1019
1425
406
05T Box C18 MP
3021
3322
301
06T Box C18 R
3021
3411
390
07T Box C16-7 MP
1937
2237
300
08T Box C16-7 R
1937
2401
464
09T Box C18 U
3021
3237
216
10T Box C16-7 U
1937
2169
232
11T Box C12b-3 U
1019
1375
356
12T Box C12b-3 R
1019
1575
556
13T Box C12b-3 MP
1019
1471
452
14T Box C14-5 U
1738
1375
-363
15T Box C14-5 R
1738
1575
-163
16T Box C14-5 MP
1738
1471
-267
17B Coach C18 R
5076
8405
3329
19C Mix C18 MP
3979
5370
1391
20T Dump C18 U
3021
3754
733
21T Dump C18 MP
3021
3795
774
22T_Dump_C16-7_MP
1937
3444
1507
23 T_Dump_C18_U
3021
3754
733
24T Dump C16-7 U
1937
3246
1309
25T Fire C18 MP
3021
3954
933
26T Fire C18 U
3021
3961
940
27T Flat C16-7 MP
1937
2232
295
28T Flat C16-7 R
1937
2396
459
29T Flat C16-7 U
1937
2087
150
30Tractor DC C18
3979
4730
751
31 Tractor DC C17
3979
4065
86
32Tractor SC C18
3979
11568
7589
33Tractor DC C18
3979
6643
2664
34T_Ref_C18_MP
3885
4498
613
1248 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
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Vehicle ID
ICE Powertrain (lbs)
BEV Powertrain (lbs)
Weight Difference (DEV-
ICE) (lbs)
35T Ref C16-7 MP
1937
3582
1645
36T Ref C18 U
3885
4498
613
37T Ref C16-7 U
1937
3539
1602
38RV C18 R
1937
6772
4835
39RV C16-7 R
1308
7029
5721
40RV C14-5 R
1164
4508
3344
42RV C18 MP
1937
6772
4835
43RV C16-7 MP
1308
6473
5165
44RV C14-5 MP
1164
4154
2990
46B School C18 MP
2665
3459
794
47B School C16-7 MP
2665
2141
-524
48B School C14-5 MP
1182
1593
411
49B School C12b-3 MP
1182
1518
336
50B School C18 U
2665
3303
638
5 IB School C16-7 U
2665
2141
-524
52B School C14-5 U
1182
1502
320
53B School C12b-3 U
1182
1425
243
54Tractor SC C18
3979
13691
9712
55B Shuttle C12b-3 MP
1261
2089
828
56B Shuttle C14-5 U
1738
2024
286
57B Shuttle C12b-3 U
1261
1947
686
58B Shuttle C16-7 MP
2665
3291
626
59B Shuttle C16-7 U
2665
3078
413
60S Plow C16-7 MP
1937
2577
640
61S Plow C18 MP
3021
4997
1976
62 S Plow C16-7 U
1937
2437
500
63 S Plow C18 U
3021
4923
1902
64V Step C16-7 MP
1308
2241
933
65V Step C14-5 MP
1738
1471
-267
66 V_Step_C12b -3MP
1019
1471
452
67 V_Step_C16 -7_U
1308
2096
788
68V Step C14-5 U
1308
1375
67
69V Step C12b-3 U
1019
1375
356
70 S_Sweep_C16 -7_U
2665
2384
-281
71T Tanker C18 R
3021
3608
587
72T Tanker C18 MP
3021
3552
531
73T Tanker C18 U
3021
3537
516
74T Tow C18 R
3021
5206
2185
75T Tow C16-7 R
1937
3704
1767
76T Tow C18 U
3021
5060
2039
77T Tow C16-7 U
1937
3259
1322
78Tractor SC C18
3979
10019
6040
80Tractor DC C18
3979
7948
3969
81 Tractor DC C17
3979
6445
2466
82Tractor DC C18
3979
7944
3965
83 T ractor_DC_C17
3979
5644
1665
384
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Vehicle ID
ICE Powertrain (lbs)
BEV Powertrain (lbs)
Weight Difference (DEV-
ICE) (lbs)
84Tractor DC C18
3979
4750
771
85B Transit C18 MP
2684
5749
3065
86B Transit C16-7 MP
1742
4504
2762
87B Transit C18 U
2684
5749
3065
88B Transit C16-7 U
1742
4156
2414
89T_Utility_C18_MP
3021
3441
420
90T_Utility_C18_R
3021
3513
492
91T Utility C16-7 MP
1937
2411
474
92T Utility C16-7 R
1937
2564
627
93 T_Utility_C14 -5MP
1738
1597
-141
94T_Utility_C12b-3_MP
1709
1529
-180
95T Utility C14-5 R
1738
1689
-49
96T Utility C12b-3 R
1709
1689
-20
97T_Utility_C18_U
3021
3392
371
98T_Utility_C16-7_U
1937
2292
355
99T Utility C14-5 U
1738
1521
-217
100T Utility C12b-3 U
1709
1442
-267
10 lTractor_DC_C18
2284
3893
1609
In the NPRM version of HD TRUCS, we calculated the payload impact1249 based on the
standard payload used to demonstrate compliance with Phase 2 (see 40 CFR 1037.801), and we
used a 30% payload threshold to exclude a BEV from consideration. Based on consideration of
the comments received, for the final rule we are not using a 30 percent payload reduction as a
metric for determining BEV suitability. Instead, we assess specific applications in HD TRUCS
on an individual basis and determine the suitability of each application for BEVs based on the
payload difference between comparable ICE vehicles and BEVs. This change was made for two
reasons: (1) the Phase 2 payloads do not reflect the full payload that is available for most
vehicles; and (2) we received persuasive comment on the effect of payload on individual vehicle
applications and have concluded that it is more appropriate to assess each of these applications,
and the included HD TRUCS vehicles, on a case-by-case basis. The applications mentioned in
comments that require additional specific assessment of payload impact are the concrete mixer,
dump truck, tanker, coach buses, and tractor applications.
Several manufacturers and associations raised issues concerning ability of cement pumpers
and mixers to achieve emission standards predicated on electrification. Before discussing
specifics, EPA notes that two issues are presented: whether application of these technologies
should be considered for these vehicles in setting the emission standard for the subcategory of
which they are a part (HHD vocational vehicle), and whether we should consider application of
these technologies in determining whether to set new optional custom chassis standards for
concrete mixers and for mixed-use vehicles. Our disposition of these issues is that it is
appropriate to include consideration of these technologies and performance of cement mixers in
1249 In the NPRM, the impact on payload calculated as the delta between the weight of the BEV powertrain
components and the weight of the ICE powertrain components divided by the payload used to determine compliance
with the HD GHG Phase 1 and Phase 2 vehicle CO2 emission standards, which is less than the maximum payload
capacity of the vehicle.
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developing the potential compliance pathway's technology packages for HHD vocational vehicle
standards, but that we are not going to revise or set new Phase 3 optional custom chassis
standards for concrete mixers and for mixed-use vehicles, for the reasons explained in this
section.
Certain commenters maintained that energy used by concrete mixers and pumpers is
significantly higher than what is represented in GEM and suggested that the load and energy
inputs for these vehicles in HD TRUCS is unrepresentative such that these vehicles in fact would
need more energy, larger batteries, and incur higher costs than EPA projected at proposal. These
comments are persuasive. For the final rule, EPA obtained data based on information provided
by one commenter which show significantly larger power demands (and hence battery sizes)
than EPA considered at proposal. As a result, EPA determined that EPA's optional custom
chassis standards for Concrete Mixers/Pumpers and Mixed-Use Vehicles will remain unchanged
from the Phase 2 MY 2027+ CO2 emission standards.
There were other comments, however, that some electrified concrete mixers and pumpers
presently exist, at least as prototypes in Europe. This suggests that these vehicles - represented in
HD TRUCS as vehicle 19C_Mix_C18_MP - could be considered for utilization of ZEV
technologies in the HD TRUCS analysis for the HHD vocational vehicle subcategory. To that
end, EPA investigates if there are payload constraints that would make such inclusion
inappropriate.1250 The HD TRUCS concrete mixer has a BEV powertrain weighing 1391 pounds
more than the comparable ICE powertrain. Although this is 9.3% of the Phase 2 payload (15,000
pounds used in HD TRUCS), a mixer user desiring a full load would see an impact of 3.5% as
the full payload is 40,000 pounds.1251 Since a cubic yard of concrete weighs about 4,000 pounds,
the mixer maximum load (by volume) would reduce from 10 cubic yards to 9.65 cubic yards.
This minor payload impact would not be a limiting factor for adoption rates of 39% at 2032, and
therefore we are continuing to include this vehicle in the HD TRUCS analysis, and
correspondingly the technology packages used in the modeled potential compliance pathway for
HHD vocational vehicles.1252
Many of the BEV powertrains weigh more than their ICE comparator with a significant
contribution coming from the battery size. Battery chemistry impacts the battery pack specific
energy and battery technology continues to evolve suggesting that battery pack weight may
decrease and payload increase. To assess the sensitivity of payload to higher specific energy,
EPA reviewed two additional scenarios 1) use of NiMn batteries (HD TRUCS uses a value that
represents a 50/50 mix of NiMn and LFP to align with battery cost assumptions) and 2) possible
NiMn battery pack specific energy improvements through 2030. Per ANL/DOE, NiMn pack
specific energy in 2027 is 226 Wh/kg and the same pack in 2030 is 248 Wh/kg. If NiMn battery
chemistry with the specific energy increasing to 226 Wh/kg is applied to concrete mixer
1250 Landgraf, Michael. Memorandum to Docket EPA-HQ-OAR-2022-0985. "HD GHG Phase 3 Rule BEV Payload
Analysis" February 26, 2024.
1251 Gerges, Rafik. "How Full Can Concrete Trucks be when Driving on Slabs-on-Grade?". Structure Magazine.
January 2017. Available online:
https://www.structuremag.org/?p=10927#:~:text=A%20typical%20fully%201oaded%20truck,of%20concrete%20ad
ds%204%2C000%20pounds.
1252 According to the CARB Large Entity Fleet Report, 54% of vocational vehicles do not weigh out in operation.
CARB. Large Entity Fleet Reporting. Page 22. Available online: https://ww2.arb.ca.gov/sites/default/files/2022-
02/Large_Entity _Reporting_Aggregated_Data_ADA.pdf.
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19C_Mix_C18_MP, the payload loss is 2.0 percent. If battery improvements over time are
realized as ANL predicts, the NiMn battery specific energy increases to 248 Wh/kg and the
payload reduction drops to 1.1 percent. This battery pack specific energy sensitivity was
evaluated for most applications that have a payload reduction due to BEV powertrain weight.
We also received comments about the potential for payload weight impacts on dump trucks.
HD TRUCS has five dump truck vehicles; 20T_Dump_C18_U, 21T_Dump_C18_MP,
22T_Dump_C16-7_MP, 23T_Dump_C18_U, and 24T_Dump_C16-7_U. The Class 8 dump trucks
have an HD TRUCS GEM payload of 15,000 pounds and a corresponding loss due to the BEV
powertrain of 4.9 to 5.2 percent. Since the maximum payload can be 30,000 lbs (Example: 10
cubic yards of rock or sand at 3,000 lbs/yd) the payload impact is 2.6 percent such that the
payload weight impact would not be an impediment towards achieving the adoption rates in the
modeled potential compliance pathway. Additionally, the battery specific energy improvements
of chemistry (226 Wh/kg) and chemistry plus improvements at 2030 (248 Wh/kg) take the
payload loss to 1.3 percent and then 0.4 percent. We therefore are retaining these vehicles in the
HD TRUCS analysis, and correspondingly in the technology packages used in the modeled
potential compliance pathway. Indeed, the 10 cubic yard volume assumption is conservative as
dump bodies (for public roads) can reach 34.6 cubic yards.1253 Vehicles 22T_Dump_C16-7_MP
and 24T_Dump_C16-7_U are Class 6-7. Applying the Class 8 ratio of peak load to GEM load
(with the rationale that a dump truck would deliver a full load and return empty such that GEM
load is logically V2 of maximum load) gives a maximum payload of 22,400 lbs as these Class 6-7
dump trucks have a GEM payload of 11,200 lb. The Class 6-7 dump trucks have a maximum
payload degradation of 6.7 percent and 5.8 percent. Applying the aforementioned specific energy
improvements of 226 Wh/kg results in payload loss of 5.0 and 4.0 percent instead of 6.7 and 5.8
percent. The 248 Wh/kg battery specification drops the payload loss to 4.0 and 3.2 percent.
While not negligible, the payload reduction is small enough that there are no payload constraints
which would disqualify these vehicles from being retained in HD TRUCS or the corresponding
technology packages for Class 6-7 vocational vehicles (note, the projected adoption rates in our
HD TRUCS analysis for the two Class 6-7 vocational vehicles is 5 percent and 14 percent in
2027 and 2032).
The tanker trucks, 71T_Tanker_C18_R, 72T_Tanker_C18_MP, and 73T_Tanker_C18_U, have
a weight impact from their BEV powertrain of 516 to 587 pounds which is a small percentage
(3.4 percent to 3.9 percent) of their GEM payload weight. Increasing the payload to a more
realistic 30,000 pounds1254 gives a payload loss of 1.7 to 2.0 percent. This small weight
disadvantage supports our assumed 2032 adoption rates (14 to 70 percent) are supported by the
specific energy opportunities. Applying the specific energy improvement of 226 Wh/kg results in
payload loss of 215 pounds (0.7 percent), and if NiMn battery pack specific energy continues to
improve as projected by ANL/DOE, there will be no payload loss for vehicles produced in MY
2030.
We have carefully examined whether there are payload constraints for each of the tractors in
our analysis and have concluded that it is appropriate for most of them to remain in our HD
1253 Municibid. "How to Calculate Dump Truck Capacity". Last updated June 14, 2023. Available online:
https://blog.municibid.com/calculate-dump-truck-capacity/
1254 Clean Management Environmental Group. "Tankers". Accessed February 20, 2024. Available online:
https://cleanmanagement.com/service/tankers/.
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TRUCS analysis and the corresponding technology packages for our modeled potential
compliance pathway. Our explanation follows.
A tractor typically weighs up to 25,000 pounds and an empty 53 foot box trailer can add
another 10,000 pounds, leaving 45,000 pounds of cargo capacity for a Class 8 tractor-trailer
maxed out at 80,000 lbs GCWR.1255 Applying the HD TRUCS payload impact to this Class 8
maximum payload of 45,000 lbs shows six vehicles (HD TRUCS Tractors 30Tractor_DC_C18,
33Tractor DC Cl8, 80Tractor_DC_C18_HH, 82Tractor_DC_C18, 84Tractor_DC_C18, and
101Tractor_DC_C18) have less than a 9 percent payload loss. In fact, 80Tractor_DC_C18_HH is
a heavy-haul tractor, so its payload can be higher and the percent of payload loss even less.
Class 8 BEV are allowed to operate at a GCWR of 82,000 pounds thus adding 2,000 pounds of
payload.1256 This allowance drives tractors like 30Tractor_DC_C18, 84Tractor_DC_C18, and
101Tractor_DC_C18 to have no payload loss while the worst-case payload loss of 3965 pounds
(82Tractor_DC_C18) is cut in half. When the battery specific energy improvements are applied
(taking specific energy to 248 Wh/kg) the worst two of these tractors lose just over 2500 pounds
which is 5.6%. When the 2,000 pound payload allowance is then applied, 4 of these tractors
have no payload loss and two have a payload reduction of just over 500 pounds or 1.1 percent.
Class 8 tractors 32Tractor_SC_C18 and 78Tractor_SC_C18 have larger payload impacts
(assuming 45,000 lbs payload): 16.9 percent and 13.4 percent respectively. With a battery
specific energy increase to 248 Wh/kg, the payload loss drops to 12.0 and 9.3 percent. When the
2,000-pound payload allowance is applied the loss is 7.6 and 4.8 percent. In considering whether
these payload losses should justify exclusion of these vehicles from the tractor technology
package, we evaluated typical cargo types in relation to payload capacity.1257 Some tractors
consistently haul heavy loads (assumed here as 90-100 percent of maximum load) while others
haul different product with each trip and must be capable of maximum or nearly maximum load
for those occasions when the product requires high payload capacity. EPA's review of Federal
Highway Administration data, and more specifically, commodity data per the 2002 Vehicle
Inventory and Use Survey (VIUS), show that 15 of 43 commodities covered had average loads at
or within 10 percent of maximum load.1258 Twenty four percent of the total tractor ton-miles
reflect delivery of this group of commodities. Using this same approach, 14 commodities had
average loads at 80 percent to 90 percent of maximum and accounted for 20 percent of ton-miles.
Also 6 commodities had average loads that were 70 percent to 80 percent of maximum and
accounted for 35 percent of ton miles. Some commodities may always or occasionally need
maximum load capability, in which case a BEV may not be a suitable application. Other
commodities such as Meat, Fish and Seafood, Precision Instruments, Machinery, Tobacco,
Alcohol, Pharmaceuticals, Milled Grain, Textiles, Furniture, Mail, Other Foodstuffs will have
consistent loads that are 10 percent to 30 percent below maximum. There is no payload capacity
1255 Hawley, Dustin. "How Much Does a Semi Truck Weigh". J.D. Power February 04, 2021. Available Online:
https://www.jdpower.com/cars/shopping-guides/how-much-does-a-semi-truck-
weigh#:~:text=The%20unladen%20weight%20of%20a,weight%20of%20about%2035%2C000%20pounds.
1256 See Consolidated Appropriations Act of 2019, at § 2, div. G, title 4, Pub. L. 116-6, 133 Stat. 13, 474 (Feb. 15,
2019) (codified at 23 U.S.C. § 127(s)).
1257 Landgraf, Michael. Memorandum to docket EPA-HQ-OAR-2022-0985. "HD GHG Phase 3 Rule BEV Payload
Analysis". February 26, 2024.
1258 Federal Highway Administration (FHWA) Office of Operations (HOP). "Research, Development, and
Application of Methods to Update Freight Analysis Framework Out-of-Scope Commodity Flow Data and Truck
Payload Factors". Available online: https://ops.fhwa.dot.gov/publications/fhwahop20011/chapl2.htm.
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loss associated with carriage of these commodities by Class 8 BEV tractors. We consequently
are not excluding these tractors from the tractor technology packages, and, moreover, we see
these data as supporting the modest adoption rates in our technology package for long haul
tractors. Put another way, our modeled compliance pathway projects most of these vehicles
remain ICE vehicles during the time frame of the Phase 3 rule which can accommodate those
commodities for which maximum loads are needed, and (as shown by the VMT data) BEVs
remain a viable alternative for other commodities.
BEV 54Tractor_SC_C18, a Class 8 sleeper cab has the highest payload impact of all the
tractors at 9,712 pounds which is 22 percent of the 45,000-pound maximum payload. Due to the
higher payload impact, we are not considering this tractor as part of the tractor technology
package for the modeled potential compliance pathway.
Class 7 tractor 3 lTractor_DC_C16-7 has no payload loss due to its BEV powertrain weight.
BEV Class 7 tractors (81Tractor_DC_C17 and 83Tractor_DC_C17) are at a payload loss of 6.7
and 9.9 percent. Turning again to VIUS data, a significant distribution exists across commodities
aligned with Class 7 tractor use. While some users will need maximum payload (taken here as
the 25,000 lbs GEM weight) other Class 7 tractors are suitable for commodities not requiring
maximum load. Examples are Animal Feed, Pulp, Electronic and Electrical Equipment, Plastics
and Rubber, and Fertilizers. These have average loads that range from 23 percent to 55 percent
lower than the 25,000 lbs GEM payload. The ability of these commodities to use BEV Class 7
tractors confirms that the HD TRUCS analysis projected adoptions rates are viable. With a pack
specific energy of 248 Wh/kg, the payload loss reduces to 2.5 percent and 5.1 percent. This
value of payload loss supports the projected adoption rates.
Coach and Transit buses (17B_Coach_C18_R, 85B_Transit_C18_MP, 86B_Transit_C16-
7_MP, 87B_Transit_C18_U, 88B_Transit_C16-7_U) see a payload impact of 20.4 to 24.7
percent. Payload loss with the 248 Wh/kg battery pack drops to 11.6 to 17.2 percent.
The remaining trucks with a 10-20 percent reduction in payload are 35T_Ref_C16-7_MP,
37T_Ref_C16-7_U, 55B_Shuttle_C12b-3_MP, 57B_Shuttle_C12b-3_U, 61S_Plow_C18_MP,
63 S_Plow_C18_U, 74T_Tow_C18_R, 75T_Tow_C16-7_R, 76T_Tow_C18_U, 77T_Tow_C16-
7_U. The range in payload loss is 11.8 percent (77T_Tow_C16-7_U) to 15.8 percent
(75T_Tow_C16-7_R). The payload loss for these trucks with the higher (248 Wh/kg) battery
pack is 6.6 to 9.8 percent. Of the 101 vehicle types in HD TRUCS, 15 have no payload loss and
54 have a 0 to 10 percent payload loss (some of which were in areas of specific interest and
discussed above).
As proposed, we are not setting new optional custom chassis standards for motor homes after
consideration of the projected impact of applying such technologies, including the weight of
batteries in BEVs in the MYs 2027-2032. The HD TRUCS evaluation of RVs demonstrates that
it is unlikely that ZEV technology will pay back for RVs that typically travel low annual miles
(as they are modeled in HD TRUCS) and are expected to travel long distances in a day over a
small number of annual operational days. Consistent with the concrete mixer in HD TRUCS, we
are reflecting the adoption rate (which are 0 percent for RVs) in the corresponding vocational
vehicle standards.
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2.9.1.2 BEV and FCEV Payload Volume Impact
Like battery weight, the physical volume required to package a battery pack can also be
challenging to integrate onto a HD vehicle. The pack-level energy density (370 Wh/L) is used to
convert the battery size in terms of kWh into the volume of the battery. For the proposal, we had
calculated the width of the physical battery using the volume, wheelbase, and 110% of the frame
rail height. If the battery width was less than 8.5 feet, we projected that the battery would
package on each vehicle. We received comments on this approach and realized there were
aspects we had not considered in our analysis, including space for tires and the width of each
frame rail. Based on consideration of comments received, we updated our approach to factor
battery volume into our analysis for BEVs. Comments and our responses for battery volume are
available in Section 3.10.3 of the RTC.
For the final rule we have taken an approach where we compare the volume of each battery
with comparable current BEVs in the market today and base our analysis on this information. In
our analysis, we found that of the 101 vehicles that we are considering as BEVs, 3 vehicles had
batteries that were greater than 15% larger than a comparable battery in a current BEV and 5
vehicles (including the 3 with batteries greater than 15% increase in battery size) had batteries
that were 10% larger than comparable current BEVs.1259 Of the vehicles that had a 10% greater
battery size than current BEVs, one is a coach bus being considered as a fuel cell vehicle (see the
following discussion in this subsection), two are sleeper cab tractors (32Tractor_SC_C18,
54Tractor_SC_C18, one is a shuttle bus (56B_Shuttle_C14-5_U), and one is a transit bus
(86B_Transit_C16-7_MP).
The shuttle bus (56B_Shuttle_C14-5_U) has a battery size of 158 kWh in HD TRUCS and a
comparable BEV has a battery size of 141 kWh. We considered this difference negligible and
that shuttle buses should not be limited by battery volume in our analysis.
The transit bus (86B_Transit_C16-7_MP) has a battery size of 373 kWh in HD TRUCS and a
comparable BEV has a battery size of 320 kWh. Even though this represents a 16 percent larger
battery for this vehicle type in HD TRUCS, we did not consider the difference to limit the battery
volume in our analysis. We made this determination based on comparisons to class 8 transit
buses which are a similarly sized vehicle, but with much larger batteries, going up to 738 kWh.
The tractor 32Tractor_SC_C18 battery size in HD TRUCS is 973 kWh and the current
comparable BEV has a battery size of 850 kWh. Even though the capacity of the battery of this
vehicle is about 14 percent larger than the current comparable BEV, the battery volume of 2.46
cubic meters is about 18 percent smaller than the battery in the comparable BEV of 3.0 cubic
meters.1260 Since the physical size of the battery for 32Tractor_SC_C18 is smaller than the
comparable current BEV, this vehicle is not limited by battery volume in our analysis.
The last vehicle with a battery larger than a comparable current BEV is 54Tractor_SC_C18,
which has a battery size of 1,164 kWh in HD TRUCS and the comparable current BEV has a
battery size of 850 kWh, an increase of 37% in battery size. The comparable current BEV in this
instance is the Tesla Semi which has a battery volume of 3 cubic meters which is larger than the
1259 Miller, Neil. See Memorandum to docket EPA-HQ-OAR-2022 0985. BEV Battery Packaging Analysis. March
3, 2024.
1260 Battery Design. 2022 Tesla Semi Specifications. Available online: https://www.batterydesign.net/2022-tesla-
semi-specifications/.
390
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battery volume calculated in HD TRUCS for this vehicle which has 2.94 cubic meters.1261 The
wheelbase of vehicle 54 in HD TRUCS is 143 inches while a typical tractor has a wheelbase
between 245 and 265 inches and the Tesla Semi is cited with a wheelbase of 156 inches. 1262>1263
By allowing the wheelbase of vehicle 54 to increase from 143 inches, the battery volume of 2.94
cubic meters would be able to package on a sleeper cab semi with the same wheelbase as a Tesla
Semi and therefore battery volume will not be a constraint for this vehicle. That said, we have
determined that this vehicle would not be included within the technology package to support the
potential compliance pathway due to our current assessment of potential near-term weight impact
of the battery (see previous subsection).
Since hydrogen tanks take up considerable space, even at pressures up to 700 bar (just over
10,000 psi), we also assessed FCEV hydrogen tank packaging for tractors and specifically Class
8 sleeper cab tractors like vehicle 79Tractor_SC_C18. Due to having few HD FCEV vehicles in
production, we relied on the FEV study to provide guidance on how HD FCEV may store and
package hydrogen.1264 FEV's analysis showed that six tanks, each with 12.8 kg of hydrogen
(10.7 kg useable) at 700 bar, could fit on a wheelbase of 265 inches with a sleeper cab. In HD
trucks, we set the FCEV sleeper cab tractor sizing VMT at 420 miles, the same as the operational
VMT. The 43.6 kg of hydrogen needed for this range (according to HD TRUCS) is well below
what FEV identified as feasible with their packaging study. See RTC Section 5.3 and RIA
Chapter 1.7.3 for additional detail.
Several stakeholders raised significant concerns related to the ability of motorcoaches
(referred to as coach buses in 40 CFR 1037.105(h) and in HD TRUCS) to perform their mission
(transporting people and their luggage) using battery electric technology. Furthermore,
commenters raised concerns regarding the infrastructure needs for electrified motorcoaches
because these vehicles would need to rely on public enroute charging.
As described in Chapter 2.2.1.2, there are some existing BEV coach buses; however, these
buses include less underfloor storage volume than comparable coach buses in the market today.
As mentioned above, HD TRUCS includes both a BEV and FCEV coach bus. EPA contracted
FEV to conduct an analysis of the packaging feasibility of a FCEV powertrain on a coach
bus.1265 FEV found that a FCEV powertrain would require the loss of 2-4 seats and 30% of the
luggage volume. The capacity loss was driven by the space needed for the hydrogen tanks, fuel
cell with BOP, and batteries. FEV did not conduct analysis of a BEV coach bus as the BEV
powertrain size and weight (and capacity loss) were greater than the FCEV.
Due to our consideration of the potential concerns raised in comment and through our
analyses, EPA's optional custom chassis standards for Coach Buses will remain unchanged from
the Phase 2 MY 2027 CO2 emission standards. Consistent with the concrete mixers and RVs in
HD TRUCS, we are reflecting the adoption rate in the corresponding primary vocational
1261 Battery Design. 2022 Tesla Semi Specifications. Available online: https://www.battervdesign.net/2022-tesla-
semi-specifications/.
1262 Carabin Shaw. Facts About 18 Wheelers. Available online: https://www.carabinshaw.com/facts-about-18-
wheelers.html.
1263 Dimensions. Tesla Semi. Available online: https://www.dimensions.com/element/tesla-semi
1264 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
1265 FEV Consulting. "Heavy Duty Commercial Vehicles Class 4 to 8: Technology and Cost Evaluation for
Electrified Powertrains—Final Report". Prepared for EPA. March 2024.
391
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standards; however, we limited the adoption rate of each coach bus to 14 percent in MY 2030
and 2032, due to potential impact on seat space and luggage capacity for ZEV coach buses.
2.9.1.3 Other Constraints
One commenter stated that utility vehicles may periodically have higher performance
demands than typical daily operation, in particular, due to the need for their extensive use after
weather events cause power outages. We agree and have consequently increased the sizing VMT
of utility vehicles with a regional application (see Chapter 2.2.1.2) and limited the ZEV adoption
rates of the regional utility HD TRUCS vehicle types in our HD TRUCS analysis and
corresponding technology packages. Specifically, in HD TRUCS, vehicles 90T_Utility_C18_R,
92T_Utility_C16-7_R, 95T_Utility_C14-5_R, and 96T_Utility_C12b-3_R were assigned zero
adoption in MY 2027 and capped at 14 percent ZEV adoption in MY 2030 and 2032. We chose
to use the regional utility vehicles because they have higher daily VMT than the urban and
multipurpose vocational vehicles and are therefore the most likely candidates for extensive use.
While there is not a regulatory subcategory that applies exclusively to utility vehicles, this has
the effect of lowering the overall utilization of ZEV technologies in our analysis for LHD and
MHD vocational vehicles.
2.9.2 Payback
As explained in Chapter 2.8 above, after assessing the suitability of the technology and costs
associated with ZEVs, EPA performed a payback calculation on each of the 101 HD TRUCS
vehicles for the BEV technology and FCEV technology that we were considering for the
technology packages for each use case for each MY in the MY 2027-2032 timeframe. The
payback period was calculated by determining the number of years that it will take for the annual
operational savings of a ZEV to offset the incremental upfront purchase price of a BEV or
FCEV. For the NPRM, the upfront costs included the RPE multiplier of 1.42 discussed in RIA
Chapter 3, accounted for the IRA section 13502 battery tax credit and IRA section 13403 vehicle
tax credit as described in Chapters 2.4.3.land 2.4.3.5, respectively, and included the charging
infrastructure costs for depot-charged BEVs. The operating costs in the NPRM included the
diesel, hydrogen, or charging costs, DEF costs, along with the maintenance and repair costs. The
payback calculation in the NPRM was performed using a 10-year average of operational costs
and compared to the incremental upfront cost of ICE vehicle and ZEV.
As explained in Chapter 2.8.8, in the final rule analysis, EPA made several changes when
calculating the payback period for each of the 101 vehicles. Upfront cost includes the component
technology costs and the associated battery tax credits and vehicle tax credits, the EVSE for
depot-charged BEVs and an updated approach to accounting for associated EVSE tax credits,
and now also accounts for the state sales tax and (as applicable) the Federal Excise tax.
Operational costs in the final rule include the fuel costs and maintenance and repair costs
considered in the NPRM (with updates to phase in the M&R scaling factor), along with the
addition of the annual insurance cost and an annual ZEV registration fee. Lastly, the operational
costs were determined on an annual basis for the final rule, instead of using a 10-year average.
The addition of State Sales Tax and Federal Excise Tax to upfront costs are simple additions
to the technology costs. The reason for the last change in payback calculation method is because
of the changes to how operational costs are computed in the analysis. As described in Chapter
2.2.1.2, operational VMT changes with the age of the vehicle based on the sourceType ID
392
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provided in MOVES. This change in VMT yields changing operational fuel costs as described in
Chapters 2.3.4.3, 2.4.4.2 and 2.5.3.1, as well as changing M&R costs as described in Chapters
2.3.4.2, 2.4.4.1, and 2.5.3.2. In this modification, total fuel costs not only change with annual
VMT but with the fuel price for that particular calendar year as well. Likewise, the M&R scaling
factor also changed with the calendar year. Therefore, it became more appropriate to account for
annual operating costs and to subtract those costs from the initial upfront costs. So, payback
period in the final rule analysis is the number of years when the cumulative operating cost
savings from purchasing a ZEV is equal to the initial upfront cost delta when compared to the
comparable ICE vehicle. As in the NPRM, payback period typically occurs during some
fractional part of a year. EPA defined the payback period as the first year where the cumulative
operational cost savings for the purchase of a ZEV is greater than the initial additional upfront
cost delta of the ZEV.
The payback results are shown in Table 2-97 and Table 2-98 for BEVs for MY 2027, MY
2030 and MY 2032, and in Table 2-100 for FCEVs for MY 2030 and MY 2032. The upfront
costs include the incremental RPE cost difference between a ZEV powertrain (PT) and an ICE
powertrain, plus the EVSE RPE, minus the applicable IRA vehicle tax credit. As discussed
above and in RIA Chapter 2.2.1.1.3, for the final rule version of HD TRUCS, we have assessed
each year of operation using the appropriate changes that occur over time for inputs such as
VMT, maintenance and repair, and fuel costs; however, we are continuing to show a 10-year
average operational costs value in tables such as those below, as a single value point of
comparison. Appendix A includes each year of a 10-year schedule for VMT. Note that not all of
the BEVs shown in these tables are included in the technology packages to support the final rule
standards. We have only included BEVs that pay back in 10 years or less in our technology
packages.
Table 2-97 Results of the BEV Payback Analysis for MY 20271266 (2022$)
ICE PT
RPE +
BEVPT
RPE +
EVSE RPE
($/unit)
IRA
Vehicle Tax
Credit
($/unit)
Average
Annual
Average
Annual
BEV
Vehicle ID
Sales Tax
Sales Tax
ICE
BEV
Payback
and FET
($/unit)
and FET
($/unit)
Operating
($/year)
Operating
($/year)
(years)
01V Amb C14-5 MP
45669
40544
13932
0
5885
3832
5
02V Amb C12b-3 MP
43602
39412
6966
0
8080
4887
2
03V Amb C14-5 U
45669
39245
13932
0
7049
4101
3
04V Amb C12b-3 U
43602
38074
13932
0
7091
4045
3
05T Box C18 MP
96937
77955
26007
0
15697
9296
2
06T Box C18 R
96937
79380
52014
0
14328
9313
7
07T Box C16-7 MP
48973
51018
13932
1947
8237
5099
5
08T Box C16-7 R
48973
53367
13932
4184
7963
5240
6
09T Box C18 U
85684
76608
52014
0
17657
9128
5
10T Box C16-7 U
48973
50044
13932
1020
8515
4847
4
11T Box C12b-3 U
42894
37433
6966
0
9949
5363
1
12T Box C12b-3 R
42894
40286
13932
0
9128
5728
4
13T Box C12b-3 MP
42894
38796
6966
0
9434
5537
1
14T Box C14-5 U
43040
37433
13932
0
6831
3862
3
15T Box C14-5 R
43040
40286
13932
0
6304
4126
6
1266 Since our assessment of publicly-charged BEVs begins in MY 2030, there is no payback year listed for MY
2027 in Table 2-97 for those vehicles.
393
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ICE PT
RPI +
BEVPT
RPE +
EVSE RPE
($/unit)
IRA
Vehicle Tax
Credit
($/unit)
Average
Annual
Average
Annual
BEV
Vehicle ID
Sales Tax
Sales Tax
ICE
BEV
Payback
and FET
($/unit)
and FET
($/unit)
Operating
($/year)
Operating
($/year)
(years)
16T Box C14-5 MP
43040
38796
6966
0
6500
3988
2
17B Coach C18 R
76281
157812
0
40000
31328
26704
NA
19C Mix C18 MP
85684
110590
52014
21283
35181
17068
3
20T Dump C18 U
96937
84845
52014
0
13093
6750
7
21T Dump C18 MP
96937
85493
26007
0
11489
6802
4
22T Dump C16-7 MP
48698
68212
26007
18581
12150
7187
6
23T Dump C18 U
85684
84845
52014
0
12804
6750
9
24T Dump C16-7 U
48698
65386
52014
15891
12907
6935
9
25T Fire C18 MP
96937
88024
52014
0
12376
7004
8
26T Fire C18 U
85684
88136
52014
2095
13905
7013
8
27T Flat C16-7 MP
48698
50871
13932
2070
8229
5095
5
28T Flat C16-7 R
48698
53220
26007
4306
8106
5319
10
29T Flat C16-7 U
48698
48804
13932
101
8686
4898
4
30Tractor DC C18
102128
106686
42148
3895
19331
13388
8
31 Tractor DC C17
80312
91530
31611
9587
17384
11941
6
32Tractor SC C18
105942
214205
0
40000
72143
60467
NA
33Tractor DC C18
81291
135847
0
40000
39247
31864
NA
34T Ref C18 MP
80656
95977
52014
13093
19825
9158
5
35T Ref C16-7 MP
48698
70184
52014
20459
23648
12579
5
36T Ref C18 U
80656
95977
52014
13093
19825
9158
5
37T Ref C16-7 U
48698
69574
52014
19878
25333
12479
5
38RV C18 R
56701
131782
13932
40000
3450
4545
>15*
39RV C16-7 R
48821
119775
13932
40000
3416
4622
>15*
40RV C14-5 R
42131
82238
13932
38190
2806
3344
>15*
42RV C18 MP
56701
131782
13932
40000
3450
4545
>15*
43RV C16-7 MP
48821
111830
13932
40000
3453
4348
>15*
44RV C14-5 MP
42131
77170
13932
33364
2867
3170
>15*
46B School C18 MP
56701
78984
26007
19042
10885
7546
9
47B School C16-7 MP
48821
49863
13932
992
10646
5884
4
48B School C14-5 MP
42131
40544
6966
0
7730
4840
3
49B School C12b-3 MP
44153
39612
6966
0
7788
4730
1
50B School C18 U
56701
76489
13932
16910
12485
7306
4
5 IB School C16-7 U
48821
49863
13932
992
10646
5884
4
52B School C14-5 U
42131
39245
6966
0
8138
4701
2
53B School C12b-3 U
44153
38274
6966
0
8196
4586
1
54Tractor SC C18
105942
248045
0
40000
72143
68463
NA
55B Shuttle C12b-3 MP
44153
47777
13932
3451
17267
9938
3
56B Shuttle C14-5 U
42131
46711
13932
4361
18210
9787
2
57B Shuttle C12b-3 U
44153
45740
13932
1511
18267
9618
2
58B Shuttle C16-7 MP
48821
66312
26007
16655
21236
12509
4
59B Shuttle C16-7 U
48821
63275
52014
13763
22555
12031
6
60S Plow C16-7 MP
48698
55818
13932
6780
9024
5356
4
61S Plow C18 MP
96937
104658
52014
6598
12444
7717
12*
62 S Plow C16-7 U
48698
53811
26007
4869
9561
5178
6
63 S Plow C18 U
85684
103476
52014
15204
13929
7637
9
64V Step C16-7 MP
48594
50965
13932
2258
11839
6968
4
65V Step C14-5 MP
42131
38796
6966
0
6474
3988
2
66V Step C12b-3 MP
43602
38729
6966
0
9265
5434
1
67V Step C16-7 U
48594
48882
13932
274
12537
6698
3
394
-------
ICE PT
RPE +
BEVPT
RPE +
EVSE RPE
($/unit)
IRA
Vehicle Tax
Credit
($/unit)
Average
Annual
Average
Annual
BEV
Vehicle ID
Sales Tax
Sales Tax
ICE
BEV
Payback
and FET
($/unit)
and FET
($/unit)
Operating
($/year)
Operating
($/year)
(years)
68V Step C14-5 U
42131
37433
13932
0
6805
3862
4
69V Step C12b-3 U
43602
37366
13932
0
9770
5262
2
70S Sweep C16-7 U
48698
53055
13932
4149
12183
6280
3
7IT Tanker C18 R
96937
82514
52014
0
13090
8197
8
72T Tanker C18 MP
85684
81629
26007
0
13812
8105
4
73T Tanker C18 U
85684
81384
52014
0
15880
8080
6
74T Tow C18 R
99968
107988
52014
6854
15798
10236
10
75T Tow C16-7 R
48698
71929
52014
22121
11928
7494
14*
76T Tow C18 U
85684
105650
52014
17062
19275
10032
6
77T Tow C16-7 U
48698
65566
52014
16062
12887
6930
9
78Tractor SC C18
105942
189518
0
40000
52307
49346
NA
80Tractor DC C18
107145
156714
47704
40000
26905
18970
8
81 Tractor DC C17
80312
129470
0
40000
36123
31698
NA
82Tractor DC C18
105943
158615
0
40000
39872
36204
NA
83Tractor DC C17
80312
116699
42148
31095
21064
14828
8
84Tractor DC C18
99430
106496
0
6039
23224
20762
NA
85B Transit C18 MP
76281
115477
63222
33496
33123
17183
5
86B Transit C16-7 MP
48821
83670
52014
33183
14894
9518
10
87B Transit C18 U
75366
115477
63222
34277
33100
17183
5
88B Transit C16-7 U
48821
78684
52014
28435
15791
9078
8
89T Utility C18 MP
96937
79855
26007
0
8493
5134
3
90T Utility C18 R
96937
81001
52014
0
7971
5210
15*
9IT Utility C16-7 MP
48698
53438
13932
4514
10814
6212
4
92T Utility C16-7 R
48698
55633
26007
6603
10635
6456
7
93T Utility C14-5 MP
45669
40604
13932
0
8800
4998
3
94T Utility C12b-3 MP
43602
39557
13932
0
4676
2904
6
95T Utility C14-5 R
45669
41920
13932
0
8337
5056
4
96T Utility C12b-3 R
43602
41854
13932
0
8278
5054
4
97T Utility C18 U
85684
79078
52014
0
9275
5083
12*
98T Utility C16-7 U
48698
51733
13932
2890
11477
6023
3
99T Utility C14-5 U
45669
39512
13932
0
9303
4877
2
100T Utility C12b-3 U
43602
38317
13932
0
4906
2821
5
lOlTractor DC C18
99430
92831
31611
0
12952
9053
7
Note: We did not include BEVs in our technology package for those vehicle types with a payback period of longer than 10 years;
these vehicle types are marked with an * in the table. Vehicles indicated with a "NA" are considered to be publicly-charged BEVs
that are not included in the technology packages prior to MY 2030.
Table 2-98 Results of the BEV Payback Analysis for MY 2030 (2022$)
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and FET
($/unit)
EVSE RPE
($/unit)
IRA Vehicle
Tax Credit
($/unit)
Average
Annual ICE
Operating
($/year)
Average
Annual BEV
Operating
($/year)
BEV
Payback
(years)
01V Amb CI
4-5 MP
45212
32934
13932
0
5896
3537
1
02V Amb CI
2b-3 MP
43166
32086
6966
0
8105
4565
0
395
-------
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and FET
($/unit)
EVSE RPE
($/unit)
IRA Vehicle
Tax Credit
($/unit)
Average
Annual ICE
Operating
($/year)
Average
Annual BEV
Operating
($/year)
BEV
Payback
(years)
03V Amb CI
45212
31969
13932
0
7069
3804
1
4-5 U
04V Amb CI
43166
31092
13932
0
7112
3756
1
2b-3 U
05T Box C18
95967
62284
26007
0
15759
8708
0
MP
06T Box C18
R
95967
63342
52014
0
14378
8713
4
07T Box C16
48483
41026
13932
0
8265
4714
2
-7 MP
08T Box C16
48483
42770
13932
0
7989
4835
3
-7 R
09T Box C18
U
84828
61283
52014
0
17743
8550
4
10T Box C16
48483
40303
13932
0
8547
4474
2
-7 U
11T Box C12
42465
30624
6966
0
9986
5036
0
b-3 U
12T Box C12
42465
32742
13932
0
9157
5376
2
b-3 R
13T Box C12
42465
31636
6966
0
9466
5198
0
b-3 MP
14T Box C14
42609
30624
13932
0
6850
3582
1
-5 U
15T Box C14
42609
32742
13932
0
6318
3822
2
-5 R
16T Box C14
42609
31636
6966
0
6516
3697
0
-5 MP
17B Coach
75518
121231
0
39065
31495
25342
2
C18 R
19C Mix CI
84828
86514
52014
1442
35420
16129
3
8 MP
20T Dump
95967
67399
52014
0
13145
6188
4
C18 U
2IT Dump
95967
67881
26007
0
11527
6235
0
C18 MP
22T Dump
48211
53776
26007
5299
12206
6631
5
C16-7 MP
23 T Dump
84828
67399
52014
0
12860
6188
5
C18 U
24T Dump
48211
51678
52014
3301
12970
6403
8
C16-7 U
25T Fire C18
95967
69760
52014
0
12422
6418
5
MP
26T Fire C18
U
84828
69843
52014
0
13970
6426
5
27T Flat C16
48211
40901
13932
0
8258
4710
2
-7 MP
28T Flat C16
48211
42645
26007
0
8133
4914
7
-7 R
396
-------
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and FET
($/unit)
EVSE RPE
($/unit)
IRA Vehicle
Tax Credit
($/unit)
Average
Annual ICE
Operating
($/year)
Average
Annual BEV
Operating
($/year)
BEV
Payback
(years)
29T Flat C16
48211
39365
13932
0
8718
4530
2
-7 U
30Tractor D
101106
85108
42148
0
19409
12555
4
C C18
31 Tractor D
79508
72789
31611
0
17455
11198
4
C C17
32Tractor SC
104883
164610
0
40000
72536
58080
2
C18
3 3 Tractor D
80478
106435
0
22182
39459
30528
1
C C18
34T Ref C18
79850
75471
52014
0
19942
8472
4
MP
35T Ref C16
48211
55240
52014
6693
23791
11886
5
-7 MP
36T Ref C18
U
79850
75471
52014
0
19942
8472
4
37T Ref C16
48211
54787
52014
6262
25492
11792
4
-7 U
38RV C18 R
56134
101904
13932
39113
3448
3752
>15*
39RV C16-
48333
92089
13932
40000
3415
3803
>15*
7 R
40RV C14-
41709
63891
13932
21121
2802
2795
>15*
5 R
42RV C18 M
P
56134
101904
13932
39113
3448
3752
>15*
43RV C16-
48333
86189
13932
36047
3452
3588
>15*
7 MP
44RV C14-
41709
60128
13932
17538
2864
2658
>15*
5 MP
46B School
56134
62703
26007
5613
10931
6994
7
C18 MP
47B School
48333
40180
13932
0
10690
5486
2
C16-7 MP
48B School
41709
32934
6966
0
7753
4517
0
C14-5 MP
49B School
43711
32258
6966
0
7810
4415
0
C12b-3 MP
50B School
56134
60850
13932
4030
12546
6773
3
C18 U
5 IB School
48333
40180
13932
0
10690
5486
2
C16-7 U
52B School
41709
31969
6966
0
8164
4389
0
C14-5 U
53B School
43711
31264
6966
0
8221
4283
0
C12b-3 U
54Tractor SC
104883
189736
0
40000
72536
65783
8
C18
55B Shuttle
43711
38320
13932
0
17339
9413
2
C12b-3 MP
56B Shuttle
41709
37513
13932
0
18291
9272
2
C14-5 U
397
-------
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and FET
($/unit)
EVSE RPE
($/unit)
IRA Vehicle
Tax Credit
($/unit)
Average
Annual ICE
Operating
($/year)
Average
Annual BEV
Operating
($/year)
BEV
Payback
(years)
57B Shuttle
43711
36807
13932
0
18349
9112
1
C12b-3 U
58B Shuttle
48333
52393
26007
3866
21342
11824
3
C16-7 MP
59B Shuttle
48333
50138
52014
1719
22673
11375
5
C16-7 U
60S Plow CI
48211
44574
13932
0
9059
4933
3
6-7 MP
61S Plow CI
95967
82110
52014
0
12488
7012
7
8 MP
62 S Plow CI
48211
43083
26007
0
9601
4771
5
6-7 U
63 S Plow CI
8 U
84828
81233
52014
0
13993
6940
7
64V Step CI
48108
40959
13932
0
11890
6529
2
6-7 MP
65V Step CI
41709
31636
6966
0
6490
3697
0
4-5 MP
66V Step CI
43166
31578
6966
0
9295
5096
0
2b-3 MP
67V Step CI
48108
39411
13932
0
12594
6277
1
6-7 U
68V Step CI
41709
30624
13932
0
6825
3582
1
4-5 U
69V Step CI
43166
30567
13932
0
9805
4936
1
2b-3 U
70S Sweep
48211
42522
13932
0
12243
5850
2
C16-7 U
71T Tanker
95967
65669
52014
0
13136
7613
4
C18 R
72T Tanker
84828
65011
26007
0
13871
7529
2
C18 MP
73T Tanker
84828
64830
52014
0
15958
7505
4
C18 U
74T Tow CI
8 R
98968
84583
52014
0
15861
9449
6
75T Tow CI
48211
56536
52014
7927
11982
6908
11*
6-7 R
76T Tow CI
8 U
84828
82847
52014
0
19378
9262
5
77T Tow CI
48211
51811
52014
3428
12950
6397
8
6-7 U
78Tractor SC
104883
146280
0
35376
52579
47390
3
C18
80Tractor D
106074
121967
47704
13581
27046
17727
6
C C18
81 Tractor D
79508
100959
0
18330
36306
30385
2
C C17
82Tractor D
104883
123843
0
16202
40077
34692
2
C C18
398
-------
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEV PT
RPE + Sales
Tax and FET
($/unit)
EVSE RPE
($/unit)
IRA Vehicle
Tax Credit
($/unit)
Average
Annual ICE
Operating
($/year)
Average
Annual BEV
Operating
($/year)
BEV
Payback
(years)
83 Tractor D
79508
91477
42148
10228
21157
13857
6
C C17
84Tractor D
98436
84838
0
0
23328
19861
0
C C18
85B Transit
75518
89798
63222
12204
33319
16163
4
C18 MP
86B Transit
48333
65281
52014
16138
14962
8800
9
C16-7 MP
87B Transit
74613
89798
63222
12977
33296
16163
4
C18 U
88B Transit
48333
61579
52014
12613
15867
8401
8
C16-7 U
89T Utility
95967
63695
26007
0
8510
4643
0
C18 MP
90 T Utility
95967
64545
52014
0
7982
4710
7
C18 R
91T Utility
48211
42806
13932
0
10862
5781
2
C16-7 MP
92 T Utility
48211
44436
26007
0
10681
6006
5
C16-7 R
93 T Utility
45212
32979
13932
0
8830
4667
1
C14-5 MP
94 T Utility
43166
32193
13932
0
4683
2642
2
C12b-3 MP
95T Utility
45212
33956
13932
0
8364
4713
1
C14-5 R
96 T Utility
43166
33898
13932
0
8305
4711
2
C12b-3 R
97 T Utility
84828
63118
52014
0
9304
4598
7
C18 U
98T Utility
48211
41540
13932
0
11531
5607
2
C16-7 U
99T Utility
45212
32167
13932
0
9338
4555
1
C14-5 U
100T Utility
43166
31273
13932
0
4915
2570
1
C12b-3 U
lOlTractor D
98436
74692
31611
0
12992
8414
2
C C18
Note: We did not include BEVs in our technology package for those vehicle types with a payback period of longer than 10
years; these vehicle types are marked with an *
in the table.
Table 2-99 Results of the BEV Payback Analysis for MY 2032 (2022$)
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and
FET ($/unit)
EVSE
RPE
($/unit)
IRA
Vehicle
Tax
Credit
($/unit)
Average
Annual
ICE
Operating
($/year)
Average
Annual
BEV
Operating
($/year)
BEV
Payback
(years)
01V Amb C14-5 MP
44755
33541
13932
0
5905
3539
2
02V Amb C12b-3 MP
42730
32603
6966
0
8126
4558
0
399
-------
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and
FET ($/unit)
EVSE
IRA
Vehicle
Average
Annual
Average
Annual
BEV
Vehicle ID
RPE
Tax
ICE
BEV
Payback
($/unit)
Credit
($/unit)
Operating
($/year)
Operating
($/year)
(years)
03V Amb C14-5 U
44755
32462
13932
0
7085
3802
1
04V Amb C12b-3 U
42730
31492
13932
0
7129
3750
1
05T Box C18 MP
94998
64303
26007
0
15815
8724
0
06T Box C18 R
94998
65485
52014
0
14423
8733
4
07T Box C16-7 MP
47993
42164
13932
0
8290
4727
3
08T Box C16-7 R
47993
44113
13932
0
8012
4854
4
09T Box C18 U
83971
63184
52014
0
17821
8564
4
10T Box C16-7 U
47993
41355
13932
0
8574
4485
2
11T Box C12b-3 U
42036
30959
6966
0
10019
5020
0
12T Box C12b-3 R
42036
33326
13932
0
9183
5367
2
13T Box C12b-3 MP
42036
32090
6966
0
9494
5186
0
14T Box C14-5 U
42179
30959
13932
0
6867
3576
1
15T Box C14-5 R
42179
33326
13932
0
6330
3822
3
16T Box C14-5 MP
42179
32090
6966
0
6530
3694
0
17B Coach C18 R
74755
130647
0
40000
31648
25500
4
19C Mix C18 MP
83971
91384
52014
6335
35636
16192
3
20T Dump C18 U
94998
70020
52014
0
13191
6233
4
2IT Dump C18 MP
94998
70558
26007
0
11559
6281
1
22T Dump C16-7 MP
47724
56436
26007
8296
12256
6680
5
23T Dump C18 U
83971
70020
52014
0
12909
6233
6
24T Dump C16-7 U
47724
54091
52014
6062
13027
6445
8
25T Fire C18 MP
94998
72658
52014
0
12462
6470
5
26T Fire C18 U
83971
72751
52014
0
14029
6478
6
27T Flat C16-7 MP
47724
42046
13932
0
8282
4724
3
28T Flat C16-7 R
47724
43995
26007
0
8157
4933
7
29T Flat C16-7 U
47724
40330
13932
0
8747
4539
2
30Tractor DC C18
100085
88389
42148
0
19480
12587
5
31Tractor DC C17
78705
76044
31611
0
17520
11232
5
32Tractor SC C18
103824
177685
0
40000
72892
58203
3
33Tractor DC C18
79665
112659
0
28195
39654
30578
1
34T Ref C18 MP
79043
79300
52014
220
20047
8540
5
35T Ref C16-7 MP
47724
58073
52014
9854
23919
11916
5
36T Ref C18 U
79043
79300
52014
220
20047
8540
5
37T Ref C16-7 U
47724
57566
52014
9372
25634
11820
4
38RV C18 R
55567
109046
13932
40000
3444
3930
>15*
39RV C16-7 R
47845
99220
13932
40000
3412
4002
>15*
40RV C14-5 R
41288
68140
13932
25568
2798
2912
>15*
42RV C18 MP
55567
109046
13932
40000
3444
3930
>15*
43RV C16-7 MP
47845
92626
13932
40000
3449
3767
>15*
44RV C14-5 MP
41288
63934
13932
21564
2860
2762
>15*
46B School C18 MP
55567
65231
26007
8258
10974
7032
7
47B School C16-7 MP
47845
41203
13932
0
10730
5491
2
48B School C14-5 MP
41288
33541
6966
0
7772
4513
0
49B School C12b-3 MP
43270
32764
6966
0
7829
4409
0
5OB School C18 U
55567
63161
13932
6489
12602
6806
3
5 IB School C16-7 U
47845
41203
13932
0
10730
5491
2
52B School C14-5 U
41288
32462
6966
0
8188
4382
0
53B School C12b-3 U
43270
31653
6966
0
8244
4274
0
54Tractor SC C18
103824
205768
0
40000
72892
65968
10
400
-------
ICE PT RPE
+ Sales Tax
and FET
($/unit)
BEVPT
RPE + Sales
Tax and
FET ($/unit)
EVSE
IRA
Vehicle
Average
Annual
Average
Annual
BEV
Vehicle ID
RPE
Tax
ICE
BEV
Payback
($/unit)
Credit
($/unit)
Operating
($/year)
Operating
($/year)
(years)
55B Shuttle C12b-3 MP
43270
39539
13932
0
17405
9398
2
56B Shuttle C14-5 U
41288
38658
13932
0
18366
9255
2
57B Shuttle C12b-3 U
43270
37849
13932
0
18423
9092
1
58B Shuttle C16-7 MP
47845
54853
26007
6673
21439
11838
3
59B Shuttle C16-7 U
47845
52333
52014
4274
22782
11383
5
60S Plow C16-7 MP
47724
46151
13932
0
9091
4958
3
61S Plow C18 MP
94998
86462
52014
0
12527
7100
8
62S Plow C16-7 U
47724
44485
26007
0
9638
4792
5
63 S Plow C18 U
83971
85481
52014
1291
14049
7025
8
64V Step C16-7 MP
47622
42126
13932
0
11935
6534
2
65V Step C14-5 MP
41288
32090
6966
0
6504
3694
0
66V Step C12b-3 MP
42730
32036
6966
0
9323
5083
0
67V Step C16-7 U
47622
40397
13932
0
12645
6277
2
68V Step C14-5 U
41288
30959
13932
0
6841
3576
2
69V Step C12b-3 U
42730
30905
13932
0
9837
4920
1
70S Sweep C16-7 U
47724
43858
13932
0
12296
5863
2
71T Tanker C18 R
94998
68086
52014
0
13176
7646
5
72T Tanker C18 MP
83971
67351
26007
0
13923
7560
2
73T Tanker C18 U
83971
67148
52014
0
16028
7536
4
74T Tow C18 R
97968
89226
52014
0
15917
9532
7
75T Tow C16-7 R
47724
59521
52014
11233
12030
6965
11*
76T Tow C18 U
83971
87285
52014
2833
19470
9340
5
77T Tow C16-7 U
47724
54240
52014
6205
13007
6440
8
78Tractor SC C18
103824
157198
0
40000
52826
47508
4
80Tractor DC C18
105003
129967
47704
21334
27173
17865
6
81Tractor DC C17
78705
107528
0
24630
36475
30443
2
82Tractor DC C18
103824
131444
0
23603
40266
34770
2
83Tractor DC C17
78705
96930
42148
15574
21242
13935
6
84Tractor DC C18
97441
88260
0
0
23423
19883
0
85B Transit C18 MP
74755
95515
63222
17741
33499
16239
4
86B Transit C16-7 MP
47845
69258
52014
20389
15023
8876
9
87B Transit C18 U
73859
95515
63222
18506
33476
16239
4
88B Transit C16-7 U
47845
65120
52014
16449
15937
8465
8
89T Utility C18 MP
94998
65880
26007
0
8523
4685
0
90T Utility C18 R
94998
66830
52014
0
7991
4754
8
91T Utility C16-7 MP
47724
44176
13932
0
10904
5796
3
92T Utility C16-7 R
47724
45997
26007
0
10722
6026
5
93T Utility C14-5 MP
44755
33591
13932
0
8857
4662
1
94T Utility C12b-3 MP
42730
32723
13932
0
4688
2647
2
95T Utility C14-5 R
44755
34683
13932
0
8387
4712
2
96T Utility C12b-3 R
42730
34629
13932
0
8329
4710
2
97T Utility C18 U
83971
65235
52014
0
9330
4637
7
98T Utility C16-7 U
47724
42761
13932
0
11579
5618
2
99T Utility C14-5 U
44755
32684
13932
0
9368
4548
1
100T Utility C12b-3 U
42730
31694
13932
0
4923
2572
2
lOlTractor DC C18
97441
76919
31611
0
13027
8439
3
Note: We did not include BEVs in our technology package for those vehicle types with a payback period of longer than 10
years; these vehicle types are marked with an *
in the table.
401
-------
Table 2-100 Results of the FCEV Payback Analysis for MY 2030 (2022$)
Vehicle ID
ICE
PT
RPE +
Sales
Tax
FCEV
PT
RPE
+
Sales
Tax
and
FET
($/uni
t)
IRA
Vehicl
e Tax
Credit
($/uni
t)
Avera
ge
Annu
al
ICE
Average
Annual
FCEV
FCE
V
Payb
ack
(year
s)
and
FET
($/unit
)
Opera
ting
($/yea
r)
Operating
($/year)
18B_Coach_C18_MP
75518
14037
8
40000
31495
27011
8
41T ractorD CC17
79508
13415
1
40000
36306
33348
8
45Tractor_DC_C18
104883
17681
9
40000
40077
38405
>15*
79Tractor_SC_C18
104883
18013
9
40000
72536
69973
12
Note: We did not include FCEVs in our technology package for
those vehicle types with a payback period of longer than 10 years;
these vehicle types are marked with an * in the table.
Table 2-101 Results of the FCEV Payback Analysis for MY 2032 (2022$)
Vehicle ID
ICE PT RPE
+ Sales Tax
and FET
($/unit)
FCEV PT
RPE + Sales
Tax and FET
($/unit)
IRA
Vehicle
Tax
Credit
($/unit)
Average
Annual
ICE
Operating
($/year)
Average Annual
FCEV Operating
(S/ycar)
FCEV
Payback
(years)
18B Coach C18 MP
74755
132431
40000
31648
25161
4
41Tractor DC C17
78705
127555
40000
36475
30961
4
45Tractor DC C18
103824
168261
40000
40266
35618
7
79Tractor SC C18
103824
170436
40000
72892
64953
6
2.9.3 HD TRUCS Results
The technology packages for our modeled potential compliance pathway includes vehicles
with ICE powertrains and vehicles with ZEV powertrains. In our analysis, the ICE vehicles
include a suite of technologies that represent a vehicle that meets the previous MY 2027 Phase 2
CO2 emission standards. These technologies exist today and continue to evolve to improve the
efficiency of the engine, transmission, drivetrain, aerodynamics, and tire rolling resistance in HD
vehicles and therefore reduce their CO2 emissions. In addition, the heavy-duty industry continues
to develop C02-reducing technologies such as hybrid powertrains and H2-ICE powered vehicles,
also discussed in preamble Section II.F.4. These further technology improvements are not part of
the modeled potential compliance pathway's technology packages on which the final rule is
predicated but are available to any manufacturer determining its own compliance pathway.
After the technology assessment, as described in preamble Section II.D.4 and the preceding
sections of this RIA Chapter 2, and the payback analysis, as just described, EPA determined the
technology mix of ICE vehicle and ZEV technologies for the technology package for each
402
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regulatory subcategory. We first determined the ZEVs that are appropriate for each of the 101
vehicle types for MYs 2027, MY 2030, and 2032 based on their technical feasibility and
payback, as shown in Table 2-97 through Table 2-101. Table 2-102 shows the total vehicle sales
fraction, the regulatory subcategory grouping and the ZEV adoption rate percentages that
correspond to the payback years for MY 2027, MY2030, and MY 2032.
Table 2-102 ZEV Percentages by HD TRUCS Vehicle Type
MY 2027 ZEV
Percentage
MY 2030
MY 2032
Vehicle ID*
Sales %
Regulatory Group3
ZEV
Percentage
ZEV
Percentage
01V Amb C14-5 MP
1.69%
LHD
14%
37%
70%
02V Amb C12b-3 MP
1.69%
LHD
20%
37%
70%
03V Amb C14-5 U
1.69%
LHD
20%
37%
70%
04V Amb C12b-3 U
1.69%
LHD
20%
37%
70%
05T Box C18 MP
0.34%
HHD
20%
37%
70%
06T Box C18 R
0.29%
HHD
14%
26%
39%
07T Box C16-7 MP
0.77%
MHD
14%
37%
39%
08T Box C16-7 R
0.58%
MHD
14%
26%
39%
09T Box C18 U
0.34%
HHD
14%
26%
39%
10T Box C16-7 U
0.77%
MHD
20%
37%
70%
11T Box C12b-3 U
1.69%
LHD
20%
37%
70%
12T Box C12b-3 R
1.69%
LHD
20%
37%
70%
13T Box C12b-3 MP
1.69%
LHD
20%
37%
70%
14T Box C14-5 U
1.69%
LHD
20%
37%
70%
15T Box C14-5 R
1.69%
LHD
14%
37%
39%
16T Box C14-5 MP
1.69%
LHD
20%
37%
70%
17B Coach C18 R
0.21%
HHD/Coach Bus
0%
14%
14%
18B Coach C18 MP
0.21%
HHD/Coach Bus
0%
5%
14%
19C Mix C18 MP
0.34%
HHD/Concrete Mixer
20%
26%
39%
20T Dump C18 U
0.54%
HHD
14%
26%
39%
2IT Dump C18 MP
0.54%
HHD
20%
37%
70%
22T Dump C16-7 MP
1.45%
MHD
14%
14%
14%
23T Dump C18 U
0.54%
HHD
5%
14%
14%
24T Dump C16-7 U
1.45%
MHD
5%
5%
5%
25T Fire C18 MP
0.34%
HHD
5%
14%
14%
26T Fire C18 U
0.34%
HHD
5%
14%
14%
27T Flat C16-7 MP
0.77%
MHD
14%
37%
39%
28T Flat C16-7 R
0.77%
MHD
5%
14%
14%
29T Flat C16-7 U
0.77%
MHD
20%
37%
70%
30Tractor DC C18
3.33%
DC
5%
26%
14%
31Tractor DC C17
1.70%
DC
14%
26%
14%
32Tractor SC C18
2.70%
SC
0%
37%
39%
33Tractor DC C18
1.51%
DC
0%
37%
70%
34T Ref C18 MP
0.21%
HHD/Refuse Hauler
14%
26%
14%
35T Ref C16-7 MP
0.04%
MHD/Refuse Hauler
14%
14%
14%
36T Ref C18 U
0.21%
HHD/Refuse Hauler
14%
26%
14%
37T Ref C16-7 U
0.04%
MHD/Refuse Hauler
14%
26%
39%
38RV C18 R
0.38%
HHD
0%
0%
0%
39RV C16-7 R
0.66%
MHD
0%
0%
0%
40RV C14-5 R
1.40%
LHD
0%
0%
0%
41Tractor DC C17
1.04%
DC
0%
5%
39%
42RV C18 MP
0.38%
HHD
0%
0%
0%
403
-------
MY 2027 ZEV
Percentage
MY 2030
MY 2032
Vehicle ID*
Sales %
Regulatory Group"
ZEV
Percentage
ZEV
Percentage
43RV C16-7 MP
0.66%
MHD
0%
0%
0%
44RV C14-5 MP
1.40%
LHD
0%
0%
0%
45Tractor DC C18
1.51%
DC
0%
0%
14%
46B School C18 MP
0.15%
HHD/School Bus
5%
14%
14%
47B School C16-7 MP
1.98%
MHD/School Bus
20%
37%
70%
48B School C14-5 MP
0.07%
LHD/School Bus
20%
37%
70%
49B School C12b-3 MP
0.07%
LHD/School Bus
20%
37%
70%
5OB School C18 U
0.15%
HHD/School Bus
20%
26%
39%
5 IB School C16-7 U
1.98%
MHD/School Bus
20%
37%
70%
52B School C14-5 U
0.07%
LHD/School Bus
20%
37%
70%
53B School C12b-3 U
0.07%
LHD/School Bus
20%
37%
70%
54Tractor SC C18
0.00%
SC
0%
0%
0%
55B Shuttle C12b-3 MP
0.31%
LHD
20%
37%
70%
56B Shuttle C14-5 U
0.53%
LHD
20%
37%
70%
57B Shuttle C12b-3 U
0.53%
LHD
20%
37%
70%
58B Shuttle C16-7 MP
0.01%
MHD
20%
26%
39%
59B Shuttle C16-7 U
0.07%
MHD
14%
14%
14%
60S Plow C16-7 MP
0.08%
MHD
20%
26%
39%
61S Plow C18 MP
0.05%
HHD
0%
14%
5%
62S Plow C16-7 U
0.08%
MHD
14%
14%
14%
63 S Plow C18 U
0.05%
HHD
5%
14%
5%
64V Step C16-7 MP
0.77%
MHD
20%
37%
70%
65V Step C14-5 MP
1.69%
LHD
20%
37%
70%
66V Step C12b-3 MP
0.30%
LHD
20%
37%
70%
67V Step C16-7 U
0.77%
MHD
20%
37%
70%
68V Step C14-5 U
1.69%
LHD
20%
37%
70%
69V Step C12b-3 U
0.30%
LHD
20%
37%
70%
70S Sweep C16-7 U
0.77%
MHD
20%
37%
70%
7IT Tanker C18 R
0.34%
HHD
5%
26%
14%
72T Tanker C18 MP
0.34%
HHD
20%
37%
70%
73T Tanker C18 U
0.34%
HHD
14%
26%
39%
74T Tow C18 R
0.34%
HHD
5%
14%
14%
75T Tow C16-7 R
0.77%
MHD
0%
0%
0%
76T Tow C18 U
0.34%
HHD
14%
14%
14%
77T Tow C16-7 U
0.77%
MHD
5%
5%
5%
78Tractor SC C18
5.30%
SC
0%
26%
39%
79Tractor SC C18
10.90%
SC
0%
0%
14%
80Tractor DC C18
0.34%
HH Tractor
5%
14%
14%
81Tractor DC C17
1.04%
DC
0%
37%
70%
82Tractor DC C18
1.51%
DC
0%
37%
70%
83Tractor DC C17
1.70%
DC
5%
14%
14%
84Tractor DC C18
3.70%
DC
0%
37%
70%
85B Transit C18 MP
2.27%
HHD/Other Bus
14%
26%
39%
86B Transit C16-7 MP
0.01%
MHD/Other Bus
5%
5%
5%
87B Transit C18 U
0.80%
HHD/Other Bus
14%
26%
39%
88B Transit C16-7 U
0.01%
MHD/Other Bus
5%
5%
5%
89T Utility C18 MP
0.34%
HHD
20%
37%
70%
90T Utility C18 R
0.34%
HHD
0%
14%
5%
9IT Utility C16-7 MP
0.77%
MHD
20%
37%
39%
92T Utility C16-7 R
0.77%
MHD
0%
14%
14%
93T Utility C14-5 MP
1.69%
LHD
20%
37%
70%
404
-------
MY 2027 ZEV
Percentage
MY 2030
MY 2032
Vehicle ID*
Sales %
Regulatory Group"
ZEV
Percentage
ZEV
Percentage
94T Utility C12b-3 MP
1.69%
LHD
14%
37%
70%
95T Utility C14-5 R
0.30%
LHD
0%
14%
14%
96T Utility C12b-3 R
0.30%
LHD
0%
14%
14%
97T Utility C18 U
0.34%
HHD
0%
14%
14%
98T Utility C16-7 U
0.77%
MHD
20%
37%
70%
99T Utility C14-5 U
1.69%
LHD
20%
37%
70%
100T Utility C12b-3 U
1.69%
LHD
14%
37%
70%
lOlTractor DC C18
0.37%
DC
14%
37%
39%
a All vocational vehicle types are assigned to either LHD, MHD, or HHD regulatory grouping. Some vehicle types are
also assigned to a second regulatory grouping for calculating the appropriate Optional Custom Chassis adoption rate,
as shown in Table 2-103.
Next, we aggregated the projected ZEVs for the specific vehicle types into their respective
regulatory groupings relative to the vehicle's sales weighting. The results for MYs 2027, 2030,
and 2032 are shown in Table 2-103. As proposed, we are retaining the Phase 2 MY 2027
emission standards for the optional custom chassis standards for emergency vehicles, mixed use
vehicles, and motorhomes. In the final rule, as discussed in Chapter 2.9.1.1 and 2.9.1.2 we have
also determined it is appropriate to retain the Phase 2 MY 2027 standards for optional custom
chassis concrete mixers and coach buses. Therefore, those vehicle types are not shown in the
table below.
Table 2-103 HD TRUCS Results: Percentage of ZEVs in MYs 2027,2030, and 2032
Regulatory Grouping
MY 2027
MY 2030
MY 2032
LHD Vocational
17%
33%
61%
MHD Vocational
13%
25%
41%
HHD Vocational
11%
22%
32%
MHD All Cab and HHD Day Cab Tractor
3%
26%
41%
Sleeper Cab Tractors
0%
13%
25%
Heavy Haul Tractors
5%
14%
14%
Optional Custom Chassis: School Bus
20%
36%
67%
Optional Custom Chassis: Other Bus
14%
26%
39%
Optional Custom Chassis: Refuse Hauler
14%
25%
16%
2.10 Supporting the Feasibility of the Final CO2 Standards
As described in Preamble Section II.F and G, after extensive analysis, EPA determined the
final CO2 standards for each subcategory, giving appropriate consideration to costs, lead time,
and other factors. Similar to the approach we used to support the HD GHG Phase 2 vehicle and
proposed Phase 3 CO2 emission standards, we developed a modeled potential compliance
pathway's technology package for each regulatory subcategory of vocational vehicles and
tractors to support the final standards. We also assessed the feasibility of those standards under
the modeled potential compliance pathway considering cost and lead time, considering among
other factors described in this section, technology costs for manufacturers and costs to purchasers
and operators, as described in preamble Section II. We applied these technology packages to
nationwide heavy-duty vehicle production volumes to support the final Phase 3 GHG vehicle
standards. The technology packages utilize the averaging portion of EPA's longstanding ABT
405
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program, and thus that part of ABT is reflected in the technology packages supporting the
stringency of the final standards.
Our modeled potential compliance pathway projects that manufacturers will produce a mix of
HD vehicles that utilize ICE-powered vehicle technologies and ZEV technologies, with specific
adoption rates foreach regulatory subcategory of vocational vehicles and tractors for each MY.
Note that we have analyzed a potential compliance pathway to support the feasibility and
appropriateness of the level of stringency for each of the final standards,1267 but manufacturers
will be able to use many different compliance pathways, that may include a combination of HD
engine or vehicle GHG-reducing technologies (including zero-emission and vehicles with ICE
technologies), to meet the standards. Furthermore, for the analysis for the final standards, we also
have evaluated additional example potential compliance pathways' technology packages with
only ICE vehicle with ICE technologies, as described in Chapter 2.11.
We discuss the calculation of the standards in detail in the following subsection.
2.10.1 Technology Packages to Support the Final Standards
The technology packages for our modeled potential compliance pathway includes vehicles
with ICE powertrains and vehicles with ZEV powertrains. In our analysis, the ICE vehicles
include a suite of technologies that represent a vehicle that meets the MY 2027 Phase 2 CO2
emission standards. These technologies exist today and continue to evolve to improve the
efficiency of the engine, transmission, drivetrain, aerodynamics, and tire rolling resistance in HD
vehicles and therefore reduce their CO2 emissions. As discussed in Chapter 2.11, there are
opportunities for further adoption of these Phase 2 ICE technologies beyond the adoption rates
used in the HD GHG Phase 2 rule, In addition, the heavy-duty industry continues to develop
C02-reducing technologies such as hybrid powertrains and H2-ICE powered vehicles, also
discussed in Chapter 2.11. These further technology improvements are not part of the modeled
potential compliance pathway's technology packages that support the final standards, but are
available to any manufacturer determining its own compliance pathway.
To determine the numerical values of the final emission standards, we adjusted some of the
adoption rates shown in Table 2-103 downward, which means we are finalizing standards that
are less stringent than the HD TRUCS results support, as a conservative approach to setting
standards. Even though the results from HD TRUCS are reasonable and supportable, we made
specific changes to certain regulatory groupings for the following reasons: (1) The MY 2030
vocational vehicle and day cab technology adoption rates were lowered to slow the phase in to
approximately 33% of the difference between the MY 2027 and MY 2032 adoption rates in
Table 2-103. This has the effect of phasing in the standards more slowly early in the program. (2)
The MY 2030 sleeper cab tractor technology adoption rates were reduced to provide more time
for the BEV public charging infrastructure and hydrogen infrastructure to develop. (3) Heavy
haul tractors were lowered to 0% in MYs 2027 and 2028, consistent with the decision discussed
below about delaying the heavy heavy-duty vocational vehicle standards, since both vehicle
types have large energy demands. For the same reason, we lowered both the MY 2030 and MY
2032 heavy haul tractor standards.
1267 Note that our modeled potential compliance pathway considers and costs only availability of averaging within
the ABT program and does not rely on any other flexibility under the ABT program.
406
-------
For the proposal, the optional chassis subcategories were calculated using the sales weighted
average results from HD TRUCS for each optional chassis application. This meant that the
optional chassis standards could be more stringent than their corresponding primary vocational
vehicle standards. For the final rule, we have taken a more conservative approach. The
companies that certify vehicles to the optional custom chassis standards have more restrictive
ABT provisions than those provisions available to companies with vehicles certified under the
primary vocational vehicle standards. Therefore, for Phase 3, we limited the increase in
stringency to the optional custom chassis standards to be no greater than the increase in
stringency of the corresponding primary vocational vehicle standards. Each optional custom
chassis subcategory corresponds to either the MHD or HHD vehicle service class.1268 Thus, the
adoption rates for the optional chassis standards for school buses were lowered to match the rates
for MHD vocational adoption rates. Similarly, the adoption rates for the optional chassis
standards for other buses were lowered to the match rates for HHD vocational vehicles. Lastly,
the adoption rates for MY 2027 and MY 2030 of the optional chassis standards for refuse haulers
were lowered to match the rates for HHD vocational.
Table 2-104 Percentage of ZEVs in the MYs 2027,2030 and 2032 Technology Packages before Product Lead
Time Adjustments
Regulatory Grouping
MY 2027
MY 2030
MY 2032
LHD Vocational
17%
32%
60%
MHD Vocational
13%
22%
40%
HHD Vocational
10%
15%
30%
MHD All Cab and HHD Day Cab Tractor
3%
16%
40%
Sleeper Cab Tractors
0%
6%
25%
Heavy Haul Tractors
0%
1%
5%
Optional Custom Chassis: School Bus
13%
22%
40%
Optional Custom Chassis: Other Bus
10%
15%
30%
Optional Custom Chassis: Coach Bus
0%
0%
0%
Optional Custom Chassis: Refuse Hauler
10%
15%
16%
Optional Custom Chassis: Concrete Mixer
0%
0%
0%
Optional Custom Chassis: Motorhomes
0%
0%
0%
Optional Custom Chassis: Emergency Vehicles
0%
0%
0%
To calculate the final adoption rates for all model years, we interpolated the intervening
model years between MYs 2027 and 2030 and between MYs 2030 and 2032. In general, the
standards for MY 2028 and MY 2029 are phased in by a linear interpolation between MY 2027
and MY 2030, and the standards for MY 2031 are a linear interpolation between MY 2030 and
MY 2032. However, because ZEV sleeper cab tractor operation may rely most heavily on public
charging and hydrogen fueling, to allow for more infrastructure development, we are phasing in
the standards at a slower rate for MY 2031 at 33% of the difference between MY 2030 and MY
2032. We are providing additional lead time in the final standards for some of the categories
when compared to the HD TRUCS results (Table 2-103) and our downward adjustments (Table
2-104). As described in the preamble in Section II.F, we will commence the Phase 3 HHD
vocational standards in MY 2029 to provide additional lead time for these heavy heavy-duty
vehicle categories. Consistent with the HHD vocational standards, we have delayed the start of
1268 See 40 CFR 1037.105(h), Table 5. The optional chassis school bus subcategory is assigned to MHD; The
optional chassis other bus and refuse hauler subcategories are assigned to HHD.
407
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the optional chassis other bus standards until MY 2029 because they are typically HHD
vocational vehicles. Also as discussed in preamble Section II.F, the Phase 3 day cab standards
will begin in MY 2028 to also provide additional lead time for development of these vehicles.
For the optional custom chassis refuse haulers, we also delayed the start of the standards to MY
2028, consistent with the day cab tractor approach because refuse haulers also consist of both
MHD and HHD vehicles.
The resulting ZEV adoption rates in our technology packages for MYs 2027-2032 by
regulatory group are shown in Table 2-105. The remaining portion of vehicles in each
technology package are projected to be ICE vehicles, as shown in Table 2-106, that achieve a
level of CO2 emissions performance equal to the Phase 2 MY 2027 emission standards.
Table 2-105 Percentage of ZEVs in the Modeled Potential Compliance Pathway's MYs 2027-2032
Technology Packages
MY 2027
MY 2028
MY 2029
MY 2030
MY 2031
MY 2032
Regulatory Group
ZEV
ZEV
ZEV
ZEV
ZEV
ZEV
Adoption
Adoption
Adoption
Adoption
Adoption
Adoption
LHD Vocational
17%
22%
27%
32%
46%
60%
MHD Vocational
13%
16%
19%
22%
31%
40%
HHD Vocational
0%
0%
13%
15%
23%
30%
MHD All Cab and HHD
0%
8%
12%
16%
28%
40%
Day Cab Tractors
Sleeper Cab Tractors
0%
0%
0%
6%
12%
25%
Heavy Haul Tractors
0%
0%
1%
1%
3%
5%
Optional Custom
13%
16%
19%
22%
31%
40%
Chassis:
School Bus
Optional Custom
0%
0%
13%
15%
23%
30%
Chassis:
Other Bus
Optional Custom
0%
0%
0%
0%
0%
0%
Chassis:
Coach Bus
Optional Custom
0%
5%
10%
15%
16%
16%
Chassis:
Refuse Hauler
Optional Custom
0%
0%
0%
0%
0%
0%
Chassis:
Concrete Mixer
Optional Custom
0%
0%
0%
0%
0%
0%
Chassis:
Motor Home
Optional Custom
0%
0%
0%
0%
0%
0%
Chassis:
Mixed Use Vehicle
Optional Custom
0%
0%
0%
0%
0%
0%
Chassis:
Emergency Vehicle
408
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Table 2-106 Percentage of ICE Vehicles in the Modeled Potential Compliance Pathway's MYs 2027-2032
Technology Packages
MY 2027
MY 2028
MY 2029
MY 2030
MY 2031
MY 2032
Regulatory Group
ZEV
ZEV
ZEV
ZEV
ZEV
ZEV
Adoption
Adoption
Adoption
Adoption
Adoption
Adoption
LHD Vocational
83%
78%
73%
68%
54%
40%
MHD Vocational
87%
84%
81%
78%
69%
60%
HHD Vocational
100%
100%
87%
85%
77%
70%
MHD All Cab and HHD
100%
92%
88%
84%
72%
60%
Day Cab Tractors
Sleeper Cab Tractors
100%
100%
100%
94%
88%
75%
Heavy Haul Tractors
100%
100%
99%
99%
97%
95%
Optional Custom
87%
84%
81%
78%
69%
60%
Chassis:
School Bus
Optional Custom
100%
100%
87%
85%
77%
70%
Chassis:
Other Bus
Optional Custom
100%
100%
100%
100%
100%
100%
Chassis:
Coach Bus
Optional Custom
100%
95%
90%
85%
84%
84%
Chassis:
Refuse Hauler
Optional Custom
100%
100%
100%
100%
100%
100%
Chassis:
Concrete Mixer
Optional Custom
100%
100%
100%
100%
100%
100%
Chassis:
Motor Home
Optional Custom
100%
100%
100%
100%
100%
100%
Chassis:
Mixed Use Vehicle
Optional Custom
100%
100%
100%
100%
100%
100%
Chassis:
Emergency Vehicle
2.10.2 Battery Pack Production Levels to Support the Technology Packages
Using the modeled potential compliance pathway's technology packages for MYs 2027-2032,
we determined the total number of gigawatt-hours (GWh) of batteries that will need to be
produced to support these levels of sales of BEVs and FCEVs. Table 2-107 shows the sales-
weighted average battery pack size and vehicle sales for MY 2027 and MY 2032 BEVs and
FCEVs used to determine the HD vehicle total. Based on our analysis, 11 GWh of batteries will
be required in MY 2027 and 58 GWh of batteries in MY 2032.
409
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Table 2-107 Sales-Weighted Battery Pack Size and MOVES MY2027 and MY2032 Vehicle Sales
2027
Sales-
2027
MOVES
BEV
Vehicle
Sales
2032
Sales-
2032
MOVES
BEV
Vehicle
Sales
2032
Sales-
2032
MOVES
FCEV
Vehicle
Sales
Source
TypelD
Reg ClassID
weighted
Average
Battery
Size per
BEV
(kWh)
weighted
Average
Battery
Size per
BEV
(kWh)
weighted
Average
Battery
Size per
FCEV
(kWh)
41
42
155
1262
155
4484
55
0
41
46
245
54
245
83
35
0
41
47
0
821
710
1558
33
759
42
42
164
389
164
1381
55
0
42
46
295
12
283
27
35
0
42
47
472
0
472
0
56
0
42
48
472
253
472
1557
56
0
43
42
112
371
112
1262
55
0
43
46
160
5022
160
17448
35
0
43
47
255
88
256
552
56
0
51
46
288
131
287
280
35
0
51
47
355
108
355
1210
56
0
52
42
110
33438
110
115613
55
0
52
46
189
9702
176
27017
35
0
52
47
297
1446
287
8933
55
0
53
42
104
737
108
3059
55
0
53
46
183
486
183
1342
35
0
53
47
252
64
252
552
56
0
54
42
365
3024
365
9268
55
0
54
46
574
969
574
2869
35
0
54
47
564
239
564
666
56
0
61
46
355
2225
475
6641
67
2239
61
47
334
3226
444
28271
98
1125
62
46
0
12
881
444
58
259
62
47
0
246
881
9628
58
5618
2.10.3 EVSE Production Levels to Support the Technology Packages
We determined the total number of EVSE ports that will be required to support the depot-
charged BEVs in the modeled potential compliance pathway's technology packages that support
the MY 2027-2032 standards. We project about 520,000 EVSE ports will be needed across all
six model years As described in Chapter 2.8.7.2,to estimate the EVSE port counts for depot
charging, we first assign the lowest-cost EVSE option that can meet each BEV's charging needs,
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allowing multiple BEVs to share an EVSE port (up to a cap) when feasible.1269 Then we use the
projected BEV sales by model year1270 for each depot-charged vehicle type in our analysis and
divide by the number of vehicles that can share a port of the assigned type. Lastly, we sum these
across all depot-charged vehicle types. The results are shown in Table 2-108. The majority (88
percent) are Level 2 ports, followed by lower-power DCFCs. We project 51 DC-350 kW ports
will be needed at depots. Table 2-108 shows the total EVSE ports by type for MY 2027 through
MY 2032 BEVs.
Table 2-108 EVSE Port Counts for Depot Charging Analysis
EVSE Type
MY 2027
MY 2028
MY 2029
MY 2030
MY 2031
MY 2032
Total
Level 2 (19.2 kW)
38,726
50,360
61,404
71,432
101,720
133,230
456,872
DC-50 kW
2,981
3,892
6,344
6,998
9,075
11,271
40,561
DC-150 kW
1,867
3,106
5,007
3,323
4,148
5,024
22,475
DC-350 kW
-
2
4
5
15
25
51
Taking into account the approximately 633,000 of MY2027-2032 BEVs that we project will
use depot charging, we estimate an overall ratio of 1.2 BEVs per depot EVSE port. See RIA
Chapter 1.6.2.3 for a discussion of how these estimates compare to charging infrastructure need
assessments in the literature.
2.10.4 Calculation of the Final CO2 Standards
The heavy-duty vehicle CO2 emission standards are in grams per ton-mile, which represents
the grams of CO2 emitted to move one ton of payload a distance of one mile. The final Phase 3
vehicle standards fall into two major categories: tractors and vocational vehicles and are then
further subdivided into standards for each regulatory subcategory. The following sections
describe how the final Phase 3 vehicle standards within each regulatory subcategory are
calculated.
2.10.4.1 Calculation of the Final Tractor Standards
The final tractor CO2 emission standards for each model year are calculated by multiplying
the fraction of ICE-powered vehicles in each technology package by the corresponding Phase 2
MY 2027 CO2 emission standards, as shown in Table 2-109. The final standards are presented in
RIA Chapter 2.10.5. We note that this is a description of how the level of the standard is
calculated and supported under the modeled potential compliance pathway. It is not a description
of how the EPA determined that the final standards are feasible and appropriate, which is
explained in preamble Section II.G.
1269 These results are summarized in Table 2-78.
1270 Estimates of new heavy-duty vehicle sales are sourced from MOVES for each model between 2027 and 2032.
BEV adoption shares by vehicle type are from HD TRUCS.
411
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Table 2-109 Phase 2 MY 2027 Tractor CO2 Emission Standards (g/ton-mile)
Class 7
Class 8
Class 8
Heavy Haul
(All Cab Styles)
(Day Cab)
(Sleeper Cab)
Low Roof
96.2
73.4
64.1
Mid Roof
103.4
78.0
69.6
48.3
High Roof
100.0
75.7
64.3
2.10.4.2 Calculation of the Final Vocational Vehicle Standards
Consistent with the final tractor standards, the final CO2 emission standards for the vocational
vehicles regulatory subcategories are calculated from technology packages that consist of both
ICE-powered vehicle technologies and ZEV technologies. The projected fraction of ZEVs that
emit zero grams CCh/ton-mile at the tailpipe in the technology packages are shown in Table
2-105. The remaining fraction of vehicles in the technology package are ICE-powered vehicles
that include the technologies listed in the Preamble in Table II-1 (reflecting the GEM inputs for
the individual technologies that make up the technology packages that meets the Phase 2 MY
2027 CO2 vocational vehicles emission standards). Thus, as noted above, in the technology
packages, the ICE-powered vehicles emit at the applicable Phase 2 MY 2027 CO2 emission
standards, as shown in Table 2-110.
Table 2-110 Phase 2 MY 2027 Vocational Vehicle CO2 Emission Standards (g/ton-mile)
CI Light
CI Medium
CI Heavy
SI Light
SI Medium
Heavy
Heavy
Heavy
Heavy
Heavy
Urban
367
258
269
413
297
Multi-Purpose
330
235
230
372
268
Regional
291
218
189
319
247
School Bus
271
S
Other Bus
286
C/3 . .
=3 00
Coach Bus
205
Refuse Hauler
298
3s
Concrete Mixer
316
.2 ^
Motor Home
226
O
Mixed-Use Vehicle
316
Emergency Vehicle
319
2.10.4.2.1 Vocational Vehicles - Primary Program
The HD GHG Phase 2 structure enables the technologies that perform best during urban
driving or the technologies that perform best at highway driving to each be properly recognized
over the appropriate drive cycles. The HD GHG Phase 2 structure was developed recognizing
that there is not a single package of engine, transmission, and driveline technologies that is
suitable for all ICE-powered vocational vehicle applications. In the proposal we recognized the
variety in vocational vehicle CO2 emissions may no longer be necessary for ZEVs because ZEVs
are deemed to have zero CO2 emissions. Similarly, the SI and CI distinction within the
vocational vehicle regulatory subcategory structure is not relevant for vocational ZEVs because
they cannot be technically described as either Si-powered or Cl-powered. We requested
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comment on possible alternative vocational vehicle regulatory subcategory structures, such as
reducing the number of vocational vehicle subcategories to only include the multi-purpose
standards in each weight class, and/or maintaining urban, multi-purpose, and Regional but
combining SI and CI into a standard for each weight class. 88 FR at 22995. After considering the
comments and the final levels of stringency that reflect a continued significant volume of ICE
vehicle production during the Phase 3 timeframe, and as discussed further in the next paragraphs,
we are finalizing a structure, as we proposed, to maintain the existing HD GHG Phase 2
vocational vehicle regulatory subcategories.
We also proposed to calculate vocational vehicle standards for the primary program, within
each weight class by calculating a g/ton-mile value based on the CI multi-purpose Phase 2 MY
2027 standard and subtracting this value from each of the Phase 2 MY 2027 standards within a
weight class. As part of the same approach, we proposed that ZEV ABT credits would be
generated relative to that single subcategory's (CI-MP) emission standard (rather than urban,
regional, or multi purpose). Specifically, as part of the process used in the proposal to calculate
the proposed standards, EPA also proposed to revise the definition of the variable "Std" in 40
CFR 1037.705 to establish a common reference emission standard for vocational vehicles with
tailpipe CO2 emissions deemed to be zero (i.e., BEVs, FCEVs, and vehicles with engines fueled
with pure hydrogen). This approach was proposed in order to create a level playing field for
potential compliance strategies that included ZEVs; however, some manufacturers pointed out
that restricting ZEV compliance to only the multi-purpose category could prevent manufacturers
from earning full credits from ZEV vehicles1271 with the intended use that best matches other
subcategories of vehicles.1272
One commenter said that EPA should continue to use the Phase 2 approach that allows
manufacturers to use good engineering judgement to determine the appropriate vocational
vehicle subcategory for ZEVs and to therefore retain the urban, regional, multipurpose
subcategories. The commenter stated that collapsing the subcategories penalizes manufacturers
with higher ZEV production levels in a subcategory other than multipurpose. Another
commenter also requested that OEMs be allowed to classify their ZEVs "according to their
intended use" noting that the proposal would reduce credits earned for ZEVs in the disfavored
subcategories and would not provide enough lead time for manufacturers unless implementation
was delayed until MY 2030. One commenter also raised concerns with the vocational vehicle
standard setting process used by EPA in the NPRM and suggested we re-evaluate the approach
for the final rule considering the potential impacts on each of the vocational vehicle
subcategories, noting that the proposed approach inherently disfavored manufacturers of
vocational vehicles in existing subcategories other than multipurpose.
1271 ABT CO2 emission credits are determined using the equation in 40 CFR 1037.705. The credits are calculated
based on the difference between the applicable standard for the vehicle and the vehicle's family emission limit
multiplied by the vehicle's regulatory pay load and useful life miles.
1272 Since, in the Phase 2 MY 2027 standards, the vocational vehicle urban standards for each weight class are
numerically higher than the multi-purpose standards, it is ZEVs that manufacturers would have certified to the urban
category that would earn fewer credits under the proposed approach. We note that under the proposed approach
manufacturers would earn more credits than for ZEVs the manufacturer would have otherwise certified to the
regional standards.
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After considering comments we are not finalizing the proposed revision to the ABT credit
calculation regulations1273 with regard to the appropriate vocational vehicle subcategory to which
manufacturers would certify ZEVs and are not using the proposed change to the ABT
calculations in demonstrating the feasibility of or setting the vocational vehicle standards. We
agree that there are legitimate concerns for manufacturers of urban ZEV vocational vehicles
under the proposed approach regarding an even playing field. After considering comments, we
are not finalizing the proposed approach of setting all the vocational vehicle standards relative to
the CI multi-purpose regulatory subcategory.
We recognize that we project in the technology packages that the majority of vocational
vehicles will continue to use ICE vehicle technologies during the implementation of Phase 3.
However, we continue to be concerned about the possibility of allowing a loophole in the
regulations that would allow manufacturers to receive more credits by assigning vocational
vehicle ZEVs to an inappropriate subcategory when complying with the Phase 3 standards. We
are thus retaining the existing requirement that ZEVs be subject to the CI standard.1274 Even
though ZEVs are neither CI nor SI, we are maintaining the reasonable approach of selecting a
single certification pathway for ZEVs, and since CI is the most common application for heavy-
duty vocational vehicles, it is reasonable to continue with this existing approach.
For the final rule, we therefore calculate the primary program vocational standards for CI
vehicles just as we did for tractors, where the final CO2 emission standards for the CI regulatory
subcategories are calculated by determining the CO2 emissions from a technology package that
consists of both ICE-powered vehicles and ZEVs. The projected fraction of ZEVs that emit zero
grams CCh/ton-mile at the tailpipe are shown in Table 2-105. The remaining fraction of vehicles
in the technology package are ICE-powered vehicles that include the technologies listed in the
Preamble in Table II-1 (reflecting the GEM inputs for the individual technologies that make up
the technology packages that meet the Phase 2 MY 2027 CO2 CI vocational emission standards).
Thus, as noted above, in the technology packages, the ICE-powered vehicles emit at the
applicable Phase 2 MY 2027 CO2 emission standards, as shown in Table 2-110.
To calculate the standards for the primary program for SI vehicles, we are finalizing an
approach that sets the stringency of SI LHD and SI MHD vocational standards such that the
technology package for modeled potential compliance pathway has the same fraction of ICE and
ZEV vehicles regardless of whether a manufacturer is certifying SI or CI vocational vehicles;
this is similar to the proposed approach but is more targeted at address manufacturers concerns,
and it will appropriately reflect the urban, multi-purpose and regional categories. This is
described in greater detail below.
To calculate the LHD and MHD SI vocational standards, the fraction of ZEV vehicles in the
technology package (found in Table 2-105) is used to calculate a g/mi value based on each of the
urban, multi-purpose, and regional Phase 2 MY 2027 CI LHD and MHD standards. These values
are then subtracted from each of the corresponding urban, multi-purpose, and regional Phase 2
MY 2027 SI standards within the corresponding weight class. Equations are shown below for
MY 2032. The Phase 2 MY 2027 standards can be found in Table 2-110, and the ZEV adoption
1273 We are not finalizing the proposed revision to the definition of the variable "Std" in 40 CFR 1037.705 to
establish a common reference emission standard for vocational vehicles with tailpipe CO2 emissions deemed to be
zero (i.e., BEVs, FCEVs, and vehicles with engines fueled with pure hydrogen).
1274 See 40 CFR 1037.615(f).
414
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rates in the technology package can be found in Table 2-105 (the ZEV adoption rates for MY
2032 are also shown in the example equations below).
Equation 2-82 Calculation for MY 2032 SI LHD Urban Standard
MY2032 StdLHD SI Urban = ^2 MY2027 StdLHD si Urban " (^2 MY2027 StdufiD ci Urban * 60%)
Equation 2-83 Calculation for MY 2032 SI LHD Multi-Purpose Standard
MY2032 StdLHD si mp = ^2 MY2027 StdLHD si mp " (^2 MY2027 StdLHD CIMP * 60%)
Equation 2-84 Calculation for MY 2032 SI LHD Regional Standard
MY2032 StdLHD si Regional =
P2 MY2027 ¦S'tdLHDsiRegionai " (^2 MY2027 StdLHD CI Regionai * 60%)
Equation 2-85 Calculation for MY 2032 SI MHD Urban Standard
MY2032 StdMHD SI Urban = ^2 MY2027 StdMHD SI Urban " (^2 MY2027 StdMHD CI Urban * 40%)
Equation 2-86 Calculation for MY 2032 SI MHD Multi-Purpose Standard
MY2032 Stdty[y{D si mp = ^2 MY2027 StdLHD si mp " (f2 MY2027 StdLHD d * 40%)
Equation 2-87 Calculation for MY 2032 SI MHD Regional Standard
MY2032 .StdLHD si Regional —
P2 MY2027 StdMHD SI Regional " ( P2MY 2027 5tdMHD CI Regional * 40%)
This approach will continue to allow manufactures to certify ZEVs to the most appropriate
urban, regional, or multi-purpose subcategory, using good engineering judgement, so the
commenters concern about potential inequities for certifying categories other than multi-purpose
is addressed with this solution. It also has the benefit of maintaining the existing, clear approach
for certifying ZEVs to the CI standard. Lastly, this approach has the benefit of ensuring that
manufacturer compliance strategies that include utilization of ZEV technologies will be able to
comply with the same fraction of ZEVs regardless of whether the manufacturer also produces SI
or CI vehicles. We recognize that this approach corresponds to a decrease in the numerical
stringency of the SI standards compared to a calculation method that is comparable to the way
the CI standards are calculated; however, this approach is reasonable because SI applications are
a smaller portion of the fleet.
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2.10.4.2.2 Vocational Vehicles - Optional Custom Chassis Program
The HD GHG Phase 2 program includes optional custom chassis emission standards for eight
specific vocational vehicle types. Those vehicle types may either meet the primary vocational
vehicle program standards or, at the vehicle manufacturer's option, they may comply with these
optional standards. The Phase 2 optional custom chassis standards are numerically less stringent
than the primary HD GHG Phase 2 vocational vehicle standards, but the ABT program is more
restrictive for vehicles certified to these optional standards. Banking and trading of credits is not
permitted, with the exception that small businesses may use traded credits to comply. Averaging
is only allowed within each subcategory for vehicles certified to these optional standards. If a
manufacturer wishes to generate tradeable credits from the production of these vehicles, they
may certify them to the primary vocational vehicle standards.
In this final action, we are adopting more stringent standards for some, but not all, of these
optional custom chassis subcategories. We are revising MY 2027 emission standards and setting
new MY 2028 through MY 2032 and later emission standards for the school bus, other bus, and
refuse hauler optional custom chassis regulatory subcategories. We are not finalizing any
changes to the existing ABT program restrictions for the optional custom chassis regulatory
subcategories. Because vehicles certified to the optional custom chassis standards will continue
to have restricted credit use and can only be used for averaging within a specific custom chassis
regulatory subcategory, we do not have the same potential concern with respect to credit
generation as we do for the primary vocational vehicle standards regarding designation of
subcategory (i.e., regional, urban, or multi-purpose).
We determined the final optional custom chassis emission standards by multiplying the
fraction of ICE-powered vehicles in the technology package (by model year) by the applicable
Phase 2 MY 2027 CO2 emission standards, like we did for determining the tractor and vocational
vehicle emission standards. The fraction of ICE-powered vehicles is 1 minus the fraction of
ZEV-powered vehicles shown in Table 2-105.
As proposed, we are not setting new standards for motor homes certified to the optional
custom chassis regulatory subcategory, as described in RIA Chapter 2.9.1. Furthermore, we also
are not finalizing new standards for emergency vehicles certified to the optional custom chassis
regulatory subcategory due to our assessment that these vehicles have unpredictable operational
requirements and may have limited access to recharging facilities while handling emergency
situations in the MYs 2027-2032 timeframe. Finally, we are not adopting new standards for
mixed-use vehicle optional custom chassis regulatory subcategory because these vehicles are
designed to work inherently in an off-road environment (such as hazardous material equipment
or off-road drill equipment) or be designed to operate at low speeds such that it is unsuitable for
normal highway operation and therefore may have limited access to on-site depot or public
charging facilities in the MYs 2027-2032 timeframe.1275 We do not have concerns that
manufacturers could inappropriately circumvent the final vocational vehicle standards or final
optional custom chassis standards because vocational vehicles are built to serve a purpose. For
example, a manufacturer cannot certify a box truck to the emergency vehicle custom chassis
standards.
1275 Mixed-use vehicles must meet the criteria as described in 40 CFR 1037.105(h)(1), 1037.631(a)(1), and
1037.631(a)(2).
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We are not finalizing new standards for the optional custom chassis categories of Coach
Buses, Concrete Mixers/Pumpers and Mixed-Use Vehicles, as described in RIA Chapter 2.9.1
and 2.9.2; these optional standards will remain unchanged from the Phase 2 MY 2027+ CO2
emission standards.
2.10.5 Final CO2 Standards
We phased in the final standards gradually between MYs 2027 and 2032 to address potential
lead time concerns associated with feasibility under the modeled potential compliance pathway
for manufacturers to deploy ZEV technologies that include consideration of time necessary to
ramp up battery production, including the need to increase the availability of critical raw
materials, assure more resilient supply chains, and expand battery production facilities, as
discussed in Preamble Section II.D.2.ii. We also phased in the final standards recognizing that
under the modeled potential compliance pathway it will take time for installation of EVSE and
necessary supporting electrical infrastructure by the BEV purchasers and the associated electrical
utility. We projected BEV adoption starting in MY 2027 for certain applications where we
projected use of depot charging, and we project adoption of BEV in applications that will depend
on public charging and FCEVs in the technology packages starting in MY 2030 for select
applications that travel longer distances (i.e., sleeper cab tractors, and certain day cab tractors).
There has been only limited development of FCEVs for the HD market to date; therefore, our
assessment is that it is appropriate to provide manufacturers with additional lead time to design,
develop, and manufacture FCEV models, but that it is feasible to do so by MY 2030, as
discussed in Preamble Section II.D.3. With substantial Federal investment in low-GHG hydrogen
production (see RIA Chapter 1.8.2), we anticipate that the price of hydrogen fuel will fall in the
2030 to 2035 timeframe to make HD FCEVs cost-competitive with comparable ICE vehicles for
some duty cycles. We also note that the hydrogen infrastructure is expected to need additional
time to further develop, as discussed in greater detail in RIA Chapter 1.8, but we expect the
refueling needs can be met by MY 2030. We also recognize the positive market signal that
regulations can have on technology and recharging/refueling infrastructure development and
deployment.
The final standards are shown in Table 2-111 and Table 2-112 for vocational vehicles and
Table 2-113 and Table 2-114 for tractors.
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Table 2-111 Final MY 2027 through 2032+ Vocational Vehicle CO2 Emission Standards (grams/ton-mile)
Model Year
Subcategory
CI Light
CI Medium
CI Heavy
SI Light
SI Medium
Heavy
Heavy
Heavy
Heavy
Heavy
2027
Urban
305
224
269
351
263
Multi-Purpose
274
204
230
316
237
Regional
242
190
189
270
219
2028
Urban
286
217
269
332
256
Multi-Purpose
257
197
230
299
230
Regional
227
183
189
255
212
2029
Urban
268
209
234
314
248
Multi-Purpose
241
190
200
283
223
Regional
212
177
164
240
206
2030
Urban
250
201
229
296
240
Multi-Purpose
224
183
196
266
216
Regional
198
170
161
226
199
2031
Urban
198
178
207
244
217
Multi-Purpose
178
162
177
220
195
Regional
157
150
146
185
179
2032 and later
Urban
147
155
188
193
194
Multi-Purpose
132
141
161
174
174
Regional
116
131
132
144
160
Table 2-112 Final MY 2027 through 2032+ Optional Custom Chassis Vocational Vehicle CO2 Emission
Standards (grams/ton-mile)
Optional Custom
MY 2027
MY 2028
MY 2029
MY 2030
MY 2031
MY 2032
Chassis Vehicle
and Later
Category
School Bus
236
228
220
211
187
163
Other Bus
286
286
249
243
220
200
Coach Bus
205
205
205
205
205
205
Refuse Hauler
298
283
268
253
250
250
Concrete Mixer
316
316
316
316
316
316
Motor home
226
226
226
226
226
226
Mixed-use vehicle
316
316
316
316
316
316
Emergency vehicle
319
319
319
319
319
319
418
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Table 2-113 Final MY 2027 through MY 2032+ Tractor CO2 Emission Standards (grams/ton-mile)
Model
Year
Roof
Height
Class 7 All Cab Styles
Class 8 Day Cab
Class 8 Sleeper Cab
2027
Low Roof
96.2
73.4
64.1
Mid Roof
103.4
78.0
69.6
High Roof
100.0
75.7
64.3
2028
Low Roof
88.5
67.5
64.1
Mid Roof
95.1
71.8
69.6
High Roof
92.0
69.6
64.3
2029
Low Roof
84.7
64.6
64.1
Mid Roof
91.0
68.6
69.6
High Roof
88.0
66.6
64.3
2030
Low Roof
80.8
61.7
60.3
Mid Roof
86.9
65.5
65.4
High Roof
84.0
63.6
60.4
2031
Low Roof
69.3
52.8
56.4
Mid Roof
74.4
56.2
61.2
High Roof
72.0
54.5
56.6
2032 and
Later
Low Roof
57.7
44.0
48.1
Mid Roof
62.0
46.8
52.2
High Roof
60.0
45.4
48.2
Table 2-114 Final MY 2027 through MY 2032+ Heavy-Haul Tractor CO2 Emission Standards (grams/ton-
mile)
Model Year
CO2 Emission Standards (grams/ton-mile)
2027
48.3
2028
48.3
2029
47.8
2030
47.8
2031
46.9
2032 and Later
45.9
2.10.6 Summary of Costs to Meet the Final Emission Standards
In this subsection we show the cost of compliance for manufacturers for the final standards as
well as costs for purchasers.
In our analysis, the ICE vehicles include a suite of technologies that represent a vehicle that
meets the MY 2027 Phase 2 CO2 emission standards and HD 2027 NOx emission standards. We
accounted for these technology costs as part of the HD GHG Phase 2 final rule and the HD 2027
NOx rule. Therefore, our technology costs for the ICE vehicles in our analysis are considered to
be $0 because we did not add additional C02-reducing technologies to the ICE vehicles in the
technology packages for this final rule beyond those already required under the existing
regulations. The incremental cost of a heavy-duty ZEV in our analysis is the marginal cost of
ZEV powertrain components compared to ICE powertrain components on a comparable ICE
vehicle. This includes the removal of the associated costs of ICE-specific components from the
baseline vehicle and the addition of the ZEV components and associated costs. Chapter 2.3.2 and
2.4.3 includes the ICE powertrain and BEV powertrain cost estimates for each of the 101 HD
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vehicle types. Chapter 2.5.2 includes the FCEV powertrain cost projections for the coach buses
and some tractors.
2.10.6.1 Manufacturer Costs
Table 2-115 through Table 2-117 show the incremental ZEV RPE costs that include the direct
manufacturing costs that reflect learning effects, the indirect costs, and the IRA section 13502
Advanced Manufacturing Production Credit for each of the HD TRUCS vehicle types for MYs
2027, 2030, and 2032.1276 These values were then aggregated by regulatory group as shown in
Table 2-118 through Table 2-120 which show the ZEV technology costs for manufacturers,
relative to the reference case described in the Preamble in Section V.A.I and Chapter 4.3.1. The
vocational vehicle costs are presented in these tables at the regulatory group level (e.g., LHD), if
they were instead presented at the regulatory subcategory level (e.g. CI LHD MP, CI, LHD R,
and CI LHD U) the costs for each regulatory subcategory would be the same as the respective
regulatory group costs. The incremental ZEV adoption rates in these tables reflect the difference
between the ZEV adoption rates in the technology packages that support our final standards and
the reference case.
Table 2-115 Incremental ZEV RPE Costs for MY 2027 (2022$)
Vehicle ID
Regulatory
Group
ZEV
Adoption
Rate
Relative to
HD Fleet
Sales
ICE PT RPE
(per vehicle)
ZEV PT RPE
Including
Battery Tax
Credit (per
vehicle)
Incremental
ZEV RPE (per
vehicle)
01V Amb C14-5 MP
LHD
0.24%
$43,486
$38,606
-$4,879
02V Amb C12b-3 MP
LHD
0.35%
$41,518
$37,528
-$3,990
03V Amb C14-5 U
LHD
0.35%
$43,486
$37,369
-$6,117
04V Amb C12b-3 U
LHD
0.35%
$41,518
$36,254
-$5,264
05T Box C18 MP
HHD
0%
$82,838
$66,617
-$16,221
06T Box C18 R
HHD
0.04%
$82,838
$67,835
-$15,003
07T Box C16-7 MP
MHD
0.10%
$46,632
$48,579
$1,947
08T Box C16-7 R
MHD
0.08%
$46,632
$50,816
$4,184
09T Box C18 U
HHD
0%
$73,222
$65,465
-$7,757
10T Box C16-7 U
MHD
0.15%
$46,632
$47,652
$1,020
11T Box C12b-3 U
LHD
0.35%
$40,843
$35,644
-$5,200
12T Box C12b-3 R
LHD
0.35%
$40,843
$38,360
-$2,483
13T Box C12b-3 MP
LHD
0.35%
$40,843
$36,941
-$3,902
14T Box C14-5 U
LHD
0.35%
$40,982
$35,644
-$5,339
15T Box C14-5 R
LHD
0.24%
$40,982
$38,360
-$2,622
16T Box C14-5 MP
LHD
0.35%
$40,982
$36,941
-$4,041
17B Coach C18 R
HHD
0%
$65,186
NA
NA
18B Coach C18 MP
HHD
0%
$65,186
NA
NA
19C Mix C18 MP
HHD
0%
$73,222
$94,505
$21,283
20T Dump C18 U
HHD
0%
$82,838
$72,505
-$10,333
2IT Dump C18 MP
HHD
0%
$82,838
$73,058
-$9,779
22T Dump C16-7 MP
MHD
0.20%
$46,370
$64,952
$18,581
2 3 T_Dump_C18_U
HHD
0%
$73,222
$72,505
-$717
1276 Indirect costs are described in detail in RIA Chapter 3.2.2.
420
-------
24T Dump C16-7 U
MHD
0.07%
$46,370
$62,261
$15,891
25T Fire C18 MP
HHD
0%
$82,838
$75,222
-$7,616
26T Fire C18 U
HHD
0%
$73,222
$75,317
$2,095
27T Flat C16-7 MP
MHD
0.10%
$46,370
$48,440
$2,070
28T Flat C16-7 R
MHD
0.04%
$46,370
$50,676
$4,306
29T Flat C16-7 U
MHD
0.15%
$46,370
$46,471
$101
30Tractor DC C18
DC
0%
$87,274
$91,169
$3,895
31Tractor DC C17
DC
0%
$68,631
$78,218
$9,587
32Tractor SC C18
SC
0%
$90,534
NA
NA
33Tractor DC C18
DC
0%
$69,467
NA
NA
34T Ref C18 MP
HHD
0%
$68,925
$82,018
$13,093
35T Ref C16-7 MP
MHD
0.01%
$46,370
$66,829
$20,459
36T Ref C18 U
HHD
0%
$68,925
$82,018
$13,093
37T Ref C16-7 U
MHD
0.01%
$46,370
$66,249
$19,878
38RV C18 R
HHD
0%
$48,454
$112,615
$64,160
39RV C16-7 R
MHD
0.00%
$46,487
$114,050
$67,563
40RV C14-5 R
LHD
0.00%
$40,117
$78,307
$38,190
41Tractor DC C17
DC
0%
$68,631
NA
NA
42RV C18 MP
HHD
0%
$48,454
$112,615
$64,160
43RV C16-7 MP
MHD
0.00%
$46,487
$106,485
$59,997
44RV C14-5 MP
LHD
0.00%
$40,117
$73,481
$33,364
45Tractor DC C18
DC
0.00%
$90,534
NA
NA
46B School C18 MP
HHD
0%
$48,454
$67,496
$19,042
47B School C16-7 MP
MHD
0.38%
$46,487
$47,480
$992
48B School C14-5 MP
LHD
0.01%
$40,117
$38,606
-$1,510
49B_School_C12b-
3 MP
LHD
0.01%
$42,042
$37,719
-$4,323
5OB School C18 U
HHD
0%
$48,454
$65,364
$16,910
5 IB School C16-7 U
MHD
0.38%
$46,487
$47,480
$992
52B School C14-5 U
LHD
0.01%
$40,117
$37,369
-$2,748
53B School C12b-3 U
LHD
0.01%
$42,042
$36,445
-$5,598
54Tractor SC C18
SC
0%
$90,534
NA
$121,435
5 5B_Shuttle_C12b -
3 MP
LHD
0.06%
$42,042
$45,493
$3,451
56B Shuttle C14-5 U
LHD
0.11%
$40,117
$44,478
$4,361
57B Shuttle C12b-3 U
LHD
0.11%
$42,042
$43,554
$1,511
58B_Shuttle_C16-
7 MP
MHD
0.00%
$46,487
$63,142
$16,655
59B Shuttle C16-7 U
MHD
0.01%
$46,487
$60,251
$13,763
60S Plow C16-7 MP
MHD
0.02%
$46,370
$53,150
$6,780
61S Plow C18 MP
HHD
0%
$82,838
$89,436
$6,598
62S Plow C16-7 U
MHD
0.01%
$46,370
$51,239
$4,869
63 S Plow C18 U
HHD
0%
$73,222
$88,426
$15,204
64V Step C16-7 MP
MHD
0.15%
$46,271
$48,529
$2,258
65V Step C14-5 MP
LHD
0.35%
$40,117
$36,941
-$3,175
66V Step C12b-3 MP
LHD
0.06%
$41,518
$36,878
-$4,640
67V Step C16-7 U
MHD
0.15%
$46,271
$46,545
$274
68V Step C14-5 U
LHD
0.35%
$40,117
$35,644
-$4,473
69V Step C12b-3 U
LHD
0.06%
$41,518
$35,580
-$5,938
70S Sweep C16-7 U
MHD
0.15%
$46,370
$50,519
$4,149
71T Tanker C18 R
HHD
0%
$82,838
$70,513
-$12,325
421
-------
72T Tanker C18 MP
HHD
0%
$73,222
$69,756
-$3,466
73T Tanker C18 U
HHD
0%
$73,222
$69,547
-$3,675
74T Tow C18 R
HHD
0%
$85,428
$92,282
$6,854
75T Tow C16-7 R
MHD
0.00%
$46,370
$68,491
$22,121
76T Tow C18 U
HHD
0%
$73,222
$90,284
$17,062
77T Tow C16-7 U
MHD
0.04%
$46,370
$62,432
$16,062
78Tractor SC C18
SC
0%
$90,534
NA
NA
79Tractor SC C18
SC
0%
$90,534
NA
NA
80Tractor DC C18
DC
0%
$91,562
$133,921
$42,359
81Tractor DC C17
DC
0%
$68,631
NA
NA
82Tractor DC C18
DC
0%
$90,534
NA
NA
83Tractor DC C17
DC
0%
$68,631
$99,726
$31,095
84Tractor DC C18
DC
0%
$84,968
NA
NA
85B Transit C18 MP
HHD
0%
$65,186
$98,682
$33,496
86BT ransit_C16 -
7 MP
MHD
0.00%
$46,487
$79,671
$33,183
87B Transit C18 U
HHD
0%
$64,405
$98,682
$34,277
88B Transit C16-7 U
MHD
0.00%
$46,487
$74,923
$28,435
89T Utility C18 MP
HHD
0%
$82,838
$68,241
-$14,597
90T Utility C18 R
HHD
0%
$82,838
$69,220
-$13,618
91T Utility C16-7 MP
MHD
0.15%
$46,370
$50,884
$4,514
92T Utility C16-7 R
MHD
0.00%
$46,370
$52,973
$6,603
93T Utility C14-5 MP
LHD
0.35%
$43,486
$38,663
-$4,822
94T_Utility_C12b-
3 MP
LHD
0.24%
$41,518
$37,666
-$3,852
95T Utility C14-5 R
LHD
0.00%
$43,486
$39,916
-$3,569
96T Utility C12b-3 R
LHD
0.00%
$41,518
$39,853
-$1,665
97T Utility C18 U
HHD
0%
$73,222
$67,577
-$5,645
98T Utility C16-7 U
MHD
0.15%
$46,370
$49,260
$2,890
99T Utility C14-5 U
LHD
0.35%
$43,486
$37,623
-$5,863
100T_Utility_C12b-
3 U
LHD
0.24%
$41,518
$36,486
-$5,032
lOlTractor DC C18
DC
0%
$84,968
$79,329
-$5,639
Note: The NA values represent vehicles that are either considered to be FCEVs or publicly-charged BEVs and
therefore are not included in the MY 2027 technology package
Table 2-116 Incremental ZEV RPE Costs for MY 2030 (2022$)
Vehicle ID
Regulatory
ZEV
ICE PT RPE
ZEV PT RPE
Incremental
Group
Adoption
Rate
(per vehicle)
Including
Battery Tax
Credit (per
vehicle)
ZEV RPE (per
vehicle)
01V Amb C14-5 MP
LHD
0.60%
$43,051
$31,360
-$11,691
02V Amb C12b-3 MP
LHD
0.60%
$41,103
$30,552
-$10,551
03V Amb C14-5 U
LHD
0.60%
$43,051
$30,441
-$12,610
04V Amb C12b-3 U
LHD
0.60%
$41,103
$29,606
-$11,497
05T Box C18 MP
HHD
0.08%
$82,009
$53,225
-$28,784
06T Box C18 R
HHD
0.05%
$82,009
$54,129
-$27,880
07T Box C16-7 MP
MHD
0.25%
$46,166
$39,065
-$7,100
08T Box C16-7 R
MHD
0.13%
$46,166
$40,726
-$5,440
422
-------
09T Box C18 U
HHD
0.06%
$72,490
$52,370
-$20,120
10T Box C16-7 U
MHD
0.25%
$46,166
$38,377
-$7,789
11T Box C12b-3 U
LHD
0.60%
$40,435
$29,160
-$11,275
12T Box C12b-3 R
LHD
0.60%
$40,435
$31,177
-$9,258
13T Box C12b-3 MP
LHD
0.60%
$40,435
$30,124
-$10,311
14T Box C14-5 U
LHD
0.60%
$40,573
$29,160
-$11,413
15T Box C14-5 R
LHD
0.60%
$40,573
$31,177
-$9,396
16T Box C14-5 MP
LHD
0.60%
$40,573
$30,124
-$10,449
17B Coach C18 R
HHD
0.02%
$64,534
$103,599
$39,065
18B Coach C18 MP
HHD
0.01%
$64,534
$119,961
$55,427
19C Mix C18 MP
HHD
0.06%
$72,490
$73,931
$1,442
20T Dump C18 U
HHD
0.10%
$82,009
$57,596
-$24,413
2IT Dump C18 MP
HHD
0.13%
$82,009
$58,008
-$24,002
22T Dump C16-7 MP
MHD
0.18%
$45,906
$51,205
$5,299
23T Dump C18 U
HHD
0.05%
$72,490
$57,596
-$14,893
24T Dump C16-7 U
MHD
0.06%
$45,906
$49,207
$3,301
25T Fire C18 MP
HHD
0.03%
$82,009
$59,614
-$22,396
26T Fire C18 U
HHD
0.03%
$72,490
$59,685
-$12,805
27T Flat C16-7 MP
MHD
0.25%
$45,906
$38,945
-$6,961
28T Flat C16-7 R
MHD
0.10%
$45,906
$40,606
-$5,300
29T Flat C16-7 U
MHD
0.25%
$45,906
$37,484
-$8,423
30Tractor DC C18
DC
0.53%
$86,401
$72,729
-$13,672
31Tractor DC C17
DC
0.27%
$67,944
$62,202
-$5,742
32Tractor SC C18
SC
0.47%
$89,628
$140,669
$51,040
33Tractor DC C18
DC
0.34%
$68,773
$90,955
$22,182
34T Ref C18 MP
HHD
0.04%
$68,236
$64,494
-$3,742
35T Ref C16-7 MP
MHD
0.00%
$45,906
$52,600
$6,693
36T Ref C18 U
HHD
0.04%
$68,236
$64,494
-$3,742
37T Ref C16-7 U
MHD
0.01%
$45,906
$52,168
$6,262
38RV C18 R
HHD
0.00%
$47,970
$87,083
$39,113
39RV C16-7 R
MHD
0.00%
$46,022
$87,687
$41,664
40RV C14-5 R
LHD
0.00%
$39,716
$60,837
$21,121
41Tractor DC C17
DC
0.03%
$67,944
$114,640
$46,695
42RV C18 MP
HHD
0.00%
$47,970
$87,083
$39,113
43RV C16-7 MP
MHD
0.00%
$46,022
$82,070
$36,047
44RV C14-5 MP
LHD
0.00%
$39,716
$57,254
$17,538
45Tractor DC C18
DC
0.00%
$89,629
$151,102
$61,473
46B School C18 MP
HHD
0.01%
$47,970
$53,583
$5,613
47B School C16-7 MP
MHD
0.65%
$46,022
$38,259
-$7,763
48B School C14-5 MP
LHD
0.03%
$39,716
$31,360
-$8,356
49B_School_C12b-
3 MP
LHD
0.03%
$41,622
$30,716
-$10,906
5OB School C18 U
HHD
0.03%
$47,970
$52,000
$4,030
5 IB School C16-7 U
MHD
0.65%
$46,022
$38,259
-$7,763
52B School C14-5 U
LHD
0.03%
$39,716
$30,441
-$9,275
53B School C12b-3 U
LHD
0.03%
$41,622
$29,770
-$11,852
54Tractor SC C18
SC
0.00%
$89,628
$162,140
$72,512
5 5B_Shuttle_C12b -
3 MP
LHD
0.11%
$41,622
$36,488
-$5,134
56B Shuttle C14-5 U
LHD
0.19%
$39,716
$35,719
-$3,996
57B Shuttle C12b-3 U
LHD
0.19%
$41,622
$35,048
-$6,574
423
-------
58B_Shuttle_C16-
7 MP
MHD
0.00%
$46,022
$49,888
$3,866
59B Shuttle C16-7 U
MHD
0.01%
$46,022
$47,742
$1,719
60S Plow C16-7 MP
MHD
0.02%
$45,906
$42,443
-$3,463
61S Plow C18 MP
HHD
0.00%
$82,009
$70,168
-$11,842
62S Plow C16-7 U
MHD
0.01%
$45,906
$41,024
-$4,883
63 S Plow C18 U
HHD
0.00%
$72,490
$69,418
-$3,072
64V Step C16-7 MP
MHD
0.25%
$45,808
$39,001
-$6,807
65V Step C14-5 MP
LHD
0.60%
$39,716
$30,124
-$9,592
66V Step C12b-3 MP
LHD
0.11%
$41,103
$30,069
-$11,034
67V Step C16-7 U
MHD
0.25%
$45,808
$37,528
-$8,281
68V Step C14-5 U
LHD
0.60%
$39,716
$29,160
-$10,556
69V Step C12b-3 U
LHD
0.11%
$41,103
$29,106
-$11,997
70S Sweep C16-7 U
MHD
0.25%
$45,906
$40,489
-$5,417
71T Tanker C18 R
HHD
0.06%
$82,009
$56,117
-$25,892
72T Tanker C18 MP
HHD
0.08%
$72,490
$55,556
-$16,934
73T Tanker C18 U
HHD
0.06%
$72,490
$55,400
-$17,089
74T Tow C18 R
HHD
0.03%
$84,574
$72,281
-$12,293
75T Tow C16-7 R
MHD
0.00%
$45,906
$53,833
$7,927
76T Tow C18 U
HHD
0.03%
$72,490
$70,797
-$1,693
77T Tow C16-7 U
MHD
0.03%
$45,906
$49,335
$3,428
78Tractor SC C18
SC
0.66%
$89,628
$125,005
$35,376
79Tractor SC C18
SC
0.00%
$89,628
$153,939
$64,310
80Tractor DC C18
DC
0.00%
$90,646
$104,227
$13,581
81Tractor DC C17
DC
0.23%
$67,944
$86,275
$18,330
82Tractor DC C18
DC
0.34%
$89,629
$105,831
$16,202
83Tractor DC C17
DC
0.14%
$67,944
$78,172
$10,228
84Tractor DC C18
DC
0.82%
$84,119
$72,499
-$11,620
85B Transit C18 MP
HHD
0.40%
$64,534
$76,738
$12,204
86BT ransit_C16 -
7 MP
MHD
0.00%
$46,022
$62,160
$16,138
87B Transit C18 U
HHD
0.14%
$63,761
$76,738
$12,977
88B Transit C16-7 U
MHD
0.00%
$46,022
$58,635
$12,613
89T Utility C18 MP
HHD
0.08%
$82,009
$54,431
-$27,579
90T Utility C18 R
HHD
0.03%
$82,009
$55,157
-$26,852
91T Utility C16-7 MP
MHD
0.25%
$45,906
$40,760
-$5,146
92T Utility C16-7 R
MHD
0.10%
$45,906
$42,312
-$3,595
93T Utility C14-5 MP
LHD
0.60%
$43,051
$31,402
-$11,649
94T_Utility_C12b-
3 MP
LHD
0.60%
$41,103
$30,654
-$10,449
95T Utility C14-5 R
LHD
0.04%
$43,051
$32,333
-$10,718
96T Utility C12b-3 R
LHD
0.04%
$41,103
$32,278
-$8,825
97T Utility C18 U
HHD
0.03%
$72,490
$53,937
-$18,552
98T Utility C16-7 U
MHD
0.25%
$45,906
$39,555
-$6,352
99T Utility C14-5 U
LHD
0.60%
$43,051
$30,630
-$12,421
100T_Utility_C12b-
3 U
LHD
0.60%
$41,103
$29,778
-$11,325
lOlTractor DC C18
DC
0.08%
$84,119
$63,828
-$20,290
424
-------
Table 2-117 Incremental ZEV RPE Costs for MY 2032 (2022$)
Vehicle ID
Regulatory
ZEV
ICE PT RPE
ZEV PT RPE
Incremental
Group
Adoption
Rate
(per vehicle)
Including
Battery Tax
Credit (per
vehicle)
ZEV RPE (per
vehicle)
01V Amb C14-5 MP
LHD
1.16%
$42,616
$31,938
-$10,679
02V Amb C12b-3 MP
LHD
1.16%
$40,688
$31,044
-$9,643
03V Amb C14-5 U
LHD
1.16%
$42,616
$30,911
-$11,706
04V Amb C12b-3 U
LHD
1.16%
$40,688
$29,987
-$10,701
05T Box C18 MP
HHD
0.23%
$81,181
$54,950
-$26,231
06T Box C18 R
HHD
0.11%
$81,181
$55,961
-$25,220
07T Box C16-7 MP
MHD
0.30%
$45,699
$40,148
-$5,551
08T Box C16-7 R
MHD
0.22%
$45,699
$42,004
-$3,695
09T Box C18 U
HHD
0.13%
$71,758
$53,995
-$17,763
10T Box C16-7 U
MHD
0.53%
$45,699
$39,378
-$6,321
11T Box C12b-3 U
LHD
1.16%
$40,026
$29,479
-$10,547
12T Box C12b-3 R
LHD
1.16%
$40,026
$31,733
-$8,293
13T Box C12b-3 MP
LHD
1.16%
$40,026
$30,556
-$9,471
14T Box C14-5 U
LHD
1.16%
$40,163
$29,479
-$10,684
15T Box C14-5 R
LHD
0.65%
$40,163
$31,733
-$8,430
16T Box C14-5 MP
LHD
1.16%
$40,163
$30,556
-$9,607
17B Coach C18 R
HHD
0.03%
$63,882
$111,645
$47,763
18B Coach C18 MP
HHD
0.03%
$63,882
$113,169
$49,287
19C Mix C18 MP
HHD
0.13%
$71,758
$78,093
$6,335
20T Dump C18 U
HHD
0.20%
$81,181
$59,836
-$21,345
2IT Dump C18 MP
HHD
0.36%
$81,181
$60,296
-$20,885
22T Dump C16-7 MP
MHD
0.20%
$45,443
$53,738
$8,296
23T Dump C18 U
HHD
0.07%
$71,758
$59,836
-$11,922
24T Dump C16-7 U
MHD
0.07%
$45,443
$51,505
$6,062
25T Fire C18 MP
HHD
0.05%
$81,181
$62,091
-$19,090
26T Fire C18 U
HHD
0.05%
$71,758
$62,170
-$9,588
27T Flat C16-7 MP
MHD
0.30%
$45,443
$40,036
-$5,407
28T Flat C16-7 R
MHD
0.11%
$45,443
$41,892
-$3,551
29T Flat C16-7 U
MHD
0.53%
$45,443
$38,402
-$7,041
30Tractor DC C18
DC
0.46%
$85,528
$75,533
-$9,995
31Tractor DC C17
DC
0.23%
$67,258
$64,983
-$2,275
32Tractor SC C18
SC
1.07%
$88,723
$151,842
$63,119
33Tractor DC C18
DC
1.03%
$68,078
$96,273
$28,195
34T Ref C18 MP
HHD
0.03%
$67,547
$67,766
$220
35T Ref C16-7 MP
MHD
0.01%
$45,443
$55,297
$9,854
36T Ref C18 U
HHD
0.03%
$67,547
$67,766
$220
37T Ref C16-7 U
MHD
0.01%
$45,443
$54,815
$9,372
38RV C18 R
HHD
0.00%
$47,485
$93,186
$45,700
39RV C16-7 R
MHD
0.00%
$45,558
$94,477
$48,919
40RV C14-5 R
LHD
0.00%
$39,314
$64,883
$25,568
41Tractor DC C17
DC
0.40%
$67,258
$109,002
$41,744
42RV C18 MP
HHD
0.00%
$47,485
$93,186
$45,700
43RV C16-7 MP
MHD
0.00%
$45,558
$88,199
$42,641
44RV C14-5 MP
LHD
0.00%
$39,314
$60,878
$21,564
425
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45Tractor DC C18
DC
0.21%
$88,723
$143,789
$55,065
46B School C18 MP
HHD
0.02%
$47,485
$55,744
$8,258
47B School C16-7 MP
MHD
1.37%
$45,558
$39,233
-$6,324
48B School C14-5 MP
LHD
0.05%
$39,314
$31,938
-$7,377
49B_School_C12b-
3 MP
LHD
0.05%
$41,201
$31,198
-$10,004
5OB School C18 U
HHD
0.05%
$47,485
$53,974
$6,489
5 IB School C16-7 U
MHD
1.37%
$45,558
$39,233
-$6,324
52B School C14-5 U
LHD
0.05%
$39,314
$30,911
-$8,404
53B School C12b-3 U
LHD
0.05%
$41,201
$30,140
-$11,061
54Tractor SC C18
SC
0.00%
$88,723
$175,840
$87,117
5 5B_Shuttle_C12b -
3 MP
LHD
0.21%
$41,201
$37,649
-$3,552
56B Shuttle C14-5 U
LHD
0.36%
$39,314
$36,810
-$2,504
57B Shuttle C12b-3 U
LHD
0.36%
$41,201
$36,040
-$5,162
58B_Shuttle_C16-
7 MP
MHD
0.00%
$45,558
$52,231
$6,673
59B Shuttle C16-7 U
MHD
0.01%
$45,558
$49,832
$4,274
60S Plow C16-7 MP
MHD
0.03%
$45,443
$43,945
-$1,498
61S Plow C18 MP
HHD
0.00%
$81,181
$73,887
-$7,294
62S Plow C16-7 U
MHD
0.01%
$45,443
$42,359
-$3,084
63 S Plow C18 U
HHD
0.00%
$71,758
$73,048
$1,291
64V Step C16-7 MP
MHD
0.53%
$45,345
$40,113
-$5,233
65V Step C14-5 MP
LHD
1.16%
$39,314
$30,556
-$8,759
66V Step C12b-3 MP
LHD
0.20%
$40,688
$30,505
-$10,183
67V Step C16-7 U
MHD
0.53%
$45,345
$38,466
-$6,879
68V Step C14-5 U
LHD
1.16%
$39,314
$29,479
-$9,836
69V Step C12b-3 U
LHD
0.20%
$40,688
$29,428
-$11,260
70S Sweep C16-7 U
MHD
0.53%
$45,443
$41,761
-$3,681
71T Tanker C18 R
HHD
0.05%
$81,181
$58,183
-$22,998
72T Tanker C18 MP
HHD
0.23%
$71,758
$57,555
-$14,202
73T Tanker C18 U
HHD
0.13%
$71,758
$57,382
-$14,376
74T Tow C18 R
HHD
0.05%
$83,719
$76,248
-$7,471
75T Tow C16-7 R
MHD
0.00%
$45,443
$56,675
$11,233
76T Tow C18 U
HHD
0.05%
$71,758
$74,590
$2,833
77T Tow C16-7 U
MHD
0.04%
$45,443
$51,648
$6,205
78Tractor SC C18
SC
2.10%
$88,723
$134,335
$45,612
79Tractor SC C18
SC
1.55%
$88,723
$145,647
$56,924
80Tractor DC C18
DC
0.02%
$89,730
$111,064
$21,334
81Tractor DC C17
DC
0.71%
$67,258
$91,888
$24,630
82Tractor DC C18
DC
1.03%
$88,723
$112,326
$23,603
83Tractor DC C17
DC
0.23%
$67,258
$82,832
$15,574
84Tractor DC C18
DC
2.53%
$83,269
$75,423
-$7,846
85B Transit C18 MP
HHD
0.84%
$63,882
$81,623
$17,741
86BT ransit_C16 -
7 MP
MHD
0.00%
$45,558
$65,947
$20,389
87B Transit C18 U
HHD
0.30%
$63,117
$81,623
$18,506
88B Transit C16-7 U
MHD
0.00%
$45,558
$62,007
$16,449
89T Utility C18 MP
HHD
0.23%
$81,181
$56,298
-$24,883
90T Utility C18 R
HHD
0.02%
$81,181
$57,110
-$24,071
91 T_Utility_C16 -7MP
MHD
0.30%
$45,443
$42,064
-$3,379
426
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92T Utility C16-7 R
MHD
0.11%
$45,443
$43,798
-$1,645
93T Utility C14-5 MP
LHD
1.16%
$42,616
$31,985
-$10,631
94T_Utility_C12b-
3 MP
LHD
1.16%
$40,688
$31,159
-$9,529
95T Utility C14-5 R
LHD
0.04%
$42,616
$33,025
-$9,591
96T Utility C12b-3 R
LHD
0.04%
$40,688
$32,974
-$7,714
97T Utility C18 U
HHD
0.05%
$71,758
$55,746
-$16,011
98T Utility C16-7 U
MHD
0.53%
$45,443
$40,717
-$4,726
99T Utility C14-5 U
LHD
1.16%
$42,616
$31,122
-$11,495
100T_Utility_C12b-
3 U
LHD
1.16%
$40,688
$30,179
-$10,508
lOlTractor DC C18
DC
0.14%
$83,269
$65,732
-$17,537
Table 2-118 Manufacturer Costs to Meet the Final MY 2027 Standards Relative to the Reference Case
(2022$)
Regulatory Group
Incremental
Per-ZEV
Fleet-Average Per-
ZEV
Manufacturer RPE
Vehicle
Adoption Rate
on Average
Manufacturer RPE
in Technology
Package
LHD Vocational Vehicles
7%
-$4,100
-$283
MHD Vocational Vehicles
6%
$3,959
$242
HHD Vocational Vehicles
0%
N/A
$0
Day Cab and Heavy Haul
0%
N/A
$0
Tractors
Sleeper Cab Tractors
0%
N/A
$0
Note: The average costs represent the average across the regulatory group. For example, the
first row represents the average across all LHD vocational vehicles
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Table 2-119 Manufacturer Costs to Meet the Final MY 2030 Standards Relative to the Reference Case
(2022$)
Incremental
ZEV Adoption
Per-ZEV
Fleet-Average Per-
Regulatory Group
Rate in
Manufacturer RPE
Vehicle Manufacturer
Technology
on Average
RPE
Package
LHD Vocational Vehicles
7%
-$10,637
-$723
MHD Vocational Vehicles
5%
-$6,164
-$296
HHD Vocational Vehicles
4%
-$7,582
-$273
Day Cab and Heavy Haul
Tractors
7%
$32
$2
Sleeper Cab Tractors
4%
$41,877
$1,717
Note: The average costs represent the average across the regulatory group. For example, the first
row represents the average across all LHD vocational vehicles
Table 2-120 Manufacturer Costs to Meet the Final MY 2032 Standards Relative to the Reference Case
(2022$)
Regulatory Group
Incremental
Per-ZEV
Fleet-Average Per-
ZEV Adoption
Manufacturer RPE
Vehicle Manufacturer
Rate in
on Average
RPE
Technology
Package
LHD Vocational Vehicles
30%
-$9,776
-$2,923
MHD Vocational Vehicles
20%
-$5,033
-$981
HHD Vocational Vehicles
16%
-$3,989
-$654
Day Cab and Heavy Haul
30%
$10,816
$3,202
Tractors
Sleeper Cab Tractors
20%
$53,295
$10,819
Note: The average costs represent the average across the regulatory group. For example, the first
row represents the average across all LHD vocational vehicles.
2.10.6.2 Purchaser Costs
We also evaluated the costs of the final standards for purchasers on average by regulatory
group. Our assessment of the upfront purchaser costs includes the incremental cost of a ZEV
relative to a comparable ICE vehicle after accounting for the two IRA tax credits (IRA section
13502, "Advanced Manufacturing Production Credit," and IRA section 13403, "Qualified
Commercial Clean Vehicles") and the associated EVSE costs (including the tax credit under IRA
section 13404, "Alternative Fuel Refueling Property Credit"), if applicable. We also assessed the
incremental annual operating savings of a ZEV relative to a comparable ICE vehicle. The
payback periods shown reflect the number of years it will take for the annual operating savings
to offset the increase in total upfront costs for the purchaser. The results of this analysis are
shown in Table 2-121 through Table 2-123.
428
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Table 2-121 MY 2027 Purchaser Per-ZEV Upfront Costs, Operating Costs, and Payback Period (2022$)
Regulatory Group
Adoption
Incremental
Total
Annual
Payback
Rate in
Per-ZEV RPE
EVSE
Incremental
Incremental
Period
Technology
Cost on
Costs Per-
Upfront Per-
Operating
(year) on
Package
Average
ZEV on
ZEV Costs on
Costs Per-
Average
(before IRA
Average
Average
ZEV on
Purchase Tax
Including
Average
Credit and
Taxes
Taxes)
LHD Vocational
17%
-$4,100
$11,623
$7,165
-$3,383
3
Vehicles
MHD Vocational
13%
$3,959
$17,084
$17,283
-$4,692
5
Vehicles
HHD Vocational
0%
N/A
N/A
N/A
N/A
N/A
Vehicles
Day Cab and Heavy
0%
N/A
N/A
N/A
N/A
N/A
Haul Tractors
Sleeper Cab Tractors
0%
N/A
N/A
N/A
N/A
N/A
Note: The average costs represent the average across the regulatory group, for example the first row represents the
average across all LHD vocational vehicles.
429
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Table 2-122 MY 2030 Purchaser Per-ZEV Upfront Costs, Operating Costs, and Payback Period (2022$)
Regulatory Group
Adoption
Rate in
Technology
Package
Incremental
Per-ZEV RPE
Cost on Average
(before IRA
Purchase Tax
Credit and
Taxes)
EVSE Costs
Per-ZEV on
Average
Total
Incremental
Upfront Per-
ZEV Costs on
Average
Including
Taxes
Annual
Incremental
Operating
Costs Per-
ZEV on
Average
Payback
Period
(year) on
Average
LHD Vocational
Vehicles
32%
-$10,637
$11,800
$629
-$3,626
1
MHD Vocational
Vehicles
22%
-$6,164
$16,133
$9,325
-$5,020
3
HHD Vocational
Vehicles
15%
-$7,582
$48,099
$34,532
-$10,412
4
Day Cab and Heavy Haul
Tractors
16%
$32
$14,272
$7,168
-$5,708
3
Sleeper Cab Tractors
6%
$41,877
$0
$11,709
-$9,034
3
Note: The average costs represent the average across the regulatory group, for example the first row represents the
average across all LHD vocational vehicles.
Table 2-123 MY 2032 Purchaser Per-ZEV Upfront Costs, Operating Costs, and Payback Period (2022$)
Regulatory
Group
Adoption
Rate in
Incremental
Per-ZEV RPE
EVSE Costs
Per-ZEV on
Total
Incremental
Annual
Incremental
Payback
Period (year)
Technology
Package
Cost on
Average
(before IRA
Purchase Tax
Credit and
Taxes)
Average
Upfront Per-
ZEV Costs on
Average
Including
Taxes
Operating
Costs on
Average
on Average
LHD
60%
-$9,776
$11,736
$1,470
-$3,682
2
Vocational
Vehicles
MHD
40%
-$5,033
$15,304
$9,678
-$5,132
3
Vocational
Vehicles
HHD
30%
-$3,989
$46,204
$34,505
-$10,514
4
Vocational
Vehicles
Day Cab and
40%
$10,816
$5,952
$4,418
-$5,516
2
Heavy Haul
Tractors
Sleeper Cab
25%
$53,295
$0
$22,366
-$8,303
5
Tractors
Note: The average costs represent the average across the regulatory group, for example the first row represents the
average across all LHD vocational vehicles.
As shown in Table 2-123, under the final rule, we estimate that the average upfront cost per
vehicle to purchase a new MY 2032 vocational ZEV and associated EVSE compared to a
comparable ICE vehicle (after accounting for three IRA tax credits: IRA section 13502,
430
-------
"Advanced Manufacturing Production Credit;" IRA section 13403, "Qualified Commercial
Clean Vehicles;" and IRA section 13404, "Alternative Fuel Refueling Property Credit"), will be
offset by operational costs (i.e., savings that come from the lower costs to operate, maintain, and
repair ZEV technologies), such that we expect the upfront cost increase will be recouped due to
operating savings in two to four years, on average for vocational vehicles. For a new MY 2032
day cab tractor ZEV and associated EVSE as applicable, we estimate the average incremental
upfront cost per vehicle will be recovered in two years, on average. Similarly, for sleeper cab
tractors, we estimate that the initial cost increase will be recouped in five years.
2.11 Additional Example Compliance Pathway Technology Packages to Support the Final
Standards
While the potential compliance pathway's technology packages that include both vehicles
with ICE and ZEV technologies discussed in preamble Section II.F.l and RIA Chapter 2.10
support the feasibility of the final standards and was modeled for rulemaking purposes, there are
many other examples of possible compliance pathways for meeting the final standards that do
not involve the widespread adoption of BEV and FCEV technologies. In this section and
preamble Section II.F.4, we provide further support for the feasibility of the final standards by
describing examples of additional potential compliance pathways that are based on nationwide
production volumes, including compliance pathways that involve only technologies for vehicles
with ICE across a range of electrification (i.e., without producing additional ZEVs to comply
with this rule).
In this section, we discuss our analysis for the technologies included in the additional example
compliance pathway of the impacts on reductions of GHG emissions; the technical feasibility
and technology effectiveness; the lead time necessary to implement the technologies; costs to
manufacturers; and willingness to purchase (including purchaser costs and payback). In short,
EPA finds that, even without manufacturers producing additional ZEVs to comply with this rule,
it would be technologically feasible to meet the final standards in the lead time provided and
taking into consideration compliance costs. Regarding reductions of GHG emissions, these
additional example potential compliance pathways meet the final Phase 3 MY 2027 through MY
2032 and later CO2 emission standards, and therefore achieve the same level of vehicle CO2
emission reductions and downstream CO2 emission reductions as presented in preamble Section
V and RIA Chapter 4. Regarding technical feasibility and lead time, depending on the
technology, we determined that either no further development of the technology is required (only
further application) or the technology is technically feasible and being actively developed by
manufacturers to be commercially available for MY 2027 and later, and that there is sufficient
lead time. Similar to the approach we considered for BEVs and FCEVs in this preamble Section
II, for relevant technologies we also included a phased approach to provide lead time to meet the
corresponding charging and refueling infrastructure needs under the final rule's additional
example potential compliance pathways. Regarding costs of compliance, consistent with our
Phase 2 assessment, we conclude that the estimated costs for all model years are reasonable for
one of the additional example potential compliance pathways, for example based on our estimate
that the MY 2032 fleet average per-vehicle cost to manufacturers by regulatory group will be
$3,800 for LHD; $7,600 for MHD vocational vehicles; and $7,700 for HHD vocational vehicles,
and range between $10,300 for day cab tractors and $10,400 for sleeper cab tractors. For another
additional example potential compliance pathway, which we developed and assessed because
manufacturers may choose to offer technologies (such as PHEVs) that have a higher projected
431
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upfront cost but also have a shorter payback period, we estimated higher costs of compliance
(e.g., approximately 18 percent of the price of a new tractor for MY 2032) and conclude these
costs are also reasonable here given consideration of the corresponding business case for
manufacturers to successfully deploy these technologies when considering willingness to
purchase, including the payback period of these technologies and the IRA purchaser tax credits
for PHEVs. Regarding our assessment of impacts on purchasers and willingness to purchase, the
technologies we assessed generally pay back within 10 years or less. As we explain elsewhere in
this preamble Section II, businesses that operate HD vehicles are under competitive pressure to
reduce operating costs, which should encourage purchasers to identify and adopt vehicle
technologies that provide a reasonable payback period. For H2-ICE tractors, our assessment is
that the operating costs exceed the operating costs of ICE tractors, but there may be other reasons
that purchasers would consider this technology such as the vehicles emit nearly zero CO2
emissions at the tailpipe, the low engine-out exhaust emissions from H2-ICE vehicles provide
the opportunity for efficient and durable after-treatment systems, and the efficiency of H2-ICE
vehicles may continue to improve with time. Overall, the fact that such a fleet as the examples
assessed in this section are possible underscores both the feasibility and the flexibility of the
performance-based standards, and confirms that manufacturers are likely to continue to offer
vehicles with a diverse range of technologies, including advanced vehicle with ICE technologies
as well as ZEVs for the duration of these standards and beyond.
The vehicles considered in these additional pathways include a suite of technologies ranging
from improvements in aerodynamics and tire rolling resistance in ICE tractors, to the use of
lower carbon fuels like CNG and LNG, to hybrid powertrains (HEV and PHEV) and H2-ICE. As
described below these technologies either exist today or are actively being developed by
manufacturers to be commercially available for MY 2027 and later.
This section presents our analysis of the effectiveness of reducing CO2 emissions, the
associated lead time, and the technology package costs for the technologies considered in these
additional possible pathways in Chapter 2.11.1 and 2.11.2 (we discuss the technologies
themselves in preamble RIA Chapter 1). We then created technology packages based on
adoption rates of aggregated individual technologies into three scenarios for MYs 2027, 2030,
and 2032 that represent additional example potential compliance pathways that further support
the feasibility of the final standards in Chapter 2.11.3. The technology packages and adoption
rates include a mix of vehicles with ICE technologies. For example, the additional example
potential compliance pathways include some vocational vehicles with the technology package
that supported the Phase 2 MY 2027 CO2 vocational vehicle emission standards (shown in
Chapter 2.3, and that include technologies such as low rolling resistance tires; tire inflation
systems; efficient engines, transmissions, and drivetrains; weight reduction; and idle reduction
technologies) as well as additional natural gas engine, H2-ICE vehicle, hybrid powertrain, and
PHEV technologies for vocational vehicles. For another example, the additional example
potential compliance pathways include tractors with further aerodynamic and tire improvements
in addition to the technology package that supported the Phase 2 MY 2027 CO2 tractor emission
standards (shown in Chapter 2.3, and that include technologies such as improved aerodynamics;
low rolling resistance tires; tire inflation systems; efficient engines, transmissions, drivetrains,
and accessories; and extended idle reduction for sleeper cabs) as well as additional natural gas
engine, H2-ICE vehicle, hybrid powertrain, and PHEV technologies for tractors. The technology
packages also include our projected reference case (see RIA Chapter 4) ZEV adoption rates.
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Scenario 1 meets the MY 2032 standards with higher adoption of vehicles with H2-ICE
technology. Scenario 2 meets the MY 2032 standards with higher adoption of PHEV technology.
We also developed another set of technology packages that do not include our projected
reference case ZEV adoption rates (i.e., they are potential compliance pathways that support the
feasibility of the standards with only technologies for vehicles with ICE, with zero nationwide
adoption of ZEV technologies) is also presented in RIA Chapter 2.11.3. Finally, we assessed the
manufacturer costs under these additional example potential compliance pathways, in Chapter
2.11.4, and purchaser costs and payback in Chapter 2.11.5.
The vehicle manufacturers that certified to EPA standards for MY 2022 and/or MY 2023 are
those listed in Table 2-124. Manufacturers used a wide variety of technologies to meet the
standards. The manufacturer names with indicate that they have EPA certifications for
vehicles that use natural gas. The manufacturer names with 'A' indicate they have EPA
certifications for vehicles with hybrid powertrains. Since the public certification data for these
MYs doesn't identify which vehicles are certified with hybrid powertrains, we relied on
information identified in Chapter 1.4 of the RIA. As for hydrogen-fueled internal combustion
engines, no manufacturers have certified to EPA standards for MY 2022 with the technology,
however a number of manufacturers have indicated that they are developing an engine that can
run on hydrogen.1277 Finally, there are a number of manufacturers that have certified ICE
vehicles that have projected CO2 FEL that are lower than the Phase 2 MY 2027 standards. The
manufacturer names with indicate that they have one or more vehicles families that currently
meet the Phase 2 MY 2027 standards, and which we thus project will have CO2 FEL that are
lower than the Phase 2 MY 2027 standards in MY 2027.
Table 2-124 Vehicle Manufacturers Certified to EPA HDV Emission Standards in MY 2022
ARBOC Specialty Vehicles, LLC *
General Motors LLC #
Rosenbauer Motors LLC
Autocar, LLC *#
Gillig LLC *A
SEA Electric
Battle Motors, Inc.*
Global Environment Product Inc *
Seagrave Fire Apparatus LLC
Blue Bird Body Company *
Grove US LLC
Spartan Fire LLC
BYD Auto Industry Company Ltd
Hino Motors, Ltd #
Temsa Skoda Sabanci Ulasim
Araclari A.S.#
Daimler Coaches North America *
HME Inc
Terex Corporation
Daimler Truck North America LLC
#
Isuzu Motors Limited #
The Shyft Group
Dennis Eagle Inc *
Motor Coach Industries *
Tifton Motor Homes Inc
Eldorado National-California Inc *
Navistar, Inc #
VanHool N.V.
Envirotech Drive Systems Inc
New Flyer of America, Inc *A
Vicinity Motor (Bus) Corp *
E-One Inc
Nikola Corporation
Volvo Group Trucks, Technology,
Powertrain Engineering, a Division
of Mack Trucks *A#
FCA US LLC #
Oshkosh Corporation A
XOS, Inc
Ferrara Fire Apparatus Inc
PACCAR Inc *#
Zeus Electric Chassis, Inc
Ford Motor Co #
Proterra Operating Company, Inc
1277 Cummins. "Cummins to Reveal Zero-Carbon H2-ICE Concept Truck at IAA Expo Powered by the B6.7H
Hydrogen Engine". September 13, 2022. Available Online:
https://www.cummins.com/news/releases/2022/09/13/cummins-reveal-zero-carbon-h2-ice-concept-truck-iaa-expo-
powered-b67h.
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2.11.1 Technology Effectiveness and Lead Time
We evaluated the potential for lower CO2 emissions from further aerodynamic and tire
improvements to ICE tractors as well as natural gas engine, H2-ICE vehicle, hybrid powertrain,
and PHEV technologies for both vocational vehicles and tractors, as discussed in Section II.D.l.
See Chapter 1.4 for further discussion of EPA's assessment that these technologies are
technically feasible.
2.11.1.1 Aerodynamic and Tire Improvements for Tractors
In these additional technology pathways, for further aerodynamic and tire improvements to
the technology packages that supported the Phase 2 MY 2027 CO2 emission standards we
evaluated technologies to reduce CO2 emissions from ICE tractors. We note that in these
additional pathways, like in our modeled compliance pathway, the ICE vocational vehicles
portion of the pathway emit at the Phase 2 MY 2027 level. Therefore, we did not add any
additional technologies or costs associated with the vocational ICE vehicles with Phase 2 MY
2027 technologies. We also note that the Phase 2 standards for vocational vehicles did not
include the use of aerodynamic technologies and were projected to be met with the use of
improvements in tire rolling resistance and other technologies.
Tractors with ICEs have the potential to have lower CO2 emissions than required by the Phase
2 MY 2027 CO2 emission standards by further reducing the aerodynamic drag of the tractor and
by reducing the tire rolling resistance. These technologies are being used by manufacturers to
certify their tractors to the Phase 2 standards. Therefore, EPA assessed this potential technology
package applicable to tractors through a combination of aerodynamic improvements and lower
rolling resistant tires.
For this Phase 3 analysis, consistent with our approach in Phase 2 for evaluating technology
effectiveness, we evaluated the technologies to reduce aerodynamic drag, as discussed in
preamble Section II.D.l.i. The aerodynamic drag performance is determined through
aerodynamic testing. The results of the test determine the aerodynamic bin (Bin I through VII)
and therefore input to GEM that is used to determine a vehicle's CO2 emissions. The
aerodynamic Bin I level represents tractor bodies which prioritize appearance or special duty
capabilities over aerodynamics. These Bin I tractors incorporate few, if any, aerodynamic
features and may have several features which detract from aerodynamics, such as bug deflectors,
custom sunshades, B-pillar exhaust stacks, and others. Bin V represents the most aerodynamic
MY 2022 tractors.
The aerodynamic technology already exists for the tractors to achieve Bin IV and Bin V
performance in MY 2021, therefore, our assessment is that there is sufficient lead time for tractor
manufacturers to increase application of these aerodynamic designs by MY 2027 and to produce
more low and mid roof tractors at a Bin IV level of performance and more high roof tractors at a
Bin V performance. Because no further development of aerodynamic technology is required,
only further application of the technologies, under the additional example potential compliance
pathways our assessment is that there is sufficient lead time to include in those technology
packages the entire tractor aerodynamic performance to the levels shown in Table 2-125.
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Table 2-125: Aerodynamic Technology Package Adoption Rates for an Additional Compliance Pathway
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low
Roof
Mid
Roof
High
Roof
Low
Roof
Mid
Roof
High
Roof
Low
Roof
Mid
Roof
High
Roof
Bin I
0%
0%
0%
0%
0%
0%
0%
0%
0%
Bin II
0%
0%
0%
0%
0%
0%
0%
0%
0%
Bin III
0%
0%
0%
0%
0%
0%
0%
0%
0%
Bin IV
100%
100%
0%
100%
100%
0%
100%
100%
0%
Bin V
0%
0%
100%
0%
0%
100%
0%
0%
100%
Bin VI
0%
0%
0%
0%
0%
0%
0%
0%
0%
Bin VII
0%
0%
0%
0%
0%
0%
0%
0%
0%
For this Phase 3 analysis, we also evaluated technologies to reduce tire rolling resistance on
tractors, as discussed in Section II.D.l.ii of the preamble. In Phase 2, we developed four levels of
tire rolling resistance. The baseline tire rolling resistance level represents the average tire rolling
resistance on tractors in 2010. Levels 1, 2, and 3 are lower rolling resistance tires, with each level
representing approximately 15 percent lower rolling resistance than the previous level. In the
MY 2021 certification data, we found that the average rolling resistance of the steer tires
installed on the day cab and sleeper cab tractors was approximately Level 2. The average rolling
resistance of the drive tires installed on day cab and sleeper cab tractors was between Level 1
and Level 2 performance. The exception was for high roof sleeper cabs where the average drive
tire rolling resistance was at Level 2. The lowest rolling resistance tires used on each of the day
cab and sleeper cab configurations was 4.7 N/kN and 4.8 N/kN ton rolling resistance of the steer
and drive tires, respectively, which is better than the Level 3 performance. Our assessment for
the additional example potential compliance pathways is that tractor tire rolling resistance can
shift to a 50/50 split of Level 2 and Level 3 tire rolling resistance for both the steer and drive
tires in MY 2027, as shown in Table 2-126.
Table 2-126 Tire Rolling Resistance Technology Package Adoption Rates for an Additional Compliance
Pathway
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low
Roof
Mid
Roof
High
Roof
Low
Roof
Mid
Roof
High
Roof
Low
Roof
Mid
Roof
High
Roof
Steer Tires (CRR)
Base
0%
0%
0%
0%
0%
0%
0%
0%
0%
Level 1
0%
0%
0%
0%
0%
0%
0%
0%
0%
Level 2
50%
50%
50%
50%
50%
50%
50%
50%
50%
Level 3
50%
50%
50%
50%
50%
50%
50%
50%
50%
Drive Tires (CRR)
Base
0%
0%
0%
0%
0%
0%
0%
0%
0%
Level 1
0%
0%
0%
0%
0%
0%
0%
0%
0%
Level 2
50%
50%
50%
50%
50%
50%
50%
50%
50%
Level 3
50%
50%
50%
50%
50%
50%
50%
50%
50%
435
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We used the technology effectiveness inputs and technology adoption rates discussed in this
section of the preamble for aerodynamics and tire rolling resistance, along with the other vehicle
technologies used in the Phase 2 MY 2027 technology package to demonstrate compliance with
the Phase 2 MY 2027 tractor standards to develop the GEM inputs for each subcategory of Class
7 and 8 tractors. The set of GEM inputs are shown in Table 2-127. Note that we have analyzed
one technology pathway for each level of stringency, but tractor manufacturers are free to use
any combination of technologies that meet the standards on average.
Table 2-127 GEM Inputs for Tractor ICE Vehicle Technologies that Achieve a 4% C02 Reduction Relative
to the Phase 2 MY 2027 Standards
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low Roof
Mid Roof
High Roof
Low Roof
Mid Roof
High Roof
Low Roof
Mid Roof
High
Roof
Engine Fuel Map
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
2027MY
11L
11L
11L
15L
15L
15L
15L
15L
15L
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
350 HP
350 HP
350 HP
455 HP
455 HP
455 HP
455 HP
455 HP
455 HP
Aerodynamics (CdA in m2)
4.75
5.85
5.70
4.75
5.85
5.20
4.75
5.85
4.90
Steer Tire Rolling Resistance (CRR in kg/metric ton)
5.3
5.3
5.3
5.3
5.3
5.3
5.3
5.3
5.3
Drive Tire Rolling Resistance (CRR in kg/metric ton)
5.5
5.5
5.5
5.5
5.5
5.5
5.5
5.5
5.5
Extended Idle Reduction Weighted Effectiveness
N/A
N/A
N/A
N/A
N/A
N/A
3%
3%
3%
Transmission = 10 speed Manual Transmission
Gear Ratios = 12.8, 9.25, 6.76, 4.90, 3.58, 2.61, 1.89, 1.38, 1.00, 0.73
Drive Axle Ratio = 3.21 for day cabs, 3.16 for sleeper cabs
6x2 Axle Weighted Effectiveness
N/A
N/A
N/A
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
Transmission Type Weighted Effectiveness =
1.6%
Neutral Idle Weighted Effectiveness
0.2%
0.2%
0.2%
0.2%
0.2%
0.2%
0.03%
0.03%
0.03%
Direct Drive Weighted Effectiveness = 1.0%
Transmission Efficiency Weighted Effectiveness = 0.7%
Axle Efficiency Improvement = 1.6%
Air Conditioner Efficiency Improvements =
0.3%
Accessory Improvements = 0.2%
Predictive Cruise Control =0.8%
Automatic Tire Inflation Systems = 0.4%
Tire Pressure Monitoring System = 0.7%
The results from GEM for this technology package are shown in Table 2-128. As shown, this
technology package within the additional example potential compliance pathway achieves 4
percent lower CO2 emissions than the Phase 2 MY 2027 tractor standards.
436
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Table 2-128 GEM Results for Phase 3 Additional Compliance Pathway for Tractors
Class 7
Class 8
Day Cab
Day Cab
Sleeper Cab
Low Roof
Mid Roof
High Roof
Low Roof
Mid Roof
High Roof
Low Roof
Mid Roof
High
Roof
Phase 2 MY 2027 Standards (g C02/ton-mile)
96.2
103.4
100.0
73.4
78.0
75.7
64.1
69.6
64.3
Phase 3 MY 2027 Additional Pathway GEM Results (g C02/ton-mile)
91.4
98.7
95.2
70.1
74.7
72.6
61.2
66.6
61.9
As previously noted, the corresponding ICE vehicle technology package used within the
additional example compliance pathway analysis for a portion of the vocational vehicles is the
same technology package used to demonstrate compliance with the Phase 2 MY 2027 standards,
as shown in Table 2-129.
Table 2-129 GEM Inputs for Vehicles Meeting the Phase 2 MY 2027 Vocational Vehicle CO2 Emission
Standards
LHD (Class 2b-5)
MHD (Class 6-7)
HHD (Class 8)
Urban
Multi-
purpose
Regional
Urban
Multi-
purpose
Regional
Urban
Multi-
purpose
Regional
SI Engine Fuel Map
2018 MY 6.8L, 300 hp engine
CI Engine Fuel Map
2027 MY 7L,
200 hp Engine
2027 MY 7L,
270 hp Engine
2027 MY 11L,
350 hp Engine
2027 MY 11L,
350 hp Engine and
2027 MY 15L
455hp Engine
Torque Converter Lockup in 1st Gear (adoption rate)
50%
50%
50%
50%
50%
50%
30%
30%
0%
6x2 Disconnect Axle (adoption rate)
0%
0%
0%
0%
0%
0%
0%
25%
30%
Automatic Engine Shutdown (adoption rate)
70%
70%
90%
70%
70%
90%
70%
70%
90%
Stop-Start (adoption rate)
30%
30%
0%
30%
30%
0%
20%
20%
0%
Neutral Idle (adoption rate)
60%
60%
0%
60%
60%
0%
70%
70%
0%
Steer Tire Rolling Resistance (CRR kg/metric ton)
6.8
6.2
6.2
6.7
6.2
6.2
6.2
6.2
6.2
Drive Tire Rolling Resistance (CRR kg/metric ton)
6.9
6.9
6.9
7.5
6.9
6.9
7.5
6.9
6.9
Weight Reduction (pounds)
75
75
75
75
75
75
125
125
125
In conclusion, under the additional example compliance pathways we project that
improvements in ICE vehicle technologies above and beyond the improvements needed to meet
the Phase 2 MY 2027 standards will be available for manufacturers to use for tractors and
estimate use of those improvements would result in an additional emissions reduction of 4
percent.
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2.11.1.2 Natural Gas Fueled Internal Combustion Engines
To estimate the technology effectiveness of natural gas-fueled engines compared to diesel
fueled engines in the Phase 3 additional example potential compliance pathways, we used the
publicly available MY 2023 heavy-duty engine certification data for CO2 emissions.1278 We
compared GHG certification data between three engines of similar displacement, power ratings,
and intended model application fueled on CNG and conventional diesel. Family Certification
CO2 Levels for the transient Federal Test Procedure (FTP) and Supplemental Emission Test
(SET) duty cycles were compared to determine the CO2 reductions possible by applying natural
gas engine technology, as shown in Table 2-130. The comparison shows that natural gas engine
technology could achieve CO2 reductions up to 7 percent for vocational vehicles and 6 percent
for tractors compared to a similar diesel fueled ICE.
Table 2-130 Heavy-Duty Engine CO2 Comparison
CNG FTP CO2
(g/hphr)
CNG SET CO2
(g/hphr)
Diesel FTP
CO2
(g/hphr)
Diesel SET
CO2
(g/hphr)
% Average
CO2
Reduction
Vocational
514
424
524
478
7%
Tractor
501
427
518
470
6%
We also considered the availability of the natural gas fueling stations. According to the U.S.
Department of Energy there are 1,464 compressed natural gas and liquified natural gas filling
stations in the United States.1279 Of these stations, approximately 90 percent of them are CNG
stations and 10 percent are LNG stations. These stations are a combination of publicly accessible
(783) and privately operated (681). Of the publicly accessible fueling stations, all will
accommodate Class 3 through 5 HD vehicles and 1,246 will accommodate HD Class 5 through 8
vehicles. After evaluating the existing, and taking into account potential future, natural gas
refueling infrastructure, similar to the approach we considered for BEVs and FCEVs in this
preamble Section II to ensure adequate lead time for corresponding infrastructure,, we
determined that there was adequate lead time for 5 percent adoption of natural gas vehicles in the
additional example potential compliance pathways based on our balancing that these
technologies are currently available and used as well as the additional consideration of the
corresponding infrastructure needed for the level of adoption under these pathways by MY 2027.
2.11.1.3 Hydrogen-Fueled Internal Combustion Engines
Since neat hydrogen fuel does not contain any carbon, H2-ICE fueled with neat hydrogen
produce zero HC, CH4, CO, and CO2 engine-out emissions.1280 However, as explained in Section
III.C.2.xviii, we recognize that, like CI ICE, there may be negligible, but non-zero, CO2
emissions at the tailpipe of H2-ICE that use SCR and are fueled with neat hydrogen due to
contributions from the aftertreatment system from urea decomposition; thus, for purposes of 40
1278 US EPA. "Annual Certification Data for Heavy-Duty Vehicles". January 2023. Available Online:
https://www.epa.gov/system/files/documents/2023-01/heavy-duty-gas-and-diesel-engines-2015-present.xlsx
1279 Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center, Alternative
Fuel Station Locator. February 2024. Available online:
https://afdc.energy.gov/stations/#/find/nearest?fuel=CNG&country=US.
1280 Note, NOx and PM emission testing is required under existing 40 CFR part 1036 for engines fueled with neat
hydrogen.
438
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CFR 1036 we are finalizing an engine testing default CO2 emission value (3 g/hp-hr) option
(though manufacturers may instead conduct testing to demonstrate that the CO2 emissions for
their engine is below 3 g/hp-hr). Under this final rule, consistent with treatments of such
contributions from the aftertreatment system from urea decomposition for diesel ICE vehicles,
we are not including such contributions as vehicle emissions for H2-ICE vehicles.1281 Thus, H2-
ICE technologies that run on neat hydrogen, as defined in 40 CFR 1037.150(f) and discussed in
Section III.C.3.ii of the preamble, have HD vehicle CO2 emissions that are deemed to be zero for
purposes of 40 CFR 1037. Therefore, the technology effectiveness (in other words CO2 emission
reduction) for the vehicles that are powered by this technology is 100%.
The lead time consideration for H2-ICE vehicles consists of two parts. The first part is the
engine technology design and development, along with the integration of the engine,
aftertreatment, and fuel storage integration into the vehicle. The second part is the hydrogen
refueling infrastructure availability.
An H2-ICE is very similar to existing ICEs and engine manufacturers can leverage the
extensive technical expertise they have developed with existing products. Many H2-ICE engine
components can be produced using an engine manufacturer's existing tooling and manufacturing
processes. Similarly, H2-ICE vehicles can be built on the same assembly lines as other ICE
vehicles, by the same workers and with many of the same component suppliers. For example,
Cummins has announced the launch of a fuel-agnostic combustion engine XI0 for MY 2026 that
can run on hydrogen fuel.1282 Many design aspects of the integration of a H2-ICE into a vehicle
can be done in parallel with the H2-ICE ramp up to the production launch of the engine.
However, there may be final validation vehicle development steps that will require the final H2-
ICE and therefore may take an additional year after the launch of the H2-ICE. Therefore, from
the technology development perspective, we project H2-ICE technology will be available in
MYs 2027 and later.
The discussion in RIA Chapter 1.8.3 details our assessment of hydrogen refueling
infrastructure. After evaluating the existing and projected future hydrogen refueling
infrastructure and similar to the approach we considered for publicly-charged BEVs and FCEVs
in this preamble Section II, we considered H2-ICE vehicle technology only in the MY 2030 and
later timeframe for the additional example potential compliance pathways, to better ensure that
our additional example potential compliance pathways provide adequate time for early hydrogen
market infrastructure development. We included the H2-ICE technology in the additional
compliance pathway relative to the reference case in MY 2031 and later, which provides nearly
seven years of lead time for the H2 refueling infrastructure buildout to phase in.
2.11.1.4 Hybrid and Plug-in Hybrid Powertrains
As discussed in Section II.D.l.v, hybrid powertrains have lower C02 emissions than ICE
powertrains due to a combination of regenerative braking and the ability to optimize the ICE
1281 The results from the fuel mapping test procedures prescribed in 40 CFR 1036.535, 40 CFR 1036.540, and 40
CFR 1036.545, are fuel consumption values; therefore, the CO2 emissions from urea decomposition is not included
in the results.
1282 Cummins. "Cummins Announces New X10 Engine, Next in The Fuel-Agnostic Series, Launching in North
America in 2026." February 2023. Available Online:
https://www.cummins.com/news/releases/2023/02/13/cummins-announces-new-xl0-engine-next-fuel-agnostic-
series-launching-north
439
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operation within the hybrid powertrain system. For this Phase 3 analysis we used the approach
described in Chapter 2.2.2.1.3 of the RIA to determine the effectiveness of hybrids based on the
amount of braking energy recovered from regenerative braking. In summary, to calculate
percent energy recovery available, we estimated the braking energy and divided by the total
tractive energy (i.e., the energy required to move the vehicle) for each drive cycle and then
weighted the results using the respective GEM test cycle weighting factors. We then multiplied
these values by the weighted energy consumption per mile to get energy recovered per mile from
regenerative braking. The average regeneration energy as a percentage of total tractive energy
was 10 percent and 5 percent, for vocational vehicles and tractors, respectively. For both tractors
and vocational vehicles, we project that hybrid technology can achieve an additional 5 percent of
effectiveness by optimizing how the engine is operated. For example, the engine could be
operated in the minimum brake-specific fuel consumption region of the engine more often in a
hybrid powertrain. In addition, the electric motor could be used to limit engine transient
operation, or the engine could be downsized. This leads to an overall CO2 emission reduction of
15 percent for vocational vehicle hybrids and 10 percent for tractor hybrids.
For hybrid electric vehicles, the projected effectiveness is further supported by powertrain
testing that was conducted by Eaton at Argonne National Laboratory. The testing was performed
with a Cummins XI5 engine and three transmissions. The transmissions were an Eaton P2/P3
hybrid, Eaton Endurant, and an Allison 4500 RDS. For each of the three powertrain
configurations, the test procedures prescribed in 40 CFR 1036.545 were followed to generate
powertrain fuel maps. Each of these fuel maps were input into GEM Version 3.5.1 to determined
gC02/ton-mile emissions from a number of representative vehicle configurations. For the heavy
heavy-duty vocational vehicles, the average CO2 emission reductions were 22, 8, and 25 percent
for multi-purpose, regional, and urban regulatory subcategories respectively. The average CO2
reductions for day cab and sleeper cab tractors was 9 percent. The data from the powertrain tests
supports the estimated CO2 emission reduction of 15 percent for vocational vehicle hybrids, as it
is expected that vocational vehicle hybrids will be certified as multi-purpose or urban. The data
from the powertrain tests also supports the estimated CO2 emission reduction of 10 percent for
tractor hybrids, since many of the individual tractors had greater than 10 percent CO2 emission
reduction, with the average at 9 percent.
In addition, other studies have also shown CO2 emission reductions from heavy-duty hybrid
vehicles. For example, a New Flyer hybrid transit bus achieves 10-29 percent reduction,
depending on route.1283 Similarly, a NovaBus hybrid transit bus found up to 30 percent reduction
in CO2 emissions at speeds ranging between 9-18 mph.1284 ANREL report of a reduction of 75
percent CO2 in idle emissions during PTO use1285 where idle operation is over 30 percent of
vehicle operating time and uses 10 percent of the fuel.1286 A study with a Pierce Manufacturing
1283 New Flyer. "Hybrid-electric mobility." Available online: https://www.newflyer.com/bus/xcelsior-hybrid/.
1284 NovaBus. "Nova LFS HEV". Available online: https://novabus.com/blog/bus/lfs_hev/
1285 Ragatz, Adam, Jonathan Burton, Eric Miller, and Matthew Thornton. "Investigation of Emissions Impacts from
Hybrid Powertrains" National Renewable Energy Lab. January 2020. Available online:
https://www.nrel.gov/docs/Iy20osti/75782.pdf.
1286 Konan, Arnaud, Adam Duran, Kenneth Kelly, Eric Miller, and Robert Prohaska. "Characterization of PTO and
Idle Behavior for Utility Vehicles". National Renewable Energy Lab. Available online:
https://www.nrel.gov/docs/Iyl7osti/66747.pdf.
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hybrid fire truck showed 1,500 gallons of diesel saved in one month which also leads to a
reduction in CO2 emissions.1287
Hybrid technology is currently being used on heavy-duty vehicles. RIA Chapter 1.4.5 details
the HD truck and bus models that are currently offered as hybrid vehicles. As shown, both
Allison and BAE offer heavy-duty hybrid systems for use in vehicles. Our assessment, based on
currently available hybrid technology that is being produced in vehicles today, is that there is
adequate lead time for manufacturers to increase the adoption of the technology for LHD and
MHD vocational vehicles in MY 2027 and for HHD vocational vehicles and tractors in MY 2030
to the adoption levels included in the additional pathways.
Plug-in hybrid electric vehicles run on both electricity and fuel. The utility factor is the
fraction of miles the vehicle travels in electric mode relative to the total miles traveled. The
percent CO2 emission reduction is directly related to the utility factor. The greater the utility
factor, the lower the tailpipe CO2 emissions from the vehicle. The utility factor depends on the
size of the battery and the operator's driving habits. For PHEVs, we project that for MY 2027
and MY 2032 tractors, a CO2 emission reduction (effectiveness) of 30 percent is achievable by
adding a high-voltage battery that could achieve a utility factor of 22 percent. For MY 2027
vocational vehicles, we project an effectiveness of 30 percent could be achieved by adding a
high-voltage battery with a utility factor of 18 percent. For MY 2030 vocational vehicles, we
project an effectiveness of 50 percent could be achieved by adding a high-voltage battery with a
utility factor of 41 percent. With utility factors between 18 to 41 percent, a significantly smaller
battery would be needed for a PHEV in comparison to the battery needed for a corresponding
battery electric vehicle.
For heavy-duty PHEVs, the projected effectiveness is further supported by powertrain testing
that was conducted by Eaton at Argonne National Laboratory. To evaluate the emissions
reductions of a plug-in hybrid powertrain, Eaton used a combination of GEM simulations and
powertrain test results. The results of the analysis showed that a vocational vehicle with a plug-in
hybrid powertrain could reduce CO2 emission by 52 percent.1288
In our lead time assessment for PHEVs, we believe it will take longer for vehicle
manufacturers to integrate this technology into vehicles than it will for hybrid technologies. We
determined that approximately 3-4 years would be necessary to develop this technology.
Therefore, we conservatively included PHEVs in limited applications (HHD vocational vehicle
and day cab tractors) beginning in MY 2030 and included a scenario in MY 2032 with and
without PHEVs in the technology packages that also include our projected reference case ZEV
adoption rates.
PHEVs, like BEVs, require an external charging source to provide electricity to the vehicle.
However, the recharging demand for a PHEV is much lower than a comparable BEV. Therefore,
most heavy-duty PHEVs could use Level 1 charging by plugging it into a 240 V outlet. Truck
operators would have access to these outlets at depots and other businesses without having to
1287 Pierce. "Pierce Volterra Platform of Electric Vehicles". Available online: https://www.piercemfg.com/electric-
fire-trucks/pierce-volterra.
1288 Sanchez, James. Memorandum to Docket EPA-HQ-OAR-2022-0985. "Eaton Hybrid Powertrain Results"
February 2024.
441
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require special installation of EVSE equipment. Operators would need to create access to such an
outlet, but this would not be a constraining factor for lead time and such costs would be low for
purchasers. Similar to the approach we considered for BEVs and FCEVs in this preamble
Section II, we determined there is adequate lead time to meet the projected charging
infrastructure needs that correspond to the technology packages for the final rule's additional
example potential compliance pathways. Furthermore, because the recharging demand for
PHEVs will be lower than the levels for BEVs in our modeled potential compliance pathway, the
demand on the grid would be less than assessed with our modeled potential compliance pathway.
2.11.1.5 Summary of the Technology Effectiveness
Table 2-131 shows the summary of the technology effectiveness (percent CO2 emission
reduction) of each of the technologies discussed in this subsection relative to the Phase 2 MY
2027 standards.
Table 2-131 Effectiveness of Technologies of Vehicles with ICE Relative to the MY 2027 Phase 2 Standards
Vehicle Type
Model Year
ICE Vehicle
Improvements
Natural Gas
ICE Vehicle
HEV
PHEV
H2 ICE
Vehicle
Tractor
MY 2027
4%
6%
10%
30%
100%
MY 2030
4%
6%
10%
30%
100%
MY 2032
4%
6%
10%
30%
100%
Vocational
MY 2027
0%
7%
15%
30%
100%
MY 2030
0%
7%
15%
50%
100%
MY 2032
0%
7%
15%
50%
100%
2.11.2 Technology Package Costs
In this section, we present the incremental technology package costs for each technology
relative to the comparable baseline vehicles that meet the Phase 2 MY 2027 emission
standards.1289
2.11.2.1 ICE Vehicle Improvements
The costs for the additional aerodynamic and low rolling resistance tire costs were developed
based on the cost assessment in the Phase 2 final rule.1290 The tractor aerodynamic technology
costs for MY 2027 for each bin represent the values shown in the Phase 2 RIA Tables 2-256
through 2-259 on pages 2-337 through 2-340. The tractor tire technology costs for MY 2027
came from the Phase 2 RIA Tables 2-227 through 2-232 on pages 2-325 through 2-328. These
technology costs developed for the Phase 2 analysis remain appropriate because the technologies
are the same and the costs including learning through MY 2027. These values were used to
develop the Phase 3 technology package costs and then the incremental cost was calculated from
the Phase 2 technology package costs for MY 2027 shown on Table 2-50 on page 2-147 of the
Phase 2 RIA. The technology costs in the Phase 2 RIA were in 2013$ and therefore a conversion
1289 The costs presented in this section do not include the learning effects after MY 2027, and therefore are higher
than they would be if they included learning (i.e., are conservative in the overestimating sense).
1290 US EPA. Regulatory Impact Analysis Greenhouse Gas Emissions and Fuel Efficiency Standards for
Medium- and Heavy-Duty Engines and Vehicles - Phase 2. Chapter 2. EPA-420-R-16-900. August 2016.
442
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factor of 1.2503 was used to convert the costs to 2022$. Table 2-132 through Table 2-135 show
the incremental vehicle technology package cost for each of the tractor subcategories.
Table 2-132 MY 2027 and Later Incremental Technology Package Cost
Sleeper Cab High Roof Tractors
Technology
2013$
2022$
Phase 3 Aero Tech Package Cost
$2,176
$2,721
Phase 2 Aero Package Cost
$639
$799
Incremental Aero Cost Increase
$1,922
Phase 3 Tire Tech Package
$44.50
$56
Total Phase 3 Tech Package Cost
$1,978
Table 2-133 MY 2027 and Later Incremental Technology Package Cost
Sleeper Cab Low/Mid Roof Tractors
Technology
2013$
2022$
Phase 3 Aero Tech Package Cost
$1,903
$2,379
Phase 2 Aero Package Cost
$415
$519
Incremental Aero Cost Increase
$1,861
Phase 3 Tire Tech Package
$44.50
$56
Total Phase 3 Tech Package Cost
$1,917
Table 2-134 MY 2027 and Later Incremental Technology Package Cost
Day Cab Low/Mid Roof Tractors
Technology
2013$
2022$
Phase 3 Tech Package
$1,663
$2,079
Phase 2 Aero Package Cost
$453
$566
Incremental Cost Increase
$1,513
Phase 3 Tire Tech Package
$44.50
$56
Total Phase 3 Tech Package Cost
$1,569
443
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Table 2-135 MY 2027 and Later Incremental Technology Package Cost
Day Cab High Roof Tractors
Technology
2013$
2022$
Phase 3 Tech Package
$1,874
$2,343
Phase 2 Aero Package Cost
$547
$684
Incremental Cost Increase
$1,659
Phase 3 Tire Tech Package
$44.50
$56
Total Phase 3 Tech Package Cost
$1,715
2.11.2.2 Natural Gas Fueled Internal Combustion Engines
EPA contracted FEV to conduct a technology and cost study for a variety of powertrains
applicable to Class 4, 5, 7, and 8 heavy-duty vehicles.1291 Vehicles studied include those listed in
Table 2-136. FEV also costed three (15L for Class 8, 10L for Class 7, and 6.6L for Class 4/5)
diesel ICE powertrains that would meet the emission standards as required by the Low NOx Rule
and the Phase 2 CO2 emission standards in MY 2027. These were used to calculate the
incremental cost of the alternative powertrain to the comparable diesel ICE powertrain baseline.
Table 2-136 FEV Vehicle Class and Application used for each Regulatory Category
Regulatory Category
Vehicle Class
Application
Light Heavy-Duty
Vocational
4,5
box trucks
step vans
Medium Heavy-Duty
Vocational
7
box trucks
transit bus
vocational vehicles
school buses
Heavy Heavy-Duty
Vocational
8
vocational vehicles
coach bus
Short-Haul Tractors
8
day cab
Long-Haul Tractors
8
long haul
The costs presented in Table 2-137 include both the direct and indirect costs of compliance
for manufacturers and represent a market stable scenario where the technologies are mature,
which is appropriate because natural gas technologies have been used in the heavy-duty
marketplace for decades. The LHD vocational cost represents an average of the Class 4/5 box
truck and step van applications. Similarly, the MHD and HHD vocational vehicle costs are an
average of the corresponding applications shown in Table 2-136. The costs represent the
incremental costs of a spark-ignited (SI) CNG engine because that is the predominant technology
being offered today in the heavy-duty market.1292
1291 Task Order "Heavy Duty Vehicles: Industry Characterization, Technology Assessment and Costing" of EPA
Contract 68HERC19D008. 2024.
1292 Cummins. Natural Gas Engine Portfolio. Available online:
https://mart.cummins.com/imagelibrary/data/assetfiles/0063969.pdf.
444
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One difference in costs between a CNG powertrain and the baseline diesel powertrain is the
fuel 'tank.' A CNG vehicle requires pressurized fuel tanks typically made with carbon fiber in
order to hold the fuel at required pressures of 250 bar. These tank types are much higher in cost
than a tank to hold diesel fuel which does not require the capability to store fuel under pressure.
The larger the vehicle and/or the longer the distance traveled per day dictates the number and
size of the tanks required. Cost of tanks for the CNG Class 8 day cab and sleeper cab tractor
powertrains were estimated to be $10,000-$16,500.1293
Another area of difference is in the aftertreatment required on CNG powertrains compared to
a diesel. The current diesel powertrain contains a DOC, DPF, SCR and associated urea
injection/mixing system. Spark-ignited CNG engines run stoichiometric combustion and
therefore only require a three way catalyst to reduce HC, CO and NOx, similar to gasoline-fueled
ICE vehicles. Engine-out PM from SI-CNG fueled vehicles meet the exhaust emission standards
without additional aftertreatment. Therefore, spark-ignited CNG vehicles do not require a DPF,
DOC, SCR or the DEF and urea mixing system and a significant cost reduction compared to the
diesel powertrain baseline is realized. Another cost reduction comes from the fuel injection
system. The diesel system has a fuel injection system used to atomize the diesel fuel as it goes
into the combustion chamber. These components are not needed on a gaseous fuel as it is already
in combustible form.
Table 2-137 Summary of the MY 2027 and Later Incremental Costs for Natural Gas Fueled Vehicles (2022$)
Vehicle Type
Total
Light Heavy-Duty Vocational
$ (7,163)
Medium Heavy-Duty Vocational
$ (4,690)
Heavy Heavy-Duty Vocational
$ (3,282)
Day Cab Tractors
$75
Sleeper Cab Tractors
$ 1,888
2.11.2.3 Hydrogen-Fueled Internal Combustion Engines
We used the same FEV cost study to develop the incremental technology costs for H2-ICE
vehicles, as shown in Table 2-138.1294
As with CNG, a major difference between H2-ICE powertrains and the baseline diesel
powertrain is the fuel 'tank.' The H2-ICE requires pressurized fuel tanks typically made with
carbon fiber and many other considerations in order to hold the fuel at required pressures. The
H2 tanks used in the FEV cost study are designed to store H2 at 700 bar so that they can hold
sufficient hydrogen. These tank types are much higher in cost than a tank to hold diesel fuel
because the fuel is pressurized. The cost of the tanks on the Class 8 sleeper cab tractors can add
on $30,000in low volumes to the H2-ICE powertrain costs.
Also similar to CNG, a significant cost decrease compared to the baseline powertrain is due to
the difference in the aftertreatment required on H2-ICE fueled powertrains compared to the
baseline diesel powertrain. The baseline diesel powertrain contains a DOC, DPF, SCR and an
1293 Caffrey, Cheryl. Memorandum to the docket EPA-HQ-OAR-2022-0985. "Alternative Powertrain Costs"
February 2024
1294 Caffrey, Cheryl. Memorandum to the docket EPA-HQ-OAR-2022-0985. "Alternative Powertrain Costs"
February 2024.
445
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associated urea mixing/dosing system. These aftertreatment components work to reduce
hydrocarbons, carbon monoxide, particulate matter and NOx, respectively. Only DOC and SCR
aftertreatment is required on a H2-ICE fueled with neat H2 in order to reduce NOx. In
developing the aftertreatment cost for the H2-ICE, an exhaust gas heater was also included in
order to reduce NOx at idle and during low power operation. Another cost decrease compared to
the baseline powertrain comes from the fuel injection system. The baseline diesel system has a
number of components to atomize the diesel fuel as it goes into the combustion chamber. These
components are not needed on a H2-ICE because the H2 is a gaseous fuel in combustible form.
Table 2-138 Summary of the MY 2030 and Later Incremental Costs for Hydrogen Fueled ICE Vehicles
(2022$)
Vehicle Type
Total
Light Heavy-Duty Vocational
$ 3,872
Medium Heavy-Duty Vocational
$ 14,100
Heavy Heavy-Duty Vocational
$ 27,873
Day Cab Tractors
$ 26,936
Sleeper Cab Tractors
$ 44,919
2.11.2.4 Hybrids and Plug-in Hybrid Powertrains
To determine the hybrid powertrain costs, we relied on the Autonomie study results published
with the 2023 DOE VTO/HFTO Transportation Decarbonization Analysis.1295 The results
include vehicle costs for conventional vehicles and parallel hybrid vehicles for each vehicle
class. To determine the incremental powertrain costs for each hybrid powertrain, first the chassis
costs were subtracted from the total vehicle costs to isolate the costs of the powertrain. Second,
the conventional powertrain costs were subtracted from the hybrid costs to determine the
incremental cost for the hybrid powertrain. There were two scenarios evaluated in the Autonomie
study - a high technology and a low technology scenario. Consistent with our approach for
developing incremental costs for BEV components discussed in RIA Chapter 2.4.3, we used an
average of the high and low cost scenarios. The report included costs for both spark-ignition and
compression-ignition engines, however for this analysis we only relied on the results from the
compression-ignition engines. The specific vehicle class and application (referred to as purpose
in the Autonomie results) from the Autonomie results for each regulatory category is outline in
Table 2-139. Finally, the costs were aggregated by regulatory category by averaging together the
high and low costs of each application within a regulatory category together. The Autonomie
results included data for MY 2025 and MY 2030, so the MY 2027 costs were determined by
interpolating the results for MY 2025 and MY 2030. The summary of the hybrid vehicles is in
Table 2-140.
1295 US Department of Energy. Available online: https://anl.box.eom/s/hv4kufocq31eoijt6v0wht2uddjuiff4 and
https://anl.box.eom/s/oy04bje31tc21rz5py4bqled4s4bn0vo.
446
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Table 2-139 Autonomic Vehicle Class and Application used for each Regulatory Category
Regulatory Category
Vehicle Class
Application
Light Heavy-Duty
Vocational
4,5
box trucks
step vans
service trucks
utility trucks
Medium Heavy-Duty
Vocational
6,7
box trucks
step vans
vocational vehicles
school buses
Heavy Heavy-Duty
Vocational
8
vocational vehicles
transit
Day Cab Tractors
Day Cab Tractors
7,8
tractors
beverage
drayage
regional
Day Cab Tractors
8
long haul
Table 2-140 Summary of MY 2027 and Later Direct and Indirect Manufacturing Costs for Hybrid Electric
Vehicles (2022$)
Vehicle Type
Direct Manufacturing
Costs
Indirect Manufacturing
Costs
Total
Light Heavy-Duty Vocational
$5,617
$2,359
$7,976
Medium Heavy-Duty Vocational
$8,436
$3,543
$11,979
Heavy Heavy-Duty Vocational
$11,936
$5,013
$16,949
Day Cab Tractors
$9,359
$3,931
$13,290
Sleeper Cab Tractors
$11,324
$4,756
$16,080
The PHEV technology combines an ICE powertrain with a BEV powertrain. Therefore, we
calculated the incremental costs of the PHEV technology using a similar approach as we did for
BEVs and ICEVs in HD TRUCS for each of the 101 vehicle types, as detailed in RIA Chapter
2.3.2 and 2.4.3. We used the same component costs for the ICE powertrain, except replaced the
ICE accessory costs with the electrified accessory component costs used in BEVs. For the
electrified portion of the PHEV, we also included the electric motor, onboard charger, and power
converter costs for a similar BEV. The key difference between the BEV and PHEV powertrain
costs is due to the size of the battery. We reduced the size of the battery for the PHEV relative to
a BEV to reflect a utility factor of 41 percent for vocational vehicles and 22 percent for tractors
and we conservatively estimated that the depth of discharge of a PHEV battery would be only 60
percent compared to the BEV battery depth of discharge of 90 percent. The incremental
component costs for each of the HD TRUCS 101 vehicle types are shown in Table 2-141.
447
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Table 2-141 MY 2030 Incremental PHEV Component Costs for Each HD TRUCS Vehicle Type (2022$)
Direct Manufacturing Cost
Battery
Tax
Credit
Vehicle ID
Battery
Motor
On-board
Power
Incremental
Incremental
Charger
Converter
Electric
Accessories
PHEV
Powertrain
01V Amb C14-5 MP
$ 7,577
$4,374
$515
$1,440
$2,478
$16,384
$2,481
02V Amb C12b-3 MP
$ 7,153
$4,374
$515
$1,440
$2,439
$15,922
$2,342
03V Amb C14-5 U
$ 7,060
$4,374
$515
$1,440
$2,478
$15,867
$2,312
04V Amb C12b-3 U
$ 6,620
$4,374
$515
$1,440
$2,439
$15,389
$2,168
05T Box C18 MP
$ 15,450
$5,755
$515
$1,440
$2,632
$25,792
$5,059
06T Box C18 R
$ 15,958
$5,755
$515
$1,440
$2,632
$26,300
$5,226
07T Box C16-7 MP
$ 10,665
$3,638
$515
$1,440
$2,555
$18,813
$3,493
08T Box C16-7 R
$ 11,600
$3,638
$515
$1,440
$2,555
$19,748
$3,799
09T Box C18 U
$ 14,968
$5,755
$515
$1,440
$2,632
$25,310
$4,902
10T Box C16-7 U
$ 10,278
$3,638
$515
$1,440
$2,555
$18,426
$3,366
11T Box C12b-3 U
$ 6,339
$4,374
$515
$1,440
$2,478
$15,146
$2,076
12T Box C12b-3 R
$ 7,474
$4,374
$515
$1,440
$2,478
$16,281
$2,448
13T Box C12b-3 MP
$ 6,881
$4,374
$515
$1,440
$2,478
$15,688
$2,253
14T Box C14-5 U
$ 6,339
$4,374
$515
$1,440
$2,478
$15,146
$2,076
15T Box C14-5 R
$ 7,474
$4,374
$515
$1,440
$2,478
$16,281
$2,448
16T Box C14-5 MP
$ 6,881
$4,374
$515
$1,440
$2,478
$15,688
$2,253
17B Coach C18 R
$ 45,031
$5,755
$515
$1,440
$2,824
$55,565
$14,746
18B Coach C18 MP
$ 66,676
$5,755
$515
$1,440
$2,824
$77,210
$21,834
19C Mix C18 MP
$ 27,105
$5,755
$515
$1,440
$2,632
$37,447
$8,876
20T Dump C18 U
$ 17,910
$5,755
$515
$1,440
$2,632
$28,252
$5,865
21T Dump C18 MP
$ 18,142
$5,755
$515
$1,440
$2,632
$28,484
$5,941
22T Dump C16-7 MP
$ 17,566
$3,638
$515
$1,440
$2,555
$25,714
$5,753
23T Dump C18 U
$ 17,910
$5,755
$515
$1,440
$2,632
$28,252
$5,865
24T Dump C16-7 U
$ 16,442
$3,638
$515
$1,440
$2,555
$24,590
$5,384
25T Fire C18 MP
$ 19,046
$5,755
$515
$1,440
$2,632
$29,388
$6,237
26T Fire C18 U
$ 19,086
$5,755
$515
$1,440
$2,632
$29,428
$6,250
27T Flat C16-7 MP
$ 10,665
$3,638
$515
$1,440
$2,555
$18,813
$3,493
28T Flat C16-7 R
$ 11,600
$3,638
$515
$1,440
$2,555
$19,748
$3,799
29T Flat C16-7 U
$ 9,842
$3,638
$515
$1,440
$2,555
$17,990
$3,223
30Tractor DC C18 MP
$ 11,941
$9,445
$515
$1,440
$2,632
$25,973
$3,910
31 Tractor DC C16-7 MP
$ 10,792
$6,563
$515
$1,440
$2,555
$21,865
$3,534
32Tractor SC C18 U
$ 33,089
$7,152
$515
$1,440
$2,670
$44,867
$10,836
33Tractor DC C18 U
$ 18,064
$9,857
$515
$1,440
$2,555
$32,431
$5,915
34T Ref C18 MP
$ 22,482
$5,755
$515
$1,440
$2,670
$32,863
$7,362
35T Ref C16-7 MP
$ 18,351
$3,638
$515
$1,440
$2,555
$26,499
$6,010
36T Ref C18 U
$ 22,482
$5,755
$515
$1,440
$2,670
$32,863
$7,362
37T Ref C16-7 U
$ 18,109
$3,638
$515
$1,440
$2,555
$26,257
$5,930
38RV C18 R
$ 35,734
$5,755
$515
$1,440
$2,824
$46,268
$11,702
39RV C16-7 R
$ 37,992
$3,638
$515
$1,440
$2,747
$46,332
$12,441
40RV C14-5 R
$ 24,170
$4,374
$515
$1,440
$2,478
$32,977
$7,915
41 Tractor DC C17 R
$ 25,317
$6,563
$515
$1,440
$2,555
$36,390
$8,291
42RV C18 MP
$ 35,734
$5,755
$515
$1,440
$2,824
$46,268
$11,702
43RV C16-7 MP
$ 34,830
$3,638
$515
$1,440
$2,747
$43,170
$11,406
44RV C14-5 MP
$ 22,153
$4,374
$515
$1,440
$2,478
$30,960
$7,255
45Tractor DC C18 R
$ 30,296
$9,445
$515
$1,440
$2,624
$44,320
$9,921
46B School C18 MP
$ 16,876
$5,755
$515
$1,440
$2,824
$27,410
$5,526
47B School C16-7 MP
$ 10,168
$3,638
$515
$1,440
$2,747
$18,509
$3,330
48B School C14-5 MP
$ 7,577
$4,374
$515
$1,440
$2,478
$16,384
$2,481
448
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Vehicle ID
Direct Manufacturing Cost
Battery
Tax
Credit
Battery
Motor
On-board
Charger
Power
Converter
Incremental
Electric
Accessories
Incremental
PHEV
Powertrain
49B School C12b-3 MP
$ 7,153
$4,374
$515
$1,440
$2,555
$16,037
$2,342
50B School C18 U
$ 15,985
$5,755
$515
$1,440
$2,824
$26,519
$5,235
5 IB School C16-7 U
$ 10,168
$3,638
$515
$1,440
$2,747
$18,509
$3,330
52B School C14-5 U
$ 7,060
$4,374
$515
$1,440
$2,478
$15,867
$2,312
53B School C12b-3 U
$ 6,620
$4,374
$515
$1,440
$2,555
$15,505
$2,168
55B Shuttle C12b-3 MP
$ 10,402
$4,374
$515
$1,440
$2,555
$19,287
$3,406
56B Shuttle C14-5 U
$ 10,031
$4,374
$515
$1,440
$2,478
$18,838
$3,285
57B Shuttle C12b-3 U
$ 9,592
$4,374
$515
$1,440
$2,555
$18,476
$3,141
58B Shuttle C16-7 MP
$ 16,715
$3,638
$515
$1,440
$2,747
$25,055
$5,474
59B Shuttle C16-7 U
$ 15,506
$3,638
$515
$1,440
$2,747
$23,846
$5,078
60S Plow C16-7 MP
$ 12,634
$3,638
$515
$1,440
$2,555
$20,782
$4,137
61S Plow C18 MP
$ 24,987
$5,755
$515
$1,440
$2,632
$35,329
$8,183
62 S Plow C16-7 U
$ 11,835
$3,638
$515
$1,440
$2,555
$19,983
$3,876
63 S Plow C18 U
$ 24,565
$5,755
$515
$1,440
$2,632
$34,907
$8,044
64V Step C16-7 MP
$ 10,743
$3,638
$515
$1,440
$2,555
$18,891
$3,518
65V Step C14-5 MP
$ 6,881
$4,374
$515
$1,440
$2,478
$15,688
$2,253
66V Step C12b-3 MP
$ 6,881
$4,374
$515
$1,440
$2,439
$15,650
$2,253
67V Step C16-7 U
$ 9,914
$3,638
$515
$1,440
$2,555
$18,062
$3,246
68V Step C14-5 U
$ 6,339
$4,374
$515
$1,440
$2,478
$15,146
$2,076
69V Step C12b-3 U
$ 6,339
$4,374
$515
$1,440
$2,439
$15,108
$2,076
70S Sweep C16-7 U
$ 11,534
$3,638
$515
$1,440
$2,555
$19,682
$3,777
7IT Tanker C18 R
$ 17,078
$5,755
$515
$1,440
$2,632
$27,420
$5,593
72T Tanker C18 MP
$ 16,762
$5,755
$515
$1,440
$2,632
$27,104
$5,489
73T Tanker C18 U
$ 16,674
$5,755
$515
$1,440
$2,632
$27,016
$5,460
74T Tow C18 R
$ 26,176
$5,755
$515
$1,440
$2,632
$36,518
$8,572
75T Tow C16-7 R
$ 19,046
$3,638
$515
$1,440
$2,555
$27,194
$6,237
76T Tow C18 U
$ 25,341
$5,755
$515
$1,440
$2,632
$35,683
$8,299
77T Tow C16-7 U
$ 16,513
$3,638
$515
$1,440
$2,555
$24,662
$5,408
78Tractor SC C18 MP
$ 28,357
$7,152
$515
$1,440
$2,670
$40,135
$9,286
79Tractor SC C18 R
$ 39,574
$7,152
$515
$1,440
$2,670
$51,352
$12,959
80Tractor DC C18 HH
$ 22,000
$8,046
$515
$1,440
$2,632
$34,634
$7,205
81 Tractor DC C17 R
$ 18,063
$6,563
$515
$1,440
$2,555
$29,136
$5,915
82Tractor DC C18 R
$ 21,599
$9,445
$515
$1,440
$2,624
$35,623
$7,073
83Tractor DC C17 U
$ 15,616
$6,563
$515
$1,440
$2,555
$26,689
$5,114
84Tractor DC C18 U
$ 12,117
$9,445
$515
$1,440
$2,632
$26,150
$3,968
85B Transit C18 MP
$ 29,910
$5,755
$515
$1,440
$2,824
$40,444
$9,795
86B Transit C16-7 MP
$ 23,623
$3,638
$515
$1,440
$2,747
$31,963
$7,736
87B Transit C18 U
$ 29,910
$5,755
$515
$1,440
$2,824
$40,444
$9,795
88B Transit C16-7 U
$ 21,638
$3,638
$515
$1,440
$2,747
$29,979
$7,086
89T Utility C18 MP
$ 16,128
$5,755
$515
$1,440
$2,632
$26,470
$5,282
90T Utility C18 R
$ 16,537
$5,755
$515
$1,440
$2,632
$26,879
$5,416
9IT Utility C16-7 MP
$ 11,687
$3,638
$515
$1,440
$2,555
$19,835
$3,827
92T Utility C16-7 R
$ 12,560
$3,638
$515
$1,440
$2,555
$20,708
$4,113
93T Utility C14-5 MP
$ 7,601
$4,374
$515
$1,440
$2,478
$16,408
$2,489
94T Utility C12b-3 MP
$ 7,210
$4,374
$515
$1,440
$2,439
$15,979
$2,361
95T Utility C14-5 R
$ 8,125
$4,374
$515
$1,440
$2,478
$16,932
$2,661
96T Utility C12b-3 R
$ 8,125
$4,374
$515
$1,440
$2,439
$16,893
$2,661
97T Utility C18 U
$ 15,851
$5,755
$515
$1,440
$2,632
$26,193
$5,191
98T Utility C16-7 U
$ 11,008
$3,638
$515
$1,440
$2,555
$19,156
$3,605
99T Utility C14-5 U
$ 7,166
$4,374
$515
$1,440
$2,478
$15,973
$2,347
449
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Vehicle ID
Direct Manufacturing Cost
Battery
Tax
Credit
Battery
Motor
On-board
Charger
Power
Converter
Incremental
Electric
Accessories
Incremental
PHEV
Powertrain
100T Utility C12b-3 U
$ 6,717
$4,374
$515
$1,440
$2,439
$15,486
$2,200
lOlTractor DC C18 U
$ 9,498
$9,445
$515
$1,440
$2,632
$23,531
$3,110
The individual vehicles were aggregated into the corresponding regulatory class.1296 The
incremental retail price equivalent (RPE) using the 1.42 multiplier for MY 2030 PHEVs by
regulatory group are shown in Table 2-142.
Table 2-142 Summary of MY 2030 Incremental RPE for Plug-in Hybrid Electric Vehicles (2022$)
Regulatory Group
RPE Costs
Light Heavy-Duty Vocational
$21,774
Medium Heavy-Duty Vocational
$28,552
Heavy Heavy-Duty Vocational
$40,627
Day Cab Tractors
$37,224
Sleeper Cab Tractors
$53,514
2.11.2.5 Summary of Technology Costs
A summary of the per vehicle incremental technology costs for each of the technologies is
shown in Table 2-143.
Table 2-143 Per Vehicle Cost of Technologies Relative to the MY 2027 Phase 2 Standards (2022$)
Vehicle Type
ICE
Vehicles
Natural Gas
HEV
PHEV
H2 ICE
Light Heavy-Duty Vocational
$0
($7,163)
$7,976
$21,774
$3,872
Medium Heavy-Duty Vocational
$0
($4,690)
$11,979
$28,552
$19,785
Heavy Heavy-Duty Vocational
$0
($3,232)
$16,949
$40,627
$27,356
Day Cab Tractors
$1,715
$75
$13,290
$37,224
$26,936
Sleeper Cab Tractors
$1,978
$1,888
$16,080
$53,514
$44,919
2.11.3 Technology Adoption Rates in the Additional Potential Compliance Pathways
For the additional example potential compliance pathways to support the feasibility of the
final standards, we developed technology packages relative to our reference case and not relative
to our reference case (i.e., with zero ZEVs). Both are presented in this section.
As we did for the modeled potential compliance pathway, for these additional example
potential compliance pathway we determined the technology mix of technologies for vehicles
with ICE across a range of electrification, which for this additional pathway consists of a mix of
adoption of natural gas vehicles, hybrid vehicles, plug-in hybrid vehicles, H2-ICE vehicles, and
aerodynamic and tire rolling resistant improvements for tractors for MYs 2027, 2030 and 2032,
and including those ZEVs from our projected reference case ZEV adoption rates as described in
1296 The sleeper cab tractor costs were calculated using Vehicles 32, 78, and 79.
450
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RIA Chapter 4. These values represent the total national HD vehicle sales, including those
accounted for in the reference case. However, for this first additional example compliance
pathway, the portion of the overall HD sales that are projected to be ZEVs in the reference case
are the same portion projected to be ZEVs under the final rule (i.e., no additional ZEVs are
included to meet the final Phase 3 standards). Thus, this additional example compliance pathway
supports the feasibility of the Phase 3 standards relative to the "no action" projection of ZEV
adoption nationwide. We considered two scenarios for the adoption rates in MY 2032. The
adoption rates for this pathway are shown in Table 2-144 through Table 2-146.
Table 2-144 Adoption Rates of Technologies to meet Final Standards for MY 2027 Relative to Reference Case
Vehicle Type
Reference Case
ZEVs
ICE Vehicles
Natural Gas
HEV
PHEV
H2 ICE
Light Heavy-Duty Vocational
10%
33%
5%
52%
0%
0%
Medium Heavy-Duty Vocational
7%
48%
5%
40%
0%
0%
Heavy Heavy-Duty Vocational
N/A, standards begin in MY 2029
Day Cab Tractors
N/A, standards begin in MY 2028
Sleeper Cab Tractors
N/A, standards begin in MY 2030
Table 2-145 Adoption Rates of Technologies to meet Final Standards for MY 2030 Relative to Reference Case
Vehicle Type
Reference Case
ZEVs
ICE
Vehicles
Natural Gas
HEV
PHEV
H2ICE
Light Heavy-Duty Vocational
25%
27%
5%
43%
0%
0%
Medium Heavy-Duty Vocational
17%
48%
5%
30%
0%
0%
Heavy Heavy-Duty Vocational
11%
71%
5%
10%
3%
0%
Day Cab Tractors
9%
74%
5%
0%
12%
0%
Sleeper Cab Tractors
2%
91%
5%
2%
0%
0%
451
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Table 2-146 Adoption Rates of Technologies to meet Final Standards for MY 2032 and later Relative to
Reference Case
Vehicle Type
Reference
Case
ZEVs
ICE Vehicles
Natural
Gas
HEV
PHEV
H2 ICE
Scenario 1 (H2-ICE focus)
Light Heavy-Duty Vocational
30%
1%
5%
40%
0%
24%
Medium Heavy-Duty
Vocational
21%
18%
5%
44%
0%
13%
Heavy Heavy-Duty Vocational
14%
42%
5%
27%
0%
12%
Day Cab Tractors
10%
39%
5%
20%
0%
26%
Sleeper Cab Tractors
5%
64%
5%
10%
0%
17%
Scenario 2 (PHEVfocus)
Light Heavy-Duty Vocational
30%
5%
5%
0%
60%
0%
Medium Heavy-Duty
Vocational
21%
19%
5%
24%
32%
0%
Heavy Heavy-Duty Vocational
14%
13%
5%
50%
18%
0%
Day Cab Tractors
10%
0%
5%
20%
55%
10%
Sleeper Cab Tractors
5%
5%
5%
30%
55%
0%
The technology packages for this additional example potential compliance pathway assumed
no ZEV sales in the heavy-duty market in MYs 2027-2032. The pathways consist of a mix of
adoption of natural gas vehicles, hybrid vehicles, plug-in hybrid vehicles, H2-ICE vehicles, and
aerodynamic and tire rolling resistant improvements for tractors.
The technology adoption rates for each of the regulatory groupings for MYs 2027 and 2030
are shown in Table 2-147and Table 2-148, respectively. We considered two scenarios for the
adoption rates in MY 2032, as shown in Table 2-149. Scenario 1 represents a package with more
H2-ICE vehicles, whereas Scenario 2 represents a package with more PHEVs.
Table 2-147 Adoption Rates of Technologies to meet Final Standards for MY 2027 Relative to No ZEV
Baseline
Vehicle Type
ICE Vehicles
Natural Gas
HEV
PHEV
H2 ICE
Light Heavy-Duty Vocational
17%
5%
48%
30%
0%
Medium Heavy-Duty Vocational
32%
5%
40%
23%
0%
Heavy Heavy-Duty Vocational
N/A, standards begin in MY 2029
Day Cab Tractors
N/A, standards begin in MY 2028
Sleeper Cab Tractors
N/A, standards begin in MY 2030
452
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Table 2-148 Adoption Rates of Technologies to meet Final Standards for MY 2030 Relative to No ZEV
Baseline
Vehicle Type
ICE Vehicles
Natural Gas
HEV
PHEV
H2 ICE
Light Heavy-Duty Vocational
2%
5%
45%
48%
0%
Medium Heavy-Duty Vocational
23%
5%
40%
32%
0%
Heavy Heavy-Duty Vocational
68%
5%
10%
7%
10%
Day Cab Tractors
60%
5%
20%
5%
10%
Sleeper Cab Tractors
72%
5%
20%
3%
0%
Table 2-149 Adoption Rates of Technologies to meet Final Standards for MY 2032 and later Relative to No
ZEV Baseline
Vehicle Type
ICE Vehicles
Natural
Gas
HEV
PHEV
H2 ICE
Scenario 1 (H2-ICE focus)
Light Heavy-Duty Vocational
10%
5%
0%
50%
35%
Medium Heavy-Duty Vocational
41%
5%
0%
28%
26%
Heavy Heavy-Duty Vocational
65%
5%
0%
0%
30%
Day Cab Tractors
56%
5%
0%
2%
37%
Sleeper Cab Tractors
73%
5%
0%
0%
22%
Scenario 2 (PHEVfocus)
Light Heavy-Duty Vocational
0%
5%
0%
70%
25%
Medium Heavy-Duty Vocational
0%
5%
24%
70%
1%
Heavy Heavy-Duty Vocational
7%
5%
51%
30%
7%
Short-Haul tractors
0%
5%
30%
40%
25%
Long-Haul tractors
25%
5%
32%
25%
13%
2.11.4 Additional Example Potential Compliance Pathways - Manufacturer Costs to Meet
the Final Standards
The fleet average per-vehicle technology costs of the additional example potential compliance
pathway relative to the reference case (that includes ZEV adoption in the reference case, at the
adoption rates of our "no action" reference case in RIA Chapter 4) are shown in Table 2-150 for
MYs 2027, 2030 and 2032.
Table 2-150 Average Technology Package Cost Per Vehicle to Meet the MY 2027, MY 2030, and MY 2032
Final Standards (2022$) Relative to Reference Case
Regulatory Group
MY 2027
MY 2030
MY 2032
Scenario 1
(H2-ICE focus)
Scenario 2
(PHEV focus)
Light Heavy-Duty Vocational
$3,789
$ 3,072
$ 3,762
$ 12,706
Medium Heavy-Duty Vocational
$4,557
$ 3,359
$ 7,608
$ 11,777
Heavy Heavy-Duty Vocational
N/A
$ 2,752
$ 7,697
$ 15,626
Day Cab Tractors
N/A
$ 5,745
$ 10,327
$ 25,822
Sleeper Cab Tractors
N/A
$ 2,218
$ 10,376
$ 34,456
453
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The fleet average per-vehicle technology costs for the additional example potential
compliance pathway with zero ZEVs are shown in Table 2-151 for MYs 2027, 2030 and 2032.
These costs assume no ZEVs in the nationwide volumes of the baseline (i.e., "No ZEV
baseline").
Table 2-151 Average Technology Package Cost Per Vehicle to Meet the MY 2027, MY 2030, and MY 2032
Final Standards (2022$) Relative to No ZEV Baseline
Vehicle Type
MY 2027
MY 2030
MY 2032
Scenario 1
(H2-ICE focus)
Scenario 2
(PHEV focus)
Light Heavy-Duty Vocational
$ 10,002
$ 13,682
$ 11,884
$ 15,851
Medium Heavy-Duty Vocational
$ 11,124
$ 13,694
$ 12,904
$ 22,825
Heavy Heavy-Duty Vocational
N/A
$ 7,113
$ 8,045
$ 22,586
Day Cab Tractors
N/A
$ 8,246
$ 11,675
$25,614
Sleeper Cab Tractors
N/A
$ 6,340
$ 11,421
$ 24,952
2.11.5 Additional Example Potential Compliance Pathways - Purchaser Cost
Considerations
In this section, we discuss items associated with the purchaser costs for each of the
technologies considered. Under this approach for vehicles with ICE technologies, our evaluation
of payback focuses on whether the technology pays back within the period of first ownership.
Consistent with our Phase 2 approach to vehicles with ICE technologies, if the vehicle with ICE
technology pays back within this period, then we consider that technology within the additional
example potential compliance pathways. We also evaluate payback period, consistent with our
approach to consideration of payback in Phase 2 for vehicles with ICE technologies.1297 See also
our discussion of first ownership in Section II.F. 1 of the preamble. We also evaluated and
included vehicle with ICE technologies if we assessed there may be other reasons that purchasers
would consider such technologies, such as that the vehicles emit nearly zero CO2 emissions at
the tailpipe, low engine-out exhaust emissions provide the opportunity for efficient and durable
after-treatment systems, and the potential for future efficiency improvements within the lead
time provided.
2.11.5.1 ICE Vehicles
Reducing the energy required to move a tractor down the road through aerodynamic
improvements and reductions in tire rolling resistance will lead to reduction in operating costs.
Our technology packages that include additional improvements to ICE vehicles reduced the CO2
emissions, and therefore energy consumption, by 4 percent. The cost savings related to the
reduction in fuel and DEF consumed depends on the number of miles driven, among other
factors. The average DEF and diesel fuel costs for each of the baseline diesel-fueled ICE vehicle
applications in HD TRUCS were developed as discussed in RIA Chapter 2.3.4. As shown in
Table 2-152, the average operating cost savings varies depending on the vehicle ID, ranging
from approximately $280 to $1,800 per year. The average annual operating savings for a day cab
tractor is $700 and is $1,600 for a sleeper cab tractor. Based on the technology package costs
1297 See 81 FR at 73621-622 (tractors) and 73718-19 (vocational vehicles).
454
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shown in Chapter 2.11.2.1 for additional ICE vehicle improvements, the payback period for the
technology improvements would be less than three years for day cab tractors and less than two
years for sleeper cab tractors.
Table 2-152 Annual Operating Savings of Tractors with Aerodynamic and Tire Rolling Resistance
Improvements (2022$)
Vehicle ID
Average
Annual DEF
Cost ($/year)
Average
Annual Diesel
Cost ($/year)
Average
Operating
Cost Savings
($/year)
30Tractor DC C18
$618
$10,839
$458
31 Tractor DC C16-7
$542
$9,501
$402
32Tractor SC C18
$2,452
$42,985
$1,817
33Tractor DC C18
$1,374
$24,102
$1,019
41Tractor DC C17
$1,204
$21,119
$893
45Tractor DC C18
$1,373
$24,097
$1,019
78Tractor SC C18
$1,751
$30,704
$1,298
79Tractor SC C18
$2,452
$42,985
$1,817
80Tractor DC C18 HH
$984
$17,256
$730
81Tractor DC C17
$1,204
$21,119
$893
82Tractor DC C18
$1,373
$24,097
$1,019
83Tractor DC C17
$672
$11,783
$498
84Tractor DC C18
$764
$13,408
$567
lOlTractor DC C18
$385
$6,747
$285
2.11.5.2 Natural Gas Fueled Vehicles
The operating savings of NG vehicles come from both the elimination of the DEF costs
because these vehicles use three-way catalysts and from the reduced fueling costs. When
comparing fuel efficiency between diesel and SI natural gas powered HD vehicles, dependent on
vehicle and duty cycle, natural gas returns 7 percent to 12 percent less fuel economy.1298
Therefore, we calculated the natural gas consumption using a conversion factor of 139.3 standard
cubic feet (scf) to diesel gallon equivalent and applying a 10 percent fuel economy penalty to the
diesel fuel consumption.1299 The average diesel fuel consumption, diesel fuel costs, and DEF
costs for each of the baseline diesel-fueled ICE vehicle applications in HD TRUCS were
developed as discussed in RIA Chapter 2.3.4. We then calculated the average annual natural gas
fuel costs for each of the HD TRUCS applications by vehicle ID using $18.23/thousand cubic
feet price, as shown in Table 2-153.1300 The natural gas powered vehicles have immediate
paybacks for some vehicle categories and payback periods of less than one year for all
applications when the operating savings are compared to the upfront incremental costs of the NG
vehicles, as shown in Chapter 2.11.2.2.
1298 Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuel Data Center, Vehicle and
Infrastructure Cash-Flow Evaluation Tool (VICE), https://afdc.energy.gov/vice_model/, accessed February 17,
2024.
1299 U.S. DOE. Available online: https://afdc.energy.gov/fuels/equivalency_methodology.html
1300 U.S. DOE/Energy Information Administration. Annual Energy Outlook 2023. Reference Case. Table 13.
Transportation Natural Gas Spot Price for 2022. Available online:
https://www.eia.gov/outlooks/aeo/data/browser/#/?id=13-AE02023&cases=ref2023&sourcekey=0
455
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Table 2-153 Annual Operating Savings of Natural Gas Heavy-Duty Vehicles (2022$)
Vehicle ID
Diesel ICE
Vehicle
Average
Annual DEF
Cost ($/year)
Diesel ICE
Vehicle
Average
Annual
Diesel Cost
($/year)
Diesel ICE
Vehicle
Annual
Diesel
Consumption
(gallons)
CNG Vehicle
Annual CNG
Consumpt.
(scf)
CNG Vehicle
Annual CNG
Fuel Costs
(S/ycar)
Average
Operating
Savings
(S/ycar)
01V Amb CI
4-5 MP
$148
$2,481
662
102,510
$1,869
$760
02V Amb CI
2b-3 MP
$216
$3,781
965
149,315
$2,722
$1,275
03V Amb CI
4-5 U
$189
$3,317
846
130,999
$2,388
$1,118
04V Amb CI
2b-3 U
$193
$3,375
861
133,300
$2,430
$1,138
05T Box C18
MP
$512
$8,981
2,292
354,711
$6,466
$3,027
06T Box C18
R
$443
$7,766
1,982
306,820
$5,593
$2,616
07T Box C16
-7 MP
$247
$4,326
1,104
170,872
$3,115
$1,458
08T Box C16
-7 R
$235
$4,125
1,053
162,957
$2,971
$1,389
09T Box C18
U
$636
$11,147
2,844
440,236
$8,026
$3,757
10T Box C16
-7 U
$265
$4,650
1,186
183,635
$3,348
$1,567
11T Box C12
b-3 U
$287
$5,037
1,285
198,932
$3,627
$1,697
12T Box C12
b-3 R
$242
$4,246
1,084
167,708
$3,057
$1,431
13T Box C12
b-3 MP
$259
$4,541
1,159
179,329
$3,269
$1,531
14T Box C14
-5 U
$184
$3,234
825
127,732
$2,329
$1,089
15T Box C14
-5 R
$156
$2,726
696
107,683
$1,963
$919
16T Box C14
-5 MP
$166
$2,915
744
115,145
$2,099
$982
17B Coach C
18 R
$1,109
$19,420
4,955
766,875
$13,980
$6,549
18B Coach C
18 MP
$1,109
$19,420
4,955
766,875
$13,980
$6,549
19C Mix C18
MP
$1,523
$26,700
3,952
611,615
$11,150
$17,073
20T Dump C
18 U
$453
$7,948
1,724
266,810
$4,864
$3,537
21T Dump C
18 MP
$365
$6,404
1,389
214,976
$3,919
$2,850
22T Dump C
16-7 MP
$409
$7,176
1,557
240,917
$4,392
$3,193
23 T Dump C
18 U
$453
$7,948
1,724
266,810
$4,864
$3,537
456
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Vehicle ID
Diesel ICE
Vehicle
Average
Annual DEF
Cost ($/year)
Diesel ICE
Vehicle
Average
Annual
Diesel Cost
($/year)
Diesel ICE
Vehicle
Annual
Diesel
Consumption
(gallons)
CNG Vehicle
Annual CNG
Consumpt.
(scf)
CNG Vehicle
Annual CNG
Fuel Costs
(S/ycar)
Average
Operating
Savings
(S/ycar)
24T Dump C
16-7 U
$451
$7,905
1,715
265,388
$4,838
$3,518
25T Fire C18
MP
$414
$7,257
1,389
214,976
$3,919
$3,752
26T Fire C18
U
$514
$9,007
1,724
266,810
$4,864
$4,657
27T Flat C16-
7 MP
$247
$4,326
1,104
170,872
$3,115
$1,458
28T Flat C16-
7 R
$240
$4,208
1,074
166,194
$3,030
$1,418
29T Flat C16-
7 U
$272
$4,766
1,216
188,228
$3,431
$1,607
30Tractor DC
C18 MP
$618
$10,839
2,767
428,301
$7,808
$3,649
31Tractor DC
C16-7 MP
$542
$9,501
2,426
375,458
$6,845
$3,198
32Tractor SC
C18 U
$2,452
$42,985
10,969
1,697,692
$30,949
$14,488
33Tractor DC
C18 U
$1,374
$24,102
6,153
952,419
$17,363
$8,113
34T Ref C18
MP
$803
$14,067
2,332
361,012
$6,581
$8,289
35T Ref C16-
7 MP
$911
$15,972
2,648
409,894
$7,472
$9,411
36T Ref C18
U
$803
$14,067
2,332
361,012
$6,581
$8,289
37T Ref C16-
7 U
$1,004
$17,594
2,917
451,528
$8,231
$10,367
38RV C18 R
$70
$1,227
313
48,393
$882
$415
39RV C16-
7 R
$72
$1,251
319
49,338
$899
$424
40RV C14-
5 R
$48
$848
216
33,428
$609
$287
41Tractor DC
C17 R
$1,204
$21,119
5,392
834,549
$15,214
$7,109
42RV C18 M
P
$70
$1,227
313
48,393
$882
$415
43RV C16-
7 MP
$74
$1,286
328
50,727
$925
$435
44RV C14-
5 MP
$52
$906
231
35,744
$652
$306
45Tractor DC
C18 R
$1,373
$24,097
6,152
952,224
$17,359
$8,111
46B School
C18 MP
$365
$6,389
1,630
252,294
$4,599
$2,155
47B School
C16-7 MP
$345
$6,042
1,541
238,577
$4,349
$2,038
48B School
C14-5 MP
$205
$3,592
917
141,861
$2,586
$1,211
457
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Vehicle ID
Diesel ICE
Vehicle
Average
Annual DEF
Cost ($/year)
Diesel ICE
Vehicle
Average
Annual
Diesel Cost
($/year)
Diesel ICE
Vehicle
Annual
Diesel
Consumption
(gallons)
CNG Vehicle
Annual CNG
Consumpt.
(scf)
CNG Vehicle
Annual CNG
Fuel Costs
(S/ycar)
Average
Operating
Savings
(S/ycar)
49B School
C12b-3 MP
$205
$3,592
917
141,861
$2,586
$1,211
50B School
C18 U
$453
$7,929
2,023
313,125
$5,708
$2,674
5 IB School
C16-7 U
$345
$6,042
1,541
238,577
$4,349
$2,038
52B School
C14-5 U
$228
$3,985
1,017
157,368
$2,869
$1,344
53B School
C12b-3 U
$228
$3,985
1,017
157,368
$2,869
$1,344
54Tractor SC
C18 R
$2,452
$42,985
10,969
1,697,692
$30,949
$14,488
55B Shuttle
C12b-3 MP
$503
$8,810
2,248
347,904
$6,342
$2,971
56B Shuttle
C14-5 U
$558
$9,773
2,493
385,934
$7,036
$3,295
57B Shuttle
C12b-3 U
$558
$9,773
2,493
385,934
$7,036
$3,295
58B Shuttle
C16-7 MP
$714
$12,503
3,190
493,732
$9,001
$4,216
59B Shuttle
C16-7 U
$786
$13,773
3,514
543,882
$9,915
$4,644
60S Plow CI
6-7 MP
$290
$5,091
1,104
170,911
$3,116
$2,265
61S Plow CI
8 MP
$404
$7,083
1,536
237,771
$4,335
$3,152
62S Plow CI
6-7 U
$320
$5,608
1,216
188,270
$3,432
$2,496
63 S Plow CI
8 U
$501
$8,790
1,907
295,100
$5,380
$3,911
64V Step C16
-7 MP
$377
$6,612
1,687
261,156
$4,761
$2,228
65V Step C14
-5 MP
$166
$2,915
744
115,145
$2,099
$982
66V Step C12
b-3 MP
$254
$4,451
1,136
175,837
$3,206
$1,499
67V Step C16
-7 U
$415
$7,284
1,859
287,682
$5,244
$2,455
68V Step C14
-5 U
$184
$3,234
825
127,732
$2,329
$1,089
69V Step C12
b-3 U
$281
$4,937
1,260
195,058
$3,556
$1,662
70S Sweep C
16-7 U
$430
$7,536
1,538
238,102
$4,341
$3,625
71T Tanker
C18 R
$416
$7,287
1,581
244,642
$4,460
$3,243
72T Tanker
C18 MP
$471
$8,261
1,792
277,319
$5,056
$3,676
458
-------
Vehicle ID
Diesel ICE
Vehicle
Average
Annual DEF
Cost ($/year)
Diesel ICE
Vehicle
Average
Annual
Diesel Cost
($/year)
Diesel ICE
Vehicle
Annual
Diesel
Consumption
(gallons)
CNG Vehicle
Annual CNG
Consumpt.
(scf)
CNG Vehicle
Annual CNG
Fuel Costs
(S/ycar)
Average
Operating
Savings
(S/ycar)
73T Tanker
C18 U
$585
$10,252
2,224
344,184
$6,274
$4,563
74T Tow C18
R
$519
$9,095
1,973
305,328
$5,566
$4,048
75T Tow C16
-7 R
$397
$6,968
1,511
233,920
$4,264
$3,101
76T Tow C18
U
$730
$12,796
2,775
429,564
$7,831
$5,695
77T Tow C16
-7 U
$450
$7,892
1,712
264,934
$4,830
$3,512
78Tractor SC
C18 MP
$1,751
$30,704
7,835
1,212,637
$22,106
$10,349
79Tractor SC
C18 R
$2,452
$42,985
10,969
1,697,692
$30,949
$14,488
80Tractor DC
C18 HH
$984
$17,256
4,403
681,518
$12,424
$5,816
81Tractor DC
C17 R
$1,204
$21,119
5,392
834,549
$15,214
$7,109
82Tractor DC
C18 R
$1,373
$24,097
6,152
952,224
$17,359
$8,111
83Tractor DC
C17 U
$672
$11,783
3,008
465,614
$8,488
$3,967
84Tractor DC
C18 U
$764
$13,408
3,423
529,857
$9,659
$4,513
85B Transit
C18 MP
$1,279
$22,400
5,715
884,542
$16,125
$7,554
86B Transit
C16-7 MP
$486
$8,507
2,170
335,916
$6,124
$2,869
87B Transit
C18 U
$1,279
$22,400
5,715
884,542
$16,125
$7,554
88B Transit
C16-7 U
$535
$9,371
2,391
370,036
$6,746
$3,160
89T Utility C
18 MP
$244
$4,273
927
143,444
$2,615
$1,902
90T Utility C
18 R
$215
$3,769
818
126,541
$2,307
$1,677
9IT Utility C
16-7 MP
$359
$6,285
1,363
211,001
$3,847
$2,797
92T Utility C
16-7 R
$349
$6,113
1,326
205,224
$3,741
$2,721
93T Utility C
14-5 MP
$253
$4,429
961
148,680
$2,710
$1,972
94T Utility C
12b-3 MP
$116
$2,027
440
68,037
$1,240
$903
95T Utility C
14-5 R
$231
$4,060
881
136,337
$2,485
$1,806
96T Utility C
12b-3 R
$231
$4,060
881
136,337
$2,485
$1,806
459
-------
Vehicle ID
Diesel ICE
Vehicle
Average
Annual DEF
Cost ($/year)
Diesel ICE
Vehicle
Average
Annual
Diesel Cost
($/year)
Diesel ICE
Vehicle
Annual
Diesel
Consumption
(gallons)
CNG Vehicle
Annual CNG
Consumpt.
(scf)
CNG Vehicle
Annual CNG
Fuel Costs
(S/ycar)
Average
Operating
Savings
(S/ycar)
97T Utility C
18 U
$302
$5,303
1,150
178,030
$3,245
$2,360
98T Utility C
16-7 U
$395
$6,924
1,502
232,433
$4,237
$3,082
99T Utility C
14-5 U
$280
$4,913
1,066
164,932
$3,007
$2,186
100T Utility
C12b-3 U
$128
$2,248
488
75,475
$1,376
$1,000
lOlTractor D
C C18 U
$385
$6,747
1,723
266,614
$4,860
$2,272
2.11.5.3 H2-ICE Vehicles
The operating costs of H2-ICE vehicles include H2 consumption to power the engine and
DEF consumption to control the NOx emissions. These costs are compared to the operating DEF
and diesel fuel costs for each of the baseline diesel-fueled ICE vehicle applications in HD
TRUCS, as discussed in RIA Chapter 2.3.4.
H2-ICE vehicles operate on H2 gas instead of diesel fuel. We calculated the H2-ICE
hydrogen fuel costs relative to our assessment of the hydrogen costs for FCEVs for each of the
vehicle applications in HD TRUCS, as discussed in RIA Chapter 2.5.3.l.When comparing
efficiencies between FCEV and H2-ICE vehicles, the FCEVs have an average efficiency of 53
percent, as discussed in RIA Chapter 2.5.1.2.1, while H2-ICEV has an efficiency of 42
percent.1301 Therefore, we calculated the H2 fueling costs for H2-ICE relative to the FCEV
fueling costs by applying a ratio of 0.53/0.42.
The H2-ICE vehicles also require a SCR system to control NOx, but the system will be
smaller than a comparable diesel ICE vehicle because the engine-out NOx emissions are lower.
We calculated the annual DEF costs for H2-ICE vehicles as 10 percent of the DEF costs for a
comparable baseline diesel ICE vehicle.1302 The average DEF costs for each of the baseline
diesel-fueled ICE vehicle applications in HD TRUCS were developed as discussed in RIA
Chapter 2.3.4. The net annual operating savings for each of the HD TRUCS vehicle applications
by vehicle ID is shown in Table 2-154. The upfront H2-ICE powertrain technology costs, as
shown in Section II.F.4.ii.c, on average would pay back in 2 years for LHD vocational vehicles,
6 years for MHD vocational vehicles, 9 years for HHD vocational vehicles. The operating costs
for H2-ICE tractors exceed the operating costs of ICE tractors, but there may be other reasons
that purchasers would consider this technology such as the vehicles emit nearly zero CO2
emissions at the tailpipe, the low engine-out exhaust emissions from H2-ICE vehicles provide
1301 FEV, "Hydrogen ICE", The Aachen Colloquium Sustainable Mobility, October 5th - 7th, 2020.
1302 Srna, Ales. Sandia National Laboratory. "The future of H2 internal combustion
engines in California?" Slide 4. December 2023. Available online: https://ww2.arb.ca.gov/sites/default/files/2023-
12/231128sandiapres.pdf
460
-------
the opportunity for efficient and durable after-treatment systems, and the efficiency of H2-ICE
vehicles may continue to improve with time.
Table 2-154 Annual Operating Savings of H2-ICE Heavy-Duty Vehicles (2022$)
Vehicle ID
Diesel Vehicle
Average
Annual DEF
Cost ($/year)
Diesel Vehicle
Average
Annual Diesel
Cost ($/year)
FCEV
Average
Annual H2
Cost ($/year)
H2-ICE
Average
Annual H2
and DEF Cost
($/year)
H2-ICE
Average
Operating
Savings
($/year)
01V Amb C14-5 MP
$148
$2,481
$1,540
$1,958
$671
02V Amb C12b-3 MP
$216
$3,781
$2,181
$2,774
$1,223
03V Amb C14-5 U
$189
$3,317
$1,629
$2,074
$1,432
04V Amb C12b-3 U
$193
$3,375
$1,618
$2,061
$1,507
05T Box C18 MP
$512
$8,981
$6,520
$8,278
$1,215
06T Box C18 R
$443
$7,766
$6,628
$8,408
$(199)
07T Box C16-7 MP
$247
$4,326
$2,704
$3,437
$1,136
08T Box C16-7 R
$235
$4,125
$2,897
$3,680
$680
09T Box C18 U
$636
$11,147
$6,297
$8,010
$3,773
10T Box C16-7 U
$265
$4,650
$2,424
$3,085
$1,830
11T Box C12b-3 U
$287
$5,037
$2,361
$3,008
$2,316
12T Box C12b-3 R
$242
$4,246
$2,811
$3,572
$916
13T Box C12b-3 MP
$259
$4,541
$2,577
$3,277
$1,523
14T Box C14-5 U
$184
$3,234
$1,528
$1,946
$1,472
15T Box C14-5 R
$156
$2,726
$1,817
$2,308
$574
16T Box C14-5 MP
$166
$2,915
$1,666
$2,119
$962
17B Coach C18 R
$1,109
$19,420
$14,660
$18,610
$1,919
18B Coach C18 MP
$1,109
$19,420
$14,593
$18,526
$2,003
19C Mix C18 MP
$1,523
$26,700
$15,693
$19,956
$8,267
20T Dump C18 U
$453
$7,948
$4,141
$5,271
$3,130
21T Dump C18 MP
$365
$6,404
$4,203
$5,341
$1,428
22T Dump C16-7 MP
$409
$7,176
$4,065
$5,170
$2,415
23T Dump C18 U
$453
$7,948
$4,141
$5,271
$3,130
24T Dump C16-7 U
$451
$7,905
$3,795
$4,834
$3,522
25T Fire C18 MP
$414
$7,257
$4,419
$5,617
$2,054
26T Fire C18 U
$514
$9,007
$4,421
$5,630
$3,891
27T Flat C16-7 MP
$247
$4,326
$2,704
$3,437
$1,136
28T Flat C16-7 R
$240
$4,208
$2,951
$3,748
$700
29T Flat C16-7 U
$272
$4,766
$2,485
$3,163
$1,875
30Tractor DC C18 MP
$618
$10,839
$9,896
$12,550
$(1,093)
31 Tractor DC C16-7 MP
$542
$9,501
$8,256
$10,472
$(429)
32Tractor SC C18 U
$2,452
$42,985
$34,601
$43,908
$1,529
33Tractor DC C18 U
$1,374
$24,102
$18,296
$23,225
$2,251
34T Ref C18 MP
$803
$14,067
$6,499
$8,281
$6,589
35T Ref C16-7 MP
$911
$15,972
$9,536
$12,125
$4,758
36T Ref C18 U
$803
$14,067
$6,499
$8,281
$6,589
37T Ref C16-7 U
$1,004
$17,594
$9,405
$11,968
$6,630
38RV C18 R
$70
$1,227
$808
$1,026
$271
39RV C16-7 R
$72
$1,251
$859
$1,091
$232
40RV C14-5 R
$48
$848
$545
$692
$204
41Tractor DC C17 R
$1,204
$21,119
$18,252
$23,153
$(830)
42RV C18 MP
$70
$1,227
$808
$1,026
$271
43RV C16-7 MP
$74
$1,286
$785
$999
$361
44RV C14-5 MP
$52
$906
$498
$634
$324
461
-------
Vehicle ID
Diesel Vehicle
Average
Annual DEF
Cost ($/year)
Diesel Vehicle
Average
Annual Diesel
Cost ($/year)
FCEV
Average
Annual H2
Cost ($/year)
H2-ICE
Average
Annual H2
and DEF Cost
($/year)
H2-ICE
Average
Operating
Savings
($/year)
45Tractor DC C18 R
$1,373
$24,097
$21,865
$27,729
$(2,259)
46B School C18 MP
$365
$6,389
$4,797
$6,090
$664
47B School C16-7 MP
$345
$6,042
$3,019
$3,845
$2,542
48B School C14-5 MP
$205
$3,592
$2,118
$2,693
$1,104
49B School C12b-3 MP
$205
$3,592
$2,073
$2,637
$1,160
50B School C18 U
$453
$7,929
$4,596
$5,845
$2,537
5 IB School C16-7 U
$345
$6,042
$3,019
$3,845
$2,542
52B School C14-5 U
$228
$3,985
$1,950
$2,483
$1,730
53B School C12b-3 U
$228
$3,985
$1,904
$2,425
$1,788
54Tractor SC C18 R
$2,452
$42,985
$41,425
$52,520
$(7,083)
55B Shuttle C12b-3 MP
$503
$8,810
$4,982
$6,338
$2,975
56B Shuttle C14-5 U
$558
$9,773
$4,640
$5,911
$4,420
57B Shuttle C12b-3 U
$558
$9,773
$4,564
$5,816
$4,515
58B Shuttle C16-7 MP
$714
$12,503
$7,897
$10,037
$3,180
59B Shuttle C16-7 U
$786
$13,773
$7,269
$9,252
$5,307
60S Plow C16-7 MP
$290
$5,091
$2,898
$3,685
$1,696
61S Plow C18 MP
$404
$7,083
$4,579
$5,819
$1,668
62 S Plow C16-7 U
$320
$5,608
$2,706
$3,447
$2,481
63 S Plow C18 U
$501
$8,790
$4,493
$5,720
$3,571
64V Step C16-7 MP
$377
$6,612
$4,121
$5,238
$1,751
65V Step C14-5 MP
$166
$2,915
$1,666
$2,119
$962
66V Step C12b-3 MP
$254
$4,451
$2,530
$3,218
$1,487
67V Step C16-7 U
$415
$7,284
$3,787
$4,820
$2,879
68V Step C14-5 U
$184
$3,234
$1,528
$1,946
$1,472
69V Step C12b-3 U
$281
$4,937
$2,318
$2,953
$2,265
70S Sweep C16-7 U
$430
$7,536
$3,702
$4,715
$3,251
71T Tanker C18 R
$416
$7,287
$5,667
$7,193
$510
72T Tanker C18 MP
$471
$8,261
$5,552
$7,054
$1,678
73T Tanker C18 U
$585
$10,252
$5,513
$7,015
$3,822
74T Tow C18 R
$519
$9,095
$6,949
$8,821
$793
75T Tow C16-7 R
$397
$6,968
$4,388
$5,577
$1,788
76T Tow C18 U
$730
$12,796
$6,705
$8,534
$4,992
77T Tow C16-7 U
$450
$7,892
$3,786
$4,823
$3,519
78Tractor SC C18 MP
$1,751
$30,704
$29,632
$37,568
$(5,113)
79Tractor SC C18 R
$2,452
$42,985
$41,425
$52,520
$(7,083)
80Tractor DC C18 HH
$984
$17,256
$15,577
$19,755
$(1,515)
81Tractor DC C17 R
$1,204
$21,119
$18,276
$23,183
$(860)
82Tractor DC C18 R
$1,373
$24,097
$21,892
$27,763
$(2,293)
83Tractor DC C17 U
$672
$11,783
$10,211
$12,952
$(497)
84Tractor DC C18 U
$764
$13,408
$12,240
$15,522
$(1,350)
85B Transit C18 MP
$1,279
$22,400
$12,253
$15,590
$8,089
86B Transit C16-7 MP
$486
$8,507
$5,278
$6,709
$2,284
87B Transit C18 U
$1,279
$22,400
$12,253
$15,590
$8,089
88B Transit C16-7 U
$535
$9,371
$4,804
$6,116
$3,790
89T Utility C18 MP
$244
$4,273
$2,776
$3,528
$989
90T Utility C18 R
$215
$3,769
$2,852
$3,620
$364
91T Utility C16-7 MP
$359
$6,285
$3,667
$4,663
$1,981
92T Utility C16-7 R
$349
$6,113
$3,952
$5,022
$1,440
93T Utility C14-5 MP
$253
$4,429
$2,376
$3,024
$1,658
462
-------
Vehicle ID
Diesel Vehicle
Average
Annual DEF
Cost ($/year)
Diesel Vehicle
Average
Annual Diesel
Cost ($/year)
FCEV
Average
Annual H2
Cost ($/year)
H2-ICE
Average
Annual H2
and DEF Cost
($/year)
H2-ICE
Average
Operating
Savings
($/year)
94T Utility C12b-3 MP
$116
$2,027
$1,047
$1,333
$810
95T Utility C14-5 R
$231
$4,060
$2,502
$3,180
$1,111
96T Utility C12b-3 R
$231
$4,060
$2,502
$3,180
$1,111
97T Utility C18 U
$302
$5,303
$2,722
$3,465
$2,140
98T Utility C16-7 U
$395
$6,924
$3,443
$4,385
$2,934
99T Utility C14-5 U
$280
$4,913
$2,232
$2,845
$2,348
100T Utility C12b-3 U
$128
$2,248
$972
$1,240
$1,136
lOlTractor DC C18 U
$385
$6,747
$6,183
$7,841
$(709)
2.11.5.4 Hybrid and Plug-in Hybrid Vehicles
Hybrid vehicles, similar to other ICE vehicle improvements, will have lower operating costs
than a comparable ICE vehicle due to reduced diesel fuel consumption and DEF consumption.
These HEV costs are compared to the operating DEF and diesel fuel costs for each of the
baseline diesel-fueled ICE vehicle applications in HD TRUCS, as discussed in RIA Chapter
2.3.4. As discussed above, we used an effectiveness level for vocational vehicle hybrid
powertrains of 15 percent and for tractor hybrid powertrains of 10 percent.
The annual operating savings for HEVs was calculated for each of the HD TRUCS vehicle
applications, as shown in Table 2-155 by reducing the diesel ICE DEF and fuel costs by 15
percent for vocational vehicles and 10 percent for tractors. The annual operating savings were
then compared to the upfront technology costs, as shown in Chapter 2.11.2.4. The hybrid
powertrain technology will pay back in 10-11 years for vocational vehicles, but in a shorter
period of time for some applications such as refuse haulers, step vans, and transit buses. The
average payback period for this technology in day cab tractors is 7.5 years and 4 years in sleeper
cab tractors.
Table 2-155 Annual Operating Savings of Hybrid Heavy-Duty Vehicles (2022$)
Diesel ICE
Diesel ICE
HEV Average
Vehicle ID
Average
Annual DEF
Average
Annual Diesel
Operating
Cost Savings
Cost ($/year)
Cost ($/year)
($/year)
01V Amb C14-5 MP
$148
$2,481
$394
02V Amb C12b-3 MP
$216
$3,781
$600
03V Amb C14-5 U
$189
$3,317
$526
04V Amb C12b-3 U
$193
$3,375
$535
05T Box C18 MP
$512
$8,981
$1,424
06T Box C18 R
$443
$7,766
$1,231
07T Box C16-7 MP
$247
$4,326
$686
08T Box C16-7 R
$235
$4,125
$654
09T Box C18 U
$636
$11,147
$1,767
10T Box C16-7 U
$265
$4,650
$737
11T Box C12b-3 U
$287
$5,037
$799
12T Box C12b-3 R
$242
$4,246
$673
13T Box C12b-3 MP
$259
$4,541
$720
14T Box C14-5 U
$184
$3,234
$513
463
-------
Diesel ICE
Diesel ICE
HEV Average
Vehicle ID
Average
Annual DEF
Average
Annual Diesel
Operating
Cost Savings
Cost ($/year)
Cost ($/year)
($/year)
15T Box C14-5 R
$156
$2,726
$432
16T Box C14-5 MP
$166
$2,915
$462
17B Coach C18 R
$1,109
$19,420
$3,079
18B Coach C18 MP
$1,109
$19,420
$3,079
19C Mix C18 MP
$1,523
$26,700
$4,233
20T Dump C18 U
$453
$7,948
$1,260
2 IT Dump C18 MP
$365
$6,404
$1,015
22T Dump C16-7 MP
$409
$7,176
$1,138
23T Dump C18 U
$453
$7,948
$1,260
24T Dump C16-7 U
$451
$7,905
$1,253
25T Fire C18 MP
$414
$7,257
$1,151
26T Fire C18 U
$514
$9,007
$1,428
27T Flat C16-7 MP
$247
$4,326
$686
28T Flat C16-7 R
$240
$4,208
$667
29T Flat C16-7 U
$272
$4,766
$756
30Tractor DC C18 MP
$618
$10,839
$1,146
31Tractor DC C16-7 MP
$542
$9,501
$1,004
32Tractor SC C18 U
$2,452
$42,985
$4,544
33Tractor DC C18 U
$1,374
$24,102
$2,548
34T Ref C18 MP
$803
$14,067
$2,231
35T Ref C16-7 MP
$911
$15,972
$2,532
36T Ref C18 U
$803
$14,067
$2,231
37T Ref C16-7 U
$1,004
$17,594
$2,790
38RV C18 R
$70
$1,227
$195
39RV C16-7 R
$72
$1,251
$198
40RV C14-5 R
$48
$848
$134
41 Tractor DC C17 R
$1,204
$21,119
$2,232
42RV C18 MP
$70
$1,227
$195
43RV C16-7 MP
$74
$1,286
$204
44RV C14-5 MP
$52
$906
$144
45Tractor DC C18 R
$1,373
$24,097
$2,547
46B School C18 MP
$365
$6,389
$1,013
47B School C16-7 MP
$345
$6,042
$958
48B School C14-5 MP
$205
$3,592
$570
49B School C12b-3 MP
$205
$3,592
$570
5OB School C18 U
$453
$7,929
$1,257
5 IB School C16-7 U
$345
$6,042
$958
52B School C14-5 U
$228
$3,985
$632
53B School C12b-3 U
$228
$3,985
$632
54Tractor SC C18 R
$2,452
$42,985
$4,544
55B Shuttle C12b-3 MP
$503
$8,810
$1,397
56B Shuttle C14-5 U
$558
$9,773
$1,550
57B Shuttle C12b-3 U
$558
$9,773
$1,550
58B Shuttle C16-7 MP
$714
$12,503
$1,983
59B Shuttle C16-7 U
$786
$13,773
$2,184
60S Plow C16-7 MP
$290
$5,091
$807
61S Plow C18 MP
$404
$7,083
$1,123
62S Plow C16-7 U
$320
$5,608
$889
63 S Plow C18 U
$501
$8,790
$1,394
64V Step C16-7 MP
$377
$6,612
$1,048
464
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Diesel ICE
Diesel ICE
HEV Average
Vehicle ID
Average
Annual DEF
Average
Annual Diesel
Operating
Cost Savings
Cost ($/year)
Cost ($/year)
($/year)
65V Step C14-5 MP
$166
$2,915
$462
66V Step C12b-3 MP
$254
$4,451
$706
67V Step C16-7 U
$415
$7,284
$1,155
68V Step C14-5 U
$184
$3,234
$513
69V Step C12b-3 U
$281
$4,937
$783
70S Sweep C16-7 U
$430
$7,536
$1,195
7IT Tanker C18 R
$416
$7,287
$1,155
72T Tanker C18 MP
$471
$8,261
$1,310
73T Tanker C18 U
$585
$10,252
$1,626
74T Tow C18 R
$519
$9,095
$1,442
75T Tow C16-7 R
$397
$6,968
$1,105
76T Tow C18 U
$730
$12,796
$2,029
77T Tow C16-7 U
$450
$7,892
$1,251
78Tractor SC C18 MP
$1,751
$30,704
$3,246
79Tractor SC C18 R
$2,452
$42,985
$4,544
80Tractor DC C18 HH
$984
$17,256
$1,824
81 Tractor DC C17 R
$1,204
$21,119
$2,232
82Tractor DC C18 R
$1,373
$24,097
$2,547
83Tractor DC C17 U
$672
$11,783
$1,246
84Tractor DC C18 U
$764
$13,408
$1,417
85B Transit C18 MP
$1,279
$22,400
$3,552
86B Transit C16-7 MP
$486
$8,507
$1,349
87B Transit C18 U
$1,279
$22,400
$3,552
88B Transit C16-7 U
$535
$9,371
$1,486
89T Utility C18 MP
$244
$4,273
$678
90T Utility C18 R
$215
$3,769
$598
9IT Utility C16-7 MP
$359
$6,285
$997
92T Utility C16-7 R
$349
$6,113
$969
93T Utility C14-5 MP
$253
$4,429
$702
94T Utility C12b-3 MP
$116
$2,027
$321
95T Utility C14-5 R
$231
$4,060
$644
96T Utility C12b-3 R
$231
$4,060
$644
97T Utility C18 U
$302
$5,303
$841
98T Utility C16-7 U
$395
$6,924
$1,098
99T Utility C14-5 U
$280
$4,913
$779
100T Utility C12b-3 U
$128
$2,248
$356
lOlTractor DC C18 U
$385
$6,747
$713
Similar to our discussion for ZEVs under the modeled potential compliance pathways, the
IRA provides powerful incentives in reducing the cost to manufacture and purchase PHEVs, as
well as reducing the cost of charging infrastructure as applicable (see further discussion just
below), that facilitates market penetration of PHEV technology in the time frame considered in
this rulemaking. The upfront costs to purchasers of PHEVs would be less than the cost to
manufacturers due to the IRA purchaser tax credit. IRA section 13403, "Qualified Commercial
Clean Vehicles," creates a tax credit of up to $40,000 per Class 4 through 8 HD vehicle (up to
$7,500 per Class 2b or 3 vehicle) for the purchase or lease of a qualified commercial clean
vehicle. This tax credit is available from CY 2023 through CY 2032 and is based on the lesser of
465
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the incremental cost of the clean vehicle over a comparable ICE vehicle or the specified
percentage of the basis of the clean vehicle, up to the maximum $40,000 limitation. Among other
specifications, these vehicles must be on-road vehicles (or mobile machinery) that are propelled
to a significant extent by a battery-powered electric motor or are qualified fuel cell motor
vehicles. For the former, the battery must have a capacity of at least 15 kWh (or 7 kWh if it has a
gross vehicle weight rating of less than 14,000 pounds (Class 3 or below)) and must be
rechargeable from an external source of electricity. For PHEVs, the per-vehicle tax credit cap
limitation is 15 percent of the vehicle cost, which is the limiting factor for many of the
applications. Since this tax credit overlaps with the model years for which we are finalizing
standards (MYs 2027 through 2032), we included it in our calculations for each of those years in
our analysis, as shown in Table 2-156.
Table 2-156 Upfront Incremental Technology Costs for Plug-in Hybrid Vehicle Purchasers - MY 2030 and
Later
Vehicle Type
PHEV Costs before
PHEV Costs After Tax
Tax Credit
Credit
Light Heavy-Duty Vocational
$21,774
$5,465
Medium Heavy-Duty Vocational
$28,552
$7,652
Heavy Heavy-Duty Vocational
$40,627
$8,962
Day Cab Tractors
$37,224
$11,024
Sleeper Cab Tractors
$53,514
$17,043
The purchaser of a HD PHEV would need to consider the recharging needs of the vehicle.
Because the battery sizes in HD PHEVs are significantly smaller than a comparable BEV and
only discharge 60 percent of their battery in-use, the recharging demand is also lower than a
comparable BEV. Therefore, for this analysis, the vehicles use depot charging and recharge with
a 240 V/50 amp outlet that we project are available at no additional cost. There may be
situations where the operator would need to create access to such an outlet, but those costs would
be low. Furthermore, as discussed in RIA Chapter 1.3.2, the IRA can also help reduce the costs
for deploying EVSE infrastructure. The IRA extends the Alternative Fuel Refueling Property
Tax Credit (Section 13404) through 2032, with modifications. Under the new provisions,
businesses would be eligible for up to 30 percent of the costs associated with purchasing and
installing charging equipment in these areas (subject to a $100,000 cap per item) if prevailing
wage and apprenticeship requirements are met.
Plug-in hybrid vehicle operating costs consist of a combination of ICE operation and battery
electric operation. These PHEV costs are calculated relative to the operating costs for each of the
baseline diesel-fueled ICE vehicle applications in HD TRUCS, as discussed in RIA Chapter
2.3.4 and the comparable BEV operating costs, as discussed in RIA Chapter 2.4.4. As discussed
above, we used a utility factor for vocational vehicle PHEV powertrains of 41 percent and for
tractor PHEV powertrains of 22 percent in MY 2030 and later. The annual operating savings was
evaluated for each of the HD TRUCS vehicle applications compared to the comparable baseline
diesel ICE vehicle, as shown in Table 2-157. The incremental cost of the PHEV powertrain
technology after accounting for the IRA tax credit as shown in Table 2-156 for vocational
vehicles will be offset by the operating savings with a payback period of 3 years. The day cab
and sleeper cab tractor upfront costs would be offset with operational savings over an 8- and 9-
year period, respectively.
466
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Table 2-157 Annual Operating Savings of Plug-in Hybrid Heavy-Duty Vehicles (2022$)
Vehicle ID
Average Annual Operating Cost ($/year)
Average PHEV
Operating Savings
Relative to Diesel ICE
($/year)
Diesel ICE
BEV
PHEV
01V Amb C14-5 MP
$5,896
$3,537
$4,928
$967
02V Amb C12b-3 MP
$8,105
$4,565
$6,653
$1,451
03V Amb C14-5 U
$7,069
$3,804
$5,730
$1,338
04V Amb C12b-3 U
$7,112
$3,756
$5,736
$1,376
05T Box C18 MP
$15,759
$8,708
$12,868
$2,891
06T Box C18 R
$14,378
$8,713
$12,056
$2,323
07T Box C16-7 MP
$8,265
$4,714
$6,809
$1,456
08T Box C16-7 R
$7,989
$4,835
$6,696
$1,293
09T Box C18 U
$17,743
$8,550
$13,974
$3,769
10T Box C16-7 U
$8,547
$4,474
$6,877
$1,670
11T Box C12b-3 U
$9,986
$5,036
$7,957
$2,030
12T Box C12b-3 R
$9,157
$5,376
$7,607
$1,550
13T Box C12b-3 MP
$9,466
$5,198
$7,716
$1,750
14T Box C14-5 U
$6,850
$3,582
$5,510
$1,340
15T Box C14-5 R
$6,318
$3,822
$5,295
$1,023
16T Box C14-5 MP
$6,516
$3,697
$5,360
$1,156
17B Coach C18 R
$31,495
$25,342
$28,972
$2,523
18B Coach C18 MP
$31,495
$26,295
$29,363
$2,132
19C Mix C18 MP
$35,420
$16,129
$27,510
$7,909
20T Dump C18 U
$13,145
$6,188
$10,293
$2,853
2IT Dump C18 MP
$11,527
$6,235
$9,357
$2,170
22T Dump C16-7 MP
$12,206
$6,631
$9,920
$2,286
23T Dump C18 U
$12,860
$6,188
$10,124
$2,735
24T Dump C16-7 U
$12,970
$6,403
$10,278
$2,693
25T Fire C18 MP
$12,422
$6,418
$9,960
$2,462
26T Fire C18 U
$13,970
$6,426
$10,877
$3,093
27T Flat C16-7 MP
$8,258
$4,710
$6,803
$1,454
28T Flat C16-7 R
$8,133
$4,914
$6,814
$1,320
29T Flat C16-7 U
$8,718
$4,530
$7,001
$1,717
30Tractor DC C18 MP
$19,409
$12,555
$17,901
$1,508
31Tractor DC C16-7 MP
$17,455
$11,198
$16,078
$1,377
32Tractor SC C18 U
$72,536
$58,080
$69,355
$3,180
33Tractor DC C18 U
$39,459
$30,528
$37,494
$1,965
34T Ref C18 MP
$19,942
$8,472
$15,240
$4,703
35T Ref C16-7 MP
$23,791
$11,886
$18,910
$4,881
36T Ref C18 U
$19,942
$8,472
$15,240
$4,703
37T Ref C16-7 U
$25,492
$11,792
$19,875
$5,617
38RV C18 R
$3,448
$3,752
$3,573
-$125
39RV C16-7 R
$3,415
$3,803
$3,574
-$159
40RV C14-5 R
$2,802
$2,795
$2,800
$3
41Tractor DC C17 R
$36,306
$31,016
$35,142
$1,164
42RV C18 MP
$3,448
$3,752
$3,573
-$125
43RV C16-7 MP
$3,452
$3,588
$3,508
-$56
44RV C14-5 MP
$2,864
$2,658
$2,780
$84
45Tractor DC C18 R
$40,077
$35,466
$39,063
$1,014
46B School C18 MP
$10,931
$6,994
$9,317
$1,614
47B School C16-7 MP
$10,690
$5,486
$8,556
$2,134
48B School C14-5 MP
$7,753
$4,517
$6,426
$1,327
467
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Vehicle ID
Average Annual Operating Cost ($/year)
Average PHEV
Operating Savings
Relative to Diesel ICE
($/year)
Diesel ICE
BEV
PHEV
49B School C12b-3 MP
$7,810
$4,415
$6,418
$1,392
5OB School C18 U
$12,546
$6,773
$10,179
$2,367
5 IB School C16-7 U
$10,690
$5,486
$8,556
$2,134
52B School C14-5 U
$8,164
$4,389
$6,616
$1,548
53B School C12b-3 U
$8,221
$4,283
$6,607
$1,615
55B Shuttle C12b-3 MP
$17,339
$9,413
$14,090
$3,250
56B Shuttle C14-5 U
$18,291
$9,272
$14,594
$3,698
57B Shuttle C12b-3 U
$18,349
$9,112
$14,562
$3,787
58B Shuttle C16-7 MP
$21,342
$11,824
$17,440
$3,902
59B Shuttle C16-7 U
$22,673
$11,375
$18,041
$4,632
60S Plow C16-7 MP
$9,059
$4,933
$7,367
$1,692
61S Plow C18 MP
$12,488
$7,012
$10,243
$2,245
62S Plow C16-7 U
$9,601
$4,771
$7,621
$1,980
63 S Plow C18 U
$13,993
$6,940
$11,101
$2,892
64V Step C16-7 MP
$11,890
$6,529
$9,692
$2,198
65V Step C14-5 MP
$6,490
$3,697
$5,345
$1,145
66V Step C12b-3 MP
$9,295
$5,096
$7,574
$1,722
67V Step C16-7 U
$12,594
$6,277
$10,004
$2,590
68V Step C14-5 U
$6,825
$3,582
$5,495
$1,329
69V Step C12b-3 U
$9,805
$4,936
$7,809
$1,996
70S Sweep C16-7 U
$12,243
$5,850
$9,622
$2,621
71T Tanker C18 R
$13,136
$7,613
$10,872
$2,264
72T Tanker C18 MP
$13,871
$7,529
$11,271
$2,600
73T Tanker C18 U
$15,958
$7,505
$12,493
$3,466
74T Tow C18 R
$15,861
$9,449
$13,232
$2,629
75T Tow C16-7 R
$11,982
$6,908
$9,902
$2,080
76T Tow C18 U
$19,378
$9,262
$15,230
$4,148
77T Tow C16-7 U
$12,950
$6,397
$10,263
$2,687
78Tractor SC C18 MP
$52,579
$47,390
$51,438
$1,142
79Tractor SC C18 R
$72,536
$65,783
$71,050
$1,486
80Tractor DC C18 HH
$27,046
$17,727
$24,996
$2,050
81Tractor DC C17 R
$36,306
$30,385
$35,003
$1,303
82Tractor DC C18 R
$40,077
$34,692
$38,893
$1,185
83Tractor DC C17 U
$21,157
$13,857
$19,551
$1,606
84Tractor DC C18 U
$23,328
$19,861
$22,565
$763
85B Transit C18 MP
$33,319
$16,163
$26,285
$7,034
86B Transit C16-7 MP
$14,962
$8,800
$12,435
$2,526
87B Transit C18 U
$33,296
$16,163
$26,272
$7,024
88B Transit C16-7 U
$15,867
$8,401
$12,806
$3,061
89T Utility C18 MP
$8,510
$4,643
$6,925
$1,585
90T Utility C18 R
$7,982
$4,710
$6,641
$1,342
91T Utility C16-7 MP
$10,862
$5,781
$8,779
$2,083
92T Utility C16-7 R
$10,681
$6,006
$8,764
$1,917
93T Utility C14-5 MP
$8,830
$4,667
$7,123
$1,707
94T Utility C12b-3 MP
$4,683
$2,642
$3,846
$837
95T Utility C14-5 R
$8,364
$4,713
$6,867
$1,497
96T Utility C12b-3 R
$8,305
$4,711
$6,832
$1,474
97T Utility C18 U
$9,304
$4,598
$7,375
$1,930
98T Utility C16-7 U
$11,531
$5,607
$9,102
$2,429
99T Utility C14-5 U
$9,338
$4,555
$7,377
$1,961
468
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Vehicle ID
Average Annual Operating Cost ($/year)
Average PHEV
Operating Savings
Relative to Diesel ICE
($/year)
Diesel ICE
BEV
PHEV
100T Utility C12b-3 U
$4,915
$2,570
$3,953
$962
lOlTractor DC C18 U
$12,992
$8,414
$11,985
$1,007
2.12 Total Cost of Ownership (TCO) Analysis
EPA conducted a TCO analysis for the final rule. This analysis complements the payback
analysis in HD TRUCS that is discussed in the sections above. The TCO analysis relies on the
same upfront and operating costs that are used in HD TRUCS, plus financing costs and residual
value, and can be calculated over several different time horizons.
2.12.1 TCO Analysis Time Horizon
We analyzed a financial time horizon of 5 years.
2.12.2 TCO Analysis Residual Value
A factor that is frequently captured in vehicle TCO analyses is the residual value of a vehicle,
which is calculated at the end of the time horizon of the TCO analysis. To estimate the residual
value for each vehicle, we relied on equations1303 and coefficients that are used in the BEAN
TCO analysis.1304 Equation 2-88 below is used to calculate the residual value fraction of a
vehicle at age k, that can then be multiplied by the upfront cost of the vehicle to estimate the
residual value of a vehicle at age k.
Equation 2-88 Residual Value Fraction
Uk ,,:.C0Rveh(Xd
Residual Value Fraction = e a b 1000
Where,
i = year of evaluation, starting with year 0,
CORveh(Yi) = Cumulative VMT over Year i
ka = Depreciation Coefficient A
kb = Depreciation Coefficient B
Coefficients:
1303 See the TCO tab in ANL's 2022 BEAN Tool MD HD Vehicle Techno-Economic Analysis.xlsm.
1304 Argonne National Laboratory. VTO HFTO Analysis Reports - 2022. "ANL - ESD-2206 Report - BEAN Tool -
MD HD Vehicle Techno-Economic Analysis.xlsm". Available online:
https://anl.app.box.eom/s/an4nx0v2xpudxtpsnkhd5peimzu4j lhk/folder/242640145714.
469
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Coefficient
Tractors
Vocational
Vehicles1305
A
-0.09753
-0.10455
B
-0.000956
-0.000947
There is limited data on residual values for HD ZEVs,1306 therefore, the depreciation
equations do not differ by powertrain type.
2.12.3 TCO Analysis Financing Costs
In response to comments received on the proposal, we included financing costs as part of our
TCO analysis to reflect that not all vehicles are purchased outright. We performed this
calculation by first finding the amount of interest paid per year. This can be seen in Equation
2-89.
/
Equation 2-89 Interest Paid per Year per Powertrain Type
\
— (J-'upfront\pT * (1 —
CupfrontlpT * (1 DP~) * (-it)
—1 * t * 12
A M-Af) , ,
11PT ~ 7
Where,
CUpfront = Upfront cost for each powertrain type ($)
DP = Down payment (%)
i = Interest rate (%)
t = Term of loan (years)
We than summed the interest per year values based on the time horizon selected for the TCO
analysis in Equation 2-90.
Equation 2-90 Total Interest per Year
trco
I cum I PT = ^ I\pt
0
Where,
1305 We used the BEAN "BoxMedium 4" coefficients for all vocational vehicles in HD TRUCS.
1306 Burnham, A., Gohlke, D., Rush, L., Stephens, T., Zhou, Y., Delucchi, M. A., Birky, A., Hunter, C., Lin, Z., Ou,
S., Xie, F., Proctor, C., Wiryadinata, S., Liu, N., Boloor, M. "Comprehensive Total Cost of Ownership
Quantification for Vehicles with Different Size Classes and Powertrains". Argonne National Laboratory. April 1,
2021. Available online: https://publications.anl.gov/anlpubs/2021/05/167399.pdf. See page 58.
470
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tTC0 = Time horizon of TCO analysis (years)
2.12.4 TCO Analysis Results
Table 2-158 shows the TCO results for each of the HD TRUCS vehicle types for MY 2032,
using a 5-year time horizon and financing over a 5-year term with an interest rate of 5% and with
a 20% down payment. The results show that costs for owning and operating a ZEV will be lower
than a comparable ICE vehicle for all MY 2032 BEVs and FCEVs in our technology packages to
support the modeled potential compliance pathway. In fact, all vehicles show several thousands
of dollars in net TCO savings at the five-year point.
Table 2-158 TCO Results for MY 2032 Vehicles (2022$)
Vehicle ID
ICE TCO
BEV TCO
FCEV TCO
Incremental
BEV TCO
Incremental
FCEV TCO
01V Amb C14-5 MP
$65,786
$54,702
$58,392
-$11,084
—
02V Amb C12b-3 MP
$76,393
$56,381
$63,821
-$20,012
—
03V Amb C14-5 U
$72,043
$55,585
$60,327
-$16,459
—
04V Amb C12b-3 U
$71,263
$54,814
$58,362
-$16,450
—
05T Box C18 MP
$178,503
$136,788
$161,327
-$41,715
—
06T Box C18 R
$172,221
$151,245
$162,482
-$20,976
—
07T Box C16-7 MP
$83,275
$68,540
$68,200
-$14,734
—
08T Box C16-7 R
$82,520
$70,633
$69,317
-$11,886
—
09T Box C18 U
$183,240
$148,169
$149,704
-$35,071
—
10T Box C16-7 U
$84,868
$66,794
$66,433
-$18,075
—
11T Box C12b-3 U
$86,089
$57,957
$65,953
-$28,132
—
12T Box C12b-3 R
$81,488
$64,514
$68,253
-$16,974
—
13T Box C12b-3 MP
$83,200
$59,453
$67,054
-$23,748
—
14T Box C14-5 U
$69,607
$53,598
$56,081
-$16,010
—
15T Box C14-5 R
$66,653
$56,135
$57,425
-$10,518
—
16T Box C14-5 MP
$67,753
$51,492
$57,919
-$16,261
—
17B Coach C18 R
$248,018
$211,242
$208,181
-$36,775
—
18B Coach C18 MP
$248,018
$248,483
$214,806
—
-$33,212
19C Mix C18 MP
$281,519
$201,559
$209,307
-$79,960
—
20T Dump C18 U
$163,604
$137,438
$139,244
-$26,166
—
2IT Dump C18 MP
$154,618
$125,582
$139,553
-$29,036
—
22T Dump C16-7 MP
$104,497
$83,335
$78,074
-$21,162
—
23T Dump C18 U
$155,915
$137,438
$128,823
-$18,477
—
24T Dump C16-7 U
$108,739
$96,045
$76,829
-$12,694
—
25T Fire C18 MP
$159,587
$140,223
$140,626
-$19,364
—
26T Fire C18 U
$162,083
$140,321
$130,217
-$21,762
—
27T Flat C16-7 MP
$83,099
$68,464
$67,964
-$14,636
—
28T Flat C16-7 R
$82,410
$76,360
$69,126
-$6,050
—
29T Flat C16-7 U
$85,657
$66,589
$66,935
-$19,068
—
30Tractor DC C18
$195,009
$173,204
$174,861
-$21,805
—
31Tractor DC C17
$171,653
$153,076
$150,768
-$18,577
—
32Tractor SC C18
$493,378
$436,686
$423,455
-$56,693
—
33Tractor DC C18
$297,265
$242,383
$251,833
-$54,882
—
34T Ref C18 MP
$190,480
$155,262
$140,250
-$35,218
—
35T Ref C16-7 MP
$164,834
$124,437
$118,435
-$40,397
—
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Vehicle ID
ICE TCO
BEV TCO
FCEV TCO
Incremental
BEV TCO
Incremental
FCEV TCO
36T Ref C18 U
$190,480
$155,262
$140,250
-$35,218
—
37T Ref C16-7 U
$174,089
$124,178
$117,745
-$49,912
—
38RV C18 R
$87,062
$81,364
$78,285
-$5,698
—
39RV C16-7 R
$56,073
$46,480
$40,832
-$9,592
—
40RV C14-5 R
$46,892
$38,928
$37,717
-$7,964
—
41Tractor DC C17
$278,628
$249,435
$246,185
—
-$32,442
42RV C18 MP
$87,062
$81,364
$78,285
-$5,698
—
43RV C16-7 MP
$56,260
$42,092
$41,446
-$14,168
—
44RV C14-5 MP
$47,204
$40,556
$38,109
-$6,648
—
45Tractor DC C18
$316,196
$294,475
$299,893
—
-$16,303
46B School C18 MP
$127,512
$116,829
$107,604
-$10,683
—
47B School C16-7 MP
$94,478
$71,400
$71,834
-$23,078
—
48B School C14-5 MP
$72,473
$55,881
$60,531
-$16,591
—
49B School C12b-3 MP
$73,769
$54,927
$62,364
-$18,843
—
5OB School C18 U
$136,193
$110,581
$106,592
-$25,612
—
5 IB School C16-7 U
$94,478
$71,400
$71,834
-$23,078
—
52B School C14-5 U
$74,686
$54,631
$59,737
-$20,054
—
53B School C12b-3 U
$75,982
$53,639
$61,562
-$22,343
—
54Tractor SC C18*
$493,378
$500,722
$480,646
$7,344
—
55B Shuttle C12b-3 MP
$121,904
$87,788
$93,821
-$34,116
—
56B Shuttle C14-5 U
$125,946
$86,533
$90,002
-$39,413
—
57B Shuttle C12b-3 U
$127,331
$85,212
$91,660
-$42,119
—
58B Shuttle C16-7 MP
$149,226
$111,662
$113,656
-$37,563
—
59B Shuttle C16-7 U
$156,382
$124,214
$110,410
-$32,168
—
60S Plow C16-7 MP
$87,552
$71,790
$68,508
-$15,763
—
61S Plow C18 MP
$160,024
$151,702
$141,635
-$8,322
—
62S Plow C16-7 U
$90,562
$75,810
$67,633
-$14,752
—
63 S Plow C18 U
$162,246
$149,311
$130,804
-$12,935
—
64V Step C16-7 MP
$102,532
$78,583
$81,501
-$23,949
—
65V Step C14-5 MP
$67,174
$51,492
$56,565
-$15,682
—
66V Step C12b-3 MP
$83,582
$59,375
$68,506
-$24,207
—
67V Step C16-7 U
$106,441
$76,274
$79,788
-$30,167
—
68V Step C14-5 U
$69,029
$53,598
$55,922
-$15,431
—
69V Step C12b-3 U
$86,466
$61,306
$67,407
-$25,159
—
70S Sweep C16-7 U
$104,890
$75,723
$76,233
-$29,167
—
7IT Tanker C18 R
$163,735
$144,979
$151,771
-$18,756
—
72T Tanker C18 MP
$161,631
$131,440
$140,747
-$30,192
—
73T Tanker C18 U
$173,224
$143,837
$140,540
-$29,387
—
74T Tow C18 R
$180,737
$168,314
$164,113
-$12,424
—
75T Tow C16-7 R
$103,255
$95,961
$79,505
-$7,295
—
76T Tow C18 U
$192,305
$163,005
$149,629
-$29,300
—
77T Tow C16-7 U
$108,632
$95,928
$76,732
-$12,704
—
78Tractor SC C18
$384,286
$357,570
$363,745
-$26,716
—
79Tractor SC C18
$493,378
$500,722
$480,646
--
-$12,732
80Tractor DC C18
$237,222
$204,681
$248,029
-$32,541
—
81Tractor DC C17
$278,628
$242,278
$246,662
-$36,349
—
82Tractor DC C18
$316,196
$283,546
$292,381
-$32,650
—
83Tractor DC C17
$192,765
$170,052
$170,060
-$22,714
—
84Tractor DC C18
$216,115
$194,500
$194,294
-$21,616
—
85B Transit C18 MP
$258,078
$197,445
$190,020
-$60,633
—
86B Transit C16-7 MP
$116,379
$100,764
$87,824
-$15,615
—
87B Transit C18 U
$257,405
$196,598
$189,173
-$60,807
--
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Vehicle ID
ICE TCO
BEV TCO
FCEV TCO
Incremental
BEV TCO
Incremental
FCEV TCO
88B Transit C16-7 U
$121,248
$100,739
$85,699
-$20,508
—
89T Utility C18 MP
$137,636
$113,496
$127,651
-$24,141
—
90T Utility C18 R
$134,706
$126,570
$128,003
-$8,135
—
9IT Utility C16-7 MP
$97,258
$75,506
$75,671
-$21,752
—
92T Utility C16-7 R
$96,256
$83,546
$77,079
-$12,711
—
93T Utility C14-5 MP
$81,436
$60,834
$66,837
-$20,602
—
94T Utility C12b-3 MP
$58,450
$49,446
$50,601
-$9,004
—
95T Utility C14-5 R
$79,696
$62,110
$67,641
-$17,586
—
96T Utility C12b-3 R
$78,365
$62,075
$65,530
-$16,290
—
97T Utility C18 U
$136,037
$125,047
$116,981
-$10,989
—
98T Utility C16-7 U
$100,974
$73,804
$74,569
-$27,170
—
99T Utility C14-5 U
$84,254
$59,744
$66,127
-$24,510
—
100T Utility C12b-3 U
$59,739
$48,533
$50,322
-$11,206
—
lOlTractor DC C18
$156,361
$135,818
$139,350
-$20,544
—
* 54Tractor_SC_C18 is not included in our technology package in the modeled potential compliance pathway
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Chapter 3 Program Costs
In this chapter, EPA presents the costs we estimate will be incurred by manufacturers and
purchasers of HD vehicles impacted by the final standards, based upon the potential compliance
pathway modeled for the final rule. We also present the social costs of the final standards. Our
analyses characterize the costs of the potential compliance pathway's technology packages
described in Section HE of the preamble; however, as we note there, manufacturers may elect to
comply using a different combination of HD vehicle and engine technologies than what we have
modeled. We present these costs not only in terms of the upfront incremental technology cost
differences between an HD BEV or FCEV powertrain and a comparable HD ICE powertrain1307
as presented in Chapter 2 of this RIA, but also how those costs will change in years following
implementation due to learning-by-doing effects as described in Chapter 3.2.1 below. These
technology costs are presented in terms of direct manufacturing costs (DMC) and associated
indirect costs (i.e., research and development (R&D), administrative costs, marketing, and other
costs of running a company). These direct and indirect costs when summed are referred to as
"technology package costs" in this section, and when summed and multiplied by vehicle sales
estimated relative to the reference case1308 represent the estimated costs incurred by
manufacturers (i.e., regulated entities) to comply with the final standards should a manufacturer
choose to comply using the compliance pathway EPA modeled as one means of showing the
standards' feasibility.1309
The analysis also includes estimates of the operating costs associated with HD ICE vehicles,
BEVs, and FCEVs. These operating costs do not represent compliance costs for manufacturers,
but rather estimated costs incurred by users of MY 2027 and later HD vehicles.1310 All costs are
presented in 2022 dollars unless noted otherwise.
We break the costs into the following categories and subcategories:
1. Technology Package Costs, which are the sum of DMC and indirect costs. This may
also be called the package retail price equivalent (package RPE). This includes:
a. DMC, which include the costs of materials and labor to produce a product or
piece of technology.
1307 Baseline vehicles are ICE vehicles meeting the MY 2027 Phase 2 standards discussed in RIA Chapter 2.2.2 and
the HD2027 Low NOx standards discussed in RIA Chapter 2.3.2.
1308 As discussed in RIA Chapter 4.2.2, the reference case is a no-action scenario that represents emissions in the
U.S. without the final rulemaking. Note, reference case cost estimates also include costs associated with replacing a
comparable ICE powertrain baseline vehicle with a BEV or FCEV powertrain for ZEV adoption rates in the
reference case.
1309 More accurately, these technology costs represent costs that manufacturers are expected to attempt to recapture
via new vehicle sales. For example, profits are included in the indirect cost calculation. Clearly, profits are not a cost
of compliance—EPA is not imposing new regulations to force manufacturers to make a profit (or dictate pricing
strategies). However, we expect that manufacturers will want to make profits. As such, we expect that manufacturers
will make a profit on the vehicles they sell and we consider those profits as part of the estimated technology costs.
1310 Importantly, the final GHG standards will apply only to new, MY 2027 and later HD vehicles. The legacy fleet
is not subject to the new requirements and, therefore, users of prior model year vehicles will not incur the operating
costs we estimate.
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b. Indirect costs, which include research and development (R&D), warranty,
corporate operations (such as salaries, pensions, health care costs, dealer
support, and marketing), and profits. As described below, we estimate indirect
costs using RPE markups.
Manufacturer Costs, or "manufacturer RPE," which is the package RPE less any
applicable battery tax credits. This includes:
a. Package RPE, as described above. Traditionally, the package RPE is the
manufacturer RPE in EPA cost analyses for HD standards.
b. Battery tax credits from IRA section 13502, "Advanced Manufacturing
Production Credit," which serve to reduce manufacturer costs. The battery tax
credit is described further in preamble Sections I and II and Chapters 1 and 2
of the RIA.
Purchaser Costs, which are the sum of purchaser 1) upfront costs (which include the
upfront vehicle costs (manufacturer (also referred to as purchaser) RPE plus applicable
federal excise and state sales taxes less any applicable vehicle tax credit) plus
applicable EVSE costs), 2) and operating costs. This includes:
a. Manufacturer RPE. In other words, the purchaser incurs the manufacturer's
package costs less any applicable battery tax credits. As described above, we
refer to this as the "manufacturer RPE" in relation to the manufacturer and, at
times, the "purchaser RPE" in relation to the purchaser. These two terms are
equivalent in this analysis.
b. Vehicle tax credit from IRA section 13403, "Qualified Commercial Clean
Vehicles," which serve to reduce purchaser costs. The vehicle tax credit is
described further in preamble Sections I and II and Chapters 1 and 2 of the
RIA.
c. Electric Vehicle Supply Equipment (EVSE) costs, which are the costs
associated with charging equipment and its installation at depots. Our EVSE
cost estimates include indirect costs so are sometimes referred to as "EVSE
RPE."
d. EVSE tax credit from IRA section 13404, "Alternative Fuel Refueling
Property Credit," which serve to reduce purchaser costs. The EVSE tax credit
is described further in Sections I and II of this preamble and Chapters 1 and 2
of the RIA.
e. Federal excise tax and state sales tax, which are upfront costs incurred for
select vehicles for excise tax and for all heavy-duty vehicles for sales tax.
f. Purchaser upfront vehicle costs, which include the manufacturer (also referred
to as purchaser) RPE plus EVSE costs plus applicable federal excise and state
sales taxes less any applicable vehicle tax credits.
g. Operating costs, which include fuel costs (including costs for diesel, gasoline,
CNG, electricity [which varies depending on whether the vehicle is charged at
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a depot or at a public charging facility], and hydrogen), costs for diesel exhaust
fluid (DEF), maintenance and repair costs, insurance, battery replacement
costs, ICE vehicle engine rebuild costs, and EVSE replacement costs.
4. Social Costs, which are the sum of package RPE, EVSE RPE, and operating costs and
computed on at a fleet level on an annual basis. Note that fuel taxes, federal excise tax,
state sales tax and battery, and vehicle and EVSE tax credits as well as state
registration fees on ZEVs are not included in the social costs. Taxes, registration fees,
and tax credits are transfers as opposed to social costs. Social costs includes:
a. Package RPE which, as described above, excludes applicable tax credits.
b. EVSE RPE (which excludes applicable tax credits).
c. Operating costs which include pre-tax fuel costs, charging costs (including
those associated with electrification infrastructure and a public charging
network), DEF costs, insurance, maintenance and repair costs, BEV battery
replacement costs, ICE vehicle engine rebuild costs, and EVSE replacement
costs.
We describe these costs and present our cost estimates in the text that follows, after we
discuss the relevant IRA tax credits and how we have considered them in our estimates. All costs
are presented in 2022 dollars, unless noted otherwise. Table 3-1 shows the gross domestic
product price deflators used to adjust to 2022 dollars. We used the MOVES scenarios discussed
in RIA Chapter 4, the reference, final standards and alternative cases,1311 to compute technology
costs and operating costs as well as social costs on an annual basis. Our costs and tax credits
estimated on a per vehicle basis and do not change between the reference and final standards
cases, but the estimated vehicle populations that will be ICE vehicles, BEVs or FCEVs do
change between the reference and final standards cases. Under our modeled potential compliance
pathway, we project an increase in BEV and FCEVs sales and a decrease of ICE vehicle sales in
the final standards case compared to the reference case, and these changes in vehicle populations
are the determining factor for total cost differences between the reference and final standards
cases. Similarly for the alternative case, we project an increase in BEV and FCEVs sales and a
decrease of ICE vehicle sales compared to the reference case but less than in the final standard
case. Like the final standards case, the changes in vehicle populations are the determining factor
for total cost differences between the reference and alternative cases.
Note that the analysis that follows sometimes presents undiscounted costs and sometimes
presents discounted costs. We discount future costs and benefits to properly characterize their
value in the present or, as directed by the Office of Management and Budget in Advisory
Circular A-4, in the year costs and benefits begin.1312 OMB Circular A-4 guidance (2003) directs
Agencies to use a constant 3-percent and 7-pecent discount rate to calculate present and
annualized values, which we have done here with some exceptions described below. While we
were conducting the analysis for this rule, OMB finalized an update to Circular A-4 (2023), in
1311 As discussed in RIA Chapter 4.2.2, the reference case is a no-action scenario that represents emissions in the
U.S. without the final rulemaking. The final standards and alternative cases represented emissions in the U.S. for
each potential set of GHG standards.
1312 See Advisory Circular A-4, Office of Management and Budget, September 17, 2003.
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which it recommended the general application of a 2-percent discount rate to costs and benefits.
Although the effective date of the updated Circular A-4 does not apply to this rulemaking, we
have also included 2 percent discount rates in our analysis. Present and annualized values are
abbreviated as PV and AV throughout the document tables in this chapter.
Table 3-1 GDP Price Deflators* Used to Adjust Costs to 2022 Dollars
Cost Basis Year
Conversion Factor
2012
1.272
2013
1.250
2014
1.227
2015
1.215
2016
1.203
2017
1.181
2018
1.153
2019
1.133
2020
1.118
2021
1.070
2022
1.000
* Based on the National Income and
Product Accounts, Table 1.1.9 Implicit
Price Deflators for Gross Domestic
Product, Bureau of Economic Analysis,
U.S. Department of Commerce, April
27, 2023.
The cost analysis is done using a tool written in Python and may be found in the docket for
this action. The Python tool, along with some supporting documentation, may be found in the
docket for this action and on our website.1313
Any applicable changes to costs discussed in the final rule preamble Section II, RIA Chapter
2, and RTC Sections 2 and 3 from proposal are reflected in the sections below. We have adjusted
our analysis so that battery learning is on the flatter portion of the learning curve used in the
proposal and is discussed in Chapter 3.2.1 of this RIA.
We also received comment about inclusion of dealer costs and we estimate them as a portion
of RPE in the indirect manufacturing costs of technology package costs in the final rule, as
discussed in Chapter 3.2.2 of this RIA.
3.1 IRA Tax Credits
Our cost analysis quantitatively includes consideration of three IRA tax credits, specifically
the "Advanced Manufacturing Production Credit,", "Qualified Commercial Clean Vehicles,",
and "Alternative Fuel Refueling Property Credit" applied to battery cost, vehicle purchase cost,
and EVSE purchase cost respectively (Sections II.E.l, II.E.2, II.E.3, and II.E.4 of the preamble
and Chapters 1.3.2 and 2.4.3 of the RIA). We note that a detailed discussion of how these tax
credits were considered in our analysis of costs in our technology packages may be found in
Section HE of the preamble and Chapter 2.4.3 of the RIA. The battery tax credits is expected to
reduce manufacturer costs, and in turn purchaser costs, as discussed in Chapter 3.3.2. The
1313 Sherwood, Todd. "Heavy-Duty Cost Tool," memorandum to docket EPA-HQ-OAR-2022-0985. March 2024
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vehicle tax credit and EVSE tax credit are also expected to reduce purchaser costs, as discussed
in Chapter 3.4.2 and Chapter 3.4.4. For the cost analysis discussed in this chapter, the battery tax
credit, vehicle tax credit, and EVSE tax credit were estimated for MYs 2027 through 2032 and
then aggregated for each MOVES source type and regulatory class.
3.2 Technology Package Costs
Technology package costs include estimated technology costs associated with compliance
with the final MY 2027 and later C02 emission standards based on the projected technology
packages modeled for the potential compliance pathway. Individual technology piece costs are
presented in Chapter 2 of the RIA and the costs presented there represent costs in the first year
that a new standard is implemented. For each of the model years following the first year of
implementation, we have applied a learning effect to the technology costs for vehicles we expect
to be sold in that model year which represent the cost reductions expected to occur via the
"learning by doing" phenomenon. 1314 However, for the final rule, we shifted the battery
learning onto the flatter portion of the learning curve used in the proposal. The "learning by
doing" phenomenon is the process by which doing something over and over results in learning
how to do that thing more efficiently which, in turn, leads to reduced resource usage, i.e., cost
savings. This provides a year-over-year cost for each technology as applied to new vehicle
production, which is then used to calculate total technology package costs of the final standards.
This technology package cost calculation approach presumes that the projected technologies
(i.e., those in the particular technology package developed by EPA as a potential compliance
pathway to support the feasibility of the final standards) will be purchased by the vehicle original
equipment manufacturers (OEMs) from their suppliers. So, while the DMC estimates for the
vehicle manufacturer in Chapter 3.2.1 include the indirect costs and profits incurred by the
supplier, the indirect cost markups we apply in Chapter 3.2.2 cover the indirect costs incurred by
vehicle manufacturers to incorporate the new technologies into their vehicles and profit margins
for the vehicle manufacturers typical of the heavy-duty vehicle industry. To address these vehicle
manufacturer indirect costs, we applied industry standard RPE markup factors to the DMC to
estimate vehicle manufacturer indirect costs associated with the new technology. These factors
represent an average price, or RPE, for products assuming all products recapture costs in the
same way. We recognize that this is rarely the actual case since manufacturers typically have
different pricing strategies for different products. For that reason, the RPE should not be
considered a price but instead should be considered more like the average cross-subsidy needed
to recapture both costs and profits to support ongoing business operations. Both the learning
effects applied to direct costs and the application of markup factors to estimate indirect costs are
consistent previous HD GHG rules with the cost estimation approaches used in EPA's past
transportation-related regulatory programs.1315 The sum of the DMC and indirect costs represents
our estimate of technology "package costs" or "package RPE" per vehicle year-over-year. These
per vehicle technology package costs multiplied by estimated sales for the final standards and
reference scenarios. Then the total technology package-related costs for manufacturers (total
1314 "Cost Reduction through Learning in Manufacturing Industries and in the Manufacture of Mobile Sources, Final
Report and Peer Review Report," EPA-420-R-16-018, November 2016.
1315 See the Phase 1 heavy-duty greenhouse gas rule (76 FR 57106, 57319, September 15, 2011); the Phase 2 heavy-
duty greenhouse gas rule (81 FR at 73863, October 25, 2016).
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package costs or total package RPE) associated with the final HD GHG Phase 3 standards is the
difference between the final standards and reference scenarios.
3.2.1 Direct Manufacturing Costs
To produce a unit of output, manufacturers incur direct and indirect manufacturing costs.
DMC includes cost of materials and labor costs. Indirect manufacturing costs are discussed in the
following section, Chapter 3.2.2. The DMCs presented here include the incremental technology
piece costs associated with compliance with the final standards as compared to the technology
piece costs1316 associated with the comparable baseline vehicle. 1317 In our analysis, the ICE
vehicles include a suite of technologies that represent a vehicle that meets the previous MY 2027
Phase 2 CO2 emission standards. Therefore, our direct manufacturing costs for the ICE vehicles
are considered to be $0 because our projected technology package did not add additional C02-
reducing technologies to the ICE vehicles beyond those in the baseline vehicle (we note that
even though such improvements were not included in the modeled potential compliance
pathway, additional ICE vehicle technologies are feasible and manufacturers could utilize such
technologies under a different compliance pathway to meet the final standards; see preamble
Section II.F.6 for one example of such an alternative compliance pathway). The DMC of the
BEVs or FCEVs could be thought of as the technology piece costs of replacing an ICE
powertrain with a BEV or FCEV powertrain.
Throughout this discussion, when we refer to reference case costs we are referring to our cost
estimate of the no-action case (impacts absent this final rule) which include costs associated with
replacing a comparable ICE powertrain baseline vehicle with a BEV or FCEV powertrain for
ZEV adoption rates in the reference case.
We have estimated the DMC by starting with the baseline vehicle, removing the cost of a
comparable ICE powertrain, and adding the cost of a BEV or FCEV powertrain. We calculated
the DMC per vehicle aggregated by MOVES source type and regulatory class via a technology-
sales-weighted average using the DMC and adoption rates for the modeled potential compliance
pathway presented in RIA Chapter 2. This calculation depended on the DMC for each of the 101
Vehicle IDs in HD TRUCS and the mix (i.e., the relative proportions) of those Vehicle IDs in
each combination of source type and regulatory class, which is dependent on overall sales and
technology adoption rates (i.e. the rates projected for our modeled potential compliance pathway)
for each Vehicle ID. DMCs for MY 2027 for each of the 101 Vehicle IDs in HD TRUCS are
shown in RIA Chapter 2.9.2 and the learning effect described later in this section was used to
project costs to future MYs. Sales for each of the 101 Vehicle IDs in HD TRUCS are shown in
Chapter 2.2.3. Technology adoption rates for MYs 2027, 2030, and 2032 for each of the 101
Vehicle IDs in HD TRUCS are shown in Chapter 2.9.3. For the purposes of this cost analysis, we
interpolated these adoption rates similar to the phase-in of the standards described in Chapter
2.10.1 to calculate the adoption rates of Vehicle IDs in each combination of source type and
regulatory class for MYs 2028, 2029, and 2031.
1316 We sometimes use the term "piece cost" simply to refer to the cost associated with a piece of technology. That
could be a turbocharger, it could be an EGR valve, it could also be a BEV powertrain in place of an ICE powertrain.
1317 Baseline vehicles are ICE vehicles meeting the previous MY 2027 Phase 2 GHG standards as discussed in RIA
Chapter 2.2.2 and the HD2027 criteria pollutant standards as discussed in RIA Chapter 2.3.2.
479
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Net incremental costs reflect adding the total costs of components added to the powertrain to
make it a BEV or FCEV, as well as removing the total costs of components removed from a
comparable ICE baseline vehicle to make it a BEV or FCEV.
Chapter 4 of the RIA contains a description of the MOVES vehicle source types and
regulatory classes. In short, we estimate costs in MOVES for vehicle source types that have both
regulatory class populations and associated emission inventories. Also, throughout this section,
LHD refers to light heavy-duty vehicles, MHD refers to medium heavy-duty vehicles, and HHD
refers to heavy heavy-duty vehicles.
For some of the BEV, FCEV and ICE vehicle technologies considered in this analysis,
manufacturer learning effects are expected to play a role in the actual end costs. The "learning
curve" or "experience curve" describes the reduction in unit production costs as a function of
accumulated production volume. We have traditionally applied learning impacts using learning
factors applied to a given cost estimate as a means of reflecting learning-by-doing effects on
future costs.1318 In theory, the cost behavior the learning curve describes applies to cumulative
production volume measured at the level of an individual manufacturer, although it is often
assumed—as EPA has done in past regulatory analyses—to apply at the industry-wide level,
particularly in industries that utilize many common technologies and component supply sources.
We believe there are indeed many factors that cause costs to decrease over time. Research in the
costs of manufacturing has consistently shown that, as manufacturers gain experience in
production, they are able to apply innovations to simplify machining and assembly operations,
use lower cost materials, and reduce the number or complexity of component parts. All of these
factors allow manufacturers to lower the per-unit cost of production (i.e., "learning by doing" the
manufacturing learning curve).1319
Learning effects are applied to all technologies, but at different rates because some of the
expected technologies are already used rather widely in the industry and, presumably, much of
the learning impacts have already occurred. We used this approach in the analysis to support the
HD Phase 2 standards where we applied a steeper learning curve to emerging technologies such
as strong hybrids and waste heat recovery.1320 The steep-portion of learning was applied to
technologies in this Phase 3 rulemaking that are considered to be new or emerging technologies -
BEVs and FCEVs. The learning algorithms applied to each scenario for BEV or FCEV
powertrain costs are summarized in Table 3-2. The final standards, alternative and reference case
all used the same learning factors presented in Table 3-2.
The direct manufacturing costs for BEV, FCEV and ICE powertrains were adjusted to
account for learning effects going forward from the first year of implementation (MY 2027), in
1318 See the 2010 light-duty greenhouse gas rule (75 FR 25324, May 7, 2010); the 2012 light-duty greenhouse gas
rule (77 FR 62624, October 15, 2012); the 2011 heavy-duty greenhouse gas rule (76 FR 57106, September 15,
2011); the 2016 heavy-duty greenhouse gas rule (81 FR 73478, October 25, 2016); the 2014 light-duty Tier 3 rule
(79 FR 23414, April 28, 2014); the heavy-duty NOx rule (88 FR 4296, January 24, 2023).
1319 See "Learning Curves in Manufacturing," L. Argote and D. Epple, Science, Volume 247; "Toward Cost Buy
down Via Learning-by-Doing for Environmental Energy Technologies, R. Williams, Princeton University,
Workshop on Learning-by-Doing in Energy Technologies, June 2003; "Industry Learning Environmental and the
Heterogeneity of Firm Performance, N. Balasubramanian and M. Lieberman, UCLA Anderson School of
Management, December 2006, Discussion Papers, Center for Economic Studies, Washington DC
1320 U.S. EPA. Regulatory Impact Analysis: Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium-
and Heavy-Duty Engines and Vehicles - Phase 2. Chapter 2.11.1. August 2016. EPA-420-R-16-900.
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an approach similar to the one taken for the HD GHG Phase 2 final rule. The same learning
factors were applied to BEV and FCEV powertrain add costs as well as ICE powertrain delete
costs1321 for the reference, final standards, and alternative scenarios and for each model year as
shown in Table 3-2. These learning factors were generated with the expectation that learning on
ICE technologies will slow, relative to their traditional rates, in favor of a focus on BEV and
FCEV technologies. More specifically, overall, under the modeled potential compliance pathway
we anticipate the number of ICE powertrains (including engines and transmissions)
manufactured each year will decrease as more ZEVs enter the market. Due to decreasing
production of ICE powertrains, this scenario may lead to slower cost reductions going forward
than would typically occur from learning-by-doing in the context of component costs for ICE
powertrains. On the other hand, with the inclusion of new hardware costs projected in our
HD2027 final rule's modeled potential compliance pathway to meet the HD2027 emission
standards, we expect learning effects will reduce the incremental cost of these technologies.
The learning algorithms were applied to the BEV, FCEV and ICE powertrains for the 101
Vehicle IDs in the HD TRUCS tool for model years 2027 through 2032 for the values shown in
Table 3-2. The values were then aggregated by MOVES source type and regulatory class via a
technology sales-weighted average using the DMC and adoption rates for the modeled potential
compliance pathway presented in RIA Chapter 2. Then the DMC costs aggregated by MOVES
source type and regulatory class from HD TRUCS for model year 2032 had the learning
algorithm applied from model year 2033 to 2055 shown in Table 3-2. The resultant direct
manufacturing costs and how those costs are expected to reduce over time are presented in
Chapter 3.3.3 on a total cost basis.
Table 3-2 Learning Curve applied to BEV, FCEV and ICE Powertrain Costs in the Reference, Final
Standards and Alternative Scenarios
Model Year
BEV and FCEV Powertrain Learning Scalar
ICE Powertrain Learning Scalar
2027
1.00
1.00
2028
0.94
0.99
2029
0.89
0.99
2030
0.86
0.99
2031
0.83
0.98
2032
0.80
0.98
2033
0.78
0.98
2034
0.76
0.97
2035
0.75
0.97
2036
0.73
0.97
2037
0.72
0.96
2038
0.71
0.96
2039
0.69
0.96
2040
0.68
0.95
2041
0.67
0.95
2042
0.66
0.95
2043
0.66
0.95
1321 Powertrain add costs are the total costs of all components added to a powertrain to make it a BEV or FCEV. ICE
powertrain delete costs are the total costs savings realized from removing all of the ICE powertrain components
from a baseline vehicle.
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Model Year
BEV and FCEV Powertrain Learning Scalar
ICE Powertrain Learning Scalar
2044
0.65
0.94
2045
0.64
0.94
2046
0.63
0.94
2047
0.63
0.94
2048
0.62
0.93
2049
0.61
0.93
2050
0.61
0.93
2051
0.60
0.92
2052
0.60
0.92
2053
0.59
0.92
2054
0.59
0.92
2055
0.59
0.92
3.2.2 Indirect Manufacturing Costs
Indirect manufacturing costs are all the costs associated with producing the unit of output that
are not direct manufacturing costs - for example, they may be related to research and
development (R&D), warranty, corporate operations (such as salaries, pensions, health care
costs, dealer support, and marketing) and profits. An example of a R&D cost for this final
rulemaking includes the engineering resources required to develop a battery state of health
monitor as described in preamble Section III.B. 1. An example of a warranty cost is the future
cost covered by the manufacturer to repair defective BEV or FCEV components and meet the
warranty requirements in Section III.B.2 of the preamble. Indirect costs are generally recovered
by allocating a share of the indirect costs to each unit of goods sold. Although direct costs can be
allocated to each unit of goods sold, it is more challenging to account for indirect costs allocated
to a unit of goods sold. To ensure that regulatory analyses capture the changes in indirect costs,
markup factors (which relate total indirect costs to total direct costs) have been developed and
used by EPA and other stakeholders. These factors are often referred to as RPE multipliers and
are typically applied to direct costs to estimate indirect costs. RPE multipliers provide, at an
aggregate level, the proportionate share of revenues relative shares of revenue where:
Revenue = Direct Costs + Indirect Costs
so that:
Revenue/Direct Costs = 1 + Indirect Costs/Direct Costs = RPE multiplier
and,
Indirect Costs = Direct Costs x (RPE - 1).
If the relationship between revenues and direct costs (i.e., RPE multiplier) can be shown to
equal an average value over time, then an estimate of direct costs can be multiplied by that
average value to estimate revenues, or total costs. Further, that difference between estimated
revenues, or total costs, and estimated direct costs can be taken as the indirect costs. Cost
analysts and regulatory agencies have frequently used these multipliers1322 to predict the
1322 See 75 FR 25324 (May 7, 2010); 76 FR 57106 (September 15, 2011); 77 FR 62624 (October 15, 2012); 79 FR
23414 (April 28, 2014); 81 FR 73478 (October 26, 2016); 86 FR 74434 (December 30, 2021).
482
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resultant impact on costs associated with manufacturers' responses to regulatory requirements
and we are using cost multipliers in this analysis.
The markup factors are based on company filings with the Securities and Exchange
Commission for several engine and engine/truck manufacturers in the HD industry, as detailed in
a study by RTI International that was commissioned by EPA.1323 The RPE factors developed by
RTI for HD engine manufacturers, HD truck manufacturers, and for the HD truck industry as a
whole are shown in Table 3-3.1324 Also shown in Table 3-3 are the RPE factors developed by
RTI for light-duty vehicle manufacturers.1325
Table 3-3 Retail Price Equivalent Factors in the Heavy-Duty and Light-Duty Industries
Cost Contributor
HD Engine
Manufacturer
HD Truck
Manufacturer
HD Truck
Industry
LD Vehicle
Industry
Direct manufacturing cost
1.00
1.00
1.00
1.00
Warranty
0.02
0.04
0.03
0.03
R&D
0.04
0.05
0.05
0.05
Other (admin, retirement, health, dealer, etc.)
0.17
0.22
0.29
0.36
Profit (cost of capital)
0.05
0.05
0.05
0.06
RPE
1.28
1.36
1.42
1.50
For this analysis, EPA based indirect cost estimates for the replacement of HD CI engines
(diesel and compressed natural gas (CNG) MOVES fuel types) on the HD Truck Industry RPE
value shown in Table 3-3. We are using an RPE of 1.42 to compute the indirect costs associated
with the replacement of a diesel-fueled or CNG-fueled powertrain with a BEV or FCEV
powertrain in HD vehicles. For this analysis, EPA based indirect cost estimates for the
replacement of HD SI engines (gasoline MOVES fuel types) on the LD Truck Vehicle RPE
value shown in Table 3-3 because the engines and vehicles more closely match those built by LD
vehicle manufacturers. We are using an RPE of 1.5 to compute the indirect costs associated with
the replacement of a gasoline-fueled powertrain in HD vehicles with a BEV or FCEV
powertrain. The heavy-duty vehicle industry is becoming more vertically integrated and the
direct and indirect manufacturing costs we are analyzing are those that reflect the technology
packages costs OEMs will try to recover at the purchaser level. For that reason, we believe the
two respective vehicle industry RPE values represent the most appropriate factors for this
analysis, and that our approach here is based on robust data and analysis.
EPA received comment that dealers may encounter new costs when new products are
introduced (which we refer to in this rulemaking as "dealer new vehicle selling costs"), such as
1323 Heavy Duty Truck Retail Price Equivalent and Indirect Cost Multipliers, Draft Report, RTI International, RTI
Project Number 021 1577.003.002, July 2010.
1324 The engine manufacturers included were Hino and Cummins; the truck manufacturers included were PACCAR,
Navistar, Daimler and Volvo. Where gaps existed such as specific line items not reported by these companies due to
differing accounting practices, data from the Heavy Duty Truck Manufacturers Industry Report by Supplier
Relations LLC (2009) and Census (2009) data for Other Engine Equipment Manufacturing Industry (NAICS
333618) and Heavy Duty Truck Manufacturing Industry (NAICS 336120) were used to fill the gaps. This is detailed
in the study report at Appendix A. 1.
1325 Rogozhin, Alex, Michael Gallaher, Gloria Helfand, and Walter McManus. "Using Indirect Cost Multipliers to
Estimate the Total Cost of Adding New Technology in the Automobile Industry." International Journal of
Production Economics 124 (2010): 360-368.
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technician training to repair ZEVs. We accounted for these costs in the retail price equivalent
(RPE) multipliers. The heavy-duty RPE in Table 3-3 is based on values from the report, "Heavy
Duty Truck Retail Price Equivalent and Indirect Cost Multipliers,"1326 which contains detailed
cost contributor subcategories, including costs associated with dealer support. Within the dealer
support costs in the study, the contribution of new dealer selling costs in the RPE mark-up
includes a 6 percent markup over manufacturing cost for dealer new vehicle selling costs, from
the "Other" cost contributor shown in Table 3-3. On a related note, we included a change in the
final rule to delay when the reduced maintenance and repair cost savings for ZEVs begin to
accrue to account for the need for initial technician training).1327
Dealer new vehicle selling costs for CY 2027 through 2032 are shown in Table 3-4. We
calculated the dealer new vehicle selling costs as 6 percent of the total direct cost calculated for
the final standards. Table 3-4 also shows the undiscounted sum of dealer new vehicle selling
costs from CY 2027 to 2032.
Table 3-4 Dealer new vehicle selling costs for final standards, undiscounted in Millions of 2022 Dollars*
Calendar Year
Dealer new vehicle
selling costs for final
standards
2027
$20
2028
$21
2029
$17
2030
$26
2031
$30
2032
$35
Sum of 2027 to 2032
$150
*Values rounded to two significant digits
3.2.3 Vehicle Technology Package RPE
Table 3-5 presents the fleet-wide incremental technology costs estimated for both the final
standards and alternative relative to the reference case for the projected adoption of ZEVs in our
technology package on an annual basis. The costs shown in Table 3-5 reflect incremental costs of
the technology package for the final standards as compared to the baseline vehicle and, therefore,
include removal of the ICE-specific components and associated savings and then addition of the
BEV or FCEV components and associated costs.
It is important to note that these are costs and not prices. We do not attempt to estimate how
manufacturers will price their products in the technology package used to develop a potential
compliance pathway. Manufacturers may pass costs along to purchasers via price increases that
reflect actual incremental costs to manufacture a ZEV when compared to a comparable ICE
vehicle. However, manufacturers may also price products higher or lower than what will be
necessary to account for the incremental cost difference. EPA is not attempting to mirror,
1326 Heavy Duty Truck Retail Price Equivalent and Indirect Cost Multipliers, Draft Report, RTI International, RTI
Project Number 021 1577.003.002, July 2010.
1327 See preamble Section II.E.5.
484
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predict, or otherwise approximate individual companies' marketing strategies in estimating costs
for the modeled potential compliance pathway.
Table 3-5 Fleet-Wide Incremental Technology Costs for ZEVs, Millions of 2022 dollars*
Calendar Year
Vehicle Package RPE for
the Final Standards
Relative to the Reference
Case
Vehicle Package RPE for the
Alternative Option Relative
to the Reference Case
2027
$30
$1.8
2028
-$14
-$32
2029
-$85
-$69
2030
$160
$110
2031
$270
$210
2032
$480
$280
2033
$310
$250
2034
$260
$270
2035
$160
$280
2036
$23
$240
2037
-$25
$230
2038
-$140
$210
2039
-$230
$190
2040
-$260
$190
2041
-$330
$180
2042
-$400
$160
2043
-$390
$160
2044
-$450
$140
2045
-$510
$120
2046
-$490
$110
2047
-$530
$100
2048
-$560
$87
2049
-$590
$75
2050
-$570
$76
2051
-$590
$67
2052
-$620
$58
2053
-$640
$50
2054
-$610
$54
2055
-$590
$55
PV, 2%
-$4,200
$3,000
PV, 3%
-$3,200
$2,600
PV, 7%
-$1,000
$1,700
AV, 2%
-$190
$140
AV, 3%
-$170
$140
AV, 7%
-$83
$140
*Values rounded to two significant digits; negative values denote lower costs,
i.e., savings in expenditures.
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3.3 Manufacturer Costs
3.3.1 Relationship to Technology Package RPE
The manufacturer costs in EPA's past HD GHG rulemaking cost analysis on an average per
vehicle basis was only the average per vehicle technology package RPE described in Chapter
3.2.3. However, in the cost analysis for this final rulemaking, we are also taking into account the
IRA battery tax credit in our estimates of manufacturer costs (also referred to in this section as
manufacturer's RPE), as we expect the battery tax credit to reduce manufacturer costs, and in
turn purchaser costs.
3.3.2 Battery Tax Credits
Table 3-6 shows the annual estimated fleet-wide battery tax credits from IRA section 13502,
"Advanced Manufacturing Production Credit," for the final standards relative to the reference
case in 2022 dollars under the potential compliance pathway. These estimates were based on the
detailed discussion in RIA Chapter 2 of how we considered battery tax credits. Both BEVs and
FCEVs include a battery in the powertrain system that may meet the IRA battery tax credit
requirements if the applicable criteria are met. The battery tax credits begin to phase down
starting in CY 2030 and expire after CY 2032.
Table 3-6 Battery Tax Credit in Millions of 2022 dollars *
Calendar Year
Battery Tax Credits
Final Standards
Relative to the
Reference Case
Battery Tax Credits
Alternative Option
Relative to the
Reference Case
2027
$67
$39
2028
$130
$63
2029
$200
$110
2030
$290
$180
2031
$440
$200
2032
$380
$140
2033 and later
$0
$0
PV, 2%
$1,400
$670
PV, 3%
$1,300
$650
PV, 7%
$1,100
$550
AV, 2%
$63
$31
AV, 3%
$69
$34
AV, 7%
$92
$45
*Values rounded to two significant digits.
3.3.3 Manufacturer RPE
The manufacturer RPE is calculated by subtracting the applicable battery tax credit in Table
3-6 from the corresponding technology package RPE from Table 3-5 and the resultant
manufacturer RPE is shown in Table 3-7 and Table 3-8 for the final standards and alternative,
respectively. Table 3-7 and Table 3-8 reflects learning effects on vehicle package RPE and
battery tax credits from CY 2027 through 2055. The sum of the vehicle package RPE and battery
tax credits for each year is shown in the manufacturer RPE column. The difference in
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manufacturer RPE between the final standards and reference case is presented in Table 3-7. The
difference in manufacturer RPE under the potential compliance pathway between the alternative
and reference case is presented in Table 3-8.
Table 3-7 Total Vehicle Package RPE, Battery Tax Credits, and Manufacturer RPE (including Battery Tax
Credits) for the Final Standards Relative to the Reference Case, All Regulatory Classes and All Fuels,
Millions of 2022 dollars*
Calendar
Package
Battery Tax
Manufacturer
Year
RPE
Credits
RPE
2027
$30
-$67
-$37
2028
-$14
-$130
-$140
2029
-$85
-$200
-$290
2030
$160
-$290
-$130
2031
$270
-$440
-$170
2032
$480
-$380
$100
2033
$310
$0
$310
2034
$260
$0
$260
2035
$160
$0
$160
2036
$23
$0
$23
2037
-$25
$0
-$25
2038
-$140
$0
-$140
2039
-$230
$0
-$230
2040
-$260
$0
-$260
2041
-$330
$0
-$330
2042
-$400
$0
-$400
2043
-$390
$0
-$390
2044
-$450
$0
-$450
2045
-$510
$0
-$510
2046
-$490
$0
-$490
2047
-$530
$0
-$530
2048
-$560
$0
-$560
2049
-$590
$0
-$590
2050
-$570
$0
-$570
2051
-$590
$0
-$590
2052
-$620
$0
-$620
2053
-$640
$0
-$640
2054
-$610
$0
-$610
2055
-$590
$0
-$590
PV, 2%
-$4,200
-$1,400
-$5,500
PV, 3%
-$3,200
-$1,300
-$4,500
PV, 7%
-$1,000
-$1,100
-$2,100
AV, 2%
-$190
-$63
-$250
AV, 3%
-$170
-$69
-$240
AV, 7%
-$83
-$92
-$170
* Negative values denote lower costs, i.e., savings in expenditures.
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Table 3-8 Total Package RPE, Battery Tax Credits, and Manufacturer RPE (including Battery Tax Credits)
for the Alternative Option Relative to the Reference Case, All Regulatory Classes and All Fuels, Millions of
2022 dollars*
Calendar Year
Package RPE
Battery Tax
Credits
Manufacturer RPE
2027
$1.8
-$39
-$37
2028
-$32
-$63
-$95
2029
-$69
-$110
-$180
2030
$110
-$180
-$75
2031
$210
-$200
$13
2032
$280
-$140
$140
2033
$250
$0
$250
2034
$270
$0
$270
2035
$280
$0
$280
2036
$240
$0
$240
2037
$230
$0
$230
2038
$210
$0
$210
2039
$190
$0
$190
2040
$190
$0
$190
2041
$180
$0
$180
2042
$160
$0
$160
2043
$160
$0
$160
2044
$140
$0
$140
2045
$120
$0
$120
2046
$110
$0
$110
2047
$100
$0
$100
2048
$87
$0
$87
2049
$75
$0
$75
2050
$76
$0
$76
2051
$67
$0
$67
2052
$58
$0
$58
2053
$50
$0
$50
2054
$54
$0
$54
2055
$55
$0
$55
PV, 2%
$3,000
-$670
$2,300
PV, 3%
$2,600
-$650
$2,000
PV, 7%
$1,700
-$550
$1,100
AV, 2%
$140
-$31
$110
AV, 3%
$140
-$34
$100
AV, 7%
$140
-$45
$91
* Values rounded to two significant digits; Negative values denote lower
costs, i.e., savings in expenditures.
3.4 Purchaser Costs
3.4.1 Purchaser RPE
The purchaser RPE is the estimated upfront vehicle cost paid by the purchaser prior to
considering the IRA vehicle tax credit. Note, as explained above in Chapter 3.3.2, we do
consider the IRA battery tax credit in estimating the manufacturer RPE, which in this analysis we
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then consider to be equivalent to the purchaser RPE because we assume pass through of the IRA
battery tax credit from the manufacturer to the purchaser. In other words, in this analysis, the
manufacturer RPE and purchaser RPE are equivalent terms. The purchaser RPEs reflect the same
values as the corresponding manufacturer RPEs presented in Chapter 3.3.3.
3.4.2 Vehicle Purchase Tax Credits
Table 3-9 shows the annual estimated vehicle tax credit for BEV and FCEV vehicles from
IRA section 13403, "Qualified Commercial Clean Vehicles," for the final standards and
alternative relative to the reference case in 2022 dollars under the potential compliance pathway.
These estimates were based on the detailed discussion in RIA Chapter 2.4.3.5 of how we
considered vehicle tax credits. The vehicle tax credits carry through to MY 2032 with the value
diminishing over time as vehicle costs decrease due to the learning effect as shown in above in
Chapter 3.2.1. Beginning in CY 2033, the tax credit program expires.
Table 3-9 Vehicle Tax Credit in Millions 2022 dollars*
Calendar Year
Vehicle Tax Credit
Vehicle Tax Credit
for the Final Standards
for the Alternative Option
Relative to the
Relative to the
Reference Case
Reference Case
2027
$39
$15
2028
$23
$5.1
2029
$10
$2.3
2030
$180
$120
2031
$450
$240
2032
$940
$390
2033 and later
$0
$0
PV, 2%
$1,500
$700
PV, 3%
$1,400
$670
PV, 7%
$1,100
$550
AV, 2%
$67
$32
AV, 3%
$73
$35
AV, 7%
$93
$45
*Values rounded to two significant digits
3.4.3 Depot Electric Vehicle Supply Equipment Costs
EVSE and associated costs are described in Chapter 2.6. EVSE is needed for charging of
BEVs and is not needed for FCEVs.1328 As discussed in this RIA, under the potential compliance
1328 As discussed in RIA Chapter 2.5, rather than focusing on depot hydrogen fueling infrastructure costs that would
be incurred upfront, we included FCEV infrastructure costs in our per-kilogram retail price of hydrogen. Retail price
of hydrogen is the total price of hydrogen when it becomes available to the end user, including the costs of
production, distribution, storage, and dispensing at a fueling station. This approach is consistent with the method we
use in HD TRUCS for comparable ICE vehicles, where the equivalent diesel fuel costs are included in the diesel fuel
price instead of accounting for the costs of fuel stations separately. We also used this approach for the final rule in
accounting for the BEVs using public charging.
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pathway we assume that EVSE costs for depot charging1329 are incurred by purchasers, i.e.,
heavy-duty vehicle purchasers/owners. The depot EVSE cost estimates are assumed to include
both direct and indirect costs and are sometimes referred to in this final rulemaking as EVSE
RPE costs. For these EVSE cost estimates, we project that up to two vocational vehicles or up to
four tractors can share one EVSE port if there is sufficient dwell time for all vehicles to meet
their daily charging needs.1330 We analyzed EVSE costs in 2022 dollars on a fleet-wide basis for
this analysis. The fleet-wide annual costs associated with EVSE for each MOVES source type
and regulatory class are shown in Table 3-10 for both the final standards and alternative options
relative to the reference case.
1329 As discussed in Chapters 2.4 and 2.6, we modeled EVSE costs for public charging as part of the operating costs.
The purchasers of these vehicles would not incur an upfront cost to purchase and install EVSE. As discussed in RIA
Chapter 2.4.4.2 for public charging and in Chapter 2.5.3 for FCEVs, we included the respective infrastructure cost in
our retail electricity prices per kwh and retail prices per kg of hydrogen.
1330 We note that for some of the vehicle types we evaluated, additional vehicles could share an EVSE port and still
meet their daily electricity consumption needs. However, we are choosing to limit sharing to two to four vehicles per
EVSE port to be conservative as the market develops.
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Table 3-10 Depot EVSE Costs, Millions 2022 dollars *
EVSE Costs for
EVSE Costs for the
the Final
Alternative Option
Calendar Year
Standards
Relative to the
Relative to the
Reference Case
Reference Case
2027
$440
$250
2028
$610
$290
2029
$730
$410
2030
$630
$360
2031
$1,300
$480
2032
$2,000
$620
2033
$1,900
$490
2034
$1,700
$380
2035
$1,600
$260
2036
$1,600
$240
2037
$1,500
$220
2038
$1,500
$200
2039
$1,500
$180
2040
$1,500
$160
2041
$1,500
$140
2042
$1,400
$130
2043
$1,400
$130
2044
$1,400
$120
2045
$1,400
$120
2046
$1,300
$110
2047
$1,300
$110
2048
$1,300
$100
2049
$1,300
$99
2050
$1,200
$95
2051
$1,200
$92
2052
$1,200
$89
2053
$1,200
$86
2054
$1,200
$82
2055
$1,100
$79
PV, 2%
$28,000
$5,000
PV, 3%
$25,000
$4,600
PV, 7%
$15,000
$3,400
AV, 2%
$1,300
$230
AV, 3%
$1,300
$240
AV, 7%
$1,300
$270
*Values rounded to two significant digits
3.4.4 Electric Vehicle Supply Equipment Tax Credits
Table 3-11 shows the annual estimated EVSE tax credit from IRA section 13404, "Alternative
Fuel Refueling Property Credit," for the final standards relative to the reference case, in 2022
dollars under the potential compliance pathway. These estimates were based on the detailed
discussion in RIA Chapter 2 of how we considered EVSE tax credits. The EVSE tax credits
carry through to MY 2032. Beginning in CY 2033, the tax credit program expires.
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Table 3-11 Incremental EVSE Tax Credit for the Final Standards Relative to the Reference Case for in
Millions 2022 Dollars*
Calendar
EVSE Tax Credit for the Final Standards
EVSE Tax Credit for the Alternative Option
Year
Relative to the Reference Case
Relative to the Reference Case
2027
$79
$46
2028
$110
$52
2029
$130
$73
2030
$110
$65
2031
$240
$87
2032
$360
$110
2033 and later
$0
$0
PV, 2%
$950
$400
PV, 3%
$910
$380
PV, 7%
$770
$330
AV, 2%
$43
$18
AV, 3%
$47
$20
AV, 7%
$63
$27
*Values rounded to two significant digits
3.4.5 Federal Excise Tax and State Sales Tax
As discussed in Preamble II.E.5, in the NPRM we did not account for the upfront taxes paid
by the purchaser of the vehicle. Several commenters raised concerns about additional costs that
were not included in HD TRUCS for the proposal. The concern raised by the greatest number of
commenters was the additional cost from Federal Excise Tax (FET) and State Sales Tax because
higher BEV and FCEV upfront vehicle cost under the potential compliance pathway. We agree
with the commenters with regards to FET and State Sales Tax. For the final rule, we added FET
and state sale tax as a part of the purchaser upfront vehicle cost calculation. A FET of 12 percent
was applied to the upfront powertrain technology retail price equivalent for Class 8 heavy-duty
vehicles and all tractors in HD TRUCS. Similarly, a state tax of 5.02 percent, the average sales
tax in the U.S. for heavy-duty vehicles discussed in RIA Chapter 2.4.3, was applied to the
upfront powertrain technology retail price equivalent and was added to all vehicles for the final
rule analysis.
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Table 3-12 Incremental Federal Excise Tax and State Sales Tax for the Final Standards Relative to the
Reference Case for in Millions 2022 Dollars*
Calendar
State Sales Taxes, Final standards
Federal Excise
Taxes, Final
standards
relative to
reference case
State Sales
Taxes,
Alternative
Federal Excise
Taxes,
Alternative
Year
relative to reference case
standards
standards
relative to
relative to
reference case
reference case
2027
-$1.9
$1.1
-$1.9
$0
2028
-$7.2
-$0.90
-$4.8
-$0.10
2029
-$14
-$7.6
-$9.1
-$3.9
2030
-$6.4
$16
-$3.8
$12
2031
-$8.7
$44
$0.65
$29
2032
$5
$110
$7.2
$50
2033
$15
$120
$13
$55
2034
$13
$110
$13
$51
2035
$8.0
$99
$14
$47
2036
$1.1
$88
$12
$42
2037
-$1.3
$82
$12
$39
2038
-$7
$73
$10
$35
2039
-$12
$64
$9.6
$32
2040
-$13
$61
$9.7
$30
2041
-$17
$54
$9.3
$27
2042
-$20
$47
$8.3
$24
2043
-$20
$45
$8.0
$24
2044
-$23
$39
$6.9
$21
2045
-$26
$33
$5.9
$19
2046
-$25
$32
$5.7
$18
2047
-$27
$28
$5.0
$16
2048
-$28
$24
$4.4
$15
2049
-$30
$19
$3.8
$13
2050
-$28
$20
$3.8
$13
2051
-$30
$17
$3.4
$12
2052
-$31
$13
$2.9
$11
2053
-$32
$10
$2.5
$9.8
2054
-$30
$11
$2.7
$9.9
2055
-$30
$11
$2.8
$9.8
PV, 2%
-$280
$990
$12
$510
PV, 3%
-$230
$890
$99
$450
PV, 7%
-$110
$580
$56
$290
AV, 2%
-$13
$45
$5.3
$23
AV, 3%
-$12
$46
$5.2
$24
AV, 7%
00
00
&
1
$47
$4.6
$24
* Values rounded to two significant digits; Negative values denote lower costs, i.e., savings in expenditures.
3.4.6 Purchaser Upfront Costs
The expected upfront incremental costs to the purchaser include the purchaser upfront vehicle
costs plus the purchaser upfront EVSE costs as applicable, after tax credits and including FET
and sales state tax, under the potential compliance pathway. In other words, the estimated
purchaser upfront incremental costs include the purchaser RPE discussed in Chapter 3.4.1 less
the vehicle tax credit discussed in Chapter 3.4.2 plus the EVSE RPE in Chapter 3.4.3 less the
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EVSE tax credit discussed in 3.4.4 plus any applicable excise and sales tax discussed in Chapter
3.4.5. Table 3-13 shows the estimated incremental upfront purchaser costs for BEVs and FCEVs
by calendar year for the final standards relative to the reference case.
Table 3-14 shows the estimated incremental upfront purchaser costs for BEVs and FCEVs by
calendar year for the alternative option relative to the reference case. Note that EVSE costs are
associated with BEVs using depot charging only; FCEVs and BEVs solely using public charging
do not have any associated upfront EVSE costs because those costs are reflected in the public
hydrogen refueling and charging electricity costs.
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Table 3-13 Incremental Purchaser Upfront Costs for the Final Standards Relative to the Reference Case for
in Millions 2022 dollars*
Calendar
Year
Purchaser
RPE
State
Sales
Taxes
Federal
Excise
Taxes
Vehicle
Purchase
Tax Credit
EVSE Costs for
Depot Charging
EVSE
Tax
Credit
Total
Upfront
Purchaser
Cost
2027
-$37
-$1.9
$1.1
-$39
$440
-$79
$280
2028
-$140
-$7.2
-$0.9
-$23
$610
-$110
$330
2029
-$290
-$14
-$7.6
-$10
$730
-$130
$280
2030
-$130
-$6.4
$16
-$180
$630
-$110
$210
2031
-$170
-$8.7
$44
-$450
$1,300
-$240
$500
2032
$100
$5.0
$110
-$940
$2,000
-$360
$920
2033
$310
$15
$120
$0
$1,900
$0
$2,300
2034
$260
$13
$110
$0
$1,700
$0
$2,100
2035
$160
$8.0
$99
$0
$1,600
$0
$1,800
2036
$23
$1.1
$88
$0
$1,600
$0
$1,700
2037
-$25
-$1.3
$82
$0
$1,500
$0
$1,600
2038
-$140
-$7
$73
$0
$1,500
$0
$1,500
2039
-$230
-$12
$64
$0
$1,500
$0
$1,300
2040
-$260
-$13
$61
$0
$1,500
$0
$1,300
2041
-$330
-$17
$54
$0
$1,500
$0
$1,200
2042
-$400
-$20
$47
$0
$1,400
$0
$1,100
2043
-$390
-$20
$45
$0
$1,400
$0
$1,100
2044
-$450
-$23
$39
$0
$1,400
$0
$960
2045
-$510
-$26
$33
$0
$1,400
$0
$860
2046
-$490
-$25
$32
$0
$1,300
$0
$850
2047
-$530
-$27
$28
$0
$1,300
$0
$780
2048
-$560
-$28
$24
$0
$1,300
$0
$710
2049
-$590
-$30
$19
$0
$1,300
$0
$650
2050
-$570
-$28
$20
$0
$1,200
$0
$650
2051
-$590
-$30
$17
$0
$1,200
$0
$610
2052
-$620
-$31
$13
$0
$1,200
$0
$560
2053
-$640
-$32
$10
$0
$1,200
$0
$510
2054
-$610
-$30
$11
$0
$1,200
$0
$530
2055
-$590
-$30
$11
$0
$1,100
$0
$530
PV, 2%
-$5,500
-$280
$990
-$1,500
$28,000
-$950
$21,000
PV, 3%
-$4,500
-$230
$890
-$1,400
$25,000
-$910
$19,000
PV, 7%
-$2,100
-$110
$580
-$1,100
$15,000
-$770
$12,000
AV, 2%
-$250
-$13
$45
-$67
$1,300
-$43
$970
AV, 3%
-$240
-$12
$46
-$73
$1,300
-$47
$970
AV, 7%
-$170
00
00
&
1
$47
-$93
$1,300
-$63
$960
*Values rounded to two significant digits; negative values denote lower costs, i.e., savings in expenditures.
495
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Table 3-14 Incremental Purchaser Upfront Costs for the Alternative Option Relative to the Reference Case in
Millions 2022 dollars*
Calendar
Year
Purchaser
RPE
State
Sales
Taxes
Federal
Excise
Taxes
Vehicle
Purchase
Tax Credit
EVSE Costs for
Depot Charging
EVSE
Tax
Credit
Total
Upfront
Purchaser
Cost
2027
-$37
-$1.9
$0
-$15
$250
-$46
$150
2028
-$95
-$4.8
-$0.10
-$5.1
$290
-$52
$130
2029
-$180
-$9.1
-$3.9
-$2.3
$410
-$73
$140
2030
-$75
-$3.8
$12
-$120
$360
-$65
$110
2031
$13
$0.65
$29
-$240
$480
-$87
$190
2032
$140
$7.2
$50
-$390
$620
-$110
$310
2033
$250
$13
$55
$0
$490
$0
$810
2034
$270
$13
$51
$0
$380
$0
$710
2035
$280
$14
$47
$0
$260
$0
$600
2036
$240
$12
$42
$0
$240
$0
$540
2037
$230
$12
$39
$0
$220
$0
$510
2038
$210
$10
$35
$0
$200
$0
$460
2039
$190
$9.6
$32
$0
$180
$0
$420
2040
$190
$9.7
$30
$0
$160
$0
$400
2041
$180
$9.3
$27
$0
$140
$0
$360
2042
$160
$8.3
$24
$0
$130
$0
$330
2043
$160
$8.0
$24
$0
$130
$0
$320
2044
$140
$6.9
$21
$0
$120
$0
$290
2045
$120
$5.9
$19
$0
$120
$0
$260
2046
$110
$5.7
$18
$0
$110
$0
$250
2047
$100
$5.0
$16
$0
$110
$0
$230
2048
$87
$4.4
$15
$0
$100
$0
$210
2049
$75
$3.8
$13
$0
$99
$0
$190
2050
$76
$3.8
$13
$0
$95
$0
$190
2051
$67
$3.4
$12
$0
$92
$0
$170
2052
$58
$2.9
$11
$0
$89
$0
$160
2053
$50
$2.5
$9.8
$0
$86
$0
$150
2054
$54
$2.7
$9.9
$0
$82
$0
$150
2055
$55
$2.8
$9.8
$0
$79
$0
$150
PV, 2%
$2,300
$120
$510
-$700
$5,000
-$400
$6,900
PV, 3%
$2,000
$99
$450
-$670
$4,600
-$380
$6,100
PV, 7%
$1,100
$56
$290
-$550
$3,400
-$330
$4,000
AV, 2%
$110
$5.3
$23
-$32
$230
-$18
$310
AV, 3%
$100
$5.2
$24
-$35
$240
-$20
$320
AV, 7%
$91
$4.6
$24
-$45
$270
-$27
$320
*Values rounded to two significant digits; negative values denote lower costs, i.e., savings in expenditures.
3.4.7 Operating Costs
We have estimated six types of operating costs associated with the final HD GHG Phase 3
emission standards and our potential projected compliance pathway's technology packages that
includes BEV or FCEV powertrains. These six types of operating costs include changes in fuel
costs of BEVs and FCEVs compared to comparable ICE vehicles, avoided diesel exhaust fluid
(DEF) consumption by BEVs and FCEV compared to comparable diesel-fueled ICE vehicles,
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reduced maintenance and repair costs of BEVs and FCEVs as compared to comparable ICE
vehicles, costs associated with insurance of BEVs and FCEVs as compared to comparable ICE
vehicles, and costs associated with battery replacement and engine rebuilding. To estimate fuel,
DEF and maintenance and repair costs of ICE vehicles, EPA used the results of MOVES runs, as
discussed in RIA Chapter 4, to estimate costs associated with fuel consumption, DEF
consumption, and VMT. Similarly, the electricity, hydrogen fuel, and maintenance and repair
costs of BEVs and FCEVs were calculated based on the MOVES outputs for fuel/electricity
consumption and VMT. Battery replacement and engine rebuild costs are based on the years in
operation of the vehicle. Insurance costs are based on the incremental upfront cost of the vehicle
and calculated for each year a vehicle is operating. We have estimated the net effect on fuel
costs, DEF costs, maintenance and repair costs, insurance, and battery replacement. We describe
our approach below.
3.4.7.1 Costs Associated with Fuel Usage and Energy Consumption
To determine the total costs associated with fuel usage for MY 2027, 2030 and 2032 ICE
vehicles, EPA multiplied the fuel consumption for each MOVES source type/regulatory
class/fuel type combination by the applicable fuel price from the AEO 2023 reference case for
diesel, gasoline, or CNG prices over the lifetime of the vehicle.1331 We used retail fuel prices
since we expect that retail fuel prices are the prices paid by owners of these ICE vehicles. For
electric vehicle costs, the electricity prices used estimates of the cost per kWh of charging at
depot and public charge points. How these costs per kWh were generated is presented in Chapter
2.4.4.2 and the values used to estimate program costs are shown in Table 3-15. For hydrogen
vehicle fuel costs, we used the hydrogen prices presented in Chapter 2.5.3.1 and presented in
Table 3-16. To calculate the average cost per mile of fuel usage for each scenario, MOVES
source type/ regulatory class/fuel type combination, the fuel cost was divided by the VMT for
each of the MY 2027 vehicles from calendar year 2027 to 2055. The estimates of fuel cost per
mile by MOVES source type, regulatory class and fuel combination for MY 2027 vehicles under
the final standards are shown in Table 3-37, Table 3-38 and Table 3-39 for with 2, 3 and 7
percent discounting, respectively. Fuel costs per mile calculations by MOVES source type,
regulatory class and fuel combination for MY 2030 at discount rates of 2, 3 and 7 percent in are
shown in Table 3-40, Table 3-41 and Table 3-42, respectively. For MY 2030, the fuel costs per
mile are from the sum of the total fuel costs and VMT from calendar year 2030 to 2055. MY
2032 fuel costs per mile by MOVES source type, regulatory class and fuel combination at
discount rates of 2, 3 and 7 percent are shown in Table 3-43, Table 3-44 and Table 3-45,
respectively. For MY 2032, the fuel costs per mile are from the sum of the total fuel costs and
VMT from calendar year 2032 to 2055. Blank values (denoted by a "-") in Table 3-37 through
Table 3-45 represent cases where a given MOVES source type and regulatory class did not use a
specific fuel type for a given MY.1332
1331 Reference Case Projection Tables, U.S. Energy Information Administration. Annual Energy Outlook 2023.
1332 For example, there were no vehicles in our MOVES runs for the transit bus source type in the MOVES LHD45
regulatory class that are diesel-fueled, so the value in the table is left blank for MY 2032.
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Table 3-15 Charging Prices by Type of Charge Point (2022 dollars per kWh)*
Calendar Year
Depot Charging
Public Charging
2027
$0.1236
$0.1960
2028
$0.1236
$0.1960
2029
$0.1209
$0.1933
2030
$0.1183
$0.1907
2031
$0.1181
$0.1905
2032
$0.1179
$0.1903
2033
$0.1177
$0.1902
2034
$0.1176
$0.1900
2035
$0.1174
$0.1898
2036
$0.1172
$0.1897
2037
$0.1171
$0.1895
2038
$0.1170
$0.1894
2039
$0.1168
$0.1892
2040
$0.1167
$0.1891
2041
$0.1161
$0.1885
2042
$0.1155
$0.1879
2043
$0.1149
$0.1873
2044
$0.1143
$0.1867
2045
$0.1137
$0.1861
2046
$0.1128
$0.1852
2047
$0.1119
$0.1843
2048
$0.1110
$0.1834
2049
$0.1101
$0.1826
2050
$0.1093
$0.1817
2051
$0.1093
$0.1817
2052
$0.1093
$0.1817
2053
$0.1093
$0.1817
2054
$0.1093
$0.1817
2055
$0.1093
$0.1817
* Values shown to 4 significant digits
Table 3-16 Hydrogen Price (2022 dollars per kg)
Calendar Year
Price
2030
$6.00
2031
$5.60
2032
$5.20
2033
$4.80
2034
$4.40
2035 and later
$4.00
The retail fuel cost per mile for MY 2027 from calendar year 2027 to 2025 across all vehicle
fuel types, as well as the change in cost relative to the reference case for the final standards and
alternative cases, are shown in Table 3-26, Table 3-27, and Table 3-28 for the 2-percent, 3-
percent and 7-percent discounting cases, respectively. The retail fuel cost per mile for MY 2030
from calendar year 2030 to 2025 across all vehicle fuel types, as well as the change in cost
relative to the reference case for the final standards and alternative cases, are shown in Table
3-29, Table 3-30, and Table 3-31 for the 2-percent, 3-percent and 7-percent discounting cases,
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respectively. The retail fuel cost per mile for MY 2032 from calendar year 2032 to 2025 across
all vehicle fuel types, as well as the change in cost relative to the reference case for the final
standards and alternative cases, are shown in Table 3-32, Table 3-33, and Table 3-34 for the 2-
percent, 3-percent and 7-percent discounting cases, respectively. When considering the retail fuel
costs per vehicle between scenarios, the impacts show no impact or a cost savings for both the
final standards and alternative cases for nearly every MOVES source type and regulatory class.
Table 3-17 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Other Buses
LHD45
-
44.7
10.9
-
MHD67
39.0
-
16.3
-
HHD8
41.4
-
25.0
48.2
Transit Bus
LHD45
-
44.4
13.0
-
MHD67
39.1
-
17.6
-
Urban Bus
41.8
-
11.7
48.0
School Bus
LHD45
-
32.6
9.2
-
MHD67
30.5
35.7
11.9
-
HHD8
32.7
-
11.2
38.9
Refuse Truck
MHD67
42.0
50.1
17.5
-
HHD8
43.5
-
21.1
51.1
Single Unit Short-haul Truck
LHD45
20.5
29.7
8.5
-
MHD67
31.0
37.5
14.5
-
HHD8
37.4
-
18.4
44.6
Single Unit Long-haul Truck
LHD45
19.2
28.2
8.6
-
MHD67
29.0
35.0
16.0
-
HHD8
34.9
-
21.8
42.1
Combination Short-haul Truck
MHD67
41.5
-
46.1
-
HHD8
43.0
-
65.4
48.3
Combination Long-haul Truck
MHD67
40.6
-
77.5
-
HHD8
41.4
-
86.6
45.7
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-18 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Other Buses
LHD45
-
40.5
9.9
-
MHD67
35.4
-
14.8
-
HHD8
37.5
-
22.7
43.7
Transit Bus
LHD45
-
40.4
11.8
-
MHD67
35.6
-
16.0
-
Urban Bus
38.1
-
10.6
43.7
School Bus
LHD45
-
29.6
8.3
-
MHD67
27.7
32.4
10.8
-
499
-------
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
HHD8
29.6
-
10.2
35.2
Refuse Truck
MHD67
38.5
46.0
16.0
-
HHD8
40.0
-
19.3
46.9
Single Unit Short-haul Truck
LHD45
19.1
27.6
7.9
-
MHD67
28.8
34.9
13.5
-
HHD8
34.8
-
17.1
41.4
Single Unit Long-haul Truck
LHD45
17.9
26.3
8.1
-
MHD67
27.0
32.7
14.9
-
HHD8
32.6
-
20.3
39.2
Combination Short-haul Truck
MHD67
38.8
-
42.9
-
HHD8
40.2
-
60.7
45.2
Combination Long-haul Truck
MHD67
37.5
-
71.6
-
HHD8
38.3
-
80.0
42.2
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-19 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Other Buses
LHD45
-
28.9
7.0
-
MHD67
25.2
-
10.6
-
HHD8
26.8
-
16.1
31.1
Transit Bus
LHD45
-
29.1
8.5
-
MHD67
25.7
-
11.5
-
Urban Bus
27.5
-
7.7
31.5
School Bus
LHD45
-
21.0
5.9
-
MHD67
19.7
23.1
7.7
-
HHD8
21.1
-
7.3
25.1
Refuse Truck
MHD67
28.5
33.9
11.8
-
HHD8
29.5
-
14.2
34.6
Single Unit Short-haul Truck
LHD45
14.7
21.2
6.1
-
MHD67
22.2
26.8
10.3
-
HHD8
26.8
-
13.1
31.9
Single Unit Long-haul Truck
LHD45
14.0
20.5
6.3
-
MHD67
21.1
25.5
11.6
-
HHD8
25.5
-
15.9
30.7
Combination Short-haul Truck
MHD67
30.6
-
33.0
-
HHD8
31.7
-
46.6
35.6
Combination Long-haul Truck
MHD67
28.5
-
54.1
-
HHD8
29.0
-
60.5
32.0
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
500
-------
Table 3-20 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
47.4
8.5
-
-
MHD67
37.1
-
15.7
-
-
HHD8
41.1
-
23.4
48.0
20.5
Transit Bus
LHD45
-
47.0
10.2
-
-
MHD67
37.1
-
16.8
-
-
Urban Bus
40.9
-
13.8
47.0
-
School Bus
LHD45
-
32.9
7.9
-
-
MHD67
28.9
34.0
11.4
-
-
HHD8
31.6
-
13.7
37.6
-
Refuse Truck
MHD67
40.0
47.8
16.2
-
-
HHD8
41.4
-
18.0
48.7
-
Single Unit Short-haul
Truck
LHD45
19.6
28.4
7.9
-
-
MHD67
29.3
35.4
13.8
-
-
HHD8
35.7
-
17.5
42.6
-
Single Unit Long-haul
Truck
LHD45
18.3
26.9
8.0
-
-
MHD67
27.4
33.1
15.2
-
-
HHD8
33.4
-
20.8
40.2
-
Combination Short-haul
Truck
MHD67
38.9
-
46.3
-
46.6
HHD8
40.4
-
54.1
45.5
50.4
Combination Long-haul
Truck
MHD67
38.5
-
56.1
-
39.8
HHD8
39.2
-
57.8
43.4
41.1
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-21 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
41.9
7.5
-
-
MHD67
32.8
-
13.9
-
-
HHD8
36.3
-
20.7
42.4
18.2
Transit Bus
LHD45
-
41.7
9.0
-
-
MHD67
32.9
-
14.9
-
-
Urban Bus
36.2
-
12.2
41.7
-
School Bus
LHD45
-
29.1
7.0
-
-
MHD67
25.6
30.0
10.0
-
-
HHD8
27.9
-
12.1
33.3
-
Refuse Truck
MHD67
35.7
42.6
14.5
-
-
HHD8
36.9
-
16.1
43.4
-
Single Unit Short-haul
Truck
LHD45
17.7
25.6
7.1
-
-
MHD67
26.4
32.0
12.4
-
-
HHD8
32.2
-
15.8
38.4
-
Single Unit Long-haul
Truck
LHD45
16.6
24.4
7.3
-
-
MHD67
24.8
30.0
13.8
-
-
501
-------
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
HHD8
30.3
-
18.8
36.5
-
Combination Short-haul
Truck
MHD67
35.4
-
42.0
-
42.6
HHD8
36.7
-
49.1
41.3
46.0
Combination Long-haul
Truck
MHD67
34.6
-
50.4
-
36.0
HHD8
35.3
-
51.9
39.0
37.1
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-22 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
26.9
4.8
-
-
MHD67
21.0
-
8.9
-
-
HHD8
23.3
-
13.2
27.2
11.9
Transit Bus
LHD45
-
27.0
5.8
-
-
MHD67
21.4
-
9.6
-
-
Urban Bus
23.5
-
7.9
27.0
-
School Bus
LHD45
-
18.6
4.5
-
-
MHD67
16.4
19.2
6.4
-
-
HHD8
17.9
-
7.7
21.3
-
Refuse Truck
MHD67
23.6
28.1
9.5
-
-
HHD8
24.4
-
10.6
28.6
-
Single Unit Short-haul
Truck
LHD45
12.2
17.6
4.9
-
-
MHD67
18.2
22.0
8.5
-
-
HHD8
22.2
-
10.8
26.4
-
Single Unit Long-haul
Truck
LHD45
11.6
17.1
5.1
-
-
MHD67
17.3
21.0
9.6
-
-
HHD8
21.2
-
13.1
25.5
-
Combination Short-haul
Truck
MHD67
24.9
-
29.3
-
30.4
HHD8
25.8
-
34.3
29.0
32.8
Combination Long-haul
Truck
MHD67
23.4
-
34.0
-
24.8
HHD8
23.9
-
35.0
26.4
25.6
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-23 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
44.4
10.3
-
-
MHD67
36.0
-
15.2
-
-
HHD8
40.6
-
22.5
47.4
18.7
Transit Bus
LHD45
-
44.0
12.3
-
-
MHD67
36.1
-
16.1
-
-
502
-------
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Urban Bus
38.2
-
16.0
43.9
-
School Bus
LHD45
-
31.4
8.4
-
-
MHD67
28.5
33.4
10.8
-
-
HHD8
30.0
-
14.6
35.7
-
Refuse Truck
MHD67
38.9
46.5
15.6
-
-
HHD8
40.5
-
16.9
47.7
-
Single Unit Short-haul
Truck
LHD45
19.0
27.5
7.6
-
-
MHD67
28.4
34.4
13.0
-
-
HHD8
34.6
-
17.3
41.3
-
Single Unit Long-haul
Truck
LHD45
17.8
26.1
7.8
-
-
MHD67
26.6
32.1
14.3
-
-
HHD8
32.2
-
20.8
38.8
-
Combination Short-haul
Truck
MHD67
37.9
-
40.8
-
37.8
HHD8
40.3
-
45.7
45.3
39.4
Combination Long-haul
Truck
MHD67
37.5
-
50.0
-
33.4
HHD8
38.3
-
51.1
42.4
34.1
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-24 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
38.6
8.9
-
-
MHD67
31.4
-
13.2
-
-
HHD8
35.3
-
19.5
41.2
16.3
Transit Bus
LHD45
-
38.4
10.7
-
-
MHD67
31.5
-
14.0
-
-
Urban Bus
33.3
-
14.0
38.3
-
School Bus
LHD45
-
27.3
7.3
-
-
MHD67
24.8
29.1
9.4
-
-
HHD8
26.1
-
12.7
31.1
-
Refuse Truck
MHD67
34.1
40.7
13.7
-
-
HHD8
35.5
-
14.8
41.8
-
Single Unit Short-haul
Truck
LHD45
16.8
24.4
6.8
-
-
MHD67
25.2
30.5
11.5
-
-
HHD8
30.7
-
15.3
36.6
-
Single Unit Long-haul
Truck
LHD45
15.9
23.3
6.9
-
-
MHD67
23.7
28.6
12.8
-
-
HHD8
28.7
-
18.5
34.6
-
Combination Short-haul
Truck
MHD67
33.8
-
36.3
-
33.7
HHD8
36.0
-
40.7
40.4
35.2
Combination Long-haul
Truck
MHD67
33.2
-
44.1
-
29.5
HHD8
33.8
-
45.0
37.4
30.1
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
503
-------
Table 3-25 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
23.1
5.3
-
-
MHD67
18.8
-
7.9
-
-
HHD8
21.2
-
11.7
24.7
9.8
Transit Bus
LHD45
-
23.2
6.5
-
-
MHD67
19.1
-
8.5
-
-
Urban Bus
20.2
-
8.5
23.2
-
School Bus
LHD45
-
16.4
4.4
-
-
MHD67
14.9
17.4
5.6
-
-
HHD8
15.6
-
7.6
18.6
-
Refuse Truck
MHD67
21.0
25.0
8.4
-
-
HHD8
21.8
-
9.1
25.7
-
Single Unit Short-haul
Truck
LHD45
10.8
15.6
4.3
-
-
MHD67
16.1
19.5
7.3
-
-
HHD8
19.6
-
9.8
23.3
-
Single Unit Long-haul
Truck
LHD45
10.3
15.1
4.5
-
-
MHD67
15.4
18.6
8.3
-
-
HHD8
18.6
-
12.0
22.4
-
Combination Short-haul
Truck
MHD67
22.1
-
23.6
-
22.1
HHD8
23.5
-
26.5
26.4
23.1
Combination Long-haul
Truck
MHD67
20.9
-
27.7
-
18.7
HHD8
21.3
-
28.3
23.6
19.1
* Values rounded to the nearest tenth of a cent; blank values represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type.
Table 3-26 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
40.6
37.9
39.3
-2.7
-1.4
MHD67
37.4
35.8
36.6
-1.6
-0.8
HHD8
41.1
41.1
41.1
0.0
0.0
Transit Bus
LHD45
40.6
38.1
39.4
-2.5
-1.2
MHD67
37.6
37.0
37.5
-0.6
-0.1
Urban Bus
40.7
40.7
40.7
0.0
0.0
School Bus
LHD45
30.1
27.9
28.8
-2.1
-1.3
MHD67
29.6
27.2
28.1
-2.4
-1.6
HHD8
32.0
32.0
32.0
0.0
0.0
Refuse Truck
MHD67
40.2
37.1
38.3
-3.1
-1.9
HHD8
43.6
43.6
43.6
0.0
0.0
LHD45
22.5
20.9
21.4
-1.6
-1.1
MHD67
31.2
30.2
30.7
-0.9
-0.4
504
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Single Unit
Short-haul
Truck
HHD8
37.0
37.0
37.0
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
21.2
21.2
21.2
0.0
0.0
MHD67
29.2
28.3
28.7
-1.0
-0.5
HHD8
34.8
34.8
34.8
0.0
0.0
Combination
Short-haul
Truck
MHD67
41.9
41.8
41.9
0.0
0.0
HHD8
44.0
44.0
44.0
0.0
0.0
Combination
Long-haul
Truck
MHD67
40.7
40.7
40.7
0.0
0.0
HHD8
41.5
41.5
41.5
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-27 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
36.9
34.4
35.6
-2.5
-1.2
MHD67
33.9
32.5
33.2
-1.4
-0.7
HHD8
37.3
37.3
37.3
0.0
0.0
Transit Bus
LHD45
36.9
34.7
35.8
-2.3
-1.1
MHD67
34.2
33.6
34.1
-0.6
-0.1
Urban Bus
37.0
37.0
37.0
0.0
0.0
School Bus
LHD45
27.2
25.3
26.1
-2.0
-1.2
MHD67
26.9
24.7
25.5
-2.2
-1.4
HHD8
29.0
29.0
29.0
0.0
0.0
Refuse Truck
MHD67
36.9
34.1
35.1
-2.8
-1.8
HHD8
40.0
40.0
40.0
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
20.9
19.4
19.9
-1.5
-1.0
MHD67
29.0
28.1
28.6
-0.9
-0.4
HHD8
34.4
34.4
34.4
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
19.8
19.8
19.8
0.0
0.0
MHD67
27.3
26.4
26.8
-0.9
-0.5
HHD8
32.4
32.4
32.4
0.0
0.0
Combination
Short-haul
Truck
MHD67
39.2
39.1
39.2
0.0
0.0
HHD8
41.1
41.1
41.1
0.0
0.0
Combination
Long-haul
Truck
MHD67
37.6
37.6
37.6
0.0
0.0
HHD8
38.4
38.4
38.4
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
505
-------
Table 3-28 Retail Fuel Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
26.2
24.5
25.4
-1.8
-0.9
MHD67
24.2
23.2
23.7
-1.0
-0.5
HHD8
26.6
26.6
26.6
0.0
0.0
Transit Bus
LHD45
26.6
25.0
25.8
-1.6
-0.8
MHD67
24.7
24.3
24.6
-0.4
-0.1
Urban Bus
26.7
26.7
26.7
0.0
0.0
School Bus
LHD45
19.4
18.0
18.6
-1.4
-0.8
MHD67
19.2
17.6
18.1
-1.6
-1.0
HHD8
20.7
20.7
20.7
0.0
0.0
Refuse Truck
MHD67
27.2
25.1
25.9
-2.1
-1.3
HHD8
29.5
29.5
29.5
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
16.1
14.9
15.3
-1.1
-0.8
MHD67
22.3
21.6
22.0
-0.7
-0.3
HHD8
26.5
26.5
26.5
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
15.4
15.4
15.4
0.0
0.0
MHD67
21.3
20.6
21.0
-0.7
-0.4
HHD8
25.4
25.4
25.4
0.0
0.0
Combination
Short-haul
Truck
MHD67
30.8
30.7
30.8
0.0
0.0
HHD8
32.3
32.3
32.3
0.0
0.0
Combination
Long-haul
Truck
MHD67
28.6
28.6
28.6
0.0
0.0
HHD8
29.2
29.2
29.2
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-29 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
34.5
33.6
34.5
-0.9
0.0
MHD67
33.3
33.3
33.3
0.0
0.0
HHD8
39.0
39.0
39.0
0.0
0.0
Transit Bus
LHD45
34.7
33.9
34.7
-0.8
0.0
MHD67
33.6
33.6
33.6
0.0
0.0
Urban Bus
37.5
35.9
37.1
-1.6
-0.3
School Bus
LHD45
25.6
24.0
24.8
-1.6
-0.8
MHD67
26.4
22.8
23.7
-3.5
-2.6
506
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
HHD8
29.6
27.9
28.8
-1.7
-0.8
Refuse Truck
MHD67
35.7
33.8
34.7
-1.9
-1.0
HHD8
40.0
37.2
38.2
-2.7
-1.7
Single Unit
Short-haul
Truck
LHD45
19.2
17.5
18.0
-1.6
-1.2
MHD67
27.7
27.3
27.7
-0.4
0.0
HHD8
34.1
33.5
34.0
-0.7
-0.1
Single Unit
Long-haul
Truck
LHD45
18.2
18.2
18.2
0.0
0.0
MHD67
26.3
25.6
26.0
-0.7
-0.3
HHD8
32.3
32.0
32.3
-0.4
0.0
Combination
Short-haul
Truck
MHD67
40.0
40.0
40.0
0.0
0.0
HHD8
42.4
42.8
42.6
0.4
0.3
Combination
Long-haul
Truck
MHD67
38.9
39.2
39.1
0.3
0.2
HHD8
39.7
40.0
39.9
0.3
0.2
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-30 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
30.5
29.7
30.5
-0.8
0.0
MHD67
29.5
29.5
29.5
0.0
0.0
HHD8
34.5
34.5
34.5
0.0
0.0
Transit Bus
LHD45
30.8
30.0
30.8
-0.7
0.0
MHD67
29.8
29.8
29.8
0.0
0.0
Urban Bus
33.2
31.8
32.9
-1.4
-0.3
School Bus
LHD45
22.7
21.2
21.9
-1.4
-0.7
MHD67
23.3
20.1
21.0
-3.1
-2.3
HHD8
26.2
24.7
25.5
-1.5
-0.7
Refuse Truck
MHD67
31.8
30.1
30.9
-1.7
-0.9
HHD8
35.6
33.2
34.1
-2.4
-1.5
Single Unit
Short-haul
Truck
LHD45
17.3
15.8
16.2
-1.5
-1.0
MHD67
25.0
24.6
25.0
-0.4
0.0
HHD8
30.8
30.2
30.7
-0.6
-0.1
Single Unit
Long-haul
Truck
LHD45
16.5
16.5
16.5
0.0
0.0
MHD67
23.8
23.2
23.6
-0.6
-0.2
HHD8
29.3
29.0
29.3
-0.3
0.0
Combination
Short-haul
Truck
MHD67
36.3
36.3
36.3
0.0
0.0
HHD8
38.5
38.9
38.8
0.4
0.3
MHD67
35.0
35.2
35.2
0.3
0.2
507
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Combination
Long-haul
Truck
HHD8
35.7
36.0
35.9
0.3
0.2
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-31 Retail Fuel Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
19.5
19.0
19.5
-0.5
0.0
MHD67
18.9
18.9
18.9
0.0
0.0
HHD8
22.1
22.1
22.1
0.0
0.0
Transit Bus
LHD45
20.0
19.5
20.0
-0.5
0.0
MHD67
19.3
19.3
19.3
0.0
0.0
Urban Bus
21.6
20.6
21.4
-0.9
-0.2
School Bus
LHD45
14.5
13.6
14.1
-0.9
-0.5
MHD67
14.9
12.9
13.4
-2.0
-1.5
HHD8
16.8
15.8
16.3
-1.0
-0.4
Refuse Truck
MHD67
21.0
19.9
20.4
-1.1
-0.6
HHD8
23.5
21.9
22.5
-1.6
-1.0
Single Unit
Short-haul
Truck
LHD45
11.9
10.9
11.2
-1.0
-0.7
MHD67
17.2
16.9
17.2
-0.3
0.0
HHD8
21.2
20.8
21.1
-0.4
-0.1
Single Unit
Long-haul
Truck
LHD45
11.5
11.5
11.5
0.0
0.0
MHD67
16.6
16.2
16.5
-0.4
-0.2
HHD8
20.5
20.2
20.5
-0.2
0.0
Combination
Short-haul
Truck
MHD67
25.5
25.5
25.5
0.0
0.0
HHD8
27.0
27.3
27.2
0.3
0.2
Combination
Long-haul
Truck
MHD67
23.7
23.9
23.8
0.2
0.1
HHD8
24.2
24.4
24.3
0.2
0.1
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
508
-------
Table 3-32 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
32.1
21.6
31.0
-10.5
-1.1
MHD67
31.7
31.7
31.7
0.0
0.0
HHD8
37.7
37.7
37.7
0.0
0.0
Transit Bus
LHD45
32.5
22.8
31.4
-9.6
-1.0
MHD67
31.9
31.6
31.9
-0.3
0.0
Urban Bus
36.1
29.9
34.8
-6.2
-1.2
School Bus
LHD45
24.0
16.1
22.0
-7.9
-2.0
MHD67
25.0
16.2
20.9
00
00
1
-4.1
HHD8
28.5
24.2
27.4
-4.3
-1.1
Refuse Truck
MHD67
33.8
29.8
33.2
-4.0
-0.6
HHD8
38.4
31.8
35.7
-6.6
-2.7
Single Unit
Short-haul
Truck
LHD45
17.9
12.5
15.9
-5.4
-1.9
MHD67
26.2
23.9
26.1
-2.3
-0.2
HHD8
32.8
30.0
32.2
-2.8
-0.6
Single Unit
Long-haul
Truck
LHD45
17.0
15.6
17.0
-1.4
0.0
MHD67
25.0
22.5
24.5
-2.5
-0.5
HHD8
31.1
28.0
30.0
-3.2
-1.2
Combination
Short-haul
Truck
MHD67
38.6
38.5
38.6
-0.1
0.0
HHD8
41.1
42.6
41.7
1.5
0.6
Combination
Long-haul
Truck
MHD67
38.0
39.1
38.6
1.1
0.6
HHD8
38.8
40.0
39.4
1.2
0.6
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
509
-------
Table 3-33 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
28.0
18.8
27.0
-9.1
-0.9
MHD67
27.6
27.6
27.6
0.0
0.0
HHD8
32.8
32.8
32.8
0.0
0.0
Transit Bus
LHD45
28.3
19.9
27.4
-8.4
-0.9
MHD67
27.9
27.6
27.9
-0.3
0.0
Urban Bus
31.5
26.1
30.4
-5.4
-1.1
School Bus
LHD45
20.8
14.0
19.1
-6.8
-1.7
MHD67
21.8
14.1
18.2
-7.6
-3.6
HHD8
24.8
21.0
23.9
-3.7
-0.9
Refuse Truck
MHD67
29.6
26.1
29.1
-3.5
-0.5
HHD8
33.6
27.8
31.3
-5.8
-2.4
Single Unit
Short-haul
Truck
LHD45
15.8
11.0
14.1
-4.8
-1.7
MHD67
23.2
21.2
23.1
-2.1
-0.1
HHD8
29.0
26.6
28.5
-2.4
-0.5
Single Unit
Long-haul
Truck
LHD45
15.2
13.9
15.2
-1.2
0.0
MHD67
22.2
20.1
21.8
-2.2
-0.4
HHD8
27.8
24.9
26.7
-2.9
-1.0
Combination
Short-haul
Truck
MHD67
34.5
34.4
34.4
-0.1
0.0
HHD8
36.7
38.0
37.2
1.4
0.5
Combination
Long-haul
Truck
MHD67
33.5
34.5
34.0
1.0
0.5
HHD8
34.2
35.3
34.8
1.0
0.5
* Values rounded to the nearest tenth of a cent; Negative values denote lower costs, i.e., savings in expenditures.
510
-------
Table 3-34 Retail Fuel Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
16.8
11.3
16.2
-5.5
-0.6
MHD67
16.6
16.6
16.6
0.0
0.0
HHD8
19.7
19.7
19.7
0.0
0.0
Transit Bus
LHD45
17.1
12.1
16.6
-5.1
-0.5
MHD67
16.9
16.7
16.9
-0.2
0.0
Urban Bus
19.1
15.8
18.4
-3.3
-0.7
School Bus
LHD45
12.5
8.4
11.5
-4.1
-1.0
MHD67
13.1
8.5
10.9
-4.6
-2.2
HHD8
14.9
12.6
14.3
-2.2
-0.6
Refuse Truck
MHD67
18.2
16.1
17.9
-2.2
-0.3
HHD8
20.7
17.1
19.2
-3.6
-1.4
Single Unit
Short-haul
Truck
LHD45
10.1
7.0
9.0
-3.1
-1.1
MHD67
14.8
13.5
14.8
-1.3
-0.1
HHD8
18.6
17.0
18.2
-1.6
-0.3
Single Unit
Long-haul
Truck
LHD45
9.8
9.0
9.8
-0.8
0.0
MHD67
14.4
13.0
14.2
-1.4
-0.3
HHD8
18.0
16.2
17.4
-1.9
-0.7
Combination
Short-haul
Truck
MHD67
22.5
22.4
22.4
-0.1
0.0
HHD8
23.9
24.8
24.2
0.8
0.3
Combination
Long-haul
Truck
MHD67
21.1
21.8
21.5
0.6
0.3
HHD8
21.6
22.2
21.9
0.6
0.3
* Values rounded to the nearest tenth of a cent; Negative values denote lower costs, i.e., savings in expenditures.
Table 3-35 and Table 3-36 present the annual undiscounted pre-tax fuel costs associated with
the final standards and alternative, respectively. CNG fuel savings are calculated as gasoline
gallon equivalents and, as such, are monetized using gasoline fuel prices.
511
-------
Table 3-35 Annual Undiscounted Pre-Tax Fuel Costs for the Final Standards Relative to the Reference Case,
Millions of 2022 dollars *
Calendar Year
Diesel
Gasoline
CNG
Electricity
Hydrogen
Sum
2027
-$100
-$59
$0
$76
$0
-$84
2028
-$260
-$110
-$2
$200
$0
-$170
2029
-$480
-$170
-$3
$370
$0
-$280
2030
-$930
-$220
-$6
$880
$100
-$170
2031
-$1,900
-$350
-$11
$1,900
$290
-$110
2032
-$3,800
-$560
-$20
$3,700
$650
$37
2033
-$5,600
-$760
-$29
$5,500
$970
$120
2034
-$7,400
-$930
-$38
$7,300
$1,200
$170
2035
-$9,200
-$1,100
-$47
$9,100
$1,400
$160
2036
-$11,000
-$1,200
-$57
$11,000
$1,700
$350
2037
-$12,000
-$1,300
-$66
$12,000
$2,000
$490
2038
-$14,000
-$1,400
-$76
$14,000
$2,300
$640
2039
-$15,000
-$1,500
-$85
$15,000
$2,500
$810
2040
-$16,000
-$1,600
-$95
$16,000
$2,700
$980
2041
-$17,000
-$1,700
-$100
$17,000
$2,900
$990
2042
-$18,000
-$1,800
-$110
$18,000
$3,100
$1,100
2043
-$19,000
-$1,800
-$120
$19,000
$3,300
$1,100
2044
-$19,000
-$1,800
-$130
$19,000
$3,400
$1,200
2045
-$20,000
-$1,900
-$140
$20,000
$3,500
$1,200
2046
-$20,000
-$1,900
-$150
$20,000
$3,600
$880
2047
-$21,000
-$1,900
-$160
$20,000
$3,700
$800
2048
-$21,000
-$2,000
-$170
$20,000
$3,700
$670
2049
-$21,000
-$2,000
-$180
$20,000
$3,800
$540
2050
-$21,000
-$2,000
-$190
$20,000
$3,800
$430
2051
-$21,000
-$2,000
-$210
$20,000
$3,900
$420
2052
-$21,000
-$2,000
-$220
$20,000
$3,900
$410
2053
-$22,000
-$2,100
-$230
$20,000
$4,000
$390
2054
-$22,000
-$2,100
-$240
$20,000
$4,000
$370
2055
-$22,000
-$2,100
-$260
$20,000
$4,000
$350
* Values rounded to two significant digits; Negative values denote lower costs, i.e., savings in expenditures.
512
-------
Table 3-36 Annual Undiscounted Pre-Tax Fuel Costs for the Alternative Relative to the Reference Case,
Millions of 2022 dollars *
Calendar Year
Diesel
Gasoline
CNG
Electricity
Hydrogen
Sum
2027
-$51
-$36
$0
$38
$0
-$50
2028
-$110
-$70
$0
$85
$0
-$97
2029
-$240
-$100
-$1
$180
$0
-$160
2030
-$520
-$130
-$2
$500
$67
-$94
2031
-$1,000
-$170
-$4
$1,000
$180
-$13
2032
-$1,700
-$230
-$7
$1,700
$350
$94
2033
-$2,500
-$270
-$10
$2,400
$480
$190
2034
-$3,100
-$300
-$12
$3,100
$600
$280
2035
-$3,800
-$310
-$15
$3,800
$680
$350
2036
-$4,300
-$320
-$17
$4,400
$810
$510
2037
-$4,900
-$310
-$19
$4,900
$930
$650
2038
-$5,300
-$310
-$22
$5,400
$1,000
$790
2039
-$5,700
-$290
-$24
$5,800
$1,100
$930
2040
-$6,100
-$280
-$26
$6,200
$1,200
$1,100
2041
-$6,400
-$260
-$28
$6,500
$1,300
$1,100
2042
-$6,600
-$240
-$30
$6,800
$1,400
$1,200
2043
-$6,800
-$210
-$32
$6,900
$1,500
$1,300
2044
-$6,900
-$190
-$34
$7,100
$1,500
$1,400
2045
-$7,000
-$170
-$36
$7,100
$1,500
$1,400
2046
-$7,100
-$160
-$38
$7,100
$1,600
$1,400
2047
-$7,200
-$140
-$40
$7,100
$1,600
$1,400
2048
-$7,100
-$120
-$43
$7,100
$1,600
$1,300
2049
-$7,100
-$110
-$45
$7,000
$1,600
$1,300
2050
-$7,100
-$100
-$47
$7,000
$1,600
$1,300
2051
-$7,100
-$93
-$50
$6,900
$1,600
$1,300
2052
-$7,100
-$85
-$52
$6,900
$1,600
$1,300
2053
-$7,000
-$78
-$55
$6,800
$1,600
$1,300
2054
-$7,000
-$71
-$58
$6,800
$1,600
$1,300
2055
-$6,900
-$66
-$60
$6,700
$1,600
$1,300
* Values rounded to two significant digits; Negative values denote lower costs, i.e., savings in expenditures.
3.4.7.2 Costs Associated with Diesel Exhaust Fluid
DEF consumption costs in heavy-duty vehicles were estimated by EPA in the HD2027 final
rule.1333 We are applying the same methodology in this analysis to estimate the total costs of
DEF under the final HD GHG Phase 3 standards. Examples of total cost estimates of DEF for
MY 2027, 2030 and 2032 vehicles are provided for 2-percent, 3-percent and 7 percent
discounting in Table 3-37 through Table 3-45. To determine the total costs associated with DEF
usage for a given model year, the DEF usage for each MOVES source type and regulatory class
was multiplied by the DEF price over the from the first year of the vehicle until 20 5 5.1334 The
total DEF cost was divided by the total VMT for a given model year vehicle for each MOVES
1333 88 FR 4413, January 24, 2023.
1334 This analysis uses the DEF prices presented in the NCP Technical Support Document (see "Nonconformance
Penalties for On-highway Heavy-duty Diesel Engines: Technical Support Document," EPA-420-R-12-014) with
growth beyond 2042 projected at the same 1.3 percent rate as noted in the NCP TSD. Note that the DEF prices used
update the NCP TSD's 2011 prices to 2022 dollars.
513
-------
Source Type and regulatory class combination from the first year of the vehicle until 2055 to
determine the average cost of DEF per mile. The DEF cost per mile was computed for the
reference case, alternative case and final standard case under the potential compliance pathway
for each fuel type. The estimates of DEF cost per mile for MY 2027 for the final standards cases
are shown in Table 3-37, Table 3-38, and Table 3-39 for 2-percent, 3-percent, and 7-percnet
discounting, respectively. The estimates of DEF cost per mile for MY 2030 for the final
standards cases are shown in Table 3-40, Table 3-41, and Table 3-42 for 2-percent, 3-percent,
and 7-percnet discounting, respectively. The estimates of DEF cost per mile for MY 2032 for the
final standards cases are shown in Table 3-43, Table 3-44, and Table 3-45 for 2-percent, 3-
percent, and 7-percnet discounting, respectively. Several source types and regulatory classes
contain no diesel-fueled ICE vehicles and therefore no DEF consumption costs. Values shown as
a dash in Table 3-37 through Table 3-45 represent cases where a given MOVES source type
and regulatory class did not use a specific fuel type. The values of 0 for gasoline, electricity,
CNG and hydrogen as those vehicles do not consume any DEF and therefore do not incur any
cost per mile.
Table 3-37 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Other Buses
LHD45
-
0.00
0.00
-
MHD67
2.33
-
0.00
-
HHD8
2.47
-
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
MHD67
2.33
-
0.00
-
Urban Bus
2.49
-
0.00
0.00
School Bus
LHD45
-
0.00
0.00
-
MHD67
1.82
0.00
0.00
-
HHD8
1.95
-
0.00
0.00
Refuse Truck
MHD67
2.48
0.00
0.00
-
HHD8
2.57
-
0.00
0.00
Single Unit Short-haul Truck
LHD45
1.20
0.00
0.00
-
MHD67
1.81
0.00
0.00
-
HHD8
2.18
-
0.00
0.00
Single Unit Long-haul Truck
LHD45
1.11
0.00
0.00
-
MHD67
1.68
0.00
0.00
-
HHD8
2.02
-
0.00
0.00
Combination Short-haul Truck
MHD67
2.40
-
0.00
-
HHD8
2.48
-
0.00
0.00
Combination Long-haul Truck
MHD67
2.37
-
0.00
-
HHD8
2.42
-
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
514
-------
Table 3-38 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Other Buses
LHD45
-
0.00
0.00
-
MHD67
2.10
-
0.00
-
HHD8
2.23
-
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
MHD67
2.11
-
0.00
-
Urban Bus
2.26
-
0.00
0.00
School Bus
LHD45
-
0.00
0.00
-
MHD67
1.65
0.00
0.00
-
HHD8
1.76
-
0.00
0.00
Refuse Truck
MHD67
2.27
0.00
0.00
-
HHD8
2.35
-
0.00
0.00
Single Unit Short-haul Truck
LHD45
1.11
0.00
0.00
-
MHD67
1.67
0.00
0.00
-
HHD8
2.02
-
0.00
0.00
Single Unit Long-haul Truck
LHD45
1.04
0.00
0.00
-
MHD67
1.56
0.00
0.00
-
HHD8
1.88
-
0.00
0.00
Combination Short-haul Truck
MHD67
2.24
-
0.00
-
HHD8
2.32
-
0.00
0.00
Combination Long-haul Truck
MHD67
2.19
-
0.00
-
HHD8
2.23
-
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
Table 3-39 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Other Buses
LHD45
-
0.00
0.00
-
MHD67
1.47
-
0.00
-
HHD8
1.56
-
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
MHD67
1.50
-
0.00
-
Urban Bus
1.60
-
0.00
0.00
School Bus
LHD45
-
0.00
0.00
-
MHD67
1.15
0.00
0.00
-
HHD8
1.23
-
0.00
0.00
Refuse Truck
MHD67
1.65
0.00
0.00
-
HHD8
1.71
-
0.00
0.00
Single Unit Short-haul Truck
LHD45
0.84
0.00
0.00
-
MHD67
1.28
0.00
0.00
-
HHD8
1.54
-
0.00
0.00
Single Unit Long-haul Truck
LHD45
0.80
0.00
0.00
-
MHD67
1.21
0.00
0.00
-
515
-------
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
HHD8
1.46
-
0.00
0.00
Combination Short-haul Truck
MHD67
1.75
-
0.00
-
HHD8
1.81
-
0.00
0.00
Combination Long-haul Truck
MHD67
1.64
-
0.00
-
HHD8
1.67
-
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
Table 3-40 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
0.00
0.00
-
-
MHD67
2.28
-
0.00
-
-
HHD8
2.52
-
0.00
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
-
MHD67
2.27
-
0.00
-
-
Urban Bus
2.50
-
0.00
0.00
-
School Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.78
0.00
0.00
-
-
HHD8
1.94
-
0.00
0.00
-
Refuse Truck
MHD67
2.43
0.00
0.00
-
-
HHD8
2.51
-
0.00
0.00
-
Single Unit Short-haul
Truck
LHD45
1.18
0.00
0.00
-
-
MHD67
1.76
0.00
0.00
-
-
HHD8
2.14
-
0.00
0.00
-
Single Unit Long-haul
Truck
LHD45
1.09
0.00
0.00
-
-
MHD67
1.63
0.00
0.00
-
-
HHD8
1.99
-
0.00
0.00
-
Combination Short-haul
Truck
MHD67
2.32
-
0.00
-
0.00
HHD8
2.41
-
0.00
0.00
0.00
Combination Long-haul
Truck
MHD67
2.32
-
0.00
-
0.00
HHD8
2.36
-
0.00
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
Table 3-41 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
0.00
0.00
-
-
MHD67
2.00
-
0.00
-
-
HHD8
2.22
-
0.00
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
-
MHD67
2.01
-
0.00
-
-
516
-------
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Urban Bus
2.21
-
0.00
0.00
-
School Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.56
0.00
0.00
-
-
HHD8
1.71
-
0.00
0.00
-
Refuse Truck
MHD67
2.16
0.00
0.00
-
-
HHD8
2.23
-
0.00
0.00
-
Single Unit Short-haul
Truck
LHD45
1.06
0.00
0.00
-
-
MHD67
1.58
0.00
0.00
-
-
HHD8
1.93
-
0.00
0.00
-
Single Unit Long-haul
Truck
LHD45
0.99
0.00
0.00
-
-
MHD67
1.48
0.00
0.00
-
-
HHD8
1.80
-
0.00
0.00
-
Combination Short-haul
Truck
MHD67
2.10
-
0.00
-
0.00
HHD8
2.18
-
0.00
0.00
0.00
Combination Long-haul
Truck
MHD67
2.08
-
0.00
-
0.00
HHD8
2.12
-
0.00
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
Table 3-42 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
0.00
0.00
-
-
MHD67
1.27
-
0.00
-
-
HHD8
1.40
-
0.00
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.28
-
0.00
-
-
Urban Bus
1.41
-
0.00
0.00
-
School Bus
LHD45
-
0.00
0.00
-
-
MHD67
0.99
0.00
0.00
-
-
HHD8
1.08
-
0.00
0.00
-
Refuse Truck
MHD67
1.41
0.00
0.00
-
-
HHD8
1.46
-
0.00
0.00
-
Single Unit Short-haul
Truck
LHD45
0.72
0.00
0.00
-
-
MHD67
1.08
0.00
0.00
-
-
HHD8
1.31
-
0.00
0.00
-
Single Unit Long-haul
Truck
LHD45
0.69
0.00
0.00
-
-
MHD67
1.02
0.00
0.00
-
-
HHD8
1.25
-
0.00
0.00
-
Combination Short-haul
Truck
MHD67
1.47
-
0.00
-
0.00
HHD8
1.52
-
0.00
0.00
0.00
Combination Long-haul
Truck
MHD67
1.39
-
0.00
-
0.00
HHD8
1.42
-
0.00
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
517
-------
Table 3-43 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 2% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
0.00
0.00
-
-
MHD67
2.25
-
0.00
-
-
HHD8
2.53
-
0.00
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
-
MHD67
2.24
-
0.00
-
-
Urban Bus
2.38
-
0.00
0.00
-
School Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.77
0.00
0.00
-
-
HHD8
1.88
-
0.00
0.00
-
Refuse Truck
MHD67
2.40
0.00
0.00
-
-
HHD8
2.50
-
0.00
0.00
-
Single Unit Short-haul
Truck
LHD45
1.16
0.00
0.00
-
-
MHD67
1.73
0.00
0.00
-
-
HHD8
2.11
-
0.00
0.00
-
Single Unit Long-haul
Truck
LHD45
1.08
0.00
0.00
-
-
MHD67
1.61
0.00
0.00
-
-
HHD8
1.96
-
0.00
0.00
-
Combination Short-haul
Truck
MHD67
2.30
-
0.00
-
0.00
HHD8
2.43
-
0.00
0.00
0.00
Combination Long-haul
Truck
MHD67
2.30
-
0.00
-
0.00
HHD8
2.34
-
0.00
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
Table 3-44 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 3% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
0.00
0.00
-
-
MHD67
1.95
-
0.00
-
-
HHD8
2.19
-
0.00
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.95
-
0.00
-
-
Urban Bus
2.07
-
0.00
0.00
-
School Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.54
0.00
0.00
-
-
HHD8
1.63
-
0.00
0.00
-
Refuse Truck
MHD67
2.10
0.00
0.00
-
-
HHD8
2.18
-
0.00
0.00
-
Single Unit Short-haul
Truck
LHD45
1.03
0.00
0.00
-
-
MHD67
1.53
0.00
0.00
-
-
HHD8
1.87
-
0.00
0.00
-
Single Unit Long-haul
Truck
LHD45
0.96
0.00
0.00
-
-
MHD67
1.43
0.00
0.00
-
-
518
-------
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
HHD8
1.74
-
0.00
0.00
-
Combination Short-haul
Truck
MHD67
2.05
-
0.00
-
0.00
HHD8
2.17
-
0.00
0.00
0.00
Combination Long-haul
Truck
MHD67
2.03
-
0.00
-
0.00
HHD8
2.06
-
0.00
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
Table 3-45 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in 2022
dollars, 7% discounting)
MOVES Source Type
Regulatory Class
Diesel
Gasoline
Electricity
CNG
Hydrogen
Other Buses
LHD45
-
0.00
0.00
-
-
MHD67
1.15
-
0.00
-
-
HHD8
1.30
-
0.00
0.00
0.00
Transit Bus
LHD45
-
0.00
0.00
-
-
MHD67
1.17
-
0.00
-
-
Urban Bus
1.24
-
0.00
0.00
-
School Bus
LHD45
-
0.00
0.00
-
-
MHD67
0.91
0.00
0.00
-
-
HHD8
0.96
-
0.00
0.00
-
Refuse Truck
MHD67
1.28
0.00
0.00
-
-
HHD8
1.33
-
0.00
0.00
-
Single Unit Short-haul
Truck
LHD45
0.65
0.00
0.00
-
-
MHD67
0.97
0.00
0.00
-
-
HHD8
1.18
-
0.00
0.00
-
Single Unit Long-haul
Truck
LHD45
0.62
0.00
0.00
-
-
MHD67
0.93
0.00
0.00
-
-
HHD8
1.12
-
0.00
0.00
-
Combination Short-haul
Truck
MHD67
1.32
-
0.00
-
0.00
HHD8
1.40
-
0.00
0.00
0.00
Combination Long-haul
Truck
MHD67
1.26
-
0.00
-
0.00
HHD8
1.29
-
0.00
0.00
0.00
* Values rounded to the nearest hundredth of a cent; blank values represent cases where a given MOVES source
type and regulatory class did not use a specific fuel type.
The DEF cost per mile for MY 2027 from Calendar Year 2027 to 2055 across all vehicle fuel
types, as well as the change in cost relative to the reference case for the final standards and
alternative cases, are shown in Table 3-46, Table 3-47, and Table 3-48 for the 2-percent, 3-
percent and 7-percent discounting cases, respectively. The retail fuel cost per mile for MY 2030
from Calendar Year 2030 to 2055 across all vehicle fuel types, as well as the change in cost
relative to the reference case for the final standards and alternative cases, are shown in Table
3-49, Table 3-50, and Table 3-51forthe 2-percent, 3-percent and 7-percent discounting cases,
respectively. The retail fuel cost per mile for MY 2032 from Calendar Year 2032 to 2055 across
all vehicle fuel types, as well as the change in cost relative to the reference case for the final
519
-------
standards and alternative cases, are shown in Table 3-52, Table 3-53, and Table 3-54 for the 2-
percent, 3-percent and 7-percent discounting cases, respectively. When considering the DEF
costs per vehicle between scenarios, the impacts show no impact or a cost savings for both the
final standards and alternative cases for nearly every MOVES source type and regulatory class.
Table 3-46 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
2.2
2.0
2.1
-0.2
-0.1
HHD8
2.0
2.0
2.0
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
2.2
2.1
2.1
-0.1
0.0
Urban Bus
2.1
2.1
2.1
0.0
0.0
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.5
1.3
1.4
-0.2
-0.1
HHD8
1.7
1.7
1.7
0.0
0.0
Refuse Truck
MHD67
2.3
2.0
2.1
-0.3
-0.2
HHD8
2.2
2.2
2.2
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
0.7
0.6
0.6
-0.1
0.0
MHD67
1.3
1.2
1.3
-0.1
0.0
HHD8
2.0
2.0
2.0
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
0.6
0.6
0.6
0.0
0.0
MHD67
1.2
1.1
1.2
-0.1
0.0
HHD8
1.8
1.8
1.8
0.0
0.0
Combination
Short-haul
Truck
MHD67
2.3
2.2
2.3
0.0
0.0
HHD8
2.4
2.4
2.4
0.0
0.0
Combination
Long-haul
Truck
MHD67
2.4
2.4
2.4
0.0
0.0
HHD8
2.4
2.4
2.4
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-47 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
2.0
1.8
1.9
-0.1
-0.1
HHD8
1.9
1.9
1.9
0.0
0.0
520
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
2.0
1.9
2.0
-0.1
0.0
Urban Bus
1.9
1.9
1.9
0.0
0.0
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.4
1.2
1.3
-0.2
-0.1
HHD8
1.5
1.5
1.5
0.0
0.0
Refuse Truck
MHD67
2.1
1.8
1.9
-0.3
-0.2
HHD8
2.0
2.0
2.0
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
0.6
0.6
0.6
-0.1
0.0
MHD67
1.2
1.1
1.2
-0.1
0.0
HHD8
1.8
1.8
1.8
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
0.6
0.6
0.6
0.0
0.0
MHD67
1.1
1.1
1.1
-0.1
0.0
HHD8
1.7
1.7
1.7
0.0
0.0
Combination
Short-haul
Truck
MHD67
2.1
2.1
2.1
0.0
0.0
HHD8
2.2
2.2
2.2
0.0
0.0
Combination
Long-haul
Truck
MHD67
2.2
2.2
2.2
0.0
0.0
HHD8
2.2
2.2
2.2
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-48 DEF Cost Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.4
1.3
1.3
-0.1
0.0
HHD8
1.3
1.3
1.3
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.4
1.4
1.4
0.0
0.0
Urban Bus
1.3
1.3
1.3
0.0
0.0
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.0
0.8
0.9
-0.1
-0.1
HHD8
1.1
1.1
1.1
0.0
0.0
Refuse Truck
MHD67
1.5
1.3
1.4
-0.2
-0.1
HHD8
1.5
1.5
1.5
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
0.5
0.4
0.4
0.0
0.0
MHD67
0.9
0.9
0.9
0.0
0.0
HHD8
1.4
1.4
1.4
0.0
0.0
LHD45
0.4
0.4
0.4
0.0
0.0
MHD67
0.9
0.8
0.8
-0.1
0.0
521
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Single Unit
Long-haul
Truck
HHD8
1.3
1.3
1.3
0.0
0.0
Combination
Short-haul
Truck
MHD67
1.7
1.6
1.7
0.0
0.0
HHD8
1.7
1.7
1.7
0.0
0.0
Combination
Long-haul
Truck
MHD67
1.6
1.6
1.6
0.0
0.0
HHD8
1.7
1.7
1.7
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-49 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.9
1.9
1.9
0.0
0.0
HHD8
1.9
1.9
1.9
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.9
1.9
1.9
0.0
0.0
Urban Bus
1.9
1.8
1.9
-0.1
0.0
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.3
1.0
1.1
-0.3
-0.2
HHD8
1.6
1.4
1.5
-0.2
-0.1
Refuse Truck
MHD67
2.0
1.8
1.9
-0.2
-0.1
HHD8
2.1
1.8
1.9
-0.2
-0.2
Single Unit
Short-haul
Truck
LHD45
0.6
0.5
0.5
-0.1
-0.1
MHD67
1.1
1.1
1.1
0.0
0.0
HHD8
1.8
1.8
1.8
-0.1
0.0
Single Unit
Long-haul
Truck
LHD45
0.5
0.5
0.5
0.0
0.0
MHD67
1.1
1.0
1.0
-0.1
0.0
HHD8
1.7
1.6
1.7
-0.1
0.0
Combination
Short-haul
Truck
MHD67
2.1
2.0
2.0
-0.1
0.0
HHD8
2.2
2.0
2.0
-0.2
-0.1
Combination
Long-haul
Truck
MHD67
2.3
2.2
2.2
-0.1
-0.1
HHD8
2.3
2.2
2.2
-0.1
-0.1
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
522
-------
Table 3-50 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.6
1.6
1.6
0.0
0.0
HHD8
1.7
1.7
1.7
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.7
1.7
1.7
0.0
0.0
Urban Bus
1.7
1.6
1.7
-0.1
0.0
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.2
0.9
1.0
-0.3
-0.2
HHD8
1.4
1.2
1.3
-0.2
-0.1
Refuse Truck
MHD67
1.8
1.6
1.7
-0.2
-0.1
HHD8
1.8
1.6
1.7
-0.2
-0.1
Single Unit
Short-haul
Truck
LHD45
0.5
0.4
0.4
-0.1
0.0
MHD67
1.0
1.0
1.0
0.0
0.0
HHD8
1.6
1.6
1.6
-0.1
0.0
Single Unit
Long-haul
Truck
LHD45
0.5
0.5
0.5
0.0
0.0
MHD67
1.0
0.9
0.9
-0.1
0.0
HHD8
1.5
1.5
1.5
-0.1
0.0
Combination
Short-haul
Truck
MHD67
1.9
1.8
1.9
-0.1
0.0
HHD8
2.0
1.8
1.9
-0.2
-0.1
Combination
Long-haul
Truck
MHD67
2.0
2.0
2.0
-0.1
0.0
HHD8
2.1
2.0
2.0
-0.1
-0.1
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-51 DEF Cost Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.0
1.0
1.0
0.0
0.0
HHD8
1.1
1.1
1.1
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.1
1.1
1.1
0.0
0.0
Urban Bus
1.1
1.0
1.1
-0.1
0.0
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
0.7
0.6
0.6
-0.2
-0.1
HHD8
0.9
0.8
0.8
-0.1
0.0
523
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Refuse Truck
MHD67
1.1
1.0
1.1
-0.1
-0.1
HHD8
1.2
1.0
1.1
-0.1
-0.1
Single Unit
Short-haul
Truck
LHD45
0.3
0.3
0.3
0.0
0.0
MHD67
0.7
0.7
0.7
0.0
0.0
HHD8
1.1
1.1
1.1
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
0.3
0.3
0.3
0.0
0.0
MHD67
0.7
0.6
0.7
0.0
0.0
HHD8
1.1
1.0
1.1
0.0
0.0
Combination
Short-haul
Truck
MHD67
1.3
1.3
1.3
-0.1
0.0
HHD8
1.4
1.2
1.3
-0.1
-0.1
Combination
Long-haul
Truck
MHD67
1.4
1.3
1.3
0.0
0.0
HHD8
1.4
1.3
1.3
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-52 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.8
1.8
1.8
0.0
0.0
HHD8
1.9
1.9
1.9
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.8
1.7
1.8
0.0
0.0
Urban Bus
1.9
1.3
1.8
-0.6
-0.1
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.3
0.5
0.9
-0.8
-0.4
HHD8
1.5
1.1
1.4
-0.5
-0.1
Refuse Truck
MHD67
1.9
1.5
1.8
-0.4
-0.1
HHD8
2.0
1.4
1.7
-0.6
-0.2
Single Unit
Short-haul
Truck
LHD45
0.5
0.2
0.4
-0.3
-0.1
MHD67
1.1
0.9
1.1
-0.2
0.0
HHD8
1.8
1.4
1.7
-0.3
-0.1
Single Unit
Long-haul
Truck
LHD45
0.5
0.4
0.5
-0.1
0.0
MHD67
1.0
0.8
1.0
-0.2
0.0
HHD8
1.6
1.1
1.5
-0.5
-0.2
Combination
Short-haul
Truck
MHD67
2.0
1.6
1.9
-0.4
-0.1
HHD8
2.1
1.3
1.8
-0.8
-0.3
MHD67
2.1
1.7
1.9
-0.4
-0.2
524
-------
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Combination
Long-haul
Truck
HHD8
2.2
1.8
2.0
-0.4
-0.2
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-53 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.5
1.5
1.5
0.0
0.0
HHD8
1.6
1.6
1.6
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.5
1.5
1.5
0.0
0.0
Urban Bus
1.6
1.1
1.5
-0.5
-0.1
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
1.1
0.4
0.8
-0.7
-0.3
HHD8
1.3
0.9
1.2
-0.4
-0.1
Refuse Truck
MHD67
1.6
1.3
1.6
-0.4
0.0
HHD8
1.7
1.2
1.5
-0.5
-0.2
Single Unit
Short-haul
Truck
LHD45
0.5
0.2
0.4
-0.2
-0.1
MHD67
1.0
0.8
0.9
-0.2
0.0
HHD8
1.6
1.3
1.5
-0.3
-0.1
Single Unit
Long-haul
Truck
LHD45
0.4
0.4
0.4
-0.1
0.0
MHD67
0.9
0.7
0.8
-0.2
0.0
HHD8
1.5
1.0
1.3
-0.4
-0.2
Combination
Short-haul
Truck
MHD67
1.8
1.5
1.7
-0.3
-0.1
HHD8
1.9
1.2
1.6
-0.7
-0.3
Combination
Long-haul
Truck
MHD67
1.9
1.5
1.7
-0.3
-0.2
HHD8
1.9
1.5
1.7
-0.4
-0.2
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
525
-------
Table 3-54 DEF Cost Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055 for each
MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in
Final
Standards
Cost in
Alternative
Final
Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
0.9
0.9
0.9
0.0
0.0
HHD8
0.9
0.9
0.9
0.0
0.0
Transit Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
0.9
0.9
0.9
0.0
0.0
Urban Bus
1.0
0.7
0.9
-0.3
-0.1
School Bus
LHD45
0.0
0.0
0.0
0.0
0.0
MHD67
0.7
0.2
0.5
-0.4
-0.2
HHD8
0.8
0.6
0.7
-0.2
-0.1
Refuse Truck
MHD67
1.0
0.8
1.0
-0.2
0.0
HHD8
1.0
0.7
0.9
-0.3
-0.1
Single Unit
Short-haul
Truck
LHD45
0.3
0.1
0.2
-0.1
-0.1
MHD67
0.6
0.5
0.6
-0.1
0.0
HHD8
1.0
0.8
0.9
-0.2
0.0
Single Unit
Long-haul
Truck
LHD45
0.3
0.2
0.3
0.0
0.0
MHD67
0.6
0.4
0.6
-0.1
0.0
HHD8
0.9
0.7
0.8
-0.3
-0.1
Combination
Short-haul
Truck
MHD67
1.2
0.9
1.1
-0.2
0.0
HHD8
1.2
0.8
1.0
-0.4
-0.2
Combination
Long-haul
Truck
MHD67
1.2
0.9
1.1
-0.2
-0.1
HHD8
1.2
1.0
1.1
-0.2
-0.1
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
The number of diesel vehicles decrease in the final standards case compared to the reference
case therefore the total DEF costs for all vehicles are less in final standards case when computed
on an annual basis. Similarly for the alternative, there number of diesel vehicles decrease in the
alternative compared to the reference case, but to a lesser extent than in the final standards. Table
3-55 and Table 3-56 show the annual savings associated with less DEF consumption in the final
standards and alternative relative to the reference case, respectively. Note that non-diesel
vehicles are shown for completeness with no savings since those vehicles do not consume DEF.
526
-------
Table 3-55 Annual Undiscounted DEF Costs for the Final Standards relative to the Reference Case, Millions
of 2022 dollars*
Calendar Year
Diesel
Gasoline
CNG
Electricity
Hydrogen
Sum
2027
-$6
$0
$0
$0
$0
-$6
2028
-$17
$0
$0
$0
$0
-$17
2029
-$32
$0
$0
$0
$0
-$32
2030
-$61
$0
$0
$0
$0
-$61
2031
-$130
$0
$0
$0
$0
-$130
2032
-$250
$0
$0
$0
$0
-$250
2033
-$380
$0
$0
$0
$0
-$380
2034
-$500
$0
$0
$0
$0
-$500
2035
-$630
$0
$0
$0
$0
-$630
2036
-$740
$0
$0
$0
$0
-$740
2037
-$860
$0
$0
$0
$0
-$860
2038
-$960
$0
$0
$0
$0
-$960
2039
-$1,100
$0
$0
$0
$0
-$1,100
2040
-$1,200
$0
$0
$0
$0
-$1,200
2041
-$1,200
$0
$0
$0
$0
-$1,200
2042
-$1,300
$0
$0
$0
$0
-$1,300
2043
-$1,400
$0
$0
$0
$0
-$1,400
2044
-$1,400
$0
$0
$0
$0
-$1,400
2045
-$1,500
$0
$0
$0
$0
-$1,500
2046
-$1,500
$0
$0
$0
$0
-$1,500
2047
-$1,600
$0
$0
$0
$0
-$1,600
2048
-$1,600
$0
$0
$0
$0
-$1,600
2049
-$1,600
$0
$0
$0
$0
-$1,600
2050
-$1,700
$0
$0
$0
$0
-$1,700
2051
-$1,700
$0
$0
$0
$0
-$1,700
2052
-$1,700
$0
$0
$0
$0
-$1,700
2053
-$1,800
$0
$0
$0
$0
-$1,800
2054
-$1,800
$0
$0
$0
$0
-$1,800
2055
-$1,800
$0
$0
$0
$0
-$1,800
* Values rounded to two significant digits; Negative values denote lower costs, i.e., savings in expenditures.
527
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Table 3-56 Annual Undiscounted DEF Costs for the Alternative relative to the Reference Case, Millions of
2022 dollars*
Calendar Year
Diesel
Gasoline
CNG
Electricity
Hydrogen
Sum
2027
-$3
$0
$0
$0
$0
-$3
2028
-$7
$0
$0
$0
$0
-$7
2029
-$15
$0
$0
$0
$0
-$15
2030
-$35
$0
$0
$0
$0
-$35
2031
-$68
$0
$0
$0
$0
-$68
2032
-$120
$0
$0
$0
$0
-$120
2033
-$170
$0
$0
$0
$0
-$170
2034
-$210
$0
$0
$0
$0
-$210
2035
-$260
$0
$0
$0
$0
-$260
2036
-$300
$0
$0
$0
$0
-$300
2037
-$340
$0
$0
$0
$0
-$340
2038
-$370
$0
$0
$0
$0
-$370
2039
-$410
$0
$0
$0
$0
-$410
2040
-$440
$0
$0
$0
$0
-$440
2041
-$460
$0
$0
$0
$0
-$460
2042
-$480
$0
$0
$0
$0
-$480
2043
-$500
$0
$0
$0
$0
-$500
2044
-$520
$0
$0
$0
$0
-$520
2045
-$530
$0
$0
$0
$0
-$530
2046
-$540
$0
$0
$0
$0
-$540
2047
-$550
$0
$0
$0
$0
-$550
2048
-$550
$0
$0
$0
$0
-$550
2049
-$560
$0
$0
$0
$0
-$560
2050
-$560
$0
$0
$0
$0
-$560
2051
-$570
$0
$0
$0
$0
-$570
2052
-$570
$0
$0
$0
$0
-$570
2053
-$570
$0
$0
$0
$0
-$570
2054
-$580
$0
$0
$0
$0
-$580
2055
-$580
$0
$0
$0
$0
-$580
* Values rounded to two significant digits; Negative values denote lower costs, i.e., savings in expenditures.
3.4.7.3 Costs Associated with Maintenance and Repair
We assessed the estimated maintenance and repair costs of all vehicles for the reference case,
the alternative case and the final standards case under the potential compliance pathway, and
compared these estimates with estimated maintenance and repair costs for all vehicles in the
baseline on an annual basis. After consideration of comments, we have reduced the maintenance
and repair costs for vocational ICE vehicles in the final rule. This change led to a decrease in the
M&R costs of the BEVs and FCEVs accordingly, as explained below. Also explained below, we
made further changes to M&R costs for BEVs and FCEVs in the early years of the Phase 3
program such that the M&R savings do not accrue as quickly as they did in our NPRM analysis.
The results of our analysis show that maintenance and repair costs associated with HD BEVs and
FCEVs are estimated to be lower than maintenance and repair costs associated with comparable
ICE vehicles.
For the estimate of maintenance and repair costs for diesel-fueled ICE vehicles, we relied on
the research compiled by Burnham et al. 2021, in Chapter 3.5.5 of "Comprehensive Total Cost of
528
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Ownership Quantification for Vehicles with Different Size Classes and Powertrains" and used
equations found in the BEAN model, as discussed in RIA Chapter 2.3.4.2.1335>1336 Burnham et al.
used data from Utilimarc and ATRI to estimate maintenance and repair costs per mile for
multiple heavy-duty vehicle categories over time. Equation 3-1 is the curve Burnham et al. used
to estimate cost per mile as a function of age and vehicle type. In the NPRM, we used two
different curves, one for long-haul tractors and the other for vocational vehicles. As discussed in
RIA Chapter 2.3.4.2, for the final rule we selected the semi-tractor curve to represent all HD
vehicles used in Burnham et al., which leads to an overall reduction in M&R costs for all
vocational vehicles (ICE vehicle, BEV, and FCEV). Table 3-57 shows the slope and intercept
used in Equation 3-1 for each vehicle type. The slope and intercept values were converted to
from 2019 to 2022 dollars in Table 3-57. We assumed that gasoline and CNG vehicles had the
same maintenance and repair costs curves as diesel vehicles.
As discussed in RIA Chapter 2.4.4.1 and 2.5.3.2, several literature sources propose
multiplying diesel vehicle maintenance costs by a factor to estimate BEV and FCEV
maintenance costs. For the NPRM, we followed this approach and used scalars based on the
research in Wang et al., 20 22.1337 In this final rule, EPA has phased in the BEV and FCEV
scaling factors for maintenance and repair. Specifically, instead of applying a single scaling
factor for every year commencing in 2027 as at proposal, EPA is starting with a higher scaling
factor and gradually decreasing it (i.e., gradually increasing the projected cost savings) from
calendar year 2027-2032. These changes are discussed in RIA Chapter 2.4.4.1 and 2.5.3.2. For
the final rule, we used the scalars listed in Table 3-58 and slope and intercept listed in Table 3-57
in Equation 3-1 to compute the maintenance and repair costs on a per mile basis.
Equation 3-1 Maintenance and repair costs dollars per mile as a function of age and vehicle type
mrage = scalar * (slope * age + intercept)
Where:
mrage is the estimated maintenance and repair cost in dollars per mile at a given age
scalar is the value based on the vehicle type and calendar year
slope is from Table 3-57 (2022 dollars)
age is the current age of the vehicle
intercept is from Table 3-57 (2022 dollars)
1335 Burnham, A., Gohlke, D., Rush, L., Stephens, T., Zhou, Y., Delucchi, M. A., Birky, A., Hunter, C., Lin, Z., Ou,
S., Xie, F., Proctor, C., Wiryadinata, S., Liu, N., Boloor, M. "Comprehensive Total Cost of Ownership
Quantification for Vehicles with Different Size Classes and Powertrains". Argonne National Laboratory. Chapter
3.5.5. April 1, 2021. Available at https://publications.anl.gov/anlpubs/2021/05/167399.pdf.
1336 Argonne National Lab, Vehicle & Mobility Systems Group, BEAN, found at:
https://vms.taps.anl.gov/tools/bean/ (accessed August 2022).
1337 Wang, G., Miller, M., and Fulton, L." Estimating Maintenance and Repair Costs for Battery Electric and Fuel
Cell Heavy Duty Trucks, 2022. Available online:
https://escholarship.org/content/qt36c08395/qt36c08395_noSplash_589098e470b036b3010eae00f3b7b618.pdf?t=r6
zwjb.
529
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Table 3-57: Values for Determining Maintenance and Repair in Equation 3-1
Equation Parameter
2019 Dollars
2022 Dollars
Slope
0.03
0.033981
Intercept
0.11
0.124598
Table 3-58 Scalars of Maintenance and Repair based on Vehicle Fuel Type by Calendar Year
Vehicle
2035
Fuel
2027
2028
2029
2030
2031
2032
2033
2034
and
Type
beyond
Diesel
1
1
1
1
1
1
1
1
1
Gasoline
1
1
1
1
1
1
1
1
1
CNG
1
1
1
1
1
1
1
1
1
Electricity
0.88
0.846
0.812
0.778
0.744
0.71
0.71
0.71
0.71
Hydrogen
1
1
1
1
0.95
0.9
0.85
0.8
0.75
For a given model year, Equation 3-1 was computed by from the for every year out to CY
2055 for each MOVES source type and fuel type to get an annual maintenance and repair cost
per mile rate Each annual maintenance and repair cost by MOVES Source Type was computed
for a single age (or calendar year) by multiplying that specific age's maintenance and repair cost
per mile by VMT at that age. Then, we calculated the total maintenance and repair costs for each
MOVES Source Type and regulatory class in by summing the cost for all years from the first
calendar year of the vehicle to CY 2055. EPA divided the total maintenance and repair cost
summed from the first calendar year of the vehicle to CY 2055 by the total VMT across from age
0 to CY 2055 for each MOVES Source Type.
Table 3-59, Table 3-60, and Table 3-61 show the computed maintenance and repair costs per
mile for MY 2027 by MOVES source type for ICE vehicles compared to BEVs for the final
standards for 2-percent, 3-percent and 7-percent discounting, respectively. Note that there are no
FCEV modeled in MOVES until 2030, so there are no maintenance and repair costs for FCEV
forMY2027 tables. Table 3-62, Table 3-63, and Table 3-64 show the computed maintenance and
repair costs per mile for MY 2030 by MOVES source type for ICE vehicles compared to BEVs
and FCEVs for the final standards at 2-percent, 3-percent and 7-percent discounting,
respectively. Table 3-65, Table 3-66, and Table 3-67 show the computed maintenance and repair
costs per mile for MY 2032 by MOVES source type for ICE vehicles compared to BEVs and
FCEVs for the final standards at 2-percent, 3-percent and 7-percent discounting, respectively.
For each MOVES source type, the cost of maintenance and repair per mile remained the same
regardless of MOVES regulatory class and are reported by MOVES source type in Table 3-59
through Table 3-67.
A comparison of the maintenance and repair cost on a per mile basis for comparable ICE
vehicles compared to BEVs are shown in Table 3-59 through Table 3-67 show the reduced cost
of maintenance and repair for ZEVs compared to ICE vehicles.
The impacts of maintenance and repairs for MY 2027, 2030 and 2032 vehicles in each
MOVES source type associated with reference, final standards, and alterative cases are shown
530
-------
for 2-percent, 3-percent and 7-percent discounting in Table 3-68 through Table 3-76. Both the
final standards and alternative cases show either no change1338 or reductions in maintenance and
repair costs when compared to the reference case.
Table 3-59 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 2% discounting)
MOVES Source Type
ICE
BEV
Other Buses
35.2
25.4
Transit Bus
34.4
24.9
School Bus
35.2
25.5
Refuse Truck
32.7
23.8
Single Unit Short-haul Truck
29.8
21.8
Single Unit Long-haul Truck
28.8
21.1
Combination Short-haul Truck
28.2
20.7
Combination Long-haul Truck
30.9
22.5
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type. There are no MY 2027 FCEV.
Table 3-60 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 3% discounting)
MOVES Source Type
ICE
BEV
Other Buses
30.7
22.3
Transit Bus
30.1
21.9
School Bus
30.7
22.3
Refuse Truck
29.1
21.2
Single Unit Short-haul Truck
26.9
19.8
Single Unit Long-haul Truck
26.1
19.2
Combination Short-haul Truck
25.7
19.0
Combination Long-haul Truck
27.7
20.3
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type. There are no MY 2027 FCEV.
1338 There are no changes to vehicle populations for MY 2027 between the final standards and reference cases for the
MOVES source type of Combination Long-haul Truck, which is why the maintenance and repair cost per mile
shows no change between the final standards and reference case in Table 3-68, Table 3-69, and Table 3-70.
531
-------
Table 3-61 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 7% discounting)
MOVES Source Type
ICE
BEV
Other Buses
19.0
13.9
Transit Bus
18.9
13.9
School Bus
19.0
13.9
Refuse Truck
19.1
14.0
Single Unit Short-haul Truck
18.7
13.9
Single Unit Long-haul Truck
18.5
13.8
Combination Short-haul Truck
18.5
13.8
Combination Long-haul Truck
18.8
13.9
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type. There are no MY 2027 FCEV.
Table 3-62 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 2% discounting)
MOVES Source Type
ICE
BEV
FCEV
Other Buses
32.4
23.1
25.0
Transit Bus
31.7
22.6
-
School Bus
32.4
23.1
-
Refuse Truck
30.6
21.8
-
Single Unit Short-haul Truck
28.0
20.0
-
Single Unit Long-haul Truck
26.8
19.2
-
Combination Short-haul Truck
26.4
18.9
20.8
Combination Long-haul Truck
28.9
20.6
22.5
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type.
Table 3-63 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 3% discounting)
MOVES Source Type
ICE
BEV
FCEV
Other Buses
27.7
19.7
21.4
Transit Bus
27.2
19.4
-
School Bus
27.7
19.7
-
Refuse Truck
26.5
18.9
-
Single Unit Short-haul Truck
24.6
17.5
-
Single Unit Long-haul Truck
23.7
17.0
-
Combination Short-haul Truck
23.5
16.8
18.6
Combination Long-haul Truck
25.2
18.0
19.7
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type.
532
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Table 3-64 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 7% discounting)
MOVES Source Type
ICE
BEV
FCEV
Other Buses
15.6
11.2
12.2
Transit Bus
15.6
11.1
-
School Bus
15.6
11.2
-
Refuse Truck
15.6
11.2
-
Single Unit Short-haul Truck
15.3
11.0
-
Single Unit Long-haul Truck
15.2
10.9
-
Combination Short-haul Truck
15.2
10.9
12.1
Combination Long-haul Truck
15.4
11.0
12.2
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type.
Table 3-65 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055
for each MOVES Source Type and Regulatory Class by Fuel Type for the Final Standards* (cents/mile in
2022 dollars, 2% discounting)
MOVES Source Type
ICE
BEV
FCEV
Other Buses
30.5
21.6
23.1
Transit Bus
29.9
21.2
-
School Bus
30.5
21.7
-
Refuse Truck
29.0
20.6
-
Single Unit Short-haul Truck
26.6
18.9
-
Single Unit Long-haul Truck
25.5
18.1
-
Combination Short-haul Truck
25.2
17.9
19.3
Combination Long-haul Truck
27.5
19.5
20.9
* Values rounded to the nearest tenth of a cent; All ICE vehicles (Diesel, Gasoline and CNG) had the same cost
per mile for each source type.
Table 3-66 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055
for Each MOVES Source Type, ICE compared to BEV Costs for the Final Standards Case* (cents/mile in
2022 dollars, 3% discounting)
MOVES Source Type
ICE
BEV
FCEV
Other Buses
25.7
18.3
19.5
Transit Bus
25.3
18.0
-
School Bus
25.7
18.3
-
Refuse Truck
24.7
17.5
-
Single Unit Short-haul Truck
23.0
16.3
-
Single Unit Long-haul Truck
22.2
15.8
-
Combination Short-haul Truck
22.0
15.6
16.8
Combination Long-haul Truck
23.6
16.8
18.0
* Values rounded to the nearest tenth of a cent.
533
-------
Table 3-67 Maintenance and Repair Per Mile for Model Year 2032 Vehicles Calendar Year 2032 to 2055 for
Each MOVES Source Type, ICE to BEV for the Final Standards Case* (cents/mile in 2021 dollars, 7%
discounting)
MOVES Source Type
ICE
BEV
FCEV
Other Buses
13.7
9.7
10.4
Transit Bus
13.6
9.7
-
School Bus
13.7
9.7
-
Refuse Truck
13.7
9.7
-
Single Unit Short-haul Truck
13.4
9.5
-
Single Unit Long-haul Truck
13.2
9.4
-
Combination Short-haul Truck
13.2
9.4
10.2
Combination Long-haul Truck
13.5
9.6
10.3
* Values rounded to the nearest tenth of a cent.
Table 3-68 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
33.9
33.2
33.5
-0.6
-0.3
MHD67
34.5
33.8
34.1
-0.7
-0.3
HHD8
34.6
34.6
34.6
0.0
0.0
Transit Bus
LHD45
33.1
32.5
32.8
-0.6
-0.3
MHD67
33.7
33.5
33.7
-0.3
0.0
Urban Bus
33.8
33.8
33.8
0.0
0.0
School Bus
LHD45
34.0
33.2
33.6
-0.8
-0.5
MHD67
34.5
33.2
33.7
-1.3
-0.8
HHD8
34.6
34.6
34.6
0.0
0.0
Refuse Truck
MHD67
32.1
30.9
31.4
-1.1
-0.7
HHD8
32.4
32.4
32.4
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
29.0
28.2
28.5
-0.8
-0.6
MHD67
29.3
28.8
29.1
-0.4
-0.2
HHD8
29.5
29.5
29.5
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
28.0
28.0
28.0
0.0
0.0
MHD67
28.2
27.7
28.0
-0.5
-0.3
HHD8
28.4
28.4
28.4
0.0
0.0
Combination
Short-haul
Truck
MHD67
27.8
27.6
27.8
-0.1
0.0
HHD8
27.8
27.8
27.8
0.0
0.0
Combination
Long-haul
Truck
MHD67
30.8
30.8
30.8
0.0
0.0
HHD8
30.8
30.8
30.8
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
534
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Table 3-69 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
29.6
29.0
29.3
-0.6
-0.3
MHD67
30.1
29.5
29.8
-0.6
-0.3
HHD8
30.2
30.2
30.2
0.0
0.0
Transit Bus
LHD45
29.0
28.5
28.8
-0.5
-0.3
MHD67
29.6
29.3
29.5
-0.2
0.0
Urban Bus
29.6
29.6
29.6
0.0
0.0
School Bus
LHD45
29.7
29.0
29.3
-0.7
-0.4
MHD67
30.2
29.0
29.4
-1.1
-0.7
HHD8
30.2
30.2
30.2
0.0
0.0
Refuse Truck
MHD67
28.5
27.5
27.9
-1.0
-0.6
HHD8
28.8
28.8
28.8
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
26.2
25.5
25.7
-0.7
-0.5
MHD67
26.4
26.0
26.2
-0.4
-0.2
HHD8
26.6
26.6
26.6
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
25.4
25.4
25.4
0.0
0.0
MHD67
25.6
25.1
25.4
-0.5
-0.2
HHD8
25.8
25.8
25.8
0.0
0.0
Combination
Short-haul
Truck
MHD67
25.4
25.2
25.4
-0.1
0.0
HHD8
25.4
25.4
25.4
0.0
0.0
Combination
Long-haul
Truck
MHD67
27.7
27.7
27.7
0.0
0.0
HHD8
27.7
27.7
27.7
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
535
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Table 3-70 Maintenance and Repair Per Mile for Model Year 2027 Vehicles from Calendar Year 2027 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
18.3
18.0
18.1
-0.3
-0.2
MHD67
18.6
18.3
18.4
-0.3
-0.2
HHD8
18.7
18.7
18.7
0.0
0.0
Transit Bus
LHD45
18.2
17.9
18.1
-0.3
-0.2
MHD67
18.6
18.4
18.5
-0.1
0.0
Urban Bus
18.6
18.6
18.6
0.0
0.0
School Bus
LHD45
18.4
18.0
18.1
-0.4
-0.3
MHD67
18.6
18.0
18.2
-0.7
-0.4
HHD8
18.7
18.7
18.7
0.0
0.0
Refuse Truck
MHD67
18.7
18.0
18.3
-0.6
-0.4
HHD8
18.9
18.9
18.9
0.0
0.0
Single Unit
Short-haul
Truck
LHD45
18.2
17.7
17.9
-0.5
-0.3
MHD67
18.4
18.1
18.2
-0.3
-0.1
HHD8
18.5
18.5
18.5
0.0
0.0
Single Unit
Long-haul
Truck
LHD45
18.0
18.0
18.0
0.0
0.0
MHD67
18.2
17.8
18.0
-0.3
-0.2
HHD8
18.3
18.3
18.3
0.0
0.0
Combination
Short-haul
Truck
MHD67
18.3
18.2
18.3
-0.1
0.0
HHD8
18.3
18.3
18.3
0.0
0.0
Combination
Long-haul
Truck
MHD67
18.8
18.8
18.8
0.0
0.0
HHD8
18.8
18.8
18.8
0.0
0.0
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
536
-------
Table 3-71 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
29.3
29.1
29.3
-0.2
0.0
MHD67
30.8
30.8
30.8
0.0
0.0
HHD8
31.0
31.0
31.0
0.0
0.0
Transit Bus
LHD45
28.7
28.5
28.7
-0.2
0.0
MHD67
30.1
30.1
30.1
0.0
0.0
Urban Bus
30.4
29.9
30.3
-0.5
-0.1
School Bus
LHD45
29.7
29.1
29.4
-0.6
-0.3
MHD67
30.9
29.0
29.5
-1.9
-1.4
HHD8
31.1
30.3
30.8
-0.8
-0.4
Refuse Truck
MHD67
29.0
28.2
28.6
-0.7
-0.4
HHD8
29.8
28.8
29.2
-1.0
-0.6
Single Unit
Short-haul
Truck
LHD45
26.0
25.1
25.4
-0.9
-0.6
MHD67
26.6
26.4
26.6
-0.2
0.0
HHD8
27.1
26.9
27.1
-0.3
-0.1
Single Unit
Long-haul
Truck
LHD45
25.0
25.0
25.0
0.0
0.0
MHD67
25.5
25.1
25.4
-0.4
-0.1
HHD8
26.0
25.8
26.0
-0.2
0.0
Combination
Short-haul
Truck
MHD67
25.8
25.5
25.6
-0.3
-0.1
HHD8
25.8
25.1
25.3
-0.7
-0.5
Combination
Long-haul
Truck
MHD67
28.7
28.4
28.5
-0.3
-0.2
HHD8
28.7
28.4
28.5
-0.3
-0.2
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
537
-------
Table 3-72 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
25.0
24.9
25.0
-0.2
0.0
MHD67
26.3
26.3
26.3
0.0
0.0
HHD8
26.5
26.5
26.5
0.0
0.0
Transit Bus
LHD45
24.6
24.4
24.6
-0.2
0.0
MHD67
25.9
25.9
25.9
0.0
0.0
Urban Bus
26.0
25.6
26.0
-0.4
-0.1
School Bus
LHD45
25.4
24.9
25.1
-0.5
-0.3
MHD67
26.4
24.8
25.2
-1.6
-1.2
HHD8
26.6
25.9
26.3
-0.7
-0.3
Refuse Truck
MHD67
25.1
24.5
24.8
-0.6
-0.3
HHD8
25.8
24.9
25.2
-0.9
-0.6
Single Unit
Short-haul
Truck
LHD45
22.9
22.1
22.3
-0.8
-0.6
MHD67
23.4
23.2
23.4
-0.2
0.0
HHD8
23.9
23.6
23.8
-0.2
0.0
Single Unit
Long-haul
Truck
LHD45
22.1
22.1
22.1
0.0
0.0
MHD67
22.6
22.2
22.4
-0.3
-0.1
HHD8
23.0
22.8
23.0
-0.2
0.0
Combination
Short-haul
Truck
MHD67
22.9
22.6
22.8
-0.3
-0.1
HHD8
22.9
22.3
22.5
-0.6
-0.4
Combination
Long-haul
Truck
MHD67
25.1
24.8
24.9
-0.3
-0.2
HHD8
25.1
24.8
24.9
-0.3
-0.2
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
538
-------
Table 3-73 Maintenance and Repair Per Mile for Model Year 2030 Vehicles from Calendar Year 2030 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
14.1
14.0
14.1
-0.1
0.0
MHD67
14.8
14.8
14.8
0.0
0.0
HHD8
15.0
15.0
15.0
0.0
0.0
Transit Bus
LHD45
14.1
14.0
14.1
-0.1
0.0
MHD67
14.8
14.8
14.8
0.0
0.0
Urban Bus
14.9
14.7
14.8
-0.2
0.0
School Bus
LHD45
14.3
14.0
14.2
-0.3
-0.1
MHD67
14.9
14.0
14.2
-0.9
-0.7
HHD8
15.0
14.6
14.8
-0.4
-0.2
Refuse Truck
MHD67
14.8
14.4
14.6
-0.4
-0.2
HHD8
15.2
14.7
14.9
-0.5
-0.3
Single Unit
Short-haul
Truck
LHD45
14.2
13.8
13.9
-0.5
-0.3
MHD67
14.6
14.4
14.6
-0.1
0.0
HHD8
14.9
14.7
14.8
-0.2
0.0
Single Unit
Long-haul
Truck
LHD45
14.1
14.1
14.1
0.0
0.0
MHD67
14.4
14.2
14.3
-0.2
-0.1
HHD8
14.7
14.6
14.7
-0.1
0.0
Combination
Short-haul
Truck
MHD67
14.8
14.6
14.7
-0.2
-0.1
HHD8
14.8
14.4
14.5
-0.4
-0.3
Combination
Long-haul
Truck
MHD67
15.3
15.2
15.2
-0.2
-0.1
HHD8
15.3
15.2
15.2
-0.2
-0.1
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
539
-------
Table 3-74 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 2%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
27.0
24.6
26.7
-2.4
-0.2
MHD67
28.6
28.6
28.6
0.0
0.0
HHD8
29.0
29.0
29.0
0.0
0.0
Transit Bus
LHD45
26.4
24.1
26.2
-2.3
-0.2
MHD67
28.1
28.0
28.1
-0.1
0.0
Urban Bus
28.3
26.5
28.0
-1.8
-0.4
School Bus
LHD45
27.5
24.6
26.8
-2.8
-0.7
MHD67
28.8
24.3
26.7
-4.5
-2.1
HHD8
29.1
27.1
28.6
-2.0
-0.5
Refuse Truck
MHD67
27.1
25.7
26.9
-1.4
-0.2
HHD8
28.1
25.7
27.1
-2.4
-1.0
Single Unit
Short-haul
Truck
LHD45
24.4
21.5
23.3
-2.9
-1.0
MHD67
25.0
24.0
25.0
-1.1
-0.1
HHD8
25.7
24.5
25.4
-1.2
-0.3
Single Unit
Long-haul
Truck
LHD45
23.4
22.6
23.4
-0.8
0.0
MHD67
24.0
22.6
23.7
-1.4
-0.3
HHD8
24.6
22.6
23.9
-2.0
-0.7
Combination
Short-haul
Truck
MHD67
24.4
23.2
24.2
-1.2
-0.2
HHD8
24.5
21.9
23.5
-2.6
-1.0
Combination
Long-haul
Truck
MHD67
27.1
25.6
26.4
-1.5
-0.7
HHD8
27.1
25.6
26.4
-1.5
-0.8
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
540
-------
Table 3-75 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 3%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
22.7
20.7
22.5
-2.0
-0.2
MHD67
24.1
24.1
24.1
0.0
0.0
HHD8
24.4
24.4
24.4
0.0
0.0
Transit Bus
LHD45
22.4
20.4
22.2
-2.0
-0.2
MHD67
23.8
23.6
23.8
-0.1
0.0
Urban Bus
24.0
22.4
23.7
-1.6
-0.3
School Bus
LHD45
23.1
20.8
22.6
-2.4
-0.6
MHD67
24.3
20.5
22.5
-3.8
-1.8
HHD8
24.5
22.8
24.1
-1.7
-0.4
Refuse Truck
MHD67
23.1
21.9
23.0
-1.2
-0.2
HHD8
24.0
21.9
23.1
-2.0
-0.8
Single Unit
Short-haul
Truck
LHD45
21.0
18.6
20.2
-2.5
-0.9
MHD67
21.6
20.7
21.6
-0.9
-0.1
HHD8
22.2
21.1
22.0
-1.0
-0.2
Single Unit
Long-haul
Truck
LHD45
20.3
19.6
20.3
-0.7
0.0
MHD67
20.9
19.7
20.6
-1.2
-0.2
HHD8
21.4
19.7
20.8
-1.7
-0.6
Combination
Short-haul
Truck
MHD67
21.3
20.3
21.1
-1.1
-0.2
HHD8
21.4
19.1
20.5
-2.2
-0.8
Combination
Long-haul
Truck
MHD67
23.3
22.0
22.7
-1.3
-0.6
HHD8
23.3
22.0
22.7
-1.3
-0.7
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
541
-------
Table 3-76 Maintenance and Repair Per Mile for Model Year 2032 Vehicles from Calendar Year 2032 to 2055
for each MOVES Source Type and Regulatory Class Across All Fuel Types* (cents/mile in 2022 dollars, 7%
discounting)
MOVES
Source Type
Regulatory
Class
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative
Change from
Reference
Other Buses
LHD45
12.1
11.1
12.0
-1.1
-0.1
MHD67
12.9
12.9
12.9
0.0
0.0
HHD8
13.0
13.0
13.0
0.0
0.0
Transit Bus
LHD45
12.1
11.0
11.9
-1.1
-0.1
MHD67
12.8
12.8
12.8
-0.1
0.0
Urban Bus
12.9
12.1
12.8
-0.8
-0.2
School Bus
LHD45
12.3
11.1
12.0
-1.3
-0.3
MHD67
12.9
10.9
12.0
-2.0
-1.0
HHD8
13.1
12.2
12.8
-0.9
-0.2
Refuse Truck
MHD67
12.8
12.1
12.7
-0.7
-0.1
HHD8
13.2
12.1
12.8
-1.1
-0.5
Single Unit
Short-haul
Truck
LHD45
12.2
10.8
11.7
-1.4
-0.5
MHD67
12.6
12.0
12.6
-0.6
0.0
HHD8
12.9
12.3
12.8
-0.6
-0.1
Single Unit
Long-haul
Truck
LHD45
12.1
11.7
12.1
-0.4
0.0
MHD67
12.5
11.8
12.3
-0.7
-0.1
HHD8
12.8
11.8
12.4
-1.0
-0.4
Combination
Short-haul
Truck
MHD67
12.8
12.2
12.7
-0.6
-0.1
HHD8
12.9
11.5
12.4
-1.3
-0.5
Combination
Long-haul
Truck
MHD67
13.3
12.6
12.9
-0.7
-0.4
HHD8
13.3
12.6
12.9
-0.7
-0.4
* Values rounded to the nearest tenth of a cent; negative values denote lower costs, i.e., savings in expenditures.
Table 3-77 and Table 3-78 present the projected total maintenance and repair costs associated
with the final standards and alternative, respectively. The total maintenance and repair costs are
attributable to changes in new vehicle sales and vehicle populations. The maintenance and repair
costs on a per vehicle basis are the same in the final standards and alternative, but as more HD
ZEVs enter the HD fleet, the total maintenance and repair costs for the fleet of those vehicles
correspondingly increases. The opposite is true for diesel, gasoline, and CNG vehicles as they
phase out of the fleet such that the total maintenance and repair costs for the fleet of those
vehicles decreases as more HD ZEVs enter the HD fleet.
542
-------
Table 3-77 Annual Undiscounted Total Maintenance & Repair Costs for the Final Standards Relative to the
Reference Case, Millions of 2022 dollars *
Calendar Year
Diesel
Vehicles
Gasoline
Vehicles
CNG
Vehicles
BEVs
FCEVs
Total
2027
-$49
-$23
$0
$63
$0
-$9
2028
-$130
-$51
$0
$160
$0
-$28
2029
-$250
-$84
-$1
$280
$0
-$64
2030
-$480
-$120
-$2
$450
$24
-$130
2031
-$950
-$190
-$4
$790
$76
-$280
2032
-$1,800
-$310
-$7
$1,400
$190
-$580
2033
-$2,800
-$440
-$11
$2,100
$310
-$900
2034
-$4,000
-$570
-$15
$2,900
$450
-$1,300
2035
-$5,300
-$710
-$21
$3,800
$580
-$1,700
2036
-$6,700
-$850
-$26
$4,700
$750
-$2,200
2037
-$8,100
-$990
-$32
$5,600
$940
-$2,600
2038
-$9,500
-$1,100
-$39
$6,500
$1,100
-$3,000
2039
-$11,000
-$1,300
-$46
$7,400
$1,300
-$3,400
2040
-$12,000
-$1,400
-$53
$8,200
$1,500
-$3,900
2041
-$13,000
-$1,500
-$60
$9,100
$1,700
-$4,300
2042
-$15,000
-$1,600
-$67
$9,800
$1,800
-$4,600
2043
-$16,000
-$1,700
-$75
$11,000
$2,000
-$5,000
2044
-$17,000
-$1,800
-$82
$11,000
$2,200
-$5,300
2045
-$17,000
-$1,800
-$90
$12,000
$2,300
-$5,500
2046
-$18,000
-$1,900
-$97
$12,000
$2,400
-$5,700
2047
-$19,000
-$2,000
-$100
$12,000
$2,500
-$5,900
2048
-$19,000
-$2,000
-$110
$13,000
$2,600
-$6,100
2049
-$20,000
-$2,000
-$120
$13,000
$2,700
-$6,200
2050
-$20,000
-$2,100
-$130
$13,000
$2,800
-$6,400
2051
-$21,000
-$2,100
-$140
$14,000
$2,900
-$6,500
2052
-$21,000
-$2,200
-$150
$14,000
$2,900
-$6,600
2053
-$21,000
-$2,200
-$150
$14,000
$3,000
-$6,700
2054
-$22,000
-$2,200
-$160
$14,000
$3,100
-$6,800
2055
-$22,000
-$2,200
-$170
$14,000
$3,100
-$6,900
* Values rounded to two significant digits; negative values denote lower costs, i.e., savings in expenditures.
543
-------
Table 3-78 Annual Undiscounted Total Maintenance & Repair Costs for the Alternative Relative to the
Reference Case, Millions of 2022 dollars *
Calendar Year
Diesel
Vehicles
Gasoline
Vehicles
CNG
Vehicles
BEVs
FCEVs
Total
2027
-$27
-$14
$0
$36
$0
-$5
2028
-$65
-$32
$0
$83
$0
-$15
2029
-$130
-$53
$0
$150
$0
-$35
2030
-$270
-$77
-$1
$260
$16
-$74
2031
-$510
-$110
-$1
$420
$49
-$150
2032
-$880
-$150
-$2
$650
$100
-$280
2033
-$1,300
-$190
-$4
$930
$160
-$410
2034
-$1,800
-$230
-$5
$1,200
$220
-$550
2035
-$2,300
-$260
-$7
$1,500
$290
-$720
2036
-$2,800
-$280
-$9
$1,800
$370
-$870
2037
-$3,300
-$300
-$11
$2,100
$450
-$1,000
2038
-$3,800
-$320
-$12
$2,400
$530
-$1,200
2039
-$4,200
-$330
-$14
$2,700
$620
-$1,300
2040
-$4,700
-$330
-$16
$2,900
$700
-$1,400
2041
-$5,100
-$330
-$18
$3,100
$780
-$1,500
2042
-$5,500
-$320
-$20
$3,300
$850
-$1,600
2043
-$5,800
-$300
-$22
$3,500
$920
-$1,700
2044
-$6,000
-$290
-$24
$3,600
$980
-$1,800
2045
-$6,200
-$270
-$26
$3,700
$1,000
-$1,800
2046
-$6,400
-$250
-$28
$3,700
$1,100
-$1,900
2047
-$6,500
-$230
-$29
$3,800
$1,100
-$1,900
2048
-$6,600
-$220
-$31
$3,800
$1,100
-$1,900
2049
-$6,700
-$200
-$33
$3,800
$1,200
-$2,000
2050
-$6,800
-$190
-$35
$3,900
$1,200
-$2,000
2051
-$6,900
-$180
-$37
$3,900
$1,300
-$2,000
2052
-$7,000
-$160
-$39
$3,900
$1,300
-$2,000
2053
-$7,000
-$150
-$41
$3,900
$1,300
-$2,000
2054
-$7,100
-$140
-$43
$3,900
$1,300
-$2,000
2055
-$7,100
-$130
-$45
$3,900
$1,300
-$2,000
* Values rounded to two significant digits; negative values denote lower costs, i.e., savings in expenditures.
3.4.7.4 Costs Associated with Insurance
As discussed in Preamble II.E.5, we did not take into account the cost of insurance on the user
in the NPRM. A few commenters suggested we should consider the addition of insurance cost
because the incremental cost of insurance for the ZEVs will be higher than ICE vehicles. We
agree that insurance costs may differ between ICE vehicles and ZEVs and this is a cost that will
be seen by the operator. Therefore, for the final rule analysis, we included the incremental
insurance costs of a ZEV relative to a comparable ICE vehicle under the potential compliance
pathway by incorporating an annual insurance cost equal to 3 percent of initial upfront vehicle
technology RPE cost, as described in Section II.E.5 of the preamble. This annual cost was
applied for each operating year of the vehicle.
To calculate the year over year insurance costs, EPA multiplied 3 percent of the initial vehicle
technology package RPE by estimated sales for the final standards and reference cases, and
continued the cost for each year that a vehicle operates. The difference between the final
544
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standards case and reference case as well as the alternative and reference case for insurance costs
are shown on an annual basis for the entire fleet in Table 3-79.
Table 3-79 Annual Insurance Costs for the Final Standards and Alternative Relative to the Reference Case,
Millions of 2022 Dollars*
Calendar Year
Final Standards
Relative to
Reference Case
Alternative Relative to
Reference Case
2027
-$1.1
-$1.1
2028
-$5.4
-$4.0
2029
-$14
-$9.4
2030
-$18
-$12
2031
-$23
-$11
2032
-$20
-$7.1
2033
-$11
$0.44
2034
-$3.3
$8.5
2035
$1.8
$17
2036
$2.7
$25
2037
$3.4
$32
2038
-$1.4
$38
2039
-$7.7
$44
2040
-$15
$50
2041
-$26
$55
2042
-$38
$59
2043
-$49
$64
2044
-$63
$67
2045
-$78
$70
2046
-$93
$73
2047
-$110
$74
2048
-$130
$76
2049
-$140
$77
2050
-$160
$79
2051
-$180
$81
2052
-$190
$80
2053
-$210
$79
2054
-$230
$79
2055
-$250
$78
PV, 2%
-$1,300
$830
PV, 3%
-$1,000
$680
PV, 7%
-$460
$310
AV, 2%
-$60
$38
AV, 3%
-$55
$35
AV, 7%
-$38
$25
* Values show 2 significant digits; negative values denote lower costs,
i.e., savings in expenditures.
3.4.7.5 Costs Associated with State Registration Fees on ZEVs
As discussed in Preamble II.E.5, we did not take into account the cost of state registration fees
on ZEVs in the NPRM. Commenters suggested we should consider the addition of state
registration fees on ZEVs because some states have adopted state ZEV registration fees in some
cases to replace gasoline and diesel road tax revenue. Currently, many states do not have any
545
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additional registration fee for EVs. For the states that do, the registration fees are generally
between $50 and $225 per year. While EPA cannot predict whether and to what extent other
states will enact EV registration fees, we have nonetheless conservatively added an annual
additional registration fee to all ZEV vehicles of $100 in our cost analysis. This annual cost was
applied for each operating year of the vehicle. Table 3-80 shows the annual estimated state
registration fees on BEVs on annual basis for both the final standards and alternative relative to
the reference case.
Table 3-80 Annual State Registration Fees on ZEVs for the Final Standards and Alternative Relative to the
Reference Case, Millions of 2022 Dollars*
Calendar Year
Final Standards
Relative to
Reference Case
Alternative Relative to
Reference Case
2027
$2.6
$1.6
2028
$5.6
$3.3
2029
$8.9
$5.3
2030
$13
$7.8
2031
$22
$11
2032
$36
$16
2033
$49
$20
2034
$62
$24
2035
$74
$27
2036
$85
$29
2037
$97
$32
2038
$110
$34
2039
$120
$36
2040
$130
$37
2041
$140
$38
2042
$150
$40
2043
$160
$41
2044
$160
$42
2045
$170
$43
2046
$180
$44
2047
$190
$44
2048
$190
$45
2049
$200
$45
2050
$210
$46
2051
$210
$46
2052
$220
$46
2053
$220
$46
2054
$220
$46
2055
$230
$46
PV, 2%
$2,500
$660
PV, 3%
$2,100
$560
PV, 7%
$1,000
$300
AV, 2%
$110
$30
AV, 3%
$110
$29
AV, 7%
$85
$25
* Values show 2 significant digits.
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3.4.7.6 Costs Associated with Battery Replacement and ICE Engine Rebuilding
As discussed in Preamble II.E.6, we did not take into account the cost of battery replacement
and engine rebuild on the user in the NPRM. In the final rule, after consideration of comment,
we added battery replacement and engine rebuild costs. Battery replacement and engine rebuild
frequency and costs depend on MOVES vehicle source type and regulatory class. The BEV
battery replacement and ICE engine rebuild cost and frequency of rebuild and replacement
estimates on per vehicle basis are shown in Table 3-81.1339
To calculate the year over year battery replacement and ICE engine rebuild costs, EPA
multiplied replacement RPE at the frequency shown for each MOVES source type and
regulatory class in the lifetime year of replacement from Table 3-81 for each vehicle of the fleet
that was still operating in their replacement year. Table 3-82 shows the annual estimated battery
replacement and ICE engine rebuild costs on annual basis for both the final standards and
alternative relative to the reference case.
1339 Sanchez, James. Memorandum to docket EPA-HQ-OAR-2022-0985. "Estimating Battery Replacement and
Engine Rebuild Costs". February 23, 2023.
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Table 3-81 Battery Replacement and ICE Engine Rebuild Costs Frequency and Costs in 2022 Dollars
MOVES Source Type
MOVES
Regulatory Class
Vehicle
Type
Lifetime
Year of
Replacement
Replacement
RPE
Other Buses
LHD45
15
$9,223
MHD67
15
$14,576
LHD45
15
$9,778
Transit Bus
MHD67
15
$17,389
Urban Bus
BEV
15
$28,116
Refuse Truck
MHD67
15
$12,448
Combination Short-haul Truck
MHD67
15
$4,430
HHD8
15
$3,725
Combination Long-haul Truck
HHD8
15
$22,126
Other Buses
LHD45
11
$7,175
MHD67
14
$6,203
LHD45
11
$7,175
Transit Bus
MHD67
14
$6,203
Urban Bus
ICE Diesel
12
$6,953
Refuse Truck
MHD67
14
$6,203
Combination Short-haul Truck
MHD67
14
$6,203
HHD8
12
$11,773
Combination Long-haul Truck
HHD8
12
$11,773
Other Buses
LHD45
11
$7,175
MHD67
11
$6,203
LHD45
11
$7,175
Transit Bus
MHD67
ICE
Gasoline
11
$6,203
Urban Bus
11
$6,953
Refuse Truck
MHD67
11
$6,203
Combination Short-haul Truck
MHD67
11
$6,953
HHD8
11
$6,953
Combination Long-haul Truck
HHD8
11
$6,953
Other Buses
LHD45
11
$7,175
MHD67
14
$6,203
LHD45
11
$7,175
Transit Bus
MHD67
14
$6,203
Urban Bus
ICE CNG
12
$6,953
Refuse Truck
MHD67
14
$6,203
Combination Short-haul Truck
MHD67
14
$6,203
HHD8
12
$11,773
Combination Long-haul Truck
HHD8
12
$11,773
548
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Table 3-82 Annual Battery Replacement and ICE Engine Rebuild Insurance Costs for the Final Standards
and Alternative Relative to the Reference Case, Millions of 2022 Dollars*
Calendar Year
Final Standards Relative
to Reference Case
Alternative Relative
to Reference Case
2027
$0
$0
2028
$0
$0
2029
$0
$0
2030
$0
$0
2031
$0
$0
2032
$0
$0
2033
$0
$0
2034
$0
$0
2035
$0
$0
2036
$0
$0
2037
-$3.7
-$1.9
2038
-$2.9
-$1.0
2039
-$22
-$4.8
2040
-$47
-$27
2041
-$98
-$62
2042
-$210
-$110
2043
-$370
-$150
2044
-$340
-$120
2045
-$270
-$91
2046
-$150
-$51
2047
-$150
-$52
2048
-$150
-$52
2049
-$150
-$51
2050
-$150
-$50
2051
-$150
-$50
2052
-$150
-$50
2053
-$150
-$48
2054
-$150
-$46
2055
-$140
-$44
PV, 2%
-$1,900
-$710
PV, 3%
-$1,500
-$590
PV, 7%
-$720
-$280
AV, 2%
-$86
-$33
AV, 3%
-$80
-$31
AV, 7%
-$58
-$23
* Values show 2 significant digits; negative values denote lower costs, i.e.,
savings in expenditures.
3.4.7.7 Costs Associated with EVSE Replacement
As discussed in Preamble II.E.6, we did not take into account the cost of EVSE replacement
on the user in the NPRM. In the final rule, after consideration of comment, we added EVSE
replacement. There is limited data on the expected lifespan of charging infrastructure. We make
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the simplifying assumption that all depot EVSE ports have a 15-year equipment lifetime.1340
After that, we assume they must be replaced at full cost. This assumption likely overestimates
costs as some EVSE providers may opt to upgrade existing equipment rather than incur the cost
of a full replacement. Some installation costs such as trenching or electrical upgrades may also
not be needed for the replacement. Table 3-83 shows the annual estimated EVSE replacement
costs on annual basis for both the final standards and alternative relative to the reference case.
Table 3-83 Annual EVSE Replacement Costs for the Final Standards and Alternative Relative to the
Reference Case, Millions of 2022 Dollars*
Calendar Year
Final Standards Relative
to Reference Case
Alternative Relative
to Reference Case
2027
$0
$0
2028
$0
$0
2029
$0
$0
2030
$0
$0
2031
$0
$0
2032
$0
$0
2033
$0
$0
2034
$0
$0
2035
$0
$0
2036
$0
$0
2037
$0
$0
2038
$0
$0
2039
$0
$0
2040
$0
$0
2041
$370
$210
2042
$520
$240
2043
$610
$340
2044
$530
$300
2045
$1,100
$410
2046
$1,700
$520
2047
$1,600
$420
2048
$1,500
$320
2049
$1,300
$230
2050
$1,300
$210
2051
$1,300
$200
2052
$1,300
$180
2053
$1,300
$160
2054
$1,300
$140
2055
$1,300
$130
PV, 2%
$11,000
$2,700
PV, 3%
$8,700
$2,200
PV, 7%
$3,700
$1,000
AV, 2%
$500
$120
AV, 3%
$450
$110
AV, 7%
$300
$81
1340 Borlaug, B., Salisbury, S., Gerdes, M., and Muratori, M. "Levelized Cost of Charging Electric Vehicles in the
United States," 2020. Available online:
https://www.sciencedirect.com/science/article/pii/S25424351203023127via%3Dihub.
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3.4.8 Analysis of Payback Periods
A payback period is the point in time at which savings from reduced operating expenses
surpass increased upfront costs, typically estimated in years. The payback period for a new
vehicle purchase is an important metric for many HD vehicle purchasers. In general, there is
greater willingness to pay for new technology if that new technology "pays back" within an
acceptable period of time. EPA calculated a payback period for each of the 101 example vehicles
in HD TRUCS. These results are shown in RIA Chapter 2.9.2. We further calculated the average
payback periods for the average of each regulatory group. These results are shown in RIA
Chapter 2.10.6. Briefly, the incremental upfront costs for ZEVs are estimated in contrast to
comparable ICE vehicles under the potential compliance pathway's technology packages. In
these incremental upfront costs for ZEVs, EPA factors in the IRA battery and vehicle tax credits
as discussed in RIA Chapter 3.3.2 and 3.4.2. Then EPA computed the expected operating costs
differences between ZEV and ICE vehicles. When the operating cost savings offset the
incremental upfront differences between ZEV and ICE vehicles, a breakeven point is met. The
amount of time from purchase to the breakeven point is defined as the payback period.
3.5 Social Costs
To compute the social costs of the final standards, alternative and reference scenarios, we
added the estimated total vehicle technology package RPE from Chapter 3.2.3, operating costs
from Chapter 3.4.7, and total EVSE RPE from Chapter 3.4.3. All of the costs are computed for
the MOVES final standards, alternative and reference cases and cost impacts are presented as the
difference between the final standards and reference case or alternative and reference case. We
note that the fuel costs in this subsection's social cost analysis are estimated pre-tax rather than
what the purchaser will pay (i.e., the retail fuel price). In addition, the battery tax credit, vehicle
tax credit, EVSE tax credit, excise tax, sales tax, and state registration fees on ZEVs, like fuel
taxes, are treated as transfers and are not included in our social costs. We present transfers in
Chapter 8.2 of this RIA.
3.5.1 Total Vehicle Technology Package RPE
Table 3-84 and Table 3-85 show the direct manufacturing costs, indirect costs, and total
technology costs of the final standard and alternative options relative to the reference case.
Values shown for a given calendar year are undiscounted values while discounted values are
presented at 2-percent, 3-percent, and 7-percent discount rates. All values are shown in 2022
dollars.
551
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Table 3-84 Total Package RPE Cost Impacts of the Final Standards Relative to the Reference Case, All
Regulatory Classes and All Fuels, Millions of 2022 dollars*
Calendar Year
Direct Manufacturing Costs
Indirect Costs
Total Technology Package Costs
2027
$21
$9.0
$30
2028
-$9.7
-$4.1
-$14
2029
-$60
-$25
-$85
2030
$120
$49
$160
2031
$190
$79
$270
2032
$340
$140
$480
2033
$220
$91
$310
2034
$180
$76
$260
2035
$110
$47
$160
2036
$16
$6.80
$23
2037
-$18
-$7.50
-$25
2038
-$98
-$41
-$140
2039
-$160
-$69
-$230
2040
-$180
-$76
-$260
2041
-$230
-$98
-$330
2042
-$290
-$120
-$400
2043
-$280
-$120
-$390
2044
-$320
-$130
-$450
2045
-$360
-$150
-$510
2046
-$350
-$150
-$490
2047
-$370
-$160
-$530
2048
-$390
-$170
-$560
2049
-$420
-$180
-$590
2050
-$400
-$170
-$570
2051
-$420
-$180
-$590
2052
-$440
-$180
-$620
2053
-$450
-$190
-$640
2054
-$430
-$180
-$610
2055
-$420
-$170
-$590
PV, 2%
-$2,900
-$1,200
-$4,200
PV, 3%
-$2,300
-$950
-$3,200
PV, 7%
-$720
-$300
-$1,000
AV, 2%
-$130
-$56
-$190
AV, 3%
-$120
-$49
-$170
AV, 7%
-$59
-$25
-$83
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in expenditures.
552
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Table 3-85 Total Package RPE Cost Impacts of the Alternative Option Relative to the Reference Case, All
Regulatory Classes and All Fuels, Millions of 2022 dollars*
Calendar Year
Direct Manufacturing Costs
Indirect Costs
Total Technology Package Costs
2027
$1.3
$0.53
$1.8
2028
-$23
-$9.5
-$32
2029
-$48
-$20
-$69
2030
$76
$32
$110
2031
$150
$62
$210
2032
$200
$83
$280
2033
$180
$74
$250
2034
$190
$79
$270
2035
$190
$82
$280
2036
$170
$71
$240
2037
$160
$69
$230
2038
$150
$61
$210
2039
$130
$57
$190
2040
$140
$57
$190
2041
$130
$55
$180
2042
$120
$49
$160
2043
$110
$47
$160
2044
$97
$41
$140
2045
$83
$35
$120
2046
$80
$34
$110
2047
$71
$30
$100
2048
$61
$26
$87
2049
$53
$22
$75
2050
$53
$22
$76
2051
$47
$20
$67
2052
$41
$17
$58
2053
$36
$15
$50
2054
$38
$16
$54
2055
$39
$16
$55
PV, 2%
$2,100
$880
$3,000
PV, 3%
$1,900
$780
$2,600
PV, 7%
$1,200
$490
$1,700
AV, 2%
$96
$40
$140
AV, 3%
$96
$40
$140
AV, 7%
$96
$40
$140
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in expenditures.
3.5.2 Total EVSE RPE
Table 3-86 shows the EVSE cost in the reference, final standard and alternative cases, as well
as the differences between the final standard and reference cases and the difference between the
alternative and reference cases. Values shown for a given calendar year are undiscounted values
while discounted values are presented at 2-percent, 3-percent, and 7-percent discount rates. All
values are shown in 2022 dollars.
553
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Table 3-86 Total EVSE Cost in the Reference, Final Standards, Alternative, Change between Final Standards
and Reference Case, Change between Alternative and Reference Case; All Regulatory Classes and All Fuels,
Millions of 2022 dollars*
Calendar
Year
Cost in
Reference
Cost in Final
Standards
Cost in
Alternative
Final Standards
Change from
Reference
Alternative Change
from Reference
2027
$820
$1,300
$1,100
$440
$250
2028
$1,200
$1,800
$1,500
$610
$290
2029
$1,600
$2,300
$2,000
$730
$410
2030
$1,600
$2,300
$2,000
$630
$360
2031
$1,700
$3,000
$2,200
$1,300
$480
2032
$1,800
$3,800
$2,400
$2,000
$620
2033
$2,000
$3,900
$2,500
$1,900
$490
2034
$2,200
$3,900
$2,600
$1,700
$380
2035
$2,400
$4,000
$2,700
$1,600
$260
2036
$2,500
$4,100
$2,800
$1,600
$240
2037
$2,600
$4,100
$2,800
$1,500
$220
2038
$2,700
$4,200
$2,900
$1,500
$200
2039
$2,700
$4,300
$2,900
$1,500
$180
2040
$2,800
$4,300
$3,000
$1,500
$160
2041
$2,900
$4,400
$3,000
$1,500
$140
2042
$3,000
$4,400
$3,100
$1,400
$130
2043
$3,100
$4,500
$3,200
$1,400
$130
2044
$3,100
$4,500
$3,200
$1,400
$120
2045
$3,200
$4,500
$3,300
$1,400
$120
2046
$3,200
$4,600
$3,300
$1,300
$110
2047
$3,300
$4,600
$3,400
$1,300
$110
2048
$3,400
$4,600
$3,500
$1,300
$100
2049
$3,400
$4,700
$3,500
$1,300
$99
2050
$3,500
$4,800
$3,600
$1,200
$95
2051
$3,600
$4,800
$3,700
$1,200
$92
2052
$3,700
$4,900
$3,800
$1,200
$89
2053
$3,800
$5,000
$3,900
$1,200
$86
2054
$3,900
$5,000
$4,000
$1,200
$82
2055
$4,000
$5,100
$4,100
$1,100
$79
PV, 2%
$57,000
$86,000
$62,000
$28,000
$5,000
PV, 3%
$49,000
$74,000
$54,000
$25,000
$4,600
PV, 7%
$28,000
$44,000
$32,000
$15,000
$3,400
AV, 2%
$2,600
$3,900
$2,800
$1,300
$230
AV, 3%
$2,600
$3,800
$2,800
$1,300
$240
AV, 7%
$2,300
$3,600
$2,600
$1,300
$270
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in expenditures.
3.5.3 Total Operating Cost
Table 3-87 and Table 3-88 show the total operating costs of the final standards case and
alternative case relative to the reference case. Each table shows the operating costs for pre-tax
fuel costs, DEF costs, maintenance and repair costs, insurance costs, battery replacement costs,
EVSE replacement costs and the net operating cost. Values shown for a given calendar year are
undiscounted values while discounted values are presented at 2-percent, 3-percent, and 7-percent
discount rates. All values are shown in 2022 dollars.
554
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Note that the fuel costs, DEF costs, and maintenance costs are shown as negative costs, or
savings. This is expected as these costs are lower for BEVs and FCEVs and the final standards
case (under the modeled potential compliance pathway) and alternative case include a greater
number of BEVs and FCEVs than the reference case.
Table 3-87 Total Operating Cost Impacts of the Final Standards Relative to the Reference Case, All
Regulatory Classes and All Fuels, Millions of 2022 dollars*
Calendar
Year
Pre-Tax
Fuel Costs
DEF
Costs
Maintenance
Costs
BEV Battery Replacement
and ICE Engine Rebuild
Insurance
Total
Operating
Costs
2027
-$84
-$6.3
-$8.60
$0
-$1.1
-$100
2028
-$170
-$17
-$28
$0
-$5.4
-$220
2029
-$280
-$32
-$64
$0
-$14
-$390
2030
-$170
-$61
-$130
$0
-$18
-$380
2031
-$110
-$130
-$280
$0
-$23
-$540
2032
$37
-$250
-$580
$0
-$20
-$810
2033
$120
-$380
-$900
$0
-$11
-$1,200
2034
$170
-$500
-$1,300
$0
-$3.30
-$1,600
2035
$160
-$630
-$1,700
$0
$1.80
-$2,200
2036
$350
-$740
-$2,200
$0
$2.70
-$2,500
2037
$490
-$860
-$2,600
-$3.7
$3.40
-$3,000
2038
$640
-$960
-$3,000
-$2.9
-$1.40
-$3,300
2039
$810
-$1,100
-$3,400
-$22
-$7.70
-$3,700
2040
$980
-$1,200
-$3,900
-$47
-$15
-$4,100
2041
$990
-$1,200
-$4,300
-$98
-$26
-$4,300
2042
$1,100
-$1,300
-$4,600
-$210
-$38
-$4,600
2043
$1,100
-$1,400
-$5,000
-$370
-$49
-$5,100
2044
$1,200
-$1,400
-$5,300
-$340
-$63
-$5,400
2045
$1,200
-$1,500
-$5,500
-$270
-$78
-$5,100
2046
$880
-$1,500
-$5,700
-$150
-$93
-$4,900
2047
$800
-$1,600
-$5,900
-$150
-$110
-$5,400
2048
$670
-$1,600
-$6,100
-$150
-$130
-$5,800
2049
$540
-$1,600
-$6,200
-$150
-$140
-$6,300
2050
$430
-$1,700
-$6,400
-$150
-$160
-$6,600
2051
$420
-$1,700
-$6,500
-$150
-$180
-$6,800
2052
$410
-$1,700
-$6,600
-$150
-$190
-$7,000
2053
$390
-$1,800
-$6,700
-$150
-$210
-$7,100
2054
$370
-$1,800
-$6,800
-$150
-$230
-$7,300
2055
$350
-$1,800
-$6,900
-$140
-$250
-$7,400
PV, 2%
$9,500
-$21,000
-$73,000
-$1,900
-$1,300
-$76,000
PV, 3%
$7,900
-$17,000
-$60,000
-$1,500
-$1,000
-$63,000
PV, 7%
$3,900
-$8,700
-$30,000
-$720
-$460
-$32,000
AV, 2%
$430
-$950
-$3,300
-$86
-$60
-$3,500
AV, 3%
$410
-$900
-$3,100
-$80
-$55
-$3,300
AV, 7%
$310
-$710
-$2,400
-$58
-$38
-$2,600
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in expenditures.
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Table 3-88 Total Operating Cost Impacts of the Alternative Option Relative to the Reference Case, All
Regulatory Classes and All Fuels, Millions of 2022 dollars*
Calendar
Year
Pre-Tax
Fuel Costs
DEF
Costs
Maintenance
Costs
BEV Battery Replacement
and ICE Engine Rebuild
Insurance
Total
Operating
Costs
2027
-$50
-$3.2
-$5
$0
-$1.1
-$59
2028
-$97
-$7.3
-$15
$0
-$4
-$120
2029
-$160
-$15
-$35
$0
-$9.4
-$220
2030
-$94
-$35
-$74
$0
-$12
-$210
2031
-$13
-$68
-$150
$0
-$11
-$240
2032
$94
-$120
-$280
$0
-$7.1
-$310
2033
$190
-$170
-$410
$0
$0.44
-$380
2034
$280
-$210
-$550
$0
$8.5
-$470
2035
$350
-$260
-$720
$0
$17
-$600
2036
$510
-$300
-$870
$0
$25
-$630
2037
$650
-$340
-$1,000
-$1.9
$32
-$670
2038
$790
-$370
-$1,200
-$1.0
$38
-$710
2039
$930
-$410
-$1,300
-$4.8
$44
-$730
2040
$1,100
-$440
-$1,400
-$27
$50
-$760
2041
$1,100
-$460
-$1,500
-$62
$55
-$640
2042
$1,200
-$480
-$1,600
-$110
$59
-$670
2043
$1,300
-$500
-$1,700
-$150
$64
-$670
2044
$1,400
-$520
-$1,800
-$120
$67
-$670
2045
$1,400
-$530
-$1,800
-$91
$70
-$560
2046
$1,400
-$540
-$1,900
-$51
$73
-$520
2047
$1,400
-$550
-$1,900
-$52
$74
-$660
2048
$1,300
-$550
-$1,900
-$52
$76
-$800
2049
$1,300
-$560
-$2,000
-$51
$77
-$950
2050
$1,300
-$560
-$2,000
-$50
$79
-$1,000
2051
$1,300
-$570
-$2,000
-$50
$81
-$1,000
2052
$1,300
-$570
-$2,000
-$50
$80
-$1,100
2053
$1,300
-$570
-$2,000
-$48
$79
-$1,100
2054
$1,300
-$580
-$2,000
-$46
$79
-$1,100
2055
$1,300
-$580
-$2,000
-$44
$78
-$1,100
PV, 2%
$16,000
-$7,500
-$25,000
-$710
$830
-$13,000
PV, 3%
$13,000
-$6,200
-$21,000
-$590
$680
-$11,000
PV, 7%
$6,500
-$3,200
-$10,000
-$280
$310
-$6,100
AV, 2%
$750
-$340
-$1,100
-$33
$38
-$600
AV, 3%
$700
-$330
-$1,100
-$31
$35
-$580
AV, 7%
$530
-$260
-$850
-$23
$25
-$490
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in expenditures.
3.5.4 Total Social Cost
Using the cost elements outlined in Chapters 3.2.3, 3.4.3, and 3.4.7, we have estimated the
costs associated with the final rulemaking1341; costs associated with the final standards case and
alternative case relative to the reference case are shown in Table 3-89 and Table 3-90,
respectively. As noted earlier, costs are presented in 2022 dollars in undiscounted annual values
1341 More exactly, the estimated costs are for the potential compliance pathway we modeled to support the feasibility
of the final standards.
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along with net present values at 2-percent, 3-percent, and 7-percent discount rates with values
discounted to the 2027 calendar year.
As shown in these tables, our analysis shows that the final standards scenario is estimated to
have the lowest net costs, followed by the alternative and reference scenarios, respectively. The
final standards case reflects the least costs because of the offsetting savings in fuel, repair and
maintenance.
Table 3-89 Total Technology, Operating and EVSE Social Cost Impacts of the Final Standards Relative to the
Reference Case, All Regulatory Classes and All Fuels, Millions of 2022 dollars*
Total
Calendar Year
Technology
Package Costs
Total Operating Costs
Total EVSE Costs
Sum
2027
$30
-$100
$440
$370
2028
-$14
-$220
$610
$380
2029
-$85
-$390
$730
$260
2030
$160
-$380
$630
$410
2031
$270
-$540
$1,300
$1,100
2032
$480
-$810
$2,000
$1,700
2033
$310
-$1,200
$1,900
$1,000
2034
$260
-$1,600
$1,700
$360
2035
$160
-$2,200
$1,600
-$450
2036
$23
-$2,500
$1,600
-$950
2037
-$25
-$3,000
$1,500
-$1,400
2038
-$140
-$3,300
$1,500
-$2,000
2039
-$230
-$3,700
$1,500
-$2,400
2040
-$260
-$4,100
$1,500
-$2,900
2041
-$330
-$4,300
$1,500
-$3,100
2042
-$400
-$4,600
$1,400
-$3,500
2043
-$390
-$5,100
$1,400
-$4,000
2044
-$450
-$5,400
$1,400
-$4,400
2045
-$510
-$5,100
$1,400
-$4,200
2046
-$490
-$4,900
$1,300
-$4,100
2047
-$530
-$5,400
$1,300
-$4,600
2048
-$560
-$5,800
$1,300
-$5,100
2049
-$590
-$6,300
$1,300
-$5,600
2050
-$570
-$6,600
$1,200
-$5,900
2051
-$590
-$6,800
$1,200
-$6,100
2052
-$620
-$7,000
$1,200
-$6,400
2053
-$640
-$7,100
$1,200
-$6,600
2054
-$610
-$7,300
$1,200
-$6,700
2055
-$590
-$7,400
$1,100
-$6,900
PV, 2%
-$4,200
-$76,000
$28,000
-$52,000
PV, 3%
-$3,200
-$63,000
$25,000
-$42,000
PV, 7%
-$1,000
-$32,000
$15,000
-$18,000
AV, 2%
-$190
-$3,500
$1,300
-$2,400
AV, 3%
-$170
-$3,300
$1,300
-$2,200
AV, 7%
-$83
-$2,600
$1,300
-$1,400
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in
expenditures.
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Table 3-90 Total Technology, Operating and EVSE Social Cost Impacts of the Alternative Option Relative to
the Reference Case, All Regulatory Classes and All Fuels, Millions of 2022 dollars*
Total
Calendar Year
Technology
Package Costs
Total Operating Costs
Total EVSE Costs
Sum
2027
$1.8
-$59
$250
$200
2028
-$32
-$120
$290
$130
2029
-$69
-$220
$410
$120
2030
$110
-$210
$360
$250
2031
$210
-$240
$480
$450
2032
$280
-$310
$620
$590
2033
$250
-$380
$490
$360
2034
$270
-$470
$380
$170
2035
$280
-$600
$260
-$66
2036
$240
-$630
$240
-$140
2037
$230
-$670
$220
-$220
2038
$210
-$710
$200
-$290
2039
$190
-$730
$180
-$350
2040
$190
-$760
$160
-$410
2041
$180
-$640
$140
-$310
2042
$160
-$670
$130
-$380
2043
$160
-$670
$130
-$380
2044
$140
-$670
$120
-$410
2045
$120
-$560
$120
-$320
2046
$110
-$520
$110
-$290
2047
$100
-$660
$110
-$460
2048
$87
-$800
$100
-$610
2049
$75
-$950
$99
-$780
2050
$76
-$1,000
$95
-$840
2051
$67
-$1,000
$92
-$880
2052
$58
-$1,100
$89
-$920
2053
$50
-$1,100
$86
-$960
2054
$54
-$1,100
$82
-$980
2055
$55
-$1,100
$79
-$1,000
PV, 2%
$3,000
-$13,000
$5,000
-$5,100
PV, 3%
$2,600
-$11,000
$4,600
-$3,800
PV, 7%
$1,700
-$6,100
$3,400
-$1,000
AV, 2%
$140
-$600
$230
-$230
AV, 3%
$140
-$580
$240
-$200
AV, 7%
$140
-$490
$270
-$83
* Values show 2 significant digits; negative values denote lower costs, i.e., savings in
expenditures.
558
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559
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Chapter 4 Emission Inventories
4.1 Introduction
This chapter presents our analysis of the national emissions impacts of the final standards and
the alternative (collectively referred to as control cases) relative to a baseline scenario that
represents the U.S. without the final rule (referred to as the reference case). We estimated
emission impacts for all calendar years from 2027 through 2055 from both downstream and
some upstream sources. Downstream emissions are those emitted directly by a vehicle, including
tailpipe and crankcase exhaust (from running, starts, or extended idle), evaporative emissions,
refueling emissions, and particulate emissions from brake wear and tire wear. Upstream
emissions are not emitted by the vehicle itself but can still be attributed to its operation.
Examples include emissions from electricity generation for charging battery electric vehicles
(BEVs), the creation of hydrogen fuel for fuel cell electric vehicles (FCEVs), the extracting and
refining of crude, and the transporting of crude or refined fuels for internal combustion engine
vehicles.
Our approach to modeling the emissions impacts of the final standards mirrors that of our
proposal with some methodological updates. First, we estimated onroad downstream national
inventories using an updated version of EPA's Motor Vehicle Emission Simulator (MOVES)
model. The version of MOVES used for the emissions inventory modeling, MOVES4.R3,1342
includes several updates from the latest widely available public version, MOVES4.0.0,1343 which
are discussed in Chapter 4.2. Second, we developed an updated reference case as described in
Chapter 4.2.2. Third, we performed new power sector modeling runs to evaluate power sector
emission impacts as described in 4.2.4. Fourth, we updated our refinery emission impacts
methodology to better account for U.S. exports of gasoline and diesel, as described in 4.2.5.
In response to the proposal, several commenters noted that our reference case should
quantitatively reflect not only the anticipated ZEV sales from the ACT rule in California and
other states which have adopted it, but also ZEV adoption resulting from numerous other factors.
The commenters specifically suggested to include: 1) state policies such as California's
Advanced Clean Fleets1344'1345 and Innovative Clean Transit1346 rules and the NESCAUM MHD
ZEV MOU1347; 2) manufacturer, fleet, and government commitments for producing and
procuring ZEVs; 3) adoption for vehicles that reach cost parity with conventional vehicles; and
1342 Murray, Evan. Memorandum to Docket EPA-HQ-OAR-2022-0985. "MOVES4.R3". February 2024.
1343 U.S. EPA. (2023). Motor Vehicle Emission Simulator: MOVES4. Office of Transportation and Air Quality.
Available online: https://github.eom/USEPA/EPA_MOVES_Model/releases/tag/MOVES4.0.0
1344 California Air Resources Board. "Advanced Clean Fleets". Available online: https://ww2.arb.ca.gov/our-
work/programs/advanced-clean-fleets
1345 EPA received a waiver request under CAA section 209(b) and 209(e) from California for the ACF rule on
November 15, 2023 (see https://www.epa.gov/state-and-local-transportation/vehicle-emissions-california-waivers-
and-authorizations#current). EPA is currently reviewing the waiver request for the CA ACF rule. Because EPA
action on California's waiver request is pending, we did not include the full effects of ACF in the reference case.
1346 California Air Resources Board. "Innovative Clean Transit". Available online: https://ww2.arb.ca.gov/our-
work/programs/innovative-clean-transit
1347 NESCAUM MOU. "Multi-State Medium- and Heavy-Duty Zero Emission Vehicle Memorandum of
Understanding." March 29, 2022. Available online: https://www.nescaum.org/documents/mhdv-zev-mou-
20220329.pdf
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4) the billions of dollars of programs to support HD ZEV deployment in the BIL and the IRA.
We revised the reference case for this final rulemaking to include greater HD ZEV adoption than
in the NPRM reference case, as described and explained in Chapter 4.2.2.
We also received comment questioning how many ZEVs will be sold nationwide as a result of
ACT. Given the comments on variability in HD ZEV adoption projections absent the final
standards, and the corresponding potential uncertainty in the reference case this variability
implies, we also performed a sensitivity analysis using a reference case that has reduced HD
ZEV adoption. We present this sensitivity analysis in Chapter 4.10.
In the NPRM analysis, we used identical rates of brake and tire wear (non-exhaust) particulate
emissions for HD diesels and HD ZEVs. Some commenters requested that EPA model increased
non-exhaust for HD ZEVs, relative to comparable ICE vehicles, and argued specifically that HD
ZEVs should have increased tirewear emissions and therefore we should model higher non-
exhaust for HD ZEVs versus comparable ICE vehicles.
Based on engineering principles, it would be reasonable to expect HD ZEVs to have offsetting
trends in brakewear and tirewear emissions. On the one hand, ZEVs tend to be heavier than
comparable ICE vehicles and have greater torque at low speeds, both of which are expected to
increase tirewear emissions. On the other hand, ZEVs are often equipped with regenerative
braking systems. When a vehicle is using regenerative brakes, some of the kinetic energy from
slowing the vehicle is directed to the motor. In a friction braking system, this kinetic energy is
normally converted to heat, so there is less material wear and emissions from brakes.
However, both of these expectations are based on engineering principles and are highly
uncertain for several reasons. First, there is no data and little literature on the brakewear and
tirewear emission rates of HD ZEVs specifically. Studies on non-exhaust emissions, including all
of those cited by the commenters, focus on light-duty BEVs because those vehicles are greater in
number and adoption. Second, the relationship between vehicle weight, torque, and braking
systems on non-exhaust emission depends greatly on the vehicles engineering, especially on
vehicle components such as the electric motor, axle configurations, tires, and brake systems. This
important fact is recognized by all the literature sources cited by the commenters.
Given the uncertainty in projecting non-exhaust emissions from HD ZEVs, and the fact that
it's reasonable to project offsetting trends for brakewear and tirewear, we did not update our
modeling of HD ZEV brakewear and tirewear emissions for the final rule. We discuss this in
more detail in the Chapter 13 of the Response to Comments document. However, in response to
these comments, we present downstream PM2.5 emissions that include brakewear and tirewear
more explicitly throughout this chapter of the RIA.
We model emissions from electricity generation units (EGUs) that result from increased
energy demand from heavy-duty electric vehicles using the 2022 post-IRA version of the
Integrated Planning Model (IPM), which is a linear programming model that forecasts EGU
operation and emissions by calculating the most cost-effective way for the electricity generation
and transmission system to meet its total demand. IPM accounts for many variables that impact
the operation and emissions of EGUs, including total energy demand (including reserve
requirements and peak load demand), planned EGU retirements, finalized rules that impact EGU
operation, fuel prices, infrastructure buildout costs, and congressional action like the Inflation
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Reduction Act.1348 More details on IPM and the specific version used in this analysis can be
found online1349 and in the docket.1350
We received several comments on our EGU emissions modeling using IPM, specifically as it
relates to modeling upstream emissions of FCEVs. In the NPRM, we assumed all hydrogen used
for FCEVs would be produced via electrolysis of water using electricity from the grid and could
therefore be entirely represented as additional demand to EGUs and modeled using IPM. We
received several comments on our EGU emissions modeling using IPM, specifically as it relates
to modeling upstream emissions of FCEVs. Many commenters noted that hydrogen in the U.S.
today is primarily produced via steam methane reforming (SMR), for which there are associated
pollutant emissions, and asserted that an analysis of upstream FCEV emissions which does not
consider this fact would be incomplete. We maintain our approach from the NPRM for the final
rulemaking analysis, as is discussed in Chapter 4.2.4.2.
In the final rule analysis, to address these comments we performed a comparative analysis that
looks at the relative difference in emissions from various hydrogen fuel production pathways,
including SMR. We compare emissions from these additional hydrogen production pathways to
electrolysis to provide relative context for how emissions would differ under different scenarios
in addition to the potential compliance pathway modeled for the final standards. This
comparative analysis is discussed in detail in Chapter 4.8.
We modeled emissions from refineries by adjusting an existing refinery inventory to account
for reduced domestic fuel demand driven by HD ZEV adoption under the potential compliance
pathway in response to the final standards. The refinery inventory adjustments were developed
using MOVES projections of liquid fuel demand for both the reference case and control cases.
In the NPRM analysis we assumed that 93 percent of the drop in domestic demand would be
reflected in reduced refinery activity. We received several comments noting that, in response to
lower domestic demand, U.S. refineries would increase exports and continue refining similar
volumes of liquid fuels. After consideration of these comments, for the final rule, we projected
that 50 percent of the drop in domestic demand would be reflected in reduced refinery activity.
This is described in more detail in Chapter 4.2.5.
We received several comments on the scope of upstream emissions to be considered and
estimated by EPA. We updated the modeling for the final rule to include the three most
significant sectors in terms of understanding the impact of the standards on overall emissions
(downstream, EGUs and refineries) in more detail than the proposal. We did not estimate
impacts on emissions from other sectors with comparatively smaller potential impacts, like those
1348 The IRA contains a number of tax credit provisions that affect power sector operations. The 2022 post-IRA
version of IPM models the following IRA provisions: the Clean Electricity Investment and Production Tax Credits
(sections 13702 and 13701), the credit for Carbon Capture and Sequestration (section 13104), the Zero-Emission
Nuclear Power Production Credit (section 13105), the Credit for the Production of Clean Hydrogen (section 13204),
and the Advanced Manufacturing Production Tax Credit (section 13502). Thus, these IRA provisions are
quantitatively reflected in our upstream modeling.
1349 U.S. EPA. "Post-IRA 2022 Reference Case". Power Sector Modeling. April 5, 2023. Available online:
https://www.epa.gov/power-sector-modeling/post-ira-2022-reference-case
1350 U.S. EPA. "Documentation for EPA's Power Sector Modeling Platform v6 Using the Integrated Planning Model
Post-IRA 2022 Reference Case". March 2023. Available online:
https://www.epa.gov/system/files/documents/2023-03/EPA%20Platform%20v6%20Post-
IRA%202022%20Reference%20Case.pdf
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related to the extraction or transportation of fuels for either EGUs or refineries or the emissions
from infrastructure buildout that may be necessary to support the level of HD ZEV adoption we
model in the potential compliance pathway for the final standards. Detailed discussion of the
comments we received on upstream modeling and our responses can be found in Chapter 13 of
the RTC.
The downstream emission inventories were developed using a single national modeling
domain (which includes the 50 U.S. states and the District of Columbia, but not any U.S.
territories), referred to as national or default scale in MOVES. Our upstream emissions modeling
also uses a single national modeling domain, so our estimated emissions impacts cover the full
national inventory. Emissions impacts in other domains, such as particular regions or localities in
the United States, are likely to differ from the impacts presented in this chapter. These impacts
are discussed for the final standards in Chapters 4.3 (downstream emissions), 4.4 (upstream
emissions), 4.5 (net emissions impacts), and 4.6 (cumulative GHG emissions impacts). Chapter
4.7 compares emission inventory impacts of the final standards and the alternative.
This chapter includes several sensitivity analyses and appendices. Chapter 4.8 presents our
analysis of the upstream emissions impact of different hydrogen production pathways and
Chapter 4.9 presents our analysis of refinery emissions impacts should refineries change exports
in different ways than our main case analysis. To better understand and explain the differences in
emission impact estimates between the NPRM and FRM, Chapter 4.10 presents a sensitivity
analysis for a reference case which resembles the one we used in the NPRM and Chapter 4.11
directly compares the proposed and final standards based on our updated FRM modeling tools
and methodologies.
Finally, Appendix B to this RIA contains detailed discussion of HD ZEV adoption rates and
tables showing the ZEV adoption rates we model in MOVES for the reference and control cases.
4.2 Model Data and Methodologies
To quantify the emissions impacts of the final standards and the alternative, EPA developed
an updated version of MOVES, called MOVES4.R3. Detailed descriptions of the underlying data
and algorithms in MOVES are documented in technical reports that can be found online1351 and
in the docket.1352 MOVES4.R3 and its supporting databases can also be found in the docket.1342
Specific updates made to MOVES4.R3, relative to MOVES4.0.0, can be found in Chapter 4.2.1.
We used MOVES4.R3 to estimate the downstream emission impacts of the final standards
and the alternative. First, we estimated emissions for the reference scenario that represents the
U.S. without the final rule. Then we estimated emissions for the final standards (using the
potential compliance pathway we modeled to support the feasibility of those standards) and
separately estimated emissions for the alternative (collectively referred to as control cases). We
calculated the emission reductions of both GHGs and non-GHGs for the control cases as the
emission inventory difference between those cases and the reference case. All model inputs,
1351 U.S. EPA. "MOVES Onroad Technical Reports: MOVES4". MOVES Onroad Technical Reports. August 2023.
1352 Murray, Evan. Memorandum to Docket EPA-HQ-OAR-2022-0985. "MOVES4.0.0 Technical Reports".
February 2024.
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MOVES ran specification (runspec) files, scripts used for the analysis, and the version of
MOVES used to generate the emissions inventories, are found in the docket.1353
The reference and control cases were run entirely using MOVES4.R3 default data except for
HD ZEV populations. The reference case was run using the HD ZEV populations described in
Chapter 4.2.2 and the control cases were run using the HD ZEV populations described in
Chapter 4.2.3. Each heavy-duty ZEV sale added in both the reference and control cases beyond
what is in the MOVES4.R3 default data is assumed to displace the sale of a comparable ICE
vehicle, and we assume that no ICE fuel type (gasoline, diesel, or CNG) is more likely to be
displaced than any other. All other activity inputs, including total VMT by source type, age
distributions, road type distributions, vehicle speeds, off-network idling, hotelling, and starts
were kept the same between the reference and the control cases. Emission rates and adjustments
were kept the same as well, including energy consumption rates for all vehicle types. Finally,
geographic fuels inputs were kept the same for the reference and control cases.
We used IPM to estimate the EGU emission impacts of the control cases. In the final rule
analysis, we improved the estimates of EGU emissions by accounting for the IRA. It is worth
noting that the ZEV adoption rates in the IPM runs are not identical to the ZEV adoption rates
and energy demand for the reference and control cases described in Chapters 4.2.2 and 4.2.3.
Chapter 4.2.4 contains detailed discussion of how we generated IPM inputs from MOVES and
how we accounted for differences between IPM scenarios we modeled and the final control cases
for this rulemaking.
Refineries are another upstream emissions source that we expect will be impacted by
increased adoption of HD ZEVs. We developed a methodology to estimate the impact the final
standards will have on emissions from refineries based on an existing refinery inventory from the
emissions modeling platform,1354'1355 projections of refining activity from the Energy
Information Administration's (EIA) Annual Energy Outlook 2023 (AEO20 23),1356 and the fuel
consumption output from the MOVES runs for each scenario. Chapter 4.2.5 contains a detailed
discussion of the methodology we used to estimate the change in refinery emissions, including
discussion of scenarios we explored regarding how U.S. refineries may change their exports in
response to lower domestic demand.
4.2.1 Updates to MOVES4.R3
MOVES defines vehicles using a combination of source type and regulatory class, where
source type roughly defines a vehicle's vocation or usage pattern, and regulatory class defines a
vehicle's gross vehicle weight rating (GVWR) or weight class. Table 4-1 defines MOVES source
types and Table 4-2 defines MOVES regulatory classes. In relation to the final standards, we
1353 Murray, Evan. Memorandum to Docket EPA-HQ-OAR-2022-0985. "MOVES Inputs and Post-Processing
Materials: HD GHG Phase 3 FRM Modeling". March 2024.
1354 The emissions modeling platform is a product of the National Emissions Inventory Collaborative consistent of
more than 245 employees of state and regional air agencies, EPA, and Federal Land Management agencies. It
includes a full suite of base year (2016) and projection year (2023 and 2028) emission inventories modeled using
EPA's full suite of emissions modeling tools, including MOVES, SMOKE, and CMAQ.
1355 U.S. EPA. "2016v3 Platform". September 22, 2023. Available online: https://www.epa.gov/air-emissions-
mode ling/2016v3 -platform.
1356 U.S. Energy Information Administration (EIA). "Annual Energy Outlook 2023". U.S. Department of Energy.
March 16, 2023. Available online: https://www.eia.gov/outlooks/aeo/
564
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synonymize combination short-haul tractors (MOVES source type 61) with day cabs and
combination long-haul tractors (MOVES source type 62) with sleeper cabs.
Table 4-1 MOVES source type definitions
sourceTypelD
Source Type Description
11
Motorcycle
21
Passenger Car
31
Passenger Truck
32
Light Commercial Truck
41
Other Bus
42
Transit Bus
43
School Bus
51
Refuse Truck
52
Single Unit Short-haul Truck
53
Single Unit Long-haul Truck
54
Motor Home
61
Combination Short-haul Truck
62
Combination Long-haul Truck
Table 4-2 MOVES regulatory class definitions
regClassID
Regulatory Class Name
Regulatory Class Description and GVWR Range
10
MC
Motorcycle
20
LDV
Light Duty Vehicles
30
LDT
Light Duty Trucks
41
LHD2B3
Chassis-certified Class 2b and 3 Trucks
8,500 lbs < GVWR < 14,000 lbs
42
LHD45
Class 4 and 5 Trucks and engine-certified Class 3 Trucks
14,000 lbs < GVWR < 19,500 lbs
46
MHD67
Class 6 and 7 Trucks
19,500 lbs < GVWR < 33,000 lbs
47
HHD8
Class 8a and 8b Trucks
GVWR >33,000 lbs
48
Urban Bus
Urban Bus (see 40 CFR 86.091-2)1357
49
Gliders
Glider Vehicles (see EPA-420-F-15-904)1358
MOVES4.R3 does not contain any major algorithmic changes or updates compared to
MOVES4.0.0, making the models similar in terms of modeling capabilities and outputs.
However, MOVES4.R3 includes a few data updates to better model the reference and control
cases for this rulemaking.
MOVES4.R3 contains updated energy consumption rates for HD BEVs. MOVES calculates
HD BEV energy consumption using the Energy Efficiency Ratio (EER) of a BEV to a diesel
vehicle so that the energy consumption of a HD BEV can be calculated using diesel energy
1357 CFRpart 86.091-2. Available online: https://www.govinfo.gov/content/pkg/CFR-1998-title40-voll2/pdf/CFR-
1998-title40-voll2-sec86-091-2.pdf
1358 U.S. EPA. "Frequently Asked Questions about Heavy-Duty 'Glider Vehicles' and 'Glider Kits'. July 2015.
Available online: https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100MUVI.PDF
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consumption rates, as shown in Equation 4-1. The EER for a BEV is generally greater than 1,
indicating that BEVs are more energy efficient than their diesel counterparts.
Equation 4-1 Calculation of HD BEV energy consumption rates using Energy Efficiency Ratio (EER)
Energydiesei
EnergyBEV =
EER
MOVES4.R3 contains updated EERs based on our technology assessment in HD TRUCS1359
that was discussed in Chapter 2. MOVES4.R3's updated EERs are specified by source type and
regulatory class (Table 4-3), as opposed to being specific only by source type in the NPRM.
EERs are only included for valid source type and regulatory class combinations in MOVES.
Table 4-3 MOVES4.R3 Energy Efficiency Ratios for HD BEVs
Source Type
LHD45
regClassID 42
MHD67
regClassID 46
HHD8
regClassID 47
Urban Bus
regClassID 48
Other Buses
sourceTypelD 41
4.24
3.85
2.71
Transit Buses
sourceTypelD 42
3.60
3.64
3.67
3.67
School Buses
sourceTypelD 43
3.91
4.06
3.16
Refuse Trucks
sourceTypelD 51
3.85
3.85
3.71
Single Unit Short-Haul Trucks
sourceTypelD 52
3.80
3.46
3.03
Single Unit Long-Haul Trucks
sourceTypelD 53
3.49
2.93
2.40
Motor Homes
sourceTypelD 54
3.35
3.09
3.06
Combination Short-Haul Trucks
sourceTypelD 61
2.26
2.18
Combination Long-Haul Trucks
sourceTypelD 62
2.02
2.02
Under this approach, even though the EERs stay constant for all model years, HD BEVs will
see a similar level of increase in efficiency as their diesel counterparts from EPA's HD GHG
Phase 2 rule, as well as associated aerodynamic improvements that we believe will apply to all
engine technologies.
In addition, MOVES4.R3 contains an updated scaling factor used to calculate FCEV energy
consumption from BEV energy consumption. This scaling factor incorporates all operational
differences between the two vehicle types, including differences in energy conversion efficiency
and other MOVES effects such as temperature and charging efficiency adjustments for BEVs.
The FCEV:BEV scaling factor in MOVES4.R3 was updated to be 1.21 based on our technology
assessment in HD TRUCS.
1359 Heavy-Duty Technology Resource Use Case Scenario (HD TRUCS) is EPA's technology assessment tool for
developing technology packages for the final standards. See RIA Chapter 2.
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Overall, both the HD BEV EER update and the FCEV:BEV scaling factor update increase the
overall energy efficiency of HD ZEVs of most vehicle types in MOVES4.R3 when compared to
the proposal and MOVES4.0.0.
Lastly, MOVES4.R3 contains an update to energy consumption and CO2 emission rates for
light- and medium-duty ICE vehicles (regulatory classes 20, 30, and 41) to make it consistent
with EPA's Optimization Model for reducing Emissions of Greenhouse Gases from Automobiles
(OMEGA)1360 modeling of previously finalized light-duty GHG rules.1361 Overall, this decreases
light- and medium-duty ICE energy demand and GHG emissions in both reference and control
scenarios compared to MOVES4.0.0.
4.2.2 MOVES Inputs for the Reference Case
In modeling heavy-duty ZEV populations in the reference case, a scenario that represents the
United States without the final standards, we considered several different factors related to
purchaser acceptance of new technologies as discussed in RIA Chapter 2, along with three
factors described below and in RIA Chapter 1. We also considered comments received from a
variety of stakeholders.
First, the market has evolved such that early HD ZEV models are in use today for some
applications and HD ZEVs are expected to expand to many more applications, as discussed in
RIA Chapters 1.1, 1.5, and 1.7. Additionally, manufacturers have announced plans to rapidly
increase their investments in ZEV technologies over the next decade. Second, the IRA and the
BIL provide many monetary incentives for the production and purchase of ZEVs in the heavy-
duty market, as well as incentives for electric vehicle charging infrastructure. Third, there have
been actions by states to accelerate the adoption of heavy-duty ZEVs.
Absent the final standards, the State of California's Advanced Clean Trucks (ACT) program
imposes minimum ZEV sales requirements beginning in model year 2024 in California and
states that have adopted the program under CAA section 177. EPA granted the waiver of
preemption for California's ACT rule waiver under CAA section 209(b) on March 30, 2023.1362
As of the time of our inventory analysis, ACT had been adopted by seven other states under
CAA section 177.1363 Because ACT is an existing final rule that is enforceable in several states,
it is one of our primary sources for determining the reference case ZEV adoption rates.
To calculate national ZEV adoption in the reference case, we developed HD ZEV adoption
rates at the state level by splitting states into two groups. California and the seven states that have
finalized adoption of ACT as of the time of our inventory analysis are referred to as ACT states,
1360 U.S. EPA. "Optimization Model for reducing Emissions of Greenhouse Gases from Automobiles (OMEGA)."
Office of Transportation and Air Quality. Available online: https://www.epa.gov/regulations-emissions-vehicles-
and-engines/optimization-model-reducing-emissions-greenhouse-gases#omega-2.1.0
1361 79 FR 23414 and 86 FR 74434.
1362 gg pr 20688. April 6, 2023. Available online: https://www.govinfo.gOv/content/pkg/FR-2023-04-06/pdf/2023-
07184.pdf
1363 At the time we performed the inventory modeling analysis, seven states had adopted ACT in addition to
California. Oregon, Washington, New York, New Jersey, and Massachusetts adopted ACT beginning in MY 2025
while Vermont adopted ACT beginning in MY 2026 and Colorado in MY 2027. Three other states, New Mexico,
Maryland, and Rhode Island adopted ACT (beginning in MY 2027) in November and December of 2023, but there
was not sufficient time for us to incorporate them as ACT states in our modeling.
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and the remaining 42 states are referred to as non-ACT states.1364 We created separate reference
case scenarios for ACT and non-ACT states, and the resulting national adoption rates are the
average of the two weighted by the portion of the heavy-duty vehicle sales1365 they represent.
The adoption rates for ACT states are based on the ZEV adoption volumes required by the
ACT rule, which are presented in Table 4-4.
Table 4-4 HD ZEV adoption rates in California's ACT rule
Model Year
Class 4-8 Vocational Vehicle Group3
Class 7-8 Tractors Group
Source Types 41-54
Source Types 61,62
2024
9%
5%
2025
11%
7%
2026
13%
10%
2027
20%
15%
2028
30%
20%
2029
40%
25%
2030
50%
30%
2031
55%
35%
2032
60%
40%
2033
65%
40%
2034
70%
40%
2035 and beyond
75%
40%
a The ACT program includes ZEV adoption rates for a Class 2b-3 Vocational Vehicle Group, which we also
included in our reference case modeling. However, we did not model the final standards as increasing ZEV
adoption in this vehicle group, so they are not presented here. Class 2b-3 Vocational Vehicle Group ZEV adoption
rates can be found in Appendix B to this RIA.
The adoption rates presented in Table 4-4 refer only to ACT's vehicle groupings which are
less detailed than both MOVES vehicle types and the EPA regulatory categories and
subcategories for HD vehicles. The ACT rule groups all Class 4-8 vocational vehicles together
and all tractors together. Manufacturers must comply with the rule by ensuring that all deficits
generated within the groups are offset by credits. For example, a manufacturer's fleet of Class 4-
8 vocational vehicles could comply either by meeting the ZEV sales percentage requirement for
the model year for all vehicle types within that group, or by generating credits from selling more
ZEVs than required for some vehicles (e.g., Class 4 step vans) and using those credits to sell
fewer ZEVs than required for others (e.g., Class 8 box trucks). In order to reflect this flexibility
and some of the nuances of ZEV suitability for different vehicle types, we apportioned HD ZEV
adoption by vehicle type in both ACT and non-ACT states in consideration of our technology
assessment described in preamble Section II and RIA Chapter 2.
1364 In this analysis, the states that adopted ACT via CAA section 177 are treated as non-ACT states until the model
year in which ACT becomes effective. For example, Colorado is considered a non-ACT state for MYs prior to 2027,
but an ACT state thereafter. New Mexico, Maryland, and Rhode Island are never treated as ACT states because they
adopted ACT after most of our modeling was already complete.
1365 We based the proportion of national HD by state on vehicle registration data in IHS2020, a source of vehicle
registration data by county from IHS Markit. We used MY 2020 registrations because it was the most recent MY
data available. However, the MY 2020 data set encompassed a partial year of registrations, so we also included MY
2019 registrations which cover the full year.
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Our technology assessment shows that ZEV adoption is more likely for lighter vocational
vehicles than for heavier ones. This consideration was factored into the ACT rule using weight
class modifiers, which specify that Class 6-7 (MHD) vocational vehicles earn 1.5 times as many
credits and deficits as Class 4-5 (LHD) vocational vehicles, and Class 8 (HHD) vocational
vehicles earn two times as many credits and deficits as Class 4-5 (LHD) vocational vehicles.1366
These ratios of 2 Class 4-5 to 1.5 Class 6-7 to 1 Class 8 are similar to our projected adoption
rates of LHD, MHD, and HHD vocational ZEVs demonstrated in HD TRUCS for MYs 2027 and
2032 in the technology packages developed as a potential compliance pathway for the final rule,
as discussed in preamble Section II and RIA Chapter 2. To apportion ZEV adoption for
vocational vehicles by weight class, we assumed that the ZEV adoption rate for LHD vocational
vehicles is double the adoption rate for HHD vocational vehicles and the adoption rate for MHD
vocational vehicles is 1.5 times the adoption rate of HHD vocational vehicles. We used this
assumption to calculate adoption rates of an ACT-compliant fleet of vocational vehicles in ACT
states in every MY.
Similarly, our technology assessment suggests that ZEV adoption is more likely for day cab
tractors than for sleeper cab tractors. We calculated an ACT-compliant fleet of tractors in ACT
states by assuming that sleeper cab tractors achieve the ZEV adoption rates shown in our NPRM
technology package, including a phase-in of 2 percent, 4 percent, and 7 percent ZEV adoption in
MYs 2027, 2028, and 2029, respectively. We then calculated how many day cab tractor ZEVs
would be needed for the tractors to comply as a group.
MOVES requires ZEV adoption rates to be specified by source type and regulatory class. For
the purposes of incorporating our projected ACT-compliant adoption rates into MOVES, we
calculated vocational vehicle adoption rates by regulatory class and applied the same adoption
rate for all source types. We calculated tractor adoption rates by source type and applied the
same adoption rate for all regulatory classes.
The ZEV adoption rates for ACT states are shown in Table 4-5. In general, we modeled all
ZEV adoption as BEVs except for some HHD vocational vehicles, short-haul tractors, and long-
haul tractors, which we modeled as FCEVs because they travel long distances and/or have heavy
loads as discussed in RIA Chapter 2. As discussed in RIA Chapter 1.8, we considered FCEVs
only in the MY 2030 and later timeframe to better ensure that we have provided adequate time
for early-market hydrogen-infrastructure development. More details on the specific adoption
rates used for constructing the reference case, by technology, regulatory class, and source type,
can be found in Appendix B to this RIA.
1366 All Class 4-8 vocational vehicles are grouped together to determine compliance with the ACT rule, so the result
of the credits is that four sales of LHD vocational ZEVs or three sales of MHD vocational ZEVs could offset the
sale two HHD vocational ZEVs.
569
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Table 4-5 Reference case ZEV adoption rate for ACT states
Model Year
LHD
Mill)
HHP
Short-Haul
Long-Haul
Vocational
Vocational
Vocational
Tractors
Tractors
2024
11.6%
8.7%
5.8%
7.5%
0.0%
2025
14.1%
10.6%
7.1%
10.5%
0.0%
2026
16.7%
12.5%
8.3%
14.9%
0.0%
2027
25.6%
19.2%
12.8%
21.4%
2.0%
2028
38.5%
28.9%
19.2%
27.9%
4.0%
2029
51.2%
38.4%
25.6%
33.9%
7.0%
2030
63.7%
47.8%
31.8%
39.8%
10.0%
2031
69.8%
52.4%
34.9%
42.4%
20.0%
2032
76.1%
57.1%
38.0%
47.4%
25.0%
2033
82.4%
61.8%
41.2%
47.4%
25.0%
2034
88.6%
66.5%
44.3%
47.4%
25.0%
2035 andbeyondA
94.8%
71.1%
47.4%
47.4%
25.0%
A Adoption rates in the vehicle categories shown can vary from model year to model year despite the overall level
of ZEV adoption driven by emission standards remaining unchanged. This is because MOVES projects variations
in vehicle sales by source type and regulatory class across model years. This can lead to small variations in
adoption rates, within a few percent, over time as sales of some vehicle types increase and others decrease.
In developing the ZEV adoption rates for non-ACT states in the reference case, we used
CALSTART's "Zeroing In On Zero-Emission Trucks, May 2023 Market Update" report that
summarizes historical ZEV deployment for medium- and heavy-duty vehicles1367 in all 50 states.
It is the only data source we found that provides a quantitative, state-by-state assessment of HD
ZEV adoption and therefore is the best source we can use to estimate future HD ZEV adoption at
the state level.1368 This allows us to compare ZEV adoption in non-ACT states relative to ACT
states to calculate a sales ratio, which we then use to project ZEV adoption rates absent the final
standards. Specifically, we calculate that for model years 2017-2022, non-ACT states have
adopted 39.4 percent of medium- and heavy-duty ZEVs and ACT states have adopted 60.6
percent of medium- and heavy-duty ZEVs.1369 Furthermore, 22.8 percent of medium- and heavy-
duty vehicles were registered in ACT states in 2022 and 77.2 percent were registered in non-
ACT states.1370 Combining these, we calculate a sales ratio of 0.192, which we multiply by the
ACT ZEV adoption rate in the near term to project non-ACT ZEV adoption rates.
The geographic discrepancy in ZEV deployment and truck registrations likely stems from
ZEV-supportive policies in ACT states (even prior to implementation of ACT in MY 2024), such
as California's Hybrid and Zero-Emission Truck and Bus Voucher Incentive Project (HVIP),1371
which help to facilitate early deployments of ZEV technologies. Thus, we expect the ZEV sales
1367 CALSTART's report provides data on Class 2b-8 vehicles. The data from this report used to develop ZEV
adoption rates for non-ACT states includes all Class 2b-8 vehicles in aggregate. While this rulemaking covers Class
4-8 vehicles and incomplete Class 2b-3 vehicles, which comprise a small share of all Class 2b-3 vehicles, the
report's data was the most comprehensive data we could find to project ZEV adoption rates occurring independently
of the final rule.
1368 CALSTART. "Zeroing In On: ZETs May 2023 Market Update". May 2023. Available online:
https://calstart.org/zio-zets-may-2023-market-update/
1369 Based on Figure 1 of CALSTART's report.
1370 Based on Figure 4 of CALSTART's report.
1371 California Air Resources Board. Hybrid and Zero-Emission Truck and Bus Voucher Incentive Project (HVIP).
Available online: https://californiahvip.org/
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ratio between ACT and non-ACT states to stay constant through the 2020s and into the 2030s.
As described in RIA Chapter 1 and 2, in recent years, at the federal level, the IRA and the BIL
have been providing many incentives for deploying medium- and heavy-duty ZEVs and
supporting infrastructure, and these incentives generally end by 2032. Beyond then, we expect
that the IRA and the BIL will have helped to spur nationwide deployment of ZEVs and
supporting infrastructure such that the ZEV adoption rate in non-ACT states trends towards
parity with the ZEV adoption rate in ACT states. Additionally, CALSTART's May 2023 Market
Update report notes that 44 percent of medium- and heavy-duty ZEV deployments in 2022 were
in ACT states and 56 percent were in non-ACT states.1372 In comparison with the cumulative
2017-2022 deployment proportions, noted above as 60.6 percent in ACT states and 39.4 percent
in non-ACT states, this suggests the proportion of ZEVs sold in non-ACT states, relative to ACT
states, may increase over time. This further supports the notion that the ZEV adoption rate in
non-ACT states will trend towards parity with ACT states, which would eventually result in a
sales ratio of 1.0.
We model the sales ratio in non-ACT states as a constant value of 0.192 through MY 2032,
then linearly increase it from 0.2 to 0.42 from MY 2033 until MY 2055. Through stakeholder
outreach with the trucking community—including manufacturers, dealers, and fleets—and
through our own analyses, we understand tractors and heavy heavy-duty vocational vehicles to
be more challenging applications for ZEV technology than other vocational vehicles, so we
model the sales ratio for those segments as half of the rest of the market. Thus, the sales ratio for
tractors and Class 8 vocational vehicles is 0.096 through MY 2032 and reaches 0.21 in MY
2055. The sales ratios are summarized in Table 4-6 below.
Table 4-6 Sales ratios for projecting reference case ZEV adoption in non-ACT States
Model YcarA
LHD, Mill)
Vocational Vehicles
HHD Vocational, Short-Haul
Tractors, Long-Haul Tractors
2027-2032
0.192
0.096
2033
0.200
0.100
2034
0.210
0.105
2035
0.220
0.110
2055
0.420
0.210
A The sales ratios for model years 2036 through 2054 increase linearly between
the ratios in model years 2035 and 2055.
Table 4-7 shows the reference case ZEV adoption rate for non-ACT states for model years
2024 through 2035. These adoption rates are calculated by multiplying the adoption rates in
Table 4-5 by the sales ratios in Table 4-6. Adoption rates increase linearly from MY 2035
1372 As explained in the report, Colorado was not included as an ACT state in the report because it describes the
market through 2022 and Colorado adopted the ACT rule in April 2023. We do include Colorado as an ACT state.
The report does not provide sufficient data to re-calculate 2022 ZEV deployments in ACT states to include
Colorado. However, given that Colorado accounts for 1.7 percent of cumulative 2017-2022 ZEV deployments
across the U.S., the 2022 ratio of 44 percent ZEV deployments in ACT states and 56 percent in non-ACT states is
not likely to be significantly different when including Colorado as an ACT state. New Mexico, Maryland, and
Rhode Island are not included as ACT states in the report or our modeling because they adopted ACT after most of
our modeling was complete.
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through MY 2055. Appendix B to this RIA contains the breakdown of non-ACT ZEV adoption
rates in the reference case by model year, source type, regulatory class, and ZEV technology.
Table 4-7 Reference case ZEV adoption rate for non-ACT states
Model YcarA
LHD
Vocational
Mill)
Vocational
HHP
Vocational
Short-Haul
Tractors
Long-Haul
Tractors
2024
2.2%
1.7%
0.6%
0.7%
0.0%
2025
2.7%
2.0%
0.7%
1.0%
0.0%
2026
3.2%
2.4%
0.8%
1.4%
0.0%
2027
4.9%
3.7%
1.2%
2.1%
0.2%
2028
7.4%
5.5%
1.8%
2.7%
0.4%
2029
9.8%
7.4%
2.5%
3.3%
0.7%
2030
12.2%
9.2%
3.1%
3.8%
1.0%
2031
13.4%
10.1%
3.4%
4.1%
1.9%
2032
14.6%
11.0%
3.7%
4.6%
2.4%
2033
16.5%
12.4%
4.1%
4.7%
2.5%
2034
18.6%
14.0%
4.7%
5.0%
2.6%
2035
20.9%
15.6%
5.2%
5.2%
2.7%
2055
38.6%
29.0%
9.7%
9.9%
5.3%
A The ZEV adoption rates for model years 2036 through 2054 increase linearly between
the adoption rates in model years 2035 and 2055. Appendix B to this RIA presents the
adoption rates for each model year from 2024 through 2055.
Finally, the national reference case HD ZEV adoption rates, based on a sales-weighting of
state-specific adoption rates, are presented in Table 4-8. Appendix B to this RIA contains a
breakdown of the national ZEV adoption rates in the reference case by model year, source type,
regulatory class, and ZEV technology.
Table 4-8 National heavy-duty ZEV adoption in the reference case
Model Ycarx
LHD
Mill)
HHP
Short-Haul
Long-Haul
Vocational
Vocational
Vocational
Tractors
Tractors
2024
3.2%
2.2%
1.1%
1.0%
0.0%
2025
5.4%
3.7%
2.4%
2.2%
0.0%
2026
6.4%
4.4%
2.8%
3.2%
0.0%
2027
10.1%
6.9%
4.6%
4.7%
0.4%
2028
15.2%
10.4%
6.9%
6.1%
0.7%
2029
20.2%
13.8%
9.2%
7.4%
1.3%
2030
25.2%
17.2%
11.4%
8.7%
1.9%
2031
27.6%
18.9%
12.5%
9.3%
3.7%
2032
30.1%
20.5%
13.6%
10.4%
4.7%
2033
33.1%
22.6%
14.9%
10.5%
4.8%
2034
36.2%
24.9%
16.2%
10.8%
4.9%
2035
39.5%
27.2%
17.5%
11.0%
5.0%
2055
52.0%
37.3%
20.3%
15.1%
7.2%
A The ZEV adoption rates for model years 2036 through 2054 increase linearly between
the adoption rates in model years 2035 and 2055. Appendix B to this RIA presents the
adoption rates for each model year from 2024 through 2055.
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Our reference case methodology has sources of uncertainty. While our methodology is based
on the best HD ZEV deployment data we can find, there is still little data on current HD ZEV
deployment, which makes projecting to 2032 and beyond challenging. For example, the
CALSTART report notes several thousand ZEVs whose deployment they could not locate
between ACT or non-ACT states, which introduces uncertainty into the calculated sales ratio for
non-ACT states. In light of this uncertainty, we performed a sensitivity analysis in which we
analyzed the final standards against a different reference case in Chapter 4.10.
4.2.3 MOVES Inputs for the Final Standards and the Alternative
In modeling the control cases for the final standards and the alternative, we analyze the
impact of the final CO2 emission standards on a heavy-duty fleet that is projected in our potential
compliance pathway to include both ICE vehicles and an increase in ZEV adoption. In our
modeling, we project that the final emission standards are achieved through increased adoption
of HD vehicle and engine technologies to reduce GHG emissions. Examples of these GHG-
reducing technologies that manufacturers may choose to adopt include ICE vehicle technologies,
heavy-duty battery electric vehicle (BEV) technologies and fuel cell vehicle (FCEV)
technologies. We projected the emission reductions from the modeled potential compliance
pathway's technology packages described in preamble section II and RIA Chapter 2.10. As we
note there, manufacturers may elect to comply using a different combination of HD vehicle and
engine technologies than we modeled. In fact, we developed additional example potential
compliance pathways that meet the final Phase 3 MY 2027 through MY 2032 and later CO2
emission standards (see Chapter 2.11). These pathways would achieve the same level of vehicle
CO2 emission reductions and downstream CO2 emission reductions discussed later in this RIA
chapter.
Our modeling of the ICE vehicle portions of the technology packages reflect CO2 emission
improvements projected in previously promulgated standards, notably HD GHG Phase 2; thus,
we do not model an increase in ICE vehicle efficiency resulting from the final standards. Future
HD ZEV populations in MOVES at the national level for the final standards and alternative were
informed by HD TRUCS based on the technology assessment for BEVs and FCEVs discussed in
preamble Sections II and IX and RIA Chapter 2. We aggregated HD TRUCS' 101-Vehicle-ID
level national ZEV adoption rates by MOVES source type and regulatory class combination with
a sales-weighted average of Vehicle IDs in each combination for MYs 2027 and 2032, with ZEV
adoption rates for MYs 2028-2031 phased-in similarly to the final and alternative standards. For
model years after 2032, ZEV adoption for each source type and regulatory class combination
was held constant at the MY 2032 level.
We then added two constraints to ZEV adoption: a) in no combination of MY, source type,
regulatory class, and location (i.e., ACT state or non-ACT state) would ZEV adoption in either
control case (i.e., final standards or the alternative) be lower than in the reference case, and b)
HD ZEV sales would first meet the requirements of the ACT rule in California and the states
which have adopted the ACT rule under CAA section 177, and then sales would increase further
in all other states in order to meet our projections of national ZEV adoption reflected in our
modeled potential compliance pathway (described in preamble Section II and RIA Chapter 2).
Table 4-9 and Table 4-10 show the ZEV adoption rates used in modeling the final and
alternative standards, respectively, in MOVES from 2027 through 2032. Further discussion of
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the ZEV adoption rates by technology, model year, source type, regulatory class, and location
can be found in Appendix B to this RIA.
Table 4-9 National heavy-duty ZEV adoption in the control case for the final standards
Model Year
LHD
Vocational
Mill)
Vocational
HHD
Vocational"
Short-Haul
Tractors
Long-Haul
Tractorsb
2027
18.4%
13.5%
4.6%
5.3%
0.4%
2028
23.6%
16.7%
9.4%
8.4%
0.7%
2029
28.8%
20.0%
11.9%
11.9%
1.3%
2030
34.0%
23.2%
14.5%
16.3%
6.2%
2031
47.5%
32.0%
20.1%
27.7%
12.5%
2032
61.2%
40.7%
25.7%
39.9%
25.0%
aFor HHD vocational vehicles, we are not finalizing revisions to MY 2027 standards. ZEV adoption for these
vehicles in this model year was set to be equal to the reference case.
b For sleeper cab tractors, which are represented by long-haul tractors (source type 62) in MOVES, we did not
propose and are not finalizing revisions to MY 2027 standards or new standards for MYs 2028 or 2029. ZEV
adoption for this source type in these model years was set to be equal to the reference case.
Table 4-10 National heavy-duty ZEV adoption in the control case for the alternative
Model Year
LHD
MHD
HHD
Short-Haul
Long-Haul
Vocational
Vocational
Vocational3
Tractors
Tractorsb
2027
15.7%
10.4%
4.6%
4.7%
0.4%
2028
20.9%
13.7%
7.3%
6.5%
0.7%
2029
26.1%
16.9%
9.8%
10.0%
1.3%
2030
31.3%
20.4%
12.3%
13.5%
5.0%
2031
36.0%
23.3%
14.5%
17.0%
10.0%
2032
40.7%
26.3%
16.6%
20.5%
15.0%
aFor HHD vocational vehicles, we are not finalizing revisions to MY 2027 standards. ZEV adoption for these
vehicles in this model year was set to be equal to the reference case.
b For sleeper cab tractors, which are represented by long-haul tractors (source type 62) in MOVES, we did not
propose and are not finalizing revisions to MY 2027 standards or new standards for MYs 2028 or 2029. ZEV
adoption for this source type in these model years was set to be equal to the reference case.
4.2.4 EGU Emissions Analysis Methodology
Because of the lead times necessary to complete our IPM modeling for the final rulemaking
analysis, we had to develop IPM input scenarios before our analysis was complete for the final
standards. Therefore, we developed reference and control scenarios which do not directly match
the reference and control cases used in our final rulemaking analysis, but that we used on an
interim basis. We ran these scenarios with the 2022 post-IRA version of IPM.
We fully document the differences between these interim scenarios and the final scenarios in
a memo to the docket.1373 Relative to the final reference case, the interim reference case has a
higher level of HD ZEV adoption, specifically in non-ACT states. The interim control case is
based on the proposed standards and has similar levels of ZEV adoption, with some updates to
the split between BEV and FCEV adoption based on our technology assessment in HD TRUCS.
1373 Murray, Evan. Memorandum to Docket EPA-HQ-OAR-2022-0985. "Modeling Inputs for IPM Modeling in the
Final Rulemaking Inventory Analysis". February 29, 2024.
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Overall, both the interim reference and control cases represent greater electricity demand than
their respective final rulemaking cases. In terms of understanding the impacts of the final
standards on the U.S. electricity grid, we consider these interim scenarios to be conservative,
especially in the near term. Nonetheless, the differences between the interim and final scenarios
are small compared to the difference between IPM defaults and the final scenarios. Therefore, we
use the IPM results to calculate adjusted inventories that provide a good approximation of the
EGU emissions impact of the final standards and alternative.
Chapter 4.2.4.1 discusses how we developed IPM inputs for each scenario and Chapter 4.2.4.2
discusses the methodology we developed to estimate EGU emissions impacts for the control
cases using IPM's outputs. We calculated refinery emissions by adjusting an existing refinery
inventory. Chapter 4.2.5 discusses the methodology we used to estimate refinery emission
impacts.
4.2.4.1 IPM Input Files
The only IPM input that we needed to update to model reference and control scenarios is the
total electricity demand. IPM's default electricity demand is based on the Energy Information
Administration (EIA) Annual Energy Outlook 2023 (AEO20 23),1356 which does not include the
full forecasted ZEV adoption in the reference case. Relative to AEO2023, the interim reference
case reflects increased HD ZEV adoption. Therefore, we developed IPM input files specific to
the demand of electric vehicles not captured by IPM's defaults, which we call incremental
heavy-duty demand input files.1374'1375
We developed a set of incremental heavy-duty demand input files for our interim reference
case and another set for our interim control case. To calculate EV electricity demand for these
scenarios, we performed state-by-state MOVES runs to account for state-specific HD ZEV
adoption rates similar to those discussed in Chapter 4.2.2.
IPM requires grid demand to be specified by day type (i.e., for an average weekday and
weekend day), hour of the day, and by each of IPM's geographic regions. We first calculated
total energy demand for a typical weekend day and weekday for both BEVs and FCEVs using
MOVES output. Because MOVES energy consumption output for BEVs represents the total grid
demand related to the running and charging of the vehicles, we used MOVES output for BEVs
with no further processing.
However, MOVES does not capture upstream emissions due to the production of hydrogen
for FCEVs. Hydrogen in the U.S. today is primarily produced via steam methane reforming
(SMR), largely as part of petroleum refining and ammonia production. Given the BIL and IRA
provisions that meaningfully incentivize reducing the emissions and carbon intensity of
hydrogen production, as well as new transportation and other demand drivers and potential future
1374 We also provided incremental light-duty demand input files to IPM based on the reference case for the proposed
Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles rule
(FR 88 29184). Incremental light-duty demand input files were generated using OMEGA. More details on light-duty
BEV energy demand relative to the IPM default demand can be found in the draft Regulatory Impact Analysis,
Chapter 5.
1375 U.S. EPA. "Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty
Vehicles: Draft Regulatory Impact Analysis". April 2023. Available online:
https://nepis.epa.gov/Exe/ZyPDF.cgi/PIO 175 J2.PDF?Dockey=P10175J2.PDF
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regulation, we anticipate there will be a shift in how hydrogen is produced. Therefore, we made a
simplifying assumption that the increased levels of hydrogen necessary to fuel FCEVs will be
produced using grid electrolysis. Thus, all hydrogen production is represented as additional
demand to EGUs and the emissions are modeled using IPM.
The relative emissions impact of hydrogen production via SMR versus grid electrolysis
depends on how electricity is produced, which varies significantly by region across the country.
Electrolysis powered by electricity from the grid on average in the U.S. may overestimate the
upstream emissions impacts that are attributable to HD FCEVs in our analysis. New electrolysis
project announcements predominantly pair electrolyzers wth zero-carbon energy sources.1376 As
the carbon intensity of the grid declines over time in response to the BIL and IRA and incentives,
these impacts should be mitigated.1377
To better understand the possible emission impacts of the hydrogen production necessary to
fuel HD FCEVs, we conducted a comparative analysis of multiple hydrogen production
pathways including SMR and autothermal reforming (ATR) compared to grid-powered
electrolysis. The methodology and results of this sensitivity analysis are discussed in RIA
Chapter 4.8. While we present the emission impacts of the electrolysis scenario, the emission
impacts of hydrogen production scenarios discussed in Chapter 4.8 offer a qualitative range for
the upstream emissions that will result from the increased FCEV adoption projected in the
modeled potential compliance pathway for the final standards.
For our inventory modeling, we developed yearly scalar multipliers to apply to MOVES
FCEV energy consumption to model emissions for hydrogen production coming from
electrolysis. The resulting energy demand represents the total grid demand from the hydrogen
production necessary to support the levels of FCEVs projected in our principal compliance
pathway. First, we assumed hydrogen is produced by a series of decentralized, grid-powered
polymer electrolyte membrane (PEM) electrolyzer systems, each with a hydrogen production
capacity around 1,500 kilograms per day.1378'1379 Next, we assumed the gaseous hydrogen is
compressed and pre-cooled for delivery to vehicles using grid-powered electrical equipment.
Finally, we assumed a linear improvement between our estimated current and future efficiency
for hydrogen production. The linear interpolation is between current values that start in 2025 and
future values represented for 2055, assuming a period of diffusion for more efficient electrolysis
technology improvements to spread. The final scaling factors range from 1.748 in 2025 to 1.616
in 2055.
We allocated total daily demand of FCEVs and BEVs by the hour of day separately. FCEV
energy demand is allocated uniformly across all hours of the day because hydrogen fuel can be
produced and compressed at any time of day.
1376 For electrolyzers using renewable energy, a fraction of electricity consumed may come from the grid, which is
more carbon intensive, to address intermittency of renewable energy.
1377 U.S. Department of Energy. "Pathways to Commercial Liftoff: Clean Hydrogen". March 2023. Available online:
https://liftoff.energy.gOv/wp-content/uploads/2023/03/20230320-Liftoff-Clean-H2-vPUB.pdf.
1378 This is based on assumptions from the Hydrogen Analysis Production (H2A) Model from the National
Renewable Energy Laboratory (NREL).
1379 National Renewable Energy Laboratory (NREL). "H2A: Hydrogen Analysis Production Model: Version
3.2018". Available online: https://www.nrel.gov/hydrogen/h2a-production-archive.html
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We developed charging load profiles to reflect the share of total daily demand from BEV
charging that we expect to occur each hour for both weekdays and weekends. Because vehicle
use and charging patterns vary by application, we developed individual charging profiles for
each of MOVES heavy-duty source types based on soak or hotelling data in MOVES.1380
Except for long-haul vehicle types, we used soak times of 12 or more hours1381 as a proxy for
when a vehicle may be parked at a depot, warehouse, or other off-shift location and can charge.
We assume charging activity to be evenly distributed across the 12 hours of soak time before the
vehicle starts. For long-haul vehicles, we instead calculate charging profiles using MOVES
hotelling data in lieu of available soak data. Hotelling data accounts for the length of time that a
vehicle is parked while en route and represents an opportunity for charging. Hotelling data is
applied directly and does not assume the same 12-hour proxy as these vehicles may not regularly
return to a depot for off-shift charging.
We expect that the charging beginning time and duration will vary due to different energy
consumption, charging equipment, and the charging preferences of BEV owners or operators.
Finally, charging profiles for each source type were weighted by their share of electricity
demand to calculate overall HD BEV national charging profiles for weekdays and weekends. We
calculated separate HD BEV charging profiles for each calendar year run in IPM and for both the
interim reference and control cases.
The HD BEV charging profiles used for the interim reference case for the calendar years in
which we ran IPM are shown in Figure 4-1 (weekdays) and Figure 4-2 (weekends). The small
differences in the profiles for each year reflect the dependency that charging profiles have on the
BEV fleet composition, as does the difference in the general profile shape between weekdays
and weekends.
1380 Soaking is the time between when a vehicle is powered off and when it starts again, so it indicates when vehicles
are not driving and may have an opportunity to charge. Hotelling is the hours spent by drivers of long-haul trucks
with their trucks parked during mandatory rest periods.
1381 For our NPRM analysis we assumed all vehicles had 12 hours of dwell time to charge at depots. As discussed in
Chapter 2.6.2.1.4, we have updated dwell times in our final rule analysis to values ranging from 7.4 to 14.5 hours
depending on vehicle type. Due to the lead times necessary to complete our IPM modeling for the final rulemaking
analysis, we used the NPRM assumption when developing load profiles for calculating IPM inputs for the interim
scenarios.
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7.0%
Figure 4-2 Heavy-duty BEV charging profiles for weekends for the interim reference case
Finally, IPM requires grid demand to be geographically allocated by IPM region. We
developed regional allocation factors based on county-level CO2 emissions in the 2016v2
emissions modeling platform.1382 We used CO2 emissions as our basis for regional allocation
because CO2 scales well with VMT while capturing differing fleet characteristics in different
1382 U.S. EPA. "2016v2 Platform". January 23, 2023. Available online: https://www.epa.gov/air-emissions-
modeling/2016v2-platform
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counties. IPM includes a mapping of each county to an IPM region, which we used to aggregate
county allocation factors by IPM region.
4.2.4.2 EGU Inventory Calculation Methodology
The IPM runs we performed to estimate EGU emissions were based on interim reference and
control cases. Because they aren't identical to our final reference and control cases, we
developed a methodology to estimate the increase in EGU emissions from the final standards and
the alternative using emission factors calculated from the IPM output.
We calculated emission factors that relate an increase in EGU emissions to an increase in HD
ZEV energy demand. This approach does not yield perfectly accurate emissions estimates
because the power generation mix, and therefore EGU emissions, depend on the total energy
demand. However, the changes in HD ZEV energy consumption between our interim and final
scenarios is small enough that this approach provides a good approximation for calculating
changes in EGU emission inventories.
We calculated emission factors in terms of the incremental change in emissions and energy
consumption and therefore call them incremental EGU emission factors. They are calculated as
the change in EGU emissions from a reference to a control case divided by the change in HD
ZEV energy consumption from the same reference and control case, as expressed in Equation
4-2.
Equation 4-2 Calculation method of an incremental EGU emission factor from a reference and control cases
¦ ¦ Emissions control Emissionsreference
incremental EGU emission factor = —
Energy Demanacontroi — Ener gyDemanareference
Table 4-11 shows the incremental EGU emission factors we calculated for four calendar years
and the GHGs and criteria pollutants we estimated using IPM. These factors represent the
increase in EGU emissions, in U.S. tons, per terawatt-hour of increased grid demand from HD
ZEVs. We calculated incremental EGU emissions factors for 2035, 2040, 2045, and 2050
because IPM runs only include a few calendar years.
Table 4-11 Incremental EGU emission factors used to estimate EGU emissions increases attributable to
additional HD ZEV adoption in the final rulemaking
Pollutant
Incremental EGU Emission Factor
(U.S. Tons / Terawatt-Hour)
2035
2040
2045
2050
Carbon Dioxide (CO2)
443,304
78,249
98,012
81,195
Methane (CH4)
28.2
6.5
2.3
1.6
Nitrous Oxide (N20)
3.9
0.9
0.3
0.2
Nitrogen Oxides (NOx)
133.6
18.4
9.8
8.7
Particulate Matter (PM2 5)
19.5
3.9
3.7
2.9
Sulfur Dioxide (SO2)
161.2
13.5
4.0
0.4
Volatile Organic Compounds (VOC)
6.4
1.2
2.1
1.1
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EGU emission factors decrease into the future, as higher-emitting power generation
technologies like coal and natural gas combustion are phased out in favor of renewable sources.
This is especially apparent in the emission factors of sulfur dioxide (SO2), which decrease by
more than 99% from 2035 to 2050 as coal is almost entirely phased out.
Because the EGU emission factors are calculated based on the increase in emissions
attributable specifically to the increase in demand from HD ZEVs, they capture the effects that
HD ZEVs have on EGU emissions. These effects include factors such as the geographic
distribution of ZEVs, the types of roads they operate o the time of day they charge, and the
electricity generation mix used to provide the electricity, among other factors.
To estimate the impact of the final standards and alternative on EGU emissions, we multiply
the incremental EGU emission factors by the additional HD ZEV energy demand modeled for
each scenario estimated in MOVES4.R3. For year-over-year inventories, we use the emission
factor from the year closest to each calendar year, such that 2027 through 2037 use the rate from
2035, 2038 through 2042 use the rate from 2040, and so on. The rate from 2050 was used to
estimate EGU emissions from 2051 through 2055.
This methodology represents a good approximation of how we expect EGU emissions to
increase because of increased HD ZEV adoption with the final standards under the potential
compliance pathway and the alternative. But the calculated emission inventory estimates are not
likely to be identical to those that would result from running IPM for the final reference and
control cases, as opposed to the interim scenarios. There are, therefore, several caveats and
limitations in the interpretation of the results from this analysis.
First, as stated earlier in this section, we do not have IPM runs that directly correlate to the
reference case used throughout this rulemaking. Because there is no total inventory calculated for
the reference case, relative comparisons between the control cases and reference case (such as
percent changes) are not possible. Second, by only considering the additional energy demand and
energy consumption of HD ZEVs, we capture how characteristics specific to their operation
affect EGU emissions. However, this method is not able to quantitatively isolate these effects,
nor is it able to partition EGU emissions to HD ZEVs of specific vehicle types such as by source
type, regulatory class, or model year.
4.2.5 Refinery Emissions Analysis Methodology
We developed the refinery emission inventory impact estimates using a similar approach to
how we developed EGU emission inventory impact estimates. Specifically, we calculated
emission factors which related a change in refinery emissions to a change in refinery activity. To
estimate the refinery emission impact, we calculated the change in refinery activity using
MOVES fuel consumption multiplied by the emission factors.
The starting point for estimating the refinery inventories was the 2016v3 emissions modeling
platform, which includes projection years of 2023 and 2026.1383 Starting from the 2026 refinery
1383 U.S. EPA. "2016v3 Platform". September 22, 2023. Available online: https://www.epa.gov/air-emissions-
mode ling/2016v3 -platform
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inventory, we calculated a refinery inventory for each calendar year in 5-year increments from
2030 to 2050 using growth factors calculated from the AEO20 23.1384
Refineries in the United States refine more products than gasoline and diesel fuel, and some
refineries do not refine any onroad fuels. We reviewed the facilities included in the 2016 refinery
sector in the emissions modeling platform and omitted facilities that did not produce gasoline or
diesel fuel. We then calculated scaling factors to apportion total emissions from refineries
specifically to the refining of gasoline and diesel versus other refined fuels and refinery
operations. The scaling factors are based on the relative energy demand of refining various fuels
calculated by Wang et al. (2004).1385 Wang et al. expressed the energy demand of refining fuels
in terms of mass and included outputs that are not refinery products (i.e., fuel gas), so we
removed non-refinery products and adjusted the energy demand factors to be based on volume
instead of mass.
Relative emissions related to the refining of various products are determined primarily by the
energy needed to refine those products, but also depend on pollutant-specific emissions specific
to refining those products. For example, the refining of gasoline causes higher methane
emissions than an equivalent volume of diesel. We developed pollutant-specific apportionment
factors based on relative emissions of refining gasoline, diesel, and other products using
emission factors from GREET 2021.1386 We use the apportionment factors to calculate the
portion of the refinery inventory attributable to the refining of each fuel type. Final
apportionment factors for each pollutant we modeled in our refinery analysis appear in Table
4-12.
1384 Specifically, within the emissions modeling platform, a projection packet was prepared for 2026 projected out to
2050 using AEO2023 for refineries. AEO categories were mapped to source classification codes (SCCs) and SCC+
North American Industry Classification System (NAICS) combinations (with SCC+NAICS taking precedence if a
mapping exists for the refinery NAICS, which are 32411/324110) using the usual industrial source AEO-SCC and
AEO-SCC-NAICS cross references "xrefs" from past platforms. Only refineries NAICS and SCCs which have
refinery emissions were included when making the packet, so the 2026-2050 packet is not something that can be
used to project the entire point source non- IPM "ptnonipm" sector. Each record in the packet references the
refineries NAICS so that it can be applied to the entire ptnonipm sector without changing any non-refineries.
1385 Wang, M., Lee, H. & Molburg, J. Allocation of energy use in petroleum refineries to petroleum products. Int J
LCA 9, 34-44 (2004). https://doi.org/10.1007/BF02978534
1386 Wang, Michael, Elgowainy, Amgad, Lee, Uisung, Bafana, Adarsh, Baneijee, Sudhanya, Benavides, Pahola T.,
Bobba, Pallavi, Burnham, Andrew, Cai, Hao, Gracida, Ulises, Hawkins, Troy R., Iyer, Rakesh K., Kelly, Jarod C.,
Kim, Taemin, Kingsbury, Kathryn, Kwon, Hoyoung, Li, Yuan, Liu, Xinyu, Lu, Zifeng, Ou, Longwen, Siddique,
Nazib, Sun, Pingping, Vyawahare, Pradeep, Winjobi, Olumide, Wu, May, Xu, Hui, Yoo, Eunji, Zaimes, George G.,
and Zang, Guiyan. Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021 Excel).
Computer Software. U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy
(EERE). 11 Oct. 2021. Web. doi: 10.11578/GREET-Excel-2021/dc.20210902.1.
581
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Table 4-12 Refinery emission apportionment factors by fuel type
Pollutant
Refinery Emissions Apportionment Factor
Gasoline
Diesel
Other
Carbon Dioxide (CO2)
0.591
0.061
0.348
Methane (CH4)
0.640
0.053
0.307
Nitrous Oxide (N20)
0.583
0.063
0.354
Nitrogen Oxides (NOx)
0.610
0.056
0.334
Particulate Matter (PM2 5)
0.620
0.054
0.326
Sulfur Dioxide (SO2)
0.596
0.058
0.346
Volatile Organic Compounds (VOC)
0.570
0.058
0.372
Table 4-13 shows how we estimated 2050 refinery emissions that are attributable to the
refining of gasoline and diesel fuel. We begin with the total refinery inventory. Then, we
apportion that to refineries that refine onroad fuels, and then we further apportion emissions to be
specific to the refining of gasoline and the refining of diesel.
Table 4-13 Refinery emission inventory apportioned by refinery type and fuel type
Pollutant
Emission Inventory by Refinery
Group (U.S. Tons)
Inventory Apportioned by
Fuel Type (U.S. Tons)
All
Refineries
Refineries that produce
gasoline and diesel
Gasoline
Diesel
Carbon Dioxide (CO2)
203,808,672
186,521,729
110,234,342
11,377,825
Methane (CH4)
11,105
9,743
6,235
514
Nitrous Oxide (N20)
1,712
1,593
928
100
Nitrogen Oxides (NOx)
81,607
77,830
47,437
4,335
Particulate Matter (PM2 5)
19,243
18,253
11,324
976
Sulfur Dioxide (SO2)
26,287
23,501
14,017
1,373
Volatile Organic Compounds (VOC)
64,091
57,829
32,972
3,374
To estimate refinery emission rates using the fuel-specific refinery inventories, we estimated
total refinery activity in terms of gasoline and diesel produced. AEO2023 has projections for
total onroad fuel demand of diesel and gasoline through 20 5 01387 but the United States is a net
exporter of gasoline and diesel. We therefore included exports of liquid fuels in our estimates of
the total fuel refined by U.S. refineries.
AEO2023 does not include estimated exports of gasoline and diesel through 2050. Instead, it
presents estimates of net exports of total refined liquid fuels.1388 To estimate exports of gasoline
and diesel, we scaled measured 2022 exports into the future using growth factors from
AEO2023. Implicit in this approach is the assumption that the relative change in exports of those
two fuels is highly correlated with exports of all refined liquid fuels.
We use combined net exports and domestic demand for gasoline and diesel fuel to estimate
the total refinery activity in terms of gallons of fuel refined. Finally, we calculate refinery
emission rates that relate a change in onroad fuel consumption to a change in refinery emissions.
1387 AEO2023 Table 11, rows "Liquid Fuels: Liquid Fuels Use: by Fuel: Motor Gasoline: Reference case" and
"Liquid Fuels: Liquid Fuels Use: by Fuel: Diesel: Reference case"
1388 AEO2023 Table 11, "Liquid Fuels: Net Product Imports: Reference case"
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Table 4-14 presents the refinery emission rates for gasoline and Table 4-15 presents the refinery
emission rates for diesel.
Table 4-14 Refinery emission rates for the refining of gasoline
Pollutant
Refinery Emission Rate
(U.S. Tons / Billion Gallons of Gasoline)
2030
2035
2040
2045
2050
Carbon Dioxide (CO2)
731,207
765,753
794,514
811,236
814,381
Methane (CH4)
42.5
44.3
45.8
46.2
46.1
Nitrous Oxide (N20)
6.2
6.4
6.7
6.8
6.9
Nitrogen Oxides (NOx)
317.4
332.1
345
350.6
350.5
Particulate Matter (PM2 5)
76.1
79.5
82.4
83.7
83.7
Sulfur Dioxide (SO2)
94.6
99
102.5
104
103.6
Volatile Organic Compounds (VOC)
225.7
235.8
243.3
245.5
243.6
Table 4-15 Refinery emission rates for the refining of diesel
Pollutant
Refinery Emission Rate
(U.S. Tons / Billion Gallons of Diesel)
2030
2035
2040
2045
2050
Carbon Dioxide (CO2)
146,741
146,209
146,442
148,050
153,504
Methane (CH4)
6.8
6.7
6.7
6.7
6.9
Nitrous Oxide (N20)
1.3
1.3
1.3
1.3
1.4
Nitrogen Oxides (NOx)
56.4
56.1
56.3
56.7
58.5
Particulate Matter (PM2 5)
12.7
12.7
12.7
12.8
13.2
Sulfur Dioxide (SO2)
18
17.9
17.9
18
18.5
Volatile Organic Compounds (VOC)
44.9
44.6
44.4
44.4
45.5
The refinery emission rates can be paired with an estimate of reduced refinery activity to
estimate the impact of the final standards. We estimate the change in refinery activity by
assuming a reduction in onroad fuel demand will lead to a reduction in the total amount of fuel
refined. However, U.S. refineries can theoretically respond to lower domestic demand by
increasing volumes of exported liquid fuels, thus allowing them to refine at the same volume and
leaving refinery emissions unchanged.
For projecting the emissions inventory impacts for the NPRM, we estimated that 7% of the
reduced domestic demand for refined fuels would be made up by increased net exports1389 based
on a comparison of the reference case and low economic growth case in AEO2021.1390 In other
words, we projected that U.S. refineries would largely decrease their refined fuel production as
U.S. refined product demand decreases. However, we also recognized the large uncertainty in
this assumption. We received comments from several organizations that refineries would
increase net exports more than we assumed and thus not reduce their production as much.
There are several reasons to expect refineries to increase net exports should domestic demand
for refined fuels drop in the future. First, many refineries refine other products, such as
1389 An increase in net exports can be the result of increased exports, reduced imports, or both. For the FRM
analysis, we do model a decrease in net imports, discussed in RIA Chapter 6.5 and RIA Chapter 7.3.
1390 U.S. Energy Information Administration (EIA). "Annual Energy Outlook 2021". U.S. Department of Energy.
February 3, 2021. Available online: https://www.eia.gov/outlooks/archive/aeo21/
583
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petrochemical feedstocks, in addition to onroad fuels. These petrochemical feedstocks have
economic value of their own so refineries which may be earning lower margins for onroad fuels
can earn a larger return from these other products. Thus, refineries coproducing petrochemicals
are more likely to continue to produce onroad fuels despite decreasing demand for refined
products.1391 Second, U.S. refiners often find it economically advantageous to refine crude oil in
the United States because feedstock prices (both natural gas and crude oil prices) tend to be
lower, thus leading to higher profit margins.1392
The higher profit margins experienced by U.S. refineries (which start in 2005) would be
expected to result in lower imports and higher exports, and this has indeed occurred. Figure 4-3
shows net U.S. import data from the U.S. from the U.S. Energy Information Administration for
gasoline and diesel fuel,1393 plotted with crude prices.1394
Net Imports and Crude Oil Spot Prices
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Figure 4-3 Net U.S. imports of refined liquid fuels and crude oil prices since 1995
We can see an increase in net exports (apparent in the plot as a decrease in net imports)
starting in 2006 associated with improved U.S. refinery margins. The increase in net exports
corresponds with an increase in crude oil prices.
1391 Erwin Seba. "Shell weighs shut Louisiana refinery's future as Baton Rouge firm promotes bid". Reuters. May
24, 2021. Available online: https://www.reuters.com/business/finance/shell-weighs-shut-louisiana-refinerys-future-
baton-rouge-firm-promotes-bid-2021-05-24/
1392 U.S. Energy Information Administration. "Lower crude feedstock costs contribute to North American refinery
profitability." Today in Energy.June 5, 2014. Available online:
https://www.eia.gov/todayinenergy/detail.php?id= 16571
1393 U.S. Energy Information Administration. "Imports by Area of Entry, Petroleum and Other Liquids". January 31,
2024. Available online: https://www.eia.gov/dnav/pet/pet_move_imp_dc_NUS-ZOO_mbblpd_a.htm
1394 U.S. Energy Information Administration. "Spot Prices, Petroleum and Other Liquids". February 14, 2024.
Available online; https://www.eia.gov/dnav/pet/pet_pri_spt_sl_a.htm
584
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Despite the favorable economic conditions for refiners in the United States, there have been
some refinery closures and conversions in recent years, in some cases associated with the lower
domestic fuel demand caused by the COVID-19 pandemic. Decisions by oil industry company
boards of directors to begin pivoting away from producing fossil fuels is also beginning to figure
into how they manage their company assets. For example, Shell cited a desire to pivot towards
lower carbon fuel options, among other reasons, as a reason to close its Convent, Louisiana
refinery at the end of 2020.1395 Additionally, several refiners have recently opted to fully or
partially convert their petroleum refineries to produce renewable diesel, including refineries in
North Dakota,1396 New Mexico,1397 Wyoming,1397 and Oklahoma.1398
The closure or conversion of some U.S. refineries in recent years despite better refinery profit
margins suggests the closure or conversion of additional refineries, such as those that have lower
margins or face other issues, is likely as domestic demand for gasoline and diesel fuel declines.
The extent to which U.S. refineries keep operating, shut down, or are converted is difficult to
project since it depends on the economics of individual refineries, the economic condition of the
parent company, and the long-term strategy pursued by each company's board for providing a
return to its shareholders.
After carefully considering stakeholder comments, the more desirable economic conditions
for refiners in the U.S., and the closure and conversion of some U.S. refineries over the past
several years, we updated our projection of how refineries will be impacted by this rulemaking.
We project refinery emissions by assuming that U.S. refineries would increase net exports to
offset half of the reduction in domestic demand for refined product. Thus, the total decrease in
refinery activity, measured in gallons of gasoline and diesel refined, is half of the estimated drop
in domestic fuel demand. This assumption is also supported by recent refining industry study that
projected how increased transportation electrification would affect refinery production in
different regions. The study evaluates three different electrification scenarios and, for each one,
the authors estimate North American refinery volumes decreasing relative to most other global
refining regions they modeled.1399
However, there remains significant uncertainty in how U.S. refineries will respond to lower
demand for liquid onroad fuels. Therefore, we performed a sensitivity analysis, presented in
1395 Kristen Mosbrucker. "Without a buyer, Shell may convert shuttered Convent refinery into alternative fuels
facility".; The Advocate. October 14, 2021. Available online:
https://www.theadvocate.com/baton_rouge/news/business/without-a-buyer-shell-may-convert-shuttered-convent-
refinery-into-alternative-fuel-facility/article_54ff85f2-2dl8-l Iec-af75-13fba5943b71.html
1396 Bismarck State College. "Marathon converts Dickinson Refinery to renewable diesel plant; wind turbines to
power site". May 26, 2021. Available online: https://bismarckstate.edu/news/dixrefinery/
1397 HF Sinclair Corporation. "HollyFrontier Announces Expansion of Renewables Business". June 1, 2020.
Available online: https://www.hollyfrontier.com/investor-relations/press-releases/Press-Release-
Details/2020/HollyFrontier-Announces-Expansion-of-Renewables-Business
1398 Biomass Magazine. "CVR To Move Forward With Wynnewood Conversion In Early 2022." November 2, 2021.
Available online: https://biomassmagazine.com/articles/cvr-to-move-forward-with-wynnewood-conversion-in-early-
2022-18449
1399 Cherry Ding, Alexandre Ferro, Tim Fitzgibbon, and Piort Szabat. "Refining in the energy transition through
2040". Oil and Gas Practice, McKinsey & Company. November 3, 2022. Available online:
https://www.mckinsey.com/industries/oil-and-gas/our-insights/refining-in-the-energy-transition-through-2040
585
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Chapter 4.9, in which we assume that 80 percent of the drop in domestic fuel demand will be
offset by an increase in net exports, instead of 50 percent.
Like our IPM modeling, the total refinery emission inventory used to calculate the emission
rates does not directly correlate to our final reference case. The refinery inventories are based on
AEO2023, which assumes much lower rates of vehicle electrification than in our reference case.
As was the case for our EGU modeling, our methodology accounts for these differences in total
fuel demand, but does not calculate an inventory that represents the final rule reference case.
Therefore, calculating relative changes compared to a total reference case inventory, like percent
change in emissions, is not possible. Because we calculate an emission inventory impact instead
of an inventory itself, and because we assume a portion of the change in onroad fuel demand will
be offset by increased net exports, it is also impossible to attribute emission inventory impacts to
particular vehicle types such as by MOVES source type, regulatory class, or model year.
4.3 National Downstream Emission Inventory Impacts of the Final Standards
This section presents the impacts of the final standards on downstream emissions of GHGs
and on several criteria pollutants and air toxics. All emission inventories were modeled using
MOVES national domain, which includes the 50 states and the District of Columbia but not any
U.S. commonwealths or territories.
Because we anticipate an increase in the adoption of HD ZEVs under the modeled potential
compliance pathway for the final standards for MYs 2027 through 2032 and later, we expect
downstream reductions of additional GHGs (methane and nitrous oxide) as well as reductions of
criteria pollutants and air toxics. We modeled the final standards in MOVES4.R3 only by
increasing the adoption of HD ZEVs (including both BEVs and FCEVs), which means the
driving factor behind all estimated emission reductions in this analysis is the displacement of HD
ICE vehicles with HD ZEVs.
The modeled downstream emission reductions are smaller than we presented in the NPRM.
This is mostly because in the final rule analysis we assumed increased HD ZEV adoption levels
in the reference case; it is not necessarily indicative that the final standards are meaningfully less
stringent than the proposed standards.
Chapter 4.3.1 presents the inventory changes for three analysis years: 2035, 2045, and 2055.
Chapter 4.3.2 presents year-over-year emission impacts from 2027 through 2055, including
cumulative emission reductions. Chapter 4.3.3 discusses these impacts in more detail, including
by vehicle type and fuel type, for calendar year 2055.
4.3.1 Analysis Year Impacts
Our estimates of the downstream emission reductions of GHGs that will result from the final
standards relative to the reference case are presented in Table 4-16 for calendar years 2035,
2045, and 2055. Total GHG emissions, or CO2 equivalent (C02e), are calculated by summing all
GHG emissions multiplied by their 100-year Global Warming Potential (GWP). The GWP
values used in Table 4-16 are consistent with the 2014 IPCC Fifth Assessment Report (AR5).1400
1400 IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L. A.
Meyer (eds.)]. Available online: https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full.pdf
586
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Table 4-16 Annual downstream heavy-duty GHG emission reductions from the final standards in calendar
years (CYs) 2035,2045, and 2055
Pollutant
100-year
GWP
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Carbon Dioxide (CO2)
1
32.5
9%
66.3
19%
70.0
20%
Methane (CH4)
28
0.002
3%
0.006
10%
0.009
12%
Nitrous Oxide (N20)
265
0.005
9%
0.01
19%
0.01
20%
CO2 Equivalent (COye)
—
33.8
9%
69.1
19%
73.0
20%
In 2055, we estimate that the final standards will reduce downstream emissions of CO2 from
heavy-duty vehicles by 20 percent, methane by 12 percent, and nitrous oxide by 20 percent,
resulting in a reduction of 20 percent for total CO2 equivalent emissions from heavy-duty
vehicles. Table 4-16 also shows that most of the GHG emission reductions are from CO2, which
represents approximately 96 percent of all heavy-duty GHG emission reductions from the final
standards.
Table 4-17 presents our estimates of the downstream emission reductions of criteria pollutants
and air toxics from heavy-duty vehicles that will result from the final standards in calendar years
2035, 2045, and 2055 relative to the reference case.
Table 4-17 Annual downstream heavy-duty criteria pollutant and air toxic emission reductions from the final
standards in calendar years (CYs) 2035,2045, and 2055
Pollutant
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
U.S. Tons
Percent
U.S. Tons
Percent
U.S. Tons
Percent
Nitrogen Oxides (NOx)
10,801
3%
47,027
16%
54,268
20%
Particulate Matter (PM2 s)A
126
2%
302
5%
331
5%
Volatile Organic Compounds (VOC)
3,014
6%
6,426
17%
7,242
20%
Sulfur Dioxide (SO2)
126
9%
256
19%
270
20%
Carbon Monoxide (CO)
49,273
6%
117,155
17%
131,014
19%
1,3-Butadiene
7
11%
14
27%
14
27%
Acetaldehyde
62
6%
138
17%
160
17%
Benzene
38
8%
80
22%
82
25%
Formaldehyde
41
4%
100
14%
126
15%
Naphthalene0
3
5%
6
22%
6
23%
A PM2.5 estimates include both exhaust and non-exhaust emissions, but all modeled reductions come from exhaust
emissions. Relative exhaust PM2 5 reductions are similar to other criteria pollutants with reductions of 3% in
2035, 18% in 2045, and 21% in 2055.
B Naphthalene includes both gas and particle phase emissions.
In 2055, we estimate the final standards will reduce heavy-duty vehicle emissions of NOx by
20 percent, PM2.5 by 5 percent, VOC by 20 percent, and SO2 by 20 percent. Reductions in air
toxics in 2055 range from 15 percent for formaldehyde to 27 percent for 1,3-butadiene.
587
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4.3.2 Year-Over-Year Impacts
Table 4-18 shows the year-over-year reductions in methane and nitrous oxide emissions that
we project will result from the final standards, in metric tons. Table 4-19 presents the year-over-
year CO2 emission reductions and total GHG emission reductions in terms of CCh-equivalent
mass. Table 4-20 presents the year-over-year reductions in criteria pollutant emissions.
Table 4-18 Year-over-year CH4 and N2O emission reductions from the final standards
Calendar
Year
CH4 Reductions
N2O Reductions
Metric Tons
Percent
Metric Tons
Percent
2027
22
0.0%
57
0.1%
2028
85
0.1%
147
0.3%
2029
152
0.2%
269
0.5%
2030
238
0.4%
508
0.9%
2031
432
0.7%
1,038
1.9%
2032
763
1.3%
1,995
3.7%
2033
1,088
1.9%
2,938
5.5%
2034
1,451
2.5%
3,860
7.2%
2035
1,803
3.1%
4,741
8.9%
2036
2,156
3.8%
5,552
10.5%
2037
2,584
4.6%
6,299
11.9%
2038
3,094
5.6%
6,973
13.2%
2039
3,577
6.5%
7,578
14.5%
2040
4,033
7.3%
8,123
15.4%
2041
4,461
8.0%
8,610
16.4%
2042
4,873
8.7%
9,030
17.2%
2043
5,264
9.3%
9,375
17.9%
2044
5,637
9.8%
9,646
18.5%
2045
5,992
10.2%
9,849
19.0%
2046
6,345
10.6%
10,009
19.3%
2047
6,688
10.9%
10,118
19.5%
2048
7,024
11.1%
10,181
19.7%
2049
7,371
11.5%
10,229
19.8%
2050
7,735
11.7%
10,295
19.9%
2051
8,085
11.8%
10,345
20.0%
2052
8,432
11.9%
10,383
20.1%
2053
8,783
12.0%
10,409
20.1%
2054
9,139
12.1%
10,421
20.1%
2055
9,497
12.1%
10,422
20.0%
588
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Table 4-19 Year-over-year CO2 and CChe emission reductions from the final standards
Calendar
Year
CO2 Reductions
Total GHG (CChe) Reductions
MMT
Percent
MMT
Percent
2027
0.5
0.1%
0.5
0.1%
2028
1.2
0.3%
1.3
0.3%
2029
2.1
0.5%
2.2
0.5%
2030
3.8
0.9%
3.9
0.9%
2031
7.4
1.9%
7.7
1.9%
2032
14.0
3.6%
14.5
3.6%
2033
20.4
5.3%
21.2
5.3%
2034
26.6
7.0%
27.7
7.0%
2035
32.5
8.7%
33.8
8.6%
2036
37.9
10.2%
39.4
10.2%
2037
42.8
11.7%
44.6
11.7%
2038
47.3
13.0%
49.2
13.0%
2039
51.3
14.2%
53.4
14.2%
2040
54.9
15.3%
57.2
15.3%
2041
58.1
16.3%
60.5
16.3%
2042
60.9
17.2%
63.4
17.1%
2043
63.2
17.9%
65.8
17.8%
2044
64.9
18.5%
67.7
18.4%
2045
66.3
19.0%
69.0
18.9%
2046
67.3
19.3%
70.2
19.3%
2047
68.1
19.6%
70.9
19.5%
2048
68.5
19.8%
71.4
19.7%
2049
68.8
19.9%
71.7
19.9%
2050
69.2
20.0%
72.2
20.0%
2051
69.5
20.1%
72.5
20.1%
2052
69.8
20.1%
72.8
20.1%
2053
69.9
20.2%
72.9
20.1%
2054
70.0
20.1%
73.0
20.1%
2055
70.0
20.1%
73.0
20.0%
589
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Table 4-20 Year-over-year emission inventory reductions for the final standards for select criteria pollutants
Calendar
Year
NOx Reductions
Total PM2.5 Reductions
VOC Reductions
U.S. Tons
Percent
U.S. Tons
Percent
U.S. Tons
Percent
2027
146
0.0%
4
0.0%
87
0.1%
2028
361
0.0%
8
0.1%
189
0.3%
2029
632
0.1%
12
0.1%
302
0.5%
2030
1,096
0.2%
18
0.2%
452
0.7%
2031
2,151
0.4%
33
0.3%
798
1.4%
2032
4,060
0.8%
57
0.6%
1,380
2.5%
2033
5,984
1.3%
80
0.9%
1,956
3.7%
2034
8,156
1.9%
103
1.2%
2,502
5.0%
2035
10,801
2.6%
126
1.5%
3,014
6.3%
2036
14,190
3.6%
150
1.9%
3,497
7.5%
2037
18,253
5.0%
173
2.6%
3,975
9.1%
2038
23,298
6.6%
196
3.0%
4,444
10.5%
2039
27,990
8.2%
217
3.3%
4,858
11.7%
2040
32,356
9.9%
236
3.7%
5,222
12.8%
2041
36,284
11.5%
254
4.0%
5,543
13.7%
2042
39,794
12.9%
270
4.2%
5,830
14.6%
2043
42,704
14.2%
283
4.5%
6,069
15.4%
2044
45,101
15.3%
294
4.6%
6,268
16.2%
2045
47,027
16.2%
302
4.8%
6,426
16.8%
2046
48,634
17.0%
309
4.9%
6,562
17.2%
2047
49,890
17.6%
315
5.0%
6,689
17.6%
2048
50,809
18.1%
319
5.1%
6,782
18.1%
2049
51,597
18.6%
322
5.1%
6,861
18.4%
2050
52,379
19.0%
325
5.1%
6,935
18.7%
2051
53,003
19.3%
327
5.2%
7,016
19.0%
2052
53,490
19.6%
329
5.2%
7,101
19.3%
2053
53,857
19.8%
330
5.1%
7,166
19.5%
2054
54,120
19.9%
331
5.1%
7,213
19.7%
2055
54,268
20.0%
331
5.1%
7,242
19.8%
We expect emission reductions to be small in earlier years as the final standards phase in. As
ZEVs represent an increasing proportion of the heavy-duty vehicle fleet, we expect emission
reductions to grow into the future. Table 4-18, Table 4-19, and Table 4-20 show that emission
reductions will increase over time, as more ICE vehicles are displaced by ZEVs.
Figure 4-4, Figure 4-5, and Figure 4-6 show yearly downstream GHG inventories for the
reference case and the final standards. The emissions estimates for methane and nitrous oxide are
presented in terms of their true mass and are not converted to CO2 equivalent mass.
590
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2030 2040 2050
Calendar Year
— Reference — Final Standards
Figure 4-4 Yearly downstream CH-t inventory for the reference case and final standards from 2027 through
2055
MOVES4.R3 models increasing methane emissions in the future based primarily on the
increased adoption of heavy-duty vehicles fueled by compressed natural gas (CNG). We expect
the final standards under the potential compliance pathway to increase demand for ZEVs in the
2030s and therefore reduce demand for CNG. While we project there is CNG growth in the
future anyway, we project the moderating of this growth by ZEVs displacing CNG would result
in significant reductions in methane emissions.
591
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2030 2040 2050
Calendar Year
— Reference — Final Standards
Figure 4-5 Yearly downstream N2O inventory for the reference case and final standards from 2027 through
2055
In MOVES4.R3, the N2O inventory is highly correlated with the VMT of HD ICE vehicles.
While overall HD VMT grows in future years, the VMT of HD ICE vehicles doesn't change
much because HD ZEV adoption increases, even in the reference case. In our modeled potential
compliance pathway, we project the final standards would further reduce the number of HD ICE
vehicles on the road as the fleet turns over to ZEVs, and therefore, N2O emissions are reduced
through the 2030s and 2040s for the final standards.
592
-------
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o
o
100-
o -
1 1 1
2030 2040 2050
Calendar Year
— Reference — Final Standards
Figure 4-6 Yearly downstream CChe inventory for the reference case and final standards from 2027 through
2055
In the reference case, we project CO2 and CChe emissions to decrease from 2027 through
2055 as HD ZEV adoption grows as described in Chapter 4.2.2 and older ICE vehicles (model
years 2015 and earlier) age out of the fleet. As HD ZEV adoption levels off after California's
ACT rule is fully phased in and HD VMT increases, the GHG inventory stops decreasing in the
late 2040s. While this trend applies to the final standards scenario as well, we expect the greater
adoption of HD ZEVs under the potential compliance pathway would result in much greater
GHG emission reductions through the 2030s and 2040s.
Figure 4-7, Figure 4-8, and Figure 4-9 show the yearly inventories for NOX, PM2.5, and VOC,
respectively.
593
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2030
2040
Calendar Year
2050
— Reference —»* Final Standards
Figure 4-7 Yearly downstream NOx inventory for the reference case and final standards from 2027 through
2055
594
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2030 2040 2050
Calendar Year
— Reference — Final Standards
Figure 4-8 Yearly downstream PM2.5 inventory for the reference case and final standards from 2027 through
2055
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Calendar Year
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Figure 4-9 Yearly downstream VOC inventory for the reference case and final standards from 2027 through
2055
Due to the HD2027 Low NOx standards, 1401 NOX emissions are projected to decrease
significantly through 2055 in the reference case, but we project the adoption of ZEVs under the
potential compliance pathway in the final standards case would lead to additional reductions. The
projected PM2.5 inventory shows a decline through the 2030s with a notable drop from calendar
year 2036 to 2037, due to the complete fleet turnover of HD diesel vehicles without diesel
particulate filters (DPFs) in MOVES. The HD PM2.5 inventory shows little change afterward in
the reference case largely because brake and tire wear represent a significant portion of the
inventory, but we estimate the inventory with the final standards would continue to decrease
modestly. Finally, the VOC emission inventory shows a similar trend as NOX, with emissions
projected to decrease from 2027 through 2055. This is mostly because of HD ZEVs displacing
LHD gasoline vehicles in the reference case. The projected increased ZEV adoption under the
potential compliance pathway in the final standards case would lead to additional emission
reductions.
4.3.3 Detailed Emission Impacts
This section presents detailed discussion of the downstream emission we project from the
final standards, including emission reductions by regulatory class, source type, fuel type, and
emission process. For the purposes of this section, we combine tailpipe and crankcase processes,
such that the running process represents both running tailpipe and crankcase processes. This is
also the case for starts and extended idle.
1401 88 FR 4296, March 27, 2023.
596
-------
In our modeling of the reference case and control cases, we model a heavy-duty fleet that
includes both ICE vehicles and ZEVs. As previously explained in this chapter, our modeling of
ICE vehicles reflects CO2 emission improvements driven by already existing regulations, such as
HD GHG Phase 2, but we do not model an increase in ICE vehicle efficiency under the potential
compliance pathway for the final standards. The emission reductions projected for the final
standards represent the reduction of emissions due to a greater adoption of ZEVs phasing out
ICE vehicles in the HD fleet under the potential compliance pathway.
In the following figures, we present a detailed breakdown of the emission reductions of
various pollutants that we expect will result from the final standards (reflecting our modeled
potential compliance pathway), with breakdowns by MOVES regulatory class, source type, fuel
type, and emission process. Figure 4-10 contains breakdowns for carbon dioxide (CO2), Figure
4-11 for methane (CH4), Figure 4-12 for nitrogen oxides (NOx), Figure 4-13 for PM2.5, and
finally Figure 4-14 for volatile organic compounds (VOC).
597
-------
60
40-
20
0 -
CY 2035
CY 2045
CY 2055
60-
40-
20
0 -
"O
-------
ZEVs displace vehicles of all fuel types and vehicle types, the largest increase in HD ZEV
adoption relative to the reference case occurs for diesel tractors and heavy heavy-duty vehicles.
7500
5000-
2500-
CY 2035
CY 2045
CY 2055
7500-
5000-
2500
"D
a>
a:
c
o
w
w
E
IJJ
CY 2035
CY 2045
CY 2055
7500-
5000-
2500
CY 2035
CY 2045
CY 2055
7500
5000-
2500
MOVES Regulatory Class
| 42-LHD45
46-MHD67
| 47-HHD8
48-Urban Bus
MOVES Source Type
41-Other Buses
42-Transit Bus
| 43-School Bus
51-Refuse Truck
52-Single Unit Short-haul Truck
53-Single Unit Long-haul Truck
61-Combination Short-haul Truck
I 62-Combination Long-haul Truck
MOVES Fuel Type
1-Gasoline
| 2-Diesel
I 3-CNG
MOVES Emission Process
| 1-Running Exhaust
| 2-Starts Exhaust
90-Extended Idle Exhaust
I 91-Diesel APU Exhaust
CY 2035
CY 2045
CY 2055
Figure 4-11 Downstream CH4 reductions from the final standards by regulatory class, source type, fuel type,
and emission process for calendar years (CY) 2035,2045, and 2055
CNG vehicles represent the largest source of HD methane emissions in MOVES4.R3 despite
their small population. This is because methane emission rates for CNG vehicles are at least 30
599
-------
times greater than comparable gasoline and diesel vehicles. We project most methane reductions,
therefore, will come from displacing CNG vehicles with ZEVs. MOVES4.R3 only models CNG
for the Class 8 and urban bus regulatory classes (IDs 47 and 48), so all modeled methane
emission reductions from CNG come from ZEV adoption for buses and heavy heavy-duty trucks.
We project only modest methane emission reductions from displacement of gasoline and diesel
vehicles with ZEVs.
600
-------
40000
20000
40000 -
£ 20000
o
I-
w
3
3
"U
a)
q;
« 40000
E
20000 -
CY 2035
CY 2045
CY 2055
CY 2035
CY 2045
CY 2055
MOVES Regulatory Class
| 42-LHD45
46-MHD67
| 47-HHD8
48-Urban Bus
49-Gliders
MOVES Source Type
41-Other Buses
| 42-Transit Bus
| 43-School Bus
51-Refuse Truck
52-Single Unit Short-haul Truck
53-Single Unit Long-haul Truck
61-Combination Short-haul Truck
I 62-Combination Long-haul Truck
MOVES Fuel Type
1-Gasoline
| 2-Diesel
3-CNG
CY 2035
CY 2045
CY 2055
40000 -
20000 -
MOVES Emission Process
| 1-Running Exhaust
| 2-Starts Exhaust
90-Extended Idle Exhaust
I 91-Diesel APU Exhaust
CY 2035
CY 2045
CY 2055
Figure 4-12 Downstream NOx reductions from the final standards by regulatory class, source type, fuel type,
and emission process for calendar years (CY) 2035, 2045, and 2055
Just as HD methane emissions are driven by CNG vehicles, HD NOx emissions are driven by
diesel vehicles. We expect that most NOx reductions will come from ZEV adoption in
combination tmcks because they represent a large portion of di esel vehi cles now and in the
future.
601
-------
300-
200-
100
0 -
300
200-
o 100
w
3
TJ
-------
Many heavy-duty gasoline vehicles have higher PM2.5 emission rates than heavy-duty diesel
vehicles because manufacturers install particulate filters in diesel engines to meet the PM
standards, while gasoline engines can meet the same PM standards without particulate filters.1402
Therefore, the projected total PM2.5 emissions impact of the standards is sensitive to the number
of HD gasoline vehicles displaced by ZEVs. We consequently estimate that the final standards
will result in greater PM2.5 emission reductions from light and medium HD vehicles than heavy
HD vehicles, due to the number of HD gasoline vehicles in each of those groups. The most
significant source of reductions is expected to be from single-unit short-haul trucks that are Class
5 and below.
1402 The use of particulate filters typically results in PM emissions nearly an order of magnitude below the standard,
where the engine-based controls in gasoline engines result in a smaller margin to the standards.
603
-------
6000-
4000-
2000-
6000-
4000-
o 2000-
l-
co
Z>
0)
or
¦2 6000j
CO
E
UJ
4000-
2000-
6000-
4000-
2000-
CY 2035
CY 2045
CY 2055
CY 2035
CY 2045
CY 2055
CY 2035
CY 2045
CY 2055
MOVES Regulatory Class
| 42-LHD45
46-MHD67
| 47-HHD8
48-Urban Bus
49-Gliders
MOVES Source Type
41-Other Buses
42-Transit Bus
| 43-School Bus
51-Refuse Truck
52-Single Unit Short-haul Truck
53-Single Unit Long-haul Truck
61-Combination Short-haul Truck
I 62-Combination Long-haul Truck
MOVES Fuel Type
1-Gasoline
| 2-Diesel
I 3-CNG
MOVES Emission Process
| 1-Running Exhaust
| 2-Starts Exhaust
| 11-Evap: Permeation
| 12-Evap: Vapor Venting
13-Evap: Fuel Leaks
18-Refueling: Vapor Loss
| 19-Refueling: Spillage
90-Extended Idle Exhaust
I 91-Diesel APU Exhaust
CY 2035
CY 2045
CY 2055
Figure 4-14 Downstream VOC reductions from the final standards by regulatory class, source type, fuel type,
and emission process for calendar years (CY) 2035, 2045, and 2055
604
-------
The detailed emission reductions of VOC are representative of reductions for air toxics, such
as benzene, formaldehyde, and 1,3-butadiene. Most heavy-duty VOC emissions come from
gasoline vehicles. VOC emissions occur during gasoline combustion while a vehicle is running
or starting (especially during starts before emission controls are fully effective), evaporation
while a vehicle is parked, or evaporation while a vehicle is refueling. As a result, we project a
significant portion of VOC emissions reductions will result from ZEVs displacing HD gasoline
vehicles, which are mostly light HD vehicles such as delivery trucks or gasoline buses. VOCs
can also be emitted from diesel or CNG combustion and refueling (especially when fuel is
spilled), so we project some VOC reductions can also be attributed to ZEVs displacing HD diesel
vehicles.
In summary, we model that the displacement of HD ICE vehicles of all fuel types with HD
ZEVs under the potential compliance pathway will drive broad emission reductions—we expect
the displacement of diesel HD vehicles will be the primary source of NOx reductions; we project
the displacement of gasoline light HD trucks will be the primary source of PM2.5 and VOC
reductions; and we anticipate the displacement of HD CNG vehicles will be the primary source
of methane reductions.
We project smaller emission reductions in this final rule analysis than we projected in the
NPRM because of the increased ZEV adoption in the reference case. Our increased reference
case ZEV adoption is greatest for light heavy-duty vehicles, which means LHD gasoline vehicles
make up a much smaller portion of the HD fleet in the final reference case than in our NPRM
reference case. Therefore, emissions reductions for pollutants which are driven by emissions
from gasoline vehicles, most notably PM2.5 and VOCs, are much smaller in our final rule analysis
than our NPRM analysis.
4.4 National Upstream Emission Inventory Impacts of the Final Standards
While we expect that downstream emissions reductions will result from increased adoption of
HD ZEVs in the final standards, we expect the final standards will increase emissions from
electricity generation units (EGUs) under our potential compliance pathway because the energy
to operate ZEVs comes from electricity. We also estimate that the final emission standards will
reduce demand for liquid fuel and reduce emissions from refineries.
EGU emissions estimates are based on IPM output as described in Chapter 4.2.4. IPM
produces emissions estimates for a more limited set of pollutants than MOVES. We have IPM
estimates for NOx, PM2.5, VOC, and SO2 emissions only, so we do not present the larger set of
criteria and air toxic pollutants in this analysis like we did for downstream emissions. MOVES
and IPM estimate emissions for an identical set of GHGs, including carbon dioxide, methane,
and nitrous oxide. Our estimates of refinery emissions include the same set of criteria pollutants
and GHGs as our EGU estimates.
As discussed in Chapter 4.2.4, the methodology used to estimate EGU and refinery emissions
cannot estimate a total EGU emissions inventory for the reference scenario. Therefore, relative
comparisons between the reference and the control scenarios (e.g., percent changes) are not
possible and only the emissions impacts in absolute tons from the final standards are presented.
605
-------
4.4.1 Analysis Year Impacts
Our estimates of the changes in GHG emissions from EGUs due to the final standards,
relative to the reference case, are presented below in Table 4-21 for calendar years 2035, 2045,
and 2055, in million metric tons (MMT). Our estimates for additional criteria pollutant emissions
are presented in Table 4-22.
Table 4-21 Annual GHG emission increases from EGUs from the final standards in calendar years (CYs)
2035,2045, and 2055
Pollutant
100-year
GWP
Additional EGU Emissions (MMT)
CY 2035
CY 2045
CY 2055
Carbon Dioxide (CO2)
1
29.3
14.5
12.9
Methane (CH4)
28
0.00186
0.00033
0.00026
Nitrous Oxide (N20)
265
0.00026
0.00004
0.00003
CO2 Equivalent (CC>2e)
—
29.4
14.5
12.9
Table 4-22 Annual criteria pollutant emission increases from EGUs from the final standards in calendar
years (CYs) 2035,2045, and 2055
Pollutant
Increase in EGU Emissions (U.S. Tons)
CY 2035
CY 2045
CY 2055
Nitrogen Oxides (NOx)
9,719
1,588
1,520
Primary PM2 5
1,418
596
513
Volatile Organic Compounds (VOC)
467
347
196
Sulfur Dioxide (SO2)
11,726
648
69
In 2055, we estimate the final standards will increase EGU emissions of CO2 by 12.9 million
metric tons, compared to 29.3 million metric tons in 2035. There are similar trends for all other
pollutants. EGU impacts decrease over time because of changes in the projected power
generation mix as electricity generation uses less fossil fuels.
We expect the final standards to lead to a decrease in refinery emissions. Table 4-23 presents
the estimated impacts of the final standards on refinery GHG emissions (in metric tons) from
refineries and Table 4-24 presents the estimated impacts on refinery criteria pollutant emissions
(in U.S. tons), both relative to the reference case.
Table 4-23 Annual GHG emission reductions from refineries from the final standards in calendar years
(CYs) 2035,2045, and 2055
Pollutant
100-year
Refinery Emission Reductions (Metric Tons)
GWP
CY 2035
CY 2045
CY 2055
Carbon Dioxide (CO2)
1
331,008
649,943
690,477
Methane (CH4)
28
17
32
34
Nitrous Oxide (N20)
265
3
6
6
CO2 Equivalent (C02e)
—
332,240
652,343
693,016
606
-------
Table 4-24 Annual criteria pollutant emission reductions from refineries from the final standards in calendar
years (CYs) 2035,2045, and 2055
Pollutant
Refinery Emission Reductions (U.S. Tons)
CY 2035
CY 2045
CY 2055
Nitrogen Oxides (NOx)
148
288
304
Primary PM2 5
34
66
70
Volatile Organic Compounds (VOC)
112
216
226
Sulfur Dioxide (SO2)
46
89
94
4.4.2 Year-over-year Impacts
We estimated emission impacts for two upstream sectors - electricity generation and fuel
refining. In general, the year-over-year emission impact of the final standards on either sector
depends on two factors. The first factor is how each sector would be impacted by an increase in
HD ZEVs from our potential compliance pathway in modeling the final standards, and the
second is how the emissions of each sector are expected to change in the future independent of
the final standards. The two factors lead to different trends for EGUs and refineries.
We expect the increase in HD ZEV adoption to cause greater electricity demand and a lower
demand for refined fuels, therefore causing an increase in EGU emissions and a decrease in
refinery emissions. MOVES models a monotonic increase in the number of HD ZEVs in the
vehicle fleet from 2027 through 2055, so we should expect the emission impacts for both sectors
to grow in magnitude over time.
Simultaneous with these impacts, the power sector is expected to shift the power generation
mix away from fossil fuel combustion in favor of renewable energy sources, therefore leading to
a decrease in emissions per unit of energy demand overall. This can be seen in Table 4-1 lfrom
Chapter 4.2.4.2. Fuel refining, on the other hand, has much more stable emission factors, as can
be seen in Table 4-14 and Table 4-15 from Chapter 4.2.5.
Because of these differences, we expect to see EGU emission impacts that show both a trend
of increasing electrification and a decrease in emissions as renewable adoption increases.
Refinery emission impacts, on the other hand, are much more closely correlated with the trend of
increasing electrification.
Our estimates of year-over-year emission impacts of the final standards on GHG emissions
from EGUs are presented in Table 4-25, Table 4-26, and Figure 4-15. Table 4-25 presents the
impacts on methane and nitrous oxide emissions in metric tons, Table 4-26 presents the impacts
on CO2 and total C02e emissions in million metric tons. Figure 4-15 presents the impacts
graphically, with emission reductions of all three GHGs presented in terms of CO2 equivalency.
607
-------
Table 4-25 Year-over-year EGU emission increases from the final standards for CH4 and N2O
Calendar
Year
EGU Emissions Increase (Metric Tons)
Methane (CH4)
Nitrous Oxide (N2O)
2027
16
2
2028
42
6
2029
79
11
2030
170
23
2031
372
51
2032
751
103
2033
1,127
155
2034
1,499
206
2035
1,863
256
2036
1,869
257
2037
1,753
241
2038
1,523
210
2039
1,190
164
2040
768
106
2041
713
97
2042
640
86
2043
550
72
2044
448
56
2045
334
38
2046
322
36
2047
307
34
2048
291
32
2049
273
29
2050
256
27
2051
258
27
2052
259
27
2053
260
27
2054
260
27
2055
261
27
608
-------
Table 4-26 Year-over-year EGU emission increases from the final standards for CO2 and CChe
Calendar
Year
EGU Emissions Increase (Million Metric Tons)
Carbon Dioxide (CO2)
CO2 Equivalent (CChe)
2027
0.3
0.3
2028
0.7
0.7
2029
1.2
1.2
2030
2.7
2.7
2031
5.8
5.9
2032
11.8
11.8
2033
17.7
17.8
2034
23.5
23.6
2035
29.3
29.4
2036
29.0
29.1
2037
26.7
26.8
2038
22.5
22.6
2039
16.6
16.7
2040
9.3
9.4
2041
10.4
10.5
2042
11.5
11.6
2043
12.6
12.6
2044
13.6
13.6
2045
14.5
14.5
2046
14.2
14.3
2047
13.9
13.9
2048
13.5
13.5
2049
13.1
13.1
2050
12.7
12.7
2051
12.8
12.8
2052
12.8
12.8
2053
12.9
12.9
2054
12.9
12.9
2055
12.9
12.9
609
-------
Pollutant
— Total GHG
— co2
— ch4
— n2o
2030
2040
Calendar Year
2050
Figure 4-15 Yearly GHG emissions increase from EGUs from the final standards from 2027 through 2055
Almost all GHG emission increases from EGUs are driven by increases in CO2 specifically,
which represents more than 99 percent of the total increase in total GHG emissions.
Our estimates of year-over-year emission impacts of the final standards on criteria pollutant
emissions from EGUs are presented in Table 4-27 and Figure 4-16.
610
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Table 4-27 Year-over-year EGU emission inventory increases for criteria pollutants from the final standards
Calendar
Year
EGU Emissions Increase (U.S. Tons)
NOx
voc
PM2S
SO2
2027
83
4
12
100
2028
220
11
32
265
2029
412
20
60
497
2030
887
43
129
1,071
2031
1,941
93
283
2,342
2032
3,915
188
571
4,724
2033
5,876
282
857
7,089
2034
7,818
375
1,140
9,432
2035
9,719
467
1,418
11,726
2036
9,541
463
1,413
11,362
2037
8,661
427
1,312
10,106
2038
7,133
362
1,122
8,030
2039
5,025
269
852
5,220
2040
2,411
153
513
1,771
2041
2,331
190
540
1,623
2042
2,204
229
562
1,431
2043
2,033
269
579
1,200
2044
1,825
308
590
936
2045
1,588
347
596
648
2046
1,582
320
583
542
2047
1,567
290
566
428
2048
1,544
258
546
310
2049
1,518
226
525
190
2050
1,494
193
505
68
2051
1,504
194
508
68
2052
1,511
195
510
68
2053
1,516
196
512
69
2054
1,519
196
513
69
2055
1,520
196
513
69
611
-------
12000 -
C/)
c
o
C0
3
0
w
03
0
C/)
C
o
E
LD
3
O
LLI
9000 -
o 6000 -
3000 -
Pollutant
— S02
NOx
— PM2.s
VOC
2030
2040
Calendar Year
2050
Figure 4-16 Yearly criteria pollutant emissions increase from EGUs from the final standards from 2027
through 2055
From 2027 through the 2030s, EGU emission increases are expected to start small and grow
as HD ZEV adoption drives greater increases in energy demand. All four criteria pollutants see
their largest increase in EGU emissions in 2035. But through the 2030s and 2040s, a substantial
increase in the use of renewable energy sources is expected to take place in the national power
generation mix, driven in part by the IRA. This is expected to lead to decreases in EGU
emissions at a national level, including a decrease in EGU emissions attributable to HD ZEVs
and the final standards.
Table 4-28 and Figure 4-17 present the year-over-year GHG emission reductions from
refineries, in metric tons. Figure 4-17 presents all GHG impacts in CO2 equivalent terms. Similar
to EGUs, CO2 represents over 99 percent of the impact of GHG emissions from refineries from
the final standards.
612
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Table 4-28 Year-over-year refinery GHG emission reductions from the final standards
Calendar
Year
Refinery Emissions Reduction (Metric Tons)
CO2
CH4
N2O
CO2 Equivalent
2027
9,858
0.5
0.1
9,896
2028
20,579
1.1
0.2
20,657
2029
32,140
1.7
0.3
32,262
2030
48,141
2.6
0.4
48,322
2031
86,429
4.5
0.7
86,753
2032
152,984
7.9
1.3
153,556
2033
216,373
11.2
1.9
217,180
2034
276,137
14.2
2.4
277,166
2035
331,008
16.9
2.9
332,240
2036
381,401
19.5
3.3
382,819
2037
427,812
21.8
3.7
429,402
2038
469,665
23.8
4.1
471,409
2039
507,369
25.7
4.4
509,253
2040
541,395
27.4
4.7
543,403
2041
571,840
28.9
4.9
573,959
2042
598,023
30.1
5.2
600,237
2043
619,458
31.1
5.4
621,749
2044
636,560
31.9
5.5
638,912
2045
649,943
32.5
5.6
652,343
2046
662,267
33.0
5.7
664,710
2047
671,612
33.4
5.8
674,089
2048
677,775
33.6
5.9
680,272
2049
683,220
33.8
5.9
685,736
2050
689,802
34.1
6.0
692,340
2051
692,111
34.2
6.0
694,658
2052
693,247
34.2
6.0
695,797
2053
693,335
34.2
6.0
695,885
2054
692,406
34.2
6.0
694,953
2055
690,477
34.1
6.0
693,016
613
-------
2030 2040 2050
Calendar Year
Figure 4-17 Yearly GHG emissions reductions from refineries from the final standards from 2027 through
2055
Table 4-29 and Figure 4-18 present the year-over-year criteria pollutant emission reductions
from refineries from the final standards.
614
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Table 4-29 Year-over-year refinery criteria pollutant emission reductions from the final standards
Calendar
Year
Refinery Emissions Reductions (U.S. Tons)
NOx
voc
PM2S
SO2
2027
5
3
1
1
2028
10
7
2
3
2029
15
11
3
5
2030
22
16
5
7
2031
39
29
9
12
2032
69
52
16
21
2033
97
73
23
30
2034
124
93
29
38
2035
148
112
34
46
2036
170
129
39
53
2037
191
144
44
59
2038
209
158
48
65
2039
226
171
52
70
2040
241
182
56
75
2041
255
192
59
79
2042
266
200
61
82
2043
275
207
64
85
2044
282
212
65
87
2045
288
216
66
89
2046
293
219
68
90
2047
297
222
68
92
2048
299
223
69
92
2049
301
225
69
93
2050
304
226
70
94
2051
305
227
70
94
2052
305
227
70
94
2053
305
227
70
94
2054
305
227
70
94
2055
304
226
70
94
615
-------
0
Pollutant
— so2
— PM2.5
voc
NOx
2030
2040
Calendar Year
2050
Figure 4-18 Yearly criteria pollutant emissions reductions from refineries from the final standards from 2027
through 2055
We estimate that refinery emission reductions start small in 2027 and grow through 2055.
Unlike for EGUs, we do not anticipate a meaningful change in the emission rates related to the
refining process, so refinery emission reductions are much more tightly correlated with the
modeled drop in liquid fuel demand as HD ZEVs make up an increasing proportion of the
national heavy-duty fleet.
4.5 Net Emissions Impacts of the Final Standards
While we present a net emissions impact of the final CO2 emission standards, it is important
to note that some upstream emission sources are not included in the estimates. As discussed in
Chapter 4.1, we received several comments on the upstream sources considered in our analysis.
Our estimates of upstream EGU and refinery emission impacts also depend on assumptions that
we made in our analysis, as discussed in Chapter 4.2.2. Therefore, we present emission impact
estimates for various other sensitivity analyses in Chapters 4.8 and 4.9.
4.5.1 Analysis Year Impacts
Table 4-30 shows a summary of our modeled downstream, upstream, and net GHG emission
impacts of the final standards relative to the reference case, in million metric tons, for calendar
years 2035, 2045, and 2055. Table 4-31 contains a summary of the modeled net impacts of the
final standards on criteria pollutant emissions.
616
-------
Table 4-30 Annual net impactsA on GHG emissions from the final standards in calendar years (CYs) 2035,
2045, and 2055
Pollutant
GWP
Calendar
Year
Emission Impact (MMT)
Downstream
EGU
Refinery
Net
Carbon Dioxide (CO2)
1
2035
-32.5
29.3
-0.3
-3.5
2045
-66.3
14.5
-0.6
-52.4
2055
-70.0
12.9
-0.7
-57.8
Methane (CH4)
28
2035
-0.002
0.002
0.000
0.000
2045
-0.006
0.000
0.000
-0.006
2055
-0.010
0.000
0.000
-0.009
Nitrous Oxide (N2O)
265
2035
-0.005
0.000
0.000
-0.005
2045
-0.010
0.000
0.000
-0.010
2055
-0.010
0.000
0.000
-0.010
CO: Equivalent (C02e)
—
2035
-33.8
29.4
-0.3
-4.7
2045
-69.1
14.5
-0.7
-55.2
2055
-73.0
12.9
-0.7
-60.8
A We present emissions reductions as negative numbers and emission increases as positive numbers.
Table 4-31 Annual net impactsA on criteria pollutant emissions from the final standards in calendar years
(CYs) 2035,2045, and 2055
Pollutant
Calendar
Year
Emission Impact (U.S. Tons)
Downstream
EGU
Refinery
Net
Nitrogen Oxides (NOx)
2035
-10,801
9,719
-148
-1,230
2045
-47,027
1,588
-288
-45,728
2055
-54,268
1,520
-304
-53,051
Particulate Matter
(PM2.5)
2035
-126
1,418
-34
1,258
2045
-302
596
-66
227
2055
-331
513
-70
113
Volatile Organic
Compounds (VOC)
2035
-3,014
467
-112
-2,659
2045
-6,426
347
-216
-6,295
2055
-7,242
196
-226
-7,272
Sulfur Dioxide (SO2)
2035
-126
11,726
-46
11,554
2045
-256
648
-89
304
2055
-270
69
-94
-295
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
In 2055, we estimate the final standards will result in a net decrease of 61 million metric tons
of GHG emissions. We also estimate net decreases in emissions of NOx, VOC, and SO2 in 2055.
However, we estimate a net increase in PM2.5 emissions.
In general, net emission impacts are determined by the interaction of two effects. First, HD
ZEV adoption increases over time, thus reducing downstream and refinery emissions. Second,
the increase in EGU emissions declines over time as the electricity grid becomes cleaner due to
EGU regulations and the future power generation mix changes, in part driven by the IRA. These
effects can balance differently for different pollutants.
Downstream emissions are a more significant source of GHG, NOx, and VOC emissions, so
net reductions grow over time. However, EGUs are a more significant source of SO2 emissions
617
-------
(largely driven by coal combustion) and PM2.5 emissions (largely driven by coal and natural gas
combustion). We estimate a net increase in SO2 emissions in 2035 and 2045 but a net decrease in
2055 as coal is phased out of the electricity sector. Natural gas remains an important fuel for
electricity generation, which is why we estimate a net increase in PM2.5 in all years. However,
consistent with the trends for other pollutants, the magnitude of the PM2.5 emission increases
diminish over time.
4.5.2 Year-over-year Impacts
Table 4-32 and Table 4-33 show our estimated year-over-year net GHG emission impacts
from the final standards. Table 4-32 presents estimates for methane and nitrous oxide in metric
tons and Table 4-33 presents the estimates for carbon dioxide and total GHG emission, in terms
of CO2 equivalency, in million metric tons. Figure 4-19 shows the net GHG impacts for CO2
equivalent total GHG emissions.
Table 4-32 Year-over-year net emission impactsA of the final standards on emissions of CH4 and N2O, in
metric tons
Calendar
Year
CH4 Impacts (Metric Tons)
N2O Impacts (Metric Tons)
Downstream
EGU
Refinery
Net
Downstream
EGU
Refinery
Net
2027
-22
16
-1
-6
-57
2
0
-55
2028
-85
42
-1
-44
-147
6
0
-142
2029
-152
79
-2
-75
-269
11
0
-259
2030
-238
170
-3
-70
-508
23
0
-485
2031
-432
372
-5
-65
-1,038
51
-1
-987
2032
-763
751
-8
-20
-1,995
103
-1
-1,893
2033
-1,088
1,127
-11
28
-2,938
155
-2
-2,785
2034
-1,451
1,499
-14
33
-3,860
206
-2
-3,656
2035
-1,803
1,863
-17
44
-4,741
256
-3
-4,488
2036
-2,156
1,869
-19
-306
-5,552
257
-3
-5,298
2037
-2,584
1,753
-22
-853
-6,299
241
-4
-6,062
2038
-3,094
1,523
-24
-1,595
-6,973
210
-4
-6,767
2039
-3,577
1,190
-26
-2,413
-7,578
164
-4
-7,419
2040
-4,033
768
-27
-3,292
-8,123
106
-5
-8,022
2041
-4,461
713
-29
-3,777
-8,610
97
-5
-8,518
2042
-4,873
640
-30
-4,263
-9,030
86
-5
-8,949
2043
-5,264
550
-31
-4,745
-9,375
72
-5
-9,308
2044
-5,637
448
-32
-5,221
-9,646
56
-6
-9,596
2045
-5,992
334
-32
-5,690
-9,849
38
-6
-9,816
2046
-6,345
322
-33
-6,056
-10,009
36
-6
-9,978
2047
-6,688
307
-33
-6,415
-10,118
34
-6
-10,090
2048
-7,024
291
-34
-6,767
-10,181
32
-6
-10,155
2049
-7,371
273
-34
-7,132
-10,229
29
-6
-10,206
2050
-7,735
256
-34
-7,513
-10,295
27
-6
-10,274
2051
-8,085
258
-34
-7,861
-10,345
27
-6
-10,324
2052
-8,432
259
-34
-8,208
-10,383
27
-6
-10,362
2053
-8,783
260
-34
-8,558
-10,409
27
-6
-10,387
2054
-9,139
260
-34
-8,912
-10,421
27
-6
-10,400
2055
-9,497
261
-34
-9,271
-10,422
27
-6
-10,401
A We present emissions reductions as negative numbers and emission increases as positive numbers.
618
-------
Table 4-33 Year-over-year net emission impactsA of the final standards on CO2 emissions and CChe
emissions, in million metric tons (MMT)
Calendar
Year
CO2 Impacts (MMT)
CChe Impacts (MMT)
Downstream
EGU
Refinery
Net
Downstream
EGU
Refinery
Net
2027
-0.5
0.2
0.0
-0.3
-0.5
0.2
0.0
-0.3
2028
-1.2
0.7
0.0
-0.6
-1.3
0.7
0.0
-0.6
2029
-2.1
1.2
0.0
-0.9
-2.2
1.2
0.0
-1.0
2030
-3.8
2.7
0.0
-1.1
-3.9
2.7
0.0
-1.3
2031
-7.4
5.8
-0.1
-1.7
-7.7
5.9
-0.1
-1.9
2032
-14.0
11.8
-0.2
-2.4
-14.5
11.8
-0.2
-2.9
2033
-20.4
17.7
-0.2
-2.9
-21.2
17.8
-0.2
-3.7
2034
-26.6
23.5
-0.3
-3.3
-27.7
23.6
-0.3
-4.3
2035
-32.5
29.3
-0.3
-3.5
-33.8
29.4
-0.3
-4.7
2036
-37.9
29.0
-0.4
-9.2
-39.4
29.1
-0.4
-10.6
2037
-42.8
26.7
-0.4
-16.5
-44.6
26.8
-0.4
-18.2
2038
-47.3
22.5
-0.5
-25.2
-49.2
22.6
-0.5
-27.1
2039
-51.3
16.6
-0.5
-35.2
-53.4
16.7
-0.5
-37.2
2040
-54.9
9.3
-0.5
-46.1
-57.2
9.4
-0.5
-48.4
2041
-58.1
10.4
-0.6
-48.3
-60.5
10.5
-0.6
-50.6
2042
-60.9
11.5
-0.6
-50.0
-63.4
11.6
-0.6
-52.5
2043
-63.2
12.6
-0.6
-51.2
-65.8
12.6
-0.6
-53.8
2044
-64.9
13.6
-0.6
-52.0
-67.7
13.6
-0.6
-54.7
2045
-66.3
14.5
-0.6
-52.4
-69.1
14.5
-0.7
-55.2
2046
-67.3
14.2
-0.7
-53.7
-70.2
14.3
-0.7
-56.6
2047
-68.1
13.9
-0.7
-54.8
-70.9
13.9
-0.7
-57.7
2048
-68.5
13.5
-0.7
-55.6
-71.4
13.5
-0.7
-58.5
2049
-68.8
13.1
-0.7
-56.4
-71.7
13.1
-0.7
-59.3
2050
-69.2
12.7
-0.7
-57.2
-72.2
12.7
-0.7
-60.2
2051
-69.5
12.8
-0.7
-57.5
-72.5
12.8
-0.7
-60.4
2052
-69.8
12.8
-0.7
-57.7
-72.8
12.8
-0.7
-60.6
2053
-69.9
12.9
-0.7
-57.8
-73.0
12.9
-0.7
-60.8
2054
-70.0
12.9
-0.7
-57.8
-73.0
12.9
-0.7
-60.8
2055
-70.0
12.9
-0.7
-57.8
-73.0
12.9
-0.7
-60.8
A We present emissions reductions as negative numbers and emission increases as positive numbers.
619
-------
Calendar Year
Figure 4-19 Year-over-year net CO2 emission impacts of the final standards from 2027 through 2055
In terms of GHG emissions, refinery emission impacts are small compared to EGUs and
downstream emissions impacts. The downstream emission reductions are larger than the increase
in EGU emissions in all years.
Table 4-34, Figure 4-20, and Figure 4-21 show our estimates for the net impact of the final
standards on emissions of nitrogen oxides and volatile organic compounds.
620
-------
Table 4-34 Year-over-year net emission impactsA of the final standards on NOx and VOC emissions, in U.S.
tons
Calendar
Year
NOx Impacts (U.S. Tons)
VOC Impacts (U.S. Tons)
Downstream
EGU
Refinery
Net
Downstream
EGU
Refinery
Net
2027
-146
83
-5
-68
-87
4
-3
-87
2028
-361
220
-10
-151
-189
11
-7
-186
2029
-632
412
-15
-235
-302
20
-11
-293
2030
-1,096
887
-22
-230
-452
43
-16
-426
2031
-2,151
1,941
-39
-249
-798
93
-29
-734
2032
-4,060
3,915
-69
-214
-1,380
188
-52
-1,243
2033
-5,984
5,876
-97
-206
-1,956
282
-73
-1,747
2034
-8,156
7,818
-124
-462
-2,502
375
-93
-2,220
2035
-10,801
9,719
-148
-1,230
-3,014
467
-112
-2,659
2036
-14,190
9,541
-170
-4,819
-3,497
463
-129
-3,162
2037
-18,253
8,661
-191
-9,783
-3,975
427
-144
-3,692
2038
-23,298
7,133
-209
-16,374
-4,444
362
-158
-4,240
2039
-27,990
5,025
-226
-23,192
-4,858
269
-171
-4,760
2040
-32,356
2,411
-241
-30,186
-5,222
153
-182
-5,251
2041
-36,284
2,331
-255
-34,208
-5,543
190
-192
-5,544
2042
-39,794
2,204
-266
-37,856
-5,830
229
-200
-5,801
2043
-42,704
2,033
-275
-40,946
-6,069
269
-207
-6,007
2044
-45,101
1,825
-282
-43,558
-6,268
308
-212
-6,171
2045
-47,027
1,588
-288
-45,728
-6,426
347
-216
-6,295
2046
-48,634
1,582
-293
-47,345
-6,562
320
-219
-6,462
2047
-49,890
1,567
-297
-48,619
-6,689
290
-222
-6,621
2048
-50,809
1,544
-299
-49,564
-6,782
258
-223
-6,747
2049
-51,597
1,518
-301
-50,380
-6,861
226
-225
-6,860
2050
-52,379
1,494
-304
-51,188
-6,935
193
-226
-6,969
2051
-53,003
1,504
-305
-51,804
-7,016
194
-227
-7,049
2052
-53,490
1,511
-305
-52,284
-7,101
195
-227
-7,133
2053
-53,857
1,516
-305
-52,646
-7,166
196
-227
-7,198
2054
-54,120
1,519
-305
-52,906
-7,213
196
-227
-7,244
2055
-54,268
1,520
-304
-53,051
-7,242
196
-226
-7,272
A We present emissions reductions as negative numbers and emission increases as positive numbers.
621
-------
05
E -20000
-40000
Emissions Source
— Downstream
— EGU
— Refinery
— Net
2030
2040
Calendar Year
2050
Figure 4-20 Year-over-year net NOx emission impacts of the final standards from 2027 through 2055
622
-------
1 1 1
2030 2040 2050
Calendar Year
Figure 4-21 Year-over-year net VOC emission impacts of the final standards from 2027 through 2055
Like greenhouse gases, the refinery emission impacts of the final standards on NOx and VOC
emissions are small compared to the EGU and downstream impacts. Downstream emission
reductions are greater than the increase in EGU emissions for all years.
Table 4-35, Figure 4-22, and Figure 4-23 show our estimates for the net impact of the final
standards on emissions of particulate matter and sulfur dioxide.
623
-------
Table 4-35 Year-over-year net emission impactsA of the final standards on emissions of particulate matter
and SO2 in U.S. tons
Calendar
Year
PM2.5 Impacts (U.S. Tons)
SO2 Impacts (U.S. Tons)
Downstream
EGU
Refinery
Net
Downstream
EGU
Refinery
Net
2027
-4
12
-1
7
-2
100
-1
96
2028
-8
32
-2
22
-5
265
-3
257
2029
-12
60
-3
44
-9
497
-5
483
2030
-18
129
-5
106
-15
1,071
-7
1,049
2031
-33
283
-9
241
-30
2,342
-12
2,300
2032
-57
571
-16
498
-55
4,724
-21
4,647
2033
-80
857
-23
754
-80
7,089
-30
6,980
2034
-103
1,140
-29
1,009
-104
9,432
-38
9,290
2035
-126
1,418
-34
1,258
-126
11,726
-46
11,554
2036
-150
1,413
-39
1,224
-147
11,362
-53
11,162
2037
-173
1,312
-44
1,095
-166
10,106
-59
9,881
2038
-196
1,122
-48
878
-183
8,030
-65
7,782
2039
-217
852
-52
583
-199
5,220
-70
4,951
2040
-236
513
-56
221
-212
1,771
-75
1,484
2041
-254
540
-59
227
-225
1,623
-79
1,320
2042
-270
562
-61
230
-235
1,431
-82
1,114
2043
-283
579
-64
232
-244
1,200
-85
871
2044
-294
590
-65
230
-251
936
-87
598
2045
-302
596
-66
227
-256
648
-89
304
2046
-309
583
-68
206
-260
542
-90
191
2047
-315
566
-68
183
-263
428
-92
74
2048
-319
546
-69
158
-264
310
-92
-47
2049
-322
525
-69
134
-266
190
-93
-169
2050
-325
505
-70
110
-267
68
-94
-293
2051
-327
508
-70
111
-269
68
-94
-294
2052
-329
510
-70
111
-269
68
-94
-295
2053
-330
512
-70
111
-270
69
-94
-296
2054
-331
513
-70
112
-270
69
-94
-295
2055
-331
513
-70
113
-270
69
-94
-295
A We present emissions reductions as negative numbers and emission increases as positive numbers.
624
-------
1500i
1000 -
500 -
Emissions Source
— Downstream
— EGU
— Refinery
— Net
2030
2040
Calendar Year
2050
Figure 4-22 Year-over-year net PM2.5 emission impacts of the final standards from 2027 through 2055
625
-------
12000 -
9000 -
W
D
0!
Q.
E
to
tz
o
'
-------
Table 4-36 Cumulative 2027-2055 downstream heavy-duty GHG emission reductions from the final standards
Pollutant
Reduction in MMT
Percent
Carbon Dioxide (CO2)
1,347
13%
Methane (CH4)
0.127
7%
Nitrous Oxide (N20)
0.199
13%
CO2 Equivalent (CC>2e)
1,404
13%
Table 4-37 Cumulative 2027-2055 GHG emission increases from EGUs from the final standards
Pollutant
Increase in MMT
Carbon Dioxide (CO2)
391.4
Methane (CH4)
0.018
Nitrous Oxide (N20)
0.002
CO2 Equivalent (C02e)
392.5
Table 4-38 Cumulative 2027-2055 GHG emission reductions from refineries from the final standards
Pollutant
Reduction in MMT
Carbon Dioxide (CO2)
13.4
Methane (CH4)
0.0007
Nitrous Oxide (N20)
0.0001
CO2 Equivalent (C02e)
13.5
Overall, we estimate the final standards will reduce net GHG emissions by just over 1 billion
metric tons between 2027 and 2055, relative to the reference case, as is presented in Table 4-39.
Table 4-39 Cumulative 2027-2055 net GHG emission impactsA (in MMT) reflecting the final standards
Pollutant
Downstream
EGU
Refineries
Net
Carbon Dioxide (CO2)
-1,347
391
-13
-969
Methane (CH4)
-0.127
0.018
-0.001
-0.109
Nitrous Oxide (N20)
-0.199
0.002
0.000
-0.197
CO2 Equivalent (C02e)
-1,404
393
-13
-1,025
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
4.7 Comparison Between the Final Standards and the Alternative
The alternative has both a less aggressive phase-in of emissions standards from 2027 through
2031 and a less stringent ending standard for model years 2032 and beyond. Both the final
standards and alternative were modeled in MOVES4.R3 by increasing ZEV adoption of HD
vehicles, which means we model the alternative as displacing fewer ICE vehicles with ZEVs as
compared to the final standards (under their respective potential compliance pathways). In
general, we expect the alternative to have lower downstream emission reductions, lower
upstream EGU emission increases, and lower refinery emission reductions when compared to the
final standards.
627
-------
4.7.1 Downstream Emission Inventory Comparison
Our estimates of the downstream emission reductions of GHGs that would result from the
alternative relative to the reference case are presented in Table 4-40 for calendar years 2035,
2045, and 2055.
Table 4-40 Annual downstream HD GHG emission reductions from the alternative in calendar years (CY)
2035,2045, and 2055
Pollutant
100-
year
GWP
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Carbon Dioxide (CO2)
1
12.9
3%
21.9
6%
20.7
6%
Methane (CH4)
28
0.001
1%
0.001
2%
0.002
3%
Nitrous Oxide (N20)
265
0.002
4%
0.003
7%
0.003
6%
CO2 Equivalent (CC>2e)
—
13.4
3%
22.8
6%
21.6
6%
Our estimated GHG emission reductions for the alternative are lower than for the final
standards (see Table 4-16). In 2055, we estimate that the alternative would reduce emissions of
CO2 by 6 percent (the final standards estimate is 20 percent), methane by 3 percent (the final
standards estimate is 12 percent), and N2O by 6 percent (the final standards estimate is 20
percent). The resulting total GHG reduction, in C02e, is 6 percent for the alternative versus 20
percent for the final standards.
We modeled an increase in the use of zero-emission technologies to meet the CO2 emission
standards for both the final standards and the alternative under their respective potential
compliance pathways. Therefore, we also project that downstream emission reductions of criteria
pollutants and air toxics would result from the alternative, as presented in Table 4-41.
Table 4-41 Annual downstream HD criteria pollutant and air toxic emission reductions from the alternative
in calendar years (CYs) 2035,2045, and 2055
Pollutant
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
U.S. Tons
Percent
U.S. Tons
Percent
U.S. Tons
Percent
Nitrogen Oxides (NOx)
4,491
1%
17,310
6%
18,107
7%
Particulate Matter (PM2 5)A
46
1%
74
1%
62
1%
Volatile Organic
Compounds (VOC)
1,118
2%
1,557
4%
1,398
4%
Sulfur Dioxide (SO2)
49
3%
82
6%
77
6%
Carbon Monoxide (CO)
18,388
2%
31,733
5%
29,995
4%
1,3-Butadiene
2
4%
2
3%
0
1%
Acetaldehyde
22
2%
31
4%
29
3%
Benzene
13
3%
10
3%
3
1%
Formaldehyde
14
1%
23
3%
25
3%
Naphthalene0
1
2%
1
4%
1
3%
A PM2.5 estimates include both exhaust and non-exhaust emissions.
B Naphthalene includes both gas and particle phase emissions.
Once again, the estimated emission reductions in criteria pollutants and air toxics that would
result from the alternative are smaller than those estimated to result from the final standards (see
628
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Table 4-17). For example, in 2055, we estimate the alternative would reduce NOx emissions by 7
percent, PM2.5 emissions by 1 percent, and VOC emissions by 4 percent. This is compared to
reductions of NOx by 20 percent, PM2.5 by 5 percent, and VOC by 20 percent for the final
standards. Estimated reductions in emissions for air toxics from the alternative range from 1
percent for benzene (the final standards estimate is 25 percent) to 3 percent for formaldehyde
(the final standards estimate is 15 percent).
The year-over-year downstream emission trends of the alternative would be similar to the
trends presented for the final standards in Chapter 4.3.2. The detailed discussion of the impacts
of the final standards presented in Chapter 4.3.3, including the detailed breakdowns of emission
reductions by fuel type, source type, regulatory class, and emissions process also applies to the
alternative. However, in all cases, the magnitude of the emission impacts would be smaller for
the alternative than for the final standards. Therefore, we do not present this detailed information
and discussion for the alternative here.
Figure 4-24 shows the year-over-year inventory of total HD GHG emissions (C02e) in the
reference case as well as for the final standards and alternative. It shows that the slower phase-in
and lower ending standards of the alternative would result in lower overall GHG reductions
compared to the final standards.
5 3e-04 -
2
o
> 2e-04 -
_c
0
(N
o
o
1e-04 -
0e+00 -
1 1 1—
2030 2040 2050
Calendar Year
— Reference — Final Standards — Alternative
Figure 4-24 Yearly downstream CChe inventory for the reference case, final standards, and alternative from
2027 through 2055
4.7.2 Upstream Emission Inventory Comparison
Our estimates of the additional GHG emissions from EGUs due to the alternative, relative to
the reference case, are presented in Table 4-42 for calendar years 2035, 2045, and 2055, in
629
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million metric tons (MMT). Our estimates for additional criteria pollutant emissions from the
alternative are presented in Table 4-43.
Table 4-42 Annual GHG emission increases from EGUs from the alternative in calendar years (CY) 2035,
2045, and 2055
Pollutant
100-year
GWP
Additional EGU Emissions (MMT)
CY 2035
CY 2045
CY 2055
Carbon Dioxide (CO2)
1
12.4
5.4
4.4
Methane (CH4)
28
0.00079
0.00013
0.00009
Nitrous Oxide (N20)
265
0.00011
0.00001
0.00001
CO2 Equivalent (CC>2e)
—
12.5
5.4
4.4
Table 4-43 Annual criteria pollutant emission increases from EGUs from the alternative in calendar years
(CYs) 2035,2045, and 2055
Pollutant
Additional EGU Emissions (U.S. Tons)
CY 2035
CY 2045
CY 2055
Nitrogen Oxides (NOx)
4,131
594
520
Primary PM2 5
603
223
176
Volatile Organic Compounds (VOC)
198
130
67
Sulfur Dioxide (SO2)
4,984
243
24
Because the alternative has lower ZEV adoption rates under its potential compliance pathway,
we project smaller increases in emissions from EGUs than the final standards (see Table 4-21
and Table 4-22). In 2055, we estimate the alternative would increase EGU emissions of CO2 by
4.4 million metric tons (compared to 12.9 million metric tons from the final standards), with
similar trends for all other pollutants. The EGU impacts decrease over time because of projected
changes in the power generation mix.
Table 4-44 presents the estimated impact of the alternative on GHG emissions from refineries
and Table 4-45 presents the estimated impact of the alternative on criteria pollutant emissions
from refineries, both relative to the reference case.
Table 4-44 Annual GHG emission reductions from refineries due to the alternative in calendar years (CY)
2035,2045, and 2055
Pollutant
100-year
Refinery Emission Reductions (Metric Tons)
GWP
CY 2035
CY 2045
CY 2055
Carbon Dioxide (CO2)
1
118,269
163,781
147,787
Methane (CH4)
28
6
8
7
Nitrous Oxide (N20)
265
1
1
1
CO2 Equivalent (C02e)
—
118,707
164,377
148,320
630
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Table 4-45 Annual criteria pollutant emission reductions from refineries due to the alternative in calendar
years (CYs) 2035,2045, and 2055
Pollutant
Refinery Emission Reductions (U.S. Tons)
CY 2035
CY 2045
CY 2055
Nitrogen Oxides (NOx)
52
70
63
Particulate Matter (PM2 5)
12
16
14
Volatile Organic Compounds (VOC)
40
54
48
Sulfur Dioxide (SO2)
16
22
20
We project smaller reductions in refinery emissions for the alternative than for the final
standards (see Table 4-23and Table 4-24), consistent with our projected impacts for downstream
emissions. We project a reduction of 147,787 metric tons of CO2 for the alternative versus
690,477 metric tons for the final standards. The general comparison of CO2 reductions is
representative of other GHG and criteria pollutants.
As was the case for downstream emissions, the year-over-year emissions impacts trends of the
alternative on both EGUs and refineries would be similar to the impacts presented in Chapter
4.4.2 for the final standards, but smaller in magnitude. Thus, we do not present information
specific to the alternative here.
4.7.3 Net Emission Inventory Comparison
Table 4-46 shows a summary of our modeled downstream, upstream, and net GHG emission
impacts of the alternative relative to the reference case (i.e., the emissions inventory without the
final standards), in million metric tons, for calendar years 2035, 2045, and 2055. Table 4-47
contains a summary of the modeled net impacts of the alternative on criteria pollutant emissions.
Table 4-46 Annual net impactsA on GHG emissions from the alternative in calendar years (CYs) 2035,2045,
and 2055
Pollutant
GWP
Calendar
Year
Emission Impact (MMT)
Downstream
EGU
Refinery
Net
Carbon Dioxide (CO2)
1
2035
-12.9
12.4
-0.1
-0.5
2045
-21.9
5.4
-0.2
-16.6
2055
-20.7
4.4
-0.1
-16.4
Methane (CH4)
28
2035
-0.001
0.001
0.000
0.000
2045
-0.001
0.000
0.000
-0.001
2055
-0.002
0.000
0.000
-0.002
Nitrous Oxide (N2O)
265
2035
-0.002
0.000
0.000
-0.002
2045
-0.003
0.000
0.000
-0.003
2055
-0.003
0.000
0.000
-0.003
CO: Equivalent (C02e)
—
2035
-13.4
12.5
-0.1
-1.0
2045
-22.8
5.4
-0.2
-17.6
2055
-21.6
4.4
-0.1
-17.3
A We present emissions reductions as negative numbers and emission increases as positive numbers.
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Table 4-47 Annual net impactsA on criteria pollutant emissions from the alternative in calendar years (CYs)
2035,2045, and 2055
Pollutant
Calendar
Year
Emission Impact (U.S. Tons)
Downstream
EGU
Refinery
Net
Nitrogen Oxides (NOx)
2035
-4,491
4,131
-52
-413
2045
-17,310
594
-70
-16,786
2055
-18,107
520
-63
-17,650
Particulate Matter
(PM2.5)
2035
-46
603
-12
545
2045
-74
223
-16
133
2055
-62
176
-14
99
Volatile Organic
Compounds (VOC)
2035
-1,118
198
-40
-960
2045
-1,557
130
-54
-1,481
2055
-1,398
67
-48
-1,379
Sulfur Dioxide (SO2)
2035
-49
4,984
-16
4,918
2045
-82
243
-22
139
2055
-77
24
-20
-73
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
In 2055, we estimate the alternative would result in a net decrease of 17 million metric tons of
GHG emissions, compared to 61 million metric tons for the final standards (see Table 4-30).
Like the final standards, we project net decreases in emissions of NOx, VOC, and SO2 in 2055
but a net increase in PM2.5 emissions (see Table 4-31). Consistent with other emissions impacts
trends discussed for the alternative, the magnitude of these net impacts would be smaller for the
alternative than for the final standards.
Finally, Figure 4-25 shows the net year-over-year GHG emissions impacts, measured in CChe
emissions, for the final standards and alternative. The net GHG impacts of the alternative would
be significantly smaller than the final standards, especially in the further future years beyond
2040 as the total number of HD ICE vehicles displaced by ZEVs is much smaller than in the
final standards under their respective potential compliance pathways.
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Calendar Year
— Alternative — Final Standards
Figure 4-25 Comparison of net CChe emission impacts of the final standards and alternative from 2027
through 2055
4.7.4 Cumulative GHG Reduction Comparison
Table 4-48, Table 4-49, and Table 4-50 present the cumulative GHG impacts that we project
would result from both the final standards and the alternative from 2027 through 2055 for
downstream emissions, EGU emissions, and refinery emissions, respectively, relative to the
reference case.
Table 4-48 Cumulative 2027-2055 downstream HD GHG emission reductions from the final standards and
the alternative
Pollutant
Final Standards
Alternative
Reduction in MMT
Percent
Reduction in MMT
Percent
Carbon Dioxide (CO2)
1,347
13%
454
4%
Methane (CH4)
0.127
7%
0.030
2%
Nitrous Oxide (N20)
0.199
13%
0.071
5%
CO2 Equivalent (C02e)
1,404
13%
473
4%
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Table 4-49 Cumulative 2027-2055 GHG emission increases from EGUs from the final standards and the
alternative
Pollutant
Increase in MMT
Final Standards
Alternative
Carbon Dioxide (CO2)
391.4
155.3
Methane (CH4)
0.018
0.008
Nitrous Oxide (N20)
0.002
0.001
CO2 Equivalent (CC>2e)
392.5
155.7
Table 4-50 Cumulative 2027-2055 GHG emission reductions from refineries from the final standards and
alternative
Pollutant
Reduction in MMT
Final Standards
Alternative
Carbon Dioxide (CO2)
13.4
3.6
Methane (CH4)
0.0007
0.0000
Nitrous Oxide (N20)
0.0001
0.0000
CO2 Equivalent (C02e)
13.5
3.6
Overall, we estimate the alternative would reduce net GHG emissions by 321 million metric
tons between 2027 and 2055, relative to the reference case, as is presented in Table 4-51. This is
less than one third the total reduction from the final standards, which is more than 1 billion
metric tons.
Table 4-51 Cumulative 2027-2055 net GHG emission impactsA (in MMT) of the alternative
Pollutant
Downstream
EGU
Refineries
Net
Carbon Dioxide (CO2)
-454
155
-4
-302
Methane (CH4)
-0.030
0.008
0.000
-0.023
Nitrous Oxide (N20)
-0.071
0.001
0.000
-0.070
CO2 Equivalent (C02e)
-473
156
-4
-321
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
4.8 Hydrogen Production Comparative Analysis
As mentioned in Chapter 4.3, for the purposes of emissions inventory modeling, we assumed
hydrogen fuel produced for the HD FCEVs in our potential compliance pathway would be
produced via grid electrolysis. IPM allowed us to represent the estimated emission impacts of
grid electrolysis-derived hydrogen fuel over the timeframe of this analysis, embedding projected
changes to electricity capacity and generation that also apply to projected emissions from
hydrogen produced via grid electrolysis.
In this section, we conduct a comparative analysis to assess how lifecycle emissions outcomes
between multiple alternative hydrogen production pathways could compare on a relative basis.
We use data from Argonne's Greenhouse Gases, Regulated Emissions, and Energy Use in
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Transportation (GREET)1403 model to show relative comparisons between estimated well-to-
wheel emission outcomes from different hydrogen production pathways per kilogram of
hydrogen. GREET is a lifecycle analysis model based on supply chains of technologies and
products. It provides lifecycle energy, water, GHG, and other air emission results intended to
evaluate the impacts of various vehicle and fuel combinations. GREET is developed by Argonne
National Laboratory (ANL) and sponsored by the U.S. Department of Energy (DOE).1404
GREET is not a dynamic model like IPM in which projections of future time periods depend
on the simulation of prior time periods.1405 However, it does include projected background data,
using projections from sources such as EIA. GREET users can estimate supply chain-related
lifecycle emissions for any target year between 1990 and 2050 but it is not an economic model
that can account for categories of indirect emission impacts that vary based on magnitudes of
fuels used or produced in a scenario. Thus, GREET can demonstrate how the estimated
emissions of a produced fuel may change over time based on various factors, such as changes in
technological efficiency, so long as available data and projections exist.1406
There are multiple potential pathways for hydrogen fuel production. Though hydrogen today
in the U.S. is predominantly produced through steam methane reforming (SMR),1407 hydrogen
production modes are expected to shift to other pathways given BIL and IRA provisions that
meaningfully incentivize reducing the emissions and carbon intensity of the fuel. Therefore, we
compare lifecycle emission estimates associated with several pathways with commercialized
technologies expected to be possible in the timeframe of the rule. This evaluation demonstrates a
range of estimated emission outcomes associated with hydrogen produced for HD FCEVs in the
potential compliance pathway.
Steam methane reforming is a process that reacts natural gas with high-pressure steam to
produce hydrogen fuel. The steam is channeled through reforming tubes that contain catalysts
that separate hydrogen molecules from the steam. Most SMR facilities in the U.S. currently
produce hydrogen for industrial processes, such as fertilizer production or petroleum refining,
and are often co-located with refineries that can make use of the excess steam generated from the
SMR to displace some natural gas usage. Future SMR facilities built to supply hydrogen fuel for
transportation purposes are unlikely to be co-located with such refineries and we do not include a
co-product credit for excess steam generated by SMR in GREET. GREET provides multiple
1403 Wang, Michael et al. Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021
Excel). Computer Software. U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy
(EERE). 11 Oct. 2021. Web. doi:10.11578/GREET-Excel-2021/dc.20210902.1.
1404 Elgowainy, A. and Wang, M. (2019) 'Overview of Life Cycle Analysis (LCA) with the GREET Model', p. 21.
Available online: https://greet.es.anl.gov/files/workshop_2019_overview
1405 This is one reason we decided to represent hydrogen produced via grid electrolysis using the dynamic model,
IPM, rather than extrapolating GREET's per-unit hydrogen emissions to represent hydrogen production in this
rulemaking.
1406 Many data sources GREET relies on do not project out to 2050 and have assumptions that flatline after a certain
year such as 2030 or 2035.
1407 U.S. Department of Energy. "Hydrogen Production: Natural Gas Reforming." Available online:
https://www.energy.gov/eere/fuelcells/hydrogen-production-natural-gas-reforming
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options for representing SMR and we present it both produced centrally and distributed1408, as
well as with and without carbon capture and sequestration (CCS).
Another hydrogen production process is autothermal reforming (ATR), which is similar to
SMR but adds high purity oxygen as part of the process. When natural gas, steam (water), and
oxygen are combined in the ATR, the results are partial combustion of the natural gas and an
output stream that is low in nitrogen gas. ATR's ability to keep nitrogen gas output lower than
SMR makes this pathway especially well-suited for connecting to CCS.1409 GREET provides one
hydrogen production pathway for ATR that includes CCS.
Table 4-52 presents GREET lifecycle CChe emission estimates for four hydrogen production
pathways that include SMR and ATR. We present pathways with and without CCS based on the
model's estimates of the technologies in 2030. SMR is considered a mature and advanced
technology that, absent use of CCS, is not expected to become significantly more efficient or
lower in carbon intensity over time.1407
Table 4-52 Lifecycle CChe emissions for hydrogen fuel production pathways from GREET in calendar year
2030
Production Pathway
Infrastructure
CCS
kgCChe/kg H2
Steam Methane Reforming (SMR)
Distributed
No
13.07
Steam Methane Reforming (SMR)
Centralized
No
13.01
Steam Methane Reforming (SMR)
Centralized
Yes
4.65
Autothermal Reforming (ATR)
Centralized
Yes
5.41
Our IPM modeling shows emissions from EGUs are expected to decline as the mixture of
electricity generating sources becomes less emitting over time.1410 We expect emissions for
producing hydrogen fuel from grid electrolysis are to be directly correlated with these trends, so
we can use IPM output to project emissions from hydrogen generated via grid electrolysis
compared to from the alternative production pathways provided by GREET. However, GREET
estimates supply chain-related lifecycle GHG emissions while IPM only estimates combustion
emissions from EGUs and does not include emissions upstream of the EGU, such as the
extraction and refining of the fossil fuel feedstocks that are combusted in EGUs. Using GREET,
we derived multiplicative factors that represent these upstream feedstock emissions for each
mode of electricity generation that has these emissions. We then applied these factors to the
specific EGU generation mix for each output year in IPM to calculate average annual lifecycle
CChe emission factors, per kilowatt-hour of electricity generated, which are shown in Table
4-53.1411
1408 Central refers to a larger-scale facility that produces hydrogen offsite from a refueling station and delivers the
fuel to a refueling station either via pipeline or truck delivery. Distributed (or forecourt) refers to fuel produced at
the refueling station itself, usually produced from small-scale equipment onsite. Production efficiencies are usually
higher for centrally generated fuels but can incur greater transportation related emissions from needing to deliver the
finished fuel to refueling stations.
1409 Khojasteh Salkuyeh, Yaser, et al. "Techno-Economic Analysis and Life Cycle Assessment of Hydrogen
Production from Natural Gas Using Current and Emerging Technologies." International Journal of Hydrogen
Energy, vol. 42, no. 30, July 2017, pp. 18894-909., https://doi.Org/10.1016/j.ijhydene.2017.05.219.
1410 This can be seen in Table 4-11, for example.
1411 These CChe values combine CO2, CH4, and N20 emissions represented by IPM using IPCC Assessment Report
5 (AR5) the 100-year global warming potential (GWP) values as shown in Table 4-55.
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Table 4-53 Calculated average annual lifecycle CChe per kWh generated from EGUs (kgCChe/kWh)
Emissions
2028
2030
2035
2040
2045
2050
2055
kgCChe/kWh Generated
0.30
0.23
0.14
0.09
0.08
0.06
0.06
To calculate the electricity needed to produce hydrogen via electrolysis, we used National
Renewable Energy Laboratory's (NREL) Hydrogen Analysis (H2A) modeling. Their modeling
shows that the electricity required to produce a kilogram of hydrogen using proton exchange
membrane (PEM) electrolysis ranges from 55.8 kWh, using current technology, to 51.4 kWh,
based on their assumption for future efficiency improvements. We then used GREET to account
for the additional electricity required for compressing and pre-cooling the hydrogen for fueling
HD FCEVs. We expect increasing amounts of hydrogen to be produced via electrolysis in the
future, and therefore expect hydrogen producers to develop better techniques and efficiencies for
producing hydrogen. We assumed a linear learning curve between 2025 and 2055 so that grid
electrolysis hydrogen production represented in IPM becomes somewhat more efficient over
time.1412 Table 4-54 presents our assumptions for electricity required to generate hydrogen at a
refueling station using PEM electrolysis.
Table 4-54 Electricity required to produce hydrogen using PEM electrolysis (kWh/kg H2)
2025
2055
PEM Electrolysis Efficiency
(kWh/kg H2)
55.8
51.4
Compression and Pre-
Cooling Energy (kWh/kg H2)
2.6
2.6
Combined Energy Required
(kWh/kg H2)
58.4
54.0
We multiplied the average annual lifecycle CO2Q emission factors from Table 4-53 by the
electricity required for hydrogen production via electrolysis in Table 4-54 to derive a projected
lifecycle CChe intensity estimates per kilogram of hydrogen produced using distributed grid
PEM electrolysis.
Figure 4-26 presents these estimates compared to the alternative hydrogen fuel production
pathways from GREET. Cases where the yellow line (representing grid electrolysis) drops below
one of the dotted lines (representing SMR or ATR) indicate when it is projected that grid
electrolysis would become comparatively less carbon intensive than the alternative production
pathway.
1412 We used a linear learning curve in this scenario to interpolate between the two data points NREL provides for
PEM electrolysis efficiency. This approximate approach is simplified compared to how industry will likely improve
the technology over time.
637
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20
0
00
O
CM
CO
C30
O
CM
CO
OO
O
CM
C\J
CO
CO
CO
CO
CO
lO
LO
LO
0
0
O
O
O
O
O
O
0
O
O
O
O
O
CM
CM
CM
CM
CM
CM
CM
CM
CM
CM
CM
CM
CM
CM
Calendar Year
Distributed Steam Methane
Reforming (No CCS)
Centralized Steam Methane
Reforming (No CCS)
Centralized Autothermal
Reforming (ATR) (With CCS)
Centralized Steam Methane
Reforming (With CCS)
Distributed Grid PEM
Electrolysis (No CCS)
Figure 4-26 Comparison of projected lifecycle CChe/kg of delivered hydrogen from distributed grid PEM
electrolysis to alternative hydrogen production pathways from 2028 through 2055
We estimate grid PEM electrolysis will become less carbon intensive on a lifecycle basis than
SMR without CCS between 2030 and 2031. This is predominantly due to the decarbonization of
electricity generation that IPM projects.14131414 This suggests that conventional SMR would be a
less carbon intensive pathway to produce hydrogen fuel before 2030. We estimate that SMR and
ATR coupled with CCS will continue to be lower emitting options for producing hydrogen until
the early to mid-2040s, at which point EGU emissions become low enough that grid PEM
electrolysis could be expected to be lower emitting than these alternatives as well.
This is an illustrative analysis comparing relative lifecycle GHG emissions across multiple
hydrogen production pathways that are already mature or are expected to become more
prominent. Other pathways exist for producing hydrogen at scale, such as coupling PEM
electrolyzers with incremental zero-emitting energy sources. Similarly, competing technologies
may replace PEM electrolysis, such as alkaline or solid oxide electrolyzers. Ultimately,
emissions from grid-derived PEM electrolysis hydrogen used in HD FCEVs, similar to
electricity used to charge HD BEVs, are sensitive to the source of the electricity.
Relative to the emission inventory impacts presented earlier in this chapter (see Chapters 4.4,
4.5, and 4.6, for example), we therefore expect that an emission inventory impacts analysis
which assumes more hydrogen produced via SMR to estimate decreased upstream GHG
emissions in earlier years and increased upstream GHG emissions in further out years. Given that
1413 Our results aligned closely with work by Tao, Meng et al. (2022) that found electrolysis using electricity from
the grid became lower emitting on a CO2 basis compared to SMR from natural gas once average electricity grid
emissions reached 0.22 kgCCh/kWh.
1414 Tao, Meng, et al. "Review—Engineering Challenges in Green Hydrogen Production Systems." Journal of The
Electrochemical Society, vol. 169, no. 5, May 2022, p. 054503. Institute of Physics, https://doi.org/10.1149/1945-
7111/ac6983.
638
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these are offsetting trends and given the uncertainty inherent in projecting how the hydrogen
needed to fuel FCEVs will be produced,1415'1416 we feel that our modeling assumption that all
hydrogen will be produced via grid electrolysis does not meaningfully skew the overall GHG
emission inventory impacts attributable to the final standards.
4.9 Refined Fuels Export Sensitivity Analysis
This chapter presents our sensitivity analysis of refinery emissions should U.S. refineries
offset the drop in domestic fuel demand from the final standards using exports to a greater extent
than we assumed in our main analysis. As discussed in RIA Chapter 4.2.5, we assumed that
refineries would offset 50 percent of the drop in domestic demand by increasing net exports in
our main analysis. Some commenters noted that refineries could increase exports more than that,
so this sensitivity analysis presents emission impacts should U.S. refineries increase exports even
more.
We evaluated the change in refinery inventory should only 20 percent of the drop in domestic
demand be reflected in decreased refinery activity, which is less than half of what we assumed
for our main modeling case. Therefore, we expect the refinery emission reductions in this
sensitivity case to be smaller than we presented in RIA Chapter 4.4 As shown in RIA Chapter
4.5 and RIA Chapter 4.6, the refinery emission impacts from the final standards tend to be much
smaller than either the downstream or EGU emission impacts. Therefore, we expect to see little
change in the net emissions impact from the final standards in the case that U.S. refineries
increase net exports more than in our final standards modeling.
Table 4-55 and Table 4-56 present the sensitivity case refinery emission reductions for GHGs
and criteria pollutants in calendar year 2055, respectively, compared to our main final standards
modeling. The reductions are about 60% smaller in our sensitivity case than the main case.
Table 4-55 Annual GHG emission reductions from refineries from the final standards in calendar year 2055
for our main modeling case and fuel export sensitivity case
100-year
CY 2055 Refinery Emission Reductions
Pollutant
GWP
(Metric Tons)
Main Case
Sensitivity Case
Carbon Dioxide (CO2)
1
690,477
276,191
Methane (CH4)
28
34
14
Nitrous Oxide (N20)
265
6
2
CO2 Equivalent (CC>2e)
—
693,016
277,206
1415 The hydrogen production tax credit (described further in RIA Chapter 1.3.2.4), designed to incentivize the
production of qualified clean hydrogen at a qualified clean hydrogen production facility, has significant potential to
reduce overall greenhouse gas emissions associated with hydrogen production in the coming years, as the value of
the credit is based on lifecycle GHG emissions associated with the hydrogen production process. The comment
period for the proposed rule by the Internal Revenue Service ended in February 2024. See 88 FR 89220.
1416 88 FR 89220. Available online: https://www.federalregister.gov/documents/2023/12/26/2023-28359/section-
45v-credit-for-production-of-clean-hydrogen-section-48al5-election-to-treat-clean-hydrogen
639
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Table 4-56 Annual criteria pollutant emission reductions from refineries from the final standards in calendar
year 2055 for our main modeling case and fuel export sensitivity case
Pollutant
CY 2055 Refinery Emission Reductions
(U.S. Tons)
Main Case
Sensitivity Case
Nitrogen Oxides (NOx)
304
122
Primary PM2 5
70
28
Volatile Organic Compounds (VOC)
226
91
Sulfur Dioxide (SO2)
94
37
Table 4-57 presents the net impacts of the final standards in our sensitivity case for GHGs and
Table 4-58 presents the same for criteria pollutants.
Table 4-57 Annual net impactsA on GHG emissions from the final standards in calendar years (CYs) 2035,
2045, and 2055, analyzed with our fuel exports sensitivity case
Pollutant
GWP
Calendar
Year
Emission Impact (MMT)
Downstream
EGU
Refinery
Net
Carbon Dioxide (CO2)
1
2035
-32.5
29.3
-0.1
-3.3
2045
-66.3
14.5
-0.3
-52.1
2055
-70.0
12.9
-0.3
-57.4
Methane (CH4)
28
2035
-0.002
0.002
0.000
0.000
2045
-0.006
0.000
0.000
-0.006
2055
-0.010
0.000
0.000
-0.009
Nitrous Oxide (N2O)
265
2035
-0.005
0.000
0.000
-0.005
2045
-0.010
0.000
0.000
-0.010
2055
-0.010
0.000
0.000
-0.010
CO: Equivalent (C02e)
—
2035
-33.8
29.4
-0.1
-4.5
2045
-69.1
14.5
-0.3
-54.8
2055
-73.0
12.9
-0.3
-60.4
A We present emissions reductions as negative numbers and emission increases as positive numbers.
We can see little change in the net GHG emission impacts. Compared to our main modeling
(see Table 4-30), the net emission impacts are about the same. Our main modeling estimates a
net reduction of 60.8 million metric tons of GHG emissions in 2055 versus 60.4 million metric
tons in our sensitivity modeling.
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Table 4-58 Annual net impactsA on criteria pollutant emissions from the final standards in calendar years
(CYs) 2035,2045, and 2055, analyzed with our fuel exports sensitivity case
Pollutant
Calendar
Year
Emission Impact (U.S. Tons)
Downstream
EGU
Refinery
Net
Nitrogen Oxides (NOx)
2035
-10,801
9,719
-59
-1,141
2045
-47,027
1,588
-115
-45,555
2055
-54,268
1,520
-122
-52,869
Particulate Matter
(PM2.5)
2035
-126
1,418
-14
1,278
2045
-302
596
-27
267
2055
-331
513
-28
155
Volatile Organic
Compounds (VOC)
2035
-3,014
467
-45
-2,592
2045
-6,426
347
-86
-6,166
2055
-7,242
196
-91
-7,137
Sulfur Dioxide (SO2)
2035
-126
11,726
-18
11,582
2045
-256
648
-36
357
2055
-270
69
-37
-239
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
In 2055, we estimate net reduction in VOC, NOx, and SO2 emissions of 7,137 tons, 52,869
tons, and 239 tons respectively. This is compared with our main case net emission reduction
estimates (see Table 4-31) of 7,272 tons of VOC emissions, 53,151 tons ofNOx emissions, and
295 tons of SO2 emissions. Because we are projecting a smaller emission reduction from
refineries in our sensitivity case, we project a larger net increase in PM2.5 emissions than in our
main case. Our estimated net PM2.5 emissions increase in the sensitivity case is 155 tons versus
113 tons in the main case.
Table 4-59 shows the net cumulative GHG impacts of the final standards evaluated with the
refinery sensitivity case. The net GHG impacts of the final standards are determined more by
downstream emission reductions versus increased EGU emissions than by the refinery emission
reductions and, by extension, the extent to which U.S. refineries offset the drop in domestic fuel
demand by increasing net exports. In our main modeling, we estimated that net GHG emissions
would decrease by 1.025 billion metric tons (see Table 4-39) versus 1.016 billion metric tons for
the sensitivity case.
Table 4-59 Cumulative 2027-2055 net GHG emission impactsA (in MMT), reflecting the final standards
analyzed with our fuel exports sensitivity case
Pollutant
Downstream
EGU
Refineries
Net
Carbon Dioxide (CO2)
-1,347
391
-5
-961
Methane (CH4)
-0.127
0.018
0.000
-0.109
Nitrous Oxide (N20)
-0.199
0.002
0.000
-0.197
CO2 Equivalent (CC>2e)
-1,404
393
-5
-1,016
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
Because the difference between our sensitivity case and main modeling cases is small, the
monetized benefits of the rule should U.S. refineries increase net exports more than we assume
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would be minimally impacted. The net benefits of the rule, therefore, are not very sensitive to the
amount that U.S. refineries may increase net exports in the future.
4.10 Reference Case ZEV Adoption Sensitivity Analysis
We performed a sensitivity analysis to evaluate the emissions impact of the final standards for
a different reference case than the one described in Chapter 4.2.2. We chose to evaluate a
sensitivity reference that has reduced HD ZEV adoption compared to the reference case, in part
because we expected such a scenario may result in a greater magnitude of costs. We model
differing HD ZEV adoption rates in the sensitivity analysis for both the reference case and final
standards case, described in Chapter 4.10.1. Chapter 4.10.2 discusses changes in manufacturer
costs.
We modeled the downstream emission inventory for the sensitivity reference case and
sensitivity final standards case using MOVES4.R3.1417 Due to the lead times necessary to run
IPM, we did not perform upstream emissions modeling for this sensitivity case. Downstream
emission inventory impacts in the sensitivity case are discussed in Chapter 4.10.3.
4.10.1 ZEV Adoption Rate Calculations
To evaluate a reference case with lower ZEV adoption, we calculated ZEV adoption rates in
the sensitivity reference case using a methodology conceptually similar to the one we used in the
NPRM. When we performed our inventory analysis for the NPRM, CARB's ACT rule had not
yet been granted its waiver and our NPRM reference case approach to HD ZEV adoption was
thus based on other considerations (like the IRA and BIL) and did not include ACT as an
enforceable rule. However, because it represented the best quantitative data source on which to
base our HD ZEV adoption rates absent the final standards (among other reasons noted in DRIA
Chapter 4.3.1), we used it as our primary source to calculate a projected national level of
reference case ZEV adoption based on the other considerations.
To estimate the adoption of HD ZEVs in the sensitivity reference case, we assumed a national
level of ZEV sales equivalent to combined volumes using the NPRM approach with updated data
(i.e. national level ZEV adoption expected from ACT in California and the other states that had
adopted ACT under CAA Section 177 at the time of our analysis).1418 We used those volumes as
the numeric basis for a projection of the number of ZEVs nationwide in model years 2024 and
beyond. While we calculated the national ZEV sales percentages based on those volumes applied
to the states that have adopted ACT, we do not explicitly model ACT (or compliance with ACT)
in those states in this sensitivity reference case; the ZEV adoption is meaningfully lower than
inclusion of ACT in our reference case. Instead, we model ZEV adoption as homogeneous across
the United States.
1417 The only difference between the sensitivity cases and our main inventory modeling is the ZEV adoption rates.
We used the same MOVES run specification files to model the sensitivity cases as those described in the beginning
of Chapter 4.3.
1418 At the time we performed the inventory modeling analysis, seven states had adopted ACT in addition to
California. Oregon, Washington, New York, New Jersey, and Massachusetts adopted ACT beginning in MY 2025
while Vermont adopted ACT beginning in MY 2026 and Colorado in MY 2027. Three other states, New Mexico,
Maryland, and Rhode Island adopted ACT (beginning in MY 2027) in November and December of 2023, but there
was not sufficient time for us to incorporate them as ACT states in our modeling.
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We made several assumptions to calculate HD ZEV adoption rates by vehicle type for the
sensitivity reference case. As we did in the NPRM, we assume, for the purposes of calculating
national HD ZEV adoption, the proportion of national HD sales in the states that adopted the
ACT program remains the same in the future as they were for MYs 2019 and 2020.1419 We
maintain the modeling of differential adoption rates within the vehicle groups defined by ACT
from the FRM reference case based on our technology assessment in HD TRUCS. This is
described in Chapter 4.2.2.1420 Our method for apportioning ZEVs between BEVs and FCEVs
also matches the algorithm described in Chapter 4.2.2 and Appendix B to this RIA.
Table 4-60 shows the sensitivity reference case ZEV adoption rates from model years 2027
through 2035. Model years 2036 and beyond have the same adoption rates as MY 2035.
Table 4-60 National heavy-duty ZEV adoption in the sensitivity reference case
Model Year
LHD
Vocational
MHD
Vocational
HHD
Vocational
Short-Haul
Tractors
Long-Haul
Tractors
2024
2.9%
1.8%
1.7%
1.0%
0.0%
2025
3.5%
2.2%
2.0%
1.4%
0.0%
2026
4.2%
2.6%
2.4%
2.0%
0.0%
2027
6.4%
4.0%
3.7%
2.9%
0.2%
2028
9.7%
6.0%
5.6%
3.8%
0.4%
2029
12.9%
8.0%
7.4%
4.6%
0.7%
2030
16.0%
9.9%
9.2%
5.4%
1.0%
2031
17.6%
10.9%
10.1%
5.8%
2.0%
2032
19.1%
11.9%
11.0%
6.5%
2.5%
2033
20.7%
12.8%
12.0%
6.5%
2.5%
2034
22.3%
13.8%
12.9%
6.5%
2.5%
2035 and beyond
23.9%
14.8%
13.8%
6.5%
2.5%
In this sensitivity analysis, we model the final standards, i.e., the sensitivity control case,
using the same stringency level, compliance pathway, and HD ZEV adoption algorithm outlined
in Chapter 4.2.3. In the HD ZEV adoption algorithm, the calculation of HD ZEV adoption rates
in the modeled compliance pathway for the final standards is not independent of the reference
case,1421 so we model a sensitivity control case that is different from the FRM final standards
control case described in Chapter 4.2.3, referred to here as the FRM control case, despite the
identical numeric level of the standards and same algorithm.
1419 We based the proportion of national HD sales in the states that have adopted ACT on vehicle registration data in
IHS2020. We used MY 2020 registrations because it was the most recent MY data available. However, the data set
encompassed a partial year of registrations, so we also included MY 2019 registrations.
1420 We model greater ZEV adoption rates in LHD vocational vehicles than MHD vocational vehicles, which have
greater ZEV adoption rates than HHD vocational vehicles. Likewise, we model greater adoption of ZEVs for short-
haul tractors than long-haul tractors.
1421 There may be some HD vehicle types in which reference case HD ZEV adoption exceeds what is needed to
comply with the final standards. In these cases, we set the HD ZEV adoption rate in our modeling of the final
standards to match the reference case. Because the sensitivity reference case has lower HD ZEV adoption rates than
the FRM reference case, there are fewer cases where sensitivity reference case ZEV adoption exceeds what is
needed to comply with the final standards than the main reference case. Therefore, the sensitivity final standards
case has slightly lower overall HD ZEV adoption than the FRM final standards case. It is important to note that the
differences are small and have minimal impact on the HD downstream emission inventories.
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Table 4-61 shows the HD ZEV adoption rates modeled in our sensitivity control case. The
differences in HD ZEV adoption in the sensitivity control case versus the FRM control case (see
Table 4-9) are small and have a minimal impact on the estimated HD downstream emission
inventories estimated in either final standards case.
Table 4-61 National heavy-duty ZEV adoption in the sensitivity analysis for the final standards
Model Year
LHD
Vocational
Mill)
Vocational
HHD
Vocational"
Short-Haul
Tractors
Long-Haul
Tractorsb
2027
18.0%
13.2%
3.7%
4.9%
0.2%
2028
22.9%
16.3%
9.0%
8.4%
0.4%
2029
27.8%
19.4%
11.4%
11.9%
0.7%
2030
32.7%
22.5%
13.8%
16.3%
6.2%
2031
46.2%
31.1%
19.4%
27.7%
12.5%
2032 and beyond
59.8%
39.8%
25.0%
39.9%
25.0%
aFor HHD vocational vehicles, the final standards do not include revisions to MY 2027 standards. ZEV adoption
for these vehicles in this model year was set to be equal to the reference case.
b For sleeper cab tractors, which are represented by long-haul tractors (source type 62) in MOVES, the final
standards do not include revisions to the MY 2027 standards or new standards for MYs 2028 or 2029. ZEV
adoption for this source type in these model years was set to be equal to the reference case.
4.10.2 Heavy-Duty Vehicle Manufacturer Costs
We do not model a change in the cost of HD ZEV costs for purchasers as part of this
sensitivity analysis. We expect the additional cost of a HD ZEV and its payback period, relative
to a comparable ICE vehicle, to remain the same regardless of how we model the reference case.
HD ZEV purchaser costs and payback periods are discussed in RIA Chapter 2.10.6.
Manufacturer costs depend on the incremental ZEV adoption rate: the difference between the
ZEV adoption rates in the technology packages that support the final standards and reference
case.1422 Because the sensitivity reference case has a lower overall level of HD ZEV adoption,
we model greater incremental ZEV adoption rates and manufacturer costs change accordingly.
More detailed discussions of manufacturer costs can be found in RIA Chapter 2.10.6.
Table 4-62 through Table 4-64 show the ZEV technology costs for manufacturers relative to
the sensitivity reference case for MYs 2027, 2030, and 2032, respectively. These cost estimates
include the direct manufacturing costs that reflect learning effects, the indirect costs, and the IRA
section 13502 Advanced Manufacturing Production Credit, on average aggregated by regulatory
group.
1422 We note that the ZEV adoption rates used in this RIA Chapter 4.10.2 are consistent with the technology
packages shown in RIA Chapter 2.10.1 and the sensitivity reference case shown in Table 4-60. Due to the lead time
required for MOVES modeling, we were not able to incorporate some changes to the final standards that occurred
late in the rulemaking process into MOVES. Thus, for the analysis shown in this RIA Chapter 4.10.2, we use the
ZEV adoption rates from RIA Chapter 2.10.1. For other program analyses which depend on data from MOVES, the
differences between the final standards and MOVES modeling are negligible because of the timescale of the
analyses, which analyze impacts out to 2055.
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Table 4-62 Manufacturer costs to meet the final MY 2027 standards through the potential compliance
pathway relative to the sensitivity reference case (2022$)
Incremental
ZEV Adoption
Per-ZEV
Fleet-Average Per-
Regulatory Group
Rate in
Manufacturer RPE
Vehicle Manufacturer
Technology
Package
on Average
RPE
LHD Vocational Vehicles
11%
-$4,100
-$435
MHD Vocational Vehicles
6%
$3,959
$356
HHD Vocational Vehicles
0%
N/A
$0
Day Cab Tractors
0%
N/A
$0
Sleeper Cab Tractors
0%
N/A
$0
Note: The average costs represent the average across the regulatory group. For example the first
row represents the average across all LHD vocational vehicles
Table 4-63 Manufacturer costs to meet the final MY 2030 standards through the potential compliance
pathway relative to the sensitivity reference case (2022$)
Incremental
Regulatory Group
ZEV Adoption
Rate in
Per-ZEV
Manufacturer RPE
Fleet-Average Per-
Vehicle Manufacturer
Technology
Package
on Average
RPE
LHD Vocational Vehicles
16%
-$10,637
-$1,702
MHD Vocational Vehicles
12%
-$6,164
-$746
HHD Vocational Vehicles
6%
-$7,582
-$440
Day Cab Tractors
11%
$32
$3
Sleeper Cab Tractors
5%
$41,877
$2,094
Note: The average costs represent the average across the regulatory group. For example the first
row represents the average across all LHD vocational vehicles
Table 4-64 Manufacturer costs to meet the final MY 2032 standards through the potential compliance
pathway relative to the sensitivity reference case (2022$)
Incremental
Regulatory Group
ZEV Adoption
Rate in
Per-ZEV
Manufacturer RPE
Fleet-Average Per-
Vehicle Manufacturer
Technology
Package
on Average
RPE
LHD Vocational Vehicles
41%
-$9,776
-$3,998
MHD Vocational Vehicles
28%
-$5,033
-$1,414
HHD Vocational Vehicles
19%
-$3,989
-$758
Day Cab Tractors
34%
$10,816
$3,623
Sleeper Cab Tractors
23%
$53,295
$11,991
Note: The average costs represent the average across the regulatory group. For example the first
row represents the average across all LHD vocational vehicles
These manufacturer costs are greater in magnitude than those in the main analysis shown in
RIA Chapter 2.10.6. This is true both when costs are projected to be positive (i.e., costs resulting
from our projection that certain HD ZEVs will be more expensive than comparable ICE
vehicles)) and negative (i.e., savings resulting from our projection that certain HD ZEVs will be
645
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cheaper than a comparable ICE vehicle). For example, the MY 2032 fleet-average per-vehicle
cost for medium heavy-duty vocational vehicles is -$1,414 here and -$981 in the main analysis.
Conversely, the MY 2032 fleet-average per-vehicle cost for sleeper cab tractors is $11,991 here
and $10,819 in the main analysis. This is because we model an increase in ZEV adoption and no
change in the per-ZEV manufacturer cost. Consistent with our discussion in preamble Section
II.G.2 for the main analysis, the fleet-average per-vehicle manufacturer costs in this reference
case sensitivity analysis are lower than those we projected for the HD GHG Phase 2 rule that we
considered to be reasonable.
4.10.3 Downstream Emission Inventory Impacts
In general, we model greater downstream emission reductions in this sensitivity analysis than
in our main modeling of the final standards. Because the sensitivity reference case has lower HD
ZEV adoption rates than the FRM reference case, we model greater incremental HD ZEV
adoption in our potential compliance pathway for the final standards and therefore greater
downstream emission reductions. The greater emission reductions do not result from us
modeling a different level of stringency of the final standards themselves.
Our estimates of the downstream emission reductions of GHGs that would result from the
final standards relative to the sensitivity reference case are presented in Table 4-65 for calendar
years 2035, 2045, and 2055.
Table 4-65 Annual downstream heavy-duty GHG emission reductions from the final standards in calendar
years (CYs) 2035,2045, and 2055, relative to the sensitivity reference case
Pollutant
100-
year
GWP
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Carbon Dioxide (CO2)
1
44.7
12%
96.9
25%
115.0
29%
Methane (CH4)
28
0.002
4%
0.008
13%
0.014
17%
Nitrous Oxide (N20)
265
0.006
12%
0.014
25%
0.017
28%
CO2 Equivalent (COye)
—
46.5
12%
100.8
25%
119.8
29%
Our estimated GHG emission reductions from the final standards relative to the sensitivity
reference case are greater than the reductions relative to the FRM reference case (see Table
4-16). In 2055, we estimate that emission reductions of CO2 by 29 percent (the main analysis
estimate is 20 percent), methane by 17 percent (the main analysis estimate is 12 percent), and
N2O by 28 percent (the main analysis estimate is 20 percent). The resulting total GHG reduction,
in C02e, is 29 percent for the sensitivity analysis versus 20 percent for the main analysis.
We also project that downstream emission reductions of criteria pollutants and air toxics
would result from the final standards in the sensitivity case, as presented in Table 4-66.
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Table 4-66 Annual downstream heavy-duty criteria pollutant and air toxic emission reductions from the final
standards in calendar years (CYs) 2035,2045, and 2055, relative to the sensitivity reference case
Pollutant
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
U.S. Tons
Percent
U.S. Tons
Percent
U.S. Tons
Percent
Nitrogen Oxides (NOx)
15,351
4%
65,923
21%
82,943
28%
Particulate Matter (PM2 s)A
181
2%
475
7%
619
9%
Volatile Organic
Compounds (VOC)
4,293
9%
10,137
24%
13,534
31%
Sulfur Dioxide (SO2)
173
12%
374
26%
448
29%
Carbon Monoxide (CO)
68,496
8%
175,468
23%
228,506
29%
1,3-Butadiene
10
15%
24
39%
31
45%
Acetaldehyde
88
9%
216
24%
290
27%
Benzene
57
11%
141
33%
189
42%
Formaldehyde
58
6%
150
20%
212
23%
Naphthalene0
4
7%
10
31%
12
38%
A PM2 5 estimates include both exhaust and non-exhaust emissions.
B Naphthalene includes both gas and particle phase emissions.
Once again, the estimated emission reductions in criteria pollutants and air toxics that would
result from the final standards are greater in the sensitivity case than our main modeling of the
final standards (see Table 4-17). For example, in 2055, we estimate the final standards would
reduce NOx emissions by 28 percent, PM2.5 emissions by 9 percent, and VOC emissions by 31
percent relative to the sensitivity reference case. This is compared to reductions of NOx by 20
percent, PM2.5 by 5 percent, and VOC by 20 percent for the main analysis. Estimated reductions
in emissions of air toxics range from 23 percent for formaldehyde (the main analysis estimate is
15 percent) to 45 percent for 1,3-butadiene (the main analysis estimate is 27 percent).
The year-over-year downstream emission trends in this sensitivity analysis are similar to the
trends presented in our main modeling of the final standards in Chapter 4.3.2. The detailed
discussion of the impacts of the final standards presented in Chapter 4.3.3, including the detailed
breakdowns of emission reductions by fuel type, source type, regulatory class, and emissions
process also broadly apply to the sensitivity analysis. However, in all cases, the magnitude of the
emission impacts would be greater in this sensitivity analysis than in our modeling of the final
standards. Therefore, we do not present this detailed information and discussion of the
downstream emission impacts of this sensitivity analysis here.
Figure 4-27 shows the year-over-year inventory of total HD GHG emissions (C02e) for both
the reference case and final standards, including both our main modeling and our sensitivity
analysis.
647
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400-
300-
>.
o
200-
O
O
100
o -
Reference
Reference - Sensitivity
Final Standards
Final Standards - Sensitivity
2030
2040
Calendar Year
2050
Figure 4-27 Yearly downstream CChe inventory for the reference case and final standards from 2027 through
2055, including both our main modeling and reference case sensitivity analysis
As discussed in Chapter 4.10.1, our modeling of the final standards is different between our
main modeling and sensitivity analysis, but the differences have a very small impact on the total
downstream HD GHG inventory. Because the sensitivity reference case has lower overall HD
ZEV adoption, it also has a greater downstream GHG inventory. As a result, we model greater
GHG emission reductions from the final standards relative to the sensitivity reference case than
the main reference case.
The warming impacts of GHGs are cumulative. Table 4-67 presents the cumulative
downstream GHG impacts that we project would result from the final standards from 2027
through 2055, relative to both the main reference case and the sensitivity reference case.
Table 4-67 Cumulative 2027-2055 downstream HD GHG emission reductions from the final standards
relative to the main reference case and sensitivity reference case
Pollutant
Main Modeling
Sensitivity Analysis
Reduction in MMT
Percent
Reduction in MMT
Percent
Carbon Dioxide (CO2)
1,347
13%
2,007
18%
Methane (CH4)
0.127
7%
0.172
10%
Nitrous Oxide (N20)
0.199
13%
0.291
18%
CO2 Equivalent (C02e)
1,404
13%
2,089
18%
Consistent with Figure 4-27, the cumulative GHG emission reductions attributable to the final
standards are greater relative to the sensitivity reference case than the main reference case.
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4.11 Comparison Between the Final Standards and Proposed Standards
As discussed in Chapter 4.6, we estimate that the final standards will reduce cumulative
greenhouse gas emissions, from 2027 through 2055, by approximately 1 billion metric tons. In
our analysis for the NPRM, our modeling showed cumulative CO2 emission reductions of 1.8
billion metric tons.1423 This difference (approximately 0.8 billion metric tons) is explained
largely by a change in the modeled downstream emission reductions. In the NPRM, we modeled
a reduction of downstream CO2 emissions of 2.2 billion metric tons, compared to downstream
GHG reductions of 1.4 billion metric tons that we estimate for the final standards.
To better understand the difference in downstream emission reductions, we remodeled the
proposed standards using our updated FRM modeling tools, which are discussed throughout
Chapter 4.2. This includes using MOVES4.R3, updated upstream emissions modeling
methodologies, and an updated technology assessment based on HD TRUCS. Here, we present
updated HD ZEV adoption estimates and downstream emissions modeling results for the
proposed standards. This modeling demonstrates that the differences in the emissions estimates
between the NPRM and FRM are attributable to our updated reference case (this is also
discussed in Chapter 4.10) and modeling methodologies as opposed to any substantial changes in
the overall stringency of the standards themselves. More detailed discussion of the FRM
modeling of the proposed standards can be found in a memorandum to the docket.1424
In the NRPM, we presented HD ZEV adoption rates for three vehicle groups - vocational
vehicles, short-haul tractors, and long-haul tractors. In this FRM, we present HD ZEV adoption
rates identically for tractors, but split vocational vehicles into three subgroups - light heavy-duty
(LHD), medium heavy-duty (MHD), and heavy heavy-duty (HHD) vocational vehicles. Table
4-68 presents the ZEV adoption rates for modeled compliance pathway for the proposed
standards, as they appear in Table 4-7 of DRIA Chapter 4.3.2.
Table 4-68 HD ZEV adoption rates for the proposed standards as presented in the NPRM
HD Vehicle Group
MY 2027
MY 2028
MY 2029
MY 2030
MY 2031
MY 2032 and later
Vocational
20%
25%
30%
35%
40%
50%
Short-Haul Tractors
10%
12%
15%
20%
30%
35%
Long-Haul Tractors
0%
0%
0%
10%
20%
25%
The NPRM adoption rates, presented in this way, are not directly comparable to the adoption
rates we used to model the final standards (presented in Table 4-9). We reanalyzed the proposed
standards by taking the ZEV adoption rates (i.e., the sum of BEV and FCEV adoption rates) by
MOVES source type and regulatory class combination from the NPRM (see DRIA Chapter
4.3.2) and applying the same two constraints to ZEV adoption noted in Chapter 4.2.3. The
updated HD ZEV adoption rates we used to model the proposed standards in MOVES4.R3 are
presented in Table 4-69.
1423 In the NRPM, we estimated net emission impacts only for CO2, instead of all greenhouse gases, because our
modeling of emissions from EGUs and refineries did not include the same set of GHGs as our downstream
modeling. See DRIA Chapter 4.6 for more details.
1424 Murray, Evan. Memorandum to Docket EPA-HQ-OAR-2022-0985. "FRM Modeling of the Proposed
Standards". March 2024.
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Table 4-69 National heavy-duty ZEV adoption in the control case for the FRM modeling of the proposed
standards
Model Year
LHD
MHD
HHD Vocational
Short-Haul
Long-Haul
Vocational
Vocational
Tractors
Tractors
2027
18.8%
19.0%
14.4%
9.5%
0.4%
2028
25.8%
22.1%
16.6%
11.6%
0.7%
2029
32.8%
25.2%
18.9%
14.6%
1.3%
2030
39.8%
28.3%
29.4%
19.6%
10.0%
2031
46.5%
31.3%
32.5%
29.5%
20.0%
2032
59.4%
37.5%
38.5%
34.5%
25.0%
The HD ZEV adoption rates resulting from our modeled potential compliance pathway for the
proposed and final standards are similar. Where they differ, the proposed standards tend to have
greater ZEV adoption in the early years of the rule (2027-2029) and greater ZEV adoption for
HHD vocational vehicles. On the other hand, the final standards tend to have greater ZEV
adoption later in the rule (2030-2032) for LHD and MHD vocational vehicles as well as for
short-haul tractors.
Aside from the differing HD ZEV adoption rates, we used identical methods to model the
emissions impact of the proposed standards as we did for the final standards. This includes using
the same algorithm to apportion ZEVs between BEVs and FCEVs1425 and an identical MOVES
version (MOVES4.R3) and run specification.
Our estimates of the downstream vehicle emission reductions of GHGs that would result from
the proposed standards, relative to the FRM reference case, are presented in Table 4-70 for
calendar years 2035, 2045, and 2055.
Table 4-70 Annual downstream heavy-duty GHG emission reductions from the proposed standards in
calendar years (CYs) 2035,2045, and 2055
Pollutant
100-
year
GWP
CY 2035 Reductions
CY 2045 Reductions
CY 2055 Reductions
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Million
Metric Tons
Percent
Carbon Dioxide (CO2)
1
35.3
9%
64.5
18%
67.5
19%
Methane (CH4)
28
0.004
7%
0.013
23%
0.024
30%
Nitrous Oxide (N20)
265
0.005
10%
0.010
19%
0.010
20%
CO2 Equivalent (CC>2e)
—
36.8
9%
67.4
19%
70.9
20%
Consistent with the differences in modeled HD ZEV adoption between the proposed and final
standards, we estimate the proposed standards have greater GHG emission reductions in earlier
years. For example, total GHG emission reductions are 36.8 MMT in 2035 for the proposed
standards versus 33.8 MMT for the final standards. In 2055, the final standards have greater
GHG emission reductions than the proposed standards (73 MMT versus 70.9 MMT).
Table 4-71 presents the cumulative downstream GHG impacts that we project would result
from both the final standards and the proposed standards from 2027 through 2055.
1425 This algorithm is discussed in Chapter 4.2.3 and Appendix B to this RIA.
650
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Table 4-71 Cumulative 2027-2055 downstream HD GHG emission reductions from the final standards and
the proposed standards
Pollutant
Final Standards
Proposed Standards
Reduction in MMT
Percent
Reduction in MMT
Percent
Carbon Dioxide (CO2)
1,347
13%
1,352
13%
Methane (CH4)
0.127
7%
0.295
17%
Nitrous Oxide (N20)
0.199
13%
0.202
13%
CO2 Equivalent (CC>2e)
1,404
13%
1,414
13%
While we model greater emission reductions for proposed standards in early years and greater
reductions for the final standards in later years, the cumulative emission reductions are almost
identical between the proposed and final standards.
We discuss the emission impacts of the proposed standards on other pollutants in a
memorandum to the docket. We also present the emission impacts of the proposed standards
from upstream EGUs and refineries, according to our updated modeling.1426 Table 4-72 presents
our net cumulative GHG impact estimates for the proposed standards.
Table 4-72 Cumulative 2027-2055 net GHG emission impactsA (in MMT) reflecting the proposed standards
Pollutant
Downstream
EGU
Refineries
Net
Carbon Dioxide (CO2)
-1,352
428
-13
-937
Methane (CH4)
-0.295
0.021
-0.001
-0.275
Nitrous Oxide (N20)
-0.202
0.003
0.000
-0.199
CO2 Equivalent (C02e)
-1,414
429
-13
-998
A We present emissions reductions as negative numbers and emission increases as positive
numbers.
We estimate the net GHG emission reductions from the proposed standards would be 0.998
billion metric tons. This is close to, but smaller than, our estimated GHG emission reductions for
the final standards (1.025 billion metric tons). We model the proposed standards to have a
greater impact on EGU emissions than the final standards, driven largely by the greater ZEV
adoption for HHD vocational vehicles.
When analyzing each scenario using our updated FRM modeling methodology and reference
case, the emission impacts of the proposed and final standards are nearly identical despite their
differences in modeled HD ZEV adoption rates. The change in estimated net emission impacts
from the NPRM to the FRM is therefore attributable to our updated modeling methodologies and
updated reference case rather than to a substantial change in the standards themselves.
1426 Like the downstream emissions modeling methodology, we used identical modeling methodologies to estimate
the upstream impacts from the proposed standards as we used for the final standards.
651
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652
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Chapter 5 Health and Environmental Impacts
5.1 Climate Change Impacts from GHG emissions
Elevated concentrations of greenhouse gases (GHGs) have been warming the planet, leading
to changes in the Earth's climate that are occuring at a pace and in a way that threatens human
health, society, and the natural environment. While EPA is not making any new scientific or
factual findings with regard to the well-documented impact of GHG emissions on public health
and welfare in support of this rule, EPA is providing in this section a brief scientific background
on climate change to offer additional context for this rulemaking and to help the public
understand the environmental impacts of GHGs.
Extensive information on climate change is available in the scientific assessments and the
EPA documents that are briefly described in this section, as well as in the technical and scientific
information supporting them. One of those documents is EPA's 2009 Endangerment and Cause
or Contribute Findings for Greenhouse Gases Under section 202(a) of the CAA (74 FR 66496,
December 15, 2009). In the 2009 Endangerment Finding, the Administrator found under section
202(a) of the CAA that elevated atmospheric concentrations of six key well-mixed GHGs - CO2,
methane (CH4), nitrous oxide (N2O), HFCs, perfluorocarbons (PFCs), and sulfur hexafluoride
(SF6) - "may reasonably be anticipated to endanger the public health and welfare of current and
future generations" (74 FR at 66523). The 2009 Endangerment Finding, together with the
extensive scientific and technical evidence in the supporting record, documented that climate
change caused by human emissions of GHGs threatens the public health of the U.S. population.
It explained that by raising average temperatures, climate change increases the likelihood of heat
waves, which are associated with increased deaths and illnesses (74 FR 66497). While climate
change also increases the likelihood of reductions in cold-related mortality, evidence indicates
that the increases in heat mortality will be larger than the decreases in cold mortality in the U.S.
(74 FR 66525). The 2009 Endangerment Finding further explained that compared with a future
without climate change, climate change is expected to increase tropospheric ozone pollution over
broad areas of the U.S., including in the largest metropolitan areas with the worst tropospheric
ozone problems, and thereby increase the risk of adverse effects on public health (74 FR 66525).
Climate change is also expected to cause more intense hurricanes and more frequent and intense
storms of other types and heavy precipitation, with impacts on other areas of public health, such
as the potential for increased deaths, injuries, infectious and waterborne diseases, and stress-
related disorders (74 FR 66525). Children, the elderly, and the poor are among the most
vulnerable to these climate-related health effects (74 FR 66498).
The 2009 Endangerment Finding also documented, together with the extensive scientific and
technical evidence in the supporting record, that climate change touches nearly every aspect of
public welfare1427in the U.S., including: Changes in water supply and quality due to changes in
drought and extreme rainfall events; increased risk of storm surge and flooding in coastal areas
and land loss due to inundation; increases in peak electricity demand and risks to electricity
1427 The CAA states in section 302(h) that "[a]ll language referring to effects on welfare includes, but is not limited
to, effects on soils, water, crops, vegetation, manmade materials, animals, wildlife, weather, visibility, and climate,
damage to and deterioration of property, and hazards to transportation, as well as effects on economic values and on
personal comfort and well-being, whether caused by transformation, conversion, or combination with other air
pollutants." 42 U.S.C. 7602(h).
653
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infrastructure; and the potential for significant agricultural disruptions and crop failures (though
offset to some extent by carbon fertilization). These impacts are also global and may exacerbate
problems outside the U.S. that raise humanitarian, trade, and national security issues for the U.S.
(74 FR 66530).
In 2016, the Administrator issued a similar finding for GHG emissions from aircraft under
section 231(a)(2)(A) of the CAA.1428 In the 2016 Endangerment Finding, the Administrator
found that the body of scientific evidence amassed in the record for the 2009 Endangerment
Finding compellingly supported a similar endangerment finding under CAA section
231(a)(2)(A), and also found that the science assessments released between the 2009 and the
2016 Findings "strengthen and further support the judgment that GHGs in the atmosphere may
reasonably be anticipated to endanger the public health and welfare of current and future
generations" (81 FR 54424).
Since the 2016 Endangerment Finding, the climate has continued to change, with new
observational records being set for several climate indicators such as global average surface
temperatures, GHG concentrations, and sea level rise. Additionally, major scientific assessments
continue to be released that further advance our understanding of the climate system and the
impacts that GHGs have on public health and welfare both for current and future generations.
1428 "Finding that Greenhouse Gas Emissions From Aircraft Cause or Contribute to Air Pollution That May
Reasonably Be Anticipated To Endanger Public Health and Welfare." 81 FR 54422, August 15, 2016. ("2016
Endangerment Finding").
654
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These updated observations and projections document the rapid rate of current and future climate
change both globally and in the u.S 1429'1430'1431'1432'1433'1434'1435'1436'1437'1438'1439'1440'1441
The most recent information demonstrates that the climate is continuing to change in response
to the human-induced buildup of GHGs in the atmosphere. These recent assessments show that
atmospheric concentrations of GHGs have risen to a level that has no precedent in human history
1429 USGCRP, 2017: Climate Science Special Report: Fourth National Climate Assessment, Volume I [Wuebbles,
D.J., D.W. Fahey, K.A. Hibbard, D.J. Dokken, B.C. Stewart, and T.K. Maycock (eds.)]. U.S. Global Change
Research Program, Washington, DC, USA, 470 pp, doi: 10.7930/J0J964J6.
1430 USGCRP, 2016: The Impacts of Climate Change on Human Health in the United States: A Scientific
Assessment. Crimmins, A., J. Balbus, J.L. Gamble, C.B. Beard, J.E. Bell, D. Dodgen, R.J. Eisen, N. Fann, M.D.
Hawkins, S.C. Herring, L. Jantarasami, D.M. Mills, S. Saha, M.C.
1431 USGCRP, 2018: Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment,
Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C.
Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, 1515 pp. doi:10.7930/NCA4.2018.
1432 IPCC, 2018: Global Warming of 1.5 °C. An IPCC Special Report on the impacts of global warming of 1.5 °C
above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the
global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-
Delmotte, V., P. Zhai, H.-O. Portner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Pean, R.
Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T.
Waterfield (eds.)].
1433 IPCC, 2019: Climate Change and Land: an IPCC special report on climate change, desertification, land
degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems [P.R.
Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Portner, D. C. Roberts, P. Zhai, R. Slade, S.
Connors, R. vanDiemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P.
Vyas, E. Huntley, K. Kissick, M. Belkacemi, J. Malley, (eds.)].
1434 IPCC, 2019: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [H.-O. Portner, D.C.
Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegria, M. Nicolai, A.
Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)].
1434 IPCC, 2023: Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working
Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core
Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 1-34, doi:10.59327/IPCC/AR6-
9789291691647.001.
1435 National Academies of Sciences, Engineering, and Medicine. 2016. Attribution of Extreme Weather Events in
the Context of Climate Change. Washington, DC: The National Academies Press, https://dio.org/10.17226/21852.
1436 National Academies of Sciences, Engineering, and Medicine. 2017. Valuing Climate Damages: Updating
Estimation of the Social Cost of Carbon Dioxide. Washington, DC: The National Academies Press.
https://doi. org/10.17226/24651.
1437 National Academies of Sciences, Engineering, and Medicine. 2019. Climate Change and Ecosystems.
Washington, DC: The National Academies Press, https://doi.org/10.17226/25504.
1438 Blunden, J. and T. Boyer, Eds., 2022: "State of the Climate in 2021". Bull. Amer. Meteor. Soc., 103 (8), Si-
S465, https://doi.org/10.1175/2022BAMSStateoftheClimate. 1.
1439 EPA. 2021. Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts. U.S.
Environmental Protection Agency, EPA 430-R-21-003.
1440 Jay, A.K., A.R. Crimmins, C.W. Avery, T.A. Dahl, R.S. Dodder, B.D. Hamlington, A. Lustig, K. Marvel, P.A.
Mendez-Lazaro, M.S. Osier, A. Terando, E.S. Weeks, and A. Zycherman, 2023: Ch. 1. Overview: Understanding
risks, impacts, and responses. In: Fifth National Climate Assessment. Crimmins, A.R., C.W. Avery, D.R. Easterling,
K.E. Kunkel, B.C. Stewart, and T.K. Maycock, Eds. U.S. Global Change Research Program, Washington, DC, USA.
https://doi.org/10.7930/NCA5.2023.CHl
1441 Jay, A.K., A.R. Crimmins, C.W. Avery, T.A. Dahl, R.S. Dodder, B.D. Hamlington, A. Lustig, K. Marvel,
P.A. Mendez-Lazaro, M.S. Osier, A. Terando, E.S. Weeks, and A. Zycherman, 2023: Ch. 1. Overview:
Understanding risks, impacts, and responses. In: Fifth National Climate Assessment. Crimmins, A.R., C.W. Avery,
D.R. Easterling, K.E. Kunkel, B.C. Stewart, and T.K. Maycock, Eds. U.S. Global Change Research Program,
Washington, DC, USA. https://doi.org/10.7930/NCA5.2023.CHl
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and that they continue to climb, primarily because of both historical and current anthropogenic
emissions, and that these elevated concentrations endanger our health by affecting our food and
water sources, the air we breathe, the weather we experience, and our interactions with the
natural and built environments. For example, atmospheric concentrations of one of these GHGs,
CO2, measured at Mauna Loa in Hawaii and at other sites around the world reached 419 parts per
million (ppm) in 2022 (nearly 50 percent higher than preindustrial levels)1442 and have continued
to rise at a rapid rate. Global average temperature has increased by about 1.1 °C (2.0 °F) in the
2011-2020 decade relative to 1850-1900.1443 The years 2015-2021 were the warmest 7 years in
the 1880-2021 record, contributing to the warmest decade on record with a decadal temperature
of 0.82 °C (1.48 °F) above the 20th century. 1444>1445 The IPCC determined (with medium
confidence) that this past decade was warmer than any multi-century period in at least the past
100,000 years.1446 Global average sea level has risen by about 8 inches (about 21 centimeters
(cm)) from 1901 to 2018, with the rate from 2006 to 2018 (0.15 inches/year or 3.7 millimeters
(mm)/year) almost twice the rate over the 1971 to 2006 period, and three times the rate of the
1901 to 2018 period.1447 The rate of sea level rise over the 20th century was higher than in any
other century in at least the last 2,800 years.1448 Higher CO2 concentrations have led to
acidification of the surface ocean in recent decades to an extent unusual in the past 65 million
years, with negative impacts on marine organisms that use calcium carbonate to build shells or
skeletons.1449 Arctic sea ice extent continues to decline in all months of the year; the most rapid
reductions occur in September (very likely almost a 13 percent decrease per decade between
1979 and 2018) and are unprecedented in at least 1,000 years.1450 Human-induced climate
change has led to heatwaves and heavy precipitation becoming more frequent and more intense,
along with increases in agricultural and ecological droughts1451 in many regions.1452
The assessment literature demonstrates that modest additional amounts of warming may lead
to a climate different from anything humans have ever experienced. The 2022 CO2 concentration
of 419 ppm is already higher than at any time in the last 2 million years.1453 If concentrations
exceed 450 ppm, they would likely be higher than any time in the past 23 million years:1454 at the
1442 https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt.
1443 IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of
Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-
Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Pean, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M.
Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yclckci. R. Yu, and B. Zhou
(eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3-32,
doi: 10.1017/9781009157896.001.
1444 NOAA National Centers for Environmental Information, State of the Climate 2021 retrieved on August 3, 2023,
from https://www.ncei.noaa.gov/bams-state-of-climate.
1445 Blunden, el al. 2022.
1446 IPCC, 2021.
1447 IPCC, 2021.
1448 USGCRP, 2018: Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment,
Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C.
Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, 1515 pp. doi:10.7930/NCA4.2018.
1449 IPCC, 2018.
27 IPCC, 2021.
1451 These are drought measures based on soil moisture.
1452 IPCC, 2021.
1453 Annual Mauna Loa CO2 concentration data from
https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt, accessed September 9, 2023.
1454 IPCC, 2013.
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current rate of increase of more than 2 ppm a year, this would occur in about 15 years. While
GHGs are not the only factor that controls climate, it is illustrative that 3 million years ago (the
last time CO2 concentrations were above 400 ppm) Greenland was not yet completely covered by
ice and still supported forests, while 23 million years ago (the last time concentrations were
above 450 ppm) the West Antarctic ice sheet was not yet developed, indicating the possibility
that high GHG concentrations could lead to a world that looks very different from today and
from the conditions in which human civilization has developed. If the Greenland and Antarctic
ice sheets were to melt substantially, sea levels would rise dramatically—the IPCC estimated that
over the next 2,000 years, sea level will rise by 7 to 10 feet even if warming is limited to 1.5 °C
(2.7 °F), from 7 to 20 feet if limited to 2 °C (3.6 °F), and by 60 to 70 feet if warming is allowed
to reach 5 °C (9 °F) above preindustrial levels.1455 For context, almost all of the city of Miami is
less than 25 feet above sea level, and the 4th National Climate Assessment (NCA4) stated that 13
million Americans would be at risk of migration due to 6 feet of sea level rise.
The NCA4 found that it is very likely (greater than 90 percent likelihood) that by mid-
century, the Arctic Ocean will be almost entirely free of sea ice by late summer for the first time
in about 2 million years.1456 Coral reefs will be at risk for almost complete (99 percent) losses
with 1 °C (1.8 °F) of additional warming from today (2 °C or 3.6 °F since preindustrial). At this
temperature, between 8 and 18 percent of animal, plant, and insect species could lose over half of
the geographic area with suitable climate for their survival, and 7 to 10 percent of rangeland
livestock would be projected to be lost.1457 The IPCC similarly found that climate change has
caused substantial damages and increasingly irreversible losses in terrestrial, freshwater, and
coastal and open ocean marine ecosystems.
Every additional increment of temperature comes with consequences. For example, the half
degree of warming from 1.5 to 2°C (0.9°F of warming from 2.7°F to 3.6°F) above preindustrial
temperatures is projected on a global scale to expose 420 million more people to frequent
extreme heatwaves, and 62 million more people to frequent exceptional heatwaves (where
heatwaves are defined based on a heat wave magnitude index which takes into account duration
and intensity—using this index, the 2003 French heat wave that led to almost 15,000 deaths
would be classified as an "extreme heatwave" and the 2010 Russian heatwave which led to
thousands of deaths and extensive wildfires would be classified as "exceptional"). It would
increase the frequency of sea-ice-free Arctic summers from once in 100 years to once in a
decade. It could lead to 4 inches of additional sea level rise by the end of the century, exposing
an additional 10 million people to risks of inundation as well as increasing the probability of
triggering instabilities in either the Greenland or Antarctic ice sheets. Between half a million and
a million additional square miles of permafrost would thaw over several centuries. Risks to food
security would increase from medium to high for several lower-income regions in the Sahel,
southern Africa, the Mediterranean, central Europe, and the Amazon. In addition to food security
issues, this temperature increase would have implications for human health in terms of increasing
ozone concentrations, heatwaves, and vector-borne diseases (for example, expanding the range
of the mosquitoes which carry dengue fever, chikungunya, yellow fever, and the Zika virus, or
the ticks which carry Lyme, babesiosis, or Rocky Mountain Spotted Fever).1458 Moreover, every
1455 IPCC, 2021.
1456 USGCRP, 2018.
1457 IPCC, 2018.
1458 IPCC, 2018.
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additional increment in warming leads to larger changes in extremes, including the potential for
events unprecedented in the observational record. Every additional degree will intensify extreme
precipitation events by about 7 percent. The peak winds of the most intense tropical cyclones
(hurricanes) are projected to increase with warming. In addition to a higher intensity, the IPCC
found that precipitation and frequency of rapid intensification of these storms has already
increased, the movement speed has decreased, and elevated sea levels have increased coastal
flooding, all of which make these tropical cyclones more damaging.1459
The NCA4 also evaluated a number of impacts specific to the U.S. Severe drought and
outbreaks of insects like the mountain pine beetle have killed hundreds of millions of trees in the
western U.S. Wildfires have burned more than 3.7 million acres in 14 of the 17 years between
2000 and 2016, and Federal wildfire suppression costs were about a billion dollars annually.1460
The National Interagency Fire Center has documented U.S. wildfires since 1983, and the 10
years with the largest acreage burned have all occurred since 2004.1461 Wildfire smoke degrades
air quality, increasing health risks, and more frequent and severe wildfires due to climate change
would further diminish air quality, increase incidences of respiratory illness, impair visibility,
and disrupt outdoor activities, sometimes thousands of miles from the location of the fire.
Meanwhile, sea level rise has amplified coastal flooding and erosion impacts, requiring the
installation of costly pump stations, flooding streets, and increasing storm surge damages. Tens
of billions of dollars of U.S. real estate could be below sea level by 2050 under some scenarios.
Increased frequency and duration of drought will reduce agricultural productivity in some
regions, accelerate depletion of water supplies for irrigation, and expand the distribution and
incidence of pests and diseases for crops and livestock. The NCA4 also recognized that climate
change can increase risks to national security, both through direct impacts on military
infrastructure and by affecting factors such as food and water availability that can exacerbate
conflict outside U.S. borders. Droughts, floods, storm surges, wildfires, and other extreme events
stress nations and people through loss of life, displacement of populations, and impacts on
livelihoods.1462
EPA modeling efforts can further illustrate how these impacts from climate change may be
experienced across the U.S. EPA's Framework for Evaluating Damages and Impacts (FrEDI)1463
uses information from over 30 peer-reviewed climate change impact studies to project the
physical and economic impacts of climate change to the U.S. resulting from future temperature
changes. These impacts are projected for specific regions within the U.S. and for more than 20
1459 IPCC, 2021.
1460 USGCRP, 2018.
1461 NIFC (National Interagency Fire Center). 2021. Total wildland fires and acres (1983-2020). Accessed August
2021. www.nifc.gov/fireInfo/fireInfo_stats_totalFires. html.
1462 USGCRP, 2018.
1463 (1) Hartin, C., et al. (2023). Advancing the estimation of future climate impacts within the United States. Earth
Syst. Dynam., 14, 1015-1037, https://dio.org/10.5194/esd-14-1015-2023. (2) Supplementary Material for the
Regulatory Impact Analysis for the Supplemental Proposed Rulemaking, "Standards of Performance for New,
Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil and Natural Gas Sector
Climate Review, " Docket ID No. EPA-HQ-OAR-2021-0317, September 2022, (3) The Long-Term Strategy of the
United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050. Published by the U.S. Department of
State and the U.S. Executive Office of the President, Washington DC. November 2021, (4) Climate Risk Exposure:
An Assessment of the Federal Government's Financial Risks to Climate Change, White Paper, Office of
Management and Budget, April 2022.
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impact categories, which span a large number of sectors of the U.S. economy.1464 Using this
framework, the EPA estimates that global emission projections, with no additional mitigation,
will result in significant climate-related damages to the U.S.1465 These damages to the U.S.
would mainly be from increases in lives lost due to increases in temperatures, as well as impacts
to human health from increases in climate-driven changes in air quality, dust and wildfire smoke
exposure, and incidence of suicide. Additional major climate-related damages would occur to
U.S. infrastructure such as roads and rail, as well as transportation impacts and coastal flooding
from sea level rise, increases in property damage from tropical cyclones, and reductions in labor
hours worked in outdoor settings and buildings without air conditioning. These impacts are also
projected to vary from region to region with the Southeast, for example, projected to see some of
the largest damages from sea level rise, the West Coast projected to experience damages from
wildfire smoke more than other parts of the country, and the Northern Plains states projected to
see a higher proportion of damages to rail and road infrastructure. While information on the
distribution of climate impacts helps to better understand the ways in which climate change may
impact the U.S., recent analyses are still only a partial assessment of climate impacts relevant to
U.S. interests and in addition do not reflect increased damages that occur due to interactions
between different sectors impacted by climate change or all the ways in which physical impacts
of climate change occurring abroad have spillover effects in different regions of the U.S.
Some GHGs also have impacts beyond those mediated through climate change. For example,
elevated concentrations of CO2 stimulate plant growth (which can be positive in the case of
beneficial species, but negative in terms of weeds and invasive species, and can also lead to a
reduction in plant micronutrients1466) and cause ocean acidification. Nitrous oxide depletes the
levels of protective stratospheric ozone.1467
Transportation is the largest U.S. source of GHG emissions, representing 27 percent of total
GHG emissions. Within the transportation sector, heavy-duty vehicles are the second largest
contributor to GHG emissions and are responsible for 25 percent of GHG emissions in the sector.
The GHG emission reductions resulting from compliance with this final rule will significantly
reduce the volume of GHG emissions from this sector. Chapter 5.4.2 of this RIA discusses
impacts of GHG emissions on individuals living in socially and economically vulnerable
communities. While EPA did not conduct modeling to specifically quantify changes in climate
impacts resulting from this rule in terms of avoided temperature change or sea-level rise, we did
quantify climate benefits by monetizing the emission reductions through the application of the
social cost of greenhouse gases (SC-GHGs), as described in Chapter 7.1 of this RIA.
1464 gpA (2021). Technical Documentation on the Framework for Evaluating Damages and Impacts (FrEDI). U.S.
Environmental Protection Agency, EPA 430-R-21-004, available at https://www.epa.gov/cira/fredi. Documentation
has been subject to both a public review comment period and an independent expert peer review, following EPA
peer-review guidelines.
1465 Compared to a world with no additional warming after the model baseline (1986-2005)
1466 Ziska, L., A. Crimmins, A. Auclair, S. DeGrasse, J.F. Garofalo, A.S. Khan, I. Loladze, A.A. Perez de Leon, A.
Showier, J. Thurston, and I. Walls, 2016: Ch. 7: Food Safety, Nutrition, and Distribution. The Impacts of Climate
Change on Human Health in the United States: A Scientific Assessment. U.S. Global Change Research Program,
Washington, DC, 189-216. https://health2016.globalchange.gov/low/ClimateHealth2016_07_Food_small.pdf.
1467 WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2018, Global Ozone
Research and Monitoring Project - Report No. 58, 588 pp., Geneva, Switzerland, 2018.
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These scientific assessments, the EPA analyses, and documented observed changes in the
climate of the planet and of the U.S. present clear support regarding the current and future
dangers of climate change and the importance of GHG emissions mitigation.
5.2 Climate Benefits
The EPA estimates the climate benefits of GHG emissions reductions expected from the final
rule using estimates of the social cost of greenhouse gases (SC-GHG) that reflect recent
advances in the scientific literature on climate change and its economic impacts and incorporate
recommendations made by the National Academies of Science, Engineering, and Medicine
(National Academies 2017).1468 The EPA published and used these estimates in the RIA for the
December 2023 Final Oil and Gas NSPS/EG Rulemaking, "Standards of Performance for New,
Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil and
Natural Gas Sector Climate Review" (EPA 2023f).1469 The EPA solicited public comment on the
methodology and use of these estimates in the RIA for the agency's December 2022 Oil and Gas
NSPS/EG Supplemental Proposal1470 and has conducted an external peer review of these
estimates, as described further below.
The SC-GHG is the monetary value of the net harm to society associated with a marginal
increase in GHG emissions in a given year, or the benefit of avoiding that increase. In principle,
SC-GHG includes the value of all climate change impacts (both negative and positive), including
(but not limited to) changes in net agricultural productivity, human health effects, property
damage from increased flood risk and natural disasters, disruption of energy systems, risk of
conflict, environmental migration, and the value of ecosystem services. The SC-GHG, therefore,
reflects the societal value of reducing emissions of the gas in question by one metric ton and is
the theoretically appropriate value to use in conducting benefit-cost analyses of policies that
affect GHG emissions. In practice, data and modeling limitations restrain the ability of SC-GHG
estimates to include all physical, ecological, and economic impacts of climate change, implicitly
assigning a value of zero to the omitted climate damages. The estimates are, therefore, a partial
accounting of climate change impacts and likely underestimate the marginal benefits of
abatement.
Since 2008, the EPA has used estimates of the social cost of various greenhouse gases (i.e.,
SC-CO2, SC-CH4, and SC-N2O), collectively referred to as the "social cost of greenhouse gases"
(SC-GHG), in analyses of actions that affect GHG emissions. The values used by the EPA from
2009 to 2016, and since 2021 - including in the proposal for this rulemaking - have been
consistent with those developed and recommended by the IWG on the SC-GHG; and the values
used from 2017 to 2020 were consistent with those required by E.O. 13783, which disbanded the
IWG. During 2015-2017, the National Academies conducted a comprehensive review of the SC-
CO2 and issued a final report in 2017 recommending specific criteria for future updates to the
1468 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1469 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:DocketID No. EPA-HQ-OAR-2021-0317.
1470 See https://www.epa.gov/environmental-economics/scghg for a copy of the final report and other related
materials.
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SC-CO2 estimates, a modeling framework to satisfy the specified criteria, and both near-term
updates and longer-term research needs pertaining to various components of the estimation
process.1471 The IWG was reconstituted in 2021 and E.O. 13990 directed it to develop a
comprehensive update of its SC-GHG estimates, recommendations regarding areas of decision-
making to which SC-GHG should be applied, and a standardized review and updating process to
ensure that the recommended estimates continue to be based on the best available economics and
science going forward.
The EPA is a member of the IWG and is participating in the IWG's work under E.O. 13990.,
As noted in previous EPA RIAs, while that process continues, the EPA is continuously
reviewing developments in the scientific literature on the SC-GHG, including more robust
methodologies for estimating damages from emissions, and looking for opportunities to further
improve SC-GHG estimation 1472 In the December 2022 Oil and Gas NSPS/EG Supplemental
Proposal RIA, the Agency included a sensitivity analysis of the climate benefits of the
Supplemental Proposal using a new set of SC-GHG estimates that incorporates recent research
addressing recommendations of the National Academies1473 in addition to using the interim SC-
GHG estimates presented in the Technical Support Document: Social Cost of Carbon, Methane,
and Nitrous Oxide Interim Estimates under Executive Order 139901474 that the IWG
recommended for use until updated estimates that address the National Academies'
recommendations are available.
The EPA solicited public comment on the sensitivity analysis and the accompanying draft
technical report, External Review Draft of Report on the Social Cost of Greenhouse Gases:
Estimates Incorporating Recent Scientific Advances, which explains the methodology underlying
the new set of estimates, in the December 2022 Supplemental Oil and Gas Proposal. The
response to comments document can be found in the docket for that action.
To ensure that the methodological updates adopted in the technical report are consistent with
economic theory and reflect the latest science, the EPA also initiated an external peer review
panel to conduct a high-quality review of the technical report, completed in May 2023. See 88
FR at 26075/2 noting this peer review process. The peer reviewers commended the agency on its
development of the draft update, calling it a much-needed improvement in estimating the SC-
GHG and a significant step towards addressing the National Academies' recommendations with
defensible modeling choices based on current science. The peer reviewers provided numerous
recommendations for refining the presentation and for future modeling improvements, especially
with respect to climate change impacts and associated damages that are not currently included in
the analysis. Additional discussion of omitted impacts and other updates have been incorporated
in the technical report to address peer reviewer recommendations. Complete information about
1471 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1472 EPA strives to base its analyses on the best available science and economics, consistent with its responsibilities,
for example, under the Information Quality Act.
1473 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1474 IWG. 2021. Social Cost of Carbon, Methane, and Nitrous Oxide: Interim Estimates under Executive Order
13990. Technical Support Government, Interagency Working Group on Social Cost of Carbon, United States
Government.
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the external peer review, including the peer reviewer selection process, the final report with
individual recommendations from peer reviewers, and the EPA's response to each
recommendation is available on EPA's website.1475
The remainder of this section provides an overview of the methodological updates
incorporated into the SC-GHG estimates used in this final RIA. A more detailed explanation of
each input and the modeling process is provided in the final technical report, EPA Report on the
Social Cost of Greenhouse Gases: Estimates Incorporating Recent Scientific Advances.
Appendix C to this RIA shows the benefits of the final rule using the interim SC-GHG estimates
presented in the proposal.1476
The steps necessary to estimate the SC-GHG with a climate change integrated assessment
model (IAM) can generally be grouped into four modules: socioeconomics and emissions,
climate, damages, and discounting. The emissions trajectories from the socioeconomic module
are used to project future temperatures in the climate module. The damage module then
translates the temperature and other climate endpoints (along with the projections of
socioeconomic variables) into physical impacts and associated monetized economic damages,
where the damages are calculated as the amount of money the individuals experiencing the
climate change impacts would be willing to pay to avoid them. To calculate the marginal effect
of emissions, i.e., the SC-GHG in year t, the entire model is run twice - first as a baseline and
second with an additional pulse of emissions in year t. After recalculating the temperature effects
and damages expected in all years beyond t resulting from the adjusted path of emissions, the
losses are discounted to a present value in the discounting module. Many sources of uncertainty
in the estimation process are incorporated using Monte Carlo techniques by taking draws from
probability distributions that reflect the uncertainty in parameters.
The SC-GHG estimates used by the EPA and many other federal agencies since 2009 have
relied on an ensemble of three widely used IAMs: Dynamic Integrated Climate and Economy
(DICE)1477 Climate Framework for Uncertainty, Negotiation, and Distribution (FUND)1478'1479
and Policy Analysis of the Greenhouse Gas Effect (PAGE)1480. In 2010, the IWG harmonized
key inputs across the IAMs, but all other model features were left unchanged, relying on the
model developers' best estimates and judgments. That is, the representation of climate dynamics
1475 EPA. 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1476 IWG. 2021. Social Cost of Carbon, Methane, and Nitrous Oxide: Interim Estimates under Executive Order
13990. Technical Support Government, Interagency Working Group on Social Cost of Carbon, United States
Government.
1477 Nordhaus, W.D. 2010. "Economic aspects of global warming in a post-Copenhagen environment." Proceedings
of the National Academy of Sciences of the United States of America 107(26), 11721-11726.
1478 Anthoff, D, and R.S.J Tol. 2013. "Erratum to: The uncertainty about the social cost of carbon: A decomposition
analysis using FUND." Climatic Change 121(2), 413.
1479 Anthoff, D, and R. S. J. Tol. 2013b. "The uncertainty about the social cost of carbon: A decomposition analysis
using FUND." Climate Change 117(3), 515-530. doi:https://doi.org/10.1007/sl0584-013-0706-7.
1480 Hope, C. 2013. "Critical issues for the calculation of the social cost of C02: why the estimates from PAGE09
are higher than those fromPAGE2002." Climate Change 117(3), 531-543. doi:https://doi.org/10.1007/sl0584-012-
0633-z.
662
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and damage functions included in the default version of each IAM as used in the published
literature was retained.
The SC-GHG estimates in this RIA no longer rely on the three IAMs (i.e., DICE, FUND, and
PAGE) used in previous SC-GHG estimates. As explained previously, EPA uses a modular
approach to estimate the SC-GHG, consistent with the National Academies' near-term
recommendations.1481 That is, the methodology underlying each component, or module, of the
SC-GHG estimation process is developed by drawing on the latest research and expertise from
the scientific disciplines relevant to that component. Under this approach, each step in the SC-
GHG estimation improves consistency with the current state of scientific knowledge, enhances
transparency, and allows for more explicit representation of uncertainty.
The socioeconomic and emissions module relies on a new set of probabilistic projections for
population, income, and GHG emissions developed under the Resources for the Future (RFF)
Social Cost of Carbon Initiative (K. P. Rennert 2021) (Rennert, Prest, et al. 2022a).1482'1483 These
socioeconomic projections (hereafter collectively referred to as the RFF-SPs) are an internally
consistent set of probabilistic projections of population, GDP, and GHG emissions (CO2, CH4,
and N2O) to 2300. Based on a review of available sources of long-run projections necessary for
damage calculations, the RFF-SPs stand out as being most consistent with the National
Academies' recommendations. Consistent with the National Academies' recommendation, the
RFF-SPs were developed using a mix of statistical and expert elicitation techniques to capture
uncertainty in a single probabilistic approach, taking into account the likelihood of future
emissions mitigation policies and technological developments, and provide the level of
disaggregation necessary for damage calculations. Unlike other sources of projections, they
provide inputs for estimation out to 2300 without further extrapolation assumptions. Conditional
on the modeling conducted for the SC-GHG estimates, this time horizon is far enough in the
future to capture the majority of discounted climate damages. Including damages beyond 2300
would increase the estimates of the SC-GHG. As discussed in EPA 2023f the use of the RFF-SPs
allows for capturing economic growth uncertainty within the discounting module.1484
The climate module relies on the Finite Amplitude Impulse Response (FaIR) model (Smith, et
al. 2018, IPCC, Climate Change 2021 - The Physical Science Basis 2021, Millar, et al.
1481 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1482 Rennert, K., Prest, B.C., Pizer, W.A., Newell, R.G., Anthoff, D., Kingdon, C., Rennels, L., Cooke, R., Raftery,
A.E., Sevcikova, H. and Errickson, F. 2021. "The social cost of carbon: Advances in long-term probablisitic
projections of poulation, GDP, emissions, and discount rates." Brookings Papers on Economic Activity 223-305.
1483 Rennert, K, F Errickson, BC Prest, L Rennels, R Newell, W Pizer, C Kingdon, J Wingenroth, and R Cooke.
2022. "Comprehensive evidence implies a higher social cost of C02." Nature 610(7933): 687-692.
1484 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:DocketID No. EPA-HQ-OAR-2021-0317.
663
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20 1 7)1485'1486'1487, a widely used Earth system model which captures the relationships between
GHG emissions, atmospheric GHG concentrations, and global mean surface temperature. The
FaIR model was originally developed by Richard Millar, Zeb Nicholls, and Myles Allen at
Oxford University, as a modification of the approach used in IPCC AR5 to assess the GWP and
GTP (Global Temperature Potential) of different gases. It is open source, widely used (e.g.,
IPCC 2018; IPCC 2021a)1488'1489 and was highlighted by the National Academies1490 as a model
that satisfies their recommendations for a near-term update of the climate module in SC-GHG
estimation. Specifically, it translates GHG emissions into mean surface temperature response and
represents the current understanding of the climate and GHG cycle systems and associated
uncertainties within a probabilistic framework. The SC-GHG estimates used in this RIA rely on
FaIR version 1.6.2 as used by the IPCC1491. It provides, with high confidence, an accurate
representation of the latest scientific consensus on the relationship between global emissions and
global mean surface temperature and offers a code base that is fully transparent and available
online. The uncertainty capabilities in FaIR 1.6.2 have been calibrated to the most recent
assessment of the IPCC (which importantly narrowed the range of likely climate sensitivities
relative to prior assessments). See EPA 2023f for more details.1492
The socioeconomic projections and outputs of the climate module are inputs into the damage
module to estimate monetized future damages from climate change1493. The National
Academies' recommendations for the damage module, scientific literature on climate damages,
1485 Smith, CJ, PMForster, M Allen, N Leach, RJ Millar, GA Passerello, and LA Regayre. 2018. "FAIR vl.3: a
simple emissions-based impulse response and carbon cycle model." Geosci. Model Dev. 11(6): 2273-2297.
doi:https://doi.org/10.5194/gmd-l 1-2273-2018.
1486 IPCC. 2021. "Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution
of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change."
Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press. 3-32.
doi: 10.1017/9781009157896.001.
1487 Millar, RJ, ZR Nicholls, P Friedlingstein, and MR Allen. 2017. "A modified impulse-response representation of
the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions."
Atmospheric Chemistry and Physics 17(11): 7213-7228.
1488 IPCC. 2018. "Global Warming of 1.5 °C. An IPCC Special Report on the impacts of global warming of 1.5 °C
above pre-industrial levels..."
1489 —. 2021a. Climate Change 2021: The Physical Science Basis. Vol. Contribution of Working Group I to the
Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Online: Cambridge University Press,
doi :https ://www. ipcc. ch/report/ar6/wg 1.
1490 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1491 IPCC. 2021. Climate Change 2021 - The Physical Science Basis. Online: Cambridge University Press,
https ://www. ipcc. ch/report/ar6/wg l/downloads/report/IPCC_AR6_W GI_Chapter07 .pdf.
1492 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1493 In addition to temperature change, two of the three damage modules used in the SC-GHG estimation require
global mean sea level (GMSL) projections as an input to estimate coastal damages. Those two damage modules use
different models for generating estimates of GMSL. Both are based off reduced complexity models that can use the
FaIR temperature outputs as inputs to the model and generate projections of GMSL accounting for the contributions
of thermal expansion and glacial and ice sheet melting based on recent scientific research. Absent clear evidence on
a preferred model, the SC-GHG estimates presented in this RIA retain both methods used by the damage module
developers. See (EPA 2023f) for more details.
664
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updates to models that have been developed since 2010, as well as the public comments received
on individual EPA rulemakings and the IWG's February 2021 TSD, have all helped to identify
available sources of improved damage functions. The IWG (e.g., (IWG2010) (IWG 2016a)
(IWG2021) 1494,1495>1496)3 the National Academies (2017) 1497, comprehensive studies (e.g.,
(Rose, et al. 2014)1498), and public comments have all recognized that the damages functions
underlying the IWG SC-GHG estimates used since 2013 (taken from DICE 2010 (W. Nordhaus
2010)1499• FUND 3.8 (Anthoff and Tol 2013b)1500; (Anthoff and Tol 20 1 3)1501; and PAGE 2009
(Hope 2013)1502) do not include all the important physical, ecological, and economic impacts of
climate change. The climate change literature and the science underlying the economic damage
functions have evolved, and DICE 2010, FUND 3.8, and PAGE 2009 now lag behind the most
recent research.
The challenges involved with updating damage functions have been widely recognized.
Functional forms and calibrations are constrained by the available literature and need to
extrapolate beyond warming levels or locations studied in that literature. Research and public
resources focused on understanding how these physical changes translate into economic impacts
have been significantly less than the resources focused on modeling and improving our
understanding of climate system dynamics and the physical impacts from climate change
(Auffhammer 20 1 8).1503 Even so, there has been a large increase in research on climate impacts
and damages in the time since DICE 2010, FUND 3.8, and PAGE 2009 were published. Along
with this growth, there continues to be wide variation in methodologies and scope of studies,
such that care is required when synthesizing the current understanding of impacts or damages.
Based on a review of available studies and approaches to damage function estimation, the EPA
uses three separate damage functions to form the damage module. They are:
1494 IWG 2010. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis under
Executive Order 12866. Accessed 2023. https://www.epa.gov/sites/default/files/2016-
12/documents/scc_tsd_2010 .pdf.
1495 IWG. 2016a. Addendum to Technical Support Document on Social Cost of Carbon for Regulatory Impact
Analysis under Executive Order 12866: Application of the Methodology to Estimate the Social Cost of Methane and
the Social Cost of Nitrous Oxide, https://www.epa.gov/sites/default/files/2016-12/documents/addendum_to_sc-
ghg_tsd_august_2016.pdf.
1496 IWG. 2021. Social Cost of Carbon, Methane, and Nitrous Oxide: Interim Estimates under Executive Order
13990. Technical Support Government, Interagency Working Group on Social Cost of Carbon, United States
Government.
1497 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1498 Rose, S, D Turner, G Blanford, J Bistline, F de la Chesnaye, and T Wilson. 2014. "Understanding the Social
Cost of Carbon: A Technical Assessment." EPRI Technical Update Report, Palo Alto, CA.
1499 Nordhaus, W.D. 2010. "Economic aspects of global warming in a post-Copenhagen environment. ." Proceedings
of the National Academy of Sciences of the United States of America 107(26), 11721-11726
i5°° Anthoff, D, and R. S. J. Tol. 2013b. "The uncertainty about the social cost of carbon: A decomposition analysis
using FUND." Climate Change 117(3), 515-530. doi:https://doi.org/10.1007/sl0584-013-0706-7.
1501 Anthoff, D, and R.S.J Tol. 2013. "Erratum to: The uncertainty about the social cost of carbon: A decomposition
analysis using FUND." Climatic Change 121(2), 413.
1502 Hope, C. 2013. "Critical issues for the calculation of the social cost of C02: why the estimates from PAGE09
are higher than those fromPAGE2002." Climate Change 117(3), 531-543. doi:https://doi.org/10.1007/sl0584-012-
0633-z.
1503 Auffhammer, M. 2018. "Quantifying economic damages from climate change." Journal of Economic
Perspectives 32(4): 33-52.
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A subnational-scale, sectoral damage function (based on the Data-driven Spatial Climate
Impact Model (DSCIM) developed by the Climate Impact Lab (CIL 2023)1504 (Carleton
2022)1505 (Rode, et al. 2021)1506, a country-scale, sectoral damage function (based on the
Greenhouse Gas Impact Value Estimator (GIVE) model developed under RFF's Social Cost of
Carbon Initiative (Rennert, Errickson, et al. 2022)1507 and a meta-analysis-based damage
function (based on (Howard and Sterner 20 1 7)1508). The damage functions in DSCIM and GIVE
represent substantial improvements relative to the damage functions underlying the SC-GHG
estimates used by the EPA to date and reflect the forefront of scientific understanding about how
temperature change and SLR lead to monetized net (market and nonmarket) damages for several
categories of climate impacts. The models' spatially explicit and impact-specific modeling of
relevant processes allow for improved understanding and transparency about mechanisms
through which climate impacts are occurring and how each damage component contributes to the
overall results, consistent with the National Academies' recommendations. DSCIM addresses
common criticisms related to the damage functions underlying current SC-GHG estimates (e.g.,
(Pindyck 2017)1509) by developing multi-sector, empirically grounded damage functions. The
damage functions in the GIVE model offer a direct implementation of the National Academies'
near-term recommendation to develop updated sectoral damage functions that are based on
recently published work and reflective of the current state of knowledge about damages in each
sector. Specifically, the National Academies noted that "[t]he literature on agriculture, mortality,
coastal damages, and energy demand provide immediate opportunities to update the
[models]",1510 which are the four damage categories currently in GIVE. A limitation of both
models is that the sectoral coverage is still limited, and even the categories that are represented
are incomplete. Neither DSCIM nor GIVE yet accommodate estimation of several categories of
temperature driven climate impacts (e.g., morbidity, conflict, migration, biodiversity loss) and
only represent a limited subset of damages from changes in precipitation. For example, while
precipitation is considered in the agriculture sectors in both DSCIM and GIVE, neither model
takes into account impacts of flooding, changes in rainfall from tropical storms, and other
precipitation related impacts. As another example, the coastal damage estimates in both models
do not fully reflect the consequences of SLR-driven salt-water intrusion and erosion, or SLR
damages to coastal tourism and recreation. Other missing elements are damages that result from
1504 CIL, Climate Impact Lab. 2023. Documentation for Data-driven Spatial Climate Impact Model (DSCIM).
https://impactlab.org/wpcontent/uploads/2023/10/DSCIM_UserManual_Version092023-EPA.pdf.
1505 Carleton, T., Jina, A., Delgado, M., Greenstone, M., Houser, T., Hsiang, S., Hultgren, A., Kopp, R.E.,
McCusker, K.E., Nath, I., Rising, J., Ashwin, A., Seo, H., Viaene, A., Yaun, J., and Zhang, A.,. 2022. "Valuing the
Global mortality Consequences of Climate Change Accounting for Adaptation Costs and Benefits." The Quarterly
Journal of Economics 137(4): 2037-2105.
1506 Rode, A, T Carleton, M Delgado, M Greenstone, T Houser, S Hsiang, A Hultgren, et al. 2021. "Estimating a
social cost of carbon for global energy consumption." Nature 598(7880): 308-314.
1507 Rennert, K, F Errickson, BC Prest, L Rennels, R Newell, W Pizer, C Kingdon, J Wingenroth, and R Cooke.
2022. "Comprehensive evidence implies a higher social cost of C02." Nature 610(7933): 687-692.
1508 Howard, PH, and T Sterner. 2017. "Few and not so far between: a meta-analysis of climate damage estimates."
Environmental Resource Economics 68(1): 197-225.
1509 Pindyck, RS. 2017. "Comments on Proposed Rule and Regulatory Impact Analysis on the Delay and Suspension
of Certain Requirements for Waster Prevention and Resource Conservation." Accessed Comment submitted on Nov.
6, 2017. https://downloads.regulations.gov/EPA-HQ-OAR-2018-0283- 6184/attachment_6.pdf.
i5i° National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
666
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other physical impacts (e.g., ocean acidification, non-temperature-related mortality such as
diarrheal disease and malaria) and the many feedbacks and interactions across sectors and
regions that can lead to additional damages1511. See EPA 2023f1512 for more discussion of
omitted damage categories and other modeling limitations. DSCIM and GIVE do account for the
most commonly cited benefits associated with CO2 emissions and climate change - C02 crop
fertilization and declines in cold related mortality. As such, while the GIVE- and DSCIM-based
results provide state-of-the-science assessments of key climate change impacts, they remain
partial estimates of future climate damages resulting from incremental changes in C02, CH4,
and N20.1513
Finally, given the still relatively narrow sectoral scope of the recently developed DSCIM and
GIVE models, the damage module includes a third damage function that reflects a synthesis of
the state of knowledge in other published climate damages literature. Studies that employ meta-
analytic techniques1514 offer a tractable and straightforward way to combine the results of
multiple studies into a single damage function that represents the body of evidence on climate
damages that pre-date CIL and RFF's research initiatives. The first use of meta-analysis to
combine multiple climate damage studies was done by (Tol 2009)1515 and included 14 studies.
The studies in (Tol 2009) served as the basis for the global damage function in DICE starting in
version 2013R (W. Nordhaus 2014)1516. The damage function in the most recent published
version of DICE, DICE 2016, is from an updated meta-analysis based on a rereview of existing
damage studies and included 26 studies published over 1994-2013. Howard and Sterner provide
a more recent published peer-reviewed meta-analysis of existing damage studies (published
through 2016) and account for additional features of the underlying studies (Howard and Sterner
2017).1517 This study address differences in measurement across studies by adjusting estimates
such that the data are relative to the same base period. They also eliminate double counting by
removing duplicative estimates. Howard and Sterner's final sample is drawn from 20 studies that
were published through 2015. Howard and Sterner present results under several specifications
and shows that the estimates are somewhat sensitive to defensible alternative modeling choices.
1511 The one exception is that the agricultural damage function in DSCIM and GIVE reflects the ways that trade can
help mitigate damages arising from crop yield impacts.
1512 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1513 One advantage of the modular approach used by these models is that future research on new or alternative
damage functions can be incorporated in a relatively straightforward way. DSCIM and GIVE developers have work
underway on other impact categories that may be ready for consideration in future updates (e.g., morbidity and
biodiversity loss).
1514 Meta-analysis is a statistical method of pooling data and/or results from a set of comparable studies of a
problem. Pooling in this way provides a larger sample size for evaluation and allows for a stronger conclusion than
can be provided by any single study. Meta-analysis yields a quantitative summary of the combined results and
current state of the literature.
1515 Tol, R. 2009. An analysis of mitigation as a response to climate change. Copenhagen Consensus on Climate,
Copenhagen Consensus Center.
1516 Nordhaus, W. 2014. "Estimates of the social cost of carbon: concepts and results from the DICE 2013R model
and alternative approaches." Journal of the Association of Environmental Economists 1(1/2): 273-312.
1517 Howard, PH, and T Sterner. 2017. "Few and not so far between: a meta-analysis of climate damage estimates."
Environmental Resource Economics 68(1): 197-225.
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As discussed in detail in EPA 2023f,1518 the damage module underlying the SC-GHG estimates
in this RIA includes the damage function specification (that excludes duplicate studies) from
Howard and Sterner that leads to the lowest SC-GHG estimates, all else equal.
The discounting module discounts the stream of future net climate damages to its present
value in the year when the additional unit of emissions was released. Given the long-time
horizon over which the damages are expected to occur, the discount rate has a large influence on
the present value of future damages. Consistent with the findings of National Academies
2017,1519 the economic literature, OMB Circular A-4's guidance for regulatory analysis, and
IWG recommendations to date1520'1521'1522'1523'1524' the EPA continues to conclude that the
consumption rate of interest is the theoretically appropriate discount rate to discount the future
benefits of reducing GHG emissions and that discount rate uncertainty should be accounted for
in selecting future discount rates in this intergenerational context. OMB's Circular A-4 points out
that "the analytically preferred method of handling temporal differences between benefits and
costs is to adjust all the benefits and costs to reflect their value in equivalent units of
consumption and to discount them at the rate consumers and savers would normally use in
discounting future consumption benefits" (OMB 2003). The damage module described above
calculates future net damages in terms of reduced consumption (or monetary consumption
equivalents), and so an application of this guidance is to use the consumption discount rate to
calculate the SC-GHG. Thus, EPA concludes that the use of the social rate of return on capital (7
percent under current OMB Circular A-4 guidance), which does not reflect the consumption rate,
to discount damages estimated in terms of reduced consumption would inappropriately
underestimate the impacts of climate change for the purposes of estimating the SC-GHG.1525
1518 gpA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1519 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1520 IWG 2010. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis under
Executive Order 12866. Accessed 2023. https://www.epa.gov/sites/default/files/2016-
12/documents/scc_tsd_2010 .pdf.
1521 IWG 2013. Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact
Analysis Under Executive Order 12866. https://www.ourenergypolicy.org/wp-
content/uploads/2013/06/social_cost_of_carbon_for_ria_2013_update.pdf.
1522 IWG. 2016a. Addendum to Technical Support Document on Social Cost of Carbon for Regulatory Impact
Analysis under Executive Order 12866: Application of the Methodology to Estimate the Social Cost of Methane and
the Social Cost of Nitrous Oxide, https://www.epa.gov/sites/default/files/2016-12/documents/addendum_to_sc-
ghg_tsd_august_2016.pdf.
1523 IWG 2016b. Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory
Impact Analysis Under Executive Order 12866. Accessed 2023. https://www.epa.gov/sites/default/files/2016-
12/documents/sc_CO2_tsd_august_2016 .pdf.
1524 IWG. 2021. Social Cost of Carbon, Methane, and Nitrous Oxide: Interim Estimates under Executive Order
13990. Technical Support Government, Interagency Working Group on Social Cost of Carbon, United States
Government.
1525 See also the discussion of the inappropriateness of discounting consumption-equivalent measures of benefits and
costs using a rate of return on capital in Circular A-4 (2023) (OMB 2003).
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For the SC-GHG estimates used in this RIA, EPA relies on a dynamic discounting approach
that more fully captures the role of uncertainty in the discount rate in a manner consistent with
the other modules. Based on a review of the literature and data on consumption discount rates,
the public comments received on individual EPA rulemakings, and the February 2021 TSD1526,
and the National Academies1527 recommendations for updating the discounting module, the SC-
GHG estimates rely on discount rates that reflect more recent data on the consumption interest
rate and uncertainty in future rates. Specifically, rather than using a constant discount rate, the
evolution of the discount rate over time is defined following the latest empirical evidence on
interest rate uncertainty and using a framework originally developed by Ramsey1528 that connects
economic growth and interest rates. The Ramsey approach explicitly reflects (1) preferences for
utility in one period relative to utility in a later period and (2) the value of additional
consumption as income changes. The dynamic discount rates used to develop the SC-GHG
estimates applied in this RIA have been calibrated following the Newell, Pizer and Prest
(2022)1529 approach, as applied in (Rennert, Errickson, et al. 2022)1530 (Rennert, Prest, et al.
2022a)1531. This approach uses the discounting formula1532 in which the parameters are calibrated
such that (1) the decline in the certainty-equivalent discount rate matches the latest empirical
evidence on interest rate uncertainty estimated by (Bauer and Rudebusch 2020)1533 (Bauer and
Rudebusch 2023)1534 and (2) the average of the certainty-equivalent discount rate over the first
decade matches a near-term consumption rate of interest. Uncertainty in the starting rate is
addressed by using three near-term target rates (1.5, 2.0, and 2.5 percent) based on multiple lines
of evidence on observed market interest rates.
The resulting dynamic discount rate provides a notable improvement over the constant
discount rate framework used for SC-GHG estimation in previous EPA RIAs. Specifically, it
provides internal consistency within the modeling and a more complete accounting of
uncertainty consistent with economic theory (Arrow, et al. 20 1 3)1535 (Cropper, et al. 2014)1536
1526 IWG. 2021. Social Cost of Carbon, Methane, and Nitrous Oxide: Interim Estimates under Executive Order
13990. Technical Support Government, Interagency Working Group on Social Cost of Carbon, United States
Government.
1527 Similarly, OMB's Circular A-4 (2023) points out that "The analytically preferred method of handling temporal
differences between benefits and costs is to adjust all the benefits and costs to reflect their value in equivalent units
of consumption before discounting them" (OMB 2003).
1528 Ramsey, FP. 1928. "A mathematical theory of saving." The Economic Journal 38(152): 543-559.
1529 Newell, RG, WA Pizer, and BC Prest. 2022. "A discounting rule for the social cost of carbon." Journal of the
Association of Environmental and Resource Economists 9(5): 1017-1046.
1530 Rennert, K, F Errickson, BC Prest, L Rennels, R Newell, W Pizer, C Kingdon, J Wingenroth, and R Cooke.
2022. "Comprehensive evidence implies a higher social cost of C02." Nature 610(7933): 687-692.
1531 Rennert, K., Prest, B.C., Pizer, W.A., Newell, R.G., Anthoff, D., Kingdon, C., Rennels, L., Cooke, R., Raftery,
A.E., Sevcikova, H. and Errickson, F. 2021. "The social cost of carbon: Advances in long-term probablisitic
projections of poulation, GDP, emissions, and discount rates." Brookings Papers on Economic Activity 223-305.
1532 Ramsey, FP. 1928. "A mathematical theory of saving." The Economic Journal 38(152): 543-559.
1533 Bauer, MD, and GD Rudebusch. 2020. "Interest rates under falling stars." American Economic Review 110(5):
1316-54.
1534 Bauer, MD, and GD Rudebusch. 2023. "The rising cost of climate change: evidence from the bond market." The
Review of Economics and Statistics 105(5): 1255-1270.
1535 Arrow, K, M Cropper, C Gollier, B Groom, G Heal, R Newell, W Nordhaus, R Pindyck, W Pizer, and P
Portney. 2013. "Determining benefits and costs for future generations." Science 341(6144) : 349-350.
1536 Cropper, ML, MC Freeman, B Groom, and WA Pizer. 2014. "Declining discount rates." American Economic
Review 104(5): 538-43.
669
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and the National Academies1537 recommendation to employ a more structural, Ramsey-like
approach to discounting that explicitly recognizes the relationship between economic growth and
discounting uncertainty. This approach is also consistent with the National Academies1538
recommendation to use three sets of Ramsey parameters that reflect a range of near-term
certainty-equivalent discount rates and are consistent with theory and empirical evidence on
consumption rate uncertainty. Finally, the value of aversion to risk associated with net damages
from GHG emissions is explicitly incorporated into the modeling framework following the
economic literature. See EPA 2023f for a more detailed discussion of the entire discounting
module and methodology used to value risk aversion in the SC-GHG estimates.1539
Taken together, the methodologies adopted in this SC-GHG estimation process allow for a
more holistic treatment of uncertainty than past estimates used by the EPA. The updates
incorporate a quantitative consideration of uncertainty into all modules and use a Monte Carlo
approach that captures the compounding uncertainties across modules. The estimation process
generates nine separate distributions of discounted marginal damages per metric ton - the
product of using three damage modules and three near-term target discount rates - for each gas
in each emissions year. These distributions have long right tails reflecting the extensive evidence
in the scientific and economic literature that shows the potential for lower-probability but higher-
impact outcomes from climate change, which would be particularly harmful to society. The
uncertainty grows over the modeled time horizon. Therefore, under cases with a lower near-term
target discount rate - that give relatively more weight to impacts in the future - the distribution
of results is wider. To produce a range of estimates that reflects the uncertainty in the estimation
exercise while also providing a manageable number of estimates for policy analysis, the EPA
combines the multiple lines of evidence on damage modules by averaging the results across the
three damage module specifications. The full results generated from the updated methodology
for methane and other greenhouse gases (SC-CO2, SC-CH4, and SC-N20) for emissions years
2020 through 2080 are provided in EPA 2023f. 1540
Table 5-1 summarizes the resulting averaged certainty-equivalent SC-GHG estimates under
each near-term discount rate that are used to estimate the climate benefits of the GHG emission
reductions expected from the final rule. These estimates are reported in 2022 dollars but are
1537 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1538 Nationai Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
1539 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1540 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
670
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otherwise identical to those presented in EPA 2023f.1541 The SC-GHGs increases over time
within the models — i.e., the societal harm from one metric ton emitted in 2030 is higher than
the harm caused by one metric ton emitted in 2027 — because future emissions produce larger
incremental damages as physical and economic systems become more stressed in response to
greater climatic change, and because GDP is growing over time and many damage categories are
modeled as proportional to GDP.
1541 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
671
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Table 5-1 Annual Rounded SC-CO2, SC-CH4, and SC-N2O Values, 2027-2055.
SC-GHG and Near-term Ramsey Discount Rate
SC-CO2 SC-CH4 SC-N2O
(2022 dollars per metric ton (2022 dollars per metric ton (2022 dollars per metric ton of
of CO2)
of CH4)
N2O)
Emission
Near-term rate
Near-term rate
Near-term rate
Year
2.5%
2.0%
1.5%
2.5%
2.0%
1.5%
2.5%
2.0%
1.5%
2027
150
250
410
1900
2400
3200
47000
70000
1 10000
2028
160
250
420
2000
2500
3300
48000
72000
1 10000
2029
160
250
430
2000
2600
3400
49000
73000
110000
2030
160
260
430
2100
2600
3500
50000
74000
120000
203 1
160
260
440
2200
2700
3600
51000
76000
120000
2032
170
270
440
2300
2800
3700
52000
77000
120000
2033
170
270
450
2400
2900
3800
53000
79000
120000
2034
170
270
450
2500
3000
4000
54000
80000
120000
2035
180
280
460
2500
3100
4100
55000
81000
120000
2036
180
280
460
2600
3200
4200
57000
83000
130000
2037
180
290
470
2700
3300
4300
58000
84000
130000
2038
190
290
470
2800
3400
4400
59000
86000
130000
2039
190
290
480
2900
3500
4500
60000
87000
130000
2040
190
300
480
3000
3600
4600
61000
88000
130000
2041
200
300
490
3100
3700
4800
62000
90000
140000
2042
200
310
490
3200
3800
4900
63000
91000
140000
2043
200
310
500
3300
3900
5000
65000
93000
140000
2044
210
320
500
3400
4100
5100
66000
95000
140000
2045
210
320
510
3500
4200
5200
67000
96000
140000
2046
210
330
520
3500
4300
5400
69000
98000
150000
2047
220
330
520
3600
4400
5500
70000
99000
150000
2048
220
340
530
3700
4500
5600
70000
100000
150000
2049
230
340
530
3800
4600
5700
72000
100000
150000
2050
230
340
540
3900
4700
5800
73000
100000
150000
2051
230
350
550
4000
4800
6000
75000
100000
150000
2052
240
350
550
4100
4900
6100
76000
110000
160000
2053
240
360
560
4200
5000
6200
77000
110000
160000
2054
240
360
560
4300
5100
6300
78000
110000
160000
2055
250
360
570
4400
5200
6400
79000
110000
160000
Source: (EPA 2023f)
Note: These SC-GHG values are identical to those reported in the technical report (EPA 2023f) adjusted for
inflation to 2022 dollars using the annual GDP Implicit Price Deflator values in the U.S. Bureau of Economic
Analysis' (BEA) NIPA Table 1.1.9 (Bureau of Economic Analysis (BEA) 2021). The values are stated in
$/metric ton GHG and vary depending on the year of GHG emissions. This table displays the values rounded to
two significant figures. The annual unrounded values used in the calculations in this RIA are available in
Appendix A.5 of (EPA 2023f) and at: www.epa.gov/environmental-economics/scghg.
The methodological updates described above represent a major step forward in bringing SC-
GHG estimation closer to the frontier of climate science and economics and address many of the
National Academies near-term recommendations.1542 Nevertheless, the resulting SC-GHG
estimates presented in Table 9-1, still have several limitations, as would be expected for any
1542 National Academies 2017. "Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide." Washington, D.C.: National Academies of Sciences, Engineering, and Medicine, The National Academies
Press, https://doi.org/10.17226/24651.
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modeling exercise that covers such a broad scope of scientific and economic issues across a
complex global landscape. There are still many categories of climate impacts and associated
damages that are only partially or not reflected yet in these estimates and sources of uncertainty
that have not been fully characterized due to data and modeling limitations. For example, the
modeling omits most of the consequences of changes in precipitation, damages from extreme
weather events, the potential for nongradual damages from passing critical thresholds (e.g.,
tipping elements) in natural or socioeconomic systems, and non-climate mediated effects of
GHG emissions. More specifically for methane, the SC-CH4 estimates do not account for the
direct health and welfare impacts associated with tropospheric ozone produced by methane. As
discussed further in (EPA 2023f)1543, recent studies have found the global ozone-related
respiratory mortality benefits of CH4 emissions reductions, which are not included in the SC-CH4
values presented in Table 7-1, to be, in 2022 dollars, approximately $2,700 per metric ton of
methane emissions in 2030 (McDuffie, et al. 2023).1544 In addition, the SC-CH4 estimates do not
reflect that methane emissions lead to a reduction in atmospheric oxidants, like hydroxyl
radicals, nor do they account for impacts associated with CO2 produced from methane oxidizing
in the atmosphere. Importantly, the updated SC-GHG methodology does not yet reflect
interactions and feedback effects within, and across, Earth and human systems. For example, it
does not explicitly reflect potential interactions among damage categories, such as those
stemming from the interdependencies of energy, water, and land use. These, and other,
interactions and feedbacks were highlighted by the National Academies as an important area of
future research for longer-term enhancements in the SC-GHG estimation framework.
5.3 Reserved
5.4 Health Effects Associated with Exposure to Non-GHG Pollutants
Heavy-duty vehicles emit non-GHG pollutants that contribute to ambient concentrations of
ozone, PM, NO2, SO2, CO, and air toxics. As described in RIA Chapter 4, the increased use of
zero-emission technology in the heavy-duty sector would reduce emissions of non-GHG
pollutants from heavy-duty vehicles. A discussion of the health effects associated with exposure
to these pollutants is presented in this section of the RIA. The following discussion of health
impacts is mainly focused on describing the effects of air pollution on the population in general.
Additionally, because children have increased vulnerability and susceptibility for adverse
health effects related to air pollution exposures, EPA's findings regarding adverse effects for
children related to exposure to pollutants that are impacted by this rule are noted in this section.
The increased vulnerability and susceptibility of children to air pollution exposures may arise
because infants and children generally breathe more relative to their size than adults, and
consequently they may be exposed to relatively higher amounts of air pollution.1545 Children also
1543 EPA 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1544 McDuffie, EE, MC Sarofim, W Raich, M Jackson, H Roman, K Seltzer, BH Henderson, et al. 2023. "The social
cost of ozone-related mortality impacts from methane emissions." Earth's Future 11(9).
doi:https://doi.org/10.1029/2023EF003853.
1545 EPA (2009) Metabolically-derived ventilation rates: A revised approach based upon oxygen consumption rates.
Washington, DC: Office of Research and Development. EPA/600/R-06/129F.
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=202543.
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tend to breathe through their mouths more than adults, and their nasal passages are less effective
at removing pollutants which leads to greater lung deposition of some pollutants such as
PM.1546'1547 Furthermore, air pollutants may pose health risks specific to children because
children's bodies are still developing.1548 For example, during periods of rapid growth such as
fetal development, infancy and puberty, their developing systems and organs may be more easily
harmed. 1549>1550 EPA produces the report titled "America's Children and the Environment,"
which presents national trends on air pollution and other contaminants and environmental health
of children.1551
5.4.1 Ozone
5.4.1.1 Background on Ozone
Ground-level ozone pollution forms in areas with high concentrations of ambient NOx and
VOCs when solar radiation is high. Major U.S. sources of NOx are highway and nonroad motor
vehicles and engines, power plants, and other industrial sources; natural sources, such as soil,
vegetation, and lightning, are smaller sources. Vegetation is the dominant source of VOCs in the
United States. Volatile consumer and commercial products, such as propellants and solvents,
highway and nonroad vehicles, engines, fires, and industrial sources also contribute to the
atmospheric burden of VOCs at ground-level.
The processes underlying ozone formation, transport, and accumulation are complex.
Ground-level ozone is produced and destroyed by an interwoven network of free radical
reactions involving the hydroxyl radical (OH), NO, NO2, and complex reaction intermediates
derived from VOCs. Many of these reactions are sensitive to temperature and available sunlight.
High ozone events most often occur when ambient temperatures and sunlight intensities remain
high for several days under stagnant conditions. Ozone and its precursors can also be transported
hundreds of miles downwind, which can lead to elevated ozone levels in areas with otherwise
low VOC or NOx emissions. As an air mass moves and is exposed to changing ambient
concentrations of NOx and VOCs, the ozone photochemical regime (relative sensitivity of ozone
formation to NOx and VOC emissions) can change.
When ambient VOC concentrations are high, comparatively small amounts of NOx catalyze
rapid ozone formation. Without available NOx, ground-level ozone production is severely
limited, and VOC reductions would have little impact on ozone concentrations. Photochemistry
1546 U.S. EPA Integrated Science Assessment for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019. Chapter 4 "Overall Conclusions" p. 4-1.
1547 Foos, B.; Marty, M.; Schwartz, J.; Bennet, W.; Moya, J.; Jarabek, A.M.; Salmon, A.G. (2008) Focusing on
children's inhalation dosimetry and health effects for risk assessment: An introduction. J Toxicol Environ Health
71A: 149-165.
1548 Children's environmental health includes conception, infancy, early childhood and through adolescence until 21
years of age as described in the EPA Memorandum: Issuance of EPA's 2021 Policy on Children's Health. October
5, 2021. Available at https://www.epa.gov/system/files/documents/2021-10/2021-policy-on-childrens-health.pdf.
1549 EPA (2006) A Framework for Assessing Health Risks of Environmental Exposures to Children. EPA,
Washington, DC, EPA/600/R-05/093F, 2006.
1550 U.S. Environmental Protection Agency. (2005). Supplemental guidance for assessing susceptibility from early-
life exposure to carcinogens. Washington, DC: Risk Assessment Forum. EPA/630/R-03/003F.
https://www3.epa.gov/airtoxics/childrens_supplement_final.pdf.
1551 U.S. EPA. America's Children and the Environment. Available at:
https://www.epa.gov/americaschildrenenvironment
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under these conditions is said to be "NOx-limited." When NOx levels are sufficiently high, faster
NO2 oxidation consumes more radicals, dampening ozone production. Under these "VOC-
limited" conditions (also referred to as "NOx-saturated" conditions), VOC reductions are
effective in reducing ozone, and NOx can react directly with ozone resulting in suppressed ozone
concentrations near NOx emission sources. Under these NOx-saturated conditions, NOx
reductions can increase local ozone under certain circumstances, but overall ozone production
(considering downwind formation) decreases and even in VOC-limited areas, NOx reductions
are not expected to increase ozone levels if the NOx reductions are sufficiently large - large
enough for photochemistry to become NOx-limited.
5.4.1.2 Health Effects Associated with Exposure to Ozone
This section provides a summary of the health effects associated with exposure to ambient
concentrations of ozone.1552 The information in this section is based on the information and
conclusions in the April 2020 Integrated Science Assessment for Ozone (Ozone ISA).1553 The
Ozone ISA concludes that human exposures to ambient concentrations of ozone are associated
with a number of adverse health effects and characterizes the weight of evidence for these health
effects.1554 The discussion below highlights the Ozone ISA's conclusions pertaining to health
effects associated with both short-term and long-term periods of exposure to ozone.
For short-term exposure to ozone, the Ozone ISA concludes that respiratory effects, including
lung function decrements, pulmonary inflammation, exacerbation of asthma, respiratory-related
hospital admissions, and mortality, are causally associated with ozone exposure. It also
concludes that metabolic effects, including metabolic syndrome (i.e., changes in insulin or
glucose levels, cholesterol levels, obesity and blood pressure) and complications due to diabetes
are likely to be causally associated with short-term exposure to ozone, and that evidence is
suggestive of a causal relationship between cardiovascular effects, central nervous system effects
and total mortality and short-term exposure to ozone.
For long-term exposure to ozone, the Ozone ISA concludes that respiratory effects, including
new onset asthma, pulmonary inflammation and injury, are likely to be causally related with
ozone exposure. The Ozone ISA characterizes the evidence as suggestive of a causal relationship
for associations between long-term ozone exposure and cardiovascular effects, metabolic effects,
reproductive and developmental effects, central nervous system effects and total mortality. The
evidence is inadequate to infer a causal relationship between chronic ozone exposure and
increased risk of cancer.
Finally, interindividual variation in human responses to ozone exposure can result in some
groups being at increased risk for detrimental effects in response to exposure. In addition, some
1552 Human exposure to ozone varies over time due to changes in ambient ozone concentration and because people
move between locations which have notable different ozone concentrations. Also, the amount of ozone delivered to
the lung is not only influenced by the ambient concentrations but also by the breathing route and rate.
1553U.S. EPA. Integrated Science Assessment (ISA) for Ozone and Related Photochemical Oxidants (Final Report).
U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-20/012, 2020.
1554 The ISA evaluates evidence and draws conclusions on the causal relationship between relevant pollutant
exposures and health effects, assigning one of five "weight of evidence" determinations: causal relationship, likely
to be a causal relationship, suggestive of a causal relationship, inadequate to infer a causal relationship, and not
likely to be a causal relationship. For more information on these levels of evidence, please refer to Table II in the
Preamble of the ISA.
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groups are at increased risk of exposure due to their activities, such as outdoor workers and
children. The Ozone ISA identified several groups that are at increased risk for ozone-related
health effects. These groups are people with asthma, children and older adults, individuals with
reduced intake of certain nutrients (i.e., Vitamins C and E), outdoor workers, and individuals
having certain genetic variants related to oxidative metabolism or inflammation. Ozone exposure
during childhood can have lasting effects through adulthood. Such effects include altered
function of the respiratory and immune systems. Children absorb higher doses (normalized to
lung surface area) of ambient ozone, compared to adults, due to their increased time spent
outdoors, higher ventilation rates relative to body size, and a tendency to breathe a greater
fraction of air through the mouth.1555 Children also have a higher asthma prevalence compared to
adults. Recent epidemiologic studies provide generally consistent evidence that long-term ozone
exposure is associated with the development of asthma in children. Studies comparing age
groups reported higher magnitude associations for short-term ozone exposure and respiratory
hospital admissions and emergency room visits among children than for adults. Panel studies
also provide support for experimental studies with consistent associations between short-term
ozone exposure and lung function and pulmonary inflammation in healthy children. Additional
children's vulnerability and susceptibility factors are listed above in Chapter 5.4.
5.4.2 Particulate Matter
5.4.2.1 Background on Particulate Matter
Particulate matter (PM) is a complex mixture of solid particles and liquid droplets distributed
among numerous atmospheric gases which interact with solid and liquid phases. Particles in the
atmosphere range in size from less than 0.01 to more than 10 micrometers (|im) in diameter.1556
Atmospheric particles can be grouped into several classes according to their aerodynamic
diameter and physical sizes. Generally, the three broad classes of particles include ultrafine
particles (UFPs, generally considered as particles with a diameter less than or equal to 0.1 |im
[typically based on physical size, thermal diffusivity or electrical mobility]), "fine" particles
(PM2.5; particles with a nominal mean aerodynamic diameter less than or equal to 2.5 |im), and
"thoracic" particles (PM10; particles with a nominal mean aerodynamic diameter less than or
equal to 10 |im). Particles that fall within the size range between PM2.5 and PM10, are referred to
as "thoracic coarse particles" (PM10-2.5, particles with a nominal mean aerodynamic diameter
1555 Children are more susceptible than adults to many air pollutants because of differences in physiology, higher per
body weight breathing rates and consumption, rapid development of the brain and bodily systems, and behaviors
that increase chances for exposure. Even before birth, the developing fetus may be exposed to air pollutants through
the mother that affect development and permanently harm the individual.
Infants and children breathe at much higher rates per body weight than adults, with infants under one year of age
having a breathing rate up to five times that of adults. In addition, children breathe through their mouths more than
adults and their nasal passages are less effective at removing pollutants, which leads to a higher deposition fraction
in their lungs.
1556U.S. EPA. Policy Assessment (PA) for the Review of the National Ambient Air Quality Standards for Particulate
Matter (Final Report, 2020). U.S. Environmental Protection Agency, Washington, DC, EPA/452/R-20/002, 2020.
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greater than 2.5 jam and less than or equal to 10 |im). EPA currently has standards that regulate
PM2.5 and PM10.1557
Most particles are found in the lower troposphere, where they can have residence times
ranging from a few hours to weeks. Particles are removed from the atmosphere by wet
deposition, such as when they are carried by rain or snow, or by dry deposition, when particles
settle out of suspension due to gravity. Atmospheric lifetimes are generally longest for PM2.5,
which often remains in the atmosphere for days to weeks before being removed by wet or dry
deposition.1558 In contrast, atmospheric lifetimes for UFP and PM10-2.5 are shorter. Within hours,
UFP can undergo coagulation and condensation that lead to formation of larger particles in the
accumulation mode or can be removed from the atmosphere by evaporation, deposition, or
reactions with other atmospheric components. PM10-2.5 are also generally removed from the
atmosphere within hours, through wet or dry deposition.1559
Particulate matter consists of both primary and secondary particles. Primary particles are
emitted directly from sources, such as combustion-related activities (e.g., industrial activities,
motor vehicle operation, biomass burning), while secondary particles are formed through
atmospheric chemical reactions of gaseous precursors (e.g., sulfur oxides (SOx), nitrogen oxides
(NOx) and volatile organic compounds (VOCs)).
5.4.2.2 Health Effects Associated with Exposure to Particulate Matter
Scientific evidence spanning animal toxicological, controlled human exposure, and
epidemiologic studies shows that exposure to ambient PM is associated with a broad range of
health effects. These health effects are discussed in detail in the Integrated Science Assessment
for Particulate Matter, which was finalized in December 2019 (2019 PM ISA), with a more
targeted evaluation of studies published since the literature cutoff date of the 2019 PM ISA in the
Supplement to the Integrated Science Assessment for PM (Supplement). 1560>1561 The PM ISA
characterizes the causal nature of relationships between PM exposure and broad health categories
(e.g., cardiovascular effects, respiratory effects, etc.) using a weight-of-evidence approach.1562
1557 Regulatory definitions of PM size fractions, and information on reference and equivalent methods for measuring
PM in ambient air, are provided in 40 CFR Parts 50, 53, and 58. With regard to national ambient air quality
standards (NAAQS) which provide protection against health and welfare effects, the 24-hour PM10 standard
provides protection against effects associated with short-term exposure to thoracic coarse particles (i.e., PM10-2.5).
1558U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019. Table 2-1.
1559U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019. Table 2-1.
1560U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1561 U.S. EPA. Supplement to the 2019 Integrated Science Assessment for Particulate Matter (Final Report, 2022).
U.S. Environmental Protection Agency, Washington, DC, EPA/635/R-22/028, 2022.
1562 The causal framework draws upon the assessment and integration of evidence from across scientific disciplines,
spanning atmospheric chemistry, exposure, dosimetry and health effects studies (i.e., epidemiologic, controlled
human exposure, and animal toxicological studies), and assess the related uncertainties and limitations that
ultimately influence our understanding of the evidence. This framework employs a five-level hierarchy that
classifies the overall weight-of-evidence with respect to the causal nature of relationships between criteria pollutant
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Within this characterization, the PM ISA summarizes the health effects evidence for short-term
(i.e., hours up to one month) and long-term (i.e., one month to years) exposures to PM2.5, PM10-
2.5, and ultrafine particles and concludes that exposures to ambient PM2.5 are associated with a
number of adverse health effects. The discussion below highlights the PM ISA's conclusions and
summarizes additional information from the Supplement where appropriate, pertaining to the
health effects evidence for both short- and long-term PM exposures. Further discussion of PM-
related health effects can also be found in the 2022 Policy Assessment for the review of the PM
NAAQS.1563
EPA has concluded that recent evidence in combination with evidence evaluated in the 2009
PM ISA supports a "causal relationship" between both long- and short-term exposures to PM2.5
and premature mortality and cardiovascular effects and a "likely to be causal relationship"
between long- and short-term PM2.5 exposures and respiratory effects.1564 Additionally, recent
experimental and epidemiologic studies provide evidence supporting a "likely to be causal
relationship" between long-term PM2.5 exposure and nervous system effects and between long-
term PM2.5 exposure and cancer. Because of remaining uncertainties and limitations in the
evidence base, EPA determined the evidence is "suggestive of, but not sufficient to infer, a
causal relationship" for long-term PM2.5 exposure and reproductive and developmental effects
(i.e., male/female reproduction and fertility; pregnancy and birth outcomes), long- and short-term
exposures and metabolic effects, and short-term exposure and nervous system effects.
As discussed extensively in the 2019 PM ISA and the Supplement, recent studies continue to
support a "causal relationship" between short- and long-term PM2.5 exposures and
mortality.1565'1566 For short-term PM2.5 exposure, multi-city studies,, in combination with single-
and multi-city studies evaluated in the 2009 PM ISA, provide evidence of consistent, positive
associations across studies conducted in different geographic locations, populations with
different demographic characteristics, and studies using different exposure assignment
techniques. Additionally, the consistent and coherent evidence across scientific disciplines for
cardiovascular morbidity, including exacerbations of chronic obstructive pulmonary disease
(COPD) and asthma, provide biological plausibility for cause-specific mortality and ultimately
total mortality. Recent epidemiologic studies evaluated in the Supplement, including studies that
employed alternative methods for confounder control, provide additional support to the evidence
base that contributed to the 2019 PM ISA conclusion for short-term PM2.5 exposure and
mortality.
exposures and health and welfare effects using the following categorizations: causal relationship; likely to be causal
relationship; suggestive of, but not sufficient to infer, a causal relationship; inadequate to infer the presence or
absence of a causal relationship; and not likely to be a causal relationship (U.S. EPA. (2019). Integrated Science
Assessment for Particulate Matter (Final Report). U.S. Environmental Protection Agency, Washington, DC,
EPA/600/R-19/188, Section P. 3.2.3).
1563 U.S. EPA. Policy Assessment (PA) for the Reconsideration of the National Ambient Air Quality Standards for
Particulate Matter (Final Report, 2022). U.S. Environmental Protection Agency, Washington, DC, EPA/452/R-22-
004, 2022
1564U.S. EPA. (2009). Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-08/139F.
1565 U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S.
Environmental Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1566 U.S. EPA. Supplement to the 2019 Integrated Science Assessment for Particulate Matter (Final Report, 2022).
U.S. Environmental Protection Agency, Washington, DC, EPA/635/R-22/028, 2022.
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The 2019 PM ISA concluded a "causal relationship" between long-term PM2.5 exposure and
mortality. In addition to reanalyses and extensions of the American Cancer Society (ACS) and
Harvard Six Cities (HSC) cohorts, multiple new cohort studies conducted in the U.S. and
Canada, consisting of people employed in a specific job (e.g., teacher, nurse) and that apply
different exposure assignment techniques, provide evidence of positive associations between
long-term PM2.5 exposure and mortality. Biological plausibility for mortality due to long-term
PM2.5 exposure is provided by the coherence of effects across scientific disciplines for
cardiovascular morbidity, particularly for coronary heart disease, stroke and atherosclerosis, and
for respiratory morbidity, particularly for the development of COPD. Additionally, recent studies
provide evidence indicating that as long-term PM2.5 concentrations decrease there is an increase
in life expectancy. Recent cohort studies evaluated in the Supplement, as well as epidemiologic
studies that conducted accountability analyses or employed alternative methods for confounder
controls, support and extend the evidence base that contributed to the 2019 PM ISA conclusion
for long-term PM2.5 exposure and mortality.
A large body of studies examining both short- and long-term PM2.5 exposure and
cardiovascular effects builds on the evidence base evaluated in the 2009 PM ISA. The strongest
evidence for cardiovascular effects in response to short-term PM2.5 exposures is for ischemic
heart disease and heart failure. The evidence for short-term PM2.5 exposure and cardiovascular
effects is coherent across scientific disciplines and supports a continuum of effects ranging from
subtle changes in indicators of cardiovascular health to serious clinical events, such as increased
emergency department visits and hospital admissions due to cardiovascular disease and
cardiovascular mortality. For long-term PM2.5 exposure, there is strong and consistent
epidemiologic evidence of a relationship with cardiovascular mortality. This evidence is
supported by epidemiologic and animal toxicological studies demonstrating a range of
cardiovascular effects including coronary heart disease, stroke, impaired heart function, and
subclinical markers (e.g., coronary artery calcification, atherosclerotic plaque progression),
which collectively provide coherence and biological plausibility. Recent epidemiologic studies
evaluated in the Supplement, as well as studies that conducted accountability analyses or
employed alternative methods for confounder control, support and extend the evidence base that
contributed to the 2019 PM ISA conclusion for both short- and long-term PM2.5 exposure and
cardiovascular effects.
Studies evaluated in the 2019 PM ISA continue to provide evidence of a "likely to be causal
relationship" between both short- and long-term PM2.5 exposure and respiratory effects.
Epidemiologic studies provide consistent evidence of a relationship between short-term PM2.5
exposure and asthma exacerbation in children and COPD exacerbation in adults as indicated by
increases in emergency department visits and hospital admissions, which is supported by animal
toxicological studies indicating worsening allergic airways disease and subclinical effects related
to COPD. Epidemiologic studies also provide evidence of a relationship between short-term
PM2.5 exposure and respiratory mortality. However, there is inconsistent evidence for respiratory
effects, specifically lung function declines and pulmonary inflammation, in controlled human
exposure studies. With respect to long term PM2.5 exposure, epidemiologic studies conducted in
the U.S. and abroad provide evidence of a relationship with respiratory effects, including
consistent changes in lung function and lung function growth rate, increased asthma incidence,
asthma prevalence, and wheeze in children; acceleration of lung function decline in adults; and
respiratory mortality. The epidemiologic evidence is supported by animal toxicological studies,
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which provide coherence and biological plausibility for a range of effects including impaired
lung development, decrements in lung function growth, and asthma development.
Since the 2009 PM ISA, a growing body of scientific evidence examined the relationship
between long-term PM2.5 exposure and nervous system effects, resulting for the first time in a
causality determination for this health effects category of a "likely to be causal relationship." The
strongest evidence for effects on the nervous system comes from epidemiologic studies that
consistently report cognitive decrements and reductions in brain volume in adults. The effects
observed in epidemiologic studies in adults are supported by animal toxicological studies
demonstrating effects on the brain of adult animals including inflammation, morphologic
changes, and neurodegeneration of specific regions of the brain. There is more limited evidence
for neurodevelopmental effects in children with some studies reporting positive associations with
autism spectrum disorder and others providing limited evidence of an association with cognitive
function. While there is some evidence from animal toxicological studies indicating effects on
the brain (i.e., inflammatory and morphological changes) to support a biologically plausible
pathway for neurodevelopmental effects, epidemiologic studies are limited due to their lack of
control for potential confounding by co-pollutants, the small number of studies conducted, and
uncertainty regarding critical exposure windows.
Building off the decades of research demonstrating mutagenicity, DNA damage, and other
endpoints related to genotoxicity due to whole PM exposures, recent experimental and
epidemiologic studies focusing specifically on PM2.5 provide evidence of a relationship between
long-term PM2.5 exposure and cancer. Epidemiologic studies examining long-term PM2.5
exposure and lung cancer incidence and mortality provide evidence of generally positive
associations in cohort studies spanning different populations, locations, and exposure assignment
techniques. Additionally, there is evidence of positive associations with lung cancer incidence
and mortality in analyses limited to never smokers. The epidemiologic evidence is supported by
both experimental and epidemiologic evidence of genotoxicity, epigenetic effects, carcinogenic
potential, and thatPM2.5 exhibits several characteristics of carcinogens, which collectively
provides biological plausibility for cancer development and resulted in the conclusion of a
"likely to be causal relationship."
For the additional health effects categories evaluated for PM2.5 in the 2019 PM ISA,
experimental and epidemiologic studies provide limited and/or inconsistent evidence of a
relationship with PM2.5 exposure. As a result, the 2019 PM ISA concluded that the evidence is
"suggestive of, but not sufficient to infer a causal relationship" for short-term PM2.5 exposure
and metabolic effects and nervous system effects and for long-term PM2.5 exposures and
metabolic effects as well as reproductive and developmental effects.
In addition to evaluating the health effects attributed to short- and long-term exposure to
PM2.5, the 2019 PM ISA also conducted an extensive evaluation as to whether specific
components or sources of PM2.5 are more strongly related with specific health effects than PM2.5
mass. An evaluation of those studies resulted in the 2019 PM ISA concluding that "many PM2.5
components and sources are associated with many health effects, and the evidence does not
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indicate that any one source or component is consistently more strongly related to health effects
than PM2.5 mass."1567
For both PM10-2.5 and UFPs, for all health effects categories evaluated, the 2019 PM ISA
concluded that the evidence was "suggestive of, but not sufficient to infer, a causal relationship"
or "inadequate to determine the presence or absence of a causal relationship." For PM10-2.5,
although a Federal Reference Method (FRM) was instituted in 2011 to measure PM10-2.5
concentrations nationally, the causality determinations reflect that the same uncertainty identified
in the 2009 PM ISA with respect to the method used to estimate PM10-2.5 concentrations in
epidemiologic studies persists. Specifically, across epidemiologic studies, different approaches
are used to estimate PM10-2.5 concentrations (e.g., direct measurement of PM10-2.5, difference
between PM10 and PM2.5 concentrations), and it remains unclear how well correlated PM10-2.5
concentrations are both spatially and temporally across the different methods used.
For UFPs, which have often been defined as particles less than 0.1 |im, the uncertainty in the
evidence for the health effect categories evaluated across experimental and epidemiologic studies
reflects the inconsistency in the exposure metric used (i.e., particle number concentration,
surface area concentration, mass concentration) as well as the size fractions examined. In
epidemiologic studies the size fraction examined can vary depending on the monitor used and
exposure metric, with some studies examining number count over the entire particle size range,
while experimental studies that use a particle concentrator often examine particles up to 0.3 |im.
Additionally, due to the lack of a monitoring network, there is limited information on the spatial
and temporal variability of UFPs within the United States, as well as population exposures to
UFPs, which adds uncertainty to epidemiologic study results.
The 2019 PM ISA cites extensive evidence indicating that "both the general population as
well as specific populations and lifestages are at risk for PM2.5-related health effects"1568 For
example, in support of its "causal" and "likely to be causal" determinations, the ISA cites
substantial evidence for (1) PM-related mortality and cardiovascular effects in older adults; (2)
PM-related cardiovascular effects in people with pre-existing cardiovascular disease; (3) PM-
related respiratory effects in people with pre-existing respiratory disease, particularly asthma
exacerbations in children; and (4) PM-related impairments in lung function growth and asthma
development in children. The ISA additionally notes that stratified analyses (i.e., analyses that
directly compare PM-related health effects across groups) provide strong evidence for racial and
ethnic differences in PM2.5 exposures and in the risk of PM2.5-related health effects, specifically
within Hispanic and non-Hispanic Black populations with some evidence of increased risk for
populations of low socioeconomic status. Recent studies evaluated in the Supplement support the
conclusion of the 2019 PM ISA with respect to disparities in both PM2.5 exposure and health risk
by race and ethnicity and provide additional support for disparities for populations of lower
socioeconomic status.1569 Additionally, evidence spanning epidemiologic studies that conducted
stratified analyses, experimental studies focusing on animal models of disease or individuals
with pre-existing disease, dosimetry studies, as well as studies focusing on differential exposure
1567 U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1568U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1569 U.S. EPA. Supplement to the 2019 Integrated Science Assessment for Particulate Matter (Final Report, 2022).
U.S. Environmental Protection Agency, Washington, DC, EPA/635/R-22/028, 2022.
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suggest that populations with pre-existing cardiovascular or respiratory disease, populations that
are overweight or obese, populations that have particular genetic variants, and current/former
smokers could be at increased risk for adverse PIVh.s-related health effects. The 2022 Policy
Assessment for the review of the PM NAAQS also highlights that factors that may contribute to
increased risk of PM2.5-related health effects include lifestage (children and older adults), pre-
existing diseases (cardiovascular disease and respiratory disease), race/ethnicity, and
socioeconomic status.1570
5.4.3 Nitrogen Oxides
5.4.3.1 Background on Nitrogen Oxides
Oxides of nitrogen (NOx) refers to nitric oxide (NO) and nitrogen dioxide (NO2). Most NO2
is formed in the air through the oxidation of nitric oxide (NO) that is emitted when fuel is burned
at a high temperature. NOx is a major contributor to secondary PM2.5 formation, and NOx along
with VOCs are the two major precursors of ozone.
5.4.3.2 Health Effects Associated with Exposure to Nitrogen Oxides
The most recent review of the health effects of oxides of nitrogen completed by EPA can be
found in the 2016 Integrated Science Assessment for Oxides of Nitrogen - Health Criteria
(Oxides of Nitrogen ISA).1571 The primary source of NO2 is motor vehicle emissions, and
ambient NO2 concentrations tend to be highly correlated with other traffic-related pollutants.
Thus, a key issue in characterizing the causality of N02-health effect relationships consists of
evaluating the extent to which studies supported an effect of NO2 that is independent of other
traffic-related pollutants. EPA concluded that the findings for asthma exacerbation integrated
from epidemiologic and controlled human exposure studies provided evidence that is sufficient
to infer a causal relationship between respiratory effects and short-term NO2 exposure. The
strongest evidence supporting an independent effect of NO2 exposure comes from controlled
human exposure studies demonstrating increased airway responsiveness in individuals with
asthma following ambient-relevant NO2 exposures. The coherence of this evidence with
epidemiologic findings for asthma hospital admissions and emergency department visits as well
as lung function decrements and increased pulmonary inflammation in children with asthma
describe a plausible pathway by which NO2 exposure can cause an asthma exacerbation. The
2016 ISA for Oxides of Nitrogen also concluded that there is likely to be a causal relationship
between long-term NO2 exposure and respiratory effects. This conclusion is based on new
epidemiologic evidence for associations of NO2 with asthma development in children combined
with biological plausibility from experimental studies.
In evaluating a broader range of health effects, the 2016 ISA for Oxides of Nitrogen
concluded that evidence is "suggestive of, but not sufficient to infer, a causal relationship"
between short-term NO2 exposure and cardiovascular effects and mortality and between long-
term NO2 exposure and cardiovascular effects and diabetes, birth outcomes, and cancer. In
addition, the scientific evidence is inadequate (insufficient consistency of epidemiologic and
1570 U.S. EPA. Policy Assessment (PA) for the Reconsideration of the National Ambient Air Quality Standards for
Particulate Matter (Final Report, 2022). U.S. Environmental Protection Agency, Washington, DC, EPA-452/R-22-
004, 2022, p. 3-53.
1571 U.S. EPA. Integrated Science Assessment for Oxides of Nitrogen - Health Criteria (2016 Final Report). U.S.
Environmental Protection Agency, Washington, DC, EPA/600/R-15/068, 2016.
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toxicological evidence) to infer a causal relationship for long-term NO2 exposure with fertility,
reproduction, and pregnancy, as well as with postnatal development. A key uncertainty in
understanding the relationship between these non-respiratory health effects and short- or long-
term exposure to NO2 is co-pollutant confounding, particularly by other roadway pollutants. The
available evidence for non-respiratory health effects does not adequately address whether NO2
has an independent effect or whether it primarily represents effects related to other or a mixture
of traffic-related pollutants.
The 2016 ISA for Oxides of Nitrogen concluded that people with asthma, children, and older
adults are at increased risk for N02-related health effects. In these groups and lifestages, NO2 is
consistently related to larger effects on outcomes related to asthma exacerbation, for which there
is confidence in the relationship with NO2 exposure.
5.4.4 Carbon Monoxide
5.4.4.1 Background on Carbon Monoxide
Carbon monoxide (CO) is a colorless, odorless gas formed by incomplete combustion of
carbon-containing fuels and by photochemical reactions in the atmosphere. Nationally,
particularly in urban areas, the majority of CO emissions to ambient air come from mobile
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sources.
5.4.4.2 Health Effects Associated with Carbon Monoxide
Information on the health effects of carbon monoxide (CO) can be found in the January 2010
Integrated Science Assessment for Carbon Monoxide (CO ISA).1573 The CO ISA presents
conclusions regarding the presence of causal relationships between CO exposure and categories
of adverse health effects.1574 This section provides a summary of the health effects associated
with exposure to ambient concentrations of CO, along with the CO ISA conclusions.1575
Controlled human exposure studies of subjects with coronary artery disease show a decrease
in the time to onset of exercise-induced angina (chest pain) and electrocardiogram changes
following CO exposure. In addition, epidemiologic studies presented in the CO ISA observed
associations between short-term CO exposure and cardiovascular morbidity, particularly
increased emergency room visits and hospital admissions for coronary heart disease (including
ischemic heart disease, myocardial infarction, and angina). Some epidemiologic evidence is also
available for increased hospital admissions and emergency room visits for congestive heart
failure and cardiovascular disease as a whole. The CO ISA concludes that a causal relationship is
1572 U.S. EPA, (2010). Integrated Science Assessment for Carbon Monoxide (Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-09/019F, 2010.
1573U.S. EPA, (2010). Integrated Science Assessment for Carbon Monoxide (Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-09/019F, 2010.
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686.
1574 The ISA evaluates the health evidence associated with different health effects, assigning one of five "weight of
evidence" determinations: causal relationship, likely to be a causal relationship, suggestive of a causal relationship,
inadequate to infer a causal relationship, and not likely to be a causal relationship. For definitions of these levels of
evidence, please refer to Section 1.6 of the ISA.
1575 Personal exposure includes contributions from many sources, and in many different environments. Total
personal exposure to CO includes both ambient and non-ambient components; and both components may contribute
to adverse health effects.
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likely to exist between short-term exposures to CO and cardiovascular morbidity. It also
concludes that available data are inadequate to conclude that a causal relationship exists between
long-term exposures to CO and cardiovascular morbidity.
Animal studies show various neurological effects with in-utero CO exposure. Controlled
human exposure studies report central nervous system and behavioral effects following low-level
CO exposures, although the findings have not been consistent across all studies. The CO ISA
concludes that the evidence is suggestive of a causal relationship with both short- and long-term
exposure to CO and central nervous system effects.
A number of studies cited in the CO ISA have evaluated the role of CO exposure in birth
outcomes such as preterm birth or cardiac birth defects. There is limited epidemiologic evidence
of a CO-induced effect on preterm births and birth defects, with weak evidence for a decrease in
birth weight. Animal toxicological studies have found perinatal CO exposure to affect birth
weight, as well as other developmental outcomes. The CO ISA concludes that the evidence is
suggestive of a causal relationship between long-term exposures to CO and developmental
effects and birth outcomes.
Epidemiologic studies provide evidence of associations between short-term CO
concentrations and respiratory morbidity such as changes in pulmonary function, respiratory
symptoms, and hospital admissions. A limited number of epidemiologic studies considered co-
pollutants such as ozone, SO2, and PM in two-pollutant models and found that CO risk estimates
were generally robust, although this limited evidence makes it difficult to disentangle effects
attributed to CO itself from those of the larger complex air pollution mixture. Controlled human
exposure studies have not extensively evaluated the effect of CO on respiratory morbidity.
Animal studies at levels of 50-100 ppm CO show preliminary evidence of altered pulmonary
vascular remodeling and oxidative injury. The CO ISA concludes that the evidence is suggestive
of a causal relationship between short-term CO exposure and respiratory morbidity, and
inadequate to conclude that a causal relationship exists between long-term exposure and
respiratory morbidity.
Finally, the CO ISA concludes that the epidemiologic evidence is suggestive of a causal
relationship between short-term concentrations of CO and mortality. Epidemiologic evidence
suggests an association exists between short-term exposure to CO and mortality, but limited
evidence is available to evaluate cause-specific mortality outcomes associated with CO exposure.
In addition, the attenuation of CO risk estimates which was often observed in co-pollutant
models contributes to the uncertainty as to whether CO is acting alone or as an indicator for other
combustion-related pollutants. The CO ISA also concludes that there is not likely to be a causal
relationship between relevant long-term exposures to CO and mortality.
5.4.5 Sulfur Oxides
5.4.5.1 Background on Sulfur Oxides
Sulfur dioxide (SO2), a member of the sulfur oxide (SOx) family of gases, is formed from
burning fuels containing sulfur (e.g., coal or oil), extracting gasoline from oil, or extracting
metals from ore. SO2 and its gas phase oxidation products can dissolve in water droplets and
further oxidize to form sulfuric acid which reacts with ammonia to form sulfates, which are
important components of ambient PM.
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5.4.5.2 Health Effects Associated with Exposure to Sulfur Oxides
This section provides an overview of the health effects associated with SO2. Additional
information on the health effects of SO2 can be found in the 2017 Integrated Science Assessment
for Sulfur Oxides - Health Criteria (SOx ISA).1576 Following an extensive evaluation of health
evidence from animal toxicological, controlled human exposure, and epidemiologic studies, the
EPA has concluded that there is a causal relationship between respiratory health effects and
short-term exposure to SO2. The immediate effect of SO2 on the respiratory system in humans is
bronchoconstriction. People with asthma are more sensitive to the effects of SO2, likely resulting
from preexisting inflammation associated with this disease. In addition to those with asthma
(both children and adults), there is suggestive evidence that all children and older adults may be
at increased risk of S02-related health effects. In free-breathing laboratory studies involving
controlled human exposures to SO2, respiratory effects have consistently been observed
following 5-10 min exposures at SO2 concentrations > 400 ppb in people with asthma engaged in
moderate to heavy levels of exercise, with respiratory effects occurring at concentrations as low
as 200 ppb in some individuals with asthma. A clear concentration-response relationship has
been demonstrated in these studies following exposures to SO2 at concentrations between 200
and 1000 ppb, both in terms of increasing severity of respiratory symptoms and decrements in
lung function, as well as the percentage of individuals with asthma adversely affected.
Epidemiologic studies have reported positive associations between short-term ambient SO2
concentrations and hospital admissions and emergency department visits for asthma and for all
respiratory causes, particularly among children and older adults (> 65 years). The studies provide
supportive evidence for the causal relationship.
For long-term SO2 exposure and respiratory effects, the EPA has concluded that the evidence
is suggestive of a causal relationship. This conclusion is based on new epidemiologic evidence
for positive associations between long-term SO2 exposure and increases in asthma incidence
among children, together with animal toxicological evidence that provides a pathophysiologic
basis for the development of asthma. However, uncertainty remains regarding the influence of
other pollutants on the observed associations with SO2 because these epidemiologic studies have
not examined the potential for co-pollutant confounding.
Consistent associations between short-term exposure to SO2 and mortality have been observed
in epidemiologic studies, with larger effect estimates reported for respiratory mortality than for
cardiovascular mortality. While this finding is consistent with the demonstrated effects of SO2 on
respiratory morbidity, uncertainty remains with respect to the interpretation of these observed
mortality associations due to potential confounding by various copollutants. Therefore, the EPA
has concluded that the overall evidence is suggestive of a causal relationship between short-term
exposure to SO2 and mortality.
5.4.6 Diesel Exhaust
5.4.6.1 Background on Diesel Exhaust
Diesel exhaust is a complex mixture composed of particulate matter, carbon dioxide, oxygen,
nitrogen, water vapor, carbon monoxide, nitrogen compounds, sulfur compounds and numerous
1576 U.S. EPA. Integrated Science Assessment (ISA) for Sulfur Oxides - Health Criteria (Final Report, Dec 2017).
U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-17/451, 2017.
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low-molecular-weight hydrocarbons. A number of these gaseous hydrocarbon components are
individually known to be toxic, including aldehydes, benzene and 1,3-butadiene. The diesel
particulate matter present in diesel exhaust consists mostly of fine particles (less than 2.5 |im), of
which a significant fraction is ultrafine particles (less than 0.1 |im). These particles have a large
surface area which makes them an excellent medium for adsorbing organics, and their small size
makes them highly respirable. Many of the organic compounds present in the gases and on the
particles, such as poly cyclic organic matter, are individually known to have mutagenic and
carcinogenic properties.
Diesel exhaust varies significantly in chemical composition and particle sizes between
different engine types (heavy-duty, light-duty), engine operating conditions (idle, acceleration,
deceleration), and fuel formulations (high/low sulfur fuel). Also, there are emissions differences
between on-road and nonroad engines because the nonroad engines are generally of older
technology. After being emitted in the engine exhaust, diesel exhaust undergoes dilution as well
as chemical and physical changes in the atmosphere. The lifetimes of the components present in
diesel exhaust range from seconds to months.
5.4.6.2 Health Effects Associated with Exposure to Diesel Exhaust
In EPA's 2002 Diesel Health Assessment Document (Diesel HAD), exposure to diesel
exhaust was classified as likely to be carcinogenic to humans by inhalation from environmental
exposures, in accordance with the revised draft 1996/1999 EPA cancer guidelines.1577'1578 A
number of other agencies (National Institute for Occupational Safety and Health, the
International Agency for Research on Cancer, the World Health Organization, California EPA,
and the U.S. Department of Health and Human Services) made similar hazard classifications
prior to 2002. EPA also concluded in the 2002 Diesel HAD that it was not possible to calculate a
cancer unit risk for diesel exhaust due to limitations in the exposure data for the occupational
groups or the absence of a dose-response relationship.
In the absence of a cancer unit risk, the Diesel HAD sought to provide additional insight into
the significance of the diesel exhaust cancer hazard by estimating possible ranges of risk that
might be present in the population. An exploratory analysis was used to characterize a range of
possible lung cancer risk. The outcome was that environmental risks of cancer from long-term
diesel exhaust exposures could plausibly range from as low as 10"5 to as high as 10"3. Because of
uncertainties, the analysis acknowledged that the risks could be lower than 10"5, and a zero risk
from diesel exhaust exposure could not be ruled out.
Noncancer health effects of acute and chronic exposure to diesel exhaust emissions are also of
concern to EPA. EPA derived a diesel exhaust reference concentration (RfC) from consideration
of four well-conducted chronic rat inhalation studies showing adverse pulmonary effects. The
RfC is 5 |ig/m3 for diesel exhaust measured as diesel particulate matter. This RfC does not
consider allergenic effects such as those associated with asthma or immunologic or the potential
for cardiac effects. There was emerging evidence in 2002, discussed in the Diesel HAD, that
1577 U.S. EPA. (1999). Guidelines for Carcinogen Risk Assessment. Review Draft. NCEA-F-0644, July.
Washington, DC: U.S. EPA. Retrieved on March 19, 2009 from
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=54932.
1578 U.S. EPA (2002). Health Assessment Document for Diesel Engine Exhaust. EPA/600/8-90/057F Office of
research and Development, Washington DC. Retrieved on March 17, 2009 from
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=29060. pp. 1-1 1-2.
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exposure to diesel exhaust can exacerbate these effects, but the exposure-response data were
lacking at that time to derive an RfC based on these then-emerging considerations. The Diesel
HAD states, "With [diesel particulate matter] being a ubiquitous component of ambient PM,
there is an uncertainty about the adequacy of the existing [diesel exhaust] noncancer database to
identify all of the pertinent [diesel exhaust]-caused noncancer health hazards." The Diesel HAD
also notes "that acute exposure to [diesel exhaust] has been associated with irritation of the eye,
nose, and throat, respiratory symptoms (cough and phlegm), and neurophysiological symptoms
such as headache, lightheadedness, nausea, vomiting, and numbness or tingling of the
extremities." The Diesel HAD notes that the cancer and noncancer hazard conclusions applied to
the general use of diesel engines then on the market and as cleaner engines replace a substantial
number of existing ones, the applicability of the conclusions would need to be reevaluated.
It is important to note that the Diesel HAD also briefly summarizes health effects associated
with ambient PM and discusses EPA's then-annual PM2.5 NAAQS of 15 |ig/m3. In 2012, EPA
revised the level of the annual PM2.5 NAAQS to 12 |ig/m3 and in 2024 EPA revised the level of
the annual PM2.5 NAAQS to 9.0 |ig/m3,1579 There is a large and extensive body of human data
showing a wide spectrum of adverse health effects associated with exposure to ambient PM, of
which diesel exhaust is an important component. The PM2.5 NAAQS provides protection from
the health effects attributed to exposure to PM2.5. The contribution of diesel PM to total ambient
PM varies in different regions of the country and also within a region from one area to another.
The contribution can be high in near-roadway environments, for example, or in other locations
where diesel engine use is concentrated.
Since 2002, several new studies have been published which continue to report increased lung
cancer risk associated with occupational exposure to diesel exhaust from older engines. Of
particular note since 2011 are three new epidemiology studies which have examined lung cancer
in occupational populations, including truck drivers, underground nonmetal miners and other
diesel motor-related occupations. These studies reported increased risk of lung cancer related to
exposure to diesel exhaust, with evidence of positive exposure-response relationships to varying
degrees.15X0-15X1 -15x2 These newer studies (along with others that have appeared in the scientific
literature) add to the evidence EPA evaluated in the 2002 Diesel HAD and further reinforce the
concern that diesel exhaust exposure likely poses a lung cancer hazard. The findings from these
newer studies do not necessarily apply to newer technology diesel engines (i.e., heavy-duty
highway engines from 2007 and later model years) since the newer engines have large reductions
in the emission constituents compared to older technology diesel engines.
In light of the growing body of scientific literature evaluating the health effects of exposure to
diesel exhaust, in June 2012 the World Health Organization's International Agency for Research
1579 https://www.epa.gov/pm-pollution/national-ambient-air-quality-standards-naaqs-pm
1580 Garshick, Eric, Francine Laden, Jaime E. Hart, Mary E. Davis, Ellen A. Eisen, and Thomas J. Smith. 2012. Lung
cancer and elemental carbon exposure in trucking industry workers. Environmental Health Perspectives 120(9):
1301-1306.
1581 Silverman, D. T., Samanic, C. M., Lubin, J. H., Blair, A. E., Stewart, P. A., Vermeulen, R., & Attfield, M. D.
(2012). The diesel exhaust in miners study: a nested case-control study of lung cancer and diesel exhaust. Journal of
the National Cancer Institute.
1582 Olsson, Ann C., et al. "Exposure to diesel motor exhaust and lung cancer risk in a pooled analysis from case-
control studies in Europe and Canada." American journal of respiratory and critical care medicine 183.7 (2011):
941-948.
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on Cancer (IARC), a recognized international authority on the carcinogenic potential of
chemicals and other agents, evaluated the full range of cancer-related health effects data for
diesel engine exhaust. IARC concluded that diesel exhaust should be regarded as "carcinogenic
to humans."1583 This designation was an update from its 1988 evaluation that considered the
evidence to be indicative of a "probable human carcinogen."
5.4.7 Air Toxics
Heavy-duty engine emissions contribute to ambient levels of air toxics that are known or
suspected human or animal carcinogens or that have noncancer health effects. These compounds
include, but are not limited to, acetaldehyde, benzene, 1,3-butadiene, formaldehyde, and
naphthalene. These compounds were all identified as national cancer risk drivers or contributors
in the 2019 Air Toxics Screening Assessment (AirToxScreen).1584'1585
The most recent available data indicate that millions of Americans live in areas where air
toxics pose potential health concerns. 1586>1587 The levels of air toxics to which people are exposed
vary depending on where people live and work and the kinds of activities in which they engage,
as discussed in detail in EPA's 2007 Mobile Source Air Toxics Rule.1588 According to EPA's
2017 National Emissions Inventory (NEI), mobile sources were responsible for 39 percent of
outdoor anthropogenic toxic emissions. Further, mobile sources were the largest contributor to
national average risk of cancer and immunological and respiratory health effects from directly
emitted pollutants, according to EPA's Air Toxics Screening Assessment (AirToxScreen) for
2019.1589'1590 Mobile sources are also significant contributors to precursor emissions which react
to form air toxics.1591 Formaldehyde is the largest contributor to cancer risk of all 72 pollutants
quantitatively assessed in the 2019 AirToxScreen. Mobile sources were responsible for 26
percent of primary anthropogenic emissions of this pollutant in the 2017 NEI and are significant
contributors to formaldehyde precursor emissions. Benzene is also a large contributor to cancer
1583 IARC [International Agency for Research on Cancer], (2013). Diesel and gasoline engine exhausts and some
nitroarenes. IARC Monographs Volume 105. [Online at
http://monographs.iarc.fr/ENG/Monographs/voll05/index.php]
1584 U.S. EPA (2022) Technical Support Document EPA's Air Toxics Screening Assessment. 2018 AirToxScreen
TSD. https://www.epa.gov/system/files/documents/2023-02/AirToxScreen_2018%20TSD.pdf.
1585 U.S. EPA (2023) 2019 AirToxScreen Risk Drivers. https://www.epa.gov/AirToxScreen/airtoxscreen-risk-
drivers.
1586 Air toxics are pollutants known to cause or suspected of causing cancer or other serious health effects. Air toxics
are also known as toxic air pollutants or hazardous air pollutants. https://www.epa.gov/AirToxScreen/airtoxscreen-
glossary-terms#air-toxics.
1587 U.S. EPA (2022) Technical Support Document EPA Air Toxics Screening Assessment. 2018 AirToxScreen
TSD. https://www.epa.gov/system/files/documents/2023-02/AirToxScreen_2018%20TSD.pdf.
1588 U.S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final
Rule. 72 FR 8434, February 26, 2007.
1589 U.S. EPA. (2022) 2019 AirToxScreen: Assessment Results. https://www.epa.gov/AirToxScreen/2019-
airtoxscreen-assessment-results.
1590 AirToxScreen also includes estimates of risk attributable to background concentrations, which includes
contributions from long-range transport, persistent air toxics, and natural sources; as well as secondary
concentrations, where toxics are formed via secondary formation. Mobile sources substantially contribute to long-
range transport and secondarily formed air toxics.
1591 Rich Cook, Sharon Phillips, Madeleine Strum, Alison Eyth & James Thurman (2020): Contribution of mobile
sources to secondary formation of carbonyl compounds, Journal of the Air & Waste Management Association, DOI:
10.1080/10962247.2020.1813839.
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risk, and mobile sources account for about 60 percent of average exposure to ambient
concentrations.
5.4.7.1 Acetaldehyde
Acetaldehyde is classified in EPA's IRIS database as a probable human carcinogen, based on
nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous routes.1592
The inhalation unit risk estimate (URE) in IRIS for acetaldehyde is 2.2 x 10"6 per |ig/m3,1593
Acetaldehyde is reasonably anticipated to be a human carcinogen by the NTP in the 14th Report
on Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the
IARC.1594'1595
The primary noncancer effects of exposure to acetaldehyde vapors include irritation of the
eyes, skin, and respiratory tract.1596 In short-term (4 week) rat studies, degeneration of olfactory
epithelium was observed at various concentration levels of acetaldehyde exposure.1597 Data from
these studies were used by EPA to develop an inhalation reference concentration of 9 |ig/m3.
Some asthmatics have been shown to be a sensitive subpopulation to decrements in functional
expiratory volume (FEV1 test) and bronchoconstriction upon acetaldehyde inhalation.1598
Children, especially those with diagnosed asthma, may be more likely to show impaired
pulmonary function and symptoms of asthma than are adults following exposure to
acetaldehyde.1599
5.4.7.2 Benzene
EPA's Integrated Risk Information System (IRIS) database lists benzene as a known human
carcinogen (causing leukemia) by all routes of exposure and concludes that exposure is
associated with additional health effects, including genetic changes in both humans and animals
1592U.S. EPA (1991). Integrated Risk Information System File of Acetaldehyde. Research and Development,
National Center for Environmental Assessment, Washington, DC. This material is available electronically at
https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=290.
1593 U.S. EPA (1991). Integrated Risk Information System File of Acetaldehyde. This material is available
electronically at https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=290.
1594 NTP (National Toxicology Program). 2016. Report on Carcinogens, Fourteenth Edition.; Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public Health Service.
https ://ntp. niehs. nih. gov/go/roc 14.
1595 International Agency for Research on Cancer (IARC). (1999). Re-evaluation of some organic chemicals,
hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to
Humans, Vol 71. Lyon, France.
1596 U.S. EPA (1991). Integrated Risk Information System File of Acetaldehyde. This material is available
electronically at https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=290.
1597 Appleman, L.M., R.A. Woutersen, and V.J. Feron. (1982). Inhalation toxicity of acetaldehyde in rats. I. Acute
and subacute studies. Toxicology. 23: 293-297.
1598 Myou, S.; Fujimura, M.; Nishi K.; Ohka, T.; and Matsuda, T. (1993). Aerosolized acetaldehyde induces
histamine-mediated bronchoconstriction in asthmatics. Am. Rev. Respir.Dis. 148(4 Pt 1): 940-943.
1599 California OEHHA, 2014. TSD for Noncancer RELs: Appendix D. Individual, Acute, 8-Hour, and Chronic
Reference Exposure Level Summaries. December 2008 (updated July 2014).
https://oehha.ca.gov/media/downloads/crnr/appendixdlfinal.pdf
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and increased proliferation of bone marrow cells in mice. 1600>1601>1602 EPA states in its IRIS
database that data indicate a causal relationship between benzene exposure and acute
lymphocytic leukemia and suggest a relationship between benzene exposure and chronic non-
lymphocytic leukemia and chronic lymphocytic leukemia. EPA's IRIS documentation for
benzene also lists a range of 2.2 x 10"6 to 7.8 x 10"6 per |ig/m3 as the unit risk estimate (URE) for
benzene. 1603>1604 The International Agency for Research on Cancer (IARC) has determined that
benzene is a human carcinogen, and the U.S. Department of Health and Human Services
(DHHS) has characterized benzene as a known human carcinogen. 1605>1606
A number of adverse noncancer health effects, including blood disorders such as preleukemia
and aplastic anemia, have also been associated with long-term exposure to benzene.1607'1608 The
most sensitive noncancer effect observed in humans, based on current data, is the depression of
the absolute lymphocyte count in blood.1609,1610 EPA's inhalation reference concentration (RfC)
for benzene is 30 |ig/m3. The RfC is based on suppressed absolute lymphocyte counts seen in
humans under occupational exposure conditions. In addition, studies sponsored by the Health
Effects Institute (HEI) provide evidence that biochemical responses occur at lower levels of
1600U.S. EPA. (2000). Integrated Risk Information System File for Benzene. This material is available
electronically at: https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=276.
1601 International Agency for Research on Cancer. (1982). IARC monographs on the evaluation of carcinogenic risk
of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agency for Research on
Cancer, World Health Organization, Lyon, France 1982.
1602 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. (1992). Synergistic action of the benzene
metabolite hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony-stimulating factor
in vitro, Proc. Natl. Acad. Sci. 89:3691-3695.
1603 A unit risk estimate is defined as the increase in the lifetime risk of an individual who is exposed for a lifetime to
1 |ig/m3 benzene in air.
i604U S. EPA. (2000). Integrated Risk Information System File for Benzene. This material is available
electronically at: https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=276.
1605 International Agency for Research on Cancer (IARC, 2018. Monographs on the evaluation of carcinogenic risks
to humans, volume 120. World Health Organization - Lyon, France. http://publications.iarc.fr/Book-And-Report-
Series/Iarc-Monographs-On-The-Identification-Of-Carcinogenic-Hazards-To-Humans/Benzene-2018.
1606 NTP (National Toxicology Program). 2016. Report on Carcinogens, Fourteenth Edition.; Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public Health Service, https://ntp.niehs.nih.gov/go/rocl4
1607 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82:193-197.
EP A-HQ-0 AR-2011-0135.
1608 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3:541-554.
1609Rothman, N., G.L. Li, M. Dosemeci, W.E. Bechtold, G.E. Marti, Y.Z. Wang, M. Linet, L.Q. Xi, W. Lu, M.T.
Smith, N. Titenko-Holland, L.P. Zhang, W. Blot, S.N. Yin, and R.B. Hayes. (1996). Hematotoxicity among Chinese
workers heavily exposed to benzene. Am. J. Ind. Med. 29: 236-246.
1610 U.S. EPA (2002). Toxicological Review of Benzene (Noncancer Effects). Environmental Protection Agency,
Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental
Assessment, Washington DC. This material is available electronically at
https://cfpub.epa.gov/ncea/iris/iris_documents/documents/toxreviews/0276tr.pdf.
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benzene exposure than previously known.1611'1612'1613'1614 EPA's IRIS program has not yet
evaluated these new data. EPA does not currently have an acute reference concentration for
benzene. The Agency for Toxic Substances and Disease Registry (ATSDR) Minimal Risk Level
(MRL) for acute inhalation exposure to benzene is 29 |ig/m3 for 1-14 days exposure.1615'1616
There is limited information from two studies regarding an increased risk of adverse effects to
children whose parents have been occupationally exposed to benzene. 1617>1618 Data from animal
studies have shown benzene exposures result in damage to the hematopoietic (blood cell
formation) system during development.1619'1620'1621 Also, key changes related to the development
of childhood leukemia occur in the developing fetus.1622 Several studies have reported that
genetic changes related to eventual leukemia development occur before birth. For example, there
is one study of genetic changes in twins who developed T cell leukemia at nine years of age.1623
5.4.7.1 1,3-Butadiene
EPA has characterized 1,3-butadiene as carcinogenic to humans by inhalation.16241625 The
IARC has determined that 1,3-butadiene is a human carcinogen, and the U.S. DHHS has
1611 Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.; Melikian, A.; Eastmond, D.; Rappaport, S.; Li, H.;
Rupa, D.; Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.; Winnik, M.; Kwok, E.; Li, Y.; Mu, R.; Xu, B.;
Zhang, X.; Li, K. (2003). HEI Report 115, Validation & Evaluation of Biomarkers in Workers Exposed to Benzene
in China.
1612 Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et al. (2002). Hematological changes among Chinese
workers with abroad range of benzene exposures. Am. J. Industr. Med. 42: 275-285.
1613 Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al. (2004). Hematotoxically in Workers Exposed to Low Levels
of Benzene. Science 306: 1774-1776.
1614 Turtletaub, K.W. and Mani, C. (2003). Benzene metabolism in rodents at doses relevant to human exposure
from Urban Air. Research Reports Health Effect Inst. Report No. 113.
1615 U. S. Agency for Toxic Substances and Disease Registry (ATSDR). (2007). Toxicological profile for benzene.
Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service.
http://www.atsdr.cdc.gov/ToxProfiles/tp3.pdf.
1616 A minimal risk level (MRL) is defined as an estimate of the daily human exposure to a hazardous substance that
is likely to be without appreciable risk of adverse noncancer health effects over a specified duration of exposure.
1617 Corti, M; Snyder, CA. (1996) Influences of gender, development, pregnancy and ethanol consumption on the
hematotoxicity of inhaled 10 ppm benzene. Arch Toxicol 70:209-217.
i(3i8 McKinney P.A.; Alexander, F.E.; Cartwright, R.A.; et al. (1991) Parental occupations of children with leukemia
in west Cumbria, north Humberside, and Gateshead, Br Med J 302:681-686.
1619 Keller, KA; Snyder, CA. (1986) Mice exposed in utero to low concentrations of benzene exhibit enduring
changes in their colony forming hematopoietic cells. Toxicology 42:171-181.
1620 Keller, KA; Snyder, CA. (1988) Mice exposed in utero to 20 ppm benzene exhibit altered numbers of
recognizable hematopoietic cells up to seven weeks after exposure. Fundam Appl Toxicol 10:224-232.
1621 Corti, M; Snyder, CA. (1996) Influences of gender, development, pregnancy and ethanol consumption on the
hematotoxicity of inhaled 10 ppm benzene. Arch Toxicol 70:209-217.
1622 U.S. EPA. (2002). Toxicological Review of Benzene (Noncancer Effects). National Center for Environmental
Assessment, Washington, DC. Report No. EPA/635/R-02/00IF. http://www.epa.gov/iris/toxreviews/0276-tr.pdf.
1623 Ford, AM; Pombo-de-Oliveira, MS; McCarthy, KP; MacLean, JM; Carrico, KC; Vincent, RF; Greaves, M.
(1997) Monoclonal origin of concordant T-cell malignancy in identical twins. Blood 89:281-285.
1624U.S. EPA. (2002). Health Assessment of 1,3-Butadiene. Office of Research and Development, National Center
for Environmental Assessment, Washington Office, Washington, DC. Report No. EPA600-P-98-001F. This
document is available electronically at https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=54499.
1625U.S. EPA. (2002) "Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0)" Environmental Protection
Agency, Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental
Assessment, Washington, DC https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=139.
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characterized 1,3-butadiene as a known human carcinogen.1626'1627'1628'1629 There are numerous
studies consistently demonstrating that 1,3-butadiene is metabolized into genotoxic metabolites
by experimental animals and humans. The specific mechanisms of 1,3-butadiene-induced
carcinogenesis are unknown; however, the scientific evidence strongly suggests that the
carcinogenic effects are mediated by genotoxic metabolites. Animal data suggest that females
may be more sensitive than males for cancer effects associated with 1,3-butadiene exposure;
there are insufficient data in humans from which to draw conclusions about sensitive
subpopulations. The URE for 1,3-butadiene is 3 x 10"5 per |ig/m3,1630 1,3-butadiene also causes a
variety of reproductive and developmental effects in mice; no human data on these effects are
available. The most sensitive effect was ovarian atrophy observed in a lifetime bioassay of
female mice.1631 Based on this critical effect and the benchmark concentration methodology, an
RfC for chronic health effects was calculated at 0.9 ppb (approximately 2 |ig/m3).
5.4.7.2 Formaldehyde
In 1991, EPA concluded that formaldehyde is a Class B1 probable human carcinogen based
on limited evidence in humans and sufficient evidence in animals.1632 An inhalation URE for
cancer and a reference dose for oral noncancer effects were developed by EPA and posted on the
IRIS database. Since that time, the NTP and IARC have concluded that formaldehyde is a known
human carcinogen.1633'1634'1635
The conclusions by IARC and NTP reflect the results of epidemiologic research published
since 1991 in combination with previous and more recent animal, human and mechanistic
evidence. Research conducted by the National Cancer Institute reported an increased risk of
nasopharyngeal cancer and specific lymphohematopoietic malignancies among workers exposed
1626 International Agency for Research on Cancer (IARC). (1999). Monographs on the evaluation of carcinogenic
risk of chemicals to humans, Volume 71, Re-evaluation of some organic chemicals, hydrazine and hydrogen
peroxide , World Health Organization, Lyon, France.
1627 International Agency for Research on Cancer (IARC). (2008). Monographs on the evaluation of carcinogenic
risk of chemicals to humans, 1,3-Butadiene, Ethylene Oxide and Vinyl Halides (Vinyl Fluoride, Vinyl Chloride and
Vinyl Bromide) Volume 97, World Health Organization, Lyon, France.
1628 NTP (National Toxicology Program). 2016. Report on Carcinogens, Fourteenth Edition.; Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public Health Service.
https://ntp. niehs. nih. gov/go/roc 14.
1629 International Agency for Research on Cancer (IARC). (2012). Monographs on the evaluation of carcinogenic
risk of chemicals to humans, Volume 100F chemical agents and related occupations, World Health Organization,
Lyon, France.
1630 U.S. EPA. (2002). "Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0)" Environmental Protection
Agency, Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental
Assessment, Washington, DC https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=139.
1631 Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996). Subchronic toxicity of 4-vinylcyclohexene in rats and mice by
inhalation. Fundam. Appl. Toxicol. 32:1-10.
1632 EPA. Integrated Risk Information System. Formaldehyde (CASRN 50-00-0)
https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm? substance_nmbr=419.
1633 NTP (National Toxicology Program). 2016. Report on Carcinogens, Fourteenth Edition.; Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public Health Service.
https ://ntp .niehs. nih. gov/go/roc 14.
1634 IARC Monographs on the Evaluation of Carcinogenic Risks to Humans Volume 88 (2006): Formaldehyde, 2-
Butoxyethanol and l-tert-Butoxypropan-2-ol.
1635 IARC Monographs on the Evaluation of Carcinogenic Risks to Humans Volume 100F (2012): Formaldehyde.
692
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to formaldehyde.1636'1637'1638 A National Institute of Occupational Safety and Health study of
garment workers also reported increased risk of death due to leukemia among workers exposed
to formaldehyde.1639 Extended follow-up of a cohort of British chemical workers did not report
evidence of an increase in nasopharyngeal or lymphohematopoietic cancers, but a continuing
statistically significant excess in lung cancers was reported.1640 Finally, a study of embalmers
reported formaldehyde exposures to be associated with an increased risk of myeloid leukemia
but not brain cancer.1641
Health effects of formaldehyde in addition to cancer were reviewed by the Agency for Toxics
Substances and Disease Registry in 1999, supplemented in 2010, and by the World Health
Organization.1642'1643'1644 These organizations reviewed the scientific literature concerning health
effects linked to formaldehyde exposure to evaluate hazards and dose response relationships and
defined exposure concentrations for minimal risk levels (MRLs). The health endpoints reviewed
included sensory irritation of eyes and respiratory tract, reduced pulmonary function, nasal
histopathology, and immune system effects. In addition, research on reproductive and
developmental effects and neurological effects was discussed along with several studies that
suggest that formaldehyde may increase the risk of asthma - particularly in the young.
In June 2010, EPA released a draft Toxicological Review of Formaldehyde - Inhalation
Assessment through the IRIS program for peer review by the National Research Council (NRC)
and public comment.1645 That draft assessment reviewed more recent research from animal and
human studies on cancer and other health effects. The NRC released their review report in April
2oi i 1646 acj(jressecj the NRC (2011) recommendations and applied systematic review
methods to the evaluation of the available noncancer and cancer health effects evidence and
1636 Hauptmann, M.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic
malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615-1623.
1637 Hauptmann, M.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality from solid cancers among
workers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130.
1638Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Hoover, R. N.; Hauptmann, M. 2009.
Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: The National Cancer
Institute cohort. J. National Cancer Inst. 101: 751-761.
1639 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers exposed to formaldehyde: an update.
Occup. Environ. Med. 61: 193-200.
1640 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of British chemical workers
exposed to formaldehyde. J National Cancer Inst. 95:1608-1615.
1641 Hauptmann, M,; Stewart P. A.; Lubin J. H.; Beane Freeman, L. E.; Hornung, R. W.; Herrick, R. F.; Hoover, R.
N.; Fraumeni, J. F.; Hayes, R. B. 2009. Mortality from lymphohematopoietic malignancies and brain cancer among
embalmers exposed to formaldehyde. Journal of the National Cancer Institute 101:1696-1708.
1642 ATSDR. 1999. Toxicological Profile for Formaldehyde, U.S. Department of Health and Human Services (HHS),
July 1999.
1643 ATSDR. 2010. Addendum to the Toxicological Profile for Formaldehyde. U.S. Department of Health and
Human Services (HHS), October 2010.
1644 IPCS. 2002. Concise International Chemical Assessment Document 40. Formaldehyde. World Health
Organization.
1645 EPA (U.S. Environmental Protection Agency). 2010. Toxicological Review of Formaldehyde (CAS No. 50-00-
0) - Inhalation Assessment: In Support of Summary Information on the Integrated Risk Information System (IRIS).
External Review Draft. EPA/635/R-10/002A. U.S. Environmental Protection Agency, Washington DC [online].
Available: http.V/cfpub.epa.gov/ncea/iris_clrafts/recordisplay.cfm?deid=223614.
1646 (National Research Council). 2011. Review of the Environmental Protection Agency's Draft IRIS
Assessment of Formaldehyde. Washington DC: National Academies Press.
http.V/books. nap. edu/openbook.php ?record_id= 13142.
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released a new draft IRIS Toxicological Review of Formaldehyde - Inhalation in April 2022.1647
In this draft, updates to the 1991 IRIS finding include a stronger determination of the
carcinogenicity of formaldehyde inhalation to humans, as well as characterization of its
noncancer effects to propose an overall reference concentration for inhalation exposure. The
National Academies of Sciences, Engineering, and Medicine released their review of EPA's
2022 Draft Formaldehyde Assessment in August 2023, concluding that EPA's "findings on
formaldehyde hazard and quantitative risk are supported by the evidence identified." 1648 EPA is
currently revising the draft IRIS assessment in response to comments received.1649
5.4.7.3 Naphthalene
Naphthalene is found in small quantities in gasoline and diesel fuels. Naphthalene emissions
have been measured in larger quantities in both gasoline and diesel exhaust compared with
evaporative emissions from mobile sources, indicating it is primarily a product of combustion.
Acute (short-term) exposure of humans to naphthalene by inhalation, ingestion, or dermal
contact is associated with hemolytic anemia and damage to the liver and the nervous system.1650
Chronic (long term) exposure of workers and rodents to naphthalene has been reported to cause
cataracts and retinal damage.1651 Children, especially neonates, appear to be more susceptible to
acute naphthalene poisoning based on the number of reports of lethal cases in children and
infants (hypothesized to be due to immature naphthalene detoxification pathways).1652 EPA
released an external review draft of a reassessment of the inhalation carcinogenicity of
naphthalene based on a number of recent animal carcinogenicity studies.1653 The draft
reassessment completed external peer review.1654 Based on external peer review comments
received, EPA is developing a revised draft assessment that considers inhalation and oral routes
of exposure, as well as cancer and noncancer effects.1655 The external review draft does not
1647 U.S. EPA. 2022. IRIS Toxicological Review of Formaldehyde-Inhalation (External Review Draft, 2022). U.S.
Environmental Protection Agency, Washington, DC, EPA/635/R-22/039.
1648 National Academies of Sciences, Engineering, and Medicine. 2023. Review of EPA's 2022 Draft Formaldehyde
Assessment. Washington, DC: The National Academies Press, https://doi.org/10.17226/27153
1649 For more information, see https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=248150#.
1650U. S. EPA. 1998. Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk),
Environmental Protection Agency, Integrated Risk Information System, Research and Development, National
Center for Environmental Assessment, Washington, DC. This material is available electronically at
https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=56434.
1651U. S. EPA. 1998. Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk),
Environmental Protection Agency, Integrated Risk Information System, Research and Development, National
Center for Environmental Assessment, Washington, DC. This material is available electronically at
https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=56434.
1652 U. S. EPA. (1998). Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk),
Environmental Protection Agency, Integrated Risk Information System, Research and Development, National
Center for Environmental Assessment, Washington, DC. This material is available electronically at
https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=56434.
1653 U. S. EPA. (1998). Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk),
Environmental Protection Agency, Integrated Risk Information System, Research and Development, National
Center for Environmental Assessment, Washington, DC. This material is available electronically at
https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=56434.
1654 Oak Ridge Institute for Science and Education. (2004). External Peer Review for the IRIS Reassessment of the
Inhalation Carcinogenicity of Naphthalene. August 2004.
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=84403.
1655 U.S. EPA. (2021) See: https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=340791.
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represent official agency opinion and was released solely for the purposes of external peer
review and public comment. The NTP listed naphthalene as "reasonably anticipated to be a
human carcinogen" in 2004 on the basis of bioassays reporting clear evidence of carcinogenicity
in rats and some evidence of carcinogenicity in mice.1656 California EPA has released a new risk
assessment for naphthalene, and the IARC has reevaluated naphthalene and re-classified it as
Group 2B: possibly carcinogenic to humans.1657
Naphthalene also causes a number of non-cancer effects in animals following chronic and
less-than-chronic exposure, including abnormal cell changes and growth in respiratory and nasal
tissues.1658 The current EPA IRIS assessment includes noncancer data on hyperplasia and
metaplasia in nasal tissue that form the basis of the inhalation RfC of 3 |ig/m3.1659 The ATSDR
MRL for acute and intermediate duration oral exposure to naphthalene is 0.6 mg/kg/day based on
maternal toxicity in a developmental toxicology study in rats.1660 ATSDR also derived an ad hoc
reference value of 6 x 10"2 mg/m3 for acute (<24-hour) inhalation exposure to naphthalene in a
Letter Health Consultation dated March 24, 2014 to address a potential exposure concern in
Illinois.1661 The ATSDR acute inhalation reference value was based on a qualitative
identification of an exposure level interpreted not to cause pulmonary lesions in mice. More
recently, EPA developed acute RfCs for 1-, 8-, and 24-hour exposure scenarios; the <24-hour
reference value is 2 x 10"2 mg/m3.1662 EPA's acute RfCs are based on a systematic review of the
literature, benchmark dose modeling of naphthalene-induced nasal lesions in rats, and
application of a PBPK (physiologically based pharmacokinetic) model.
5.4.8 Exposure and Health Effects Associated with Traffic
Locations near major roadways generally have elevated concentrations of many air pollutants
emitted from motor vehicles. Hundreds of studies have been published in peer-reviewed journals,
concluding that concentrations of CO, CO2, NO, NO2, benzene, aldehydes, particulate matter,
black carbon, and many other compounds are elevated in ambient air within approximately 300-
600 meters (about 1,000-2,000 feet) of major roadways. The highest concentrations of most
pollutants emitted directly by motor vehicles are found within 50 meters (about 165 feet) of the
edge of a roadway's traffic lanes.
1656 (National Toxicology Program). 2016. Report on Carcinogens, Fourteenth Edition.; Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public Health Service.
https ://ntp. niehs. nih. gov/go/roc 14.
1657 International Agency for Research on Cancer (IARC). (2002). Monographs on the Evaluation of the
Carcinogenic Risk of Chemicals for Humans. Vol. 82. Lyon, France.
1658 U. S. EPA. (1998). Toxicological Review of Naphthalene, Environmental Protection Agency, Integrated Risk
Information System, Research and Development, National Center for Environmental Assessment, Washington, DC.
This material is available electronically at https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=56434.
1659U.S. EPA. (1998). Toxicological Review of Naphthalene. Environmental Protection Agency, Integrated Risk
Information System (IRIS), Research and Development, National Center for Environmental Assessment,
Washington, DC https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=56434.
1660 ATSDR. Toxicological Profile for Naphthalene, 1-Methylnaphthalene, and 2-Methylnaphthalene (2005).
https ://www. atsdr. cdc. gov/T oxProfile s/tp67 -p .pdf
1661 ATSDR. Letter Health Consultation, Radiac Abrasives, Inc., Chicago, Illinois (2014).
https://www.atsdr.cdc.gov/HAC/pha/RadiacAbrasives/Radiac%20 Abrasives,%20Inc.%20_%20LHC%20(Final)%20
_%2003 -24-2014%20(2)_508.pdf
1662 U. S. EPA. Derivation of an acute reference concentration for inhalation exposure to naphthalene. Report No.
EPA/600/R-21/292. https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=355035.
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A large-scale review of air quality measurements in the vicinity of major roadways between
1978 and 2008 concluded that the pollutants with the steepest concentration gradients in
vicinities of roadways were CO, ultrafine particles, metals, elemental carbon (EC), NO, NOx,
and several VOCs.1663 These pollutants showed a large reduction in concentrations within 100
meters downwind of the roadway. Pollutants that showed more gradual reductions with distance
from roadways included benzene, NO2, PM2.5, and PM10. In reviewing the literature, Karner et al.
(2010) reported that results varied based on the method of statistical analysis used to determine
the gradient in pollutant concentration. More recent studies of traffic-related air pollutants
continue to report sharp gradients around roadways, particularly within several hundred meters.
I664,i665,i666,i667,i668,i669,i670,i67i js evidence that EPA's regulations for vehicles have
lowered the near-road concentrations and gradients.1672 Starting in 2010, EPA required through
the NAAQS process that air quality monitors be placed near high-traffic roadways for
determining concentrations of CO, NO2, and PM2.5. The monitoring data for NO2 and CO
1663 Karner, A.A.; Eisinger, D.S.; Niemeier, D.A. (2010). Near-roadway air quality: synthesizing the findings from
real-world data. Environ Sci Technol 44: 5334-5344.
1664 McDonald, B.C.; McBride, Z.C.; Martin, E.W.; Harley, R.A. (2014) High-resolution mapping of motor vehicle
carbon dioxide emissions. J. Geophys. Res.Atmos.,119, 5283-5298, doi:10.1002/2013JD021219.
1665 Kimbrough, S.; Baldauf, R.W.; Hagler, G.S.W.; Shores, R.C.; Mitchell, W.; Whitaker, D.A.; Croghan, C.W.;
Vallero, D.A. (2013) Long-term continuous measurement of near-road air pollution in Las Vegas: seasonal
variability in traffic emissions impact on air quality. Air Qual Atmos Health 6: 295-305. DOI 10.1007/sll869-
012-0171-x.
1666 Kimbrough, S.; Palma, T.; Baldauf, R.W. (2014) Analysis of mobile source air toxics (MSATs)—Near-road
VOC and carbonyl concentrations. Journal of the Air &Waste Management Association, 64:3, 349-359, DOI:
10.1080/10962247.2013.863814.
1667 Kimbrough, S.; Owen, R.C.; Snyder, M.; Richmond-Bryant, J. (2017) NO to NO2 Conversion Rate Analysis and
Implications for Dispersion Model Chemistry Methods using Las Vegas, Nevada Near-Road Field Measurements.
Atmos Environ 165: 23-24.
i66s Apte, J.S.; Messier, K.P.; Gani, S.; Brauer, M.; Kirchstetter, T.W.; Lunden, M.M.; Marshall, J.D.; Portier, C.J.;
Vermeulen, R.C.H.; Hamburg, S.P. (2017) High-Resolution Air Pollution Mapping with Google Street View Cars:
Exploiting Big Data. Environ Sci Technol 51: 6999-7008. https://doi.org/10.1021/acs.est.7b00891.
1669 Gu, P.; Li, H.Z.; Ye, Q.; et al. (2018) Intercity variability of particulate matter is driven by carbonaceous sources
and correlated with land-use variables. Environ Sci Technol 52: 52: 11545-11554. [Online at
http://dx. doi. org/10.1021/acs. est. 8b 03833].
1670 Hilker, N.; Wang, J.W.; Jong, C-H.; Healy, R.M.; Sofowote, U.; Debosz, J.; Su, Y.; Noble, M.; Munoz, A.;
Doerkson, G.; White, L.; Audette, C.; Herod, D.; Brook, J.R.; Evans, G.J. (2019) Traffic-related air pollution near
roadways: discerning local impacts from background. Atmos. Meas. Tech., 12, 5247-5261.
https://doi. org/10.5194/amt-l2-5247-2019.
1671 Dabek-Zlotorzynska, E., V. Celo, L. Ding, D. Herod, C-H. Jeong, G. Evans, andN. Hilker. 2019.
"Characteristics and sources of PM2.5 and reactive gases near roadways in two metropolitan areas in Canada."
Atmos Environ 218: 116980.
1672 Sarnat, J.A.; Russell, A.; Liang, D.; Moutinho, J.L; Golan, R.; Weber, R.; Gao, D.; Sarnat, S.; Chang, H.H.;
Greenwald, R.; Yu, T. (2018) Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room
Inhalation to Vehicle Emissions (DRIVE) Study. Health Effects Institute Research Report Number 196. [Online at:
https://www. healtheffects.org/publication/developing-multipollutant-exposure-indicators-traffic-pollution-dorm-
room-inhalation].
696
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indicate that in urban areas, monitors near roadways often report the highest
concentrations.1673-1674
For pollutants with relatively high background concentrations relative to near-road
concentrations, detecting concentration gradients can be difficult. For example, many carbonyls
have high background concentrations because of photochemical breakdown of precursors from
many different organic compounds. However, several studies have measured carbonyls in
multiple weather conditions and found higher concentrations of many carbonyls downwind of
roadways.1675'1676 These findings suggest a substantial roadway source of these carbonyls.
In the past 30 years, many studies have been published with results reporting that populations
who live, work, or go to school near high-traffic roadways experience higher rates of numerous
adverse health effects, compared to populations far away from major roads.1677 In addition,
numerous studies have found adverse health effects associated with spending time in traffic, such
as commuting or walking along high-traffic roadways, including studies among
children 1678>1679>1680>1681
Numerous reviews of this body of health literature have been published. In a 2022 final
report, an expert panel of the Health Effects Institute (HEI) employed a systematic review
focusing on selected health endpoints related to exposure to traffic-related air pollution.1682 The
HEI panel concluded that there was a high level of confidence in evidence between long-term
exposure to traffic-related air pollution and health effects in adults, including all-cause,
1673 Gantt, B; Owen, R.C.; Watkins, N. (2021) Characterizing nitrogen oxides and fine particulate matter near major
highways in the United States using the National Near-road Monitoring Network. Environ Sci Technol 55: 2831-
2838. [Online athttps://doi.org/10.1021/acs.est.0c05851],
1674 Lai, R.M.; Ramaswani, A.; Russell, A.G. (2020) Assessment of the near-road (monitoring) network including
comparison with nearby monitors within U.S. cities. Environ Res Letters 15: 114026. [Online at
https://doi. org/10.1088/1748-9326/ab8156]
1675 Liu, W.; Zhang, J.; Kwon, J.l; et 1. (2006). Concentrations and source characteristics of airborne carbonyl
compounds measured outside urban residences. J Air Waste Manage Assoc 56: 1196-1204.
1676 Cahill, T.M.; Charles, M.J.; Seaman, V.Y. (2010). Development and application of a sensitive method to
determine concentrations of acrolein and other carbonyls in ambient air. Health Effects Institute Research Report
149. Available at https://www.healtheffects.org/system/files/Cahilll49.pdf.
1677 In the widely used PubMed database of health publications, between January 1, 1990 and December 31, 2021,
1,979 publications contained the keywords "traffic, pollution, epidemiology," with approximately half the studies
published after 2015.
1678 Laden, F.; Hart, J.E.; Smith, T.J.; Davis, M.E.; Garshick, E. (2007) Cause-specific mortality in the unionized
U.S. trucking industry. Environmental Health Perspect 115:1192-1196.
\6i9 pC(Crs a.; von Klot, S.; Heier, M.; Trentinaglia, I.; Hormann, A.; Wichmann, H.E.; Lowel, H. (2004) Exposure
to traffic and the onset of myocardial infarction. New England J Med 351: 1721-1730.
1680 Zanobetti, A.; Stone, P.H.; Spelzer, F.E.; Schwartz, J.D.; Coull, B.A.; Suh, H.H.; Nearling, B.D.; Mittleman,
M. A.; Verrier, R.L.; Gold, D.R. (2009) T-wave alternans, air pollution and traffic in high-risk subjects. Am J
Cardiol 104: 665-670.
1681 Adar, S.; Adamkiewicz, G.; Gold, D.R.; Schwartz, J.; Coull, B.A.; Suh, H. (2007) Ambient and
microenvironmental particles and exhaled nitric oxide before and after a group bus trip. Environ Health Perspect
115: 507-512.
1682 HEI Panel on the Health Effects of Long-Term Exposure to Traffic-Related Air Pollution (2022) Systematic
review and meta-analysis of selected health effects of long-term exposure to traffic-related air pollution. Health
Effects Institute Special Report 23. [Online at https://www.healtheffects.org/publication/systematic-review-and-
meta-analysis-selected-health-effects-long-term-exposure-traffic] This more recent review focused on health
outcomes related to birth effects, respiratory effects, cardiometabolic effects, and mortality.
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circulatory, and ischemic heart disease mortality.1683 The panel also found that there is a
moderate-to-high level of confidence in evidence of associations with asthma onset and acute
respiratory infections in children and lung cancer and asthma onset in adults. The panel
concluded that there was a moderate level of evidence of associations with small for gestational
age births, but low-to-moderate confidence for other birth outcomes (term birth weight and
preterm birth). This report follows on an earlier expert review published by HEI in 2010, where
it found strongest evidence for asthma-related traffic impacts. Other literature reviews have been
published with conclusions generally similar to the HEI panels'. 1684>1685>1686>1687 Additionally, in
2014, researchers from the U.S. Centers for Disease Control and Prevention (CDC) published a
systematic review and meta-analysis of studies evaluating the risk of childhood leukemia
associated with traffic exposure and reported positive associations between postnatal proximity
to traffic and leukemia risks, but no such association for prenatal exposures.1688 The U.S.
Department of Health and Human Services' National Toxicology Program published a
monograph including a systematic review of traffic-related air pollution and its impacts on
hypertensive disorders of pregnancy. The National Toxicology Program concluded that exposure
to traffic-related air pollution is "presumed to be a hazard to pregnant women" for developing
hypertensive disorders of pregnancy.1689
For several other health outcomes there are publications to suggest the possibility of an
association with traffic-related air pollution, but insufficient evidence to draw definitive
conclusions. Among these outcomes are neurological and cognitive impacts (e.g., autism and
1683 Boogaard, H.; Patton, A.P.; Atkinson, R.W.; Brook, J.R.; Chang, H.H.; Crouse, D.L.; Fussell, J.C.; Hoek, G.;
Hoffmann, B.; Kappeler, R.; Kutlar Joss, M.; Ondras, M.; Sagiv, S.K.; Samoli, E.; Shaikh, R.; Smargiassi, A.;
Szpiro, A.A.; Van Vliet, E.D.S.; Vienneau, D.; Weuve, J.; Lurmann, F.W.; Forastiere, F. (2022) Long-term exposure
to traffic-related air pollution and selected health outcomes: A systematic review and meta-analysis. Environ
Internatl 164: 107262. [Online at https://doi.Org/10.1016/j.envint.2022.107262]
1684 Boothe, V.L.; Shendell, D.G. (2008). Potential health effects associated with residential proximity to freeways
and primary roads: review of scientific literature, 1999-2006. J Environ Health 70: 33-41.
1685 Salam, M.T.; Islam, T.; Gilliland, F.D. (2008). Recent evidence for adverse effects of residential proximity to
traffic sources on asthma. Curr Opin Pulm Med 14: 3-8.
1686 Sun, X.; Zhang, S.; Ma, X. (2014) No association between traffic density and risk of childhood leukemia: a
meta-analysis. Asia Pac J Cancer Prev 15: 5229-5232.
1687 Raaschou-Nielsen, O.; Reynolds, P. (2006). Air pollution and childhood cancer: a review of the epidemiological
literature. Int J Cancer 118: 2920-9.
1688 Boothe, VL.; Boehmer, T.K.; Wendel, A.M.; Yip, F.Y. (2014) Residential traffic exposure and childhood
leukemia: a systematic review and meta-analysis. Am J Prev Med 46: 413-422.
1689 National Toxicology Program (2019) NTP Monograph on the Systematic Review of Traffic-related Air
Pollution and Hypertensive Disorders of Pregnancy. NTP Monograph 7.
https://ntp.niehs.nih.gov/ntp/ohat/trap/mgraph/trapjinal_508.pdf.
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reduced cognitive function, academic performance, and executive function) and reproductive
outcomes (e.g., preterm birth, low birth weight). 1690>1691>1692>1693>1694>1695
Numerous studies have also investigated potential mechanisms by which traffic-related air
pollution affects health, particularly for cardiopulmonary outcomes. For example, some research
indicates that near-roadway exposures may increase systemic inflammation, affecting organ
systems, including blood vessels and lungs 1696>1697>1698>1699 Additionally, long-term exposures in
near-road environments have been associated with inflammation-associated conditions, such as
atherosclerosis and asthma.1700'1701'1702
As described in Chapter 5.6.3, people who live or attend school near major roadways are
more likely to be people of color and/or have a low SES. Additionally, people with low SES
often live in neighborhoods with multiple stressors and health risk factors, including reduced
health insurance coverage rates, higher smoking and drug use rates, limited access to fresh food,
visible neighborhood violence, and elevated rates of obesity and some diseases such as asthma,
diabetes, and ischemic heart disease. Although questions remain, several studies find stronger
associations between air pollution and health in locations with such chronic neighborhood stress,
1690 Volk, H.E.; Hertz-Picciotto, I.; Delwiche, L.; et al. (2011). Residential proximity to freeways and autism in the
CHARGE study. Environ Health Perspect 119: 873-877.
1691 Franco-Suglia, S.; Gryparis, A.; Wright, R.O.; et al. (2007). Association of black carbon with cognition among
children in a prospective birth cohort study. Am J Epidemiol, doi: 10.1093/aje/kwm308. [Online at
http://dx. doi. org].
1692 Power, M.C.; Weisskopf, M.G.; Alexeef, S.E.; et al. (2011). Traffic-related air pollution and cognitive function
in a cohort of older men. Environ Health Perspect 2011: 682-687.
1693 Wu, J.; Wilhelm, M.; Chung, J.; Ritz, B. (2011). Comparing exposure assessment methods for traffic-related air
pollution in an adverse pregnancy outcome study. Environ Res 111: 685-692.
https://doi.Org/10.1016/j.envres.2011.03.008
1694 Stenson, C.; Wheeler, A.J.; Carver, A.; et al. (2021) The impact of traffic-related air pollution on child and
adolescent academic performance: a systematic review. Environ Intl 155: 106696 [Online at
https://doi. org/10.1016/j. envint. 2021.106696],
1695 Gartland, N.; Aljofi, H.E.; Dienes, K.; et al. (2022) The effects of traffic air pollution in and around schools on
executive function and academic performance in children: a rapid review. Int J Environ Res Public Health 19: 749.
https://doi.org/10.3390/ijerphl9020749
1696 Riediker, M. (2007). Cardiovascular effects of fine particulate matter components in highway patrol officers.
Inhal Toxicol 19: 99-105. doi: 10.1080/08958370701495238
1697 Alexeef, S.E.; Coull, B.A.; Gryparis, A.; et al. (2011). Medium-term exposure to traffic-related air pollution and
markers of inflammation and endothelial function. Environ Health Perspect 119: 481-486.
doi: 10.1289/ehp. 1002560.
1698 Eckel. S.P.; Berhane, K.; Salam, M.T.; et al. (2011). Residential Traffic-related pollution exposure and exhaled
nitric oxide in the Children's Health Study. Environ Health Perspect. doi: 10.1289/ehp. 1103516.
1699 Zhang, J.; McCreanor, J.E.; Cullinan, P.; et al. (2009). Health effects of real-world exposure diesel exhaust in
persons with asthma. Res Rep Health Effects Inst 138. [Online at http://www.healtheffects.org],
1700 Adar, S.D.; Klein, R.; Klein, E.K.; et al. (2010). Air pollution and the microvasculature: a cross-sectional
assessment of in vivo retinal images in the population-based Multi-Ethnic Study of Atherosclerosis. PLoS Med
7(11): E1000372. doi:10.1371/journal.pmed.l000372. Available at http://dx.doi.org.
1701 Kan, H.; Heiss, G.; Rose, K.M.; et al. (2008). Prospective analysis of traffic exposure as a risk factor for incident
coronary heart disease: The Atherosclerosis Risk in Communities (ARIC) study. Environ Health Perspect 116:
1463-1468. doi: 10.1289/ehp. 11290. Available at http://dx.doi.org.
1702 McConnell, R.; Islam, T.; Shankardass, K.; et al. (2010). Childhood incident asthma and traffic-related air
pollution at home and school. Environ Health Perspect 1021-1026.
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suggesting that populations in these areas may be more susceptible to the effects of air pollution.
1703,1704,1705,1706,1707,1708,1709,1710
The risks associated with residence, workplace, or school near major roads are of potentially
high public health significance due to the large population in such locations.
The 2013 U.S. Census Bureau's American Housing Survey (AHS) was the last AHS that
included whether housing units are within 300 feet of an "airport, railroad, or highway with four
or more lanes."1711 The 2013 AHS reports that 17.3 million housing units, or 13 percent of all
housing units in the United States, were in such areas. Assuming that populations and housing
units are in the same locations, this corresponds to a population of more than 41 million U.S.
residents near high-traffic roadways or other transportation sources.1712 According to the Central
Intelligence Agency's World Factbook, based on data collected between 2012-2022, the United
States had 6,586,610 km of roadways, 293,564 km of railways, and 13,513 airports.1713 As such,
highways represent the overwhelming majority of transportation facilities described by this
factor in the AHS.
Scientific literature suggests that some sociodemographic factors may increase susceptibility
to the effects of traffic-associated air pollution. For example, several studies have found stronger
adverse health associations in children experiencing chronic social stress, such as living in
1703 Islam, T.; Urban, R.; Gauderman, W.J.; et al. (2011). Parental stress increases the detrimental effect of traffic
exposure on children's lung function. Am J Respir Crit Care Med.
1704 Clougherty, J.E.; Kubzansky, L.D. (2009) A framework for examining social stress and susceptibility to air
pollution in respiratory health. Environ Health Perspect 117: 1351-1358. Doi:10.1289/ehp.0900612
1705 Clougherty, J.E.; Levy, J.I.; Kubzansky, L.D.; Ryan, P.B.; Franco Suglia, S.; Jacobson Canner, M.; Wright, R.J.
(2007) Synergistic effects of traffic-related air pollution and exposure to violence on urban asthma etiology.
Environ Health Perspect 115: 1140-1146. doi:10.1289/ehp.9863.
1706Finkelstein, M.M.; Jerrett, M.; DeLuca, P.; Finkelstein, N.; Verma, D.K.; Chapman, K.; Sears, M.R. (2003)
Relation between income, air pollution and mortality: a cohort study. Canadian Med Assn J 169: 397-402.
1707 Shankardass, K.; McConnell, R.; Jerrett, M.; Milam, J.; Richardson, J.; Berhane, K. (2009) Parental stress
increases the effect of traffic-related air pollution on childhood asthma incidence. Proc Natl Acad Sci 106: 12406-
12411. doi:10.1073/pnas.0812910106.
1708 Chen, E.; Schrier, H.M.; Strunk, R.C.; et al. (2008). Chronic traffic-related air pollution and stress interact to
predict biologic and clinical outcomes in asthma. Environ Health Perspect 116: 970-5.
1709 Currie, J. and R. Walker (2011) Traffic Congestion and Infant Health: Evidence from E-ZPass. American
Economic Journal: Applied Economics, 3 (1): 65-90. https://doi.Org/10.1257/app.3.l.65
1710 Knittel, C.R.; Miller, D.L.; Sanders N.J. (2016) Caution, Drivers! Children Present: Traffic, Pollution, and Infant
Health. The Review of Economics and Statistics, 98 (2): 350-366. https://doi.org/10.1162/REST_a_00548
1711 The variable was known as "ETRANS" in the questions about the neighborhood.
1712 The analysis of population living near major roads based on the Freight Analysis Framework, version 4,
described just below, is intended to provide comparable estimates as the AHS analyses for the conterminous United
States (i.e., "the lower 48"). As stated below, population estimates for the two methods result in very good
agreement - 41 million people living within 300 feet/100 meters using the AHS 2009 dataset, and 41 million people
living within a 100 meters of a road in the FAF4 network using the data in that analysis.
1713 Central Intelligence Agenda. World Factbook: United States. [Online at https://www.cia.gov/the-world-
factbook/countries/united-states/#transportation]
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violent neighborhoods or in homes with low incomes or high family stress.1714'1715'1716'1717 HEI's
2022 critical review of traffic and health studies mentions additional potential mediators or effect
modifiers of the relationship between traffic-related air pollution and health, including
preexisting morbidities (e.g., obesity, hypertension), the built environment (i.e., green space,
walkability), and socioeconomic characteristics, but notes that additional research is needed to
better understand such interactions.1718
In examining schools near major roadways, we used the Common Core of Data from the U.S.
Department of Education, which includes information on all public elementary and secondary
schools and school districts nationwide.1719 To determine school proximities to major roadways,
we used a geographic information system to map each school and roadways based on the U.S.
Census's TIGER roadway file.1720'1721 We estimated that about 10 million students attend
schools within 200 meters of major roads, about 20 percent of the total number of public school
students in the United States.1722 About 800,000 students attend public schools within 200 meters
of primary roads, or about 2 percent of the total.1723 We found that students of color were
overrepresented at schools within 200 meters of primary roadways, and schools within 200
meters of primary roadways had a disproportionately greater population of students eligible for
free or reduced-price lunches. Black students represent 22 percent of students at schools located
within 200 meters of a primary road, compared to 17 percent of students in all U.S. schools.
Hispanic students represent 30 percent of students at schools located within 200 meters of a
primary road, compared to 22 percent of students in all U.S. schools.1724
EPA also conducted a study to estimate the number of people living near truck freight routes
in the United States, which includes many large highways and other routes where light- and
1714 Islam, T., R. Urban, W.J. Gauderman, and et al. 2011. "Parental stress increases the detrimental effect of traffic
exposure on children's lung function." Am J Respir Crit Care Med.
1715 Clougherty, J.E., J.I. Levy, L.D. Kubzansky, and et al. 2007. "Synergistic effects of traffic-related air pollution
and exposure to violence on urban asthma etiology." Environ Health Perspect 115:1140-1146.
1716 Chen, E., H.M. Schrier, R.C. Strunk, and et al. 2008. "Chronic traffic-related air pollution and stress interact to
predict biologic and clinical outcomes in asthma." Environ Health Perspect 116: 970-975.
1717 Long, D., D. Lewis, and C. Langpap. 2021. "Negative traffic externalities and infant health: the role of income
heterogeneity and residential sorting." Environ and Resource Econ 80: 637-674.
1718 HEI. 2022. HEI Panel on the Health Effects of Long-Term Exposure to Traffic-Related Air Pollution (2022)
Systematic review and meta-analysis of selected health effects of long-term exposure to traffic-related air pollution.
Health Effects Institute Special Report 23. https://www.healtheffects.org/system/files/hei-special-report-23_l.pdf.
1719 http://nces. ed.gov/ccd/.
1720 This information is available at: http://nces.ed.gov/ccd/.
1721 TIGER/Line shapefiles for the year 2010. [Online at https://www.census.gov/geographies/mapping-files/time-
series/geo/tiger-line-file.2010.html]
1722 Here, "major roads" refer to those TIGER classifies as either "Primary" or "Secondary." The Census Bureau
describes primary roads as "generally divided limited-access highways within the Federal interstate system or under
state management." Secondary roads are "main arteries, usually in the U.S. highway, state highway, or county
highway system."
1723 For this analysis we analyzed a 200-meter distance based on the understanding that roadways generally influence
air quality within a few hundred meters from the vicinity of heavily traveled roadways or along corridors with
significant trucking traffic. See U.S. EPA, 2014. Near Roadway Air Pollution and Health: Frequently Asked
Questions. EPA-420-F-14-044.
1724Pedde, M.; Bailey, C. (2011) Identification of Schools within 200 Meters of U.S. Primary and Secondary Roads.
Memorandum to docket EPA-HQ-OAR-2011-0135.
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medium-duty vehicles operate.'1725 Based on a population analysis using the U.S. Department of
Transportation's (USDOT) Freight Analysis Framework 4 (FAF4) and population data from the
2010 decennial census, an estimated 72 million people live within 200 meters of these FAF4
roads, which are used by all types of vehicles.1726' The FAF4 analysis includes the population
living within 200 meters of major roads, while the AHS uses a 100-meter distance; the larger
distance and other methodological differences explain the difference in the two estimates for
populations living near major roads.1727
The EPA's Exposure Factor Handbook also indicates that, on average, Americans spend more
than an hour traveling each day, bringing nearly all residents into a high-exposure
microenvironment for part of the day.1728"1729 While near-roadway studies focus on residents near
roads or others spending considerable time near major roads, the duration of commuting results
in another important contributor to overall exposure to traffic-related air pollution. Studies of
health that address time spent in transit have found evidence of elevated risk of cardiac
impacts.1730'1731'1732 Studies have also found that school bus emissions can increase student
exposures to diesel-related air pollutants, and that programs that reduce school bus emissions
may improve health and reduce school absenteeism.1733'1734'1735'1736
1725 U.S. EPA (2021). Estimation of Population Size and Demographic Characteristics among People Living Near
Truck Routes in the Conterminous United States. Memorandum to docket EPA-HQ-OAR-2019-0055.
1726 FAF4 is a model from the USDOT's Bureau of Transportation Statistics (BTS) and Federal Highway
Administration (FHWA), which provides data associated with freight movement in the U.S. It includes data from
the 2012 Commodity Flow Survey (CFS), the Census Bureau on international trade, as well as data associated with
construction, agriculture, utilities, warehouses, and other industries. FAF4 estimates the modal choices for moving
goods by trucks, trains, boats, and other types of freight modes. It includes traffic assignments, including truck
flows on a network of truck routes. https://ops.Jhwa.dot.gov/freight/freight_analysis/faf/.
1727 The same analysis estimated the population living within 100 meters of a FAF4 truck route is 41 million.
1728 EPA. (2011) Exposure Factors Handbook: 2011 Edition. Chapter 16. Online at
https://www.epa.gov/expobox/about-exposure-factors-handbook.
1729 It is not yet possible to estimate the long-term impact of growth in telework associated with the COVID-19
pandemic on travel behavior. There were notable changes during the pandemic. For example, according to the 2021
American Time Use Survey, a greater fraction of workers did at least part of their work at home (38%) as compared
with the 2019 survey (24%). [Online at https://www.bls.gov/news.release/atus.nrO.htm],
1730 Riediker, M.; Cascio, W.E.; Griggs, T.R.; et al. (2004) Particulate matter exposure in cars is associated with
cardiovascular effects in healthy young men. Am J Respir Crit Care Med 169. [Online at
https://doi. org/10.1164/rccm. 200310-14630C\.
1731 Peters, A.; von Klot, S.; Heier, M.; et al. (2004) Exposure to traffic and the onset of myocardial infarction. New
Engl JMed 1721-1730. [Online athttps://doi.org/10.1056/NEJMoa040203.]
1732 Adar, S.D.; Gold, D.R.; Coull, B.A.; (2007) Focused exposure to airborne traffic particles and heart rate
variability in the elderly. Epidemiology 18: 95-103 [Online at 351:
https://doi. org/10.1097/01.ede. 0000249409.81050.46\.
1733 Sabin, L.; Behrentz, E.; Winer, A.M.; et al. Characterizing the range of children's air pollutant exposure during
school bus commutes. J Expo Anal Environ Epidemiol 15: 377-387. [Online at
https://doi. org/10.1038/sj.jea. 7500414],
1734 Li, C.; N, Q.; Ryan, P.H.; School bus pollution and changes in the air quality at schools: a case study. J Environ
Monitll: 1037-1042. [https://doi.org/10.1039/b819458kl
1735 Austin, W.; Heutel, G.; Kreisman, D. (2019) School bus emissions, student health and academic performance.
Econ Edu Rev 70: 108-12.
1736 Adar, S.D.; D.Souza, J.; Sheppard, L.; et al. (2015) Adopting clean fuels and technologies on school buses.
Pollution and health impacts in children. Am J Respir Crit Care Med 191. [Online at
http://doi.org/! 0.1164/rccm.201410-1924OC],
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5.5 Welfare Effects Associated with Exposure to Non-GHG Pollutants
This section discusses the environmental effects associated with criteria and toxic pollutants
affected by this rule.
5.5.1 Visibility
Visibility can be defined as the degree to which the atmosphere is transparent to visible
light.1737 Visibility impairment is caused by light scattering and absorption by suspended
particles and gases. It is dominated by contributions from suspended particles except under
pristine conditions. Visibility is important because it has direct significance to people's
enjoyment of daily activities in all parts of the country. Individuals value good visibility for the
well-being it provides them directly, where they live and work and in places where they enjoy
recreational opportunities. Visibility is also highly valued in significant natural areas, such as
national parks and wilderness areas, and special emphasis is given to protecting visibility in these
areas. For more information on visibility see the final 2019 PM ISA.1738
EPA is working to address visibility impairment. Reductions in air pollution from
implementation of various programs associated with the Clean Air Act Amendments of 1990
provisions have resulted in substantial improvements in visibility and will continue to do so in
the future. Nationally, because trends in haze are closely associated with trends in particulate
sulfate and nitrate due to the relationship between their concentration and light extinction,
visibility trends have improved as emissions of SO2 and NOx have decreased over time due to air
pollution regulations such as the Acid Rain Program.1739 However, in the western part of the
country, changes in total light extinction were smaller, and the contribution of particulate organic
matter to atmospheric light extinction was increasing due to increasing wildfire emissions.1740
In the Clean Air Act Amendments of 1977, Congress recognized visibility's value to society
by establishing a national goal to protect national parks and wilderness areas from visibility
impairment caused by manmade pollution.1741 In 1999, EPA finalized the regional haze program
to protect the visibility in Mandatory Class I Federal areas.1742 There are 156 national parks,
forests and wilderness areas categorized as Mandatory Class I Federal areas.1743 These areas are
defined in CAA section 162 as those national parks exceeding 6,000 acres, wilderness areas and
memorial parks exceeding 5,000 acres, and all international parks which were in existence on
August 7, 1977.
1737 National Research Council, (1993). Protecting Visibility in National Parks and Wilderness Areas. National
Academy of Sciences Committee on Haze in National Parks and Wilderness Areas. National Academy Press,
Washington, DC. This book can be viewed on the National Academy Press Website at
https://www. nap.edu/catalog/2097/protecting-visibility-in-national-parks-and-wilderness-areas.
1738 U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1739U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1740 Hand, JL;Prenni, AJ; Copeland, S; Schichtel, BA; Malm, WC. (2020). Thirty years of the Clean Air Act
Amendments: Impacts on haze in remote regions of the United States (1990-2018). Atmos Environ 243: 117865.
1741 See Section 169(a) of the Clean Air Act.
1742 64 FR 35714, July 1, 1999.
1743 62 FR 38680-38681, July 18, 1997.
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EPA has also concluded that PM2.5 causes adverse effects on visibility in other areas that are
not targeted by the Regional Haze Rule, such as urban areas, depending on PM2.5 concentrations
and other factors such as dry chemical composition and relative humidity (i.e., an indicator of the
water composition of the particles). The secondary (welfare-based) PM NAAQS provide
protection against visibility effects. In recent PM NAAQS reviews, EPA evaluated a target level
of protection for visibility impairment that is expected to be met through attainment of the
existing secondary PM standards.
5.5.2 Ozone Effects on Ecosystems
The welfare effects of ozone include effects on ecosystems, which can be observed across a
variety of scales, i.e., subcellular, cellular, leaf, whole plant, population and ecosystem. Ozone
effects that begin at small spatial scales, such as the leaf of an individual plant, when they occur
at sufficient magnitudes (or to a sufficient degree), can result in effects being propagated to
higher and higher levels of biological organization. For example, effects at the individual plant
level, such as altered rates of leaf gas exchange, growth and reproduction, can, when widespread,
result in broad changes in ecosystems, such as productivity, carbon storage, water cycling,
nutrient cycling, and community composition.
Ozone can produce both acute and chronic injury in sensitive plant species depending on the
concentration level and the duration of the exposure.1744 In those sensitive species1745, effects
from repeated exposure to ozone throughout the growing season of the plant can tend to
accumulate, so that even relatively low concentrations experienced for a longer duration have the
potential to create chronic stress on vegetation.1746,1747 Ozone damage to sensitive plant species
includes impaired photosynthesis and visible injury to leaves. The impairment of photosynthesis,
the process by which the plant makes carbohydrates (its source of energy and food), can lead to
reduced crop yields, timber production, and plant productivity and growth. Impaired
photosynthesis can also lead to a reduction in root growth and carbohydrate storage below
ground, resulting in other, more subtle plant and ecosystems impacts.1748 These latter impacts
include increased susceptibility of plants to insect attack, disease, harsh weather, interspecies
competition and overall decreased plant vigor. The adverse effects of ozone on areas with
sensitive species could potentially lead to species shifts and loss from the affected
ecosystems,1749 resulting in a loss or reduction in associated ecosystem goods and services.1750
Additionally, visible ozone injury to leaves can result in a loss of aesthetic value in areas of
special scenic significance like national parks and wilderness areas and reduced use of sensitive
ornamentals in landscaping.1751 In addition to ozone effects on vegetation, newer evidence
1744 73 FR 16486 (March 27, 2008).
1745 Only a small percentage of all the plant species growing within the U.S. (over 43,000 species have been
catalogued in the USDA PLANTS database) have been studied with respect to ozone sensitivity.
1746U.S. EPA. Integrated Science Assessment (ISA) for Ozone and Related Photochemical Oxidants (Final Report).
U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-20/012, 2020.
1747 The concentration at which ozone levels overwhelm a plant's ability to detoxify or compensate for oxidant
exposure varies. Thus, whether a plant is classified as sensitive or tolerant depends in part on the exposure levels
being considered.
1748 7 3 FR 16492 (March 27, 2008).
1749 Per footnote above, ozone impacts could be occurring in areas where plant species sensitive to ozone have not
yet been studied or identified.
1750 7 3 FR 16493-16494 (March 27, 2008).
1751 73 FR 16490/16497 (March 27, 2008).
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suggests that ozone affects interactions between plants and insects by altering chemical signals
(e.g., floral scents) that plants use to communicate to other community members, such as
attraction of pollinators.
The most recent Ozone Integrated Science Assessment (ISA) presents more detailed
information on how ozone affects vegetation and ecosystems.1752 The Ozone ISA reports causal
and likely causal relationships between ozone exposure and a number of welfare effects and
characterizes the weight of evidence for different effects associated with ozone.1753 The Ozone
ISA concludes that visible foliar injury effects on vegetation, reduced vegetation growth, reduced
plant reproduction, reduced productivity in terrestrial ecosystems, reduced yield and quality of
agricultural crops, alteration of below-ground biogeochemical cycles, and altered terrestrial
community composition are causally associated with exposure to ozone. It also concludes that
increased tree mortality, altered herbivore growth and reproduction, altered plant-insect
signaling, reduced carbon sequestration in terrestrial ecosystems, and alteration of terrestrial
ecosystem water cycling are likely to be causally associated with exposure to ozone.
5.5.3 Deposition
The most recent Integrated Science Assessment for Oxides of Nitrogen, Oxides of Sulfur, and
Particulate Matter - Ecological Criteria documents the ecological effects of the deposition of
these criteria air pollutants.1754 It is clear from the body of evidence that oxides of nitrogen,
oxides of sulfur, and particulate matter contribute to total nitrogen (N) and sulfur (S) deposition.
In turn, N and S deposition cause either nutrient enrichment or acidification depending on the
sensitivity of the landscape or the biological species in question. Both enrichment and
acidification are characterized by an alteration of the biogeochemistry and the physiology of
organisms, resulting in ecologically harmful declines in biodiversity in terrestrial, freshwater,
wetland, and estuarine ecosystems in the U.S. Decreases in biodiversity mean that some species
become relatively less abundant and may be locally extirpated. In addition to the potential loss
of unique living species, the decline in total biodiversity can be harmful because biodiversity is
an important determinant of the stability of ecosystems and their ability to provide socially
valuable ecosystem services.
Terrestrial, wetland, freshwater, and estuarine ecosystems in the U.S. are affected by nitrogen
enrichment/eutrophication caused by nitrogen deposition. These effects, though improving
recently as emissions and deposition decline, have been consistently documented across the U.S.
for hundreds of species and have likely been occurring for decades. In terrestrial systems
nitrogen loading can lead to loss of nitrogen-sensitive plant and lichen species, decreased
biodiversity of grasslands, meadows and other sensitive habitats, and increased potential for
invasive species and potentially for wildfire. In aquatic systems nitrogen loading can alter
species assemblages and cause eutrophication. The sensitivity of terrestrial and aquatic
1752U.S. EPA. Integrated Science Assessment (ISA) for Ozone and Related Photochemical Oxidants (Final Report).
U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-20/012, 2020.
1753 The Ozone ISA evaluates the evidence associated with different ozone related health and welfare effects,
assigning one of five "weight of evidence" determinations: causal relationship, likely to be a causal relationship,
suggestive of a causal relationship, inadequate to infer a causal relationship, and not likely to be a causal
relationship. For more information on these levels of evidence, please refer to Table II of the ISA.
1754 U.S. EPA. Integrated Science Assessment (ISA) for Oxides of Nitrogen, Oxides of Sulfur and Particulate Matter
Ecological Criteria (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-20/278,
2020.
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ecosystems to acidification from nitrogen and sulfur deposition is predominantly governed by the
intersection of geology and deposition. Prolonged exposure to excess nitrogen and sulfur
deposition in sensitive areas acidifies lakes, rivers, and soils. Increased acidity in surface waters
creates inhospitable conditions for biota and affects the abundance and biodiversity of fishes,
zooplankton and macroinvertebrates and ecosystem function. Over time, acidifying deposition
also removes essential nutrients from forest soils, depleting the capacity of soils to neutralize
future acid loadings and negatively affecting forest sustainability. Major effects in forests include
a decline in sensitive tree species, such as red spruce (Picea rubens) and sugar maple (Acer
saccharum).
Building materials including metals, stones, cements, and paints undergo natural weathering
processes from exposure to environmental elements (e.g., wind, moisture, temperature
fluctuations, sunlight, etc.). Pollution can worsen and accelerate these effects. Deposition of PM
is associated with both physical damage (materials damage effects) and impaired aesthetic
qualities (soiling effects). Wet and dry deposition of PM can physically affect materials, adding
to the effects of natural weathering processes, by potentially promoting or accelerating the
corrosion of metals, by degrading paints and by deteriorating building materials such as stone,
concrete and marble.1755 The effects of PM are exacerbated by the presence of acidic gases and
can be additive or synergistic due to the complex mixture of pollutants in the air and surface
characteristics of the material. Acidic deposition has been shown to have an effect on materials
including zinc/galvanized steel and other metal, carbonate stone (as monuments and building
facings), and surface coatings (paints).1756 The effects on historic buildings and outdoor works of
art are of particular concern because of the uniqueness and irreplaceability of many of these
objects. In addition to aesthetic and functional effects on metals, stone and glass, altered energy
efficiency of photovoltaic panels by PM deposition is also an emerging consideration for impacts
of air pollutants on materials.
5.5.4 Welfare Effects of Air Toxics
Emissions from producing, transporting, and combusting fuel contribute to ambient levels of
pollutants that contribute to adverse effects on vegetation. Volatile organic compounds (VOCs),
some of which are considered air toxics, have long been suspected to play a role in vegetation
damage.1757 In laboratory experiments, a wide range of tolerance to VOCs has been observed.1758
Decreases in harvested seed pod weight have been reported for the more sensitive plants, and
some studies have reported effects on seed germination, flowering, and fruit ripening. Effects of
individual VOCs or their role in conjunction with other stressors (e.g., acidification, drought,
temperature extremes) have not been well studied. In a recent study of a mixture of VOCs
including ethanol and toluene on herbaceous plants, significant effects on seed production, leaf
water content, and photo synthetic efficiency were reported for some plant species.1759
1755 U.S. EPA. Integrated Science Assessment (ISA) for Particulate Matter (Final Report, 2019). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1756 Irving, P.M., e.d. 1991. Acid Deposition: State of Science and Technology, Volume III, Terrestrial, Materials,
Health, and Visibility Effects, The U.S. National Acid Precipitation Assessment Program, QtaEtgr 24, page 24-76.
1757 U.S. EPA. (1991). Effects of organic chemicals in the atmosphere on terrestrial plants. EPA/600/3-91/001.
1758 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. (2003). Effects
of VOCs on herbaceous plants in an open-top chamber experiment. Environ. Pollut. 124:341-343.
1759 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. (2003).
Effects of VOCs on herbaceous plants in an open-top chamber experiment. Environ. Pollut. 124:341-343.
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Research suggests an adverse impact of vehicle exhaust on plants, which has in some cases
been attributed to aromatic compounds and in other cases to nitrogen oxides.1760'1761'1762 The
impacts of VOCs on plant reproduction may have long-term implications for biodiversity and
survival of native species near major roadways. Most of the studies of the impacts of VOCs on
vegetation have focused on short-term exposure, and few studies have focused on long-term
effects of VOCs on vegetation and the potential for metabolites of these compounds to affect
herbivores or insects.
5.6 Environmental Justice
5.6.1 Overview
Communities with environmental justice concerns, which can include a range of communities
and populations, face relatively greater cumulative impacts associated with environmental
exposures of multiple types, as well as impacts from non-chemical stressors. Numerous studies
have found that environmental hazards such as air pollution are more prevalent in areas where
people of color and low-income populations represent a higher fraction of the population
compared with the general population.1763'1764'1765'1766 As described in Chapter 5.4.8, there is
some literature to suggest that different sociodemographic factors may increase susceptibility to
the effects of traffic-associated air pollution. In addition, compared to non-Hispanic Whites,
some other racial groups experience greater levels of health problems during some life stages.
For example, in 2018-2020, about 12 percent of non-Hispanic Black; 9 percent of non-Hispanic
American Indian/Alaska Native; and 7 percent of Hispanic children were estimated to currently
have asthma, compared with 6 percent of non-Hispanic White children.1767 Nationally, on
average, non-Hispanic Black and non-Hispanic American Indian or Alaska Native people also
have lower than average life expectancy based on 2019 data.1768
EPA's 2016 "Technical Guidance for Assessing Environmental Justice in Regulatory
Analysis" provides recommendations on conducting the highest quality analysis feasible of
environmental justice (EJ) issues associated with a given regulatory decision, though it is not
prescriptive, recognizing that data limitations, time and resource constraints, and analytic
1760 Viskari E-L. (2000). Epicuticular wax of Norway spruce needles as indicator of traffic pollutant deposition.
Water, Air, and Soil Pollut. 121:327-337.
1761 Ugrekhelidze D, F Korte, G Kvesitadze. (1997). Uptake and transformation of benzene and toluene by plant
leaves. Ecotox. Environ. Safety 37:24-29.
1762KammerbauerH, H Selinger, RRommelt, A Ziegler-Jons, D Knoppik, B Hock. (1987). Toxic components of
motor vehicle emissions for the spruce Picea abies. Environ. Pollut. 48:235-243.
1763 Rowangould, G.M. (2013) A census of the near-roadway population: public health and environmental justice
considerations. Trans Res D 25: 59-67. http://dx.doi.Org/10.1016/j.trd.2013.08.003.
1764 Marshall, J.D. (2000) Environmental inequality: Air pollution exposures in California's South Coast Air Basin.
Atmos Environ21: 5499- 5503. https://doi.Org/10.1016/j.atmosenv.2008.02.005.
1765 Marshall, J.D. (2008) Environmental inequality: air pollution exposures in California's South Coast Air Basin.
Atmos Environ21: 5499-5503. https://doi.Org/10.1016/j.atmosenv.2008.02.005.
1766 Mohai, P.; Pellow, D.; Roberts Timmons, J. (2009) Environmental justice. Annual Reviews 34: 405-430.
https://doi.org/10.1146/annurev-environ082508-094348.
1767 Current Asthma Prevalence by Race and Ethnicity (2018-2020).
[Online at https://www.cdc.gov/asthma/most_recent_national_asthma_data.htm.]
1768 Arias, E. Xu, J. (2022) United States Life Tables, 2019. National Vital Statistics Report, Volume 70, Number
19. [Online at https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-19.pdf].]
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challenges will vary by media and regulatory context.1769 Where applicable and practicable, the
Agency endeavors to conduct such an EJ analysis. There is evidence that communities with EJ
concerns are disproportionately and adversely impacted by heavy-duty vehicle emissions.1770
In Chapter 5.6.2, we discuss the EJ impacts of this final rule's GHG emission standards from
the anticipated reduction of GHGs. We also discuss in Chapter 5.6.3 the potential additional EJ
impacts from the non-GHG (criteria pollutant and air toxic) emissions changes we estimate
would result from compliance with the CO2 emission standards, including impacts near
roadways and from upstream sources. EPA did not consider potential adverse disproportionate
impacts of vehicle emissions in selecting the CO2 emission standards, but we provide
information about adverse impacts of vehicle emissions for the public's understanding of this
rulemaking, which addresses the need to protect public health consistent with CAA section
202(a)(l)-(2). When assessing the potential for disproportionate and adverse health or
environmental impacts of regulatory actions on populations with potential EJ concerns, EPA
strives to answer the following three broad questions, for purposes of the EJ analysis. (1) Is there
evidence of potential EJ concerns in the baseline (the state of the world absent the regulatory
action)? Assessing the baseline will allow EPA to determine whether pre-existing disparities are
associated with the pollutant(s) under consideration (e.g., if the effects of the pollutant(s) are
more concentrated in some population groups); (2) Is there evidence of potential EJ concerns for
the regulatory option(s) under consideration? Specifically, how are the pollutant(s) and its effects
distributed for the regulatory options under consideration?; and (3) Do the regulatory option(s)
under consideration exacerbate or mitigate EJ concerns relative to the baseline? It is not always
possible to provide quantitative answers to these questions.
EPA received several comments related to the environmental justice impacts of heavy-duty
vehicles in general and the impacts of the proposal specifically. We summarize and respond to
those comments in Section 18 of the Response to Comments document that accompanies this
rulemaking. After consideration of comments, EPA updated our review of the literature, while
maintaining our general approach to the environmental justice analysis. We note that analyses in
this section are based on data that was the most appropriate recent data at the time we undertook
the analyses. We intend to continue analyzing data concerning disproportionate impacts of
pollution in the future, using the latest available data.
5.6.2 GHG Impacts on Environmental Justice and Vulnerable or Overburdened
Populations
In the 2009 Endangerment Finding, the Administrator considered how climate change
threatens the health and welfare of the U.S. population. As part of that consideration, she also
considered risks to people of color and low-income individuals and communities, finding that
certain parts of the U.S. population may be especially vulnerable based on their characteristics or
circumstances. These groups include economically and socially disadvantaged communities;
individuals at vulnerable life stages, such as the elderly, the very young, and pregnant or nursing
women; those already in poor health or with comorbidities; the disabled; those experiencing
1769 "Technical Guidance for Assessing Environmental Justice in Regulatory Analysis." Epa.gov, Environmental
Protection Agency, https://www.epa.gov/sites/production/files/2016-06/documents/ejtg_5_6_16_v5.Lpdf. (June
2016).
1770 Demetillo, M.A.; Harkins, C.; McDonald, B.C.; et al. (2021) Space-based observational constraints onNCh air
pollution inequality from diesel traffic in major US cities. Geophys Res Lett 48, e2021GL094333.
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homelessness, mental illness, or substance abuse; and Indigenous or other populations dependent
on one or limited resources for subsistence due to factors including but not limited to geography,
access, and mobility.
Scientific assessment reports produced over the past decade by the USGCRP,1771 1772 the
IPCC,1773 1774 1775 1776 the National Academies of Science, Engineering, and Medicine,1777 1778
and the EPA1779 add more evidence that the impacts of climate change raise potential EJ
concerns. These reports conclude that less-affluent, traditionally marginalized and predominantly
non-White communities can be especially vulnerable to climate change impacts because they
tend to have limited resources for adaptation, are more dependent on climate-sensitive resources
such as local water and food supplies or have less access to social and information resources.
Some communities of color, specifically populations defined jointly by ethnic/racial
characteristics and geographic location (e.g., African-American, Black, and Hispanic/Latino
1771 USGCRP, 2018: Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment,
Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C.
Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, 1515 pp. doi:10.7930/NCA4.2018.
1772 USGCRP, 2016: The Impacts of Climate Change on Human Health in the United States: A Scientific
Assessment. Crimmins, A., J. Balbus, J.L. Gamble, C.B. Beard, J.E. Bell, D. Dodgen, R.J. Eisen, N. Fann, M.D.
Hawkins, S.C. Herring, L. Jantarasami, D.M. Mills, S. Saha, M.C. Sarofim, J. Trtanj, andL. Ziska, Eds. U.S. Global
Change Research Program, Washington, DC, 312 pp. https://health2016.globalchange.gov/.
1773 Oppenheimer, M., M. Campos, R. Warren, J. Birkmann, G. Luber, B. O'Neill, andK. Takahashi, 2014:
Emergent risks and key vulnerabilities. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A:
Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea,
T.E. Bilir, M. Chatteijee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken,
P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, pp. 1039-1099.
1774 Porter, J.R., L. Xie, A.J. Challinor, K. Cochrane, S.M. Howden, M.M. Iqbal, D.B. Lobell, and M.I. Travasso,
2014: Food security and food production systems. In: Climate Change 2014: Impacts, Adaptation, and
Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D.
Mastrandrea, T.E. Bilir, M. Chatteijee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S.
MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom
and New York, NY, USA, pp. 485-533.
1775 Smith, K.R., A. Woodward, D. Campbell-Lendrum, D.D. Chadee, Y. Honda, Q. Liu, J.M. Olwoch, B. Revich,
and R. Sauerborn, 2014: Human health: impacts, adaptation, and co-benefits. In: Climate Change 2014: Impacts,
Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working GroupII to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J.
Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatteijee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel,
A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge,
United Kingdom and New York, NY, USA, pp. 709-754.
1776 IPCC, 2018: Global Warming of 1.5 °C. An IPCC Special Report on the impacts of global warming of 1.5 °C
above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the
global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-
Delmotte, V., P. Zhai, H.-O. Portner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Pean, R.
Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T.
Waterfield (eds.)]. In Press.
1777 National Research Council. 2011. America's Climate Choices. Washington, DC: The National Academies Press.
https://doi.org/10.17226/12781.
1778 National Academies of Sciences, Engineering, and Medicine. 2017. Communities in Action: Pathways to Health
Equity. Washington, DC: The National Academies Press, https://doi.org/10.17226/24624.
1779 EPA. 2021. Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts. U.S.
Environmental Protection Agency, EPA 430-R-21-003.
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communities; Native Americans, particularly those living on tribal lands and Alaska Natives),
may be uniquely vulnerable to climate change health impacts in the U.S., as discussed below. In
particular, the 2016 scientific assessment on the Impacts of Climate Change on Human
Health1780 found with high confidence that vulnerabilities are place- and time-specific, lifestages
and ages are linked to immediate and future health impacts, and social determinants of health are
linked to greater extent and severity of climate change-related health impacts. The GHG
emission reductions from this final rule would contribute to efforts to reduce the probability of
severe impacts related to climate change.
5.6.2.1 Effects on Specific Communities and Populations
Per the Fourth National Climate Assessment (NCA4), "Climate change affects human health
by altering exposures to heat waves, floods, droughts, and other extreme events; vector-, food-
and waterborne infectious diseases; changes in the quality and safety of air, food, and water; and
stresses to mental health and well-being."1781 Many health conditions such as cardiopulmonary
or respiratory illness and other health impacts are associated with and exacerbated by an increase
in GHGs and climate change outcomes, which is problematic as these diseases occur at higher
rates within vulnerable communities. Importantly, negative public health outcomes include those
that are physical in nature, as well as mental, emotional, social, and economic.
The scientific assessment literature, including the aforementioned reports, demonstrates that
there are myriad ways in which particular communities and populations may be affected at the
individual and community levels. Individuals face differential exposure to criteria pollutants, in
part due to the proximities of highways, trains, factories, and other major sources of pollutant-
emitting sources to less-affluent residential areas. Outdoor workers, such as construction or
utility crews and agricultural laborers, who frequently are comprised of already at-risk groups,
are exposed to poor air quality and extreme temperatures without relief. Furthermore, people in
communities with EJ concerns face greater housing, clean water, and food insecurity and bear
disproportionate and adverse economic impacts and health burdens associated with climate
change effects. They have less or limited access to healthcare and affordable, adequate health or
homeowner insurance.1782 Finally, resiliency and adaptation are more difficult for economically
vulnerable communities; these communities have less liquidity, individually and collectively, to
move or to make the types of infrastructure or policy changes to limit or reduce the hazards they
face. They frequently are less able to self-advocate for resources that would otherwise aid in
building resilience and hazard reduction and mitigation.
The assessment literature cited in EPA's 2009 and 2016 Endangerment and Cause or
Contribute Findings, as well as Impacts of Climate Change on Human Health, also concluded
that certain populations and life stages, including children, are most vulnerable to climate-related
178° (JSGCRP. 2016: The Impacts of Climate Change on Human Health in the United States: A Scientific
Assessment.
1781 Ebi, K.L., J.M. Balbus, G. Luber, A. Bole, A. Crimmins, G. Glass, S. Saha, M.M. Shimamoto, J. Trtanj, and J.L.
White-Newsome, 2018: Human Health. In Impacts, Risks, and Adaptation in the United States: Fourth National
Climate Assessment, Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K.
Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, pp. 539-571.
doi: 10.7930/NCA4.2018.CH14.
1782 USGCRP, 2016: The Impacts of Climate Change on Human Health in the United States: A Scientific
Assessment.
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health effects.1783 The assessment literature produced from 2016 to the present strengthens these
conclusions by providing more detailed findings regarding related vulnerabilities and the
projected impacts youth may experience. These assessments - including the NCA4 and The
Impacts of Climate Change on Human Health in the United States (2016) - describe how
children's unique physiological and developmental factors contribute to making them
particularly vulnerable to climate change. Impacts to children are expected from heat waves, air
pollution, infectious and waterborne illnesses, and mental health effects resulting from extreme
weather events. In addition, children are among those especially susceptible to allergens, as well
as health effects associated with heat waves, storms, and floods. Additional health concerns may
arise in low-income households, especially those with children, if climate change reduces food
availability and increases prices, leading to food insecurity within households. More generally,
these reports note that extreme weather and flooding can cause or exacerbate poor health
outcomes by affecting mental health because of stress; contributing to or worsening existing
conditions, again due to stress or also as a consequence of exposures to water and air pollutants;
or by impacting hospital and emergency services operations.1784 Further, in urban areas in
particular, flooding can have significant economic consequences due to effects on infrastructure,
pollutant exposures, and drowning dangers. The ability to withstand and recover from flooding is
dependent in part on the social vulnerability of the affected population and individuals
experiencing an event.1785 In addition, children are among those especially susceptible to
allergens, as well as health effects associated with heat waves, storms, and floods. Additional
health concerns may arise in low-income households, especially those with children, if climate
change reduces food availability and increases prices, leading to food insecurity within
households.
The Impacts of Climate Change on Human Health1786 also found that some communities of
color, low-income groups, people with limited English proficiency, and certain immigrant groups
(especially those who are undocumented) are subject to many factors that contribute to
vulnerability to the health impacts of climate change. While difficult to isolate from related
socioeconomic factors, race appears to be an important factor in vulnerability to climate-related
stress, with elevated risks for mortality from high temperatures reported for Black or African
American individuals compared to White individuals after controlling for factors such as air
conditioning use. Moreover, people of color are disproportionately more exposed to air pollution
based on where they live, and disproportionately vulnerable due to higher baseline prevalence of
underlying diseases such as asthma. As explained earlier, climate change can exacerbate local air
pollution conditions so this increase in air pollution is expected to have disproportionate and
adverse effects on these communities. Locations with greater health threats include urban areas
1783 74 FR 66496, December 15, 2009; 81 FR 54422, August 15, 2016.
1784 Ebi, K.L., J.M. Balbus, G. Luber, A. Bole, A. Crimmins, G. Glass, S. Saha, M.M. Shimamoto, J. Trtanj, and J.L.
White-Newsome, 2018: Human Health. In Impacts, Risks, and Adaptation in the United States: Fourth National
Climate Assessment, Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K.
Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, pp. 539-571.
doi:10.7930/NCA4.2018.CH14.
1785 National Academies of Sciences, Engineering, and Medicine 2019. Framing the Challenge of Urban Flooding in
the United States. Washington, DC: The National Academies Press, https://doi.org/10.17226/25381.
1786 USGCRP, 2016: The Impacts of Climate Change on Human Health in the United States: A Scientific
Assessment. Crimmins, A., J. Balbus, J.L. Gamble, C.B. Beard, J.E. Bell, D. Dodgen, R.J. Eisen, N. Fann, M.D.
Hawkins, S.C. Herring, L. Jantarasami, D.M. Mills, S. Saha, M.C. Sarofim, J. Trtanj, andL. Ziska, Eds. U.S. Global
Change Research Program, Washington, DC, 312 pp. http://dx.doi.org/10.7930/J0R49NQX.
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(due to, among other factors, the "heat island" effect where built infrastructure and lack of green
spaces increases local temperatures), areas where airborne allergens and other air pollutants
already occur at higher levels, and communities experienced depleted water supplies or
vulnerable energy and transportation infrastructure.
The recent EPA report on climate change and social vulnerability1787 examined four socially
vulnerable groups (individuals who are low income, minority, without high school diplomas,
and/or 65 years and older) and their exposure to several different climate impacts (air quality,
coastal flooding, extreme temperatures, and inland flooding). This report found that Black and
African-American individuals were 40 percent more likely to currently live in areas with the
highest projected increases in mortality rates due to climate-driven changes in extreme
temperatures, and 34 percent more likely to live in areas with the highest projected increases in
childhood asthma diagnoses due to climate-driven changes in particulate air pollution. The report
found that Hispanic and Latino individuals are 43 percent more likely to live in areas with the
highest projected labor hour losses in weather-exposed industries due to climate-driven warming,
and 50 percent more likely to live in coastal areas with the highest projected increases in traffic
delays due to increases in high-tide flooding. The report found that American Indian and Alaska
Native individuals are 48 percent more likely to live in areas where the highest percentage of
land is projected to be inundated due to sea level rise, and 37 percent more likely to live in areas
with high projected labor hour losses. Asian individuals were found to be 23 percent more likely
to live in coastal areas with projected increases in traffic delays from high-tide flooding. Persons
with low income or no high school diploma are about 25 percent more likely to live in areas with
high projected losses of labor hours, and 15 percent more likely to live in areas with the highest
projected increases in asthma due to climate-driven increases in particulate air pollution, and in
areas with high projected inundation due to sea level rise.
In a more recent 2023 report, Climate Change Impacts on Children's Health and Weil-Being
in the U.S., the EPA considered the degree to which children's health and well-being may be
impacted by five climate-related environmental hazards—extreme heat, poor air quality, changes
in seasonality, flooding, and different types of infectious diseases 1788. The report found that
children's academic achievement is projected to be reduced by 4-7 percent per child, as a result
of moderate and higher levels of warming, impacting future income levels. The report also
projects increases in the numbers of annual emergency department visits associated with asthma,
and that the number of new asthma diagnoses increases by 4-11 percent due to climate-driven
increases in air pollution relative to current levels. In addition, more than 1 million children in
coastal regions are projected to be temporarily displaced from their homes annually due to
climate-driven flooding, and infectious disease rates are similarly anticipated to rise, with the
number of new Lyme disease cases in children living in 22 states in the eastern and midwestern
U.S. increasing by approximately 3,000-23,000 per year compared to current levels. Overall, the
report confirmed findings of broader climate science assessments that children are uniquely
vulnerable to climate-related impacts and that in many situations, children in the U.S. who
identify as Black, Indigenous, and People of Color, are limited English-speaking, do not have
1787 epa. 2021. Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts. U.S.
Environmental Protection Agency, EPA 430-R-21-003.
1788 epa. 2023. Climate Change Impacts on Children's Health and Well-Being in the U.S., EPA EPA 430-R-23-001
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health insurance, or live in low-income communities may be disproportionately more exposed to
the most severe adverse impacts of climate change.
Tribes and Indigenous communities face disproportionate and adverse risks from the impacts
of climate change, particularly those communities impacted by degradation of natural and
cultural resources within established reservation boundaries and threats to traditional subsistence
lifestyles. Indigenous communities whose health, economic well-being, and cultural traditions
depend upon the natural environment will likely be affected by the degradation of ecosystem
goods and services associated with climate change. The IPCC indicates that losses of customs
and historical knowledge may cause communities to be less resilient or adaptable.1789 The NCA4
noted that while Tribes and Indigenous Peoples are diverse and will be impacted by the climate
changes universal to all Americans, there are several ways in which climate change uniquely
threatens Tribes and Indigenous Peoples' livelihoods and economies.1790 In addition, as noted in
the following paragraph, there can be institutional barriers (including policy-based limitations
and restrictions) to their management of water, land, and other natural resources that could
impede adaptive measures.
For example, Indigenous agriculture in the Southwest is already being adversely affected by
changing patterns of flooding, drought, dust storms, and rising temperatures leading to increased
soil erosion, irrigation water demand, and decreased crop quality and herd sizes. The
Confederated Tribes of the Umatilla Indian Reservation in the Northwest have identified climate
risks to salmon, elk, deer, roots, and huckleberry habitat. Housing and sanitary water supply
infrastructure are vulnerable to disruption from extreme precipitation events Additionally, NCA4
noted that Tribes and Indigenous Peoples generally experience poor infrastructure, diminished
access to quality healthcare, and greater risk of exposure to pollutants. Consequently, Native
Americans often have disproportionately higher rates of asthma, cardiovascular disease,
Alzheimer's disease, diabetes, and obesity. These health conditions and related effects
(disorientation, heightened exposure to PM2.5, etc.) can all contribute to increased vulnerability
to climate-driven extreme heat and air pollution events, which also may be exacerbated by
stressful situations, such as extreme weather events, wildfires, and other circumstances.
NCA4 and IPCC's Fifth Assessment Report1791 also highlighted several impacts specific to
Alaskan Indigenous Peoples. Coastal erosion and permafrost thaw will lead to more coastal
erosion, rendering winter travel riskier and exacerbating damage to buildings, roads, and other
infrastructure—impacts on archaeological sites, structures, and objects that will lead to a loss of
cultural heritage for Alaska's Indigenous people. In terms of food security, the NCA4 discussed
reductions in suitable ice conditions for hunting, warmer temperatures impairing the use of
traditional ice cellars for food storage, and declining shellfish populations due to warming and
acidification. While the NCA4 also noted that climate change provided more opportunity to hunt
from boats later in the fall season or earlier in the spring, the assessment found that the net
impact was an overall decrease in food security. In addition, the U.S. Pacific Islands and the
1789 Porter, et al.. 2014: Food security and food production systems.
1790 Jantarasami, L.C., R. Novak, R. Delgado, E. Marino, S. McNeeley, C. Narducci, J. Raymond-Yakoubian, L.
Singletary, and K. Powys Whyte, 2018: Tribes and Indigenous Peoples. In Impacts, Risks, and Adaptation in the
United States: Fourth National Climate Assessment, Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling,
K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research Program,
Washington, DC, USA, pp. 572-603. doi:10.7930/NCA4. 2018. CH15.
1791 Porter, et al., 2014: Food security and food production systems.
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Indigenous communities that live there are also uniquely vulnerable to the effects of climate
change due to their remote location and geographic isolation. They rely on the land, ocean, and
natural resources for their livelihoods, but they face challenges in obtaining energy and food
supplies that need to be shipped in at high costs. As a result, they face higher energy costs than
the rest of the nation and depend on imported fossil fuels for electricity generation and diesel.
These challenges exacerbate the climate impacts that the Pacific Islands are experiencing. NCA4
notes that Tribes and Indigenous Peoples of the Pacific are threatened by rising sea levels,
diminishing freshwater availability, and negative effects to ecosystem services that threaten these
individuals' health and well-being.
5.6.3 Non-GHG Impacts
In Chapter 4.6., in addition to GHG emissions impacts, we also discuss potential additional
emission changes of non-GHGs (i.e., criteria and air toxic pollutants) that we project from
compliance with the final GHG emission standards. This Chapter 5.6.3 describes evidence that
communities with EJ concerns are disproportionately and adversely impacted by relevant non-
GHG emissions. We discuss the potential impact of non-GHG emissions for two specific
contexts: near-roadway (5.6.3.1) and upstream sources (5.6.3.2).
5.6.3.1 Near Roadway Analysis
As described in Chapter 5.4.8 of this RIA, concentrations of many air pollutants are elevated
near high-traffic roadways. We recently conducted an analysis of the populations within the
CONUS living in close proximity to truck freight routes as identified in USDOT's FAF4.1792
FAF4 is a model from the USDOT's Bureau of Transportation Statistics and Federal Highway
Administration, which provides data associated with freight movement in the United States.1793
Relative to the rest of the population, people living near FAF4 truck routes are more likely to be
people of color and have lower incomes than the general population. People living near FAF4
truck routes are also more likely to live in metropolitan areas. Even controlling for region of the
country, county characteristics, population density, and household structure, race, ethnicity, and
income are significant determinants of whether someone lives near a FAF4 truck route.
We additionally analyzed other national databases that allowed us to evaluate whether homes
and schools were located near a major road and whether disparities in exposure may be occurring
in these environments. Until 2009, the U.S. Census Bureau's American Housing Survey (AHS)
included descriptive statistics of over 70,000 housing units across the nation and asked about
transportation infrastructure near respondents' homes every two years.1794'1795 We also analyzed
1792U.S. EPA (2021). Estimation of Population Size and Demographic Characteristics among People Living Near
Truck Routes in the Conterminous United States. Memorandum to the Docket.
1793FAF4 includes data from the 2012 Commodity Flow Survey (CFS), the Census Bureau on international trade, as
well as data associated with construction, agriculture, utilities, warehouses, and other industries. FAF4 estimates the
modal choices for moving goods by trucks, trains, boats, and other types of freight modes. It includes traffic
assignments, including truck flows on a network of truck routes.
https://ops.Jhwa.dot.gov/freight/freight_analysis/faf/.
1794 U.S. Department of Housing and Urban Development, & U.S. Census Bureau, (n.d.). Age of other residential
buildings within 300 feet. In American Housing Survey for the United States: 2009 (pp. A-l). Retrieved from
https://www.census.gOv/programs-surveys/ahs/data/2009/ahs-2009-summary-tables0/hl50-09.html.
1795 The 2013 AHS again included the "etrans" question about highways, airports, and railroads within half a block
of the housing unit but has not maintained the question since then.
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the U.S. Department of Education's Common Core of Data, which includes enrollment and
location information for schools across the United States.1796
In analyzing the 2009 AHS, we focused on whether a housing unit was located within 300
feet of a "4-or-more lane highway, railroad, or airport" (this distance was used in the AHS
analysis).1797 We analyzed whether there were differences between households in such locations
compared with those in locations farther from these transportation facilities.1798 We included
other variables, such as land use category, region of country, and housing type. We found that
homes with a non-White householder were 22-34 percent more likely to be located within 300
feet of these large transportation facilities than homes with White householders. Homes with a
Hispanic householder were 17-33 percent more likely to be located within 300 feet of these large
transportation facilities than homes with non-Hispanic householders. Households near large
transportation facilities were, on average, lower in income and educational attainment and more
likely to be a rental property and located in an urban area compared with households more
distant from transportation facilities.
In examining schools near major roadways, we used the Common Core of Data from the U.S.
Department of Education, which includes information on all public elementary and secondary
schools and school districts nationwide.1799 To determine school proximities to major roadways,
we used a geographic information system to map each school and roadways based on the U.S.
Census's TIGER roadway file.1800 We estimated that about 10 million students attend schools
within 200 meters of major roads, about 20 percent of the total number of public school students
in the United States.1801 About 800,000 students attend public schools within 200 meters of
primary roads, or about 2 percent of the total. We found that students of color were
overrepresented at schools within 200 meters of primary roadways, and schools within 200
meters of primary roadways had a disproportionate population of students eligible for free or
reduced-price lunches.1802 Black students represent 22 percent of students at schools located
within 200 meters of a primary road, compared to 17 percent of students in all U.S. schools.
Hispanic students represent 30 percent of students at schools located within 200 meters of a
primary road, compared to 22 percent of students in all U.S. schools.
We also reviewed existing scholarly literature examining the potential for disproportionate
exposure to these pollutants among people of color and people with low socioeconomic status
1796 http://nces.ed.gov/ccd/.
1797 This variable primarily represents roadway proximity. According to the Central Intelligence Agency's World
Factbook, in 2010, the United States had 6,506,204 km of roadways, 224,792 km of railways, and 15,079 airports.
Highways thus represent the overwhelming majority of transportation facilities described by this factor in the AHS.
1798 Bailey, C. (2011) Demographic and Social Patterns in Housing Units Near Large Highways and other
Transportation Sources. Memorandum to docket.
1799 http://nces. ed.gov/ccd/.
i8°°pedde, M.; Bailey, C. (2011) Identification of Schools within 200 Meters of U.S. Primary and Secondary Roads.
Memorandum to the docket.
1801 Here, "major roads" refer to those TIGER classifies as either "Primary" or "Secondary." The Census Bureau
describes primary roads as "generally divided limited-access highways within the Federal interstate system or under
state management." Secondary roads are "main arteries, usually in the U.S. highway, state highway, or county
highway system."
i 802 For this analysis we analyzed a 200-meter distance based on the understanding that roadways generally influence
air quality within a few hundred meters from the vicinity of heavily traveled roadways or along corridors with
significant trucking traffic. See U.S. EPA, 2014. Near Roadway Air Pollution and Health: Frequently Asked
Questions. EPA-420-F-14-044.
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(SES). Numerous studies evaluating the demographics and socioeconomic status of populations
or schools near roadways have found that they include a greater percentage of residents of color,
as well as lower SES populations (as indicated by variables such as median household income).
Locations in these studies include Los Angeles, CA; Seattle, WA; Wayne County, MI; Orange
County, FL; Tampa, FL; the State of California; the State of Texas; and
nationally.1803'1804'1805'1806'1807'1808'1809'1810'1811'1812'1813'1814 Such disparities may be due to multiple
1803 Marshall, J.D. (2008) Environmental inequality: air pollution exposures in California's South Coast Air Basin.
Atmos Environ42: 5499-5503. doi:10.1016/j.atmosenv.2008.02.00
1804 Su, J.G.; Larson, T.; Gould, T.; Cohen, M.; Buzzelli, M. (2010) Transboundary air pollution and environmental
justice: Vancouver and Seattle compared. GeoJournal 57: 595-608. doi:10.1007/sl0708-009-9269-6
1805 Chakraborty, J.; Zandbergen, P.A. (2007) Children at risk: measuring racial/ethnic disparities in potential
exposure to air pollution at school and home. J Epidemiol Community Health 61: 1074-1079.
doi:10.1136/jech.2006.054130.
1806 Green, R.S.; Smorodinsky, S.; Kim, J.J.; McLaughlin, R.; Ostro, B. (2004) Proximity of California public
schools to busy roads. Environ Health Perspect 112: 61-66. doi:10.1289/ehp.6566
1807 Wu, Y; Batterman, S. A. (2006) Proximity of schools in Detroit, Michigan to automobile and truck traffic. J
Exposure Sci & Environ Epidemiol, doi: 10.1038/sj.jes.7500484.
1808 Su, J.G.; Jerrett, M.; de Nazelle, A.; Wolch, J. (2011) Does exposure to air pollution in urban parks have
socioeconomic, racial, or ethnic gradients? Environ Res 111: 319-328.
1809 Jones, M.R.; Diez-Roux, A.; Hajat, A.; et al. (2014) Race/ethnicity, residential segregation, and exposure to
ambient air pollution: The Multi-Ethnic Study of Atherosclerosis (MESA). Am J Public Health 104: 2130-2137.
[Online at: https://doi.org/10.2105/AJPH.2014.302135.].
1810 Stuart A.L., ZeagerM. (2011) An inequality study of ambient nitrogen dioxide and traffic levels near elementary
schools in the Tampa area. Journal of Environmental Management. 92(8): 1923-1930.
https://doi.Org/10.1016/j.jenvman.2011.03.003.
1811 Stuart A.L., Mudhasakul S., Sriwatanapongse W. (2009) The Social Distribution of Neighborhood-Scale Air
Pollution and Monitoring Protection. Journal of the Air & Waste Management Association. 59(5): 591-602.
https://doi.Org/10.3155/1047-3289.59.5.591
1812 Willis M.D., Hill E.L., Kile M.L., Carozza S., Hystad P. (2020) Assessing the effectiveness of vehicle emission
regulations on improving perinatal health: a population-based accountability study. International Journal of
Epidemiology. 49(6): 1781-1791. https://doi.org/10.1093/ije/dyaal37
1813 Collins, T.W., Grineski, S.E., Nadybal, S. (2019) Social disparities in exposure to noise at public schools in the
contiguous United States. Environ. Res. 175, 257-265. https://doi.Org/10.1016/j.envres.2019.05.024.
1814 Kingsley S., Eliot M., Carlson L., Finn J., Macintosh D.L., Suh H.H., Wellenius G.A. (2014) Proximity of US
schools to major roadways: a nationwide assessment. J Expo Sci Environ Epidemiol. 24: 253-259.
https://doi.Org/10.1038/jes.2014.5
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factors, such as historic segregation, redlining, residential mobility, and daily
mobility 1815>1816>1817>1818>1819>1820
Several publications report nationwide analyses that compare the demographic patterns of
people who do or do not live near major roadways 1821>1822>1823>1824>1825>1826 Three of these studies
found that people living near major roadways are more likely to be people of color or of low
SES.1827'1828'1829 They also found that the outcomes of their analyses varied between regions
within the United States. However, only one such study looked at whether such conclusions were
confounded by living in a location with higher population density and looked at how
demographics differ between locations nationwide.1830 That study generally found that higher
density areas have higher proportions of low-income residents and people of color. In other
1815 Depro, B.; Timmins, C. (2008) Mobility and environmental equity: do housing choices determine exposure to
air pollution? Duke University Working Paper.
1816 Rothstein, R. The Color of Law: A Forgotten History of How Our Government Segregated America. New
York: Liveright, 2018.
1817 Lane, H.J.; Morello-Frosch, R.; Marshall, J.D.; Apte, J.S. (2022) Historical redlining is associated with present-
day air pollution disparities in US Cities. Environ Sci & Technol Letters 9: 345-350. DOI: [Online at:
https://doi.org/10.1021/acs.estlett.lc01012],
1818 Ware, L. (2021) Plessy's legacy: the government's role in the development and perpetuation of segregated
neighborhoods. RSF: The Russel Sage Foundation Journal of the Social Sciences, 7:92-109. DOI: DOI:
10.7758/RSF.2021.7.1.06.
1819 Archer, D.N. (2020) "White Men's Roads through Black Men's Homes": advancing racial equity through
highway reconstruction. Vanderbilt Law Rev 73: 1259.
1820 Park, Y.M.; Kwan, M.-P. (2020) Understanding Racial Disparities in Exposure to Traffic-Related Air Pollution:
Considering the Spatiotemporal Dynamics of Population Distribution. Int. J. Environ. Res. Public Health. 17 (3):
908. https://doi.org/10.3390/ijerphl7030908
1821 Rowangould, G.M. (2013) A census of the U.S. near-roadway population: public health and environmental
justice considerations. Transportation Research Part D; 59-67.
1822 Tian, N.; Xue, J.; Barzyk. T.M. (2013) Evaluating socioeconomic and racial differences in traffic-related metrics
in the United States using a GIS approach. J Exposure Sci Environ Epidemiol 23: 215-222.
1823 CDC (2013) Residential proximity to major highways - United States, 2010. Morbidity and Mortality Weekly
Report 62(3): 46-50.
1824 Clark, L.P.; Millet, D.//B., Marshall, J.D. (2017) Changes in transportation-related air pollution exposures by
race-ethnicity and socioeconomic status: outdoor nitrogen dioxide in the United States in 2000 and 2010. Environ
Health Perspect https://doi. org/10.1289/EHP959.
1825 Mikati, I.; Benson, A.F.; Luben, T.J.; Sacks, J.D.; Richmond-Bryant, J. (2018) Disparities in distribution of
particulate matter emission sources by race and poverty status. Am J Pub Health
https://ajph. aphapublications. org/doi/abs/10.2105/AJPH.2017.304297?journalCode =ajph.
1826 Alotaibi, R.; Bechle, M.; Marshall, J.D.; Ramani, T.; Zietsman, J.; Nieuwenhuijsen, M.J.; Khreis, H. (2019)
Traffic related air pollution and the burden of childhood asthma in the continuous United States in 2000 and 2010.
Environ International 127: 858-867. https://www.sciencedirect.com/science/article/pii/S0160412018325388.
1827 Tian, N.; Xue, J.; Barzyk. T.M. (2013) Evaluating socioeconomic and racial differences in traffic-related metrics
in the United States using a GIS approach. J Exposure Sci Environ Epidemiol 23: 215-222.
1828 Rowangould, G.M. (2013) A census of the U.S. near-roadway population: public health and environmental
justice considerations. Transportation Research Part D; 59-67.
1829 CDC (2013) Residential proximity to major highways - United States, 2010. Morbidity and Mortality Weekly
Report 62(3): 46-50.
1830 Rowangould, G.M. (2013) A census of the U.S. near-roadway population: public health and environmental
justice considerations. Transportation Research Part D; 59-67.
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publications assessing a city, county, or state, the results are similar.1831'1832'1833 Furthermore,
students of lower-income families and students with disabilities are more likely to travel to
school by bus or public transit than are other students 1834'1835'1836
Two recent studies provide strong evidence that reducing emissions from heavy-duty vehicles
is likely to reduce the disparity in exposures to traffic-related air pollutants. Both use NO2
observations from the recently launched TROPospheric Ozone Monitoring Instrument satellite
sensor as a measure of air quality, which provides high-resolution observations that heretofore
were unavailable from any satellite.1837
One study evaluated NO2 concentrations during the COVID-19 lockdowns in 2020 and
compared them to NO2 concentrations from the same dates in 2019.1838 That study found that
average NO2 concentrations were highest in areas with the lowest percentage of White
populations, and that the areas with the greatest percentages of non-White or Hispanic
populations experienced the greatest declines in NO2 concentrations during the lockdown. These
NO2 reductions were associated with the density of highways in the local area.
In the second study, NO2 measured from 2018-2020 was averaged by racial groups and
income levels in 52 large U.S. cities.1839 Using census tract-level NO2, the study reported
average population-weighted NO2 levels to be 28 percent higher for low-income non-White
people compared with high-income White people. The study also used weekday-weekend
differences and bottom-up emission estimates to estimate that diesel traffic is the dominant
source of NO2 disparities in the studied cities.
Overall, there is substantial evidence that people who live or attend school near major
roadways are more likely to be of a non-White race, Hispanic, and/or have a low SES. As
described in Chapter 5.4.8, traffic-related air pollution may have disproportionate and adverse
impacts on health across racial and sociodemographic groups. We expect communities near
roads will benefit from the reduced vehicle emissions of PM, NOx, SO2, VOC, CO, and mobile
1831 pra(( G.C.; Vadali, M.L.; Kvale, D.L.; Ellickson, K.M. (2015) Traffic, air pollution, minority, and socio-
economic status: addressing inequities in exposure and risk. Int J Environ Res Public Health 12: 5355-5372.
http://dx.doi.org/10.3390/ijerphl20505355.
1832 Sohrabi, S.; Zietsman, J.; Khreis, H. (2020) Burden of disease assessment of ambient air pollution and premature
mortality in urban areas: the role of socioeconomic status and transportation. Int J Env Res Public Health
doi:10.3390/ijerphl7041166.
1833 Aizer A., Currie J. (2019) Lead and Juvenile Delinquency: New Evidence from Linked Birth, School, and
Juvenile Detention Records. The Review of Economics and Statistics. 101 (4): 575-587.
https://doi.org/10.1162/rest_a_00814
1834 Bureau of Transportation Statistics (2021) The Longer Route to School. [Online at
https://www.bts.gov/topics/passenger-travel/back-school-2019]
1835 Wheeler, K.; Yang, Y.; Xiang, H. (2009) Transportation use patterns of U.S. children and teenagers with
disabilities. Disability and Health J 2: 158-164. https://doi.Org/10.1016/j.dhjo.2009.03.003
1836 Park, K.; Esfahani, H.N.; Novack, V.L.; et al. (2022) Impacts of disability on daily travel behaviour: A
systematic review. Transport Reviews 43: 178-203. https://doi.org/10.1080/01441647.2022.2060371
1837 TROPospheric Ozone Monitoring Instrument (TROPOMI) is part of the Copernicus Sentinel-5 Precursor
satellite.
1838 Kerr, G.H.; Goldberg, D.L.; Anenberg, S.C. (2021) COVID-19 pandemic reveals persistent disparities in
nitrogen dioxide pollution. PNAS 118. https://doi.org/10.1073/pnas.2022409118.
1839 Demetillo, M.A.; Harkins, C.; McDonald, B.C.; et al. (2021) Space-based observational constraints onN02 air
pollution inequality from diesel traffic in major US cities. Geophys Res Lett 48, e2021GL094333.
https://doi. org/10.1029/2021GL094333.
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source air toxics projected to result from this final rule. Although we were not able to conduct air
quality modeling of the estimated emission reductions, we believe it a fair inference that because
vehicular emissions disproportionately and adversely affect these communities with
environmental justice concerns due to roadway proximity, and because we project this rule will
result in significant reductions in vehicular emissions, these communities' exposures to non-
GHG air pollutants will be reduced. EPA is considering how to better estimate the near-roadway
air quality impacts of its regulatory actions and how those impacts are distributed across
populations.
5.6.3.2 Upstream Source Impacts
As described in Chapter 4.5. of the RIA, we expect some non-GHG emissions reductions
from sources related to refining petroleum fuels and increases in emissions from EGUs, both of
which would lead to changes in exposure for people living in communities near these facilities.
The EGU emissions increases become smaller over time because of changes in the projected
power generation mix as electricity generation uses less fossil fuels.
Analyses of communities in close proximity to EGUs have found that a higher percentage of
communities of color and low-income communities live near these sources when compared to
national averages.1840 EPA compared the percentages of people of color and low-income
populations living within three miles of fossil fuel-fired power plants regulated under EPA's
Acid Rain Program and/or EPA's Cross-State Air Pollution Rule to the national average and
found that there is a greater percentage of people of color and low-income individuals living near
these power plants than in the rest of the country on average. According to 2020 census data, on
average, the U.S. population is comprised of 40 percent people of color and 30 percent low-
income individuals. In contrast, the population living near fossil fuel-fired power plants is
comprised of 53 percent people of color and 34 percent low-income individuals.1841 Historically
redlined neighborhoods are more likely to be downwind of fossil fuel power plants and to
experience higher levels of exposure to relevant emissions than non-redlined neighborhoods.1842
Analysis of populations near refineries and oil and gas wells also indicates there may be potential
disparities in pollution-related health risk from these sources 1843>1844>1845>1846 See also Chapter 4
of this RIA, discussing issues pertaining to lifecycle emissions more generally.
1840 See 80 FR 64662, 64915-64916 (October 23, 2015).
1841 U.S. EPA (2023) 2021 Power Sector Programs - Progress Report.
https: //www 3 .epa.gov/airmarkets/progress/reports/
1842 Cushing L.J., Li S., SteigerB.B., Casey J.A. (2023) Historical red-lining is associated with fossil fuel power
plant siting and present-day inequalities in air pollutant emissions. Nature Energy. 8: 52-61.
https://doi.org/10.1038/s41560-022-01162-y
1843 U.S. EPA (2014). Risk and Technology Review—Analysis of Socio-Economic Factors for Populations Living
Near Petroleum Refineries. Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina.
January.
1844 Carpenter, A., and M. Wagner. Environmental justice in the oil refinery industry: A panel analysis across United
States counties. J. Ecol. Econ. V. 159 (2019).
1845 Gonzalez, J.X., et al. Historic redlining and the siting of oil and gas wells in the United States. J. Exp. Sci. &
Env. Epi. V. 33. (2023). p. 76-83.
1846 In comparison to the national population, the EPA publication reports higher proportions of the following
population groups in block groups with higher cancer risk associated with emissions from refineries: "minority,"
"African American," "Other and Multiracial," "Hispanic or Latino," "Ages 0-17," "Ages 18-64," "Below the Poverty
Level," "Over 25 years old without a HS diploma," and "Linguistic isolations."
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Chapter 6 Economic and Other Impacts
This chapter discusses potential impacts of the final rule on HD vehicle sales including
potential impacts on vehicles sales, and potential shifts among modes and classes of vehicles,
and between domestic and foreign sales, under the modeled potential compliance pathway. It
also discusses the acceptance of ZEVs by HD purchasers and the potential for rebound effects on
VMT. This chapter then discusses the potential impacts of the rule on employment. Finally, this
chapter discusses the impacts of the rule on U.S. oil imports and electricity consumption.
6.1 Impact on Sales, Fleet Turnover, Mode Shift, Class Shift, and Domestic Production
6.1.1 Vehicle Sales and Fleet Turnover
The effects of the CO2 emission standards under the modeled potential compliance pathway
on HD vehicle sales will depend, at least in part, on the extent to which purchasers consider fuel,
maintenance, and repair savings associated with the HD GHG Phase 3 program in their purchase
decisions. Our analyses for the modeled potential compliance pathway indicate that, while some
heavy-duty ZEVs and associated EVSE, as applicable, will be more expensive to purchase than
comparable ICE vehicles, ZEVs will be less expensive to operate and maintain than comparable
ICE vehicles. The more these savings are considered, the smaller the impact on sales due to an
increase in the price of the vehicle. In addition, if the savings considered by a purchaser
outweigh the increase in the price of the vehicle and EVSE, which we show is possible with most
ZEVs (see RIA Chapter 2.9.4.2), sales of that vehicle may increase.
In addition to effects on total sales of HD vehicles, perceptions about post-regulation vehicles
and cost differences between pre- and post-regulation vehicles (both upfront and operational
costs) have the potential to lead to an increase in the sale of ICE vehicles before the standards
become effective in order to avoid perceived potential cost, quality, or other changes due to the
regulation, a phenomenon called "pre-buy." These are vehicles that are purchased earlier than
would have happened in the absence of the standards. Another reason pre-buy might occur is due
to purchaser beliefs about the availability of their vehicle type of choice in the post-regulation
market. For example, if purchasers think that they might not be able to get the HD ICE vehicle
they want after the regulation is promulgated, they may pre-buy a HD ICE vehicle.1847
Our assessment, with respect to ZEV technologies included in our potential compliance
pathway, is that purchasers' consideration of the lower operational costs of ZEVs, as well as the
federal vehicle and battery tax credits, and EVSE tax credits for those purchasers eligible for
them, will mitigate possible pre-buy by reducing the perceived purchase price or lifetime
operational costs difference of a new, post-rule ZEV compared to a new pre- or post-rule
comparable ICE vehicle. We also expect that the final rule's more gradual phase-in of more
stringent standards compared to the proposal will mitigate possible pre-buy. Additionally, pre-
buy, to the extent it might occur, could be mitigated in multiple other ways, including by
reducing the higher upfront cost of post-regulation vehicles, or by reducing uncertainty about
new technology through purchasers being educated on the new technology, or increasing
1847 We note that the HD TRUCS model used in this rulemaking to analyze ZEV technologies matched performance
capabilities of ZEVs to an existing ICE vehicle for each use case where the ZEV vehicle technologies are
technologically feasible.
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exposure to the new technology. For example, education on the benefits of ZEV ownership and
operational characteristics (for example, reduced operating costs, decreased exposure to exhaust
emissions and engine noise, and smoother acceleration) and on charging and hydrogen refueling
infrastructure technology and availability may lead to less uncertainty about each of these
technologies. Though our final standards do not mandate the use of a specific technology, they
may increase purchaser exposure to ZEVs, as well as incentivize manufacturers and dealers to
educate HD vehicle purchasers on ZEVs, including the benefits of ZEVs, accelerating the
reduction of purchaser risk aversion (see RIA Chapter 6.2). Local and federal actions investing in
ZEV infrastructure and supply chain, including the CHIPS Act, BIL and IRA, will lead to
reduced uncertainty surrounding ZEV ownership, likely further mitigating possible pre-buy. For
more information on purchaser acceptance of HD ZEVs, see RIA Chapter 6.2. For more
information on the charging and hydrogen refueling infrastructure analysis in this rule, see RIA
Chapters 1.6, 1.8, and 2.6.
As noted in Preamble ES.D, the estimated fleet-average costs to manufacturers per-vehicle for
this rule are less than those estimated for the HD GHG Phase 2 rule, which EPA found to be
reasonable, and we do not have data showing a significant level of pre-buy for Phase 2. As also
noted in Preamble ES.D, HD ZEV purchasers' incremental upfront costs (after the tax credits)
are recovered through operational savings such that payback occurs between two and four years
on average for vocational vehicles, two years for short-haul tractors, and five years on average
for long-haul tractors. These operational cost savings, and the associated payback of higher
upfront costs, will also mitigate pre-buy to the extent they are considered in the purchase
decision. With respect to possible purchaser anxiety over being unable to purchase an ICE
vehicle after promulgation of the regulation, we note that these final standards do not mandate
the production or purchase of any particular vehicle or use of any particular technology in such
vehicles. As described in Preamble Section ES.C, and Preamble Section II, we model a potential
compliance pathway to meet the standards with a diverse mix of ICE vehicle and ZEV
technologies, as well as additional compliance pathways to meet the standards that do not
include increasing utilization of ZEV technologies. In addition, the phasing-in of the standards
will allow ample time for purchasers to make decisions about their vehicle of choice and the
potential compliance pathway modeled for this rule reflects that the majority of vehicles will
remain ICE vehicles, even in MY 2032.
In addition to pre-buy, there is the possibility of "low-buy," a scenario in which there would
be a decrease in HD vehicle sales after the regulation becomes effective. In a low-buy scenario,
sales of HD vehicles would decrease in the months after the regulation becomes effective,
compared to what would have happened in the absence of the regulation, due to purchasers either
pre-buying or delaying a planned purchase. Low-buy may be due directly to pre-buy, where
vehicle purchases that would have been made in the months after the effective date of the new
emission standards are pulled forward to before the effective date of the new emission standards.
Alternatively, low-buy may be due to purchasers delaying the purchase of a new vehicle due to
the new emissions standards, for example because of increased costs or uncertainty related to the
regulated vehicles. If pre-buy is smaller than low-buy, to the extent they both might occur, this
would lead to reduced fleet turnover, at least in the short-term.1848 The older trucks would remain
1848 Fleet turnover refers to the pace at which new vehicles are purchased and older vehicles are retired. A slower
fleet turnover means older vehicles are kept on the road longer, and the fleet is older on average. A faster fleet
turnover means that the fleet is younger, on average.
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in use longer than they would have in the absence of the new emission standards. This would
lead to lower emission reductions than we estimate will be achieved as a result of the standards.
If pre-buy is larger than low-buy, short-term fleet turnover would increase; fleets would be, on
average, comprised of newer model year vehicles. Though these new vehicles are expected to
have lower emissions than the vehicles they are replacing, and emission reductions would be
expected to be larger than under a scenario where low-buy exceeds pre-buy, emission reductions
would still be lower than we estimated will be achieved as a result of the emission standards.
Under a situation where low-buy matches pre-buy, we would also expect lower emission
reductions than estimated, and emission reductions would likely be somewhere between the two
relative pre-buy /low-buy scenarios discussed above. We expect low-buy, to the extent it might
occur, to be mitigated under the same circumstances described above for pre-buy. Both pre-buy
and low-buy, if they were to occur, are short-term phenomena.
At proposal, we discussed an analysis of previously promulgated EPA HD emission standards
that indicates that where pre- or low-buy is seen, the magnitude has been small.1849 EPA recently
contracted with Eastern Research Group, Inc. (ERG) to complete a literature review on research
that estimates sales impacts, as well as to conduct original research to estimate sales impacts for
previous EPA HD vehicle rules on pre- and low-buy for HD vehicles. This work suggested that
pre- and low-buy effects may occur for up to a year before or after a regulation is implemented,
if they occur at all. 1850>1851 The resulting analysis examined the effect of four HD regulations,
those that became effective in 2004, 2007, 2010 and 2014, on the sales of Class 6, 7 and 8
vehicles over the twelve months before and after each standard.1852 For the purposes of this
discussion, we will call these the 2004 rule, 2007 rule, 2010 rule and 2014 rule. The 2004, 2007
and 2010 rules focused on reducing criteria pollutant emissions. The 2014 rule (the HD GHG
Phase 1 rule promulgated in 2014) focused on reducing GHG emissions. The report finds little
evidence of sales impacts for Class 6 and 7 vehicles. For Class 8 vehicles, evidence of pre-buy
was found before the 2010 rule's implementation and for only one month before the 2014 rule's
implementation dates, and evidence of low-buy was found after the 2002, 2007 and 2010 rules'
1849 For example, Lam, T., and Bausell, C. "Strategic Behaviors Toward Environmental Regulation: A Case of
Trucking Industry." Contemporary Economic Policy 25(1): 3-13. 2007, Rittenhouse, K., and Zaragoza-Watkins,M.
"Anticipation and Environmental Regulation." Journal of Environmental Economics and Management 89: 255-277.
2018, and an unpublished report by Harrison, D., Jr., and LeBel, M. "Customer Behavior in Response to the 2007
Heavy-Duty Engine Emission Standards: Implications for the 2010 NOX Standard." NERA Economic Consulting.
2008. For EPA's summary on these studies, see the EPA peer review study U.S. Environmental Protection Agency.
"Analysis of Heavy-Duty Vehicle Sales Impacts Due to New Regulation." EPA-420-R-21-013. 2021.
https://cfpub.epa.gov/si/si_public_pra_view.cfm7dirEntryID=349838&Lab=OTAQ, or the recently published EPA
Heavy-Duty 2027 rule at Docket ID EPA-HQ-2019-0555
1850 U.S. Environmental Protection Agency. "Analysis of Heavy-Duty Vehicle Sales Impacts Due to New
Regulation." EPA-420-R-21-013. 2021.
https://cfpub.epa.gov/si/si_public_pra_view.cfm7dirEntry ID=349838&Lab=OTAQ
1851 This report will be referred to as the ERG report in the rest of this discussion.
1852 The 2004 rule, "Final Rule for Control of Emission of Air Pollution From Highway Heavy-Duty Engines", was
finalized in 1997. The 2007 and 2010 rules were finalized as phase-ins in the "Final Rule for Control of Emissions
of Air Pollution from 2004 and Later Model Year Heavy-Duty Highway Engines and Vehicles; Revision of Light-
Duty On-Board Diagnostics Requirements" in 2000. The 2014 GHG rule, "Final Rule for Phase 1 Greenhouse
House Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles,"
was finalized in 2011. These rules can be found on the EPA website https://www.epa.gov/regulations-emissions-
vehicles-and-engines/regulations-emissions-commercial-trucks-and-buses-heavy.
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implementation dates. The report findings, however, do suggest that the range of possible results
include a lower bound of zero, i.e., no pre-buy or low-buy due to EPA rules.1853
However, at proposal we also made it clear that, while it is instructive that the ERG report
found little to no pre-buy or low-buy effects due to our HD rules, the approach to estimate a
change in the sales of HD vehicles before and after the promulgation of a rule due to the cost of
that rule (as was done in the ERG report) should not be used to estimate sales effects from this
rule for three main reasons.1854 First, most of the statistically significant sales effects in the report
were estimated using data from criteria pollutant rules (the 2002, 2004 and 2007 rules), which
are not appropriate for use in estimating effects from GHG rules. This is due to differences in
how costs are incurred and benefits to HD vehicle purchasers are accrued as a result of HD
vehicle criteria pollutant regulations versus HD GHG regulations, which may lead to differences
in how HD vehicle buyers react to a particular regulation. For example, the 2014 rule reduced
GHG emissions, and had lower estimates of associated technology costs relative to the criteria
pollutant rules, and compliance with the GHG rule was associated with fuel savings. We also
expect operating savings due to this rule, as described in Chapter 3.4.
Second, there was relatively more uncertainty in the net estimated price change from the 2014
GHG rule than in the criteria pollutant rules. The performance-based GHG standards had many
different compliance pathways which led to both capital cost increases, as well as reductions in
operating costs through fuel savings. As such, the cost of the regulation could vary greatly across
firms, and may have led to net cost savings. As this estimated change in cost is what was used to
estimate the effect of the rule on pre-buy and low-buy, the likely variation in net costs of the rule
are associated with uncertainty about the results of the pre-buy and low-buy sales effects from
the 2014 rule.
Third, the approach outlined in the ERG report was estimated only using data from HD ICE
vehicles (for example, cost of compliance due to adding HD ICE engine technologies to a HD
ICE engine). The modeled potential compliance pathway for this rule includes ZEV
technologies, which are associated with additional EVSE infrastructure. The possible impacts of
this are not represented in the results of the report.
Though there is uncertainty related to the costs used in the 2014 rule analysis, the results of
the ERG report, combined with the literature review completed for the report, indicate that there
is little evidence of pre-buy or low-buy associated with GHG rules. This is supported by data
from the U.S. Bureau of Economic Analysis, which shows that sales of heavy-weight trucks
were fairly consistently increasing from the end of 2009 through the end of 20 1 5.1855 Altogether,
this suggests that there was likely little to no pre- or low-buy due to the 2014 GHG rule.
Though the increased purchase price due to this rule could potentially lead to pre- and/or low-
buy, it is unlikely to occur in a significant manner. Specifically, we expect that they will either
1853 The ERG report includes statistically significant results of no effect for pre-buy on the 2002 rule, as well as
results where no effect cannot be ruled out for pre-buy on the 2007, 2010 and 2014 rules, and for low-buy on the
2002, 2010 and 2014 rules.
1854 See the Chapter 10 in the RIA for the HD 2027 rule for an example of how we might estimate potential impacts
of a HD regulation on vehicle sales, including pre-buy and low-buy, using the approach introduced in the ERG
report. 88 FR 14296. January 24, 2023.
1855 The graph of monthly, seasonally adjusted heavy weight truck sales from the Bureau of Economic Analysis can
be found at: https://fred.stlouisfed.org/series/HTRUCKSSAAR.
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not occur at all, or if they do, occur in a limited way that will not significantly affect the GHG
emissions reductions projected by this rule or that would unduly disrupt the HD vehicle market.
This is due, in part, to the operating cost savings we estimate will be achieved in complying with
this rule. For the modeled compliance pathway for this rule, that cost savings are expected to
wholly offset the increase upfront purchase cots for ZEVs, which leads to payback periods of
between two and five years. The historical data described in this section indicate that little to no
pre- or low-buy has been seen from previously promulgated EPA HD emission standards. Lastly,
it should be noted that many studies estimating how large or expensive purchases are made,
including that of HD vehicles, purchase decisions are heavily influenced by macroeconomic
factors unrelated to regulations, for example, interest rates, economic activity, and the general
state of the economy.1856 For example, according to the Economic Research Division of the
Federal Reserve, retail sales of heavy weight trucks fell dramatically between September of 2019
and May of 2020 (about 46 percent fewer sales), likely in great part due to the COVID-19
pandemic, and then they rebounded through the May of 2021 to be only about 13 percent lower
than in September of the previous year.1857 The historical data described in this section, relatively
low projection of the increase in market share for ZEVs in the modeled potential compliance
pathway, and the associated continued availability of ICE vehicles, also support little to no pre-
or low-buy due to this rule. It should be noted, however, that, unlike the previous HD
regulations, infrastructure availability and the perception of the same is likely to impact purchase
decisions. This is discussed more in RIA Chapter 6.2.
This rule is expected to lead to a decrease in total HD highway fleet emissions, though this
decrease will happen gradually as the HD fleet turns over.1858 This is because the fraction of the
total on-highway HD vehicle fleet that are new compliant vehicles will initially be a small
portion of the entire HD market. As more vehicles compliant with this rule are sold, and as older
HD vehicles are retired, greater emission reductions will accumulate. The emission reductions
attributable to each HD segment that will be affected by this rule will depend on many factors,
including the rate of purchase of compliant vehicles in each market segment over time and the
proportion of those vehicles that utilize each of the mix of technologies under the compliance
pathways manufacturers choose. For example, if ZEV technologies uptake occurs faster than
projected under the modeled potential compliance pathway, emission reductions will accumulate
faster than estimated. In addition, if pre-buy or low-buy occurs associated with this rule,
emission reductions will be smaller than estimated as well. This is because, under pre-buy
conditions, fleets would, on average, be comprised of newer model year vehicles. Though these
new vehicles are expected to have lower emissions than the vehicles they are replacing, emission
reductions could still be lower than we estimate will be achieved as a result of the final emission
standards. Under low-buy, we expect older, more polluting, HD vehicles to remain in use longer
than they otherwise would in the absence of new regulation. If pre-buy is smaller than low-buy,
to the extent both might occur, this would lead to a slower fleet turnover, at least in the short
1856 See the literature review found in the ERG report mentioned earlier in this Section, "Analysis of Heavy-Duty
Vehicle Sales Impacts Due to New Regulation." Found at
https://cfpub.epa.gov/si/si_public_pra_view.cfm?dirEntryID=349838&Lab=OTAQ for more information.
1857 jjlc graph 0f monthly, seasonally adjusted heavy weight truck sales from the Bureau of Economic Analysis can
be found at: https://fred.stlouisfed.org/series/HTRUCKSSAAR.
1858 See Preamble Section V and RIA Chapter 4.4 for details on estimated HD emissions effects due to this final rule.
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term.1859 Conversely, if pre-buy is larger than low-buy, short-term fleet turnover would increase
and fleets would, on average, be comprised of newer model year vehicles, and though emission
reductions would be expected to be larger than under a scenario where low-buy exceeds pre-buy,
emission reductions would still be lower than we estimate will be achieved as a result of the final
emission standards. Under a situation where low-buy matches pre-buy, we would also expect
lower emission reductions than estimated, and emission reductions would likely be somewhere
between the two relative pre-buy /low-buy scenarios discussed in this paragraph.
6.1.2 Mode Shift
Mode shift would occur if goods that would normally be shipped by HD vehicles are shipped
by another method (e.g., rail, boat, air) due to the emission standards. EPA does not expect this
rule to result in a transportation mode shift. Generally, shipping cargo via truck is more
expensive per ton-mile than barge or rail, and less expensive than air. 1860>1861 This is due to many
factors, not the least of which is labor costs (each truck has at least one driver). Even though
trucking is more expensive than rail or marine on a ton-mile basis, it is a very attractive
transportation alternative for several reasons: shipping via truck is generally faster and more
convenient than rail or marine, trucks can reach more places, and trucks may be less constrained
by available infrastructure than barge or rail. In addition, shipping via truck does not require
trans-shipments (transferring from one mode to another, for example to deliver cargo to or from
the port or rail yard), and it allows partial deliveries at many locations. This speed, infrastructure
availability, and delivery flexibility make trucking the transportation solution of choice for many
kinds of cargo across most distances. As a result, smaller shipments of higher-valued goods (e.g.,
consumer goods) tend to be transported by air or truck, while larger shipments of lower-valued
goods (e.g., raw materials) tend to go via rail or barge.1860'1862
Studies of intermodal freight shifts, such as Comer et al. (2010) or Bushnell and Hughes
(2019), focus on changes in cost per ton-mile as a potential source of transportation mode
shift.1860'1862 Comer et al. note, for instance, that fuel consumption "depend[s] on the type of
freight being moved, route characteristics, transport speed, and locomotive/truck
characteristics."1860 Bushnell and Hughes estimate that increased fuel prices for truck
transportation lead to small substitutions between truck and rail for small or large shipments, and
higher shifts for intermediate-sized shipments.1862 The findings from this study suggest that the
variation in the kinds and values of goods shipped by different modes likely result in only a
small amount of mode shift in response to a change in operating cost (e.g., fuel prices). However,
due to data availability, this study approximates freight rates with fuel costs, assumes shipping
distances using different modes are the same, and mostly does not consider transportation
1859 Fleet turnover refers to the pace at which new vehicles are purchased and older vehicles are retired. A slower
fleet turnover means older vehicles are kept on the road longer, and the fleet is older on average. A faster fleet
turnover means that the fleet is younger, on average.
1860 Comer, B.; Corbett, J. J.; Hawker, J.S.; Korfmacher, K.; Lee , E.E.; Prokop, C.; and Winebrake. J. "Marine
Vessels as Substitutes for Heavy-Duty Trucks in Great Lakes Freight Transportation." Journal of the Air & Waste
Management Association 60: 884-890. 2010.
1861 U.S. EPA Office of Transportation and Air Quality. "Economic Impacts of the Category 3 Marine Rule on Great
Lakes Shipping." EPA-420-R-12-005. 2012.
1862 Bushnell, J., and Hughes, J. "Mode Choice, Energy Consumption and Emissions in U.S. Freight
Transportation." Working paper. 2019. Available online:
https://spot.colorado.edu/~jonathug/Jonathan_E._Hughes/Main_files/Freight_Modes.pdf, accessed 10/21/2019.
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availability constraints affecting some modes in some regions. These limitations may distort the
effects they estimate.
A mode shift study EPA carried out in 2012 in the context of new sulfur limits for fuel used in
large ships operating on the Great Lakes may help address some of these limitations.1861 The
methodology used a combination of geospatial modeling and freight rate analysis to examine the
impact of an increase in ship operating costs. While the focus of the study was transportation
mode shift away from marine and toward land, it noted that truck transportation is far more
expensive than both rail and marine on a ton-mile basis.1863 It also shows that even a large
percentage increase in marine fuel costs did not raise freight rates by a similar percentage,
because fuel costs are only part of total operating costs. In the case of truck transportation,
operating costs are a much smaller portion of total costs. The results of this study combined with
the others cited in this section indicate that changing the cost of truck transportation is unlikely to
create mode shift.
Whether shippers switch to a different transportation mode for freight depends not only on the
cost per mile of the shipment (i.e., freight rate), but also the value of the shipment, the speed of
transport needed for shipment (for example, for non-durable goods), and the availability of
supporting infrastructure (e.g., rail lines, highways, waterways). Shifting from HD vehicles to
other modes of transportation may occur if the cost of shipping goods by truck increases relative
to shipping by other modes in cases where there is another mode of transport available that can
meet the required timing. Though we are unable to estimate what affect this rule might have on
shipping costs, in part because we are not able to estimate how a change in upfront vehicle costs
affects shipping rates, or how much of a change in operational costs is passed through to the
shipping rates, we do estimate that, under the potential compliance pathway projected for this
rule, average net upfront costs are paid back in five years or less for the vehicle groups affected
by this rule, and these vehicles are expected to experience reduced operational costs. In addition,
the vehicles that comply with this rule are expected to have positive total costs of ownership over
both five- and ten-year time horizons, and thus, we do not expect a significant increase in
shipping rates. For these reasons, we do not expect mode shift from HD vehicles to a different
mode of transportation is a likely outcome of this regulation.1864
6.1.3 Class Shift
Class shift would occur if purchasers shift their purchases from one class of vehicle to another
class of vehicle due to impacts of the rule on vehicle attributes, including performance and
relative costs, among vehicle types that could practically be switched. Heavy-duty vehicles are
typically configured and purchased to perform a function. For example, a concrete mixer truck is
purchased to transport concrete, a combination tractor is purchased to move freight with the use
of a trailer, and a Class 4 box truck could be purchased to make deliveries. The purchaser makes
decisions based on many attributes of the vehicle, including the gross vehicle weight rating,
which in part determines the amount of freight or equipment that can be carried. If the Phase 3
standards impact either the performance or cost of a vehicle relative to the other vehicle classes,
1863 Figure 1-5 in U.S. EPA Office of Transportation and Air Quality. "Economic Impacts of the Category 3 Marine
Rule on Great Lakes Shipping." EPA-420-R-12-005. 2012.
1864 We note that a study published by Argonne National Laboratory in 2017 indicates that if mode shift were to
occur as a result of this rule, it would likely result in further decreasing transportation GHG emissions and upstream
energy usage, https://publications.anl.gov/anlpubs/2017/08/137467.pdf.
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then purchasers may choose to purchase a different vehicle, resulting in the unintended
consequence of increased fuel consumption or GHG emissions in-use.
A purchaser in need of a specific vocational vehicle, such as a bus, box truck or street
sweeper, would not be able to shift the purchase to a vehicle with a less stringent emission
standard (such as the optional custom chassis standards for emergency vehicles, recreational
vehicles, or mixed use (nonroad) type vehicles) and still meet their needs. The purchaser makes
decisions based on many attributes of the vehicle, including the gross vehicle weight rating or
gross combined weight rating of the vehicle, which in part determines the amount of freight or
equipment that can be carried. Due to this, it is not likely feasible for purchasers to switch to
other vehicle classes simply due to the emission standards.
As described in Section II.D.3 of the Preamble, we account for differences in vehicle uses
and payload capacity in HD TRUCS, incorporating that analysis into our consideration of
possible compliance pathways to support the feasibility of the final standards. In the modeled
potential compliance pathway, we estimate the new vehicles produced and sold that are
compliant with the rule, including ZEVs, are able to perform the same function as vehicles
produced without the rule in place. For example, BEV technologies were not included within the
potential compliance pathway in situations where the performance needs of a BEV would result
in a battery that was too large or heavy due to the impact on payload and potential work
accomplished relative to a comparable ICE vehicle.1865 Also, it should be noted that for this final
rule, we projected multiple pathways to compliance, including pathways that did not project an
increase in ZEV penetration. Furthermore, although there are possible pathways that include
reduced ZEV penetration compared to the modeled potential compliance pathway estimated in
the analysis for this rule, there may also be greater ZEV penetration in one or more vehicle
classes than we estimate in the modeled potential compliance pathway.
Class shift could occur if one class of vehicle becomes significantly more expensive relative
to another class of vehicle due to the technology and operating costs associated with the new
emission standards. We expect that class shifting, if it does occur, would be very limited because
this rule applies new emission standards to all HD vehicle classes that would practically be
switched as described in Preamble Section II. In addition, the purchase cost of HD vehicles
typically increases with the class of the vehicle, and the modeled compliance pathway for this
rule does not lead to situations where the cost to purchase a heavier class of vehicles becomes
lower than the cost to purchase a lighter class (see Preamble Section II.F.2). Also, the average
payback period for the technologies in the modeled potential compliance pathway for all of the
classes of vehicles are within the first ownership period, and our analysis shows a positive total
cost of ownership over a five-year time horizon.
If a limited amount of shifting were to occur, we would expect negligible emission impacts
(compared to those emission reductions estimated to occur as a result of the emission standards).
For more information see Preamble Section VI.E.l.
6.1.4 Domestic Production
The final standards are not expected to provide incentives for manufacturers to shift between
domestic and foreign production. This is because the standards apply to any vehicles sold in the
1865 We assess the incremental weight increase or decrease of ZEVs compared to ICE vehicles in RIA Chapter 2.9.1.
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U.S. regardless of where they are produced. If foreign manufacturers already have relatively
more expertise in satisfying the requirements of the standards, there may be some initial
incentive for foreign production. However, offsetting this potential effect, and given increasing
global interest in reducing vehicle emissions, specifically through the use of ZEV technologies,
as domestic manufacturers produce vehicles with reduced emissions (including ZEVs) the
opportunity for domestic manufacturers to sell in other markets might increase. To the extent that
the requirements of this rule might lead to application and use of technologies that other
countries may seek now or in the future, developing this capacity for domestic producers now
may provide some additional ability to serve those markets. In addition, this rule and other
federal actions including the IRA and BIL support the U.S. in our efforts to remain competitive
on a global scale by encouraging and supporting the expansion of and investment in domestic
manufacturing of ZEV technologies, supply chains, charging infrastructure and other industries
related to green transportation technology.
As discussed in Preamble Section ES.B, and RIA Chapter 1.3, IRA section 13502, "Advanced
Manufacturing Production Credit," contains a battery tax credit for the production and sale of
battery cells and modules (of up to $45 per kilowatt-hour (kWh), and for 10 percent of the cost
of producing applicable critical minerals (including those found in batteries and fuel cells,
provided that the minerals meet certain specifications)), which is conditioned on such
components or minerals being produced in the United States and, thus, is designed to encourage
such domestic production. Our cost analysis reflects that in our modeled potential compliance
pathway we project an increasing percentage of batteries used in HD BEVs will be eligible for
this tax credit beginning in MY 2027 through MY 2032, in addition to consideration of the other
tax incentives that apply to vehicle and EVSE purchasers, as described in Sections II and IV of
the Preamble and Chapters 2 and 3 of the RIA.
6.2 Purchaser Acceptance
In the modeled potential compliance pathway for the final rule, we project an increase in the
adoption of HD BEVs and FCEVs for most of the HD vehicle types for MYs 2027 and beyond
(see preamble Section II or the RIA Chapter 2 for details). As explained in RIA Chapter 2.10,
although some HD ZEVs have higher upfront purchaser costs for some vehicles than comparable
ICE vehicles (including consideration of EVSE, as applicable), our cost analysis shows that this
incremental upfront purchaser cost difference would be partially or fully offset by a combination
of the federal vehicle purchase tax credits, battery tax credits, and EVSE tax credits for HD
ZEVs that are available through MY 2032, and further offset over time through the operational
cost savings. Our analysis shows that, in our modeled compliance pathway, the vehicle types for
which we project ZEV adoption for MY 2032 have an average payback period of between two
and five years, depending on the regulatory group, when compared to a comparable ICE vehicle,
even after considering the upfront purchaser and operating costs of the associated EVSE.1866 The
savings are due to our assessment of the expected cost savings in fuel, maintenance, and repair
over the life of the HD ZEV when compared to a comparable ICE vehicle. See Sections II and
IV of the preamble and Chapters 2 and 3 of this RIA for further discussion of payback.
1866 Estimates of average per-ZEV payback of purchaser upfront costs shown in RIA Chapter 2.10.6 show LHD
vocational vehicles have a payback period of 2 years, MHD vocation vehicles have a payback period of 3 years,
HHD vocational vehicles have a payback period of 4 years, day cab tractors have a payback period of 2 years, and
sleeper cab tractors have a payback period of 5 years.
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Businesses that operate HD vehicles are under competitive pressure to reduce operating costs,
which should encourage purchasers to identify and rapidly adopt new vehicle technologies that
reduce operating costs. As outlays for labor and fuel generally constitute the two largest shares of
HD vehicle operating costs, depending on the price of fuel, distance traveled, type of HD
vehicle, and commodity transported (if any), businesses that operate HD vehicles face strong
incentives to reduce these costs. 1867>1868 Thus, potential savings in operating costs appear to offer
HD vehicle buyers strong incentives to pay higher upfront prices for vehicles that feature
technology or equipment that reduces operating costs, such as HD ZEVs as explained above.
Economic theory suggests a normally functioning competitive market would lead HD vehicle
buyers to want to purchase, and HD vehicle manufacturers to incorporate, technologies that
contribute to lower net costs.
Indeed, given EPA's assessment in HD TRUCS for this rule showing significant reductions in
operating costs for HD ZEVs compared to comparable ICE vehicles, economic theory suggests
that the market should deliver those savings, and increase ZEV adoption, even without EPA's
standards. We are currently seeing increasing demand for, and increasing investment in, ZEV
technology prior to the adoption of the final standards.1869 Thus, even with our revised reference
case for the final rule, it is possible that adoption of ZEVs, and other technologies, could occur
more rapidly than EPA projects in the reference case.1870
Though theory suggests the market should adopt technology associated with operating cost
savings (like ZEVs), as discussed extensively in the HD Phase 2 rule,1871 an "energy efficiency
gap" or "energy paradox" has existed, where available technologies that would reduce the total
cost of ownership for the vehicle (when evaluated over their expected lifetimes using
conventional discount rates) have not been widely adopted, or the adoption is relatively slow,
despite their potential to repay buyers' initial investments rapidly. Economic research offers
several possible explanations for why the prospect of these apparent savings might not lead HD
manufacturers and buyers to adopt technologies that are expected to reduce operating costs.
Though existing research focuses specifically on adoption of ICE technologies that result in
decreased fuel costs, many of the explanations may also hold true for the adoption of ZEV
technologies, which we estimate will result in decreased fuel or other operating costs.
Explanations include constraints on access to capital for investment, imperfect or asymmetrical
information about the new technology (for example, real-world operational cost savings,
durability, or performance), uncertainty about supporting infrastructure (for example, ease of
charging a BEV), uncertainty about the resale market, and first-mover disadvantages for
manufacturers. Below, we discuss how some of these may impact the adoption of HD ZEVs as
well as factors that may mitigate them.
Constraints on investment, either for manufacturers of the technology or for potential
purchasers of the technology, lead to slower adoption rates. Federal or other incentives to
manufacture or purchase energy efficient technology will reduce the impact that constraints on
investment have on adoption of that technology. For ZEVs, the availability of existing
1867 American Transportation Research Institute, An Analysis of the Operational Costs of Trucking, September 2013.
Docket ID: EPA-HQ-OAR-2014-0827-0512.
18(38 Transport Canada, Operating Cost of Trucks, 2005. Docket ID: EPA-HQ-OAR-2014-0827-0070.
1869 See Preamble ES.C.
187° epa's reference case is discussed in RIA Chapter 4.
1871 See 81 FR at 73859-62.
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incentives, including the Federal purchaser (vehicle and EVSE) and battery manufacturing tax
credits in the IRA, is expected to lead to lower upfront costs for purchasers of HD ZEVs than
would otherwise occur.1872 More specifically, we expect that adoption rates of HD ZEVs would
be impacted by purchasers taking advantage of existing incentives, specifically the IRA vehicle
tax credit and EVSE tax credit (as applicable),1873 to lower the upfront costs for purchasers of
HD ZEVs (including depot EVSE). We expect this will result in a higher ZEV adoption rate than
would otherwise exist absent such incentives, and so counteracts the energy efficiency gap under
the modeled potential compliance pathway for manufacturers.
In addition, as purchasers consider more of the operational cost savings, for example, of a
ZEV over a comparable ICE vehicle, in their purchase decision, the smaller the impact the higher
upfront costs for purchasers has on that decision, and purchasers are more likely to purchase the
vehicle with that technology (in this example, a ZEV). However, one reason purchasers may not
consider the full, or even a portion of, operational cost savings of a ZEV over a comparable ICE
vehicle, is due to uncertainty, e.g., uncertainty about future fuel and electricity prices.1874
Adoption may be affected by additional areas of uncertainty as well such as purchasers'
impressions of BEV charging and FCEV fueling infrastructure support and availability,
perceptions of the comparisons of quality and durability of the different HD powertrains, and
resale value of the vehicle. Another factor that may affect adoption of ZEVs is purchasers'
uncertainty about the technology, both with respect to ZEVs, as well as with new technology
applied to ICE vehicles.1875
In a working paper by Bae, et al. (2022),1876 the authors report the results of interviews
conducted in 2018 and 2019 with eighteen HD fleet operators in California on their perspectives
on viable alternative fuel options over the next decade and beyond, as well as what motivators or
barriers exist to adopting those alternatives. Though electric, hydrogen, compressed natural gas
and hybrid options were generally seen as viable in the 2030's, operators reported concerns
related to functional unsuitability of electric options, uncompetitive upfront costs of hydrogen,
and unpromising support from state government. In addition, for electric and hydrogen options
specifically, fleet operators expressed concern that infrastructure might not be ready to support
electric or hydrogen adoption, that there is an uncertain return on investment, and that there is a
perceived unavailability of vehicles.
We first note that significant changes have already occurred since these interviews were
conducted, including an increase in the number of HD ZEV models available in the market, and
the important incentives provided in the BIL and the IRA which provide support for
development and purchase of heavy-duty ZEVs, including reducing the costs of purchasing
ZEVs and reducing the costs of ZEV refueling infrastructure. In addition, as described in RIA
Chapter 1.6, there are several existing and planned projects from manufacturers and other entities
1872 Note that the incentives exist in the reference case and under our final standards case.
1873 The IRA battery tax credit is also expected to reduce upfront costs for purchasers, although it is a tax credit for
battery manufacturers, not purchasers. We expect vehicle manufacturers to reduce the price of their vehicles in
accordance with their ability to take advantage of this battery tax credit in order to remain competitive in the market.
1874 See Chapter 6.1.1 for further discussion on how uncertainty related to ZEVs may affect vehicles sales.
1875 As mentioned in Preamble ES.F, some manufacturers are including maintenance in leasing agreements. This
could reduce uncertainty related to new technology.
1876 Bae, Youngeun and Rindt, Craig R. and Mitra, Suman and Ritchie, Stephen G., Fleet Operator Perspectives on
Alternative Fuels for Heavy-Duty Vehicles. 2022. Available at SSRN: https://ssrn.com/abstract=4253440
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aimed at expanding public charging infrastructure for electric trucks or other commercial
vehicles. As HD ZEVs become more affordable and more represented on the roadways, we
expect uncertainty related to this technology, including uncertainty related to durability and
resale value, to wane. We acknowledge that such uncertainties, as well as other uncertainties
including infrastructure, could affect manufacturer compliance strategies and potentially lead to
compliance strategy decisions involving fewer ZEV technologies than we project in the potential
compliance pathway for these standards (including a compliance pathway that does not utilize
ZEV technologies at all), which may reduce the non-GHG emission reductions estimated in this
rule.1877 As discussed in detail in RIA Chapter 2.6 and 2.10.3, EPA has carefully analyzed the
infrastructure needs and costs to support the potential compliance pathway's technology
packages that support the MY 2027-2032 standards. Additionally, as purchasers learn more
about ZEV technologies, and as the penetration of the technologies and supporting infrastructure
in the market increases, the exposure to ZEV technologies in the real world will reduce
uncertainty related to viability or durability of the vehicles and the availability of supporting
infrastructure. As described in RIA 1.5, about 60 makes and models of HD BEVs were available
for purchase, with more product lines in some stage of early development, with the market
projected to grow to about 180 models of HD BEVs by MY 2024. In addition, companies with
large distribution needs, including UPS, FedEx, DHL, Walmart, Anheuser-Busch Co., Amazon
and PepsiCo Inc., have expressed significant interest in fleet electrification. For example,
Amazon and UPS placed orders for 10,000 BEVs in 2020, with Amazon planning to scale up to
100,000 BEV vans by 2030. In 2022, PepsiCo added their first of 100 planned Tesla Semis to its
fleet. Some fleet owners and operators, including Amazon and Walmart, are also considering
hydrogen technologies to lower fleet emissions. Though increasing penetration of HD ZEVs is
projected to continue to happen regardless of the standards, as explained in our reference case,
these standards are expected to help accelerate the process, incentivizing manufacturers to
educate purchasers on the benefits of their compliance strategy technologies, like HD ZEVs.
Another reason purchasers may not consider the full, or even a portion of the, operational cost
savings of a ZEV over a comparable ICE vehicle is if a principal-agent problem exists, causing
split incentives.1878 A principal-agent problem could exist if truck operators (agents) and truck
purchasers who are not also operators (principals) value characteristics of the trucks under
purchase consideration differently (split incentives) which could lead to differences in purchase
decisions between truck operators and truck purchasers. Characteristics may include physical
characteristics (for example noise, vibration or acceleration), cost characteristics (for example
operational costs, purchase prices, or cost of EVSE installation), or other characteristics (for
example availability of EVSE infrastructure). Such potential split incentives, or market failures,
could, for example, impact HD ZEV adoption rates if agents weigh characteristics more
associated with ICE vehicles greater than those associated with ZEV vehicles in a manner
different than represented in the analysis of the modeled compliance pathway for this rule. The
possibility of a principal-agent problem could be mitigated through measures that cause an
alignment of interests between the principal and the agent, for example, measures that lead to
sharing of the benefits and/or costs that may cause the issue. While this is a theoretical issue,
EPA is not aware of any data or analysis persuasively demonstrating if the principal-agent
1877 This is assuming that the GHG standards are being met, and assuming there are no pre- or low-buy effects.
1878 A principal-agent problem happens when there is a conflict in priorities (split incentives) between a "principal,"
or the owner of an asset, and an "agent," or the person to whom control of the asset has been delegated, such as a
manager or HD vehicle operator.
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problem significantly affects HD vehicle purchases generally, or specifically with respect to HD
ZEV purchases. However, we note that, given the commercial nature of how HD vehicles are
used and the need to minimize costs in competitive business environments, we think it is
reasonable, absent empirical evidence to the contrary, to conclude that truck purchasers are very
unlikely to ignore the significant operational cost savings associated with HD ZEVs.
Though ZEVs are being introduced in the HD market, their adoption is currently low, and
their representation in the resale market is almost non-existent.1879 There is uncertainty
surrounding the ability of the original owners to recover their original investment. In addition,
the uncertainties mentioned above for new HD ZEV buyers, including those related to payback,
durability, and infrastructure, also exist for purchasers of used ZEVs. However, some
uncertainties will likely be reduced. For example, the used ZEV market will mature more slowly
than the new ZEV market, giving time for future used ZEV owners to learn about the technology
and for the supporting infrastructure to mature. As more used ZEVs enter the market, uncertainty
related to used ZEVs, and the associated resale market, will shrink.
Potential "first-mover disadvantage" may exist in manufacturing, especially in situations
where developing, implementing, or marketing a new technology requires large initial
investment. For example, in order for someone to purchase a HD ZEV for their specific needs,
the vehicle that meets those needs must exist in the market. The first-mover disadvantage occurs
when the "first-mover" pays a higher proportion of the costs of developing, implementing, or
marketing a new technology and loses the long-term advantage when other businesses move into
that market. However, there could also be "dynamic increasing returns" to adopting new
technologies, wherein the value of a new technology may depend on how many other companies
have adopted the technology. Additionally, there can be research and development synergies
when many companies work on the same technologies at the same time, assuming there's a
reason to innovate at the same time.
Standards such as those in this rule can create conditions under which companies invest in
major innovations. As discussed in RIA Chapter 1.5, HD manufacturers are already producing
some ZEV models and investing in the development and production of additional models, and
large companies that rely on HD vehicles have already expressed an interest in purchasing HD
ZEV technology. This rule is expected to provide a meaningful signal to manufacturers to
produce more technologies with the potential to reduce large amounts of GHG emissions, like
HD ZEV models, to invest in educating purchasers on the benefits of such technologies, and to
invest in supporting infrastructure. For example, Daimler Trucks North America, Volvo Trucks,
Navistar, PACCAR, and Cummins are a few of the HD companies investing in ZEVs, including
1879 In Chapter 2.12 of the RIA, we provide a discussion and analysis of HD vehicle total cost of ownership, which
includes an estimate of residual values, though we do not distinguish by powertrain technology.
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in ZEV infrastructure, and supporting the education of ZEV purchasers. 1880>1881 We also note
that under the modeled potential compliance pathway for this rule, we project demand for
infrastructure buildout, and therefore utilities may rely on this rule as support for building out
such infrastructure.1882
To take into consideration of purchaser acceptance of BEVs and FCEVs , we used the tools
and information available to evaluate and project ZEV adoption rates in HD TRUCS, in
consideration and recognition of the various factors that may affect the adoption of technology in
the real world. We acknowledge that the data and research needed to definitively discuss what
affects whether HD buyers will adopt BEVs or FCEVs is limited.1883 Based on our consideration
of available information, we expect that, similar to the decisions made by LD vehicle EV buyers,
part of the decision on whether to purchase a BEV or FCEV over an ICE vehicle may depend on
the relative price of the vehicles, the amount to which purchasers account for fuel, and other
operating cost savings in their purchase decision, and on understanding (or perceived
understanding) of the charging or refueling infrastructure. In addition, more unique to the HD
market, we expect that understanding of the technical suitability of the vehicle to its intended
application may impact the decision of whether to purchase an HD ZEV or ICE vehicle. For
example, a long-haul Class 8 tractor will have different needs than a local delivery Class 8
tractor.
In our modeled potential compliance pathway that supports the feasibility of the standards, we
account for and consider willingness to purchase considerations in several ways (and,
correspondingly, impacts on HD ZEV adoption included in the modeled potential compliance
pathway). This includes considering uncertainty about vehicle weight, component (e.g., battery)
sizing, infrastructure availability, upfront purchaser costs, and payback for purchasers, as well as
including limitations in our analysis to phase in the final standards to provide additional time and
a slower pace of adjustment in early model years. For example, our HD TRUCS analysis applies
oversize factors for batteries to account for temperature effects, potential battery degradation and
188° Dajmier Truck North America. "Daimler Trucks North America, Portland General Electric open first-of-its-kind
heavy-duty electric truck charging site". April 21, 2021. Available online:
https://northamerica.daimlertruck.com/PressDetail/daimler-trucks-north-america-portland-general-2021-04-21.
188° v0iv0 Trucks USA. "Volvo Trucks Simplifies EV Charger Procurement with Vendor Direct Shipping
Program". September 29, 2022. Available online: https://www.volvotrucks.us/news-and-stories/press-
releases/2022/september/volvo-trucks-simplifies-ev-charger-procurement-with-vendor-direct-shipping-program.
Navistar. "Navistar and In-Charge Energy Now Offer Carbon-Neurtral Electric Vehicle Charging". Available
online: https://news.navistar.com/2021-10-25-Navistar-and-In-Charge-Energy-Now-Offer-Carbon-Neutral-Electric-
Vehicle-Charging. Paccar Parts. "Electric Vehicle Chargers". Available online:
https://www .paccarparts. com/technology/ev-chargers/..
1881 See also RIA Chapters 1.5 and 1.6 for more information on announcements from manufacturers regarding ZEVs
and infrastructure.
1882 See Comments of Edison Electric Institute EPA-HQ-OAR-2022-0985-1509 at 6 ("A HDV Phase 3 rule that
supports the continued electrification of the transportation sector and leverages the existing investment in the electric
system and the electric sector's ongoing clean energy transformation will provide both environmental benefits and
send appropriate signals to support the continued buildout of infrastructure to support increased electrification.").
1883 EPA has recently completed an in-depth, peer reviewed, study of adoption of LD BEVs. See "Literature Review
of U.S. Consumer Acceptance of New Personally Owned Light Duty Plug-in Electric Vehicles" at
https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=OTAQ&dirEntryId=353465 for more information.
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more; we sized most batteries for the 90th percentile of estimated VMT;1884 and we sized EVSE
such that vehicles' batteries could be fully recharged during the dwell time available to specific
vehicle applications. In addition, in our HD TRUCS analysis we cap the ZEV adoption rate for
each vehicle type to be no more than 70 percent for MY 2032 and no more than 20 percent in
MY 2027. For more detail on the constraints we considered and included, see Preamble Sections
II.D, II.E and II.F. In the HD TRUCS analysis, we developed a method to include consideration
of payback in assessing adoption rates of BEVs and FCEVs for the modeled potential
compliance pathway after considering methods in the literature.1885 Our payback curve, and
methods considered and explored in the formulation of the method used in this rule, are
described in RIA Chapter 2.7. As stated there, given information currently available, and our
experience with the HD vehicle industry, payback period is the most relevant metric to the HD
vehicle industry.1886 The payback schedule caps used in our model are lower in MY 2027
compared to MY 2032 to recognize additional time for the ZEV technology and infrastructure to
mature. Fleet owners and drivers will have had more exposure to ZEV technology in 2032
compared to 2027, which may work to alleviate concerns related to ZEVs (for example, concerns
of reliability) and result in a lower impression of risk of these newer technologies. In addition,
infrastructure to support ZEV technologies will have had more time to expand and mature,
further supporting increased HD ZEV adoption rates.
In summary, EPA recognizes that businesses that operate HD vehicles are under competitive
pressure to reduce operating costs, which should encourage HD vehicle buyers to identify and
rapidly adopt cost-effective technologies that reduce operating costs and the total cost of
ownership. Outlays for labor and fuel generally constitute the two largest shares of HD vehicle
operating costs, depending on the price of fuel, distance traveled, type of HD vehicle, and
commodity transported (if any), so businesses that operate HD vehicles face strong incentives to
reduce these costs. However, EPA also recognizes that there is uncertainty related to
technologies that manufacturers may adopt in their compliance strategies for this final rule, like
ZEVs, that may impact the adoption of these technologies even though they reduce operating
costs. Markets for both new and used HD vehicles may face these problems, although it is
difficult to assess empirically the degree to which they do. We expect these final Phase 3
standards as well as other factors we discussed will help overcome such barriers by incentivizing
the development of technologies and supporting infrastructure that reduce operating costs and
total cost of ownership, like ZEV technologies, and reduce uncertainties for HD vehicle
purchasers on such technologies' benefits and other potential concerns. As noted, the final rule
also sends a signal to electric utilities of demand under the modeled potential compliance
pathway, and thus provides support justifying buildout of electrification infrastructure.
1884 We designed a small number of vehicle types in HD TRUCS to refuel (with electricity or hydrogen) en-route,
sizing them such that they could reach the 90th percentile VMT with one half hour or less refueling event per day—
within a driver's required break period. We modeled the ZEV adoption rate for these vehicle types as 0 percent prior
to MY 2030, when we anticipate that sufficient en-route refueling infrastructure will be available to support these
types of vehicles.
1885 Adoption rates estimated in HD TRUCS are one of several factors considered in determining the appropriate
level of the standards. These estimated adoption rates in HD TRUCS demonstrate that the adoption rates in our
modeled potential compliance pathway are all feasible.
1886 Our assessment of total cost of ownership, shown in RIA Chapter 2.12, further supports our assessment of
payback periods.
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6.3 VMT Rebound
The "rebound effect" refers to the increase in demand for an energy service when the cost of
the energy service is reduced due to efficiency improvements.1887'1888'1889 In the context of HD
vehicles, this has been interpreted as more intensive vehicle use, resulting in an increase in liquid
fuel consumption, in response to increased ICE vehicle fuel efficiency. Although much of this
possible vehicle use increase is likely to take the form of an increase in the number of miles
vehicles are driven, it can also take the form of increases in the loaded operating weight of a
vehicle or altering routes and schedules in response to improved fuel efficiency of the HD ICE
vehicle. More intensive use of those HD ICE vehicles consumes fuel and generates emissions,
which reduces fuel savings and avoided emissions that would otherwise be expected to result
from increasing fuel efficiency of HD ICE vehicles.
Unlike the LD vehicle rebound effect, there is little published literature on the HD vehicle
rebound effect, and all of it focuses on increased ICE fuel efficiency. Winebrake et al. (2012)
suggest that vocational trucks and tractor trailers have a rebound effect of essentially zero. Leard
et al. (2015) estimate that tractor trailers have a rebound effect of 30 percent, while vocational
vehicles have a 10 percent rebound rate.1890 Patwary et al. (2021) estimated that the average
rebound effect of the U.S. road freight sector is between about 7 to 9 percent, though their study
indicated that rebound has increased over time.1891 This is slightly smaller than the value found
by Leard et al. (2015) for the similar sector of tractors.
In the HD GHG Phase 2 final rule RIA, we estimated a 5 percent rebound effect for
vocational trucks and for tractors being applied to ICE vehicles. These estimates were
determined using the most recent studies in HD rebound at the time, as well as in response to
comments submitted on the proposed HD GHG Phase 2 rule. As mentioned above, all the current
research focuses on VMT rebound of HD ICE vehicles. With respect to ZEVs, specifically, we
do not have data that operational cost savings of switching from an ICE vehicle to a ZEV will
affect the VMT of that vehicle, nor do we have data on how changing fuel prices might affect
VMT of ZEVs over time. Given the increasing penetration of ZEVs in the HD fleet, even in the
reference case, as well as the wide range of effects discussed in the literature, we do not believe
the rebound estimates in literature cited here are appropriate for use in our analysis. In addition,
the majority of research on VMT rebound has been performed in the light-duty vehicle context.
The factors influencing light-duty and heavy-duty VMT are generally different. For example,
light-duty VMT is generally related to personal considerations, including costs and benefits
associated with driving, while HD VMT is more a function of profits or impacts on labor. It is
1887 Winebrake, J.J., Green, E.H., Comer, B., Corbett, J.J., Froman, S., 2012. Estimating the direct rebound effect for
on-road freight transportation. Energy Policy 48, 252-259.
1888 Greene, D.L., Kahn, J.R., Gibson, R.C., 1999, "Fuel economy rebound effect for U.S. household vehicles," The
Energy Journal, 20.
i 889 For a discussion of the wide range of definitions found in the literature, see Appendix D: Discrepancy in
Rebound Effect Definitions, in EERA (2014), "Research to Inform Analysis of the Heavy-Duty vehicle Rebound
Effect," and Excerpts of Draft Final Report of Phase 1 under EPA contract EP-C-13-025. (Docket ID: EPA-HQ-
OAR-2014-0827). See also Greening, L.A., Greene, D.L., Difiglio, C., 2000, "Energy efficiency and consumption
— the rebound effect — a survey," Energy Policy, 28, 389-401.
1890 Leard, B., Linn, J., McConnell, V., and Raich, W. (2015). Fuel Costs, Economic Activity, and the Rebound
Effect for Heavy-Duty Trucks. Resources For the Future Discussion Paper, 14-43.
1891 Patwary, A. L., Yu, T. E., English, B.C., Hughes, D. W., and Cho, S. H. (2021). Estimating the rebound effect of
the US road freight transport. Transportation Research Record, 2675(6), 165-174.
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also important to note that even if there is an increase in VMT in new vehicles, this may be offset
by a decrease in VMT on older vehicles. This may occur if operational cost savings on newer
vehicles due to this rule lead operators to shift VMT to these newer, more efficient vehicles.
As in the proposal, we are not estimating any VMT rebound due to this rule (or, put another
way, we estimate the effect is zero). If either ICE vehicles or ZEVs instead do exhibit some
rebound effect, our approach would include slight overestimates of the emission reductions
associated with these standards, as well as slight underestimates of additional traffic congestions
and collisions. However, there may also be reductions in the severity of collisions if the rebound
effect leads to lighter loads, as these lighter trucks would be less likely to cause an injury or
fatality in a collision.1892 Also, if rebound occurs, there may be some increase in non-GHG
emissions and in brake and tire wear, but also an increase in benefits associated with increased
vehicle use (for example, increased economic activity associated with the services provided by
those vehicles), as well as positive impacts on employment. However, possible rebound may be
reduced if owner/operators use those operational cost savings in other ways, for example to
reduce their payback period. Also, as noted in the Winebrake at al. (2012) study, possible
rebound impacts are likely reduced by adjustments in other operational costs such as labor, and
the nature of the freight industry as an input to a larger supply chain system.
6.4 Employment Impacts
This section discusses potential employment impacts of the regulation. If the U.S. economy is
at full employment, we expect that even a large-scale environmental regulation is unlikely to
have a noticeable impact on aggregate net employment. Instead, labor would primarily be
reallocated from one productive use to another, as workers transition away from jobs that are less
environmentally protective and towards jobs that are more environmentally protective. Affected
sectors may nevertheless experience transitory effects as workers change jobs. Some workers
may retrain or relocate in anticipation of new requirements or require time to search for new
jobs, while shortages in some sectors or regions could bid up wages to attract workers. These
adjustment costs can lead to local labor disruptions. Even if the net change in the national
workforce is small, localized reductions in employment may adversely impact individuals and
communities just as localized increases may have positive impacts. If the economy is operating
at less than full employment, economic theory does not clearly indicate the direction or
magnitude of the net impact of environmental regulation on employment; it could cause either a
short-run net increase or short-run net decrease as discussed further below.
6.4.1 Background and Literature
Economic theory of labor demand indicates that employers affected by environmental
regulation may change their demand for different types of labor in different ways. They may
increase their demand for some types, decrease demand for other types, or maintain demand for
still other types. The uncertain direction of labor impacts is due to the different ways regulations
affect labor demand. A variety of conditions can affect employment impacts of environmental
regulation, including baseline labor market conditions, employer and worker characteristics,
industry, and region. In general, the employment effects of environmental regulation are difficult
to disentangle from other economic changes, including, for example, the impacts of the
1892 Nehiba, C., 2020. Taxed to death? Freight truck collision externalities and diesel taxes, Regional Science and Urban
Economics, Volume 85.
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coronavirus pandemic on labor markets, the general state of the macroeconomy, as well as a
myriad of business decisions that affect employment. These changes have variable employment
impacts, both over time and across regions and industries. In light of these difficulties, we look
to economic theory to provide a constructive framework for approaching these assessments and
for better understanding the inherent complexities in such assessments.
In this chapter, we describe three ways employment at the firm level might be affected by
changes in a firm's production costs due to environmental regulation: a factor-shift effect, in
which post-regulation production technologies may have different labor intensities than their pre-
regulation counterparts; a demand effect, caused by higher production costs increasing market
prices and decreasing demand; and a cost effect, caused by additional environmental protection
costs leading regulated firms to increase their use of inputs, including labor, to produce the same
level of output. These effects are outlined in a paper by Morgenstern et al. (2002), which
provides the theoretical foundation for EPA's analysis of the impacts of this regulation on
labor.1893 Due to data limitations, EPA is not quantifying the impacts of the final regulation on
firm-level employment for affected companies, although we acknowledge these potential
impacts. Instead, for our analysis of the potential compliance pathway, we describe possible
effects on employment due to utilization of ZEV technologies, and then discuss factor-shift,
demand, and cost employment effects for the regulated sector at the industry level.
Additional papers approach employment effects through similar frameworks. Berman and Bui
(2001)1894 model two components that drive changes in firm-level labor demand: output effects
and substitution effects.1895 Deschenes (20 1 8)1896 describes environmental regulations as
requiring additional capital equipment for pollution abatement that does not increase labor
productivity. For an overview of the neoclassical theory of production and factor demand, see
Chapter 9 of Layard and Walters' Microeconomic Theory.1897 Ehrenberg and Smith (2000)1898
describe how, at the industry level, labor demand is more likely to be responsive to regulatory
costs if: (1) the elasticity of labor demand is high relative to the elasticity of labor supply, and (2)
labor costs are a large share of total production costs.
Arrow, Cropper, et al. (1996)18" state that, in the long run, environmental regulation is
expected to cause a shift of employment among employers rather than affect the general
employment level. Even if they are mitigated by long-run market adjustments to full
1893 Morgenstern, R., Pizer, W., & Shih, J.-S. (2002). Jobs Versus the Environment:" An Industry-Level Perspective.
Journal of Environmental Econometrics and Management, 43, 412-436.
1894 Berman, E., & Bui, L. (2001). Environmental Regulation and Labor Demand: Evidence from the South Coast
Air Basin. Journal of Public Economics, 79(2), 265-295
1895 Berman and Bui (2001) also discuss a third component, the impact of regulation on factor prices, but conclude
that this effect is unlikely to be important for large competitive factor markets, such as labor and capital.
1896 Deschenes, O. (2018). Balancing the Benefits of Environmental Regulations for Everyone and the Costs to
Workers adn Firms. IZA World of Labor, 22v2. Retrieved from
https://wol.iza.org/uploads/articles/458/pdfs/environmental-regulations-and-labor-markets.pdf
1897 Layard, R., & Walters, A. (1978). Microeconomic Theory. London: McGraw-Hill.
1898 Ehrenberg, R., & Smith, R. (2000). Modern Labor Economics: Theory and Public Policy. Addison Wesley
Longman, Inc.
1899 Arrow, R., Cropper, M., Eads, G., Hahn, R., Lave, L., Noll, R., Stavins, R. (1996). Is There a Role for Benefit-
Cost Analysis in Environmental, Health, and Safety Regulation? Science, 272(5259), 221-222
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employment, many regulatory actions have transitional effects in the short run.1900'1901 These
movements of workers in and out of jobs in response to environmental regulation are potentially
important distributional impacts of interest to policy makers. Of particular concern are
transitional job losses experienced by workers operating in declining industries, exhibiting low
migration rates, or living in communities or regions where unemployment rates are high.
Workers affected by changes in labor demand due to regulation may experience a variety of
impacts including job gains or involuntary job loss and unemployment. Compliance with
environmental regulation can result in increased demand for the inputs or factors (including
labor) used in the production of environmental protection. However, the regulated sector
generally relies on revenues generated by their other market outputs to cover the costs of
supplying increased environmental quality, which can lead to reduced demand for labor and
other factors of production used to produce the market output. Workforce adjustments in
response to decreases in labor demand can be costly to firms as well as workers, so employers
may choose to adjust their workforce over time through natural attrition or reduced hiring, rather
than incur costs associated with job separations (see, for instance, Curtis (2018)1902 and Hafstead
and Williams (2018)1903).
As suggested in this discussion, the overall employment effects of environmental regulation
are difficult to estimate. Estimation is difficult due to the multitude of small changes that occur
in different sectors related to the regulated industry, both upstream and downstream, or in sectors
producing substitute or complimentary products. In the following sections, we qualitatively
discuss potential impacts of the rule on the vehicle manufacturing, battery production, and
charging and refueling infrastructure sectors due to the utilization of ZEV technologies under the
potential compliance pathway, and due to the factor-shift, demand and cost effects. Then, we
briefly discuss potential impacts on additional sectors such as the retail firms selling products
transported by HD trucks and the petroleum refining industry.
6.4.2 Potential Employment Impacts of the Final Rule
Manufacturing vehicles that include GHG-reducing technology may lead to employment
effects. For example, should manufacturers choose to comply by using ZEV technologies as part
of their compliance strategies, the increasing adoption of BEVs and FCEVs in the market is
likely to affect both the number and the nature of employment in the HD manufacturing and
related sectors, such as providers of battery charging and refueling infrastructure. Over time, as
ZEVs become a greater portion of the new HD vehicle fleet, the kinds of jobs in HD
manufacturing would be expected to change. For instance, there will be no need for engine and
exhaust system assembly for BEVs, while many assembly tasks will instead involve electrical
rather than mechanical fitting. Batteries represent a significant portion of the manufacturing
content of an electrified vehicle, and some automakers are likely to purchase the cells, if not pre-
1900 Smith, V. (2015). Should Benefit-Cost Methods Take Account of High Unemployment? Review of
Environmental Economics and Policy, 9(2), 165-178.
1901 U.S. OMB. (2015). 2015 Report to Congress on the Benefits and Costs of Federal Regulations and Agency
Compliance with the Unfunded Mandates Reform Act. Retrieved from
https://obamawhitehouse.archives.gov/sites/default/files/omb/inforeg/2015_cb/2015-cost-benefit-repot.pdf/
1902 Curtis, M. (2018). Who Loses Under Cap-and-Trade Programs? The Labor Market Effects of the NOx Budget
Trading Program. The Review of Economics and Statistics, 100(1), 151-166.
1903 Hafstead, M., & Williams III, R. (2018). Unemployment and Environmental Regulation in General Equilibrium.
Journal of Public Economics, 160, 50-65.
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assembled modules or packs, from suppliers whose employment will thereby be affected.
Employment will be affected in building and maintaining battery charging or fuel cell refueling
infrastructure needed to support the ever-increasing number of ZEVs on the road, as well as in
the maintenance and operation of distribution infrastructure for fossil fuels. For much of these
effects, there is not enough data to quantitatively assess how employment might change as a
function of the increased electrification expected to result under the standards.
A recent report from the Seattle Jobs Initiative identified sectors most strongly associated with
LD ICE vehicle and BEV production, where electrical equipment and manufacturing and other
electrical equipment and component manufacturing were said to be associated with LD BEV
production (including batteries), and motor vehicle manufacturing, motor vehicle body and
trailer manufacturing, and motor vehicle parts manufacturing were associated with both LD BEV
and ICE vehicle production.1904 These sectors also include HD vehicle manufacturing. The
Employment Requirements Matrix (ERM) provided by the U.S. Bureau of Labor Statistics (BLS)
provides direct estimates of employees per $1 million in expenditures for a total of 202
aggregated sectors that roughly correspond to the 4-digit NAICS code level, and provides data
from 1997 through 2022.1905 These estimates are averages, covering all the activities in these
sectors and may not be representative of the labor effects when expenditures are required for
specific activities, or when manufacturing processes change due to compliance activities in such
a way that labor intensity changes. For instance, the ratio of workers to production cost for the
motor vehicle body and trailer manufacturing sector represents this ratio for all motor vehicle
body and trailer manufacturing activities, and not just for production processes related to
emission reductions compliance activities. In addition, these estimates do not include changes in
sectors that supply these sectors, such as steel or electronics producers. However, examining that
data over time suggests general employment trends in light- and heavy-duty manufacturing.
Using this historical data, we can see that the workers per $1 million in sales for all six of these
sectors has, generally, decreased over time. Over time, the amount of labor needed in the motor
vehicle industry has changed: automation and improved production methods have generally led
to significant productivity increases. The BLS ERM, for instance, provides estimates that, in
2002, about 0.95 workers in the Motor Vehicle Manufacturing sector was needed per $1 million,
(in 2022$), while, for 2022 this figure had decreased to only 0.76 workers per $1 million
(2022$). Though two sectors mainly associated with the production of components that go into
BEVs and the battery electric portion of PHEV manufacturing, electrical equipment
manufacturing and other electrical equipment and component manufacturing, show an increase
in recent years.
Figure 6-1 shows the estimates of employment per $1 million of expenditure for each sector
for each data source over the past twenty years, adjusted to 2022 dollars using the U.S. Bureau of
Economic Analysis Gross Domestic Product Implicit Price Deflator retrieved from the Federal
1904 Seattle Jobs Initiative. (2020). Amping Up Electric Vehicle Manufacturing in the PNW: Opportunities for
Business, Workforce, and Education. Retrieved from
https://www.seattle.gov/Documents/Departments/OSE/ClimateDocs/TE/EV%20Field%20in%200R%20and%20W
A_February20.pdf
1905 Bureau of Labor Statistics. (2023). Real Domestic Employment Requirements. Retrieved January 2023, from
http://www.bls.gov/emp/ep_data_emp_requirements.htm
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Reserve Bank of St. Louis. The values are adjusted to remove effects of imports through the use
of a ratio of domestic production to domestic sales of 0.81.1906
8.000
7.000
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ra
cn
c 5.000
P 4.000
V*
2 3.000
| 2.000
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0.000
Year
— ~ — Semiconductor and other electronic component manufacturing
— • — Electrical equipment manufacturing
— •— Other electrical equipment and component manufacturing
Motor vehicle manufacturing
» Motor vehicle body and trailer manufacturing
9 Motorvehicle parts manufacturing
Figure 6-1 Workers per million dollars in sales, adjusted for domestic production.
Though most of the research on employment effects associated with a market shift from ICE
vehicles to ZEVs is focused on the light-duty market, many of the same ideas transfer to the HD
market as well. Generally, research is not consistent on the expected direction or magnitude of
change in employment as new ICE vehicle sales are replaced with new BEV or fuel cell vehicle
sales. The BlueGreen Alliance states that although battery electric vehicles have fewer parts than
their ICE counterparts, there is potential for job growth in electric vehicle component
manufacturing, including batteries, electric motors, regenerative braking systems and
semiconductors, and manufacturing those components in the US can lead to an increase in
jobs.1907 They go on to state that if the U.S. does not become a major producer for these
components, there is risk of job loss. EDF also reports that the job growth and investment in the
EV sector that has been seen over the last eight years is expected to continue, with new factories
19116 To estimate the proportion of domestic production affected by the change in sales, we use data from WardsAuto
for total car and truck production in the U.S. compared to total car and truck sales in the U.S. Over the period 2012-
2022, the proportion averages 84 percent. From 2017-2022, the proportion average is slightly lower, at 81 percent.
19117 BlueGreen Alliance. (2021). Backgrounder: EVs are Coming. Will They be Made in the USA? Retrieved from
https://www.bluegreenalliance.org/wp-content/uploads/2021/04/Backgrounder-EVs-Are-Coming.-Will-They-Be-
Made-in-the-U S A-vFINAL .pdf
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741
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or production lines for EVs, batteries, components and chargers supporting more than 125,000
jobs being announced across 26 states.1908 In updates reported to EPA in comments on the
proposed rule, EDF reports that more than 70,000 jobs have been created in U.S. battery and
battery component production since 2015.
In anticipation of shifts in the skills necessary for workers in the automobile industry due to a
greater share of electric vehicles, the International Union, United Automobile, Aerospace and
Agricultural Implement Workers of America (UAW) states that re-training programs will be
needed to prepare workers that might be displaced by the shift to the new technology.1909 Though
the UAW commented that a slower increase in the penetration of EVs in the market than what
we estimated in our proposal will better support employees in auto manufacturing and the
supporting industries, they are also working to support employees as this shift in manufacturing
is being made, as evidenced by the recent UAW autoworkers strike, with one goal being to
support to employees working on EVs.1910 Volkswagen states that labor requirements for ICE
vehicles are about 70% higher than their electric counterpart, but these changes in employment
intensities in the manufacturing of the vehicles can be offset by shifting to the production of new
components, for example batteries or battery cells.1911 Research from the Seattle Jobs initiative
indicates that employment in a collection of sectors related to both battery electric and ICE
vehicle manufacturing is expected to grow slightly through 2029.1912 Though most of these
statements are specifically referring to light-duty vehicles, they hold true for the HD market as
well.
Climate Nexus also indicates that increasing penetrations of electric vehicles will lead to a net
increase in jobs, a claim that is partially supported by the rising investment in batteries, vehicle
manufacturing and charging stations.1913 The expected investment mentioned by Climate Nexus
is also supported by recent federal investment which will allow for increased investment along
the vehicle supply chain, including domestic critical minerals, materials processing, battery
manufacturing, charging infrastructure, and vehicle assembly and vehicle component
manufacturing, both in the LD and HD markets.1914 This investment includes the BIL, the
1908 EDF. (2023). New climate laws drive boom in electric vehicle jobs. Retrieved November 1, 2023 from
https://vitalsigns.edf.org/story/new-climate-laws-drive-boom-electric-vehicle-jobs
1909 UAW. (2020). Taking the High Road: Strategies for a Fair EV Future. Retrieved from https://uaw.org/wp-
content/uploads/2019/07/190416-EV-White-Paper-REVISED-January-2020-Final.pdf
1910 Olander, O., and Niedzwiadek, N. (2023). What the pending UAW-Big 3 deals mean for workers, Biden and the
economy. Politico. Retrieved November 3, 2023 from https://www.politico.com/news/2023/10/30/uaw-big-3-labor-
biden-economy-00124368
1911 Herrmenn, F., Beinhauer, W., Borrmann, D., Hertwig, M., Mack, J., Potinecke, T.,. . . Rally, P. (2020).
Employment 2030: Effect of Electric Mobility and Digitalisation on the Quality ond Quantity of Employment at
Volkswagen. Fraunhofer Institute for Industrial Engineering IAO. Retrieved from
https://www.volkswagenag.com/presence/stories/2020/12/frauenhofer-studie/6095_EMDI_VW_Summary_um.pdf
1912 Seattle Jobs Initiative. (2020). Amping Up Electric Vehicle Manufacturing in the PNW: Opportunities for
Business, Workforce, and Education. Retrieved from
https://www.seattle.gov/Documents/Departments/OSE/ClimateDocs/TE/EV%20Field%20in%200R%20and%20W
A_February20.pdf
1913 Climate Nexus. (2022). Job Impacts From the Shift to Electric Cars and Trucks. Retrieved December 2022,
from https://climatenexus.org/climate-issues/energy/ev-job-impacts/
1914 Inflation Reduction Act of 2022, H.R. 5376 (117th Cong., 2nd sess. 2022).
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CHIPS Act,1915 and the IRA, which are expected to create domestic employment opportunities
along the full automotive sector supply chain, from components and equipment manufacturing
and processing to final assembly, as well as incentivize the development of reliable EV battery
supply chains both for BEVs and PHEVs.1916 The IRA is expected to impact domestic
employment through conditions on eligibility for purchase incentives and battery manufacturing
incentives. These conditions include contingencies for domestic assembly, domestic critical
materials production, and domestic battery manufacturing. As an example, a new joint venture
between Daimler Trucks, Cummins, and PACCAR recently announced a new battery factory to
be built in the U.S. to manufacture cells and packs initially focusing on heavy-duty and industrial
applications was announced in September 2023.1917 The BlueGreen Alliance and the Political
Economy Research Institute estimate that the IRA will create over 9 million jobs over the next
decade, with about 400,000 of those jobs being attributed directly to the IRA's battery and fuel
cell vehicle provisions. 1918>1919 in addition, the IRA is expected to lead to increased demand in
ZEVs through tax credits for purchasers of ZEVs. However, even with increases in employment
in component production and new domestic jobs related to ZEVs, these shifts in production of
HD vehicles may negatively affect workers currently employed in production of ICE vehicles.
As discussed in RTC Section 19.6, there are many existing and planned projects focused on
training new and existing employees in fields related to green jobs, and specifically green jobs
associated with electric vehicle production, maintenance and repair, and the associated charging
infrastructure. This includes work by the Joint Office of Energy and Transportation (JOET),
created by the BIL, which supports efforts related to deploying infrastructure, chargers, and zero
emission transit and school buses.1920 One example of a project from the JOET is the Ride and
Drive grant program, which targets investments in EV charging resiliency, community-driven
workforce development and EV charging performance and reliability. Another example is the
Battery Workforce Initiative established by the Department of Energy (DOE) in coordination
with the Department of Labor (DOL), AFL-CIO, and other organizations with the goal of
1915 The CHIPS Act is the Creating Helpful Incentives to Produce Semiconductors and Science Act and was signed
into law on August 9, 2022. It is designed to strengthen supply chains, domestic manufacturing, and national
security. More information can be found at https://www.whitehouse.gov/briefing-room/statements-
releases/2022/08/09/fact-sheet-chips-and-science-act-will-lower-costs-create-jobs-strengthen-supply-chains-and-
counter-china/.
1916 More information on how these acts are expected to aid employment growth and create opportunities for growth
along the supply chain can be found in the January, 2023 White House publication "Building a Clean Energy
Economy: A Guidebook to the Inflation Reduction Act's Investments in Clean Energy and Climate Action." found
online at https://www.whitehouse.gov/wp-content/uploads/2022/12/Inflation-Reduction-Act-Guidebook.pdf
1917 Daimler Trucks North America. "Accelera by Cummins, Daimler Truck and PACCAR form a joint venture to
advance battery cell production in the United States." September 6, 2023. Available online:
https://media.daimlertruck.com/marsMediaSite/en/instance/ko/Accelera-by-Cummins-Daimler-Truck-and-
PACCAR-form-a-joint-venture-to-advance-battery-cell-production-in-the-United-States.xhtml?oid=52385590 (last
accessed October 23, 2023).
1918 Note that these are not all net new employment and reflects where workers may be hired away from other jobs.
As the labor market gets tighter and the economy is closer to full employment, there will be a greater number of
employees shifting from one job to another.
1919 Political Economy Research Institute. (2022). Job Creation Estimates Through Proposed Inflation Reduction
Act. University of Massachusetts Amherst. Retrieved from https://www.bluegreenalliance.org/site/9-million-good-
jobs-from-climate-action-the-inflation-reduction-act/
1920 More information on these programs, and other programs, can be found in the memo "Labor/Employment
Initiatives in the Battery/Vehicle Electrification Space" from the Employment and Training Administration (ETA) at
DOL to Elizabeth Miller, located in the docket for this rule.
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accelerating the development of high-quality training. DOL has also established the Building
Pathways to Infrastructure Jobs Grant Program, which support worker-centered sector strategy
training programs. DOL also provides grants to help community colleges provide skilled
pathways to good jobs in the transportation and clean energy sectors. DOL is also providing
technical assistance to the Southeast EV Collaborative, which is made up of collection of state
workforce agencies in the southeast region of the U.S. focused on identifying opportunities to
work together to provide equitable access to good jobs across the region.
6.4.3 The Factor-Shift Effect
The factor-shift effect refers to employment changes due to changes in labor intensity of
production resulting from compliance activities. The final standards do not mandate the use of a
specific technology, and EPA anticipates that a compliant fleet under the standards will include a
diverse range of technologies including ICE vehicle and ZEV technologies. A factor shift effect
of this rule might occur if this regulation affects the labor intensity of production of ICE
vehicles. It may also occur if a ZEV replaces an ICE vehicle (holding total sales constant). We
do not have data on how the regulation might affect labor intensity of production within ICE
vehicle production. ZEVs and ICE vehicles require different inputs and have different costs of
powertrain production, though there are many common parts as well. There is little research on
the relative labor intensity needs of producing a HD ICE vehicle and producing a comparable
HD ZEV. Though there are some news articles and research from the light-duty motor vehicle
market, they do not provide a clear indication of the relationship between employment needs for
ZEVs and ICE vehicles. Some studies find that LD BEVs are less complex, requiring fewer
person-hours to assemble than a comparable ICE vehicle.1921 Others find that there is not a
significant difference in the employment needed to produce LD ICE vehicles when compared to
BEVs.
EPA worked with a research group, FEV, to produce a peer-reviewed tear-down study of a
BEV (Volkswagen ID.4) to its comparable ICE vehicle counterpart (Volkswagen Tiguan).1922
Included in this study are estimates of labor intensity needed to produce each vehicle under three
different assumptions of vertical integration of manufacturing scenarios ranging from a scenario
where most of the assemblies and components are sourced from outside suppliers to a scenario
where most of the assemblies and components are assembled in house. Under the low and
moderate levels of vertical integration, results indicate that assembly time of the BEV at the plant
is reduced compared to assembly time of the ICE vehicle.1923 Under a scenario of high vertical
integration, which includes the BEV battery assembly, results show an increase in time needed to
assemble the BEV. When powertrain systems are ignored (battery, drive units, transmission, and
engine assembly), the BEV requires more time to assemble under all three vertical integration
scenarios. The results indicate that the largest difference in assembly comes from the building of
the battery pack assembly. When the battery cells are built in-house, the BEV will require more
labor hours to build. Though this research, along with the other studies mentioned above, focus
1921 Barrett, Jim and Josh Bivens. "The stakes for workers in how policymakers manage the coming shift to all-
electric vehicles". Economic Policy Institute. September 22, 2021. Available online:
https://www.epi.org/publication/ev-policy-workers/.
1922 See RIA Chapter 2.5.2.2.3 for more information.
1923 In the FEV report, "assembly time" is the time (in hours) it takes to assemble the vehicle from the component
parts.
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on LD electrification, it is likely the same principles apply to the manufacturing of electric HD
vehicles.
What is not discussed in this research is that battery cells must be built, regardless of where
that occurs. As described above, and in Section II.D of the Preamble, battery plants are being
planned and built in the U.S., with support from the IRA, BIL and CHIPs. Though we have more
information today on differences in the time it takes to build an ICE vehicle and a comparable
BEV or PHEV, we do not have enough information to estimate a factor-shift effect of the final
rule. We do not know how OEMs will be (and are) manufacturing their vehicles, or what this
will look like in several years as the MY 2027 and later standards become effective and the
projected share of electric vehicles being produced and sold increases. Nor do we have
information on labor needs of other low or zero-emission heavy-duty vehicles compared to
internal combustion gas or diesel powertrain vehicles. We can say, generally, that the study
described above indicates that if production of electric vehicles and their power supplies take
place in the U.S. at the same rates as ICE vehicles, we do not expect employment in vehicle
production to fall due to increasing penetration of HD electric vehicles, and it may likely
increase. As production in the related sectors of battery production and the construction of
charging and refueling stations is ramped up, their labor intensities may increase or decrease
relative to the reference case scenario. Given the current lack of data and inconsistency in the
existing literature, we are unable to estimate a quantitative factor-shift effect as a function of this
rule.
6.4.4 The Demand Effect
The demand effect refers to potential employment changes due to changes in new HD vehicle
sales. In general, if HD ICE vehicle sales increase, keeping the share of ZEVs in the new HD
vehicle fleet constant, more people would be needed to assemble trucks and the components used
to manufacturer them. On the other hand, if HD ZEV sales increase, we expect more people
would be needed to assemble ZEVs and their components, including batteries. If ZEVs and ICE
vehicles have different labor intensities of production, the relative change in ZEV and ICE sales
would impact the demand effect on employment. If, for example, the ZEV sales increased
relative to ICE vehicles, the increase in employment would depend on the relative labor
intensities. Additionally, short-term effects might be seen if pre- or low-buy were to occur,
depending on the magnitude of those effects (as discussed above). If they are of small
magnitudes, as expected, turnover of workers might not be affected. At higher magnitudes, if
pre-buy occurs, HD vehicle sales may increase temporarily, leading to temporary increases in
employment in the related manufacturing sectors. If low-buy occurs, there may be temporary
decreases in employment in the related manufacturing sectors. However, as noted above, EPA
does not expect significant pre-buy or low-buy resulting from this rule. In addition, as noted in
RIA Chapter 6.1, we do not anticipate much mode or class shift in HD market affected by this
rule, which also supports a minimal demand effect on employment.
6.4.5 The Cost Effect
The cost effect on employment refers to the impact on labor due to increased costs of
adopting technologies needed for vehicles to meet new emission standards, with the condition
that other factors (output and factor intensities) are held constant. In the HD ICE vehicle
manufacturing sector, if firms invest in lower-emitting HD ICE vehicles, there might be labor
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used to implement those technologies. For firms producing ZEVs, we do not expect the rule to
require additional compliance activities, as such vehicles by definition have zero tailpipe
emissions.1924 In addition, the standards do not mandate the use of a specific technology and
EPA anticipates that a compliant fleet under the standards will include a diverse range of
technologies including ICE and ZEV technologies. Under the additional compliance pathways
projected for this final rule that include only technology adoption in ICE vehicles, we expect
there could be some increase in employment related to implementing these ICE technologies.
However, the level of employment due to implementing new ICE technology as result of this
rule will depend on the relative rate of the adoption of the technology.
6.4.6 Overall Effects
In conclusion, the overall effect of the rule on HD manufacturing employment depends on the
relative magnitude of factor-shift, cost, and demand effects. Due to a lack of data, we are not
able to estimate quantitative employment effects from this rule on HD manufacturing. The
qualitative discussion above suggests that the direction of impacts could potentially be positive
or negative. If HD vehicle production shifts from HD ICE to HD ZEV, there may be negative
impacts on workers currently employed in ICE production. However, looking more broadly and
including consideration of employment impacts on battery manufacturing and battery and
refueling infrastructure, Climate Nexus indicates that increasing penetrations of electric vehicles
will lead to a net increase in jobs, as described in Chapter 6.4.2. This is also supported by recent
federal investment which will allow for increased investment along the vehicle supply chain,
including domestic battery manufacturing, charging infrastructure, and vehicle manufacturing.
The BIL was signed in November 2021 and provides over $24 billion in investment in electric
vehicle chargers, critical minerals, and components needed by domestic manufacturers of EV
batteries and for clean transit and school buses.1925 The CHIPS Act, signed in August 2022,
invests in expanding America's manufacturing capacity for the semiconductors used in electric
vehicles and chargers.1926
We note that employment impacts may be felt outside of the U.S., though this depends on
many factors, including firm-level decisions, macroeconomic factors in different locations,
geographic-based specializations, and more. We also note that, as discussed in 6.1.4, the final
standards are not expected to provide incentives for manufacturers to shift between domestic and
foreign production. Furthermore, the IRA provides incentives for producers to expand domestic
manufacturing of BEVs and domestic sourcing of components and critical minerals needed to
produce them.1927 The IRA also provides incentives for consumers to purchase both new and
used ZEVs. These pieces of legislation are expected to create domestic employment
opportunities along the full automotive sector supply chain, from components and equipment
manufacturing and processing to final assembly, as well as incentivize the development of
1924 We note that there may be indirect impacts, for example through battery durability monitoring or warranty
requirements. See Preamble Section III.B for more information on these requirements.
1925 The Bipartisan Infrastructure Law is officially titled the Infrastructure Investment and Jobs Act. More
information can be found at https://www.fhwa.dot.gov/bipartisan-infrastructure-law/
1926 The CHIPS and Science Act was signed by President Biden in August, 2022 to boost investment in, and
manufacturing of, semiconductors in the U.S. The fact sheet can be found at https://www.whitehouse.gov/briefing-
room/statements-releases/2022/08/09/fact-sheet-chips-and-science-act-will-lower-costs-create-jobs-strengthen-
supply-chains-and-counter-china/
1927 Inflation Reduction Act of 2022, H.R. 5376 (117th Cong., 2nd sess. 2022).
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reliable EV battery supply chains.1928 Importantly, domestic employment is expected to be
positively impacted due to the domestic assembly, production and manufacturing conditions on
eligibility for purchase incentives and battery manufacturing incentives in the IRA. Estimates
from the BlueGreen Alliance and the Political Economy Research Institute state that the IRA
could lead to over 9 million jobs over the next decade, about 400,000 of which are attributed
directly to the IRA's battery and fuel cell vehicle provisions.1929
6.4.7 Employment in Additional Related Sectors
As the share of ZEVs in the HD market increases under the potential compliance pathway, we
also expect effects on employment in the associated BEV charging and hydrogen refueling
infrastructure industries, described in RIA Chapters 1.6 and 1.8. This can happen through many
avenues, including increased demand for batteries, and therefore increased employment needs,
through greater demand for charging and fueling infrastructure to support more ZEVs, leading to
more private and public charging facilities being constructed, or through greater use of existing
facilities, which can lead to increased maintenance needs for those facilities. For example, as
described in RIA Chapter 2.10.3, we estimated the total number of EVSE ports that will be
required to support the depot-charged BEVs in the technology packages developed to support the
MY 2027-2032 standards. We find about 520,000 EVSE ports will be needed at depots across
all six model years. This increased demand in EVSE will increase the employment in this sector.
Employment related to constructing and maintaining these facilities is expected to increase.
Though we received comments with concerns that there are not enough qualified technicians to
support the infrastructure needs estimated as a function of this rule under the potential
compliance pathway, we expect this to be a gradual increase, with more technicians being trained
over time. If there is a shortage of technicians in this sector, economic theory suggests that as
demand for technicians in this sector increases, employment in the industry may become more
attractive (either due to higher wages because of the rarity of the skill set, more opportunities due
to high demand for the skill set, or both), and the number of workers willing to train, and
companies willing to invest in those workers, is expected to increase. Also, as described
elsewhere in this chapter, Federal actions, as well as projects through federal agencies and other
groups have already been and are expected to continue to support and expand training for
employees in this sector. See RIA Chapters 1.3.2 and 1.6.2 (along with RTC Section 6) for a
summary of planned and ongoing charging infrastructure investments.
EPA expects possible employment impacts on additional downstream and upstream sectors
from the shifts in HD vehicle manufacturing due to this rule. With respect to the potential for
downstream effects, this action could provide some positive impacts on the supply of drivers in
the heavy-duty trucking industry. As discussed in Preamble Section IV, under the potential
compliance pathway the reduction in fuel costs from purchasing a ZEV instead of an ICE vehicle
is expected to not only reduce operating costs for ZEV owners and operators, compared to an
ICE vehicle, but may also provide additional incentives to purchase a HD ZEV over a HD ICE
1928 More information on how these Acts are expected to aid employment growth and create opportunities for growth
along the supply chain can be found in the January 2023 White House publication "Building a Clean Energy
Economy: A Guidebook to the Inflation Reduction Act's Investments in Clean Energy and Climate Action." found
online at https://www.whitehouse.gov/wp-content/uploads/2022/12/Inflation-Reduction-Act-Guidebook.pdf
1929 Political Economy Research Institute. (2022). Job Creation Estimates Through Proposed Inflation Reduction
Act. University of Massachusetts Amherst. Retrieved from https://www.bluegreenalliance.org/site/9-million-good-
jobs-from-climate-action-the-inflation-reduction-act/
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vehicle. For example, in comments submitted on the proposal, the Clean Air Task Force, RMI
and the Zero Emission Transportation Association stated that electric trucks are desirable to
drivers because they are more comfortable, have a smoother ride with minimal vibrations,
produce less noise pollution, do not smell, and have a high-tech driving experience. The
commenters state that the more desirable electric trucks have the possibility of decreasing truck
driver shortages and increasing driver retention.
Another potential downstream impact is on the services provided by HD vehicles. Because of
the diversity of the HD vehicle market, we expect entities from a wide range of transportation
sectors to purchase vehicles subject to the emission standards. HD vehicles are typically
commercial in nature, and typically provide an "intermediate good," meaning that they are used
to provide a commercial service (transporting goods, municipal service vehicles, etc.), rather
than serving as final consumer goods themselves (as most light-duty vehicles do). As a result, the
purchase price of a new HD vehicle likely impacts the price of the service provided by that
vehicle. Purchase incentives, as might be available for a new ZEV, may also impact the price of
services provided through the impact on the upfront cost of that vehicle. In addition, lifetime
operating costs may impact the prices of services provided. If a change in these costs results in
higher prices for the services provided by these vehicles compared to the same services provided
by a pre-regulation vehicle, it would potentially reduce demand for the services such vehicles
provide. In turn, there may be less employment in the sectors providing such services. On the
other hand, if a change in these costs results in lower prices for services provided, there may be
an increase in employment in the sectors providing such services. We estimate that there are
savings over the life of operating a ZEV relative to an ICE vehicle, which may decrease
downstream prices. We expect that the actual effects on demand for the services provided by
these vehicles and related employment will depend on cost pass-through, as well as
responsiveness of demand to changes in transportation cost, should such changes occur.1930
This action may also produce upstream employment effects in other sectors, for example, in
firms providing liquid fuel. While reduced liquid fuel consumption represents cost savings for
purchasers of liquid fuel, it could also represent a loss in value of output for the petroleum
refining industry, which could result in reduced employment in that sector. These impacts may
also pass up the supply chain to, for example, pipeline construction, operation and maintenance,
and domestic oil production. In this final rule, we estimate that the reduction in fuel consumption
(see RIA Chapter 6.5) will be met by increasing net exports by half of the amount of reduced
domestic demand for refined product, with the other half being met by reductions in U.S.
refinery output (see RIA Chapter 4.3 for more information on our assumptions of changes in
U.S. refinery output). As discussed in RIA Chapter 4.3, there have been several closures or
conversions of refineries in recent years that are attributed to many factors, including lower fuel
demand due to COVID-19 or decisions to pivot away from fossil fuels. Though the reduced
domestic output may lead to future closures or conversions of individual refineries, we are
unable to estimate the future decisions of refineries to keep operating, shut down or convert away
from fossil fuels because they depend on the economics of individual refineries, economic
conditions of parent companies, long-term strategies for each company, and on the larger macro-
economic conditions of both the U.S. and the global refinery market. Therefore, we are unable to
estimate the possible effect this rule will have on employment in the petroleum refining sector.
1930 Cost pass-through refers to the amount of increase in up-front cost incurred by the HD vehicle owner that is then
passed on to their customers in the form of higher prices for services provided by the HD vehicle owner.
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However, because the petroleum refining industry is material intensive and not labor intensive,
and we estimate that only part of the reduction in liquid fuel consumption will be met by reduced
refinery production in the U.S., we expect that any employment effect due to reduced petroleum
demand will be small.
An additional employment impact could be felt on the industries that service and maintain HD
vehicles. Due to less need for maintenance of ZEV vehicles relative to ICE vehicles, demand for
such workers could decrease. In addition, commenters stated that, similar to technicians
supporting charging infrastructure, there is currently a lack of qualified technicians able to
service and maintain HD ZEVs. However, this may be a short-term issue. As the share of HD
ZEVs in the market grows, demand for qualified technicians will also grow.1931 As mentioned in
the discussion of infrastructure technicians, if there is a shortage of technicians who can maintain
and service HD ZEVs, employment in the industry may become more attractive (either due to
higher wages because of the rarity of the skill set, more opportunities due to high demand for the
skill set, or both), and workers willing to train, and companies willing to invest in those workers,
is expected to increase. Also, it is not unreasonable to assume that technicians trained to work on
HD vehicles will be uniquely qualified to retrain for ZEVs. Though ZEV maintenance requires
additional skillsets beyond those learned by a traditional HD vehicle technician, there are aspects
of the knowledge base acquired by working on HD vehicles that should transfer to ZEVs. In
addition, as described above in Chapter 6.4.2, DOL, DOE and other groups are involved in
existing and planned projects focused on training new and existing employees in green energy
jobs, including maintenance and repair.
This action could also provide some positive impacts on driver employment in the HD
trucking industry. As discussed in Preamble Section IV, the reduction in fuel costs from
purchasing a ZEV instead of an ICE vehicle will be expected to not only reduce operational costs
for ZEV owners and operators compared to an ICE vehicle, but it may also provide additional
incentives to purchase a HD ZEV over a HD ICE vehicle. For example, comments submitted on
the proposed rule stated that HD ZEVs are associated with increased driver satisfaction due to
quieter operations, better visibility, a smoother ride, faster acceleration, less odor, and a smoother
and safer experience when driving in high traffic or urban environments. The commenters state
that these positive attributes have the possibility of decreasing truck driver shortages and
increasing driver retention. Also, drivers of HD ZEVs, as well as other HD vehicles compliant
with this rule, will benefit from the decreased emissions of the vehicle they are driving.
An additional factor to consider for employment impacts across all industries that might be
affected by this rule under the potential compliance pathway, or by the increase in the share of
HD ZEVs in the market, is that though more ZEVs are being introduced to the market, regardless
of this rule, the vehicles on the road will still continue to be dominated by HD ICE vehicles, and
many HD ICE vehicles will continue to be sold. This gradual shift avoids abrupt changes and
will reduce impacts in acceptance, infrastructure availability, employment, supply chain, and
more.
1931 As discussed in Section 3.7 of the RTC, we account for a transition period during which extra training needs for
ZEV maintenance and repair may be required in the first few years of the rule. To account for this, we use a
decreasing scaling factor over 5 years, starting in 2027 for BEVs and 2031 for FCEVs, which, in effect, reduces the
projected cost savings due to maintenance and repair in the early years compared to those in the later years.
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6.5 Oil Imports and Electricity and Hydrogen Consumption
We project that the final emission standards will reduce not only GHG emissions but also
liquid fuel consumption while simultaneously increasing electricity and hydrogen consumption.
Reducing fuel consumption is a significant means of reducing GHG emissions from the
transportation sector.
Table 6-1 shows the impacts on fossil fuel consumption. The diesel and gasoline gallons are
straight gallons of retail liquid fuel, while the CNG reductions represent gasoline gallon
equivalents. We do not include CNG reductions in our estimates of oil import reductions or our
estimates of energy security benefits (see RIA Chapter 7.3). We do include CNG reductions in
our estimate of monetized fuel savings (see RIA Chapter 3.5.3) where we apply gasoline fuel
prices to the reduced gallons of gasoline equivalents.
Table 6-1 Fossil Fuel Reductions due to the Final Rule, Millions of Gallons
Calendar Year
Diesel
Gasoline
CNG
(Gasoline Equivalents)
2027
-32
-23
0
2028
-84
-45
-1
2029
-160
-66
-1
2030
-300
-85
-2
2031
-610
-140
-4
2032
-1,200
-220
-8
2033
-1,800
-290
-11
2034
-2,300
-360
-15
2035
-2,800
-410
-18
2036
-3,300
-460
-22
2037
-3,800
-500
-25
2038
-4,200
-540
-28
2039
-4,600
-570
-32
2040
-4,900
-600
-35
2041
-5,200
-630
-39
2042
-5,400
-650
-42
2043
-5,600
-660
-45
2044
-5,800
-680
-49
2045
-5,900
-690
-52
2046
-6,000
-690
-55
2047
-6,100
-700
-58
2048
-6,100
-700
-61
2049
-6,100
-700
-65
2050
-6,200
-700
-68
2051
-6,200
-700
-72
2052
-6,200
-700
-75
2053
-6,300
-700
-78
2054
-6,300
-690
-82
2055
-6,300
-690
-86
Sum
-120,000
-15,000
-1,100
750
-------
As discussed in Preamble Section V, we used an updated version of EPA's MOVES model to
estimate the impact of the final standards on heavy-duty vehicle emissions, fuel consumption,
electricity consumption, and hydrogen consumption. Table 6-2 shows the estimated reduction in
U.S. oil imports under the final emission standards relative to the revised reference case scenario
and, also, shows the projected increase in electricity and hydrogen consumption due to the final
rule.
The oil import reductions are the result of reduced consumption (i.e., reduced liquid fuel
demand) of both diesel fuel and gasoline and our estimate of 94.8 percent of reduced liquid fuel
demand results in reduced imports. The 94.8 percent oil import factor is based upon revised
refinery throughput assumptions for this final rule. See Chapter 7 of the RIA for a discussion of
how the change in the refinery throughput estimate for this final rule results in the 94.8 percent
oil import reduction factor. Thus, on balance, each gallon of petroleum reduced as a result of the
final CO2 emission standards is anticipated to reduce total U.S. imports of petroleum by 0.948
gallons.1932
To estimate how reductions in liquid fuel consumption translate to reductions in oil imports,
we used the following factors:
• Every gallon of reduced retail gasoline (E10) consumption consists of 10 percent
ethanol and 90 percent petroleum-based product (termed E0 for ease hereafter).
• Every gallon of reduced E0 has an energy density ratio of 0.881 relative to crude oil,
based on the ratio of energy densities of E0 (114,200 BTU/gallon) to crude oil
(129,670 BTU/gallon).
• Every gallon of reduced diesel consumption has an energy density ratio of 0.998
relative to crude oil, based on the ratio of energy densities of diesel fuel (129,488
BTU/gallon) to crude oil (129,670 BTU/gallon).
• 42 gallons per barrel of crude oil.
1932
The estimated benefits from a reduction in U.S. oil imports are due to the U.S.'s decreased exposure to global
oil price shocks. We characterized these energy security benefits in Chapter 7.3 of this RIA.
751
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Table 6-2 Estimated U.S. Oil Import Reductions and Electricity and Hydrogen Consumption Increases due to
the Final Rule*
Calendar
Year
Imported
Oil
(Million
Barrels
per
Year)
%of
2022
U.S.
Imports
of
Crude
Electricity
Consumption
(GWh)
% of 2022
U.S.
Electricity
Consumption
Hydrogen
Consumption
(1000 metric tons
per year)
% of 2020
U.S. Hydrogen
Consumption
2027
-1
0.0%
620
0.0%
0
0.0%
2028
-3
-0.1%
1,600
0.0%
0
0.0%
2029
-5
-0.2%
3,100
0.1%
0
0.0%
2030
-8
-0.4%
5,700
0.1%
17
0.2%
2031
-16
-0.7%
12,000
0.3%
51
0.5%
2032
-31
-1.3%
22,000
0.5%
130
1.3%
2033
-45
-2.0%
32,000
0.8%
200
2.0%
2034
-58
-2.5%
43,000
1.1%
280
2.8%
2035
-71
-3.1%
53,000
1.3%
350
3.5%
2036
-83
-3.6%
62,000
1.5%
430
4.3%
2037
-94
-4.1%
71,000
1.7%
500
5.0%
2038
-100
-4.5%
79,000
1.9%
560
5.6%
2039
-110
-4.9%
86,000
2.1%
630
6.3%
2040
-120
-5.3%
93,000
2.3%
680
6.8%
2041
-130
-5.6%
99,000
2.4%
730
7.3%
2042
-130
-5.8%
100,000
2.6%
780
7.8%
2043
-140
-6.1%
110,000
2.7%
820
8.2%
2044
-140
-6.2%
110,000
2.8%
850
8.5%
2045
-150
-6.4%
110,000
2.8%
880
8.8%
2046
-150
-6.5%
120,000
2.9%
900
9.0%
2047
-150
-6.5%
120,000
2.9%
920
9.2%
2048
-150
-6.6%
120,000
2.9%
930
9.3%
2049
-150
-6.6%
120,000
2.9%
950
9.5%
2050
-150
-6.6%
120,000
3.0%
960
9.6%
2051
-150
-6.7%
120,000
3.0%
980
9.8%
2052
-150
-6.7%
120,000
3.0%
980
9.8%
2053
-150
-6.7%
120,000
3.0%
990
9.9%
2054
-150
-6.7%
120,000
3.0%
1,000
10%
2055
-150
-6.7%
120,000
3.0%
1,000
10%
Sum
-3,000
2,300,000
18,000
*According to EIA, 2022 US crude oil imports were 6.28 million barrels per day, or 2.29 billion barrels for the
year, 2022 U.S. electricity consumption was 4.05 trillion kWh, or 4.05 million GWh, and according to NREL in
October 2020, U.S. hydrogen demand is 10 million metric tons annually.1933 Note that the electricity consumption
presented here reflects changes in battery electric vehicle consumption and is the consumption used in estimating
fuel costs; it does not include changes in electricity generation to produce hydrogen.
We also conducted a sensitivity with respect to the impact on domestic refining in response to
a demand reduction in domestic liquid fuel. That sensitivity and how it impacts refinery
emissions is discussed in Chapter 4.10 of this RIA. Associated with that sensitivity is the impact
on U.S. imports of oil because changes in domestic refining are likely to impact the level of
1933 See "2022_crude_oil_imports.pdf' and "2022_electricity_consumption.pdf' contained in the docket for this
rule, both last accessed on November 22, 2023. See "H2_consumption_NREL.pdf' contained in the docket for this
rule and last accessed on January 25, 2023.
752
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imported oil. In our central analysis, we estimate that half of all reductions in domestic liquid
fuel demand will result in reductions in domestic refining and, as a result, 94.8 percent of that
reduced demand will result in reduced U.S. oil imports, as described above. In our sensitivity, we
estimate that only 20 percent of the reduced domestic demand will result in reduced domestic
refining. The result being a 97.9 percent reduction in U.S. oil imports. Under that scenario, the
reductions in U.S. oil imports would be as shown in Table 6-3.
Table 6-3 Estimated U.S. Oil Import Reductions due to the Final Rule under the Refinery Sensitivity *
Calendar Year
Imported Oil
(Million Barrels per Year)
% of 2022
U.S. Imports of Crude
2027
-1
-0.1%
2028
-3
-0.1%
2029
-5
-0.2%
2030
-9
-0.4%
2031
-17
-0.7%
2032
-32
-1.4%
2033
-46
-2.0%
2034
-60
-2.6%
2035
-74
-3.2%
2036
-86
-3.7%
2037
-97
-4.2%
2038
-110
-4.7%
2039
-120
-5.1%
2040
-120
-5.4%
2041
-130
-5.8%
2042
-140
-6.0%
2043
-140
-6.3%
2044
-150
-6.4%
2045
-150
-6.6%
2046
-150
-6.7%
2047
-150
-6.7%
2048
-160
-6.8%
2049
-160
-6.8%
2050
-160
-6.8%
2051
-160
-6.9%
2052
-160
-6.9%
2053
-160
-6.9%
2054
-160
-6.9%
2055
-160
-6.9%
Sum
-3,100
*According to EIA, 2022 US crude oil imports were 6.28 million barrels per day, or 2.29 billion barrels for the
year.
753
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Chapter 7 Benefits
7.1 Benefits of GHG Reductions
Tables 7-1 through 7-4 present the estimated annual, undiscounted climate benefits of reduced
GHG emissions, and consequently the annual quantified benefits (i.e., total GHG benefits), for
each of the three SC-GHG values estimated within U.S. EPA (2023f)1934 for the stream of years
beginning with the first year of rule implementation, 2027, through 2055. Also shown are the
present values (PV) and equivalent annualized values (AV) associated with each of the three SC-
GHG values. In this analysis, to calculate the present and annualized values of climate benefits,
EPA uses the same discount rate as the near-term target Ramsey rate used to discount the climate
benefits from future GHG reductions. That is, future climate benefits estimated with the SC-
GHG at the near-term 2 percent Ramsey rate are discounted to the base year of the analysis using
the same 2 percent rate.1935 Appendix C to this RIA contains the benefits of the final rule using
the interim SC-GHG estimates calculated within the proposal.
1934 U.S. Environmental Protection Agency (2023f). Supplementary Material for the Regulatory Impact Analysis for
the Final Rulemaking, "Standards of Performance for New, Reconstructed, and Modified Sources and Emissions
Guidelines for Existing Sources: Oil and Natural Gas Sector Climate Review": EPA Report on the Social Cost of
Greenhouse Gases: Estimates Incorporating Recent Scientific Advances. Washington, DC: U.S. EPA
1935 As discussed in U.S. EPA (2023f), the error associated with using a constant discount rate rather than the
certainty-equivalent rate path to calculate the present value of a future stream of monetized climate benefits is small
for analyses with moderate time frames (e.g., 30 years or less). (EPA 2023f) also provides an illustration of the
amount that climate benefits from reductions in future emissions will be underestimated by using a constant discount
rate relative to the more complicated certainty-equivalent rate path.
754
-------
Table 7-1 Benefits of Reduced CO2 Emissions from the Rule, Millions of 2022 dollars
Emissions Year
Near-Term Ramsey Discount Rate and Statistic
2.5% Average
2.0% Average
1.5% Average
2027
$43
$69
$120
2028
$94
$150
$250
2029
$150
$240
$400
2030
$180
$300
$490
2031
$280
$440
$730
2032
$400
$630
$1,000
2033
$500
$790
$1,300
2034
$580
$920
$1,500
2035
$630
$990
$1,600
2036
$1,700
$2,600
$4,300
2037
$3,000
$4,700
$7,700
2038
$4,700
$7,300
$12,000
2039
$6,700
$10,000
$17,000
2040
$8,900
$14,000
$22,000
2041
$9,500
$15,000
$24,000
2042
$10,000
$15,000
$25,000
2043
$10,000
$16,000
$26,000
2044
$11,000
$16,000
$26,000
2045
$11,000
$17,000
$27,000
2046
$12,000
$18,000
$28,000
2047
$12,000
$18,000
$29,000
2048
$12,000
$19,000
$29,000
2049
$13,000
$19,000
$30,000
2050
$13,000
$20,000
$31,000
2051
$13,000
$20,000
$31,000
2052
$14,000
$20,000
$32,000
2053
$14,000
$21,000
$32,000
2054
$14,000
$21,000
$32,000
2055
$14,000
$21,000
$33,000
PV
$130,000
$210,000
$370,000
AV
$6,200
$9,700
$16,000
Note: Climate benefits are based on changes (reductions) in CO2 emissions and are
calculated using updated estimates of the SC-CO2 from (EPA 2023f). Climate benefits
include changes in vehicle, EGU and refinery CO2 emissions.
755
-------
Table 7-2 Benefits of Reduced CH4 Emissions from the Rule, Millions of 2022 dollars
Emissions Year
Near-Term Ramsey Discount Rate and Statistic
2.5% Average
2.0% Average
1.5% Average
2027
$0
$0
$0
2028
$0
$0
$0
2029
$0
$0
$0
2030
$0
$0
$0
2031
$0
$0
$0
2032
$0
$0
$0
2033
$0
$0
$0
2034
$0
$0
$0
2035
$0
$0
$0
2036
$1
$1
$1
2037
$2
$3
$4
2038
$5
$6
$7
2039
$7
$9
$11
2040
$10
$12
$15
2041
$12
$14
$18
2042
$14
$17
$21
2043
$16
$19
$24
2044
$18
$21
$27
2045
$20
$24
$30
2046
$22
$26
$33
2047
$24
$28
$35
2048
$26
$31
$38
2049
$28
$33
$41
2050
$30
$36
$44
2051
$32
$38
$47
2052
$34
$40
$50
2053
$36
$43
$53
2054
$38
$46
$57
2055
$41
$48
$60
PV
$240
$320
$440
AV
$12
$14
$19
Note: Climate benefits are based on changes (reductions) in GHG emissions and are
calculated using updated estimates of the SC-CH4 from (EPA 2023f). Climate benefits
include changes in vehicle, EGU and refinery CH4 emissions.
756
-------
Table 7-3 Benefits of Reduced N2O Emissions from the Rule, Millions of 2022 dollars
Emissions Year
Near-Term Ramsey Discount Rate and Statistic
2.5% Average
2.0% Average
1.5% Average
2027
$3
$4
$6
2028
$7
$10
$16
2029
$13
$19
$29
2030
$24
$36
$56
2031
$50
$75
$120
2032
$99
$150
$230
2033
$150
$220
$340
2034
$200
$290
$450
2035
$250
$360
$560
2036
$300
$440
$670
2037
$350
$510
$770
2038
$400
$580
$880
2039
$440
$640
$970
2040
$490
$710
$1,100
2041
$530
$760
$1,200
2042
$570
$820
$1,200
2043
$600
$870
$1,300
2044
$630
$910
$1,400
2045
$660
$940
$1,400
2046
$680
$970
$1,400
2047
$700
$1,000
$1,500
2048
$720
$1,000
$1,500
2049
$740
$1,000
$1,500
2050
$750
$1,100
$1,600
2051
$770
$1,100
$1,600
2052
$780
$1,100
$1,600
2053
$800
$1,100
$1,600
2054
$810
$1,100
$1,700
2055
$820
$1,200
$1,700
PV
$8,200
$13,000
$21,000
AV
$400
$590
$910
Note: Climate benefits are based on changes (reductions) in N20 emissions and are
calculated using updated estimates of the SC-N20 from (EPA 2023f). Climate benefits
include changes in vehicle, EGU and refinery N20 emissions.
757
-------
Table 7-4 Benefits of Reduced GHG Emissions from the Final Rule, Millions of 2022 dollars
Emissions Year
Near-Term Ramsey Discount Rate and Statistic
2.5% Average
2.0% Average
1.5% Average
2027
$46
$73
$120
2028
$100
$160
$270
2029
$160
$260
$430
2030
$210
$330
$550
2031
$330
$510
$850
2032
$500
$770
$1,300
2033
$650
$1,000
$1,600
2034
$780
$1,200
$2,000
2035
$880
$1,400
$2,200
2036
$2,000
$3,100
$4,900
2037
$3,400
$5,300
$8,500
2038
$5,100
$7,900
$13,000
2039
$7,100
$11,000
$18,000
2040
$9,400
$15,000
$23,000
2041
$10,000
$15,000
$25,000
2042
$11,000
$16,000
$26,000
2043
$11,000
$17,000
$27,000
2044
$11,000
$17,000
$28,000
2045
$12,000
$18,000
$28,000
2046
$12,000
$19,000
$29,000
2047
$13,000
$19,000
$30,000
2048
$13,000
$20,000
$31,000
2049
$14,000
$20,000
$32,000
2050
$14,000
$21,000
$32,000
2051
$14,000
$21,000
$33,000
2052
$14,000
$21,000
$33,000
2053
$15,000
$22,000
$34,000
2054
$15,000
$22,000
$34,000
2055
$15,000
$22,000
$34,000
PV
$130,000
$220,000
$390,000
AV
$6,600
$10,000
$17,000
Note: Climate benefits are based on changes (reductions) in GHG emissions and are
calculated using updated estimates of the SC-GHG from (EPA 2023f). Climate benefits
include changes in vehicle, EGU and refinery GHG emissions.
Unlike many environmental problems where the causes and impacts are distributed more
locally, GHG emissions are a global externality making climate change a true global challenge.
GHG emissions contribute to damages around the world regardless of where they are emitted.
Because of the distinctive global nature of climate change, in the RIA for this final rule the EPA
centers attention on a global measure of climate benefits from GHG reductions. Consistent with
all IWG recommended SC-GHG estimates to date, the SC-GHG values presented in Section 6
provide a global measure of monetized damages from CO2, CH4 and N2O and Table 7-1 through
Table 7-4 present the monetized global climate benefits of the CO2, CH4 and N2O emission
reductions expected from the final rule. This approach is the same as that taken in EPA
regulatory analyses from 2009 through 2016 and since 2021. It is also consistent with OMB
Circular A-4 guidance (2003) that states when a regulation is likely to have international effects,
758
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"these effects should be reported"1936'1937. EPA also notes that EPA's cost estimates in RIAs,
including the cost estimates contained in this RIA, regularly do not differentiate between the
share of compliance costs expected to accrue to U.S. firms versus foreign interests, such as to
foreign investors in regulated entities1938. A global perspective on climate effects is therefore
consistent with the approach EPA takes on costs. There are many reasons, as summarized in this
section - and as articulated by OMB and in IWG assessments (IWG, 2010)1939 (IWG, 2013)1940
(IWG, 2016a)1941 (IWG, 2016b)1942 (IWG, 2021)1943, the 2015 Response to Comments (IWG,
2015)1944 and in detail in (EPA 2023f)1945 and in Appendix A of the Response to Comments
document for the December 2023 Final Oil and Gas NSPS/EG Rulemaking - why the EPA
1936 Available online: https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4.
1937 While OMB Circular A-4 recommends that international effects we reported separately, the guidance also
explains that "[d]ifferent regulations may call for different emphases in the analysis, depending on the nature and
complexity of the regulatory issues". Circular A-4 (2023) states that "In certain contexts, it may be particularly
appropriate to include effects experienced by noncitizens residing abroad in your primary analysis. Such contexts
include, for example, when:
• assessing effects on noncitizens residing abroad provides a useful proxy for effects on U.S. citizens and residents
that are difficult to otherwise estimate;
• assessing effects on noncitizens residing abroad provides a useful proxy for effects on U.S. national interests that
are not otherwise fully captured by effects
experienced by particular U.S. citizens and residents (e.g., national security interests, diplomatic interests, etc.);
• regulating an externality on the basis of its global effects supports a cooperative international approach to the
regulation of the externality by potentially inducing
other countries to follow suit or maintain existing efforts; or
• international or domestic legal obligations require or support a global calculation of regulatory effects".
1938 For example, in the RIA for the 2018 Proposed Reconsideration of the Oil and Natural Gas Sector Emission
Standards for New, Reconstructed, and Modified Sources, the EPA acknowledged that some portion of regulatory
costs will likely "accru[e] to entities outside U.S. borders" through foreign ownership, employment, or consumption
(EPA 2018). In general, a significant share of U.S. corporate debt and equities are foreign-owned, including in the
oil and gas industry.
1939 IWG. 2010. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis under
Executive Order 12866. Accessed 2023. https://www.epa.gov/sites/default/files/2016-
12/documents/scc_tsd_2010 .pdf.
1940 —2013. Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact
Analysis Under Executive Order 12866. https://www.ourenergypolicy.org/wp-
content/uploads/2013/06/social_cost_of_carbon_for_ria_2013_update.pdf.
1941 —. 2016a. Addendum to Technical Support Document on Social Cost of Carbon for Regulatory Impact
Analysis under Executive Order 12866: Application of the Methodology to Estimate the Social Cost of Methane and
the Social Cost of Nitrous Oxide, https://www.epa.gov/sites/default/files/2016-12/documents/addendum_to_sc-
ghg_tsd_august_2016.pdf.
1942 —2016b. Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact
Analysis Under Executive Order 12866. Accessed 2023. https://www.epa.gov/sites/default/files/2016-
12/documents/sc_CO2_tsd_august_2016.pdf.
1943 —. 2021. Technical Support Document: Social Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates
under Executive Order 13990. Accessed 2023. https://www.whitehouse.gov/wp-
content/uploads/2021/02/TechnicalSupportDocument_SocialCostofCarbonMethaneNitrouSOXide.pdf.
1944 i\yG. 2015. Response to comments: social cost of carbon for regulatory impact analysis under executive order
12866. Response to Comments, United States Government.
https://obamawhitehouse.archives.gov/sites/default/files/omb/inforeg/scc-responseto-comments-final-july-2015.pdf.
1945 EPA. 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
759
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focuses on the global value of climate change impacts when analyzing policies that affect GHG
emissions.
International cooperation and reciprocity are essential to successfully addressing climate
change, as the global nature of greenhouse gases means that a ton of GHGs emitted in any other
country harms those in the U.S. just as much as a ton emitted within the territorial U.S.
Assessing the benefits of U.S. GHG mitigation activities requires consideration of how those
actions may affect mitigation activities by other countries, as those international mitigation
actions will provide a benefit to U.S. citizens and residents by mitigating climate impacts that
affect U.S. citizens and residents. This is a classic public goods problem because each country's
reductions benefit everyone else, and no country can be excluded from enjoying the benefits of
other countries' reductions. The only way to achieve an efficient allocation of resources for
emissions reduction on a global basis — and so benefit the U.S. and its citizens and residents —
is for all countries to base their policies on global estimates of damages. A wide range of
scientific and economic experts have emphasized the issue of international cooperation and
reciprocity as support for assessing global damages of GHG emission in domestic policy
analysis. Using a global estimate of damages in U.S. analyses of regulatory actions allows the
U.S. to continue to actively encourage other nations, including emerging major economies, to
also assess global climate damages of their policies and to take steps to reduce emissions. For
example, many countries and international institutions have already explicitly adapted the global
SC-GHG estimates used by EPA in their domestic analyses (e.g., Canada, Israel) or developed
their own estimates of global damages (e.g., Germany), and recently, there has been renewed
interest by other countries to update their estimates since the draft release of the updated SC-
GHG estimates presented in the December 2022 Oil and Gas NSPS/EG Supplemental Proposal
RIA1946. Several recent studies have empirically examined the evidence on international GHG
mitigation reciprocity, through both policy diffusion and technology diffusion effects. See U.S.
EPA (EPA 2023f)1947 for more discussion.
For all of these reasons, the EPA believes that a global metric is appropriate for assessing the
climate benefits of avoided GHG emissions in this final RIA. In addition, as emphasized in the
(National Academies, 2017)1948 recommendations, "[i]t is important to consider what constitutes
a domestic impact in the case of a global pollutant that could have international implications that
impact the United States." The global nature of GHG pollution and its impacts means that U.S.
interests are affected by climate change impacts through a multitude of pathways and these need
to be considered when evaluating the benefits of GHG mitigation to U.S. citizens and residents.
The increasing interconnectedness of global economy and populations means that impacts
1946 In April 2023, the government of Canada announced the publication of an interim update to their SC-GHG
guidance, recommending SC-GHG estimates identical to the EPA's updated estimates presented in the December
2022 Supplemental Proposal RIA. The Canadian interim guidance will be used across all Canadian federal
departments and agencies, with the values expected to be finalized by the end of the year. See more at
https://www.canada.ca/en/environment-climate-change/services/climate-change/science-research-data/social-cost-
ghg.html.
1947 EPA. 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1948 National Academies. 2017. Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon
Dioxide. Washington, D.C.: The National Academies Press.
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occuring outside of U.S. borders can have significant impacts on U.S. interests. Examples of
affected interests include direct effects on U.S. citizens and assets located abroad, international
trade, and tourism, and spillover pathways such as economic and political destabilization and
global migration that can lead to adverse impacts on U.S. national security, public health, and
humanitarian concerns. Those impacts point to the global nature of the climate change problem
and are better captured within global measures of the social cost of greenhouse gases.
In the case of these global pollutants, for the reasons articulated in this section, the assessment
of global net damages of GHG emissions allows EPA to fully disclose and contextualize the net
climate benefits of GHG emission reductions expected from this final rule. The EPA disagrees
with public comments received on the December 2022 Oil and Gas NSPS/EG Supplemental
Proposal that suggested that the EPA can or should use a metric focused on benefits resulting
solely from changes in climate impacts occuring within U.S. borders. The global models used in
the SC-GHG modeling described above do not lend themselves to be disaggregated in a way that
could provide sufficiently robust information about the distribution of the rule's climate benefits
to citizens and residents of particular countries, or population groups across the globe and within
the U.S. Two of the models used to inform the damage module, the GIVE and DSCIM models,
have spatial resolution that allows for some geographic disaggregation of future climate impacts
across the world. This permits the calculation of a partial GIVE and DSCIM-based SC-GHG
measuring the damages from four or five climate impact categories projected to physically occur
within the U.S., respectively, subject to caveats. As discussed at length in (EPA 2023f)1949 these
damage modules are only a partial accounting and do not capture all of the pathways through
which climate change affects public health and welfare. For example, this modeling omits most
of the consequences of changes in precipitation, damages from extreme weather events (e.g.,
wildfires), the potential for nongradual damages from passing critical thresholds (e.g., tipping
elements) in natural or socioeconomic systems, and non-climate mediated effects of GHG
emissions other than CO2 fertilization (e.g., tropospheric ozone formation due to CH4 emissions).
Thus, they only cover a subset of potential climate change impacts. Furthermore, as discussed at
length in (EPA 2023f), the damage modules do not capture spillover or indirect effects whereby
climate impacts in one country or region can affect the welfare of residents in other countries or
regions— through the effect of climate change on international markets, trade, tourism, and other
activities. Supply chain disruptions are a prominent pathway through which U.S. business and
consumers can be affected by climate change impacts abroad. Additional climate change-induced
international spillovers can occur through pathways such as damages across transboundary
resources, economic and political destabilization, and global migration that can lead to adverse
impacts on U.S. national security, public health, and humanitarian concerns.
Additional modeling efforts can and have shed further light on some omitted damage
categories. For example, the Framework for Evaluating Damages and Impacts (FrEDI) is an
open-source modeling framework developed by the EPA1950 to facilitate the characterization of
1949 EPA. 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:Docket ID No. EPA-HQ-OAR-2021-0317.
1950 The FrEDI framework and Technical Documentation have been subject to a public review comment period
and an independent external peer review, following guidance in the EPA Peer-Review Handbook for Influential
Scientific Information (ISI). Information on the FrEDI peer-review is available at the EPA Science Inventory.
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net annual climate change impacts in numerous impact categories within the contiguous U.S. and
monetize the associated distribution of modeled damages (Hartin, et al., 2023)1951 (EPA,
2021)1952. The additional impact categories included in FrEDI reflect the availability of U.S.-
specific data and research on climate change effects. As discussed in U.S. EPA (EPA, 2023f)1953
results from FrEDI show that annual damages resulting from climate change impacts within the
contiguous U.S. (CONUS) (i.e., excluding Hawaii, Alaska, and U.S. territories) and for impact
categories not represented in GIVE and DSCIM are expected to be substantial. As discussed in
U.S. EPA (EPA, 2021)1954, results from FrEDI show that annual damages resulting from climate
change impacts within the contiguous U.S. (CONUS) (i.e., excluding Hawaii, Alaska, and U.S.
territories) and for impact categories not represented in GIVE and DSCIM are expected to be
substantial. For example, FrEDI estimates a partial SC-CO2 of $41/mtC02 for damages
physically occurring within CONUS for 2030 emissions (under a 2 percent near-term Ramsey
discount rate) (Hartin, et al., 20 23)1955, compared to a GIVE and DSCIM-based U.S.-specific
SC-CO2 of $18/mtC02 and $16/mtC02, respectively, for 2030 emissions (2022 USD). While the
FrEDI results help to illustrate how monetized damages physically occurring within CONUS
increase as more impacts are reflected in the modeling framework, they are still subject to many
of the same limitations associated with the DSCIM and GIVE damage modules, including the
1951 Hartin, C. 2023. "Advancing the estimation of future climate impacts within the United States." Earth System
Dynamics 14: 1015-1037. https://dio.org/10.5194/esd-14-1015-2023.
1952 EPA. 2021. "Technical Documentation on the framework for evaluating damages and impacts (FrEDI)." EPA
Science Inventory.
https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=351316&Lab=OAP&simplesearch=0&showcriteri
a=2&sortby=pubDate&searchall=fredi&timstype=&datebeginpublishedpresented=02/14/2021.
Technical Documentation on The Framework for Evaluating Damages and Impacts (FrEDI) | Science Inventory | US
EPA
1953 EPA. 2023f. "Supplementary Material for the Regulatory Impact Analysis for the Final Rulemaking: Standards
of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review." EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances, Washington, DC. doi:DocketID No. EPA-HQ-OAR-2021-0317.
1954 EPA. 2021. "Technical Documentation on the framework for evaluating damages and impacts (FrEDI)." EPA
Science Inventory.
https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=351316&Lab=OAP&simplesearch=0&showcriteri
a=2&sortby=pubDate&searchall=fredi&timstype=&datebeginpublishedpresented=02/14/2021.
Technical Documentation on The Framework for Evaluating Damages and Impacts (FrEDI) | Science Inventory | US
EPA
1955 Hartin, C. 2023. "Advancing the estimation of future climate impacts within the United States." Earth System
Dynamics 14: 1015-1037. https://dio.org/10.5194/esd-14-1015-2023.
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omission or partial modeling of important damage categories1956'1957. Finally, none of these
modeling efforts - GIVE, DSCIM, and FrEDI - reflect non-climate mediated effects of GHG
emissions experienced by U.S. populations (other than CO2 fertilization effects on agriculture).
In addition to its climate impacts, methane also contributes to the chemical formation of
tropospheric ozone, which contributes to mortality. One recent paper on this effect (McDuffie, et
al., 2023)1958 estimated the monetized increase in respiratory-related human mortality risk from
the ozone produced from a marginal pulse of methane emissions. Using the socioeconomics from
the RFF-SPs and the 2 percent near-term Ramsey discounting approach, this additional health
risk to U.S. populations is on the order of approximately $360/mtCH4 (2022 USD) for 2030
emissions.
Applying the U.S.-specific partial SC-GHG estimates derived from the multiple lines of
evidence described above to the GHG emissions reduction expected under the final rule would
yield substantial benefits. For example, the present value of the climate benefits of the final rule
as measured by FrEDI from climate change impacts in CONUS are estimated to be $33 billion
(under a 2 percent near-term Ramsey discount rate)1959. However, the numerous explicitly
omitted damage categories and other modeling limitations discussed above and throughout (EPA
2023f) make it likely that these estimates underestimate the benefits to U.S. citizens and
residents of the GHG reductions from the final rule; the limitations in developing a U.S.-specific
estimate that accurately captures direct and spillover effects on U.S. citizens and residents further
demonstrates that it is more appropriate to use a global measure of climate benefits from GHG
reductions. The EPA will continue to review developments in the literature, including more
robust methodologies for estimating the magnitude of the various damages to U.S. populations
from climate impacts and reciprocal international mitigation activities, and explore ways to
better inform the public of the full range of GHG impacts.
1956 Another method that has produced estimates of the effect of climate change on U.S.-specific outcomes uses a
top-down approach to estimate aggregate damage functions. Published research using this approach include total-
economy empirical studies that econometrically estimate the relationship between GDP and a climate variable,
usually temperature. As discussed in U.S. EPA (EPA 2023f) the modeling framework used in the existing published
studies using this approach differ in important ways from the inputs underlying the SC-GHG estimates described
above (e.g., discounting, risk aversion, and scenario uncertainty) and focus solely on SC-C02. Hence, we do not
consider this line of evidence in the analysis for this RIA. Updating the framework of total-economy empirical
damage functions to be consistent with the methods described in this RIA and (EPA 2023f) would require new
analysis. Finally, because total-economy empirical studies estimate market impacts, they do not include any non-
market impacts of climate change (e.g., heat related mortality) and therefore are also only a partial estimate. The
EPA will continue to review developments in the literature and explore ways to better inform the public of the full
range of GHG impacts.
1957 FrEDI estimates a partial SC-CH4 (N20) of $660/mtCH4 ($12,000/mtN20) for damages physically occurring
within CONUS for 2030 emissions (under a 2 percent near-term Ramsey discount rate) (Hartin et al. 2023)
compared to a GIVE and DSCIM-based U.S.-specific SC-CH4 of $310/mtCH4 ($5,600/mtN20) and $84/mtCH4
($4,300/mtN2O), respectively, for 2030 emissions (2022 USD).
1958 McDuffie, EE, MC Sarofim, W Raich, M Jackson, H Roman, K Seltzer, BH Henderson, et al. 2023. "The social
cost of ozone-related mortality impacts from methane emissions." Earth's Future 11(9).
doi:https://doi.org/10.1029/2023EF003853.
1959 DCIM and GIVE use global damage functions. Damage functions based on only U.S.-data and research, but
not for other parts of the world, were not included in those models. FrEDI does make use of some of this U.S.-
specific data and research and as a result has a broader coverage of climate impact categories.
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7.2 Estimated Human Health Benefits of Non-GHG Emission Reductions
This section discusses the economic benefits from reductions in health and environmental
impacts resulting from criteria pollutant emission reductions that can be expected to occur as a
result of the final rule standards, or under the alternative standards. GHG emissions are
predominantly the byproduct of fossil fuel combustion processes that also produce criteria and
hazardous air pollutant emissions. The heavy-duty vehicles and engines that are subject to the
final standards are also significant sources of mobile source air pollution such as directly-emitted
PM, NOx, VOCs and air toxics. Our projected emission reductions, monetized here, reflect the
projected compliance pathway presented in Section II of the preamble that accompanies this rule.
However, as noted elsewhere, there are other means of achieving the standards, including
pathways not utilizing ZEV technologies. Resulting emission reductions would differ from those
presented here in such cases (EPA expects that different manufacturers will choose different
compliance pathways) (see RIA Chapter 4). Under the modeled pathway, zero-emission
technologies will also affect emissions from upstream sources that occur during, for example,
electricity generation and from the refining and distribution of fuel (see RIA Chapter 4).1960 This
final rule's benefits analysis includes added emissions due to increased electricity generation and
emissions reductions from reduced petroleum refining.
Changes in ambient concentrations of ozone, PM2.5, and air toxics that will result from the
final CO2 emission standards under the modeled pathway are expected to affect human health by
reducing premature deaths and other serious human health effects, and they are also expected to
result in other important improvements in public health and welfare. Children, especially, benefit
from reduced exposures to criteria and toxic pollutants because they tend to be more sensitive to
the effects of these respiratory pollutants. Ozone and particulate matter have been associated
with increased incidence of asthma and other respiratory effects in children, and particulate
matter has been associated with a decrease in lung maturation.
When feasible, EPA conducts full-scale photochemical air quality modeling to demonstrate
how its national mobile source regulatory actions affect ambient concentrations of regional
pollutants throughout the United States. The estimation of the human health impacts of a
regulatory action requires national-scale photochemical air quality modeling to conduct a full-
scale assessment of PM2.5- and ozone-related health benefits. Air quality modeling and
associated analyses are not available for this rule.
For the analysis of the final CO2 and alternative CO2 emission standards, we instead use a
reduced-form "benefit-per-ton" (BPT) approach to estimate the monetized PIVh.s-related health
benefits of this final rule. The BPT approach estimates the monetized economic value of PM2.5-
related emission reductions (such as direct PM, NOx and SO2) due to implementation of the final
program. Similar to the SC-GHG approach for monetizing reductions in GHGs, the BPT
approach estimates monetized health benefits of avoiding one ton of PM2.5-related emissions
from a particular source sector. The value of health benefits from reductions (or increases) in
PM2.5 emissions associated with this final rule was estimated by multiplying PM2.5-related BPT
1960 Like downstream emissions, the upstream emission impacts also depend on the compliance pathway chosen by
manufacturers. Should they comply, for example, by using more ICE technologies, the increased upstream
emissions would be smaller.
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values by the corresponding annual reduction (or increase) in tons of directly-emitted PM2.5 and
PM2.5 precursor emissions (NOx and SO2).
The BPT approach monetizes avoided premature deaths and illnesses that are expected to
occur as a result of reductions in directly-emitted PM2.5 and PM2.5 precursors. A chief limitation
to using PM2.5-related BPT values is that they do not reflect benefits associated with reducing
ambient concentrations of ozone, direct exposure to NO2, or exposure to mobile source air
toxics, nor do they account for improved ecosystem effects or visibility. The estimated benefits
of this final rule would be larger if we were able to monetize these unquantified benefits at this
time.
Using the BPT approach, we estimate the annualized value of the benefits of the final
program (over the analysis period from 2027 to 2055) to be $120 to $22 million at a 3% discount
rate and -$32 to -$9.1 million at a 7% discount rate.1961'1962 Benefits are reported in year 2022
dollars and reflect the PIVh.s-related benefits associated with reductions in NOx, SO2, and direct
PM2.5 emissions. The monetized criteria pollutant health benefits include reductions in PM2.5-
related emissions from HD vehicles. Monetized upstream health impacts associated with the
standards also include benefits associated with reduced PIVh.s-related emissions from refineries
and health disbenefits associated with increased PIVh.s-related emissions from EGUs. Negative
monetized values are associated with health disbenefits related to increases in estimated
emissions from EGUs. Depending on the discount rate used, the annualized value of the stream
of PM2.5-related benefits may either be positive or negative.
7.2.1 Approach to Estimating Human Health Benefits
This section summarizes EPA's approach to estimating the economic value of the PM2.5-
related benefits for this final rule. We use a BPT approach that is conceptually consistent with
EPA's use of BPT estimates in its regulatory analyses.1963'1964 In this approach, the PIVh.s-related
BPT values are the total monetized human health benefits (the sum of the economic value of the
reduced risk of premature death and illness) that are expected from reducing one ton of NOx,
SO2 or directly-emitted PM2.5.
1961 We note that the PM2 5-related health benefits of the final rule are smaller than those estimated for the proposal
for a number of reasons. First, the updates to the reference (no-action) case lead to a cleaner no-action scenario and
thus less incremental impact of the final standards. Second, there are other methodological changes and updates that
are included in the emissions modeling for the final rule, which are explained in RIA Chapter 4. Finally, there was
an error in the proposed criteria pollutant benefits calculation that resulted in an overestimate of the benefits
associated with reductions in direct PM emissions. The difference in criteria pollutant benefits between the proposed
and final rules does not reflect changes in the stringency of the standard, nor does it affect our consideration of the
proposed and final standards.
1962 Because premature mortality typically constitutes the vast majority of monetized benefits in a PM2 5 benefits
assessment, we present PM benefits based on risk estimates reported from two different long-term exposure studies
using different cohorts to account for uncertainty in the benefits associated with avoiding PM-related premature
deaths (see RIA Chapter 7.2.2).
1963 U.S. Environmental Protection Agency (U.S. EPA). 2018. Estimating the Benefit per Ton of Reducing PM2 5
Precursors from 17 Sectors. Available at: https://www.epa.gov/sites/default/files/2018-
02/documents/sourceapportionmentbpttsd_2018.pdf.
1964 U.S. Environmental Protection Agency (U.S. EPA). 2023.Estimating the Benefit per Ton of Reducing Directly-
Emitted PM2.5, PM2.5 Precursors and Ozone Precursors from 21 Sectors. January. Available at:
https://www.epa.gOv/system/files/documents/2021-10/source-apportionment-tsd-oct-2021_0.pdf
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The mobile sector BPT estimates used in this final rule were published in 2019 but have been
updated to be consistent with the health benefits Technical Support Document (Benefits TSD)
that accompanied the 2023 PM NAAQS Reconsideration Proposal.1965 >1966>1967>1968 The Benefits
TSD details the approach used to estimate the PIVh.s-related benefits reflected in these BPTs. The
upstream EGU BPT estimates used in this final rule were also recently updated to be consistent
with the Benefits TSD.1969 We multiply these BPT values by national reductions in annual
emissions in tons to estimate the total monetized human health benefits associated with the final
rule.
Our procedure for calculating BPT values follows three steps:
1. Using source apportionment photochemical modeling, predict annual average ambient
concentrations of NOx, SO2 and primary PM2.5 that are attributable to each source sector
(Onroad Heavy-Duty Diesel, Onroad Heavy-Duty Gas, EGUs, and refineries), for the
Continental U.S. (48 states). This yields the estimated ambient pollutant concentrations to
which the U.S. population is exposed.
2. For each sector, estimate the health impacts, and economic value of those impacts,
associated with the attributable ambient concentrations of NOx, SO2 and primary PM2.5
using the environmental Benefits Mapping and Analysis Program-Community Edition
(BenMAP-CE).1970 This yields the estimated total monetized value of health effects
associated with exposure to the relevant pollutants by sector.
3. For each sector, divide the monetary value of health impacts by the inventory of
associated precursor emissions. That is, primary PM2.5 benefits for a given sector are
divided by direct PM2.5 emissions from that same sector, sulfate benefits are divided by
SO2 emissions, and nitrate benefits are divided by NOx emissions. This yields the
estimated monetary value of one ton of sector-specific direct PM2.5 SO2 or NOx
emissions.
The quantified and monetized PM2.5 health categories that are included in the BPT values are
summarized in Table 7-5. Table 7-17 in Section 7.2.6 lists a sampling of the PM2.5, ozone, and
1965 Note that the Final PM NAAQS Reconsideration, released in February 2024, based its benefits analysis on the
same Benefits TSD that accompanied the PM NAAQS Reconsideration proposal.
1966 Wolfe, P.; Davidson, K.; Fulcher, C.; Fann, N.; Zawacki, M.; Baker, K. R. 2019. Monetized Health Benefits
Attributable to Mobile Source Emission Reductions across the United States in 2025. Sci. Total Environ. 650, 2490-
2498. Available at: https://doi.Org/10.1016/J.SCITOTENV.2018.09.273.
1967 U.S. Environmental Protection Agency (U.S. EPA). 2022. 2022 PM NAAQS Reconsideration Proposal RIA.
EPA-HQ-OAR-2019-0587.
1968U.S. Environmental Protection Agency (U.S. EPA). 2021. Estimating PM25- and Ozone-Attributable Health
Benefits. Technical Support Document (TSD) for the 2023 PM NAAQS Reconsideration Proposal." EPA-HQ-OAR-
2019-0587.
1969 U.S. Environmental Protection Agency (U.S. EPA). 2023. Technical Support Document: Estimating the Benefit
per Ton of Reducing Directly-Emitted PM25, PM25 Precursors and Ozone Precursors from 21 Sectors.
1970 BenMAP-CE is an open-source computer program developed by the EPA that calculates the number and
economic value of air pollution-related deaths and illnesses. The software incorporates a database that includes
many of the concentration-response relationships, population files, and health and economic data needed to quantify
these impacts. Information on BenMAP is found at: https://www.epa.gov/benmap/benmap-community-edition, and
the source code is available at: https://github.eom/BenMAPCE/BenMAP-CE.
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air toxics health categories that are not quantified and monetized by the BPT approach and are
therefore not included in the estimated benefits analysis for this rulemaking.
Table 7-5 Human Health Effects of PM2.5
Pollutant Effect (age)
Effect
Quantified
Effect
Monetized
More
Information
Adult premature mortality based on cohort study
PM ISA
estimates (>17 or >64)
Infant mortality (<1)
PM ISA
Non-fatal heart attacks (>18)
PM ISA
Hospital admissions - cardiovascular (all)
PM ISA
Hospital admissions - respiratory (<19 and >64)
PM ISA
Hospital admissions - Alzheimer's disease (>64)
PM ISA
Hospital admissions - Parkinson's disease (>64)
PM ISA
Emergency department visits - cardiovascular (all)
PM ISA
Emergency department visits - respiratory (all)
PM ISA
Emergency hospital admissions (>65)
PM ISA
Non-fatal lung cancer (>29)
PM ISA
PM? s Stroke incidence (50-79)
PM ISA
New onset asthma (<12)
PM ISA
Exacerbated asthma - albuterol inhaler use (asthmatics,
6-13)
PM ISA
Lost work days (18-64)
PM ISA
Other cardiovascular effects (e.g., doctor's visits,
prescription medication)
—
—
PM ISA1
Other respiratory effects (e.g., pulmonary function,
PM ISA1
other ages)
Other cancer effects (e.g., mutagenicity, genotoxicity)
—
—
PM ISA1
Other nervous system effects (e.g., dementia)
—
—
PM ISA1
Metabolic effects (e.g., diabetes, metabolic syndrome)
—
—
PM ISA1
Reproductive and developmental effects (e.g., low birth
PM ISA1
weight, pre-term births)
1 We assess these benefits qualitatively due to epidemiological or economic data limitations.
Of the PM-related health endpoints listed in Table 7-5, EPA estimates the incidence of air
pollution effects for only those classified as either "causal" or "likely-to-be-causal" in the 2019
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PM Integrated Science Assessment (ISA) and the 2022 PM ISA update.1971-1972-1973 The full
complement of human health effects associated with PM remains unquantified because of current
limitations in methods or available data. Thus, our quantified PM-related benefits omit a number
of known or suspected health effects linked with PM, either because appropriate health impact
functions are not available or because outcomes are not easily interpretable (e.g., changes in
heart rate variability).
We anticipate the final program will also yield benefits from reduced exposure to ambient
concentrations of ozone. However, the complex, non-linear photochemical processes that govern
ozone formation prevent us from developing reduced-form ozone BPT values for mobile
sources. This BPT approach also omits health effects associated with ambient concentrations of
NO2 as well as criteria pollutant-related welfare effects such as improvements in visibility,
reductions in materials damage, ecological effects from reduced PM deposition, ecological
effects from reduced nitrogen emissions, and vegetation effects from reduced ozone exposure. A
list of these unquantified benefits can be found in Table 7-17.
We also do not provide estimated monetized benefits due to reductions in mobile source air
toxics. This is because currently available tools and methods to assess air toxics risk from mobile
sources at the national scale are not adequate for extrapolation to incidence estimation or benefits
assessment.
7.2.2 Estimating PM2.5-attributable Adult Premature Death
Of the PM2.5-related health endpoints listed in Table 7-5, adult premature deaths typically
account for the majority of total monetized PM benefits and are thus the primary component of
the PM2.5-related BPT values. In this section, we provide more detail on PM mortality effect
coefficients and the concentration-response functions that underlie the BPT values.
A substantial body of published scientific literature documents the association between PM2.5
concentrations and the risk of premature death.1974'1975 This body of literature reflects thousands
1971 U.S. EPA. 2019. Integrated Science Assessment (ISA) for Particulate Matter (Final Report). U.S. Environmental
Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment.
Research Triangle Park, NC. U.S. EPA. EPA/600/R-19/188. December 2019. Available at:
https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review.
1972U.S. EPA. 2022. Supplement to the 2019 Integrated Science Assessment for Particulate Matter (Final Report).
U.S. Environmental Protection Agency, Office of Research and Development, Center for Public Health and
Environmental Assessment. Research Triangle Park, NC. U.S. EPA. EPA/600/R-22/028. May 2022. Available at:
https://www.epa.gov/isa/integrated-science-assessment-isa-particulate-matter.
1973 The ISA synthesizes the toxicological, clinical and epidemiological evidence to determine whether each
pollutant is causally related to an array of adverse human health outcomes associated with either acute (i.e., hours-
or days-long) or chronic (i.e., years-long) exposure. For each outcome, the ISA reports this relationship to be causal,
likely to be causal, suggestive of a causal relationship, inadequate to infer a causal relationship, or not likely to be a
causal relationship.
1974U.S. EPA. 2019. Integrated Science Assessment (ISA) for Particulate Matter (Final Report). U.S. Environmental
Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment.
Research Triangle Park, NC. U.S. EPA. EPA/600/R-19/188. December 2019. Available at:
https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review.
1975U.S. EPA. 2022. Supplement to the 2019 Integrated Science Assessment for Particulate Matter (Final Report).
U.S. Environmental Protection Agency, Office of Research and Development, Center for Public Health and
Environmental Assessment. Research Triangle Park, NC. U.S. EPA. EPA/600/R-22/028. May 2022. Available at:
https://www.epa.gov/isa/integrated-science-assessment-isa-particulate-matter.
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of epidemiology, toxicology, and clinical studies. The PM ISA, completed as part of the review
of the recently finalized PM NAAQS reconsideration and reviewed by the Clean Air Scientific
Advisory Committee (CASAC),1976 concluded that there is a causal relationship between
mortality and both long-term and short-term exposure to PM2.5 based on the full body of
scientific evidence. The size of the mortality effect estimates from epidemiologic studies, the
serious nature of the effect itself, and the high monetary value ascribed to prolonging life make
mortality risk reduction the most significant health endpoint quantified in this analysis. EPA
selects Hazard Ratios from cohort studies to estimate counts of PM-related premature death,
following a systematic approach detailed in the Benefits TSD.
For adult PM-related mortality, the BPT values are based on the risk estimates from two
alternative long-term exposure mortality studies: the National Health Interview Survey (NHIS)
cohort study (Pope III et al., 2019) and an extended analysis of the Medicare cohort (Wu et al.,
2020). 1977>1978 in past analyses, EPA has used two alternate estimates of mortality: one from the
American Cancer Society cohort and one from the Medicare cohort (Turner et al., 2016 and Di et
al., 2017, respectively).1979'1980 We use a risk estimate from Pope III et al., 2019 study in place of
the risk estimate from the Turner et al., 2016 analysis, as it: (1) includes a longer follow-up
period that includes more recent (and lower) PM2.5 concentrations; (2) the NHIS cohort is more
representative of the U.S. population than is the ACS cohort with respect to the distribution of
individuals by race, ethnicity, income and education.
Based on the 2022 Supplement to the PM ISA,1981 EPA substituted a risk estimate from Wu
et al., 2020 in place of a risk estimate from Di et al., 2017. These two epidemiologic studies
share many attributes, including the cohort and model used to characterize population exposure
to PM2.5. As compared to Di et al., 2017, Wu et al., 2020 includes a longer follow-up period and
reflects more recent PM2.5 concentrations.
The PM ISA also concluded that the scientific literature supports the use of a no-threshold
log-linear model to portray the PM-mortality concentration-response relationship while
recognizing potential uncertainty about the exact shape of the concentration-response
relationship. The 2019 PM ISA, which informed the final 2024 PM NAAQS Reconsideration,
reviewed available studies that examined the potential for a population-level threshold to exist in
1976 Sheppard, EL (2022). Letter from Elizabeth A. (Lianne) Sheppard, Chair, Clean Air Scientific Advisory
Committee, to Administrator Michale Regan. Re:CASAC Review of the EPA's Supplement to the 2019 Integrated
Science Assessment for Particulate Matter (External Review Draft - October 2021). March 18, 2022. EPA-CASAC-
22-001. Office of the Adminstrator, Science Advisory Board Washington, DC.
1977 Pope III, CA, Lefler, JS, Ezzati, M, Higbee, JD, Marshall, JD, Kim, S-Y, Bechle, M, Gilliat, KS, Vernon, SE and
Robinson, AL (2019). Mortality risk and fine particulate air pollution in a large, representative cohort of US adults.
Environmental health perspectives 127(7): 077007.
1978 Wu, X, Braun, D, Schwartz, J, Kioumourtzoglou, M and Dominici, F (2020). Evaluating the impact of long-term
exposure to fine particulate matter on mortality among the elderly. Science advances 6(29): eaba5692.
1979 Turner, MC, Jerrett, M, Pope, A, III, Krewski, D, Gapstur, SM, Diver, WR, Beckerman, BS, Marshall, JD, Su, J,
Crouse, DL and Burnett, RT (2016). Long-term ozone exposure and mortality in a large prospective study.
American Journal of Respiratory and Critical Care Medicine 193(10): 1134-1142.
1980 Di, Q, Wang, Y, Zanobetti, A, Wang, Y, Koutrakis, P, Choirat, C, Dominici, F and Schwartz, JD (2017). Air
pollution and mortality in the Medicare population. New England Journal of Medicine 376(26): 2513-2522.
1981 U.S. EPA. 2022. Supplement to the 2019 Integrated Science Assessment for Particulate Matter (Final Report).
U.S. Environmental Protection Agency, Office of Research and Development, Center for Public Health and
Environmental Assessment. Research Triangle Park, NC. U.S. EPA. EPA/600/R-22/028. May 2022. Available at:
https://www.epa.gov/isa/integrated-science-assessment-isa-particulate-matter.
769
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the concentration-response relationship. Based on such studies, the ISA concluded that "evidence
from recent studies reduce uncertainties related to potential co-pollutant confounding and
continues to provide strong support for a linear, no-threshold concentration-response
relationship." 1982 Consistent with this evidence, the Agency historically has estimated health
impacts above and below the prevailing NAAQS.
7.2.3 Economic Value of Health Benefits
The BPT values used in this analysis are a reduced-form approach for relating emission
reductions to reductions in ambient concentrations of PM2.5 and associated improvements in
human health. Reductions in ambient concentrations of air pollution generally decrease the risk
of future adverse health effects by a small amount for a large population. To monetize these
benefits, the appropriate economic measure is willingness to pay (WTP) for changes in risk of a
health effect. For some health effects, such as hospital admissions, WTP estimates are generally
not available, so we use the cost of treating or mitigating the effect. These cost-of-illness (COI)
estimates generally (although not necessarily in every case) understate the true value of
reductions in risk of a health effect. They tend to reflect the direct expenditures related to
treatment, but not the value of avoided pain and suffering from the health effect. The WTP and
COI unit values for each endpoint are provided in the Benefits TSD. These unit values were used
to monetize the underlying health effects included in the PM2.5 BPT values.
Avoided premature deaths typically account for the majority of monetized PM2.5-related
benefits. The economics literature concerning the appropriate methodology for valuing
reductions in premature mortality risk is still developing and is the subject of continuing
discussion within the economics and public policy analysis community. Following the advice of
the SAB's Environmental Economics Advisory Committee (SAB-EEAC), EPA currently uses
the value of statistical life (VSL) approach in calculating estimates of mortality benefits. This
calculation provides the most reasonable single estimate of an individual's WTP for reductions
in mortality risk.1983 The VSL approach is a summary measure for the value of small changes in
mortality risk experienced by a large number of people.
EPA consulted several times with the SAB-EEAC on valuing mortality risk reductions and
continues work to update the Agency's guidance on the issue. Until updated guidance is
available, EPA determined that a single, peer-reviewed estimate applied consistently best reflects
the SAB-EEAC advice we have received. Therefore, EPA applies the VSL that was vetted and
endorsed by the SAB in the Agency's Guidelines for Preparing Economic Analyses.1984 The
mean VSL across these studies is $4.8 million (1990$). We then adjust this VSL to account for
the currency year and to account for income growth from 1990 to the analysis year. Specifically,
the VSL applied in this analysis in 2022 dollars after adjusting for income growth to 2022 is
$12.6 million.
1982U.S. EPA. 2019. Integrated Science Assessment (ISA) for Particulate Matter (Final Report). U.S. Environmental
Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment.
Research Triangle Park, NC. U.S. EPA. EPA/600/R-19/188. December 2019. Available at:
https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review.
1983 U.S. EPA-SAB. 2000. An SAB Report onEPA's White Paper Valuing the Benefits of Fatal Cancer Risk
Reduction. Available at: https://www.epa.gov/system/files/documents/2022-03/86189901_0.pdf.
1984U.S. EPA. 2016. Guidelines for Preparing Economic Analyses. Available at:
https://www.epa.gov/sites/default/files/2017-08/documents/ee-0568-50.pdf.
770
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EPA is committed to using scientifically sound, appropriately reviewed evidence in valuing
changes in the risk of premature death and continues to engage with the SAB to identify
scientifically sound approaches to update its mortality risk valuation estimates. Most recently,
the Agency proposed new meta-analytic approaches for updating its estimates, which were
subsequently reviewed by the SAB-EEAC.1985 EPA is taking the SAB's formal
recommendations under advisement.
7.2.4 Health Benefits Results
The value of health benefits from reductions in PM2.5 emissions associated with this final rule
were estimated by multiplying PM2.5-related BPT values by the corresponding annual reduction
in tons of directly-emitted PM2.5 and PM2.5 precursor emissions (NOx and SO2). As explained
above, the PM2.5 BPT values represent the monetized value of human health benefits, including
reductions in both premature mortality and nonfatal illnesses. Table 7-6 presents the PM2.5 BPT
values estimated from two different PM-related premature mortality cohort studies, Wu et al.,
2020 (the Medicare cohort study) and Pope III et al., 2019 (the NHIS cohort study). The table
reports different values by source and pollutant because different pollutant emissions do not
equally contribute to ambient PM2.5 formation and different emissions sources do not equally
contribute to population exposure and associated health impacts. BPT values are also estimated
using either a 3-percent or 7-percent discount rate to account for avoided health outcomes that
are expected to accrue over more than a single year (the "cessation lag" between the change in
PM exposures and the total realization of changes in health effects). The source sectors include:
onroad heavy-duty diesel trucks, onroad heavy-duty gasoline trucks, electricity generating units
(EGUs), and refineries.
Table 7-7 and Table 7-8 present the NOx, SO2 and direct PM2.5 emission reductions, and
associated monetized PM2.5-related health benefits, of the final program for heavy-duty diesel
and heavy-duty gasoline vehicles, respectively. Benefits for each heavy-duty vehicle type (diesel
or gasoline engine) are presented for the stream of years beginning with the first year of rule
implementation, 2027, through 2055. The tables also include the present value (PV) and
annualized value (AV) of the stream of benefits over this time series, discounted using both 3-
percent and 7-percent discount rates. Table 7-9 presents the NOx, SO2, and direct PM2.5
emissions increases, and associated monetized PM2.5-related health impacts, for EGUs for the
final rule. Table 7-10presents the NOx, SO2, and direct PM2.5 emissions reductions, and
associated monetized PM2.5-related health benefits, from refineries for the final rule.
Table 7-11 presents the total net PM2.5-related benefits (onroad heavy-duty vehicles and
upstream) for the final rule. Table 7-12 through Table 7-16 present similar results for the
alternative.
1985U.S. EPA. 2017. SAB Review of EPA's Proposed Methodology for Updating Mortality Risk Valuation
Estimates for Policy Analysis. Available at:
https://nepis. epa.gov/Exe/ZyPDF. cgi/P100ROQR.PDF?Dockey=P100ROQR.PDF.
771
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Table 7-6 PIVh.s-related Benefit Per Ton values (2022$) associated with the changes of NOx, SO2 and directly
emitted PM2.5 emissions for (A) Onroad Heavy-Duty Diesel Vehicles, (B) Onroad Heavy-Duty Gasoline
Vehicles, (C) Electricity Generating Units, and (D) Refineries.
A. Onroad Heavy-Duty Diesel
NOx
S02
Direct PM
3% Discount Rate
7% Discount Rate
3% Discount Rate
7% Discount Rate
3% Discount Rate
7% Discount Rate
Wu
Pope
Wu
Pope
Wu
Pope
Wu
Pope
Wu
Pope
Wu
Pope
2025
$7,070
$15,000
$6,350
$13,500
$299,000
$ 643,000
$269,000
$578,000
$468,000
$1,010,000
$420,000
$ 904,000
2030
$7,950
$16,400
$7,140
$14,700
$341,000
$ 709,000
$306,000
$637,000
$534,000
$1,110,000
$479,000
$ 996,000
2035
$8,930
$18,000
$8,020
$16,200
$390,000
$ 790,000
$350,000
$710,000
$609,000
$1,230,000
$547,000
$1,110,000
2040
$9,740
$19,300
$8,750
$17,300
$436,000
$ 867,000
$392,000
$780,000
$680,000
$1,350,000
$611,000
$1,220,000
2045
$10,300
$20,200
$9,270
$18,200
$476,000
$ 936,000
$428,000
$842,000
$741,000
$1,460,000
$666,000
$1,310,000
2050
$10,700
$20,700
$9,590
$18,700
$510,000
$ 991,000
$458,000
$892,000
$792,000
$1,540,000
$711,000
$1,380,000
2055
$11,100
$21,400
$9,970
$19,200
$547,000
$1,050,000
$491,000
$947,000
$846,000
$1,630,000
$760,000
$1,460,000
B. Onroad Heavy-Duty Gasoline
NOx
S02
Direct PM
3% Discount Rate
7% Discount Rate
3% Discount Rate
7% Discount Rate
3% Discount Rate
7% Discount Rate
Wu
Pope
Wu
Pope
Wu
Pope
Wu
Pope
Wu
Pope
Wu
Pope
2025
$6,970
$14,800
$6,260
$13,300
$161,000
$344,000
$144,000
$310,000
$614,000
$1,310,000
$551,000
$1,180,000
2030
$7,850
$16,100
$7,050
$14,500
$183,000
$379,000
$164,000
$340,000
$700,000
$1,450,000
$629,000
$1,300,000
2035
$8,840
$17,700
$7,940
$16,000
$208,000
$421,000
$187,000
$379,000
$801,000
$1,620,000
$720,000
$1,450,000
2040
$9,670
$19,100
$8,690
$17,200
$232,000
$461,000
$209,000
$415,000
$895,000
$1,770,000
$804,000
$1,590,000
2045
$10,300
$20,100
$9,240
$18,100
$253,000
$496,000
$227,000
$446,000
$976,000
$1,910,000
$877,000
$1,720,000
2050
$10,700
$20,700
$9,600
$18,600
$269,000
$523,000
$242,000
$471,000
$1,040,000
$2,020,000
$936,000
$1,820,000
2055
$11,100
$21,500
$10,000
$19,300
$288,000
$554,000
$259,000
$498,000
$1,110,000
$2,130,000
$997,000
$1,920,000
C. Electricity Generating Units (EGUs)
NOx SO2 Direct PM
3% Discount Rate 7% Discount Rate 3% Discount Rate 7% Discount Rate 3% Discount Rate 7% Discount Rate
Wu Pope Wu Pope Wu Pope Wu Pope Wu Pope Wu Pope
2025
$8,450
$17,900
$7,590
$16,100
$62,400
$133,000
$56,200
$120,000
$124,000
$266,000
$111,000
$239,000
2030
$9,460
$19,300
$8,510
$17,400
$70,400
$146,000
$63,300
$131,000
$141,000
$292,000
$127,000
$262,000
2035
$10,600
$21,100
$9,520
$19,100
$79,000
$159,000
$71,100
$144,000
$161,000
$325,000
$145,000
$292,000
2040
$11,500
$22,600
$10,300
$20,400
$86,400
$172,000
$77,700
$154,000
$179,000
$355,000
$161,000
$320,000
D. Refineries
NOx SO2 Direct PM
3% Discount Rate 7% Discount Rate 3% Discount Rate 7% Discount Rate 3% Discount Rate 7% Discount Rate
Wu Pope Wu Pope Wu Pope Wu Pope Wu Pope Wu Pope
2025
$25,400
$54,600
$22,800
$49,100
$56,100
$121,000
$50,300
$109,000
$405,000
$878,000
$364,000
$789,000
2030
$28,000
$58,200
$25,200
$52,400
$62,000
$129,000
$55,600
$116,000
$447,000
$934,000
$401,000
$840,000
2035
$32,200
$65,000
$28,900
$58,600
$70,900
$144,000
$63,800
$130,000
$512,000
$1,040,000
$460,000
$940,000
2040
$36,100
$71,600
$32,500
$64,300
$79,300
$158,000
$71,200
$142,000
$576,000
$1,150,000
$518,000
$1,030,000
Notes: All estimates are rounded to three significant figures. The benefit-per-ton (BPT) estimates presented in this table assume
either a 3 percent or 7 percent discount rate in the valuation of premature mortality to account for a twenty-year segmented
cessation lag. BPT values were estimated for the years 2025, 2030, 2035, 2040, 2045, 2050, and 2055 for mobile sources, and
for years 2025, 2030, 2035, and 2040 for EGUs and refineries. We interpolate values for intervening years (e.g., the 2032 BPT
values are linearly interpolated using BPT values for 2030 and 2035) and hold values constant past 2040 for EGU and refinery
BPTs.
772
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Table 7-7 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Heavy-Duty
Diesel Vehicles and the associated monetized PIVh.s-related health benefits (millions, 2022$) for the final
program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
97
$0.72-1.5
$0.65-1.4
1.2
$0.37-0.79
$0.34-0.71
1.5
$0.72-1.5
$0.64-1.4
2028
260
$2.0-4.1
$1.8-3.7
3.1
$1.0-2.1
$0.91-1.9
3.2
$1.6-3.5
$1.5-3.1
2029
480
$3.7-7.7
$3.4-7
5.8
$1.9-4
$1.7-3.6
5.3
$2.8-5.8
$2.5-5.2
2030
890
$7.1-15
$6.4-13
11
$3.8-7.9
$3.4-7.1
9.0
$4.8-9.9
$4.3-8.9
2031
1,800
$15-30
$13-27
23
$8.1-17
$7.2-15
17
$9.4-19
$8.4-17
2032
3,500
$29-60
$26-54
44
$16-33
$14-30
32
$18-37
$16-33
2033
5,200
$45-91
$40-82
66
$24-50
$22-45
46
$27-54
$24-49
2034
7,200
$63-130
$57-110
86
$33-67
$29-60
60
$36-72
$32-65
2035
9,700
$87-170
$78-160
110
$41-84
$37-75
74
$45-91
$41-82
2036
13,000
$120-240
$110-210
120
$50-100
$45-90
88
$55-110
$49-100
2037
17,000
$160-310
$140-280
140
$58-120
$52-100
100
$65-130
$58-120
2038
22,000
$200-410
$180-370
160
$65-130
$59-120
120
$76-150
$68-140
2039
26,000
$250-500
$230-450
170
$73-140
$65-130
130
$86-170
$78-150
2040
30,000
$300-590
$270-530
180
$79-160
$71-140
140
$97-190
$87-170
2041
34,000
$340-670
$300-600
190
$86-170
$77-150
150
$110-210
$96-190
2042
38,000
$380-740
$340-670
200
$92-180
$82-160
160
$120-230
$100-210
2043
41,000
$410-800
$370-720
210
$97-190
$87-170
170
$120-240
$110-220
2044
43,000
$440-860
$390-770
220
$100-200
$91-180
180
$130-260
$120-230
2045
45,000
$460-900
$410-810
220
$110-210
$95-190
190
$140-270
$120-240
2046
46,000
$480-940
$430-850
220
$110-210
$97-190
190
$140-280
$130-250
2047
47,000
$500-970
$450-870
230
$110-220
$100-200
190
$150-290
$130-260
2048
48,000
$510-990
$460-890
230
$110-220
$100-200
190
$150-290
$130-260
2049
49,000
$520-1000
$470-910
230
$120-230
$100-200
200
$150-300
$140-270
2050
50,000
$530-1000
$480-930
230
$120-230
$110-210
200
$160-300
$140-270
2051
50,000
$540-1100
$490-950
230
$120-230
$110-210
200
$160-310
$140-280
2052
51,000
$550-1100
$500-960
230
$120-240
$110-210
200
$160-320
$150-280
2053
51,000
$560-1100
$500-980
230
$120-240
$110-220
200
$170-320
$150-290
2054
52,000
$570-1100
$510-990
230
$130-240
$110-220
200
$170-330
$150-290
2055
52,000
$570-1100
$520-1000
230
$130-250
$110-220
200
$170-330
$150-300
PV
$4,700-9,200
$2,000-4,000
$1,200-2,400
$540-1,100
$1,500-3,000
$680-1,300
AV
$250-480
$170-320
$62-120
$44-87
$79-160
$55-110
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the
NHIS study (Pope III et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values presented here are not discounted.
The present value of benefits is the total aggregated value of the series of discounted annual benefits that occur between 2027-2055 (in 2022 dollars) using
either a 3% or 7% discount rate.
773
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Table 7-8 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Heavy-Duty
Gasoline Vehicles and the associated monetized PM2.s-related health benefits (millions, 2022$) for the final
program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
49
$0.36-0.75
$0.32-0.67
1.1
$0.19-0.4
$0.17-0.36
2.4
$1.5-3.2
$1.4-2.9
2028
100
$0.75-1.6
$0.68-1.4
2.2
$0.38-0.8
$0.34-0.72
4.7
$3.1-6.5
$2.8-5.9
2029
150
$1.2-2.4
$1-2.2
3.2
$0.57-1.2
$0.51-1.1
7.0
$4.8-9.9
$4.3-8.9
2030
200
$1.6-3.3
$1.4-3
4.2
$0.76-1.6
$0.68-1.4
9.3
$6.5-13
$5.9-12
2031
340
$2.7-5.6
$2.5-5
6.6
$1.2-2.6
$1.1-2.3
16
$12-24
$10-21
2032
540
$4.5-9.1
$4-8.2
11
$2.1-4.2
$1.9-3.8
26
$19-39
$17-35
2033
740
$6.2-13
$5.6-11
14
$2.9-5.8
$2.6-5.2
35
$27-54
$24-49
2034
920
$7.9-16
$7.1-14
18
$3.6-7.3
$3.2-6.5
43
$34-68
$30-61
2035
1,100
$9.7-19
$8.7-17
20
$4.2-8.5
$3.8-7.7
52
$42-84
$38-76
2036
1,300
$12-23
$10-21
23
$4.8-9.7
$4.4-8.8
62
$51-100
$46-92
2037
1,500
$13-27
$12-24
25
$5.4-11
$4.9-9.8
72
$60-120
$54-110
2038
1,600
$15-30
$14-27
27
$6-12
$5.4-11
81
$69-140
$62-120
2039
1,800
$17-33
$15-30
29
$6.5-13
$5.8-12
88
$77-150
$69-140
2040
1,900
$18-36
$17-33
30
$7-14
$6.3-13
95
$85-170
$76-150
2041
2,000
$20-39
$18-35
31
$7.4-15
$6.7-13
100
$92-180
$83-160
2042
2,100
$21-41
$19-37
33
$7.8-16
$7.1-14
110
$99-200
$89-180
2043
2,200
$22-43
$20-39
34
$8.2-16
$7.4-15
110
$110-210
$95-190
2044
2,300
$23-45
$21-41
34
$8.5-17
$7.6-15
120
$110-220
$100-200
2045
2,300
$24-47
$21-42
35
$8.8-17
$7.9-16
120
$120-230
$100-200
2046
2,400
$25-48
$22-43
35
$9-18
$8.1-16
120
$120-230
$110-210
2047
2,400
$25-49
$23-44
36
$9.2-18
$8.3-16
120
$120-240
$110-220
2048
2,400
$26-50
$23-45
36
$9.4-18
$8.4-16
130
$130-250
$110-220
2049
2,500
$26-51
$24-46
36
$9.6-19
$8.6-17
130
$130-250
$120-230
2050
2,500
$27-52
$24-46
36
$9.7-19
$8.8-17
130
$130-260
$120-230
2051
2,500
$27-52
$24-47
36
$9.9-19
$8.9-17
130
$140-260
$120-240
2052
2,500
$27-53
$25-48
36
$10-19
$9.1-18
130
$140-270
$130-240
2053
2,500
$28-54
$25-48
36
$10-20
$9.2-18
130
$140-270
$130-250
2054
2,500
$28-54
$25-49
36
$10-20
$9.3-18
130
$140-280
$130-250
2055
2,500
$28-54
$25-49
36
$10-20
$9.4-18
130
$140-280
$130-250
PV
$280-540
$130-250
$110-210
$49-98
$1,300-2,600
$600-1,200
AV
$14-28
$10-20
$5.5-11
$4.0-8.0
$69-140
$49-96
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the NHIS
study (Pope III et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values presented here are not discounted. The present
value of benefits is the total aggregated value of the series of discounted annual benefits that occur between 2027-2055 (in 2022 dollars) using either a 3% or 7%
discount rate.
774
-------
Table 7-9 Summary of the estimated tons of increased NOx, SO2 and direct PM2.5 per year from EGUs and
the associated monetized PIVh.s-related health impacts (millions, 2022$) for the final program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
83
$(0.73)-(1.5)
$(0.66)-(1.4)
100
$(6.5)-(14)
$(5.9)-(12)
12
$(1.6)-(3.3)
$(1.4)-(3.0)
2028
220
$(2.0)-(4.1)
$(1.8)-(3.7)
260
$(18)-(37)
$(16)-(34)
32
$(4.3)-(9.0)
$(3.9)-(8.1)
2029
410
$(3.8)-(7.8)
$(3.4)-(7.1)
500
$(34)-(71)
$(31)-(64)
60
$(8.3)-(17)
$(7.4)-( 15)
2030
890
$(8.4)-(17)
$(7.6)-(15)
1,100
$(75)-(160)
$(68)-(140)
130
$(18)-(38)
$(16)-(34)
2031
1,900
$(19)-(38)
$(17)-(34)
2,300
$(170)-(350)
$(150)-(310)
280
$(41)-(84)
$(37)-(76)
2032
3,900
$(39)-(79)
$(35)-(71)
4,700
$(350)-(710)
$(310)-(640)
570
$(85)-(170)
$(76)-(160)
2033
5,900
$(60)-(120)
$( 54)-( 110)
7,100
$(540)-(l 100)
$(480)-(980)
860
$(130)-(270)
$(120)-(240)
2034
7,800
$(81)-(160)
$(73)-( 150)
9,400
$(730)-( 1500)
$(660)-(1300)
1,100
$(180)-(360)
$(160)-(330)
2035
9,700
$(100)-(210)
$(93)-(190)
12,000
$(930)-(1900)
$(830)-(1700)
1,400
$(230)-(460)
$(210)-(410)
2036
9,500
$(100)-(200)
$(92)-( 180)
11,000
$(910)-(1800)
$(820)-(1700)
1,400
$(230)-(470)
$(210)-(420)
2037
8,700
$(95)-(190)
$(85)-(170)
10,000
$(830)-(1700)
$(750)-(l 500)
1,300
$(220)-(440)
$(200)-(400)
2038
7,100
$(80)-(160)
$(71)-(140)
8,000
$(670)-(1300)
$(600)-(1200)
1,100
$(190)-(3 80)
$(170)-(350)
2039
5,000
$(57)-(l 10)
$(51 )-(l 00)
5,200
$(440)-(880)
$(400)-(790)
850
$(150)-(300)
$(130)-(270)
2040
2,400
$(28)-(55)
$(25)-(49)
1,800
$(150)-(300)
$(140)-(270)
510
$(92)-( 180)
$(82)-(160)
2041
2,300
$(27)-(53)
$(24)-(47)
1,600
$(140)-(280)
$(130)-(250)
540
$(96)-(190)
$(87)-(170)
2042
2,200
$(25)-(50)
$(23)-(45)
1,400
$(120)-(250)
$(110)-(220)
560
$(100)-(200)
$(90)-(180)
2043
2,000
$(23)-(46)
$(21)-(41)
1,200
$( 100)-(210)
$(93)-(180)
580
$( 100)-(210)
$(93)-(190)
2044
1,800
$(21)-(41)
$(19)-(37)
940
$(81)-(160)
$(73)-(140)
590
$(110)-(210)
$(95)-(190)
2045
1,600
$(18)-(36)
$(16)-(32)
650
$(56)-(l 10)
$(50)-(100)
600
$(110)-(210)
$(96)-(190)
2046
1,600
$(18)-(36)
$(16)-(32)
540
$(47)-(93)
$(42)-(83)
580
$( 100)-(210)
$(94)-(190)
2047
1,600
$(18)-(35)
$(16)-(32)
430
$(37)-(74)
$(33)-(66)
570
$(100)-(200)
$(91)-(180)
2048
1,500
$(18)-(35)
$(16)-(31)
310
$(27)-(53)
$(24)-(48)
550
$(98)-(190)
$(88)-(170)
2049
1,500
$(18)-(34)
$(16)-(31)
190
$(16)-(33)
$(15)-(29)
530
$(94)-(190)
$(84)-(170)
2050
1,500
$(17)-(34)
$(15)-(30)
68
$(5.8)-(12)
$(5.3)-(10)
500
$(90)-( 180)
$(81)-(160)
2051
1,500
$(17)-(34)
$(16)-(31)
68
$(5.9)-(12)
$(5.3)-(10)
510
$(91)-( 180)
$(82)-(160)
2052
1,500
$(17)-(34)
$(16)-(31)
68
$(5.9)-(12)
$(5.3)-(ll)
510
$(91)-( 180)
$(82)-(160)
2053
1,500
$(17)-(34)
$(16)-(31)
69
$(5.9)-(12)
$(5.3)-(ll)
510
$(91)-( 180)
$(82)-(160)
2054
1,500
$(18)-(34)
$(16)-(31)
69
$(5.9)-(12)
$(5.3)-(ll)
510
$(92)-( 180)
$(82)-(160)
2055
1,500
$(18)-(34)
$(16)-(31)
69
$(5.9)-(12)
$(5.3)-(ll)
510
$(92)-( 180)
$(82)-(160)
PV
$(670)-(l,300)
$(600)-(l ,200)
$(4,800)-(9,700)
$(4,300)-(8,700)
$(2,000)-(3,900)
$( 1,800)-(3,500)
AV
$(35)-(69)
$(31)-(62)
$(250)-(510)
$(230)-(460)
$(100)-(200)
$(92)-(180)
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the NHIS study
(Pope III et al., 2019). A negative benefit value (in parentheses) implies an increase in adverse health outcomes. All benefits estimates are rounded to two significant
figures. Annual benefit values presented here are not discounted. The present value of benefits is the total aggregated value of the series of discounted annual benefits
that occur between 2027-2055 (in 2022 dollars) using either a 3% or 7% discount rate.
775
-------
Table 7-10 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Refineries
and the associated monetized PIVh.s-related health benefits (millions, 2022$) for the final program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
4.6
$0.12-0.26
$0.11-0.23
1.4
$0,081-0.17
$0,073-0.16
1.1
$0.46-0.98
$0.41-0.88
2028
9.5
$0.26-0.54
$0.23-0.49
2.9
$0.17-0.36
$0.15-0.33
2.3
$0.97-2.1
$0.87-1.8
2029
15
$0.41-0.85
$0.37-0.77
4.5
$0.27-0.57
$0.25-0.52
3.5
$1.5-3.2
$1.4-2.9
2030
22
$0.62-1.3
$0.55-1.1
6.7
$0.42-0.87
$0.37-0.78
5.1
$2.3-4.8
$2.1-4.3
2031
39
$1.1-2.3
$1.0-2.1
12
$0.77-1.6
$0.69-1.4
9.1
$4.2-8.7
$3.8-7.9
2032
69
$2.0-4.2
$1.8-3.8
21
$1.4-2.9
$1.3-2.6
16
$7.6-16
$6.8-14
2033
97
$3.0-6.0
$2.7-5.4
30
$2.0-4.1
$1.8-3.7
23
$11-23
$9.9-20
2034
120
$3.9-7.9
$3.5-7.1
38
$2.6-5.4
$2.4-4.9
29
$14-29
$13-26
2035
150
$4.8-9.6
$4.3-8.7
46
$3.2-6.6
$2.9-6.0
34
$18-36
$16-32
2036
170
$5.6-11
$5.0-10
53
$3.8-7.7
$3.4-7.0
39
$21-42
$19-38
2037
190
$6.4-13
$5.8-12
59
$4.4-8.8
$3.9-8.0
44
$24-48
$21-43
2038
210
$7.2-14
$6.5-13
65
$4.9-9.9
$4.4-8.9
48
$27-54
$24-48
2039
230
$8.0-16
$7.2-14
70
$5.4-11
$4.9-9.8
52
$29-59
$27-53
2040
240
$8.7-17
$7.8-16
75
$5.9-12
$5.3-11
56
$32-64
$29-58
2041
250
$9.2-18
$8.3-16
79
$6.2-12
$5.6-11
59
$34-68
$30-61
2042
270
$9.6-19
$8.6-17
82
$6.5-13
$5.9-12
61
$35-71
$32-64
2043
280
$9.9-20
$8.9-18
85
$6.7-13
$6.1-12
64
$37-73
$33-66
2044
280
$10-20
$9.2-18
87
$6.9-14
$6.2-12
65
$38-75
$34-67
2045
290
$10-21
$9.3-19
89
$7.1-14
$6.3-13
66
$38-77
$34-69
2046
290
$11-21
$9.5-19
90
$7.2-14
$6.4-13
68
$39-78
$35-70
2047
300
$11-21
$9.6-19
92
$7.3-15
$6.5-13
68
$39-79
$35-71
2048
300
$11-21
$9.7-19
92
$7.3-15
$6.6-13
69
$40-80
$36-71
2049
300
$11-22
$9.8-19
93
$7.4-15
$6.6-13
69
$40-80
$36-72
2050
300
$11-22
$9.9-20
94
$7.4-15
$6.7-13
70
$40-81
$36-72
2051
300
$11-22
$9.9-20
94
$7.4-15
$6.7-13
70
$40-81
$36-73
2052
310
$11-22
$9.9-20
94
$7.5-15
$6.7-13
70
$41-81
$36-73
2053
310
$11-22
$9.9-20
94
$7.5-15
$6.7-13
70
$41-81
$36-73
2054
300
$11-22
$9.9-20
94
$7.4-15
$6.7-13
70
$40-81
$36-73
2055
300
$11-22
$9.9-20
94
$7.4-15
$6.7-13
70
$40-81
$36-72
PV
$120-240
$110-220
$82-160
$74-150
$450-900
$400-800
AV
$6.3-13
$5.7-11
$4.3-8.6
$3.8-7.7
$23-47
$21-42
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020)
and the NHIS study (Pope III et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values presented here
are not discounted. The present value of benefits is the total aggregated value of the series of discounted annual benefits that occur between
2027-2055 (in 2022 dollars) using either a 3% or 7% discount rate.
776
-------
Table 7-11 Year-over-year monetized PIVh.s-related health benefits (millions, 2022$) associated with Onroad
Heavy-Duty Vehicle and upstream (EGU plus refinery) emissions from the final program
Total Onroad Benefits
Upstream
Benefits
Net Benefits
3%
7%
3%
7%
3%
7%
Discount Rate
Discount Rate
Discount Rate
Discount Rate
Discount Rate
Discount Rate
2027
$3.9-8.2
$3.5-7.4
$(8.2)-(17)
$(7.4)-( 15)
$(4.3)-(9.0)
$(3.9)-(8.1)
2028
$8.9-19
$8.0-17
$(23)-(47)
$(20)-(43)
$(14)-(29)
$(12)-(26)
2029
$15-31
$13-28
$(44)-(92)
$(40)-(82)
$(29)-(61)
$(26)-(54)
2030
$25-51
$22-46
$(99)-(200)
$(89)-( 180)
$(74)-( 150)
$(67)-(140)
2031
$48-98
$43-88
$(220)-(460)
$(200)-(410)
$(180)-(360)
$(160)-(320)
2032
$89-180
$80-160
$(460)-(940)
$(420)-(850)
$(370)-(760)
$(340)-(690)
2033
$130-270
$120-240
$(710)-(1,400)
$(640)-(l,300)
$(580)-(l,200)
$(520)-(l,100)
2034
$180-360
$160-320
$(970)-(2,000)
$(870)-(l,800)
$(790)-(l,600)
$(710)-(1,400)
2035
$230-460
$210-420
$(l,200)-(2,500)
$(l,100)-(2,200)
$(l,000)-(2,000)
$(900)-(l,800)
2036
$290-580
$260-520
$(l,200)-(2,500)
$(l,100)-(2,200)
$(930)-(l,900)
$(840)-(l,700)
2037
$360-720
$320-640
$(l,100)-(2,200)
$(l,000)-(2,000)
$(750)-(l,500)
$(680)-(l,400)
2038
$440-870
$390-780
$(900)-(l,800)
$(810)-(1,600)
$(470)-(940)
$(420)-(840)
2039
$510-1,000
$460-910
$(610)-(1,200)
$(550)-(l,100)
$(96)-(190)
$(87)-(170)
2040
$580-1,200
$520-1,000
$(230)-(450)
$(200)-(400)
$360-710
$320-640
2041
$650-1,300
$580-1,200
$(210)-(420)
$(190)-(380)
$440-860
$390-770
2042
$710-1,400
$640-1,300
$(200)-(390)
$(180)-(350)
$510-1,000
$460-910
2043
$760-1,500
$690-1,400
$(180)-(350)
$(160)-(320)
$590-1,200
$530-1,000
2044
$810-1,600
$730-1,400
$(150)-(300)
$(140)-(270)
$660-1,300
$590-1,200
2045
$850-1,700
$770-1,500
$(130)-(250)
$(110)-(220)
$730-1,400
$650-1,300
2046
$880-1,700
$800-1,600
$(110)-(220)
$(100)-(200)
$770-1,500
$690-1,400
2047
$910-1,800
$820-1,600
$(99)-(200)
$(89)-( 180)
$810-1,600
$730-1,400
2048
$940-1,800
$840-1,600
$(84)-(170)
$(76)-( 150)
$850-1,700
$770-1,500
2049
$960-1,900
$860-1,700
$(70)-(140)
$(62)-(120)
$890-1,700
$800-1,600
2050
$980-1,900
$880-1,700
$(55)-(l 10)
$(49)-(97)
$920-1,800
$830-1,600
2051
$1,000-1,900
$900-1,700
$(55)-(l 10)
$(49)-(98)
$940-1,800
$850-1,600
2052
$1,000-2,000
$910-1,800
$(56)-(l 10)
$(50)-(99)
$960-1,900
$860-1,700
2053
$1,000-2,000
$930-1,800
$(56)-(l 10)
$(50)-(99)
$970-1,900
$880-1,700
2054
$1,000-2,000
$940-1,800
$(56)-(l 10)
$(50)-(100)
$990-1,900
$890-1,700
2055
$1,100-2,000
$950-1,800
$(56)-(l 10)
$(51 )-(l 00)
$1,000-1,900
$900-1,700
PV
$9,100-18,000
$4,000-7,900
$(6,800)-(14,000)
$(4,100)-(8,300)
$2,300-4,200
$(110)-(400)
AV
$480-930
$330-650
$(350)-(710)
$(340)-(680)
$120-220
$(9.1)-(32)
Notes:
The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020)
and the NHIS study (Pope et al., 2019), respectively. All benefits estimates are rounded to two significant figures. Annual benefit values
presented here are not discounted. Negative values in parentheses are health disbenefits related to increases in estimated emissions. The
present value of benefits is the total aggregated value of the series of discounted annual benefits that occur between 2027-2055 (in 2022
dollars) using either a 3% or 7% discount rate. Depending on the discount rate used, the present and annualized value of the stream of
PM2.5 health benefits may either be positive or negative. The upstream impacts associated with the standards presented here include
health benefits associated with reduced criteria pollutant emissions from refineries and health disbenefits associated with increased
criteria pollutant emissions from EGUs. The benefits in this table also do not include the full complement of health and environmental
benefits (such as health benefits related to reduced ozone exposure) that, if quantified and monetized, would increase the total
monetized benefits.
777
-------
Table 7-12 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Heavy-Duty
Diesel Vehicles and the associated monetized PIVh.s-related health benefits (millions, 2022$) for the alternative
program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
51
$0.38-0.79
$0.34-0.71
0.60
$0.19-0.40
$0.17-0.36
0.64
$0.32-0.67
$0.29-0.61
2028
110
$0.87-1.8
$0.78-1.6
1.3
$0.44-0.92
$0.39-0.83
1.3
$0.67-1.4
$0.6-1.3
2029
240
$1.8-3.8
$1.6-3.4
2.8
$0.94-2.0
$0.85-1.8
2.4
$1.2-2.6
$1.1-2.3
2030
500
$4.0-8.2
$3.6-7.3
6.3
$2.1-4.4
$1.9-4.0
4.5
$2.4-5.0
$2.2-4.5
2031
940
$7.7-16
$6.9-14
12
$4.2-8.7
$3.8-7.9
8.0
$4.4-9.0
$3.9-8.1
2032
1,600
$13-27
$12-24
21
$7.4-15
$6.7-14
13
$7.4-15
$6.6-14
2033
2,300
$19-39
$17-35
29
$11-22
$9.5-20
18
$10-21
$9.3-19
2034
3,100
$27-54
$24-49
36
$14-28
$12-25
22
$13-27
$12-24
2035
4,100
$37-74
$33-66
43
$17-34
$15-31
27
$17-33
$15-30
2036
5,500
$50-100
$45-91
50
$20-40
$18-36
32
$20-40
$18-36
2037
7,200
$67-130
$60-120
56
$23-46
$20-41
36
$23-47
$21-42
2038
9,100
$86-170
$77-150
61
$25-51
$23-46
41
$27-53
$24-48
2039
11,000
$100-210
$94-190
65
$28-55
$25-50
45
$30-60
$27-54
2040
12,000
$120-240
$110-220
69
$30-60
$27-54
49
$33-66
$30-59
2041
14,000
$140-270
$120-240
72
$32-63
$29-57
52
$36-71
$32-64
2042
15,000
$150-290
$130-260
74
$34-67
$30-60
55
$38-76
$35-68
2043
16,000
$160-310
$140-280
76
$35-69
$32-62
57
$41-80
$36-72
2044
17,000
$170-330
$150-300
78
$36-72
$33-64
58
$42-83
$38-75
2045
17,000
$180-340
$160-310
78
$37-73
$33-66
59
$44-86
$39-77
2046
17,000
$180-350
$160-320
79
$38-74
$34-67
59
$45-87
$40-78
2047
18,000
$180-360
$170-320
79
$38-75
$35-68
59
$45-88
$41-80
2048
18,000
$190-370
$170-330
78
$39-76
$35-68
59
$46-89
$41-80
2049
18,000
$190-370
$170-330
78
$39-76
$35-69
59
$46-90
$42-81
2050
18,000
$190-380
$170-340
78
$40-77
$36-69
59
$47-91
$42-82
2051
18,000
$200-380
$180-340
77
$40-78
$36-70
59
$47-91
$42-82
2052
18,000
$200-380
$180-340
77
$40-78
$36-70
58
$47-92
$43-83
2053
18,000
$200-380
$180-340
76
$41-79
$37-71
58
$48-92
$43-83
2054
18,000
$200-380
$180-350
76
$41-79
$37-71
57
$48-92
$43-83
2055
18,000
$200-380
$180-350
75
$41-79
$37-71
57
$48-92
$43-83
PV
$1,800-3,500
$780-1,500
$430-850
$200-400
$490-960
$220-440
AV
$94-180
$64-130
$22-44
$16-32
$25-50
$18-36
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al.,
2020) and the NHIS study (Pope III et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values
presented here are not discounted. The present value of benefits is the total aggregated value of the series of discounted annual benefits
that occur between 2027-2055 (in 2022 dollars) using either a 3% or 7% discount rate.
778
-------
Table 7-13 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Heavy-Duty
Gasoline Vehicles and the associated monetized PM2.s-related health benefits (millions, 2022$) for the
alternative program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
31
$0.23-0.48
$0.21-0.43
0.69
$0.12-0.25
$0.1-0.22
1.5
$0.98-2.1
$0.88-1.9
2028
63
$0.47-0.98
$0.42-0.88
1.3
$0.23-0.48
$0.21-0.43
3.0
$2.0-4.2
$1.8-3.7
2029
94
$0.72-1.5
$0.65-1.3
1.9
$0.34-0.71
$0.3-0.63
4.4
$3.0-6.3
$2.7-5.7
2030
130
$1.0-2.1
$0.90-1.8
2.5
$0.46-0.94
$0.41-0.85
5.9
$4.2-8.6
$3.7-7.7
2031
180
$1.5-3.0
$1.3-2.7
3.3
$0.62-1.3
$0.56-1.2
8.8
$6.4-13
$5.7-12
2032
250
$2.1-4.2
$1.9-3.8
4.4
$0.86-1.8
$0.77-1.6
12
$9.0-18
$8.1-17
2033
310
$2.6-5.3
$2.3-4.7
5.2
$1.0-2.1
$0.92-1.9
15
$11-23
$10-21
2034
350
$3.0-6.1
$2.7-5.5
5.7
$1.2-2.3
$1.0-2.1
17
$13-27
$12-24
2035
380
$3.4-6.7
$3.0-6.0
5.9
$1.2-2.5
$1.1-2.2
19
$15-30
$13-27
2036
410
$3.7-7.3
$3.3-6.6
5.9
$1.3-2.5
$1.1-2.3
20
$17-33
$15-30
2037
420
$3.9-7.8
$3.5-7.0
5.9
$1.3-2.6
$1.2-2.3
21
$18-36
$16-32
2038
430
$4.1-8.0
$3.6-7.2
5.8
$1.3-2.6
$1.2-2.3
22
$19-38
$17-34
2039
430
$4.1-8.1
$3.7-7.3
5.6
$1.3-2.5
$1.1-2.3
22
$19-38
$17-34
2040
420
$4.1-8.0
$3.7-7.2
5.3
$1.2-2.4
$1.1-2.2
21
$19-38
$17-34
2041
400
$3.9-7.7
$3.5-7.0
5.0
$1.2-2.3
$1.1-2.1
20
$19-37
$17-33
2042
380
$3.8-7.4
$3.4-6.6
4.6
$1.1-2.2
$0.99-2.0
20
$18-36
$16-32
2043
350
$3.5-6.9
$3.2-6.2
4.2
$1.0-2.0
$0.93-1.8
18
$17-34
$15-30
2044
330
$3.3-6.5
$3.0-5.8
3.9
$0.96-1.9
$0.86-1.7
17
$16-32
$15-29
2045
300
$3.1-6.0
$2.8-5.4
3.5
$0.89-1.7
$0.8-1.6
15
$15-29
$13-26
2046
280
$2.9-5.6
$2.6-5.0
3.2
$0.83-1.6
$0.74-1.5
14
$14-27
$12-24
2047
260
$2.7-5.2
$2.4-4.7
3.0
$0.77-1.5
$0.69-1.3
13
$13-25
$11-22
2048
240
$2.5-4.9
$2.2-4.4
2.7
$0.71-1.4
$0.64-1.2
12
$12-23
$11-21
2049
220
$2.3-4.6
$2.1-4.1
2.5
$0.67-1.3
$0.6-1.2
11
$11-21
$9.8-19
2050
210
$2.2-4.3
$2.0-3.9
2.4
$0.64-1.2
$0.57-1.1
10
$10-20
$9.0-18
2051
200
$2.1-4.1
$1.9-3.7
2.2
$0.61-1.2
$0.55-1.1
8.8
$9.3-18
$8.4-16
2052
190
$2.0-3.9
$1.8-3.5
2.1
$0.59-1.1
$0.53-1.0
8.2
$8.7-17
$7.8-15
2053
180
$2.0-3.8
$1.8-3.4
2.0
$0.57-1.1
$0.51-0.98
7.4
$8.1-16
$7.2-14
2054
170
$1.9-3.7
$1.7-3.3
1.9
$0.55-1.1
$0.49-0.95
6.7
$7.4-14
$6.6-13
2055
160
$1.8-3.5
$1.6-3.2
1.9
$0.53-1.0
$0.48-0.92
6.0
$6.7-13
$6.0-12
PV
$48-95
$26-51
$16-31
$8.7-18
$220-430
$120-230
AV
$2.5-4.9
$2.1-4.2
$0.8-1.6
$0.7-1.4
$11-23
$10-19
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the NHIS study
(Pope III et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values presented here are not discounted. The present value of
benefits is the total aggregated value of the series of discounted annual benefits that occur between 2027-2055 (in 2022 dollars) using either a 3% or 7% discount
rate.
779
-------
Table 7-14 Summary of the estimated tons of increased NOx, S02 and direct PM2.5 per year from EGUs and
the associated monetized PIVh.s-related health impacts (millions, 2022$) for the alternative program
NOx
so2
Direct PM
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
41
$(0,36)-(0.75)
$(0.33)-(0.68)
49
$(3.2)-(6.8)
$(2.9)-(6.1)
6.0
$(0.78)-(1.6)
$(0.70)-(1.5)
2028
92
$(0.83)-(1.7)
$(0.75)-(1.6)
110
$(7.5)-(16)
$(6.7)-(14)
13
$(1.8)-(3.8)
$(1.6)-(3.4)
2029
200
$(1.9)-(3.8)
$(1.7)-(3.4)
240
$(17)-(35)
$(15)-(31)
29
$(4.0)-(8.4)
$(3.6)-(7.5)
2030
510
$(4.8)-(9.9)
$(4.3)-(8.9)
620
$(43)-(90)
$(39)-(81)
74
$(ll)-(22)
$(9.4)-(20)
2031
1,000
$(10)-(21)
$(9.1)-(19)
1,300
$(91)-(190)
$(82)-(170)
150
$(22)-(46)
$(20)-(41)
2032
1,900
$(18)-(37)
$(17)-(34)
2,200
$(170)-(340)
$(150)-(300)
270
$(40)-(83)
$(36)-(74)
2033
2,600
$(27)-(54)
$(24)-(49)
3,200
$(240)-(490)
$(220)-(440)
390
$(59)-(120)
$(53)-(l 10)
2034
3,400
$(35)-(71)
$(32)-(64)
4,100
$(320)-(640)
$(290)-(580)
500
$(78)-(160)
$(70)-(140)
2035
4,100
$(44)-(87)
$(39)-(79)
5,000
$(390)-(790)
$(350)-(720)
600
$(97)-(200)
$(87)-(180)
2036
4,000
$(43)-(85)
$(39)-(77)
4,700
$(380)-(770)
$(340)-(690)
590
$(97)-(190)
$(87)-(180)
2037
3,600
$(39)-(77)
$(35)-(70)
4,200
$(340)-(680)
$(310)-(610)
540
$(90)-(180)
$(81)-(160)
2038
2,900
$(32)-(64)
$(29)-(57)
3,300
$(270)-(540)
$(240)-(490)
450
$(78)-(160)
$(70)-(140)
2039
2,000
$(23)-(45)
$(20)-(40)
2,100
$(180)-(350)
$(160)-(320)
340
$(60)-(120)
$(54)-(l 10)
2040
950
$(ll)-(22)
$(9.8)-(19)
700
$(61)-(120)
$(54)-(l 10)
200
$(36)-(72)
$(33)-(65)
2041
910
$(11)-(21)
$(9.4)-(19)
630
$(55)-(l 10)
$(49)-(98)
210
$(38)-(75)
$(34)-(68)
2042
850
$(9.8)-(19)
$(8.8)-(17)
550
$(48)-(95)
$(43)-(85)
220
$(39)-(77)
$(35)-(70)
2043
780
$(9.0)-(18)
$(8)-(16)
460
$(40)-(79)
$(36)-(71)
220
$(40)-(79)
$(36)-(71)
2044
690
$(8.0)-(16)
$(7.1)-(14)
350
$(31)-(61)
$(28)-(54)
220
$(40)-(79)
$(36)-(71)
2045
590
$(6.9)-(13)
$(6.1)-(12)
240
$(21)-(42)
$(19)-(37)
220
$(40)-(79)
$(36)-(71)
2046
590
$(6.8)-(13)
$(6)-(12)
200
$(17)-(34)
$(16)-(31)
220
$(39)-(77)
$(35)-(69)
2047
570
$(6.6)-(13)
$(5.9)-(12)
160
$(14)-(27)
$(12)-(24)
210
$(37)-(74)
$(33)-(66)
2048
560
$(6.5)-(13)
$(5.8)-(ll)
110
$(9.7)-(19)
$(8.8)-(17)
200
$(35)-(70)
$(32)-(64)
2049
550
$(6.3)-(12)
$(5.7)-(ll)
68
$(5.9)-(12)
$(5.3)-(ll)
190
$(34)-(67)
$(30)-(61)
2050
530
$(6.2)-(12)
$(5.5)-(ll)
24
$(2.1)-(4.2)
$(1.9)-(3.7)
180
$(32)-(64)
$(29)-(58)
2051
530
$(6.2)-(12)
$(5.5)-(ll)
24
$(2.1)-(4.2)
$(1.9)-(3.7)
180
$(32)-(64)
$(29)-(58)
2052
530
$(6.1)-(12)
$(5.5)-(ll)
24
$(2.1)-(4.1)
$(1.9)-(3.7)
180
$(32)-(64)
$(29)-(57)
2053
530
$(6.1)-(12)
$(5.5)-(ll)
24
$(2.1)-(4.1)
$(1.9)-(3.7)
180
$(32)-(63)
$(29)-(57)
2054
520
$(6.0)-(12)
$(5.4)-(ll)
24
$(2.0)-(4.1)
$(1.8)-(3.6)
180
$(32)-(63)
$(28)-(57)
2055
520
$(6.0)-(12)
$(5.4)-(ll)
24
$(2.0)-(4.0)
$(1.8)-(3.6)
180
$(31)-(62)
$(28)-(56)
PV
$(280)-(550)
$(250)-(500)
$(2,100)-(4,200)
$(l,900)-(3,700)
$(790)-( 1,600)
$(710)-(l ,400)
AV
$(14)-(29)
$(13)-(26)
$(110)-(220)
$(97)-(190)
$(41)-(83)
$(37)-(75)
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the NHIS study
(Pope III et al., 2019). A negative benefit value (in parentheses) implies an increase in adverse health outcomes. All benefits estimates are rounded to two significant
figures. Annual benefit values presented here are not discounted. The present value of benefits is the total aggregated value of the series of discounted annual benefits
that occur between 2027-2055 (in 2022 dollars) using either a 3% or 7% discount rate.
780
-------
Table 7-15 Summary of the estimated tons of reduced NOx, SO2 and direct PM2.5 per year from Refineries
and the associated monetized PIVh.s-related health benefits (millions, 2022$) for the alternative program
NOx Reduction Benefits
S02 Reduction Benefits
Direct PM Reduction Benefits
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
Emissions
(tons)
3%
Discount
Rate
7%
Discount
Rate
2027
2.7
$0,073-0.15
$0,065-0.14
0.8
$0,048-0.1
$0,043-0.092
0.7
$0.27-0.58
$0.25-0.53
2028
5.4
$0.15-0.31
$0.13-0.28
1.6
$0,097-0.2
$0,087-0.18
1.3
$0.55-1.2
$0.49-1.0
2029
8.4
$0.23-0.48
$0.21-0.44
2.6
$0.16-0.33
$0.14-0.29
2.0
$0.87-1.8
$0.78-1.7
2030
13
$0.36-0.75
$0.33-0.68
4.0
$0.25-0.51
$0.22-0.46
3.0
$1.4-2.8
$1.2-2.5
2031
20
$0.58-1.2
$0.52-1.1
6.2
$0.39-0.81
$0.35-0.74
4.7
$2.2-4.5
$1.9-4.0
2032
30
$0.90-1.8
$0.81-1.7
9.3
$0.61-1.3
$0.55-1.1
7.0
$3.3-6.9
$3.0-6.2
2033
39
$1.2-2.4
$1.1-2.2
12
$0.81-1.7
$0.73-1.5
9.0
$4.4-9.0
$3.9-8.1
2034
46
$1.5-2.9
$1.3-2.7
14
$0.99-2.0
$0.89-1.8
11
$5.3-11
$4.8-9.8
2035
52
$1.7-3.4
$1.5-3.1
16
$1.2-2.3
$1.0-2.1
12
$6.2-13
$5.6-11
2036
57
$1.9-3.8
$1.7-3.4
18
$1.3-2.6
$1.2-2.4
13
$6.9-14
$6.2-13
2037
62
$2.1-4.2
$1.9-3.8
19
$1.4-2.9
$1.3-2.6
14
$7.6-15
$6.9-14
2038
65
$2.2-4.5
$2.0-4.0
20
$1.5-3.1
$1.4-2.8
15
$8.2-17
$7.4-15
2039
68
$2.4-4.8
$2.1-4.3
21
$1.6-3.3
$1.5-3.0
16
$8.7-18
$7.9-16
2040
70
$2.5-5.0
$2.3-4.5
22
$1.7-3.4
$1.6-3.1
16
$9.2-18
$8.2-16
2041
71
$2.6-5.1
$2.3-4.5
22
$1.8-3.5
$1.6-3.2
16
$9.3-19
$8.4-17
2042
71
$2.6-5.1
$2.3-4.6
22
$1.8-3.5
$1.6-3.2
16
$9.4-19
$8.4-17
2043
71
$2.6-5.1
$2.3-4.6
22
$1.8-3.5
$1.6-3.2
16
$9.4-19
$8.4-17
2044
71
$2.6-5.1
$2.3-4.6
22
$1.8-3.5
$1.6-3.2
16
$9.3-19
$8.4-17
2045
70
$2.5-5.0
$2.3-4.5
22
$1.8-3.5
$1.6-3.2
16
$9.2-18
$8.3-17
2046
70
$2.5-5.0
$2.3-4.5
22
$1.7-3.5
$1.6-3.1
16
$9.1-18
$8.2-16
2047
69
$2.5-4.9
$2.2-4.4
22
$1.7-3.4
$1.5-3.1
16
$9.0-18
$8.1-16
2048
68
$2.5-4.9
$2.2-4.4
21
$1.7-3.4
$1.5-3.1
15
$8.9-18
$8.0-16
2049
68
$2.4-4.8
$2.2-4.3
21
$1.7-3.4
$1.5-3.0
15
$8.8-18
$7.9-16
2050
67
$2.4-4.8
$2.2-4.3
21
$1.7-3.3
$1.5-3.0
15
$8.7-18
$7.9-16
2051
66
$2.4-4.7
$2.2-4.3
21
$1.7-3.3
$1.5-3.0
15
$8.6-17
$7.8-16
2052
65
$2.4-4.7
$2.1-4.2
21
$1.6-3.3
$1.5-2.9
15
$8.5-17
$7.7-15
2053
64
$2.3-4.6
$2.1-4.1
20
$1.6-3.2
$1.4-2.9
15
$8.4-17
$7.5-15
2054
63
$2.3-4.5
$2.1-4.1
20
$1.6-3.2
$1.4-2.9
14
$8.3-17
$7.4-15
2055
63
$2.3-4.5
$2.0-4.0
20
$1.6-3.1
$1.4-2.8
14
$8.1-16
$7.3-15
PV
$33-65
$29-59
$22-45
$20-41
$120-240
$110-220
AV
$1.7-3.4
$1.5-3.1
$1.2-2.3
$1.1-2.1
$6.2-12
$5.6-11
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020)
and the NHIS study (Pope III et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values presented here
are not discounted. The present value of benefits is the total aggregated value of the series of discounted annual benefits that occur between
2027-2055 (in 2022 dollars) using either a 3% or 7% discount rate.
781
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Table 7-16 Year-over-year monetized PIVh.s-related health benefits (millions, 2022$) associated with Onroad
Heavy-Duty Vehicle and upstream (EGU plus refinery) emissions from the alternative program
Total Onroad Benefits
Upstream Benefits
Net Benefits
3%
Discount
Rate
7%
Discount
Rate
3%
Discount
Rate
7%
Discount
Rate
3%
Discount
Rate
7%
Discount
Rate
2027
$2.2-4.6
$2.0-4.2
$(4.0)-(8.4)
$(3.6)-(7.5)
$(1.8)-(3.7)
$(1.6)-(3.3)
2028
$4.7-9.8
$4.2-8.8
$(9.3)-(19)
$(8.4)-(17)
$(4.6)-(9.7)
$(4.2)-(8.7)
2029
$8.1-17
$7.3-15
$(21)-(44)
$(19)-(40)
$(13)-(27)
$(12)-(24)
2030
$14-29
$13-26
$(57)-(120)
$(51 )-(l 10)
$(43)-(88)
$(38)-(79)
2031
$25-51
$22-46
$(120)-(250)
$(110)-(220)
$(96)-(200)
$(86)-(180)
2032
$40-82
$36-74
$(220)-(450)
$(200)-(400)
$(180)-(370)
$(160)-(330)
2033
$55-110
$50-100
$(320)-(650)
$(290)-(590)
$(260)-(540)
$(240)-(490)
2034
$71-140
$64-130
$(420)-(860)
$(380)-(770)
$(350)-(710)
$(320)-(640)
2035
$90-180
$81-160
$(530)-(l,100)
$(470)-(950)
$(440)-(880)
$(390)-(790)
2036
$110-220
$100-200
$(510)-(1,000)
$(460)-(920)
$(400)-(800)
$(360)-(720)
2037
$140-270
$120-240
$(460)-(920)
$(410)-(830)
$(320)-(650)
$(290)-(580)
2038
$160-320
$150-290
$(370)-(740)
$(330)-(660)
$(210)-(410)
$(190)-(370)
2039
$190-370
$170-330
$(250)-(490)
$(220)-(440)
$(61)-(120)
$(55)-( 110)
2040
$210-410
$190-370
$(94)-(190)
$(85)-(170)
$110-230
$100-200
2041
$230-450
$200-400
$(89)-( 180)
$(80)-(160)
$140-270
$120-240
2042
$240-480
$220-430
$(83)-(160)
$(74)-(150)
$160-320
$140-290
2043
$260-510
$230-450
$(74)-( 150)
$(67)-(130)
$180-360
$160-320
2044
$270-530
$240-470
$(65)-(130)
$(58)-(120)
$200-400
$180-360
2045
$280-540
$250-490
$(54)-(l 10)
$(49)-(97)
$220-430
$200-390
2046
$280-550
$250-490
$(49)-(98)
$(44)-(88)
$230-450
$210-410
2047
$280-560
$260-500
$(44)-(87)
$(40)-(79)
$240-470
$220-420
2048
$290-560
$260-500
$(39)-(76)
$(35)-(69)
$250-480
$220-440
2049
$290-560
$260-510
$(33)-(66)
$(30)-(59)
$260-500
$230-450
2050
$290-570
$260-510
$(28)-(55)
$(25)-(49)
$260-510
$240-460
2051
$290-570
$260-510
$(28)-(55)
$(25)-(50)
$270-520
$240-460
2052
$300-570
$270-520
$(28)-(55)
$(25)-(50)
$270-520
$240-470
2053
$300-570
$270-520
$(28)-(55)
$(25)-(49)
$270-520
$240-470
2054
$300-570
$270-520
$(28)-(55)
$(25)-(49)
$270-520
$240-470
2055
$300-570
$270-510
$(27)-(54)
$(25)-(49)
$270-520
$240-470
PV
$3,000-5,900
$1,400-2,700
$(3,000)-(5,900)
$(l,800)-(3,600)
$40-(58)
$(440)-(950)
AV
$160-310
$110-220
$(150)-(310)
$(150)-(300)
$2.1-(3.0)
$(36)-(77)
Notes:
The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al.,
2020) and the NHIS study (Pope et al., 2019), respectively. All benefits estimates are rounded to two significant figures. Annual
benefit values presented here are not discounted. Negative values in parentheses are health disbenefits related to increases in
estimated emissions. The present value of benefits is the total aggregated value of the series of discounted annual benefits that occur
between 2027-2055 (in 2022 dollars) using either a 3% or 7% discount rate. Depending on the discount rate used, the present and
annualized value of the stream of PM25 health benefits may either be positive or negative. The upstream impacts associated with the
standards presented here include health benefits associated with reduced criteria pollutant emissions from refineries and health
disbenefits associated with increased criteria pollutant emissions from EGUs. The benefits in this table also do not include the full
complement of health and environmental benefits (such as health benefits related to reduced ozone exposure) that, if quantified and
monetized, would increase the total monetized benefits.
We use a constant 3-percent and 7-pecent discount rate to calculate present and annualized
values, consistent with current applicable OMB Circular A-4 guidance (2003). For the purposes
of presenting total net benefits (see RIA Chapter 8), we also use a constant 2-percent discount
rate to calculate present and annualized values. We note that we do not currently have BPT
estimates that use a 2-percent discount rate to account for cessation lag. If we discount the stream
of annual benefits of the final rule based on the 3-percent cessation lag BPT values using a
constant 2-percent discount rate, the annualized value of total PM2.5-related benefits would be
$160 to $300 million and the present value of total PM2.5-related benefits would be $3.5 to $6.5
billion.
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7.2.5 Characterizing Uncertainty in the Estimated Benefits
There are likely to be sources of uncertainty in any complex analysis using estimated
parameters and inputs from numerous models, including this analysis. The Benefits TSD details
our approach to characterizing uncertainty in both quantitative and qualitative terms. That TSD
describes the sources of uncertainty associated with key input parameters including emissions
inventories, air quality data from models (with their associated parameters and inputs),
population data, population estimates, health effect estimates from epidemiology studies,
economic data for monetizing benefits, and assumptions regarding the future state of the country
(i.e., regulations, technology, and human behavior). Each of these inputs is uncertain and affects
the size and distribution of the estimated benefits.
The BPT approach is a simplified approach that relies on additional assumptions and has its
own limitations, some of which are described in Section 7.2.6. We plan to consider a more
complete assessment of benefits in future rulemakings. Additional uncertainties related to key
assumptions underlying the estimates for PM2.5-related premature mortality described in Section
7.2.2 of this chapter include the following:
• We assume that all fine particles, regardless of their chemical composition, are equally
potent in causing premature mortality. This is an important assumption because PM2.5
varies considerably in composition across sources, but the scientific evidence is not yet
sufficient to allow differentiation of effect estimates by particle type. The PM ISA, which
was reviewed by CASAC, concluded that "across exposure durations and health effects
categories ... the evidence does not indicate that any one source or component is
consistently more strongly related with health effects than PM2.5 mass."1986
• We assume that the health impact function for fine particles is log-linear down to the
lowest air quality levels modeled in this analysis. Thus, the estimates include health
benefits from reducing fine particles in areas with varied concentrations of PM2.5,
including both regions that are in attainment with the fine particle standard and those that
do not meet the standard down to the lowest modeled concentrations. The PM ISA
concluded that "the majority of evidence continues to indicate a linear, no-threshold
concentration-response relationship for long-term exposure to PM2.5 and total
(nonaccidental) mortality."1987
• We assume that there is a "cessation" lag between the change in PM exposures and the
total realization of changes in mortality effects. Specifically, we assume that some of the
incidences of premature mortality related to PM2.5 exposures occur in a distributed
fashion over the 20 years following exposure based on the advice of the SAB-HES,
which affects the valuation of mortality benefits at different discount rates. The above
assumptions are subject to uncertainty.1988 Similarly, we assume there is a cessation lag
between the change in PM exposures and both the development and diagnosis of lung
cancer.
1986 U.S. Environmental Protection Agency (U.S. EPA). 2019. Integrated Science Assessment (ISA) for Particulate
Matter (Final Report, 2019). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1987 U.S. Environmental Protection Agency (U.S. EPA). 2019. Integrated Science Assessment (ISA) for Particulate
Matter (Final Report, 2019). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-19/188, 2019.
1988 U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2004. Advisory Council on
Clean Air Compliance Analysis Response to Agency Request on Cessation Lag. EPA-COUNCIL-LTR-05-001.
December. Available at: https://council.epa.gov/ords/sab/f?p=104:12:968651521971.
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7.2.6 Benefit-per-Ton Estimate Limitations
All BPT estimates have inherent limitations. One limitation of using the PM2.5-related BPT
approach is an inability to provide estimates of the health and welfare benefits associated with
exposure to ozone, welfare benefits and some unquantified health benefits associated with PM2.5,
as well as health and welfare benefits associated with ambient NO2 and SO2. Table 7-17 presents
a selection of unquantified criteria pollutant health and welfare benefits categories. Another
limitation is that the mobile sector-specific air quality modeling that underlies the PM2.5 BPT
value did not provide estimates of the PM2.5-related benefits associated with reducing VOC
emissions, but these unquantified benefits are generally small compared to benefits associated
with other PM2.5 precursors.
Table 7-17 Unquantified Criteria Pollutant Health and Welfare Benefits Categories
Category
Improved Human Health
Mortality from exposure to ozone
Nonfatal morbidity from exposure to
ozone
Reduced incidence of morbidity
from exposure to N02
Improved Environment
Reduced visibility impairment
Reduced effects on materials
Reduced effects from PM deposition
(metals and organics)
Reduced vegetation and ecosystem
effects from exposure to ozone
Unquantified Effect More
Information
Premature respiratory mortality from short-term exposure (0-99) Ozone ISAa
Premature respiratory mortality from long-term exposure (age 30-99) Ozone ISAa
Hospital admissions—respiratory (ages 65-99) Ozone ISAa
Emergency department visits—respiratory (ages 0-99) Ozone ISAa
Asthma onset (0-17) Ozone ISAa
Asthma symptoms/exacerbation (asthmatics age 5-17) Ozone ISAa
Allergic rhinitis (hay fever) symptoms (ages 3-17) Ozone ISAa
Minor restricted-activity days (age 18-65) Ozone ISAa
School absence days (age 5-17) Ozone ISAa
Decreased outdoor worker productivity (age 18-65) Ozone ISAb
Metabolic effects (e.g., diabetes) Ozone ISAb
Other respiratory effects (e.g., premature aging of lungs) Ozone ISAb
Cardiovascular and nervous system effects Ozone ISAb
Reproductive and developmental effects Ozone ISAb
Asthma hospital admissions N02 ISA1989 a
Chronic lung disease hospital admissions N02 ISAa
Respiratory emergency department visits N02 ISAa
Asthma exacerbation N02 ISAa
Acute respiratory symptoms N02 ISAa
Premature mortality N02 ISAab c
Other respiratory effects (e.g., airway hyperresponsiveness and N02 ISAb,c
inflammation, lung function, other ages and populations)
Visibility in Class 1 areas PM ISAa
Visibility in residential areas PM ISAa
Household soiling PM ISAab
Materials damage (e.g., corrosion, increased wear) PM ISAb
Effects on individual organisms and ecosystems PM ISAb
Visible foliar injury on vegetation Ozone ISAa
Reduced vegetation growth and reproduction Ozone ISAa
Yield and quality of commercial forest products and crops Ozone ISAa
Damage to urban ornamental plants Ozone ISAb
Carbon sequestration in terrestrial ecosystems Ozone ISAa
Recreational demand associated with forest aesthetics Ozone ISAb
Other non-use effects Ozone ISAb
Ecosystem functions (e.g., water cycling, biogeochemical cycles, net Ozone ISAb
primary productivity, leaf-gas exchange, community composition)
1989U.S. Environmental Protection Agency (U.S. EPA). 2016. Integrated Science Assessment for Oxides of Nitrogen
- Health Criteria (Final Report). National Center for Environmental Assessment, Research Triangle Park, NC. July.
Available at: < https://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=310879>.
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Category
Unquantified Effect
More
Information
Reduced effects from acid deposition
Recreational fishing
NOx SOx ISA1
Tree mortality and decline
NOx SOxISAb
Commercial fishing and forestry effects
NOx SOxISAb
Recreational demand in terrestrial and aquatic ecosystems
NOx SOxISAb
Other non-use effects
NOx SOxISAb
Ecosystem functions (e.g., biogeochemical cycles)
NOx SOxISAb
Reduced effects from nutrient
Species composition and biodiversity in terrestrial and estuarine
NOx SOxISAb
enrichment
ecosystems
Coastal eutrophication
NOx SOxISAb
Recreational demand in terrestrial and estuarine ecosystems
NOx SOxISAb
Other non-use effects
NOx SOxISAb
Ecosystem functions (e.g., biogeochemical cycles, fire regulation)
NOx SOxISAb
Reduced vegetation effects from
Injury to vegetation from S02 exposure
NOx SOxISAb
ambient exposure to S02 and NOx
Injury to vegetation from NOx exposure
NOx SOxISAb
a We assess these benefits qualitatively due to data and resource limitations for this RIA.
b We assess these benefits qualitatively because we do not have sufficient confidence in available data or methods.
c We assess these benefits qualitatively because current evidence is only suggestive of causality or there are other significant concerns
over the strength of the association.
There are also benefits associated with reductions in air toxic pollutant emissions that will
result from the program (see RIA Chapter 5) but that the PM2.5-related BPT approach also does
not capture. While EPA continues to work to improve its benefits estimation tools, there remain
critical limitations for estimating incidence and assessing benefits of reducing air toxics.
National-average BPT values reflect the geographic distribution of the underlying modeled
emissions used in their calculation, which may not exactly match the geographic distribution of
the emission reductions that will occur due to a specific rulemaking. Similarly, BPT estimates
may not reflect local variability in population density, meteorology, exposure, baseline health
incidence rates, or other local factors for any specific location. For instance, even though we
assume that all fine particles have equivalent health effects, the BPT estimates vary across
precursors depending on the location and magnitude of their impact on PM2.5 levels, which
drives population exposure. The photochemically-modeled emissions of the onroad mobile and
upstream sector-attributable PM2.5 concentrations used to derive the BPT values may not match
the change in air quality resulting from the control strategies associated with the final standards.
For this reason, the PM-related health benefits reported here may be larger, or smaller, than those
that will be realized through this final rule.
Given the uncertainty that surrounds BPT analysis, EPA systematically compared benefits
estimated using its BPT approach (and other reduced-form approaches) to benefits derived from
full-form photochemical model representation. This work is referred to as the "Reduced Form
Tool Evaluation Project" (Project), which began in 2017, and the initial results were available at
the end of 2018.1991 The Agency's goal was to better understand the suitability of alternative
reduced-form air quality modeling techniques for estimating the health impacts of criteria
pollutant emissions changes in EPA's benefit-cost analysis. The Project analyzed air quality
policies that varied in the magnitude and composition of their emissions changes and in the
1990U s. Environmental Protection Agency (U.S. EPA). 2008. Integrated Science Assessment for Oxides of Nitrogen
and Sulfur-Ecological Criteria National (Final Report). National Center for Environmental Assessment - RTP
Division, Research Triangle Park, NC. EPA/600/R-08/139. December. Available at:
.
1991 U.S. EPA. 2019. Reduced Form Evaluation Project Report. Available at: https://www.epa.gov/benmap/reduced-
form-evaluation-project-report
785
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emissions source affected (e.g., on-road mobile, industrial point, or electricity generating units).
The policies also differed in terms of the spatial distribution of emissions and concentration
changes, and in their impacts on directly-emitted PM2.5 and secondary PM2.5 precursor emissions
(NOx and SO2).
For scenarios where the spatial distribution of emissions was similar to the inventories used to
derive the BPT, the Project found that total PM2.5 BPT-derived benefits were within
approximately 10 percent to 30 percent of the health benefits calculated from full-form air
quality modeling, though the discrepancies varied by regulated scenario and PM2.5 species. The
scenario-specific emission inputs developed for the Project, and a final project report, are
available online.1992 We note that while the BPT values used to monetize the benefits of the final
program were not part of the Project, they reflect our best estimate of benefits absent air quality
modeling, and we have confidence that the BPT approach provides a reasonable estimate of the
monetized PM2.5-related health benefits associated with this rulemaking. EPA continues to
research and develop reduced-form approaches for estimating PM2.5 benefits.
7.3 Energy Security
The final CO2 emission standards are designed to require reductions in GHG emissions from
HD vehicles in the MYs 2027-2032 and beyond timeframe and, thereby, are expected to reduce
liquid fuel consumption. Our modeled potential compliance pathway projects a mix of ZEV
technologies and ICE vehicle technologies in compliant fleets. Our analysis is based on this
modeled potential compliance pathway but, as noted, many other potential pathways to
compliance exist, and analytic results would differ from those presented here in such cases.
Under our modeled compliance pathway, the standards will be met through a combination of
zero-emission and ICE vehicle technologies, which will, in turn, reduce the demand for oil and
enable the U.S. to reduce its petroleum imports. A reduction of U.S. petroleum imports reduces
both financial and strategic risks caused by potential sudden disruptions in the supply of
imported petroleum to the U.S., thus increasing U.S. energy security. In other words, reduced
U.S. oil imports act as a "shock absorber" when there is a supply disruption in world oil markets.
This section summarizes the Agency's estimates of U.S. oil import reductions and energy
security benefits of the final HD GHG Phase 3 program for model years 2027-2032. Energy
security is broadly defined as the uninterrupted availability of energy sources at affordable
prices.1993 Most discussions of U.S. energy security revolve around the topic of the economic
costs of U.S. dependence on oil imports.1994 Energy independence and energy security are
distinct but related concepts, and an analysis of energy independence informs our analysis of
energy security. The goal of U.S. energy independence is generally the elimination of all U.S.
1992U.S. EPA. 2019. Reduced Form Evaluation Project Report. Available at: https://www.epa.gov/benmap/reduced-
form-evaluation-project-report
1993 https://www.iea.org/topics/energy-security
1994 The issue of cyberattacks is another energy security issue that could grow in significance over time. For
example, in 2021, one of the U.S.'s largest pipeline operators, Colonial Pipeline, was forced to shut down after
being hit by a ransomware attack. The pipeline carries refined gasoline and jet fuel from Texas to New York.
Cyberattack Forces a Shutdown of a Top U.S. Pipeline. New York Times. May 8th, 2021.
786
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imports of petroleum and other foreign sources of energy, or more broadly, reducing the
sensitivity of the U.S.'s economy to energy imports and foreign energy markets.1995
The U.S.'s oil consumption had been gradually increasing in recent years (2015-2019) before
the COVID-19 pandemic in 2020 dramatically decreased U.S. and global oil consumption.1996By
July 2021, however, U.S. oil consumption had returned to pre-pandemic levels and has remained
fairly stable since then.1997 The U.S. has increased its production of oil, particularly "tight" (i.e.,
shale) oil, over the last decade.1998 As a result of the recent increase in U.S. oil production, the
U.S. became a net exporter of crude oil and refined petroleum products in 2020 and is now
projected to be a net exporter of crude oil and refined petroleum products through 2027 to
2050.1999 This is a significant reversal of the U.S.'s net export position since the U.S. has been a
substantial net importer of crude oil and refined petroleum products starting in the early
1950s.2000
Oil is a commodity that is globally traded and, as a result, an oil price shock is transmitted
globally. Given that the U.S. is projected to be a net exporter of crude oil and refined petroleum
products in the 2027-2055 timeframe of this analysis, one could reason that the U.S. no longer
has a significant energy security problem. However, U.S. refineries still rely on significant
imports of heavy crude oil which could be subject to supply disruptions. Also, oil exporters with
a large share of global production have the ability to raise or lower the price of oil by exerting
the market power associated with a cartel, the Organization of Petroleum Exporting Countries
(OPEC), to alter oil supply relative to demand. The degree of market power that OPEC has
during the timeframe of this analysis is difficult to quantify. These factors contribute to the
continued vulnerability of the U.S. economy to episodic oil supply shocks and price spikes, even
when the U.S. is projected to be a net exporter of crude oil and refined petroleum products in the
timeframe of this analysis, 2027-2055.
For this final HDV GHG Phase 3 rule, EPA distinguishes between energy security and
mineral/metal security and security issues associated with the importation of critical minerals,
EV batteries and component parts (i.e., EV supply chain issues). We address energy security
issues involving U.S. oil consumption and oil imports associated with this final rule in this
Chapter of the RIA and Section 22 of the RTC document. Comments associated with wider use
of EV's impacts on the U.S. mineral/metal security and security issues associated with the
importation of EV batteries and their component parts (i.e., EV supply chain issues) are
addressed in Section II.D.l.ii of this final rule's preamble, Chapter 1 of the RIA and in Section
17 of the RTC document.
7.3.1 Review of Historical Energy Security Literature
Energy security discussions are typically based around the concept of the oil import premium.
The oil import premium is the extra cost and impacts of importing oil beyond the price of the oil
1995 Greene, D. 2010. Measuring energy security: Can the United States achieve oil independence? Energy Policy 38,
pp. 1614-1621.
1996 EIA. 2022. Monthly Energy Review. Table 3.1. Petroleum Overview. December.
1997 Ibid.
1998 Ibid.
1999 EIA. 2023 .Annual Energy Outlook 2022. Reference Case. Table A11. Petroleum and Other Liquids Supply and
Disposition.
2000 EIA https://www.eia.gov/energyexplained/oil-and-petroleum-products/imports-and-exports.php
787
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itself as a result of: (1) potential macroeconomic disruption and increased oil import costs to the
economy from oil price spikes or "shocks", and (2) monopsony impacts. Monopsony impacts
stem from changes in the demand for imported oil, which changes the price of all imported oil.
The so called oil import premium gained attention as a guiding concept for energy policy in
the aftermath of the oil price shocks of the 1970's (Bohi and Montgomery 1982, EMF 1981).2001
Plummer et al. (1982) provided valuable discussion of many of the key issues related to the oil
import premium as well as the analogous oil stockpiling premium.2002 Bohi and Montgomery
(1982) detailed the theoretical foundations of the oil import premium and established many of
the critical analytic relationships.2003 Hogan (1981) and Broadman and Hogan (1986, 1988)
revised and extended the established analytical framework to estimate optimal oil import premia
with a more detailed accounting of macroeconomic effects.2004 Since the original work on energy
security was undertaken in the 1980's, there have been several reviews on this topic by Leiby et
al. (1997) and Parry and Darmstadter (2004).2005>2006
The economics literature on whether oil shocks are the same level of threat to economic
stability as they once were, is mixed. Some of the literature asserts that the macroeconomic
component of the energy security externality is small. For example, the National Research
Council (2009) argued that the non-environmental externalities associated with dependence on
foreign oil are small, and potentially trivial.2007 Analyses by Nordhaus (2007) and Blanchard and
Gali (2010) questioned the impact of oil price shocks on the economy in the early 2000
timeframe.2008 They were motivated by attempts to explain why the economy actually expanded
during the oil shock in the early 2000 timeframe, and why there was no evidence of higher
energy prices being passed on through higher wage inflation. One reason, according to Nordhaus
and Blanchard and Gali, is that monetary policy has become more accommodating to the price
impacts of oil shocks. Another reason is that consumers have simply decided that such
2001 Bohi, D. and Montgomery, D. 1982. Social Cost of Imported and U.S. Import Policy, Annual Review of Energy,
7:37-60. Energy Modeling Forum, 1981. World Oil, EMF Report 6, Stanford University Press: Stanford 39 CA.
2002 Plummer, J. et al. (Ed.). 1982. Energy Vulnerability, "Basic Concepts, Assumptions and Numerical Results," pp.
13-36, Cambridge MA: Ballinger Publishing Co.
2003 Bohi, D. and Montgomery, D. 1982. Social Cost of Imported Oil and U.S. Import Policy, Annual Review of
Energy, 7:37-60.
2004 Hogan, W. 1981. "Import Management and Oil Emergencies," Chapter 9 in Deese, David and Joseph Nye, eds.
Energy and Security. Cambridge, MA: Ballinger Publishing Co. Broadman, H. 1986. "The Social Cost of Imported
Oil," Energy Policy 14(3):242-252. Broadman H. and Hogan, W. 1988. "Is an Oil Import Tariff Justified? An
American Debate: The Numbers Say 'Yes'". The Energy Journal 9: 7-29.
2005 Leiby, P., Jones, D., Curlee, R. and Lee, R. 1997. Oil Imports: An Assessment of Benefits and Costs, ORNL-
6851, Oak Ridge National Laboratory, November.
2006 Parry, I. and Darmstadter, J. 2004. "The Costs of U.S. Oil Dependency," Resources for the Future, November
17, 2004. Also published as NCEP Technical Appendix Chapter 1: Enhancing Oil Security, the National
Commission on Energy Policy 2004 Ending the Energy Stalemate-A Bipartisan Strategy to Meet America's Energy
Challenges.
2007 National Research Council. 2009. Hidden Costs of Energy: Unpriced Consequences of Energy Production and
Use. National Academy of Science, Washington, DC.
2008 Nordhaus, W. 2007. "Who's Afraid of a Big Bad Oil Shock?". Brookings Papers on Economic Activity,
Economic Studies Program, The Brookings Institution, Volume 38(2), pp. 219-240. Blanchard, O. and Gali, J. 2010.
The macroeconomic effects of oil price shocks: why are the 2000's so different from the 1970s. International
Dimensions of Monetary Policy. University of Chicago Press.
788
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movements are temporary and have noted that price impacts are not passed on as inflation in
other parts of the economy.
Hamilton (2012) reviewed the empirical literature on oil shocks and suggests that the results
are mixed. Hamilton notes that some work by Blanchard and Gali (2010) and Rasmussen and
Roitman (2011) finds less evidence for economic effects of oil shocks or declining effects of
shocks, while other work continues to find evidence regarding the economic importance of oil
shocks.2009 For example, Baumeister and Peersman (2012) find that an "oil price increase of a
given size seems to have a decreasing effect over time, but noted that the declining price-
elasticity of demand means that a given physical disruption had a bigger effect on price and
turned out to have a similar effect on output as in the earlier data."2010 Hamilton observed that "a
negative effect of oil prices on real output has also been reported for a number of other countries,
particularly when nonlinear functional forms have been employed", citing as examples Kim
(2012) and Engemann, Kliesen, and Owyang (2011) 2011>2012 Alternatively, rather than a
declining effect, Ramey and Vine (2010) find "remarkable stability in the response of aggregate
real variables to oil shocks once we account for the extra costs imposed on the economy in the
1970s by price controls and a complex system of entitlements that led to some energy rationing
and shortages."2013
Some of the literature on oil price shocks emphasizes that economic impacts depend on the
nature of the oil shock, with differences between price increases caused by a sudden supply loss
and those caused by rapidly growing demand. Recent analyses of oil price shocks have
confirmed that "demand-driven" oil price shocks have greater effects on oil prices and tend to
have positive effects on the economy while "supply-driven" oil shocks still have negative
economic impacts, see Baumeister, Peersman and Robays (2010).2014 A paper by Kilian and
Vigfusson (2014), for example, assigned a more prominent role to the effects of price increases
that are unusual, in the sense of being beyond the range of recent experience.2015 Kilian and
Vigfussen also concluded that the difference in response to oil shocks may well stem from the
different effects of demand- and supply-based price increases: "One explanation is that oil price
shocks are associated with a range of oil demand and oil supply shocks, some of which stimulate
2009 Hamilton, J. 2012. Oil Prices, Exhaustible Resources, and Economic Growth. In Handbook of Energy and
Climate Change. Retrieved from http://econweb.ucsd.edu/~jhamilto/handbook_climate.pdf. Blanchard, O. and Gali,
J. 2010. The macroeconomic effects of oil price shocks: why are the 2000's so different from the 1970s.
International Dimensions of Monetary Policy. University of Chicago Press. Rasmussen, T. and Roitman, A. 2011.
Oil Shocks in a Global Perspective: Are They Really That Bad. IMF Working Paper Series.
2010 Baumeister, C. and Peersman, G. 2012. The Role of Time-Varying Price Elasticities in Accounting for Volatility
Changes in the Crude Oil Market. Journal of Applied Economics.
2011 Kim, D. 2012. What is an oil shock? Panel data evidence. Empirical Economics, Volume 43, pp. 121-143.
2012 Engemann, K., Kliesen. K. and Owyang, M. 2011. Do Oil Shocks Drive Business Cycles, Some U.S. and
International Evidence. Federal Reserve Bank of St. Louis, Working Paper Series. No. 2010-007D.
2013 Ramey, V. and Vine, D. 2010. "Oil, Automobiles, and the U.S. Economy: How Much have Things Really
Changed?". National Bureau of Economic Research Working Papers. WP 16067. June.
2014 Baumeister C., Peersman, G. and Van Robays, I. 2010. "The Economic Consequences of Oil Shocks:
Differences across Countries and Time". RBA Annual Conference Volume in: Renee Fry & Callum Jones &
Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
2015 Kilian, L. and Vigfusson, R. 2014. "The role of oil price shocks in causing U.S. recessions". CFS Working
Paper Series 460, Center for Financial Studies.
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the U.S. economy in the short-run and some of which slow down U.S. economic growth (see
Kilian (2009))".2016
The general conclusion that oil supply-driven shocks reduce economic output is also reached
in a paper by Cashin et al. (2014) which focused on 38 countries from 1979-2011.2017 They
stated: "The results indicate that the economic consequences of a supply-driven oil-price shock
are very different from those of an oil-demand shock driven by global economic activity, and
vary for oil-importing countries compared to energy exporters". Cashin et al. continues "oil
importers (including the U.S.) typically face a long-lived fall in economic activity in response to
a supply-driven surge in oil prices". But almost all countries see an increase in real output for an
oil-demand disturbance.
EPA's assessment of the energy security literature finds that there are benefits to the U.S.
from reductions in U.S. oil imports. But there is some debate in the economics literature as to the
magnitude of energy security benefits from U.S. oil import reductions. Over the last decade,
differences in economic impacts from oil demand and oil supply shocks have been distinguished.
The oil security premium calculations in this analysis are based on price shocks from potential
future supply events only. Oil supply shocks, which reduce economic activity, have been the
predominant focus of oil security issues since the oil price shocks/oil embargoes of the 1970's.
7.3.2 Review of Recent Energy Security Literature
There have also been a handful of recent studies that are relevant for the issue of energy
security: one by Resources for the Future (RFF), a study by Brown, two studies by Oak Ridge
National Laboratory (ORNL), and three studies by Newell and Prest, Bj0rnland et al. and Walls
and Zheng, on the responsiveness of U.S. tight oil (i.e., shale oil) to world oil price changes.
2018,2019,2020,2021,2022,2023,2024 \ye provide a review and high-level summary of each of these studies
below.
7.3.2.1 Recent Oil Security Studies
The first studies on the energy security impacts of oil that we review are by Resources for the
Future (RFF), a study by Brown, and two studies by Oak Ridge National Laboratory (ORNL).
2016 Kilian, L. 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude
Oil Market." American Economic Review. 99 (3): pp. 1053-69.
2017 Cashin, P., Mohaddes, K., and Raissi, M. 2014. The Differential Effects of Oil Demand and Supply Shocks on
the Global Economy, Energy Economics. 12 (253).
2018 Krupnick, A., Morgenstern, R., Balke, N., Brown, S., Herrara, M. and Mohan, S. 2017. "Oil Supply Shocks,
U.S. Gross Domestic Product, and the Oil Security Problem," Resources for the Future Report.
2019 Brown, S. 2018. New estimates of the security costs of U.S. oil consumption". Energy Policy, 113 pp. 171-192.
2020 Uria-Martinez, R., Leiby, P., Oladosu, G., Bowman, D., Johnson, M. 2018. Using Meta-Analysis to Estimate
World Oil Demand Elasticity, ORNL Working Paper.
2021 Oladosu, G., Leiby, P., Bowman, D., Uria-Martinez, R., Johnson, M. 2018. Impacts of oil price shocks on the
U.S. economy: a meta-analysis of oil price elasticity of GDP for net oil-importing economies, Energy Policy 115.
2022 Newell, R. and Prest, B. 2019. The Unconventional Oil Supply Boom: Aggregate Price Response from
Microdata. The Energy Journal. Volume 40, Issue Number 3.
2023 Bjornland, H., Nordvik, F. and Rohrer, M. 2021. "Supply flexibility in the shale patch: Evidence from North
Dakota". Journal of Applied Econometrics. February.
2024 Walls, W. D., & Zheng, X. 2022. Fracking and Structural Shifts in Oil Supply. The Energy Journal, 43(3).
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The RFF study (2017) attempts to develop updated estimates of the relationship among gross
domestic product (GDP), oil supply and oil price shocks, and world oil demand and supply
elasticities. In a follow-on study, Brown summarized the RFF study results as well. The RFF
study argues that there have been major changes that have occurred in recent years that have
reduced the impacts of oil shocks on the U.S. economy. First, the U.S. is less dependent on
imported oil than in the early 2000s due in part to the 'Tracking revolution" (i.e., tight/shale oil),
and to a lesser extent, increased U.S. production of renewable fuels such as ethanol and
biodiesel. In addition, RFF argues that the U.S. economy is more resilient to oil shocks than in
the earlier 2000s timeframe. Some of the factors that make the U.S. more resilient to oil shocks
include increased global financial integration and greater flexibility of the U.S. economy
(especially labor and financial markets), many of the same factors thatNordhaus and Blanchard
and Gali pointed to as discussed above.
In the RFF effort, a number of comparative modeling scenarios are conducted by several
economic modeling teams using three different types of energy-economic models to examine the
impacts of oil shocks on U.S. GDP. The first is a dynamic stochastic general equilibrium model
developed by Balke and Brown.2025 The second set of modeling frameworks use alternative
structural vector autoregressive models of the global crude oil market.2026 The last of the models
utilized is the U.S. Energy Information Administration's (EIA) National Energy Modeling
System (NEMS).
Two key parameters are focused upon to estimate the impacts of oil shock simulations on U.S.
GDP: oil price responsiveness (i.e., the short-run price elasticity of demand for oil) and GDP
sensitivity (i.e., the elasticity of GDP to an oil price shock). The more inelastic (i.e., the less
responsive) short-run oil demand is to changes in the price of oil, the higher will be the price
impacts of a future oil shock. Higher price impacts from an oil shock result in higher GDP
losses. The more inelastic (i.e., less sensitive) GDP is to an oil price change, the less the loss of
U.S. GDP with future oil price shocks.
For oil price responsiveness, RFF reports three different values: a short-run price elasticity of
oil demand from their assessment of the "new literature," -0.17; a "blended" elasticity estimate;
-0.05, and short-run oil price elasticities from the "new models" RFF uses, ranging from -0.20
to -0.35. The "blended" elasticity is characterized by RFF in the following way: "Recognizing
that these two sets of literature [old and new] represent an evolution in thinking and modeling,
but that the older literature has not been wholly overtaken by the new, Benchmark-E [the
blended elasticity] allows for a range of estimates to better capture the uncertainty involved in
calculating the oil security premiums."
The second parameter that RFF examines is the GDP sensitivity. For this parameter, RFF's
assessment of the "new literature" finds a value of-0.018, a "blended elasticity" estimate of-
2025 Balke, N. and Brown, S. 2018. "Oil Supply Shocks and the U.S. Economy: An Estimated DSGE Model."
Energy Policy, 116.
2026 These models include Kilian, L. 2009. "Not All Oil Price Shocks are Alike: Disentangling Demand and Supply
Shocks in the Crude Oil Market", American Economic Review, 99:3, pp., 1053-1069; Kilian, L. and Murphy, D.
2013. "The Role of Inventories and Speculative Trading in the Global Market for Crude Oil, "Journal of Applied
Econometrics 29(3); and Baumeister, C. and Hamilton, J. 2019. "Structural Interpretation of Vector Autoregressions
with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic
Review, 109(5).
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0.028, and a range of GDP elasticities from the "new models" that RFF uses that range from -
0.007 to -0.027. One of the limitations of the RFF study is that the large variations in oil price
over the last fifteen years are believed to be predominantly "demand shocks;" for example, a
rapid growth in global oil demand followed by the Great Recession and then the post-recession
recovery.
There have only been two recent situations where events have led to a potential significant
supply-side oil shock in the last several years. The first event was the attack on the Saudi
Aramco Abqaiq oil processing facility and the Khurais oil field. On September 14th, 2019, a
drone and cruise missile attack damaged the Saudi Aramco Abqaiq oil processing facility and the
Khurais oil field in eastern Saudi Arabia. The Abqaiq oil processing facility is the largest crude
oil processing and stabilization plant in the world, with a capacity of roughly 7 million barrels of
oil per day (MMBD) or about 7 percent of global crude oil production capacity.2027 On
September 16th, the first full day of commodity trading after the attack, both Brent and West
Texas Intermediate (WTI) crude oil prices surged by $7.17/barrel and $8.34/barrel, respectively,
in response to the attack, the largest price increase in roughly a decade.
However, by September 17th, Saudi Aramco reported that the Abqaiq plant was producing 2
MMBD, and they expected its entire output capacity to be fully restored by the end of
September.2028 Tanker loading estimates from third-party data sources indicated that loadings at
two Saudi Arabian export facilities were restored to the pre-attack levels.2029 As a result, both
Brent and WTI crude oil prices fell on September 17th, but not back to their original levels. The
oil price spike from the attack on the Abqaiq plant and Khurais oil field was prominent and
unusual, as Kilian and Vigfusson (2014) describe. While pointing to possible risks to world oil
supply, the oil shock was short-lived, and generally viewed by market participants as being
transitory, so it did not influence oil markets over a sustained time period.
The second situation is the set of events leading to the recent world oil price spike
experienced in 2022. World oil prices rose fairly rapidly in the beginning of 2022. For example,
as of January 3rd, 2022, the WTI crude oil price was roughly $76 per barrel. The WTI oil price
increased to roughly $123 per barrel on March 8th, 2022, a 62 percent increase.2030 High and
volatile oil prices in the first half of 2022 were a result of supply concerns with Russia's invasion
of Ukraine on February 24th contributing to crude oil price increases.2031 Russia's invasion of
Ukraine came during eight consecutive quarters (from the third quarter of 2020 to the second
quarter of 2022) of global crude oil inventory decreases. The lower inventory of crude oil stocks
was the result of rising economic activity after COVID-19 pandemic restrictions were eased. Oil
prices drifted downwards throughout the second half of 2022 and early 2023. Since both
significant demand and supply factors influenced world oil prices in 2022, it is not clear how to
evaluate these oil market price trends from an energy security standpoint. Thus, the attack of the
Abqaiq oil processing facility in Saudi Arabia and the unfolding events in the world oil market in
2027 EIA. September 23, 2019. "Saudi Arabia crude oil production outage affects global crude oil and gasoline
prices." Today in Energy.
2028 Ibid.
2029 Ibid.
2030 EIA. 2022. Petroleum and Other Liquids Spot Prices, https://www.eia.gov/dnav/pet/pet_pri_spt_sl_d.htm
2031 U.S. Energy Information Administration. Today in Energy. Crude oil prices increased in the first half of 2022
and declined in the second half of 2022. January.
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2022 do not currently offer enough empirical evidence to provide an updated estimate of the
response of the U.S. economy to an oil supply shock of a significant magnitude.2032
More recently, in its November 2023 Short-term Energy Outlook, EIA is forecasting global
oil production will increase by 1.0 million barrels per day in 2024.2033 Ongoing OPEC+
production cuts will offset production growth from non-OPEC countries and help maintain a
relatively balanced global oil market next year. The surprise attack by Hamas on Israel on
October 7th, 2023, leading to the Hamas-Israel War, is leaving oil markets on edge, increasing
fears that fighting between Israel and Hamas may affect oil production in the Middle East.2034
Although the conflict between Israel and Hamas has not affected physical oil supply at this point,
uncertainties surrounding the conflict and other global oil supply conditions could put upward
pressure on crude oil prices in the coming months. EIA is forecasting the Brent crude oil price
will average $93/barrel in 2024.
A second set of recent studies related to energy security are from ORNL. In the first study,
ORNL (2018) undertakes a quantitative meta-analysis of world oil demand elasticities based
upon the recent economics literature. The ORNL study estimates oil demand elasticities for two
sectors (transportation and non-transportation) and by world regions (OECD and Non-OECD) by
meta-regression. To establish the dataset for the meta-analysis, ORNL undertakes a literature
search of peer reviewed journal articles and working papers between 2000 and 2015 that contain
estimates of oil demand elasticities. The dataset consisted of 1,983 elasticity estimates from 75
published studies. The study finds a short-run price elasticity of world oil demand of-0.07 and a
long-run price elasticity of world oil demand of-0.26. The second relevant ORNL (2018) study
from the standpoint of energy security is a meta-analysis that examines the impacts of oil price
shocks on the U.S. economy as well as many other net oil-importing economies. Nineteen
studies after 2000 were identified that contain quantitative/accessible estimates of the economic
impacts of oil price shocks. Almost all studies included in the review were published since 2008.
The key result that the study finds is a short-run oil price elasticity of U.S. GDP, roughly one
year after an oil shock, of-0.021, with a 68 percent confidence interval of-0.006 to -0.036.
7.3.2.2 Recent Tight (i.e., Shale) Oil Studies
The discovery and development of U.S. tight (i.e., shale) oil reserves that started in the mid-
20008 could affect U.S. energy security in at least a couple of ways.2035 First, the increased
availability of domestic supplies has resulted in a reduction of U.S. oil imports and an increasing
role of the U.S. as an exporter of crude oil and petroleum-based products. In December 2015, the
40-year ban on the export of domestically produced crude oil was lifted as part of the
Consolidated Appropriations Act, 2016. Pub. L. 114-113 (Dec. 18, 2015).2036 According to the
2032 The Hurricanes Katrina/Rita in 2005 primarily caused a disruption in U.S. oil refinery production, with a more
limited disruption of some crude supply in the U.S. Gulf Coast area. Thus, the loss of refined petroleum products
exceeded the loss of crude oil, and the regional impact varied even within the U.S. The Katrina/Rita Hurricanes were
a different type of oil disruption event than is quantified in the Stanford EMF risk analysis framework, which
provides the oil disruption probabilities than ORNL is using.
2033 U.S. EIA, Short-term Energy Outlook, November 7th, 2023.
2034 IEA, Oil Market Report, October 2023. https://www.iea.org/reports/oil-market-report-october-2023
2035 Union of Concerned Scientist. "What is Tight Oil?". 2015. "Tight oil is a type of oil found in impermeable shale
and limestone rock deposits. Also known as "shale oil", tight oil is processed into gasoline, diesel, and jet fuels-just
like conventional oil-but is extracted using hydraulic fracturing, or "fracking".
2036 https://uscode.house.gov/statutes/pl/114/113.pdf (see 129 stat. 2987).
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GAO, the ban was lifted in part due to increases in tight (i.e., shale) 0il.2037'2038 Second, due to
differences in development cycle characteristics and average well productivity, tight oil
producers could be more price responsive than most other oil producers. However, the oil price
level that triggers a substantial increase in tight oil production appears to be higher in 2021-2022
relative to the 2010s as tight oil producers seek higher profit margins per barrel in order to
reduce the debt burden accumulated in previous cycles of production growth.2039
U.S. crude oil production increased from 5.0 MMBD in 2008 to an all-time peak of 12.7
MMBD in 2023 (January through July) and tight oil wells have been responsible for most of the
increase.2040 Figure 7-1 below shows tight oil (i.e., shale oil) production changes from various
tight oil producing regions (i.e., Eagle Ford, Bakken etc.) in the U.S. and the West Texas
Intermediate (WTI) crude oil spot price. Viewing Figure 7-1, one can see that the annual average
U.S. tight oil production grew from 0.6 MMBD in 2008 to 7.8 MMBD in 2019.2041 Growth in
U.S. tight oil production during this period was only interrupted in 2015-2016 following the
world oil price downturn which began in mid-2014. The second growth phase started in late
2016 and continued until 2020. The sharp decrease in demand that followed the onset of the
COVID-19 pandemic resulted in a 25 percent decrease in tight oil production in the period from
December 2019 to May 2020. U.S. tight oil production in 2020 and 2021 averaged 7.4 MMBD
and 7.2 MMBD, respectively. More recently, in March 2023, tight oil production surpassed the
previous historical maximum (8.37 MMBD in November 2019) with 8.43 MMBD. Growth has
continued in the following months and July 2023 production reached 8.57 MMBD. Most of the
2023 growth has come from two Permian producing regions: Spraberry and Bonespring. U.S.
tight oil production represents a relatively modest share (less than 10 percent in 2019) of global
liquid fuel supply.2042
Importantly, U.S. tight oil is considered the most price-elastic component of non-OPEC
supply due to differences between its development and production cycle and that of conventional
oil wells. Unlike conventional wells where oil starts flowing naturally after drilling, shale oil
wells require the additional step of fracking to complete the well and release the oil.2043 Shale oil
producers keep a stock of drilled but uncompleted wells and can optimize the timing of the
completion operation depending on price expectations. Combining this decoupling between
2037 According to the GAO, "Between 1975 and the end of 2015, the Energy Policy and Conservation Act directed a
ban on nearly all exports of U.S. crude oil. This ban was not considered a significant policy issue when U.S. oil
production was declining and import volumes were increasing. However, U.S. crude oil production roughly doubled
from 2009 to 2015, due in part to a boom in shale oil production made possible by advancements in drilling
technologies. In December 2015, Congress effectively repealed the ban, allowing the free export of U.S. crude oil
worldwide".
2038 GAO, 2020. Crude Oil Markets: Effects of the Repeal of the Crude Oil Export Ban. GAO-21-118.
2039 Kemp, J. 2021. U.S. shale restraint pushes oil prices to multi-year high. Reuters. June 4th, 2021.
2040 EIA. 2021. Crude Oil Production. Accessed on 12/20/2021:
https://www.eia.gov/dnav/pet/pet_crd_crpdn_adc_mbbl_m.htm
2041 EIA. 2021. Tight oil production estimates by play. Accessed on 12/20/2021:
https://www.eia.gOv/petroleum/data.php#prices
2042 The 2019 global crude oil production value used to compute the U.S. tight oil share is from EIA International
Energy Statistics, https://www.eia.gov/international/data/world/petroleum-and-other-liquids/annual-petroleum-and-
other-liquids-production.
2043 Hydraulic fracturing ("fracking") involves injecting water, chemicals, and sand at high pressure to open
fractures in low-permeability rock formations and release the oil that is trapped in them.
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drilling and production with the "front-loaded" production profile of tight oil-the fraction of total
output from a well that is extracted in the first year of production is higher for tight oil wells than
conventional oil wells-tight oil producers have a clear incentive to be responsive to prices in
order to maximize their revenues.2044
io-
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-150
120 .
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o
c
~
CT
O"
2008
2010
2012
2014
2016
2018
2020
2022
Producing Regions
¦ Bakken Niobrara-Codell
(ND& MT) ¦ (CO& WY)
¦ Spraberry I Wolfcamp
(TX Permian) (IX & NM Permian)
Price
Bonespring
(TX& NM Permian)
Rest of US
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(TX)
WTI
Figure 7-1 U.S. Tight Oil Production by Producing Regions (in MMBD) and West Texas Intermediate (WTI)
Crude Oil Spot Price (in U.S. Dollars per Barrel), Source: EIA2045-2046
Only in recent years have the implications of the "tight/shale oil revolution" been felt in the
international market where U.S. production of oil is rising to be roughly on par with Saudi
Arabia and Russia. Recent economics literature of the tight (i.e., shale/unconventional) oil
expansion in the U.S. has a bearing on the issue of energy security as well. It could be that the
large expansion in tight oil has eroded the ability of OPEC to set world oil prices to some degree,
since OPEC cannot directly influence tight oil production decisions. Also, by effecting the
percentage of global oil supply controlled by OPEC, the growth in U.S. oil production may be
influencing OPEC's degree of market power. But given that the tight oil expansion is a relatively
recent trend, it is difficult to know how much of an impact the increase in tight oil is having, or
will have, on OPEC behavior.
Three recent studies have examined the characteristics of tight oil supply that have relevance
for the topic of energy security. In the context of energy security, the question that arises is: Can
tight oil respond to an oil price shock more quickly and substantially than conventional oil? If so,
21144 Bjornland, H., Nordvik, F. and Rolirer, M. 2021. "Supply flexibility in the shale patch: Evidence from North
Dakota," Journal of Applied Econometrics, February.
21145 EIA. 202. Tight oil production estimates by play. https://www.eia.gOv/petroleuin/data.php#prices
21146 EIA. 2023. Petroleum and Other Liquids Spot Prices, https://www.eia.gov/dnav/pet/pet_pri_spt_sl_d.htm
795
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then tight oil could potentially lessen the impacts of future oil shocks on the U.S. economy by
moderating the price increases from a future oil supply shock.
Newell and Prest (2019) look at differences in the price responsiveness of conventional versus
shale oil wells, using a detailed dataset of 150,000 oil wells, during the timeframe of 2005-2017
in five major oil-producing states: Texas, North Dakota, California, Oklahoma, and Colorado.
For both conventional oil wells and shale oil wells (i.e., unconventional oil wells), Newell and
Prest estimate the elasticities of drilling operations and well completion operations with respect
to expected revenues and the elasticity of supply from wells already in operation with respect to
spot prices. Combining the three elasticities and accounting for the increased share of tight oil in
total U.S. oil production during the period of analysis, they conclude that U.S. oil supply
responsiveness to prices increased more than tenfold from 2006 to 2017. They find that
tight/shale oil wells are more price responsive than conventional oil wells, mostly due to their
much higher productivity, but the estimated oil supply elasticity is still relatively small. Newell
and Prest note that the tight oil supply response still takes more time to arise than is typically
considered for a "swing producer," referring to a supplier able to increase production quickly,
within 30-90 days. In the past, only Saudi Arabia and possibly one or two other oil producers in
the Middle East have been able to ramp up oil production in such a short period of time.
Another study, by Bj0rnland et al. (2021), uses a well-level monthly production data set
covering more than 16,000 crude oil wells in North Dakota from February 1990 to June 2017 to
examine differences in supply responses between conventional and tight oil/shale oil. They find a
short-run (i.e., one-month) supply elasticity with respect to oil price for tight oil wells of 0.71,
whereas the one-month response of conventional oil supply is not statistically different from
zero. It should be noted that the elasticity value estimated by Bj0rnland et al. combines the
supply response to changes in the spot price of oil as well as changes in the spread between the
spot price and the 3-month futures price.
Walls and Zheng (2022) explore the change in U.S. oil supply elasticity that resulted from the
tight oil revolution using monthly, state-level data on oil production and crude oil prices from
January 1986 to February 2019 for North Dakota, Texas, New Mexico, and Colorado. They
conduct statistical tests that reveal an increase in the supply price elasticities starting between
2008 and 2011 coinciding with the times in which tight oil production increased sharply in each
of these states. Walls and Zheng also find that supply responsiveness in the tight oil era is greater
with respect to price increases than price decreases. The short-run (one-month) supply elasticity
with respect to price increases during the tight oil era ranges from zero in Colorado to 0.076 in
New Mexico; pre-tight oil, it ranged from zero to 0.021.
The results from Newell and Prest, Bj0rnland et al., and Walls and Zheng all suggest that tight
oil may have a larger supply response to oil prices in the short-run than conventional oil,
although the estimated short-run elasticity is still relatively small. The three studies use datasets
that end in 2019 or earlier. The responsiveness of U.S. tight oil production to recent price
increases does not appear to be consistent with that observed during the episodes of crude oil
price increases in the 2010s captured in these three studies. Despite an 80 percent increase in the
WTI crude oil spot price from October 2020 to the end of 2021, Figure 7-1 shows that U.S. tight
oil production has increased by only 8 percent in the same period. It is a somewhat challenging
period in which to examine the supply response of tight oil to its price to some degree, given that
the 2020-2021 time period coincided with the COVID-19 pandemic. Previous shale oil
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production growth cycles were financed predominantly with debt, at very low interest rates.2047
Most U.S. tight oil producers did not generate positive cashflow.2048 As of 2021, U.S. shale oil
producers have pledged to repay their debt and reward shareholders through dividends and stock
buybacks.2049 These pledges translate into higher prices that need to be reached (or sustained for
a longer period) than in the past decade to trigger larger increases in drilling activity.
In its first quarter 2022 energy survey, the Dallas Fed (i.e., the Federal Reserve Bank of
Dallas) asked oil exploration and production firms about the WTI price levels needed to cover
operating expenses for existing wells or to profitably drill a new well. The average breakeven
price to continue operating existing wells in the shale oil regions ranged from $23/barrel (bbl) to
$35/bbl. To profitably drill new wells, the required average WTI prices ranged from $48/bbl to
$69/bbl. For both types of breakeven prices, there was substantial variation across companies,
even within the same region.
The actual WTI price level observed in the first quarter of 2022 has been roughly $95/bbl,
substantially larger than the breakeven price to drill new wells. However, the median production
growth expected by the respondents to the Dallas Fed Energy Survey from the fourth quarter of
2021 to the fourth quarter of 2022 is modest (6 percent among large firms and 15 percent among
small firms). Investor pressure to maintain capital discipline was cited by 59 percent of
respondents as the primary reason why publicly traded oil producers are restraining growth
despite high oil prices. The other reasons cited included supply chain constraints, difficulty in
hiring workers, environmental, social, and governance concerns, lack of access to financing, and
government regulations.2050
Given the recent behavior of tight oil producers, we do not believe that tight oil will provide
additional significant energy security benefits in the timeframe of analysis of this final rule,
2027-2055, due to its muted price responsiveness. The ORNL model still accounts for the effect
of U.S. tight oil production increases on U.S. oil imports and, in turn, the U.S.'s energy security
position.
Finally, despite continuing uncertainty about oil market behavior and outcomes and the
sensitivity of the U.S. economy to oil shocks, it is generally agreed that it is beneficial to reduce
petroleum fuel consumption from an energy security standpoint. The relative significance of
petroleum consumption and import levels for the macroeconomic disturbances that follow from
oil price shocks is not fully understood. Recognizing that changing petroleum consumption will
change U.S. imports, our quantitative assessment of oil energy security costs of this rule focuses
on those incremental social costs that follow from the resulting changes in net imports,
employing the usual oil import premium measure.
7.3.3 Cost of Existing U.S. Energy Security Policies
An additional often-identified component of the full economic costs of U.S. oil imports is the
costs to the U.S. taxpayers of existing U.S. energy security policies. The two primary examples
2047 McLean, B. The Next Financial Crisis Lurks Underground. New York Times, September 1st, 2018.
2048 Ibid.
2049 https://www.bloomberg.com/news/articles/2021-08-02/shale-heavyweights-shower-investors-with-dividends-
on-oil-rally
2050 https://www.dallasfed.org/research/surveys/des/2022/2201 ,aspx#tab-questions
797
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are maintaining the Strategic Petroleum Reserve (SPR) and maintaining a military presence to
help secure a stable oil supply from potentially vulnerable regions of the world.
The SPR is the largest stockpile of government-owned emergency crude oil in the world.
Established in the aftermath of the 1973/1974 oil embargo, the SPR provides the U.S. with a
response option should a disruption in commercial oil supplies threaten the U.S. economy.2051
Emergency SPR drawdowns have taken place in 1991 (Operation Desert Storm), 2005
(Hurricane Katrina), 2011 (Libyan Civil War), and 2022. All of these releases have been in
coordination with releases of strategic stocks from other International Energy Agency (IEA)
member countries.
In the first four months of 2022, using the statutory authority under Section 161 of the Energy
Policy and Conservation Act, President Biden directed the U.S. DOE to conduct two emergency
SPR drawdowns in response to ongoing oil supply disruptions.2052 The first drawdown resulted
in a sale of 30 million barrels in March 2022. The second drawdown, announced in April,
authorized a total release of approximately one MMBD from May to October 2022.2053 In 2023,
the DOE sold 26 million barrels of oil between April and June.2054 A total of 246.6 million
barrels were released from the SPR from January 2022 to July 2023. By the end of July 2023, the
SPR stock level was 346.8 million barrels (the lowest level since August 1983). To start
replenishing the stock, the SPR office purchased 10.23 million barrels through competitive
solicitations conducted between May and November of 2023, for deliveries from August 2023 to
February 2024. While the costs for building and maintaining the SPR are more clearly related to
U.S. oil use and imports, these costs have not varied historically in response to changes in U.S.
oil import levels. Thus, while the effect of the SPR in moderating price shocks is factored into
the analysis that EPA is using to estimate the macroeconomic oil security premiums, the cost of
maintaining the SPR is excluded.
We have also considered the possibility of quantifying the military benefits components of
energy security but have not done so here for several reasons. The literature on the military
components of energy security has described four broad categories of oil-related military and
national security costs, all of which are hard to quantify. These include possible costs of U.S.
military programs to secure oil supplies from unstable regions of the world, the energy security
costs associated with the U.S. military's reliance on petroleum to fuel its operations, possible
national security costs associated with expanded oil revenues to "rogue states" and, relatedly, the
foreign policy costs of oil insecurity.
Of these categories listed above, the one that is most clearly connected to petroleum use and
is, in principle, quantifiable is the first: the cost of military programs to secure oil supplies and
stabilize oil supplying regions. There is an ongoing literature on the measurement of this
component of energy security, but methodological and measurement issues - attribution and
incremental analysis - pose two significant challenges to providing a robust estimate of this
2051 Energy Policy and Conservation Act, 42 U.S. Code § 6241(d) (1975).
2052 https://www.energy.gov/fecm/articles/doe-announces-emergency-notice-sale-crude-oil-strategic-petroleum-
reserve-address-oil
2053 https://www.energy.gov/articles/doe-announces-second-emergency-notice-sale-crude-oil-strategic-petroleum-
reserve-address
2054 https://www.energy.gov/ceser/articles/doe-issues-notice-congressionally-mandated-sale-purchase-crude-oil-
strategic
798
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component of energy security. The attribution challenge is to determine which military programs
and expenditures can properly be attributed to oil supply protection, rather than some other
objective. The incremental analysis challenge is to estimate how much the petroleum supply
protection costs might vary if U.S. oil use were to be reduced or eliminated. Methods to address
both of these challenges are necessary for estimating the effect on military costs arising from a
modest reduction (not elimination) in oil use attributable to this final rule.
Since "military forces are, to a great extent, multipurpose and fungible" across theaters and
missions (Crane et al. (2009)), and because the military budget is presented along regional
accounts rather than by mission, the allocation to particular missions is not always clear.2055
Approaches taken usually either allocate "partial" military costs directly associated with
operations in a particular region, or allocate a share of total military costs (including some that
are indirect in the sense of supporting military activities overall) (Koplow and Martin
(1998)).2056
The challenges of attribution and incremental analysis have led some to conclude that the
mission of oil supply protection cannot be clearly separated from others, and the military cost
component of oil security should be taken as near zero (Moore et al. (1997)).2057 Stern (2010), on
the other hand, argues that many of the other policy concerns in the Persian Gulf follow from oil,
and the reaction to U.S. policies taken to protect oil.2058 Stern presents an estimate of military
cost for Persian Gulf force projection, addressing the challenge of cost allocation with an
activity-based cost method. He uses information on actual naval force deployments rather than
budgets, focusing on the costs of carrier deployment. As a result of this different data set and
assumptions regarding allocation, the estimated costs are much higher, roughly 4 to 10 times,
than other estimates. Stern also provides some insight on the analysis of incremental effects, by
estimating that Persian Gulf force projection costs are relatively strongly correlated to Persian
Gulf petroleum export values and volumes. Still, the issue remains of the marginality of these
costs with respect to Persian Gulf oil supply levels, the level of U.S. oil imports, or U.S. oil
consumption levels.
Delucchi and Murphy (2008) seek to deduct from the cost of Persian Gulf military programs
the costs associated with defending U.S. interests other than the objective of providing a more
stable oil supply and price to the U.S. economy.2059 Excluding an estimate of cost for missions
unrelated to oil, and for the protection of oil in the interest of other countries, Delucchi and
Murphy estimated military costs for all U.S. domestic oil interests of between $24 and $74
billion annually. Delucchi and Murphy assume that military costs from oil import reductions can
be scaled proportionally, attempting to address the incremental issue.
2055 Crane, K., Goldthau, A., Toman, M., Light, T., Johnson, S., Nader, A., Rabasa, A. and Dogo, H. 2009. Imported
oil and US national security. RAND. 2009.
2056 Koplow, D. and Martin, A. 1998. Fueling Global Warming: Federal Subsidies to Oil in the United States.
Greenpeace, Washington, D.C.
2057 Moore, J., Behrens, C. and Blodgett, J. 1997. "Oil Imports: An Overview and Update of Economic and Security
Effects". CRS Environment and Natural Resources Policy Division Report 98, no. 1: pp. 1-14.
2058 Stern, R. 2010. "United States cost of military force projection in the Persian Gulf, 1976-2007". Energy Policy
38, no. 6. June: 2816-2825.
2059 Delucchi, M. and Murphy, J. 2008. "US military expenditures to protect the use of Persian Gulf oil for motor
vehicles". Energy Policy 36, No. 6. June.
799
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Crane et al. considers force reductions and cost savings that could be achieved if oil security
were no longer a consideration. Taking two approaches and guided by post-Cold War force draw
downs and by a top-down look at the current U.S. allocation of defense resources, they
concluded that $75—$91 billion, or 12-15 percent of the current U.S. defense budget, could be
reduced. Finally, an Issue Brief by Securing America's Future Energy (SAFE) (2018) found a
conservative estimate of approximately $81 billion per year spent by the U.S. military protecting
global oil supplies.2060 This is approximately 16 percent of the recent U.S. Department of
Defense's budget. Spread out over the 19.8 million barrels of oil consumed daily in the U.S. in
2017, SAFE concludes that the implicit subsidy for all petroleum consumers is approximately
$11.25 per barrel of crude oil, or $0.28 per gallon. According to SAFE, a more comprehensive
estimate suggests the costs could be greater than $30 per barrel, or over $0.70 per gallon.2061
As in the examples above, an incremental analysis can estimate how military costs would vary
if the oil security mission is no longer needed, and many studies stop at this point. It is
substantially more difficult to estimate how military costs would vary if U.S. oil use or imports
are partially reduced, as is projected to be a consequence of this final rule. Partial reduction of
U.S. oil use likely diminishes the magnitude of the energy security problem, but there is
uncertainty that supply protection forces and their costs could be scaled down in proportion, and
there remains the associated goal of protecting supply and transit for U.S. allies and other
importing countries, if they do not decrease their petroleum use as well.2062 We are unaware of a
robust methodology for assessing the effect on military costs of a partial reduction in U.S. oil
use. Therefore, we are unable to quantify this effect resulting from the projected reduction in
U.S. oil use attributable to this final rule.
7.3.4 U.S. Oil Import Reductions Expected from the Final Rule
In this section, we compare oil import reductions from this final rule with an assessment of
overall U.S. oil market trends. The U.S. Department of Energy's (DOE) Energy Information
Administration's (EIA) Annual Energy Outlook (AEO) 2023 (Reference Case) projects oil
market trends to 2050, which are reported below in Table 7-20.2063 The AEO 2023 (Reference
Case) projects that the U.S. will be both an exporter and an importer of crude oil through
2050.2064 The U.S. produces more light crude oil than its refineries can refine. Thus, the U.S.
exports lighter crude oil and imports heavier crude oils to satisfy the needs of U.S. refineries,
which are configured to efficiently refine heavy crude oil. U.S. crude oil exports are projected to
remain relatively stable, ranging between 2.9 and 3.4 MMBD between 2027 and 2050. U.S.
crude oil imports, meanwhile, are projected to range between 6.6 and 7.2 MMBD over the 2027-
2050 timeframe.
The AEO 2023 projects that U.S. net refined petroleum product exports will grow from 5.8
MMBD in 2027 to 6.7 MMBD in 2045 before dropping off somewhat to 6.2 MMBD in 2050.
2060 Securing America's Future Energy. 2018. Issue Brief. The Military Cost of Defending the Global Oil Supply.
2061 Ibid.
2062 Crane, K., Goldthau, A., Toman, M., Light, T., Johnson, S., Nader, A., Rabasa, A. and Dogo, H. 2009. Imported
oil and US national security. 2009. RAND.
2063 The AEO 2023 oil market trends are projected out to 2050. Thus, we report U.S. oil market trends through 2050
based upon the AEO 2023. However, EPA's analysis of this final rule is from 2027-2055. Therefore, EPA provides
estimate of U.S. oil reductions from this final rule through 2055.
2064 EIA. 2023 .Annual Energy Outlook 2023. Reference Case. Table Al 1. Petroleum and Other Liquids Supply and
Disposition.
800
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Given the pattern of U.S. crude oil exports/imports, and U.S. net refined petroleum product
exports, the U.S. is projected to be a net petroleum (crude oil and refined petroleum products)
exporter from 2027 through 2050, with net exports ranging between 2.3 and 2.9 MMBD during
that time period. Since the U.S. is projected to continue importing significant quantities of crude
oil through 2050, EPA's assessment is that the U.S. is not expected to achieve an overall goal of
U.S. energy independence during the analytical timeframe of this rule. However, the U.S. is
projected to be a net exporter of crude oil and refined petroleum products through 2050.
U.S. oil consumption is projected to be fairly steady for the time period from 2027 to 2050,
ranging between 18.2 and 18.9 MMBD. Thus, during the 2027-2050 timeframe, the AEO 2023
projects that the U.S. will continue to consume significant quantities of oil and will likewise
continue to rely on significant quantities of crude oil imports.
Estimated petroleum consumption changes from this final rule are presented in Chapter 6.5 of
the RIA. EPA uses an oil import reduction factor to estimate how changes in U.S. refined
product demand from this rule (i.e., changes in U.S. oil consumption) influence U.S. net oil
imports (i.e., changes in U.S. oil imports). For the proposed rule, EPA used an oil import
reduction factor of 86.4 percent. After carefully reviewing comments on refinery throughput and
in consultation with DOE and NHTSA, EPA is updating its assessment of the impact of this final
rule on U.S. refinery throughput and, in turn, the air quality impacts from refinery emissions.
Instead of estimating that U.S. refineries would largely reduce their production in response to
reduced refined product demand from this rule, we are now estimating that U.S. refinery output
will decline by half (50 percent) of the reduced demand, while increases in refined product
exports (i.e., equivalently a decline in net refined product imports) will account for the other half
(50 percent) of that reduced demand. We also look at an additional case in a sensitivity analysis
where U.S. refinery throughput would be maintained by 80 percent as a result by increases in
refined product exports, while 20 percent of the refinery throughput would be reduced. See
Chapter 4 of the RIA and Section 13 of the Response to Comment document for more discussion
of how EPA is updating its refinery throughput assumptions and, in turn, air quality impacts
from refinery emissions, as a result of this rule. See Section 22 of the Response to Comment
document for EPA's response to comments on EPA's updated estimate of the oil import
reduction factor.
Since EPA's refinery throughput assumptions are being updated for this final rule, this will
influence EPA's estimate of the oil import reductions and, in turn, the energy security benefits
estimated in this analysis. For the DRIA, a summary table was docketed that contained the
estimates of the oil import reduction factor. Table 7-18 shows that for a reduction in refined
product estimated by AEO's 2022 Low Economic Growth Case relative to the Reference Case,
88.9 percent of the reduced product demand is attributed to reduced imported crude oil, while 2.6
percent is attributed to increased net imported products - resulting in the 86.4 percent oil import
reduction factor. Global (i.e., rest of the world) oil demand is not changed in the Low Economic
Growth Case compared to the Reference Case, so the comparison between the AEO Reference
Case and the Low Economic Growth Case is only in the overall pattern of U.S. oil demand
changes.
801
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Table 7-18 Oil Import Reduction Factor based on AEO 2022
Average over the years 2027 to 2050
88.9
Percent reduction of imported crude oil
13.3
Percent reduction in domestic crude oil
-2.6
Percent reduction in net imported product
100.0
86.4
Total percentage of imported petroleum
For the final rule, the same methodology based on the AEO 2023 results in an 89.6 percent oil
import reduction factor - 84.8 percent of which would be due to reduced imported crude oil and
4.8 percent would be due to reduced net U.S. imported products.2065
Table 7-19 Oil Import Reduction Factor based on AEO 2023
Average over the years 2027 to 2050
84.8
Percent of imported crude oil
10.3
Percent reduction in domestic crude oil
4.8
Percent reduction in net imported product
100.0
89.6
Total percentage of imported petroleum
Use of the two AEO cases cited above estimates a large reduction in U.S. refinery throughput
- AEO 2022 estimates that 102.2 percent (89.9+13.3) of the reduced product demand would be
attributed to reduced throughput at U.S. refineries - this is rounded down to 100 percent. Based
on AEO 2023, the reduction in U.S. refinery throughput would be 95.1 percent (84.8+10.3).
However, for the final rulemaking, as noted above, we are estimating that U.S. refineries will
not reduce their throughput to the same extent. Instead, for a given reduction in a volume of
gasoline and diesel fuel demand, 50 percent of that reduced demand will be due to reduced
production by U.S. refineries, while for the other 50 percent, refineries will continue to operate,
and the U.S. will increase its refined product exports (i.e., reduce its net refined product imports).
Thus, we needed a way to estimate the energy security impacts assuming that U.S. refiners
would continue producing domestic fuels at a much higher level associated with the 50/50
assumption.
Since we are now estimating that in response to reduced refined product demand, half of that
reduced demand will be reduced production from U.S. refineries and the other half will be
increases in the exports of refined products (i.e., a decline in net refined product imports), two
different methods for estimating the oil import reduction factor are being used. The portion of
reduced refinery demand projected to result in reduced refinery throughput can be represented by
the oil import reduction factor estimated by the two 2023 AEO cases. However, since reduced
refinery throughput is estimated to comprise all of the reduced demand, we instead assumed that
the percent reduction in net U.S. imported product would also be reduced imported crude oil -
2065 Memo to Docket. Oil Import Reduction Factor Using AEO 2023. March 2024. Docket EPA-HQ-OAR-2022-
0985.
802
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thus, all of the 89.6 percent reduced imported petroleum would be imported crude oil.
Conversely, the balance of reduced refinery demand which U.S. refineries keep operating can be
represented by the oil import reduction factor which, by definition, would be 100 percent, since
U.S. refined product exports increase at the same rate that refinery demand decreases. Thus, the
oil import reduction factor is estimated by the following equation:
Oil Import Reduction Factor = 89.6% x 0.5 + 100% x 0.5 = 94.8%
If the sensitivity analysis 80/20 percent refinery throughput assumption is utilized, the oil
import reduction factor is estimated by the following equation:
Oil Import Reduction Factor = 89.6% x 0.2 + 100% x 0.8 = 97.9%
Based upon the changes in oil consumption estimated in Chapter 6.5 and the revised 94.8
percent oil import reduction factor, the reduction in U.S. oil imports as a result of the final CO2
emission standards for selected years are estimated below for the 2027-2055 timeframe. Once
U.S. oil import reductions are calculated, EPA multiplies the oil import reductions from the final
rule by the oil security premiums to calculate total energy security benefits over the timeframe of
the analysis of the final rule.
For comparison purposes, based upon the AEO 2023 (Reference Case), Table 7-20 also shows
the U.S.'s projected crude oil exports and imports, net refined petroleum product exports, net
crude oil/refined petroleum product exports and U.S. oil consumption for the same years in the
2027-2050 timeframe.2066
Table 7-20 Projected Trends in U.S. Oil Exports/Imports, Net Refined Petroleum Product Exports, Net
Crude Oil/Refined Petroleum Product Exports, Oil Consumption and U.S. Oil Import Reductions Resulting
from the Final Rule for Selected Years from 2027 to 2055 (MMBD)
2027
2030
2032
2035
2040
2045
2050
2055
U.S. Crude Oil Exports
3.3
3.4
3.4
3.4
3.2
3.2
2.9
-
U.S. Crude Oil Imports
6.9
7.0
7.1
7.1
7.2
7.1
6.6
-
U.S. Net Refined Petroleum Product
5.8
6.0
6.1
6.4
6.7
6.7
6.2
-
Exportsa
U.S. Net Crude Oil and Petroleum
2.3
2.4
2.5
2.8
2.8
2.9
2.7
-
Product Exports
U.S. Oil Consumption13
18.6
18.4
18.3
18.2
18.2
18.5
18.9
-
Reduction in U.S. Oil Imports from
the Final Standards 0
0.00
0.02
0.08
0.20
0.33
0.40
0.42
0.42
a Calculated from AEO 2023 Table A11 as Net Product Exports minus Ethanol, Biodiesel, Renewable Diesel, and
Other Biomass-derived Liquid Net Exports
b Calculated from AEO 2023 Table All as "Total Primary Supply" minus "Biofuels"
0 U.S. oil import reductions (in MMBD) are derived from Table 6-2 Estimated U.S. Oil Import Reductions and
Electricity and Hydrogen Consumption Increases due to the Final Rule in Chapter 6.5 of the RIA. Estimated U.S.
oil imports are rounded off from the estimates in Table 6-2
2066 EIA. 2023 .Annual Energy Outlook 2023. Reference Case. Table A11. Petroleum and Other Liquids Supply and
Disposition.
803
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7.3.5 Oil Security Premiums Used in the Final Rule
The total energy security benefits of this final HDV GHG Phase 3 rule are calculated based
upon U.S. net oil import reductions multiplied by the oil security premiums estimated for this
rule. In the proceeding section (Chapter 7.3.4), we present estimates of the U.S. oil import
reductions from this rule. In the section below, we present estimates of the oil security premiums
used for this rule.
In order to understand the energy security implications of reducing U.S. oil imports, EPA has
worked with Oak Ridge National Laboratory (ORNL), which has developed approaches for
evaluating the social costs and energy security implications of oil use. The energy security
estimates provided below are based upon a methodology developed in a peer-reviewed study
entitled, "The Energy Security Benefits of Reduced Oil Use, 2006-2015," completed in 2008.2067
This ORNL study is an updated version of the approach used for estimating the energy security
benefits of U.S. oil import reductions developed in a 1997 ORNL report.2068 This same approach
was first used in EPA GHG rules to estimate energy security benefits for the March 2010 RFS2
final rule.2069 ORNL has updated this methodology regularly for EPA to account for updated
projections of future energy market and economic trends reported in the U.S. EIA's AEO.
The ORNL methodology is used to compute the oil import premium (concept defined above
in Chapter 7.3.1) per b arrel of imported oil. The values of U. S. oil import premium components
(macroeconomic disruption/adjustment costs and monopsony components) are numerically
estimated with a compact model of the oil market by performing simulations of market outcomes
using probabilistic distributions for the occurrence of oil supply shocks, calculating marginal
changes in economic welfare with respect to changes in U.S. oil import levels in each of the
simulations, and summarizing the results from the individual simulations into a mean and 90
percent confidence intervals for the import premium estimates. The macroeconomic
disruption/adjustment import cost component is the sum of two parts: the marginal change in
expected import costs during disruption events and the marginal change in gross domestic
product due to the disruption. The monopsony component is the long-run change in U.S. oil
import costs as the level of oil import changes.
For this final rule, EPA is using oil import premiums that incorporate the oil price projections
and energy market and economic trends, particularly global regional oil supplies and demands
(i.e., the U.S./OPEC/rest of the world), from the AEO 2023 into its model.2070 EPA only
2067 Leiby, P. 2008. Estimating the Energy Security Benefits of Reduced U.S. Oil Imports. Final Report. ORNL/TM-
2007/028. Oak Ridge National Laboratory. March.
2068 Lejby. p.. Jones, D., Curlee, R. and Lee, R. 1997. Oil Imports: An Assessment of Benefits and Costs, ORNL-
6851. Oak Ridge National Laboratory. November.
2069 See 40 CFR Part 80, Regulation of Fuels and Fuels Additives: Changes to the Renewable Fuel Standard
Program; Final Rule, March 26, 2010.
2070 The oil market projection data used for the calculation of the oil import premiums came from AEO 2023,
supplemented by the latest EIA international projections from the International Energy Outlook (IEO) 2021. Global
oil prices and all variables describing U.S. supply and disposition of petroleum liquids (domestic supply, tight oil
supply fraction, imports, demands) as well as U.S. non-petroleum liquids supply and demand are from AEO 2023.
Global and OECD Europe supply/demand projections as well as OPEC oil production share are from IEO 2021. The
need to combine AEO 2023 and IEO 2021 data arises due to two reasons: (a) EIA stopped including Table 21
"International Petroleum and Other Liquids Supply, Disposition, and Prices" in the U.S. focused Annual Energy
Outlook after 2019, (b) EIA does not publish complete updates of the IEO every year.
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considers the avoided macroeconomic disruption/adjustment oil import premiums (i.e., labeled
macroeconomic oil security premiums below) as costs, since we consider the monopsony
impacts stemming from changes in U.S. oil imports transfer payments. In previous EPA rules
when the U.S. was projected by EIA to be a net importer of crude oil and petroleum-based
refined products, monopsony impacts represented reduced payments by U.S. consumers to oil
producers outside of the U.S. There was some debate among economists as to whether the U.S.
exercise of its monopsony power in oil markets, for example from the implementation of EPA's
rules, was a "transfer payment" or a "benefit". Given the redistributive nature of this monopsony
impact from a global perspective, and since there are no changes in resource costs when the U.S.
exercises its monopsony power, some economists argued that it is a transfer payment. Other
economists argued that monopsony impacts were a benefit since they partially address, and
partially offset, the market power of OPEC. In previous EPA rules, after weighing both
countervailing arguments, EPA concluded that the U.S.'s exercise of its monopsony power was a
transfer payment, and not a benefit.2071
In the timeframe covered by this final HD vehicle rule, the U.S.'s oil trade balance is
projected to be quite a bit different than during the time periods covered in many previous EPA
rules. Starting in 2020, the U.S. became a net exporter of crude oil and refined oil products and
the U.S. is projected to continue to be a net exporter of oil and refined petroleum products in the
timeframe covered by the analysis of the final GHG emission standards, 2027-2055. As a result,
reductions in U.S. oil consumption and, in turn, U.S. oil imports, still are expected to lower the
world oil price modestly. But the net effect of the lower world oil price in the 2027-2055 period
of this final rule is expected to be a decrease in revenue for U.S. exporters of crude oil and
refined petroleum products, instead of a decrease in payments to foreign oil producers. The
argument that monopsony impacts address the market power of OPEC is no longer appropriate.
Thus, we continue to consider the U.S. exercise of monopsony power to be transfer payments.
We also do not consider the effect of this final rule on the costs associated with existing energy
security policies (e.g., maintaining the Strategic Petroleum Reserve or strategic military
deployments), which are discussed above.
In addition, EPA and ORNL have worked together to revise the oil import premiums based
upon recent energy security literature. Based upon EPA and ORNL's review of the recent energy
security literature, EPA is assessing its macroeconomic oil security premiums for this final rule.
The recent economics literature (discussed in Chapter 7.3.2) focuses on three factors that can
influence the macroeconomic oil security premiums: the price elasticity of oil demand, the GDP
elasticity in response to oil price shocks, and the impacts of the U.S. tight (i.e., shale) oil boom.
We discuss each factor below and provide a rationale for how we are developing estimates for
the first two factors for the macroeconomic oil security premiums being used in this final rule.
We are not accounting for how U.S. tight oil is influencing the macroeconomic oil security
premiums in this final rule, other than how it significantly reduces the need for U.S. oil imports.
First, we assess the price elasticity of demand for oil. In previous EPA Vehicle rulemakings,
EPA used a short-run elasticity of demand for oil of-0.045.2072 In the most recent EPA rule
2071 See the previous EPA GHG vehicle assessment, Proposed Determination on the Appropriateness of the Model
Year 2022-2025 Light-Duty Greenhouse Gas Standards under the Mid-Term Evaluation. July 2016. Technical
Support Document. EPA-420-D-16-900.
2072 Ibid.
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setting GHG emissions standards for passenger cars and light trucks through model year 2026,
we used a short-run elasticity of demand for oil of-0.07, an update of previously used elasticities
based on the below considerations.2073 For this rule, we continue to use the elasticity value of-
0.07.
From the RFF study, the "blended" price elasticity of demand for oil is -0.05. The ORNL
meta-analysis estimate of this parameter is -0.07. We find the elasticity estimates from what RFF
characterizes as the "new literature," -0.175, and from the "new models" that RFF uses, -0.20 to
-0.33, somewhat high. We believe it would be surprising if short-run oil demand responsiveness
has changed in a dramatic fashion.
The ORNL meta-analysis estimate encompasses the full range of the economics literature on
this topic and develops a meta-analysis estimate from the results of many different studies in a
structured way, while the RFF study's "new models" results represent only a small subset of the
economics literature's estimates. Thus, we believe using a short-run price elasticity of demand
for oil of-0.07 is more appropriate. This increase has the effect of lowering the macroeconomic
oil security premium estimates undertaken by ORNL for EPA.
Second, we consider the elasticity of GDP to an oil price shock. In previous EPA Vehicle
rulemakings, EPA used an elasticity of GDP to an oil shock of-0.032.2074 In the most recent
EPA rule setting GHG emissions standards for passenger cars and light trucks through model
year 2026, we used an elasticity of GDP of-0.021, an update of previously used elasticities
based on the below considerations.2075 For this rule, we continue to use the elasticity value of-
0.021.
The RFF "blended" GDP elasticity is -0.028, the RFF's "new literature" GDP elasticity is -
0.018, while the RFF "new models" GDP elasticities range from -0.007 to -0.027. The ORNL
meta-analysis GDP elasticity is -0.021. We believe that the ORNL meta-analysis value is
representative of the recent literature on this topic since it considers a wider range of recent
studies and does so in a structured way. Also, the ORNL meta-analysis estimate is within the
range of GDP elasticities of RFF's "blended" and "new literature" elasticities. For this final rule,
EPA is using a GDP elasticity of-0.021, a 34 percent reduction from the GDP elasticity used
previously (i.e., the -0.032 value). This GDP elasticity is within the range of RFF's "new
literature" elasticity, -0.018, and the elasticity EPA has used in previous rulemakings, -0.032,
but lower than RFF's "blended" GDP elasticity, -0.028. This decrease has the effect of lowering
the macroeconomic oil security premium estimates. For U.S. tight oil, EPA has not made any
adjustments to the ORNL model, given the limited tight oil production response to rising world
oil prices in the recent 2020-2023 timeframe.2076 Increased tight oil production still results in
2073 Regulatory Impact Analysis: Revised 2023 and Later Model Year Light Duty Vehicle GHG Emissions
Standards. EPA-420-R-21-028, December 2021.
2074 See the previous EPA GHG vehicle assessment, Proposed Determination on the Appropriateness of the Model
Year 2022-2025 Light-Duty Greenhouse Gas Standards under the Mid-Term Evaluation. Technical Support
Document. EPA-420-R-16-021. November. 2016.
2075 Regulatory Impact Analysis: Revised 2023 and Later Model Year Light Duty Vehicle GHG Emissions
Standards. EPA-420-R-21-028, December 2021.
2076 The short-run oil supply elasticity assumed in the ORNL model is 0.06 and is applied to production from both
conventional and tight (i.e., shale) oil wells.
806
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energy security benefits though, through its impact of reducing U.S. oil imports in the ORNL
model.
Table 7-21 provides estimates of EPA's macroeconomic oil security premium estimates in the
2027-2055 timeframe. The macroeconomic oil security premiums are relatively steady over the
time period of this final rule at $3.73/barrel (9 cents/gallon) in 2027, $3.65/barrel in 2030 (9
cents/gallon), $4.61/barrel (11 cents per gallon) in 2040 and $5.22/barrel (12 cents/gallon) in
2050 and 2055 (in 2022 U.S. dollars).
Table 7-21 Macroeconomic Oil Security Premiums for Final Rule from 2027-2055 (2022$/Barrel)*
Calendar Year
Macroeconomic Oil Security Premiums (Mid-point/range)
2027
$3.73 ($0.51-$7.02)
2028
$3.78 ($0.51 -$7.15)
2029
$3.87 ($0.54-$7.31)
2030
$3.92 ($0.51 -$7.46)
2031
$4.00 ($0.55 - $7.62)
2032
$4.05 ($0.53 - $7.77)
2033
$4.11 ($0.47 - $7.93)
2034
$4.16 ($0.44 - $8.07)
2035
$4.22 ($0.45 - $8.20)
2036
$4.28 ($0.44 - $8.29)
2037
$4.35 ($0.47 - $8.40)
2038
$4.44 ($0.52 - $8.55)
2039
$4.50 ($0.53 - $8.66)
2040
$4.62 ($0.65 - $8.85)
2041
$4.73 ($0.70 - $9.04)
2042
$4.77 ($0.69-$9.15)
2043
$4.82 ($0.67 - $9.27)
2044
$4.85 ($0.66 - $9.35)
2045
$4.91 ($0.68 - $9.43)
2046
$4.98 ($0.71 -$9.52)
2047
$5.09 ($0.82 - $9.68)
2048
$5.14 ($0.85 - $9.79)
2049
$5.16 ($0.82 - $9.85)
2050
$5.22 ($0.91 -$9.89)
205 It
$5.22 ($0.91 -$9.89)
2052t
$5.22 ($0.91 -$9.89)
2053t
$5.22 ($0.91 -$9.89)
2054t
$5.22($0.91 - $9.89)
2055t
$5.22 ($0.91 -$9.89)
* Top-values in each cell are mean values. Values in parentheses are 90 percent
confidence intervals.
t The ORNL oil security premium estimation methodology does not provide
estimates for years after 2050 (the final year in the AEO projections which are used
in the ORNL energy security premium model). We extend the estimated 2050
premium to the years 2051 through 2055, which can be considered a conservative
assumption given the steadily increasing premium estimates produced through time
by the ORNL model.
807
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7.3.6 Energy Security Benefits of the Final Rule
Estimates of the total annual energy security benefits for the revised CO2 emission standards
for model year 2027 HD vehicles and new CO2 emission standards for HD vehicles in model
years 2028 through 2032 are based upon the ORNL oil import premium methodology with
updated oil import premium estimates reflecting the recent energy security literature and using
the AEO 2023. Annual per-gallon benefits are applied to the reductions in U.S. crude oil and
refined petroleum product imports. We do not consider military cost impacts or the monopsony
effect of U.S. crude oil and refined petroleum product import changes on the energy security
benefits of this final rule. The energy security benefits of this final rule are presented below in
Table 7-22, Energy Security Benefits from the Final Rule (in millions of 2022 dollars).
Table 7-22 Energy Security Benefits from the Final Rule (millions of 2022 dollars)
Calendar Year
Energy Security
Benefits
2027
$4
2028
$10
2029
$18
2030
$32
2031
$65
2032
$120
2033
$180
2034
$240
2035
$300
2036
$360
2037
$410
2038
$460
2039
$510
2040
$560
2041
$600
2042
$640
2043
$670
2044
$690
2045
$720
2046
$740
2047
$760
2048
$770
2049
$780
2050
$790
2051
$800
2052
$800
2053
$800
2054
$800
2055
$800
PV, 2%
$9,800
PV, 3%
$8,200
PV, 7%
$4,200
AV, 2%
$450
AV, 3%
$430
AV, 7%
$340
808
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809
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Chapter 8 Comparison of Benefits and Costs
This chapter compares the estimated range of benefits associated with reductions of GHGs,
monetized health benefits from reductions in PM2.5, energy security benefits, fuel savings, and
vehicle-related operating savings to total costs associated with the modeled potential compliance
pathway for the final rule and for the alternative. Estimated costs are detailed and presented in
Chapter 3 of this RIA. Those costs include costs for both the new technology in our modeled
potential compliance pathways' technology packages and the operating costs associated with that
new technology. Importantly, as detailed in Section IV of the preamble and Chapter 3 of this
RIA, the vehicle costs presented here exclude the IRA battery tax credit, the vehicle tax credit,
and the EVSE tax credit, while the fuel savings exclude fuel taxes. As such, as presented in this
section, these costs, along with other operating costs, represent the social costs and/or savings
associated with the final standards. Benefits from the reduction of GHG emissions and criteria
pollutant emissions and energy security benefits associated with reductions of imported oil are
presented in Chapter 7.
8.1 Methods
EPA presents three different benefit-cost comparisons for the final rule and the for the
alternative:
1. A future-year snapshot comparison of annual benefits and costs in the year 2055, chosen
to approximate the annual costs and benefits that will occur in a year when most of the
regulated fleet will consist of HD vehicles subject to the HD GHG Phase 3 standards due
to fleet turnover. Benefits, costs, and net benefits are presented in year 2022 dollars and
are not discounted.
2. The present value (PV) of the stream of benefits, costs, and net benefits calculated for the
analytical time horizon of 2027-2055, discounted back to the first year of implementation
of the final rule (2027) using 2-percent, 3-percent, and 7-percent discount rates, and
presented in year 2022 dollars.2077 Note that year-over-year costs are presented in RIA
Chapter 3 and year-over-year benefits can be found in RIA Chapter 7.
3. The equivalent annualized value (AV) of benefits, costs and net benefits representing a
flow of constant annual values that, had they occurred in each year from 2027 through
2055, will yield an equivalent present value to those estimated in method 2 (using a 2-
percent, 3-percent, and 7-percent discount rate). Each AV represents a typical benefit,
cost, or net benefit for each year of the analysis and is presented in year 2022 dollars.
2077 We use a constant 3-percent and 7-pecent discount rate to calculate present and annualized values, consistent
with current applicable OMB Circular A-4 guidance (2003). While we were conducting the analysis for this rule,
OMB finalized an update to Circular A-4 (2023), in which it recommended the general application of a 2-percent
discount rate to costs and benefits (see https://www.whitehouse.gOv/wp-content/uploads/2023/l l/CircularA-4.pdf).
Although the effective date of the updated Circular A-4 does not apply to this rulemaking, we have also included 2
percent discount rates in our analysis. Climate benefits, however, are based on reductions in GHG emissions and are
calculated using three different social cost estimates that assume either a 1.5-percent, 2.0-percent, or 2.5-percent
near-term Ramsey discount rate. For presentational purposes, we also use a constant 2-percent discount rate to
calculate present and annualized values to be approximately consistent with the SC-GHG values estimated using the
2-percent near-term Ramsey discount rate.
810
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8.2 Results
Table 8-1 shows the undiscounted annual monetized vehicle-related projected technology
package RPE costs of the final rule and the alternative in calendar year 2055. The table also
shows the PV and AV of those costs for the calendar years 2027-2055 using 2-percent, 3-percent
and 7-percent discount rates. The table includes an estimate of the projected vehicle technology
packages RPE costs and corresponding costs associated with EVSE.
Note that all costs, savings, and benefits estimates presented in the tables that follow are
rounded to two significant figures; numbers may not sum due to independent rounding.
Table 8-1 Vehicle-Related Technology Costs Associated with the Final Rule and Alternative, Millions of 2022
dollars
Final Rule
Alternative
Vehicle
EVSE RPE
Sum
Vehicle
EVSE RPE
Sum
Technology
Package
RPE
Technology
Package
RPE
2055
-$590
$1,100
$550
$55
$79
$130
PV, 2%
-$4,200
$28,000
$24,000
$3,000
$5,000
$8,000
PV, 3%
-$3,200
$25,000
$22,000
$2,600
$4,600
$7,200
PV, 7%
-$1,000
$15,000
$14,000
$1,700
$3,400
$5,000
AV, 2%
-$190
$1,300
$1,100
$140
$230
$370
AV, 3%
-$170
$1,300
$1,100
$140
$240
$380
AV, 7%
-$83
$1,300
$1,200
$140
$270
$410
Table 8-2 and Table 8-3 show the undiscounted annual monetized vehicle-related operating
savings of the final rule and alternative, respectively, in calendar year 2055. The tables also show
the PV and AV of those savings for the calendar years 2027-2055 using 2-percent, 3-percent and
7-percent discount rates. The savings in DEF consumption arise in the modeled potential
compliance pathway's technology packages from the decrease in diesel engine-equipped vehicles
which require DEF to maintain compliance with NOx emission standards. The maintenance and
repair savings are due again to the HD vehicle technologies utilized in the modeled potential
compliance pathway; BEVs are projected to ultimately require 71 percent of the maintenance
and repair and HD FCEVs are projected to ultimately require 75 percent of the maintenance and
repair required of HD ICE vehicles (see RIA Chapter 3.4.5).
811
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Table 8-2 Vehicle-Related Operating Savings Associated with the Final Rule, Millions of 2022 dollars *
Pre-tax
DEF
Savings
Maintenance
Insurance
Savings
Vehicle
EVSE
Sum of
Savings
Fuel
Savings
& Repair
Savings
Replacement
Savings
Replacement
Savings
2055
-$350
$1,800
$6,900
$250
$140
-$1,300
$7,400
PV, 2%
-$9,500
$21,000
$73,000
$1,300
$1,900
-$11,000
$76,000
PV, 3%
-$7,900
$17,000
$60,000
$1,000
$1,500
-$8,700
$63,000
PV, 7%
-$3,900
$8,700
$30,000
$460
$720
-$3,700
$32,000
AV, 2%
-$430
$950
$3,300
$60
$86
-$500
$3,500
AV, 3%
-$410
$900
$3,100
$55
$80
-$450
$3,300
AV, 7%
-$310
$710
$2,400
$38
$58
-$300
$2,600
*Fuel savings are net of savings in diesel, gasoline, and CNG consumption with increased electricity and
hydrogen consumption; DEF savings accrue only to diesel vehicles; maintenance and repair savings include
impacts associated with all fuels; replacement savings are net of costs associated with replacement/rebuild of
liquid-fueled engines and replacement of batteries on electric vehicles.
Table 8-3 Vehicle-Related Operating Savings Associated with the Alternative, Millions of 2022 dollars *
Pre-tax
DEF
Savings
Maintenance
Insurance
Savings
Vehicle
EVSE
Sum of
Savings
Fuel
Savings
& Repair
Savings
Replacement
Savings
Replacement
Savings
2055
-$1,300
$580
$2,000
-$78
$44
-$130
$1,100
PV, 2%
-$16,000
$7,500
$25,000
-$830
$710
-$2,700
$13,000
PV, 3%
-$13,000
$6,200
$21,000
-$680
$590
-$2,200
$11,000
PV, 7%
-$6,500
$3,200
$10,000
-$310
$280
-$1,000
$6,100
AV, 2%
-$750
$340
$1,100
-$38
$33
-$120
$600
AV, 3%
-$700
$330
$1,100
-$35
$31
-$110
$580
AV, 7%
-$530
$260
$850
-$25
$23
-$81
$490
*Fuel savings are net of savings in diesel, gasoline, and CNG consumption with increased electricity and
hydrogen consumption; DEF savings accrue only to diesel vehicles; maintenance and repair savings include
impacts associated with all fuels; replacement savings are net of costs associated with replacement/rebuild of
liquid-fueled engines and replacement of batteries on electric vehicles.
Table 8-4 shows the undiscounted annual monetized energy security benefits of the final rule
and the alternative in calendar year 2055. The table also shows the PV and AV of those benefits
for the calendar years 2027-2055 using 2-percent, 3-percent and 7-percent discount rates.
Table 8-4 Energy Security Benefits Associated with the Final Rule and Alternative, Millions of 2022 dollars
Final Rule
Alternative
2055
$800
$240
PV, 2%
$9,800
$3,400
PV, 3%
$8,200
$2,800
PV, 7%
$4,200
$1,500
AV, 2%
$450
$150
AV, 3%
$430
$150
AV, 7%
$340
$120
Table 8-5 shows the benefits of reduced GHG emissions, and consequently the annual
quantified benefits (i.e., total GHG benefits), for each of the three social cost of GHG (SC-GHG)
812
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values estimated by the EPA Report on the Social Cost of Greenhouse Gases: Estimates
Incorporating Recent Scientific Advances (EPA 2023).2078 As discussed in RIA Chapter 7, there
are some limitations to the SC-GHG analysis, including the incomplete way in which the
integrated assessment models capture catastrophic and non-catastrophic impacts, their
incomplete treatment of adaptation and technological change, uncertainty in the extrapolation of
damages to high temperatures, and assumptions regarding risk aversion. These climate benefits
include benefits associated with changes to HD vehicle GHGs and both refinery and EGU GHG
emissions, but do not include any impacts associated with the extraction or transportation of
fuels for either EGUs or refineries.
Table 8-6 shows the undiscounted annual monetized PIVh.s-related health benefits of the final
rule and the alternative in calendar year 2055. The table also shows the PV and AV of those
benefits for the calendar years 2027 through 2055 using a 2-percent, 3-percent and 7-percent
discount rate. The benefits in Table 8-6 reflect the two premature mortality estimates derived
from the Medicare study (Wu et al., 2020) and the NHIS study (Pope et al., 2019).2079'2080 The
monetized criteria pollutant health benefits include reductions in PM2.5-related emissions from
HD vehicles. Monetized upstream health impacts associated with the standards also include
benefits associated with reduced PM2.5-related emissions from refineries and health disbenefits
associated with increased PM2.5-related emissions from EGUs. Negative monetized values are
associated with health disbenefits related to increases in estimated emissions from EGUs.
Depending on the discount rate used, the present and annualized value of the stream of PM2.5-
related benefits may either be positive or negative.
Table 8-5 Climate Benefits from Reduction in GHG Emissions Associated with the Final Rule and
Alternative, Millions of 2022 dollars
Final Rule
Alternative
1.5% Average
2% Average
2.5% Average
1.5%
Average
2% Average
2.5% Average
2055
$15,000
$22,000
$34,000
$4,300
$6,400
$9,800
PV
$130,000
$220,000
$390,000
$42,000
$71,000
$120,000
AV
$6,600
$10,000
$17,000
$2,100
$3,200
$5,300
Notes:
Climate benefits are based on changes (reductions) in CO2, CH4, and N20 emissions and are calculated using
three different estimates of the social cost of carbon (SC-CO2), the social cost of methane (SC-CH4), and the
social cost of nitrous oxide (SC-N20) (model average at 1.5-percent, 2-percent, and 2.5-percent Ramsey discount
rates). See RIA Chapter 7.1 for more information. Annual benefits shown are undiscounted values.
2078 For more information about the development of these estimates, see www.epa.gov/environmental-
economics/scghg.
2079 Wu, X, Braun, D, Schwartz, J, Kioumourtzoglou, M and Dominici, F (2020). Evaluating the impact of long-term
exposure to fine particulate matter on mortality among the elderly. Science advances 6(29): eaba5692.
2080 Pope III, CA, Lefler, JS, Ezzati, M, Higbee, JD, Marshall, JD, Kim, S-Y, Bechle, M, Gilliat, KS, Vernon, SE
and Robinson, AL (2019). Mortality risk and fine particulate air pollution in a large, representative cohort of US
adults. Environmental health perspectives 127(7): 077007.
813
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Table 8-6 Monetized PIVh.s-related Emission Benefits Associated with the Final Rule and Alternative, Millions
of 2022 dollars
Final Rule
Alternative
2%
3%
7%
2%
3%
7%
2055
$1,000-1,900
$1,000-1,900
$900-1,700
$270-520
$270-520
$240-470
PV
$3,500-6,500
$2,300-4,200
$(110)-(400)
$320-480
$40-(58)
$(440)-(950)
AV
$160-300
$120-220
$(9.1)-(32)
$15-22
$2.1-(3.0)
$(36)-(77)
Notes:
Monetized PM2 5-related health impacts are based on benefit-per-ton (BPT) values. The benefits in this table
reflect two premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the NHIS study
(Pope III et al., 2019), respectively. Annual PM25 BPT estimates use 3-percent and 7-percent discount rates to
account for avoided health outcomes that are expected to accrue over more than a single year (the "cessation lag"
between the change in PM exposures and the total realization of changes in health effects). We do not currently
have BPT estimates that use a 2-percent discount rate to account for cessation lag; for this reason, annual benefits
in 2055 are the same in the 2% and 3% columns.
All benefits estimates are rounded to two significant figures. The present value of benefits is the total aggregated
value of the series of discounted annual benefits that occur between 2027-2055 (in 2022 dollars) using either a 2-
percent, 3-percent, or 7-percent discount rate.
Monetized criteria pollutant health benefits include reductions in PM2 5-related emissions from HD vehicles.
Monetized upstream health impacts associated with the standards also include benefits associated with reduced
PM2 5-related emissions from refineries and health disbenefits associated with increased PM2 5-related emissions
from EGUs. Negative monetized values in parentheses are associated with health disbenefits related to increases
in estimated emissions from EGUs. Depending on the discount rate used, the present and annualized value of the
stream of PM2 5 benefits may either be positive or negative.
The benefits in this table also do not include the full complement of health and environmental benefits (such as
health benefits related to reduced ozone exposure) that, if quantified and monetized, would increase the total
monetized benefits.
Table 8-7 shows the undiscounted annual total benefits of the final standards and alternative
in calendar year 2055, as well as the PV and AV of the total benefits for the calendar years 2027
through 2055. Total benefits are the sum of climate benefits, non-GHG benefits and energy
security benefits. The present and annualized values of energy security benefits and PM2.5 health
impacts are discounted using either a 2-percent, 3-percent, or 7-percent constant discount rate
(see Table 8-4 and Table 8-6, respectively). Climate benefits are based on reductions in GHG
emissions and are calculated using three different social cost estimates that assume either a 1.5-
percent, 2.0-percent, or 2.5-percent near-term Ramsey discount rate (see Table 8-5). For
presentational purposes in Table 8-7, we use the climate benefits associated with the SC-GHG
under the 2-percent near-term Ramsey discount rate for the total benefits calculation. The
benefits include those associated with changes to HD vehicle GHGs and both EGU and refinery
GHG emissions, but do not include any impacts associated with the extraction or transportation
of fuels for either EGUs or refineries. This likely underestimates the refinery-related emission
reductions projected in the rule but likely also underestimates EGU-related emission increases in
the rule.
814
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Table 8-7 Total Benefits Associated with the Final Rule and Alternative, Millions of 2022 dollars
Final Rule
Alternative
2055
$25,000
$7,100
PV, 2%
$240,000
$75,000
PV, 3%
$240,000
$73,000
PV, 7%
$230,000
$71,000
AV, 2%
$11,000
$3,400
AV, 3%
$11,000
$3,400
AV, 7%
$11,000
$3,300
Notes:
Total benefits are the sum of climate benefits, PM2 5-related benefits and energy security benefits.
Climate benefits are based on reductions in GHG emissions and are calculated using three different SC-
GHG estimates that assume either a 1.5-percent, 2.0-percent, or 2.5-percent near-term Ramsey discount rate
(see Table 8-5). For presentational purposes in this table, we use the climate benefits associated with the
SC-GHG under the 2-percent near-term Ramsey discount rate for the total benefits calculation.
The present and annualized values of energy security benefits and PM2 5 health impacts are discounted using
either a 2-percent, 3-percent, or 7-percent constant discount rate (see Table 8-4 and Table 8-6, respectively).
For presentational clarity, we use the monetized suite of total avoided PM2 5-related health effects that
includes avoided deaths based on the Pope III et al., 2019 study, which is the larger of the two PM25 health
benefits estimates presented in RIA Chapter 7.2. All benefits estimates are rounded to two significant
figures.
We summarize the vehicle costs, operational savings, and benefits of the final rule, as shown
in Table 8-8. Table 8-8 reproduces the final rule's costs from Table 8-1, operating savings from
Table 8-2, benefits from Table 8-7 (comprised of benefits presented in Table 8-4 through Table
8-6), in a single table. We summarize the vehicle costs, operational savings, and benefits of the
alternative in Table 8-9. We remind readers that, in the NPRM, we used the interim SC-GHG
values, while in this final rule we are using the updated SC-GHG values (see RIA Chapter 7.1).
We include the 2 percent discount rate here for consistency with the 2 percent near-term Ramsey
discount rate used in the updated SC-GHG values.
815
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Table 8-8 Summary of Vehicle Costs, Operating Savings, and Benefits of the Final Rule, Billions of 2022
Dollars
CY 2055
PV, 2%
PV, 3%
PV, 7%
AV, 2%
AV, 3%
AV, 7%
Vehicle Technology Package
RPE
-$0.59
-$4.2
-$3.2
-$1
-$0.19
-$0.17
-$0,083
EVSE RPE
$1.1
$28
$25
$15
$1.3
$1.3
$1.3
Sum of Vehicle Costs
$0.55
$24
$22
$14
$1.1
$1.1
$1.2
Pre-tax Fuel Savings
-$0.35
-$9.5
-$7.9
-$3.9
-$0.43
-$0.41
-$0.31
Diesel Exhaust Fluid
Savings
$1.8
$21
$17
$8.7
$0.95
$0.9
$0.71
Repair & Maintenance
Savings
$6.9
$73
$60
$30
$3.3
$3.1
$2.4
Insurance Savings
$0.25
$1.3
$1
$0.46
$0.06
$0,055
$0,038
Vehicle Replacement
Savings
$0.14
$1.9
$1.5
$0.72
$0,086
$0.08
$0,058
EVSE Replacement Savings
-$1.3
-$11
-$8.7
-$3.7
-$0.5
-$0.45
-$0.3
Sum of Operating Savings
$7.4
$76
$63
$32
$3.5
$3.3
$2.6
Energy Security Benefits
$0.8
$9.8
$8.2
$4.2
$0.45
$0.43
$0.34
Climate Benefits - 2%
Average Ramsey3
$22
$220
$220
$220
$10
$10
$10
PM2 5 Health Benefitsbcd
$1.9
$6.5
$4.2
-$0.4
$0.3
$0.22
-$0,032
Sum of Benefits
$25
$240
$240
$230
$11
$11
$11
Net Benefits
$32
$290
$280
$250
$13
$13
$12
a Climate benefits are based on reductions in GHG emissions and are calculated using three different SC-GHG
estimates that assume either a 1.5-percent, 2.0-percent, or 2.5-percent near-term Ramsey discount rate. For
presentational purposes in this table, we use the climate benefits associated with the SC-GHG under the 2-percent
near-term Ramsey discount rate. See Table 8-5 for the full range of monetized climate benefit estimates. All other
costs and benefits are discounted using either a 2-percent, 3-percent, or 7-percent constant discount rate. For
further discussion of the SC-GHGs and how EPA accounted for these estimates, please refer to Chapter 7 of the
RIA.
b Monetized non-GHG health benefits are based on PM2 5-related benefit-per-ton (BPT) values. To calculate net
benefits, we use the monetized suite of total avoided PM2 5-related health effects that includes avoided deaths
based on the Pope III et al., 2019 study, which is the larger of the two PM25 health benefits estimates presented in
RIA Chapter 7.2.
0 The annual PM2 5 health benefits estimate presented in the CY 2055 column reflects the value of certain avoided
health outcomes, such as avoided deaths, that are expected to accrue over more than a single year discounted
using a 3-percent discount rate.
d We do not currently have year-over-year estimates of PM2 5 benefits that discount such annual health outcomes
using a 2-percent discount rate. We have therefore discounted the annual stream of health benefits that reflect a 3-
percent discount rate lag adjustment using a 2-percent discount rate to populate the PV, 2% and AV, 2% columns.
The annual stream of PM2 5-related health benefits that reflect a 3-percent and 7-percent discount rate lag
adjustment were used to populate the PV/AV 3% and PV/AV 7% columns, respectively. See RIA Chapter 7.2 for
more details on the annual stream of PM2 5-related benefits associated with this rule.
816
-------
Table 8-9 Summary of Vehicle Costs, Operating Savings, and Benefits of the Alternative, Billions of 2022
Dollars
CY
PV,
PV,
PV,
AV,
AV,
AV,
2055
2%
3%
7%
2%
3%
7%
Vehicle Technology Package RPE
$0,055
$3
$2.6
$1.7
$0.14
$0.14
$0.14
EVSE RPE
$0,079
$5
$4.6
$3.4
$0.23
$0.24
$0.27
Sum of Vehicle Costs
$0.13
$8
$7.2
$5
$0.37
$0.38
$0.41
Pre-tax Fuel Savings
-$1.3
-$16
-$13
-$6.5
-$0.75
-$0.7
-$0.53
Diesel Exhaust Fluid Savings
$0.58
$7.5
$6.2
$3.2
$0.34
$0.33
$0.26
Repair & Maintenance Savings
$2
$25
$21
$10
$1.1
$1.1
$0.85
Insurance Savings
-$0,078
-$0.83
-$0.68
-$0.31
-$0,038
-$0,035
-$0,025
Vehicle Replacement Savings
$0,044
$0.71
$0.59
$0.28
$0,033
$0,031
$0,023
EVSE Replacement Savings
-$0.13
-$2.7
-$2.2
-$1
-$0.12
-$0.11
-$0,081
Sum of Operating Savings
$1.1
$13
$11
$6.1
$0.6
$0.58
$0.49
Energy Security Benefits
$0.24
$3.4
$2.8
$1.5
$0.15
$0.15
$0.12
Climate Benefits - 2% Average
Ramsey3
$0.64
$71
$71
$71
$3.2
$3.2
$3.2
PM2 5 Health Benefitsbcd
$0.52
$0.48
-$0,058
-$0.95
$0,022
-$0,003
-$0,077
Sum of Benefits
$7.1
$75
$73
$71
$3.4
$3.4
$3.3
Net Benefits®
$8.1
$80
$77
$72
$3.6
$3.6
$3.4
a Climate benefits are based on reductions in GHG emissions and are calculated using three different SC-GHG
estimates that assume either a 1.5 percent, 2.0 percent, or 2.5 percent near-term Ramsey discount rate. For
presentational purposes in this table, we use the climate benefits associated with the SC-GHG under the 2-percent
near-term Ramsey discount rate. See Table 8-5 for the full range of monetized climate benefit estimates. All other
costs and benefits are discounted using either a 2-percent, 3-percent, or 7-percent constant discount rate. For
further discussion of the SC-GHGs and how EPA accounted for these estimates, please refer to Chapter 7 of the
RIA.
b Monetized non-GHG health benefits are based on PM2 5-related benefit-per-ton (BPT) values. To calculate net
benefits, we use the monetized suite of total avoided PM2 5-related health effects that includes avoided deaths
based on the Pope III et al., 2019 study, which is the larger of the two PM2.5 health benefits estimates presented in
RIA Chapter 7.2.
0 The annual PM2.5 health benefits estimate presented in the CY 2055 column reflects the value of certain avoided
health outcomes, such as avoided deaths, that are expected to accrue over more than a single year discounted
using a 3-percent discount rate.
d We do not currently have year-over-year estimates of PM2.5 benefits that discount such annual health outcomes
using a 2-percent discount rate. We have therefore discounted the annual stream of health benefits that reflect a 3-
percent discount rate lag adjustment using a 2-percent discount rate to populate the PV, 2% and AV, 2% columns.
The annual stream of PM2 5-related health benefits that reflect a 3-percent and 7-percent discount rate lag
adjustment were used to populate the PV/AV 3% and PV/AV 7% columns, respectively. See RIA Chapter 7.2 for
more details on the annual stream of PM2 5-related benefits associated with this rule.6 Net benefits are the sum of
benefits and operating savings minus vehicle costs.
We have also estimated the total transfers, or taxes, associated with the final standards, as
shown in Table 8-10 and the alternative, as shown in Table 8-11. The transfers consist of the
IRA battery tax credit, vehicle tax credit, EVSE tax credits, fuel, federal excise and state sales
taxes, and annual vehicle registration fees on all ZEVs. None of these are included in the prior
tables in this comparison of benefits and costs. Note that the transfers are presented from the
perspective of purchasers, so positive values represent transfers to purchasers.
817
-------
Table 8-10 Transfers Associated with the Final Rule, Millions of 2022 Dollars
Battery
Tax
Credits
Vehicle
Tax
Credits
EVSE
Tax
Credits
Fuel
Taxes
Federal
Excise
Taxes
State
Sales
Taxes
State
Registration
Fees on
ZEVs
Sum
2055
$0
$0
$0
$3,400
-$11
$30
-$230
$3,200
PV, 2%
$1,400
$1,500
$950
$46,000
-$990
$280
-$2,500
$46,000
PV, 3%
$1,300
$1,400
$910
$38,000
-$890
$230
-$2,100
$39,000
PV, 7%
$1,100
$1,100
$770
$20,000
-$580
$110
-$1,000
$22,000
AV, 2%
$63
$67
$43
$2,100
-$45
$13
-$110
$2,100
AV, 3%
$69
$73
$47
$2,000
-$46
$12
-$110
$2,100
AV, 7%
$92
$93
$63
$1,600
-$47
$8.8
-$85
$1,800
Table 8-11 Transfers Associated with the Alternative, Millions of 2022 Dollars
Battery
Tax
Credits
Vehicle
Tax
Credits
EVSE
Tax
Credits
Fuel
Taxes
Federal
Excise
Taxes
State
Sales
Taxes
State
Registration
Fees on
ZEVs
Sum
2055
$0
$0
$0
$990
-$9.8
-$2.8
-$46
$930
PV, 2%
$670
$700
$400
$16,000
-$510
-$120
-$660
$16,000
PV, 3%
$650
$670
$380
$13,000
-$450
-$99
-$560
$14,000
PV, 7%
$550
$550
$330
$7,100
-$290
-$56
-$300
$7,800
AV, 2%
$31
$32
$18
$710
-$23
-$5.3
-$30
$740
AV, 3%
$34
$35
$20
$680
-$24
-$5.2
-$29
$720
AV, 7%
$45
$45
$27
$570
-$24
-$4.6
-$25
$640
818
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Chapter 9 Small Business Analysis
The Regulatory Flexibility Act, as amended by the Small Business Regulatory Enforcement
Fairness Act of 1996 (SBREFA), generally requires an agency to prepare a regulatory flexibility
analysis for any rule subject to notice-and-comment rulemaking requirements under the
Administrative Procedure Act or any other statute. This requirement does not apply if the agency
certifies that the rule will not have a significant economic impact on a substantial number of
small entities. This chapter contains an overview of small entities in the heavy-duty vehicle and
engine market and our assessment that the rule will not have a significant impact on a substantial
number of small entities.
9.1 Definition of Small Businesses
Under the Regulatory Flexibility Act (5 USC 601 et seq.), a small entity is defined as: (1) a
business that meets the definition for small business based on the Small Business
Administration's (SBA) size standards; (2) a small governmental jurisdiction that is a
government of a city, county, town, school district or special district with a population of less
than 50,000; or (3) a small organization that is any not-for-profit enterprise which is
independently owned and operated and is not dominant in its field.
This analysis considers only small business entities that are potentially affected by the final
GHG emission standards. Small governmental jurisdictions and small not-for-profit
organizations are not subject to the rule as they have no certification or compliance requirements.
Note that while the proposed rule included changes to the locomotive preemption provision, that
portion of the proposed rule was finalized in a separate action and is therefore not part of this
RFA analysis.
9.2 Categories of Small Businesses Potentially Affected by the Rule
There are four broad categories of highway heavy-duty engine and vehicle entities that are
potentially affected by the rule:
• Heavy-duty engine manufacturers
• Heavy-duty conventional vehicle manufacturers, including:
o Manufacturers that make both the engine and the vehicle
o Manufacturers that make a vehicle of its own design using an engine certified
by another company
o Manufacturers that finish an incomplete vehicle produced and certified by
another company
• Heavy-duty electric vehicle manufacturers
• Alternative fuel engine converters
819
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Table 9-1 provides an overview of the primary SB A small business categories for the industry
sectors potentially affected by this rule, by NAICS category.
Table 9-1 Primary Small Business NAICS Categories Affected by this Rule2081
NAICS Codes
(2022)2082
Defined by SBA
(3/17/2023) as a small
business if less than or
equal to:2083
Other Engine Equipment
Manufacturing
333618
1,500 employees
Automobile and Light Duty
Motor Vehicle Manufacturing
336110
1,500 employees
Heavy-Duty Truck
Manufacturer,
Conventional or Electric
336120
1,500 employees
Secondary manufacturer:
Motor Vehicle Body
Manufacturing
336211
1,000 employees
Secondary manufacturer:
Motor home manufacturing
336213
1,250 employees
All Other Automotive Repair
and Maintenance (alternative
fuel engine converters)
811198
$10.0 million annual
receipts
This regulatory flexibility analysis was performed using data on small entities assembled for
EPA's Final Rule: Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine and
Vehicle Standards, finalized in December 2022. Chapter 11 of the Regulatory Impact
Assessment for that rule describes how EPA identified the small entities in each of the relevant
NAICS categories and the results of applying that methodology.2084 The following small entities
were identified: 14 small entity heavy-duty vehicle manufacturers (one conventional vehicle
manufacturer and 13 electric vehicle manufacturers; this was reduced to 9 in the following
analysis because three did not meet the definition of small entity and one has not filed a
production report with EPA and is therefore assumed to not be producing vehicles), 249 small
entity secondary vehicle manufacturers, and 2 small entity alternative fuel engine converters.
2081 According to SBA's regulations (13 CFR Part 121), businesses with no more than the listed number of
employees or dollars in annual receipts are considered "small entities" for RFA purposes.
2082 North American Industry Classification System, United States, 2022. Executive Office of the President, Office
of Management and Budget. Downloaded 2/10/23. The official OMB publication is available at
https://www.census.gov/naics/reference_files_tools/2022_NAICS_Manual.pdf.
2083 U.S. Small Business Administration. Table of Small Business Size Standards Matched to North American
Industry Classification System Codes. Effective March 17, 2023. Downloaded 12/12/23. The official SBA
publication is available at https://www.sba.gov/document/support-table-size-standards; .pdf version at
https://www.sba.gov/sites/default/files/2023-
06/Table%20of%20Size%20Standards_Effective%20March%2017%2C%202023%20%282%29.pdf
2084 See Chapter 11, Small Business Analysis, in Control of Air Pollution from New Motor Vehicles: Heavy-Duty
Engine and Vehicle Standards Draft Regulatory Impact Analysis, EPA-420-D-22-001, March 2022, finalized
December 2022, EPA-420-R-22-035.
820
-------
9.3 Description of Small Businesses Potentially Affected by the Rule
This section provides a brief description of each of the four categories of manufacturers and
the number of small entities potentially affected by the rule. The information about these
companies presented below is consistent with the Regulatory Flexibility Analysis developed for
our recently finalized HD 2027 rulemaking.2085
9.3.1 Heavy-Duty Engine Manufacturers
Heavy-duty engine manufacturers have been developing, testing, and certifying engines for
many years in compliance with EPA rulemakings adopted under the CAA. The heavy-duty
engine manufacturers that certify engines to EPA's program include no small entities based on
the SBA definition for this category. This rule does not include new heavy-duty engine
standards.
9.3.2 Heavy-Duty Conventional Vehicle Manufacturers
There are three types of companies that manufacture heavy-duty vehicles and that may be
affected by the rule.
The first type of company manufactures both the engine and the associated vehicle. None of
these companies are small entities based on the SBA definition for this category.
The second type of vehicle manufacturer produces a vehicle of its own design using a
certified engine produced and certified by a different company. We identified one small entity
engaged in the manufacture of conventional vehicles based on the SBA definition for this
category and employment data from Hoovers D&B. This company is not subject to the new
standards; instead, the company will continue to be subject to the previously promulgated
standards. We assessed the regulatory burden of the program for this company by comparing its
expected burden (a one-time cost of about $4,855 to review the regulations and make any needed
changes to their general certification processes) to annual revenue obtained from Experian.
According to this analysis, the small entity is expected to experience an impact of less than 1
percent of annual revenue.
The third type of vehicle manufacturer finishes an incomplete vehicle produced and certified
by a different company; these so-called "secondary manufacturers" complete the vehicle by
adding the truck body and other equipment. We identified 249 alternative fuel converters that are
small businesses based on the SBA definition for this category and employment data from
Hoovers D&B. Because the incomplete vehicle is already certified, these secondary vehicle
manufacturers are not subject to the standards. Notes that any cost increases incurred by the
primary manufacturer that are passed on to the secondary manufacturer through their delegated
assembly agreement are included under the compliance costs of the main program, and are not
part of this regulatory flexibility analysis.
2085 See Chapter 11, Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine and Vehicle Standards
Regulatory Impact Analysis (EPA-420-R-22-035 December 2022).
https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1016A9N.pdf.
821
-------
9.3.3 Heavy-Duty Electric Vehicle Manufacturers
Heavy-duty electric vehicle manufacturers make both the engine and the associated vehicle.
In 2021, 25 companies that make electric heavy-duty vehicles certified with EPA. We identified
9 small entities based on the SBA definition for this category and employment data from
Hoovers D&B.
Qualifying small EV manufacturers are not subject to the new standards; instead, the
company will continue to be subject to the previously promulgated standards (see Section II of
the Preamble). However, small EV manufacturers will have to comply with a new regulation to
provide a battery health monitor and make associated changes to vehicle owners manuals. We
estimate compliance will impose a one-time cost of about $20,000 for each EV manufacturer,
including small manufacturers2086. In addition, EV manufacturers will be subject to the warranty
requirement at 40 CFR 1037.120. Because EV manufacturers already provide vehicle warranties
and thus have the systems in place to implement the warranty requirements in their pricing,
compliance costs will be limited to reporting their warranty periods on their certification
application and updating owners manuals. We estimate compliance will impose a one-time cost
of about $991 for each EV manufacturer, including small manufacturers.2087 Finally, we
estimate a one-time cost of about $4,855 for each manufacturer, including small EV
manufacturers, to review the regulations and make any needed changes to their general
certification processes.
We assessed the regulatory burden of the program for each of the 9 small EV manufacturers
by comparing estimated compliance costs with annual revenue obtained from Hoovers or
Experian for that company or its parent company if the affected company is a subsidiary of
another company. According to this analysis, no small entity is expected to experience an
impact greater than 3 percent of annual revenue. Eight of the 9 companies are expected to
experience an impact of less than one percent and 1 is expected to experience an impact of 1 to 3
percent.
9.3.4 Alternative Fuel Engine Converters
Alternative fuel engine converters are also subject to heavy-duty highway engine standards.
We identified two alternative fuel converters that are small businesses based on the SBA
definition for this category and employment data from Hoovers D&B. We are not adopting new
engine standards for this sector in this rule and there is no new burden for alternative fuel engine
converters, including small entities, as a result of this rule.
9.4 Potential Impacts on Small Entities
EPA is certifying that the rule will not have a significant economic impact on a substantial
number of small entities. Small entities are exempt from the revisions to EPA's HD Phase 2
GHG requirements for MY 2027 and the HD Phase 3 GHG program requirements for model
years 2028 through 2032. While small entities will be required to comply with the new
regulations regarding battery health monitors and make associated changes to their owners
2086 We estimate $15,100 in Operations and Maintenance costs and $4,378 in Labor costs. See the Supporting
Statement for the draft Information Collection Request for this rule, in Docket EPA-HQ-OAR-2022-0985.
2087 See the Supporting Statement for the draft Information Collection Request for this rule, in Docket EPA-HQ-
OAR-2022-0985.
822
-------
manuals, we estimate that these costs will exceed 3 percent of annual revenue for no small
companies within the regulated industries. Given the results of this analysis, we have therefore
concluded that this action will not have a significant economic impact on a substantial number of
small entities. Table 9-2 summarizes the results.
Table 9-2 Summary of Small Entity Impacts
Number of
Impact as
percent of annual
NAICS
Category
Sector description
SBA
Threshold
small companies
subject to the
revenue,
number of small
rule
companies
>3%
1-3%
<1%
336120
Heavy-duty conventional
vehicle manufacturer
1,500 employees
1
1
336120
Heavy-duty electric
vehicle manufacturers
1,500 employees
9
0
1
8
Total
10
0
1
9
823
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Appendix A - VMT for HD TRUCS
This Appendix A presents the VMT used in the final version of HD TRUCS for each of the
first ten years of operation. The 10-year schedule for VMT in Table A-l, combined with the
M&R cost per mile (by vehicle age), the cost of diesel and DEF per gallon (by calendar year),
and the cost of insurance can be used to calculate the operating costs for each year of a 10-year
schedule (see RIA Chapter 2).
Table A-l VMT by Vehicle Age
Vehicle ID
Vehicle Age (years)
0
1
2
3
4
5
6
7
8
9
01V Amb C14-5 MP
8,480
8,444
8,448
8,508
8,091
7,612
7,072
6,579
6,158
5,863
02V Amb C12b-3 MP
12,353
12,300
12,305
12,392
11,786
11,088
10,301
9,583
8,969
8,540
03V Amb C14-5 U
9,769
9,728
9,731
9,801
9,321
8,769
8,147
7,579
7,094
6,754
04V Amb C12b-3 U
9,941
9,899
9,902
9,973
9,485
8,923
8,290
7,712
7,218
6,873
05T Box C18 MP
16,500
16,430
16,436
16,553
15,743
14,810
13,759
12,800
11,981
11,407
06T Box C18 R
16,500
16,430
16,436
16,553
15,610
14,543
13,360
12,267
11,305
10,565
07T Box C16-7 MP
9,961
9,918
9,922
9,993
9,504
8,941
8,306
7,727
7,233
6,886
08T Box C16-7 R
9,961
9,918
9,922
9,993
9,423
8,779
8,065
7,405
6,824
6,378
09T Box C18 U
16,500
16,430
16,436
16,553
15,743
14,810
13,759
12,800
11,981
11,407
10T Box C16-7 U
9,718
9,676
9,680
9,749
9,272
8,722
8,104
7,539
7,056
6,718
11T Box C12b-3 U
14,836
14,773
14,778
14,883
14,155
13,316
12,371
11,509
10,772
10,256
12T Box C12b-3 R
14,836
14,773
14,778
14,883
14,155
13,316
12,371
11,509
10,772
10,256
13T Box C12b-3 MP
14,836
14,773
14,778
14,883
14,155
13,316
12,371
11,509
10,772
10,256
14T Box C14-5 U
9,526
9,485
9,489
9,556
9,089
8,550
7,944
7,390
6,917
6,585
15T Box C14-5 R
9,526
9,485
9,489
9,556
9,089
8,550
7,944
7,390
6,917
6,585
16T Box C14-5 MP
9,526
9,485
9,489
9,556
9,089
8,550
7,944
7,390
6,917
6,585
17B Coach C18 R
39,506
38,247
37,040
35,834
34,679
33,578
32,528
31,479
30,482
29,485
18B Coach C18 MP
39,506
38,247
37,040
35,834
34,679
33,578
32,528
31,479
30,482
29,485
19C Mix C18 MP
22,339
22,244
22,252
22,410
21,314
20,051
18,628
17,329
16,220
15,443
20T Dump C18 U
10,000
9,958
9,961
10,032
9,541
8,976
8,339
7,758
7,261
6,913
2IT Dump C18 MP
10,000
9,958
9,961
10,032
9,541
8,976
8,339
7,758
7,261
6,913
22T Dump C16-7 MP
14,044
13,984
13,989
14,089
13,399
12,606
11,711
10,895
10,197
9,709
23T Dump C18 U
10,000
9,958
9,961
10,032
9,541
8,976
8,339
7,758
7,261
6,913
24T Dump C16-7 U
14,044
13,984
13,989
14,089
13,399
12,606
11,711
10,895
10,197
9,709
25T Fire C18 MP
10,000
9,958
9,961
10,032
9,541
8,976
8,339
7,758
7,261
6,913
26T Fire C18 U
10,000
9,958
9,961
10,032
9,541
8,976
8,339
7,758
7,261
6,913
27T Flat C16-7 MP
9,961
9,918
9,922
9,993
9,504
8,941
8,306
7,727
7,233
6,886
28T Flat C16-7 R
9,961
9,918
9,922
9,993
9,504
8,941
8,306
7,727
7,233
6,886
29T Flat C16-7 U
9,961
9,918
9,922
9,993
9,504
8,941
8,306
7,727
7,233
6,886
30Tractor DC C18
24,250
24,250
24,250
24,250
22,630
21,010
19,389
17,769
16,149
14,528
31Tractor DC C17
24,256
24,256
24,256
24,256
22,635
21,014
19,394
17,773
16,152
14,532
32Tractor SC C18
105,000
105,000
105,000
105,000
99,463
93,926
88,389
82,853
77,316
71,779
33Tractor DC C18
53,925
53,925
53,925
53,925
50,322
46,719
43,116
39,513
35,910
32,307
34T Ref C18 MP
12,995
12,995
12,995
12,995
12,414
11,834
11,253
10,672
10,091
9,510
35T Ref C16-7 MP
23,400
23,400
23,400
23,400
22,354
21,308
20,262
19,216
18,170
17,124
36T Ref C18 U
12,995
12,995
12,995
12,995
12,414
11,834
11,253
10,672
10,091
9,510
37T Ref C16-7 U
23,400
23,400
23,400
23,400
22,354
21,308
20,262
19,216
18,170
17,124
38RV C18 R
2,680
2,673
2,676
2,693
2,678
2,649
2,595
2,557
2,541
2,499
39RV C16-7 R
2,680
2,673
2,676
2,693
2,678
2,649
2,595
2,557
2,541
2,499
824
-------
Vehicle ID
Vehicle Age (years)
0
1
2
3
4
5
6
7
8
9
40RV C14-5 R
2,680
2,673
2,676
2,693
2,678
2,649
2,595
2,557
2,541
2,499
41Tractor DC C17
53,914
53,914
53,914
53,914
50,312
46,710
43,107
39,505
35,902
32,300
42RV C18 MP
2,680
2,673
2,676
2,693
2,678
2,649
2,595
2,557
2,541
2,499
43RV C16-7 MP
2,680
2,673
2,676
2,693
2,678
2,649
2,595
2,557
2,541
2,499
44RV C14-5 MP
2,680
2,673
2,676
2,693
2,678
2,649
2,595
2,557
2,541
2,499
45Tractor DC C18
53,914
53,914
53,914
53,914
50,312
46,710
43,107
39,505
35,902
32,300
46B School C18 MP
12,000
11,617
11,251
10,884
10,534
10,199
9,880
9,562
9,259
8,956
47B School C16-7 MP
12,777
12,369
11,979
11,589
11,216
10,859
10,520
10,181
9,858
9,536
48B School C14-5 MP
12,000
11,617
11,251
10,884
10,534
10,199
9,880
9,562
9,259
8,956
49B School C12b-3 MP
12,000
11,617
11,251
10,884
10,534
10,199
9,880
9,562
9,259
8,956
5OB School C18 U
12,000
11,617
11,251
10,884
10,534
10,199
9,880
9,562
9,259
8,956
5 IB School C16-7 U
12,777
12,369
11,979
11,589
11,216
10,859
10,520
10,181
9,858
9,536
52B School C14-5 U
12,000
11,617
11,251
10,884
10,534
10,199
9,880
9,562
9,259
8,956
53B School C12b-3 U
12,000
11,617
11,251
10,884
10,534
10,199
9,880
9,562
9,259
8,956
54Tractor SC C18
105,000
105,000
105,000
105,000
99,463
93,926
88,389
82,853
77,316
71,779
55B Shuttle C12b-3 MP
29,429
28,491
27,592
26,693
25,833
25,013
24,231
23,449
22,707
21,964
56B Shuttle C14-5 U
29,429
28,491
27,592
26,693
25,833
25,013
24,231
23,449
22,707
21,964
57B Shuttle C12b-3 U
29,429
28,491
27,592
26,693
25,833
25,013
24,231
23,449
22,707
21,964
58B Shuttle C16-7 MP
29,429
28,491
27,592
26,693
25,833
25,013
24,231
23,449
22,707
21,964
59B Shuttle C16-7 U
29,429
28,491
27,592
26,693
25,833
25,013
24,231
23,449
22,707
21,964
60S Plow C16-7 MP
9,963
9,921
9,924
9,995
9,506
8,943
8,308
7,729
7,234
6,888
61S Plow C18 MP
11,060
11,013
11,017
11,096
10,553
9,928
9,223
8,580
8,031
7,646
62S Plow C16-7 U
9,963
9,921
9,924
9,995
9,506
8,943
8,308
7,729
7,234
6,888
63 S Plow C18 U
11,060
11,013
11,017
11,096
10,553
9,928
9,223
8,580
8,031
7,646
64V Step C16-7 MP
15,224
15,159
15,165
15,273
14,525
13,665
12,695
11,810
11,054
10,525
65V Step C14-5 MP
9,526
9,485
9,489
9,556
9,089
8,550
7,944
7,390
6,917
6,585
66V Step C12b-3 MP
14,836
14,773
14,778
14,883
14,035
13,076
12,012
11,029
10,164
9,499
67V Step C16-7 U
15,224
15,159
15,165
15,273
14,525
13,665
12,695
11,810
11,054
10,525
68V Step C14-5 U
9,526
9,485
9,489
9,556
9,089
8,550
7,944
7,390
6,917
6,585
69V Step C12b-3 U
14,836
14,773
14,778
14,883
14,035
13,076
12,012
11,029
10,164
9,499
70S Sweep C16-7 U
12,600
12,547
12,551
12,640
12,022
11,310
10,507
9,775
9,149
8,711
7IT Tanker C18 R
12,900
12,845
12,850
12,941
12,308
11,579
10,757
10,007
9,367
8,918
72T Tanker C18 MP
12,900
12,845
12,850
12,941
12,308
11,579
10,757
10,007
9,367
8,918
73T Tanker C18 U
12,900
12,845
12,850
12,941
12,308
11,579
10,757
10,007
9,367
8,918
74T Tow C18 R
16,100
16,032
16,038
16,152
15,361
14,451
13,426
12,490
11,690
11,131
75T Tow C16-7 R
14,020
13,960
13,966
14,065
13,377
12,584
11,691
10,876
10,180
9,692
76T Tow C18 U
16,100
16,032
16,038
16,152
15,361
14,451
13,426
12,490
11,690
11,131
77T Tow C16-7 U
14,020
13,960
13,966
14,065
13,377
12,584
11,691
10,876
10,180
9,692
78Tractor SC C18
75,000
75,000
75,000
75,000
71,045
67,090
63,135
59,181
55,226
51,271
79Tractor SC C18
105,000
105,000
105,000
105,000
99,463
93,926
88,389
82,853
77,316
71,779
80Tractor DC C18
26,500
26,388
26,397
26,585
25,284
23,786
22,098
20,558
19,242
18,320
81Tractor DC C17
53,914
53,914
53,914
53,914
50,312
46,710
43,107
39,505
35,902
32,300
82Tractor DC C18
53,914
53,914
53,914
53,914
50,312
46,710
43,107
39,505
35,902
32,300
83Tractor DC C17
30,080
30,080
30,080
30,080
28,070
26,060
24,050
22,041
20,031
18,021
84Tractor DC C18
30,000
30,000
30,000
30,000
27,996
25,991
23,987
21,982
19,978
17,973
85B Transit C18 MP
33,928
32,847
31,810
30,774
29,783
28,837
27,935
27,034
26,178
25,322
86B Transit C16-7 MP
20,022
19,384
18,773
18,161
17,576
17,018
16,486
15,954
15,449
14,944
87B Transit C18 U
33,928
32,847
31,810
30,774
29,783
28,837
27,935
27,034
26,178
25,322
88B Transit C16-7 U
20,022
19,384
18,773
18,161
17,576
17,018
16,486
15,954
15,449
14,944
89T Utility C18 MP
6,673
6,644
6,647
6,694
6,366
5,989
5,564
5,176
4,845
4,613
90T Utility C18 R
6,673
6,644
6,647
6,694
6,366
5,989
5,564
5,176
4,845
4,613
825
-------
Vehicle ID
Vehicle Age (years)
0
1
2
3
4
5
6
7
8
9
9IT Utility C16-7 MP
12,300
12,248
12,252
12,340
11,736
11,040
10,257
9,542
8,931
8,503
92T Utility C16-7 R
12,300
12,248
12,252
12,340
11,736
11,040
10,257
9,542
8,931
8,503
93T Utility C14-5 MP
12,300
12,248
12,252
12,340
11,736
11,040
10,257
9,542
8,931
8,503
94T Utility C12b-3 MP
5,629
5,605
5,607
5,647
5,370
5,052
4,694
4,366
4,087
3,891
95T Utility C14-5 R
12,300
12,248
12,252
12,340
11,636
10,841
9,959
9,144
8,427
7,875
96T Utility C12b-3 R
12,300
12,248
12,252
12,340
11,636
10,841
9,959
9,144
8,427
7,875
97T Utility C18 U
6,673
6,644
6,647
6,694
6,366
5,989
5,564
5,176
4,845
4,613
98T Utility C16-7 U
12,300
12,248
12,252
12,340
11,736
11,040
10,257
9,542
8,931
8,503
99T Utility C14-5 U
12,300
12,248
12,252
12,340
11,736
11,040
10,257
9,542
8,931
8,503
100T Utility C12b-3 U
5,629
5,605
5,607
5,647
5,370
5,052
4,694
4,366
4,087
3,891
lOlTractor DC C18
15,095
15,096
15,095
15,095
14,087
13,078
12,070
11,061
10,052
9,044
826
-------
Appendix B - Additional MOVES Adoption Rates
This Appendix B contains tables showing HD BEV and FCEV adoption rates in the reference
case, final standards case (reflecting the technology package for the modeled compliance
pathway), and alternative case (reflecting a different technology package). The ZEV adoption
rates shown elsewhere in this RIA chapter and in preamble Sections V and IX are the sum of the
BEV and FCEV adoption rates. We calculated the BEV and FCEV adoption rates based on our
technology assessment using HD TRUCS as described in RIA Chapter 2 and preamble Section
II.
All ZEVs are modeled as BEVs except for some day cab tractors (MOVES source type 61),
sleeper cab tractors (MOVES source type 62), and coach buses (MOVES source type 41 and
regulatory class 47) which have a mix of BEV and FCEV adoption. All ZEVs are modeled as
BEVs for MY 2029 and earlier. For the tractors in the reference case, we calculated ZEV
adoption rates as described in Chapter 4.3.1 and apportioned them to BEVs and FCEVs in MY
2030 and beyond using the mix of BEV and FCEV technology by MOVES source type and
regulatory class from HD TRUCS for MY 2032 as shown in RIA Chapter 2. These are shown in
Table B-l below. For coach buses, any increase to the ZEV adoption rate above the MY 2029
level is apportioned to FCEVs, with the MY 2029 BEV adoption rate held constant in MY 2029
and beyond. We note that ZEV adoption rates for coach buses are constant across the reference
and control cases.
Table B-l Proportion of tractor ZEVs that are BEVs and FCEVs for MY 2030 and beyond
Source type
Regulatory class
Proportion of ZEVs that are
BEVs for MY 2030 and beyond
Proportion of ZEVs that are
FCEVs for MY 2030 and
beyond
61
46
0.748
0.252
61
47
0.962
0.038
62
46,a 47
0.632
0.368
a MOVES regulatory class 46 corresponds to Class 6-7. Sleeper cab tractors (source type 62) in this
regulatory class are not modeled in HD TRUCS, but they do exist in MOVES, so we based all ZEV adoption
rates for regulatory class 46 sleeper cab tractors on regulatory class 47 sleeper cab tractors.
The rest of the appendix presents the adoption tables of BEVs and FCEVs used in our
modeling for the reference case, final standards, and alternative by MOVES source type,
regulatory class, and model year. Appendix B.l shows adoption rates in ACT states, Appendix
B.2 shows the adoption rates in non-ACT states, Appendix B.3 shows national adoption rates,
which are based on a sales-weighting of state-specific adoption rates, and Appendix B.4 shows
the results of the HD ZEV adoption sensitivity analysis.
827
-------
B.l ZEV Sales Percentages in ACT States
Table B-2 ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
25.6%
25.6%
25.6%
0%
0%
0%
2028
38.5%
38.5%
38.5%
0%
0%
0%
2029
51.2%
51.2%
51.2%
0%
0%
0%
2030
63.7%
63.7%
63.7%
0%
0%
0%
2031
69.8%
69.8%
69.8%
0%
0%
0%
2032
76.1%
76.1%
76.1%
0%
0%
0%
2033
82.4%
82.4%
82.4%
0%
0%
0%
2034
88.6%
88.6%
88.6%
0%
0%
0%
2035
94.8%
94.8%
94.8%
0%
0%
0%
2036
94.7%
94.7%
94.7%
0%
0%
0%
2037
94.6%
94.6%
94.6%
0%
0%
0%
2038
94.4%
94.4%
94.4%
0%
0%
0%
2039
94.2%
94.2%
94.2%
0%
0%
0%
2040
94.1%
94.1%
94.1%
0%
0%
0%
2041
94.0%
94.0%
94.0%
0%
0%
0%
2042
93.9%
93.9%
93.9%
0%
0%
0%
2043
93.8%
93.8%
93.8%
0%
0%
0%
2044
93.7%
93.7%
93.7%
0%
0%
0%
2045
93.4%
93.4%
93.4%
0%
0%
0%
2046
93.1%
93.1%
93.1%
0%
0%
0%
2047
93.0%
93.0%
93.0%
0%
0%
0%
2048
92.9%
92.9%
92.9%
0%
0%
0%
2049
92.7%
92.7%
92.7%
0%
0%
0%
2050
92.6%
92.6%
92.6%
0%
0%
0%
2051
92.4%
92.4%
92.4%
0%
0%
0%
2052
92.3%
92.3%
92.3%
0%
0%
0%
2053
92.2%
92.2%
92.2%
0%
0%
0%
2054
92.1%
92.1%
92.1%
0%
0%
0%
2055
91.9%
91.9%
91.9%
0%
0%
0%
828
-------
Table B-3 ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
19.2%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
52.4%
52.4%
0%
0%
0%
2032
57.1%
57.1%
57.1%
0%
0%
0%
2033
61.8%
61.8%
61.8%
0%
0%
0%
2034
66.5%
66.5%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
69.8%
69.8%
0%
0%
0%
2047
69.7%
69.7%
69.7%
0%
0%
0%
2048
69.7%
69.7%
69.7%
0%
0%
0%
2049
69.6%
69.6%
69.6%
0%
0%
0%
2050
69.5%
69.5%
69.5%
0%
0%
0%
2051
69.3%
69.3%
69.3%
0%
0%
0%
2052
69.2%
69.2%
69.2%
0%
0%
0%
2053
69.1%
69.1%
69.1%
0%
0%
0%
2054
69.0%
69.0%
69.0%
0%
0%
0%
2055
69.0%
69.0%
69.0%
0%
0%
0%
829
-------
Table B-4 ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0.0%
0.0%
0.0%
2028
19.2%
19.2%
19.2%
0.0%
0.0%
0.0%
2029
25.6%
25.6%
25.6%
0.0%
0.0%
0.0%
2030
25.6%
25.6%
25.6%
6.3%
6.3%
6.3%
2031
25.6%
25.6%
25.6%
9.3%
9.3%
9.3%
2032
25.6%
25.6%
25.6%
12.5%
12.5%
12.5%
2033
25.6%
25.6%
25.6%
15.6%
15.6%
15.6%
2034
25.6%
25.6%
25.6%
18.7%
18.7%
18.7%
2035
25.6%
25.6%
25.6%
21.8%
21.8%
21.8%
2036
25.6%
25.6%
25.6%
21.8%
21.8%
21.8%
2037
25.6%
25.6%
25.6%
21.7%
21.7%
21.7%
2038
25.6%
25.6%
25.6%
21.6%
21.6%
21.6%
2039
25.6%
25.6%
25.6%
21.5%
21.5%
21.5%
2040
25.6%
25.6%
25.6%
21.5%
21.5%
21.5%
2041
25.6%
25.6%
25.6%
21.4%
21.4%
21.4%
2042
25.6%
25.6%
25.6%
21.4%
21.4%
21.4%
2043
25.6%
25.6%
25.6%
21.3%
21.3%
21.3%
2044
25.6%
25.6%
25.6%
21.2%
21.2%
21.2%
2045
25.6%
25.6%
25.6%
21.1%
21.1%
21.1%
2046
25.6%
25.6%
25.6%
21.0%
21.0%
21.0%
2047
25.6%
25.6%
25.6%
20.9%
20.9%
20.9%
2048
25.6%
25.6%
25.6%
20.9%
20.9%
20.9%
2049
25.6%
25.6%
25.6%
20.8%
20.8%
20.8%
2050
25.6%
25.6%
25.6%
20.7%
20.7%
20.7%
2051
25.6%
25.6%
25.6%
20.6%
20.6%
20.6%
2052
25.6%
25.6%
25.6%
20.6%
20.6%
20.6%
2053
25.6%
25.6%
25.6%
20.5%
20.5%
20.5%
2054
25.6%
25.6%
25.6%
20.4%
20.4%
20.4%
2055
25.6%
25.6%
25.6%
20.4%
20.4%
20.4%
830
-------
Table B-5 ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
25.6%
25.6%
25.6%
0%
0%
0%
2028
38.5%
38.5%
38.5%
0%
0%
0%
2029
51.2%
51.2%
51.2%
0%
0%
0%
2030
63.7%
63.7%
63.7%
0%
0%
0%
2031
69.8%
69.8%
69.8%
0%
0%
0%
2032
76.1%
76.1%
76.1%
0%
0%
0%
2033
82.4%
82.4%
82.4%
0%
0%
0%
2034
88.6%
88.6%
88.6%
0%
0%
0%
2035
94.8%
94.8%
94.8%
0%
0%
0%
2036
94.7%
94.7%
94.7%
0%
0%
0%
2037
94.6%
94.6%
94.6%
0%
0%
0%
2038
94.4%
94.4%
94.4%
0%
0%
0%
2039
94.2%
94.2%
94.2%
0%
0%
0%
2040
94.1%
94.1%
94.1%
0%
0%
0%
2041
94.0%
94.0%
94.0%
0%
0%
0%
2042
93.9%
93.9%
93.9%
0%
0%
0%
2043
93.8%
93.8%
93.8%
0%
0%
0%
2044
93.7%
93.7%
93.7%
0%
0%
0%
2045
93.4%
93.4%
93.4%
0%
0%
0%
2046
93.1%
93.1%
93.1%
0%
0%
0%
2047
93.0%
93.0%
93.0%
0%
0%
0%
2048
92.9%
92.9%
92.9%
0%
0%
0%
2049
92.7%
92.7%
92.7%
0%
0%
0%
2050
92.6%
92.6%
92.6%
0%
0%
0%
2051
92.4%
92.4%
92.4%
0%
0%
0%
2052
92.3%
92.3%
92.3%
0%
0%
0%
2053
92.2%
92.2%
92.2%
0%
0%
0%
2054
92.1%
92.1%
92.1%
0%
0%
0%
2055
91.9%
91.9%
91.9%
0%
0%
0%
831
-------
Table B-6 ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
19.2%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
52.4%
52.4%
0%
0%
0%
2032
57.1%
57.1%
57.1%
0%
0%
0%
2033
61.8%
61.8%
61.8%
0%
0%
0%
2034
66.5%
66.5%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
69.8%
69.8%
0%
0%
0%
2047
69.7%
69.7%
69.7%
0%
0%
0%
2048
69.7%
69.7%
69.7%
0%
0%
0%
2049
69.6%
69.6%
69.6%
0%
0%
0%
2050
69.5%
69.5%
69.5%
0%
0%
0%
2051
69.3%
69.3%
69.3%
0%
0%
0%
2052
69.2%
69.2%
69.2%
0%
0%
0%
2053
69.1%
69.1%
69.1%
0%
0%
0%
2054
69.0%
69.0%
69.0%
0%
0%
0%
2055
69.0%
69.0%
69.0%
0%
0%
0%
832
-------
Table B-7 ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0%
0%
0%
2028
19.2%
19.2%
19.2%
0%
0%
0%
2029
25.6%
25.6%
25.6%
0%
0%
0%
2030
31.8%
31.8%
31.8%
0%
0%
0%
2031
34.9%
34.9%
34.9%
0%
0%
0%
2032
38.0%
39.0%
38.0%
0%
0%
0%
2033
41.2%
41.2%
41.2%
0%
0%
0%
2034
44.3%
44.3%
44.3%
0%
0%
0%
2035
47.4%
47.4%
47.4%
0%
0%
0%
2036
47.3%
47.3%
47.3%
0%
0%
0%
2037
47.3%
47.3%
47.3%
0%
0%
0%
2038
47.2%
47.2%
47.2%
0%
0%
0%
2039
47.1%
47.1%
47.1%
0%
0%
0%
2040
47.0%
47.0%
47.0%
0%
0%
0%
2041
47.0%
47.0%
47.0%
0%
0%
0%
2042
46.9%
46.9%
46.9%
0%
0%
0%
2043
46.9%
46.9%
46.9%
0%
0%
0%
2044
46.8%
46.8%
46.8%
0%
0%
0%
2045
46.7%
46.7%
46.7%
0%
0%
0%
2046
46.6%
46.6%
46.6%
0%
0%
0%
2047
46.5%
46.5%
46.5%
0%
0%
0%
2048
46.4%
46.4%
46.4%
0%
0%
0%
2049
46.4%
46.4%
46.4%
0%
0%
0%
2050
46.3%
46.3%
46.3%
0%
0%
0%
2051
46.2%
46.2%
46.2%
0%
0%
0%
2052
46.1%
46.1%
46.1%
0%
0%
0%
2053
46.1%
46.1%
46.1%
0%
0%
0%
2054
46.0%
46.0%
46.0%
0%
0%
0%
2055
46.0%
46.0%
46.0%
0%
0%
0%
833
-------
Table B-8 ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
25.6%
25.6%
25.6%
0%
0%
0%
2028
38.5%
38.5%
38.5%
0%
0%
0%
2029
51.2%
51.2%
51.2%
0%
0%
0%
2030
63.7%
63.7%
63.7%
0%
0%
0%
2031
69.8%
69.8%
69.8%
0%
0%
0%
2032
76.1%
76.1%
76.1%
0%
0%
0%
2033
82.4%
82.4%
82.4%
0%
0%
0%
2034
88.6%
88.6%
88.6%
0%
0%
0%
2035
94.8%
94.8%
94.8%
0%
0%
0%
2036
94.7%
94.7%
94.7%
0%
0%
0%
2037
94.6%
94.6%
94.6%
0%
0%
0%
2038
94.4%
94.4%
94.4%
0%
0%
0%
2039
94.2%
94.2%
94.2%
0%
0%
0%
2040
94.1%
94.1%
94.1%
0%
0%
0%
2041
94.0%
94.0%
94.0%
0%
0%
0%
2042
93.9%
93.9%
93.9%
0%
0%
0%
2043
93.8%
93.8%
93.8%
0%
0%
0%
2044
93.7%
93.7%
93.7%
0%
0%
0%
2045
93.4%
93.4%
93.4%
0%
0%
0%
2046
93.1%
93.1%
93.1%
0%
0%
0%
2047
93.0%
93.0%
93.0%
0%
0%
0%
2048
92.9%
92.9%
92.9%
0%
0%
0%
2049
92.7%
92.7%
92.7%
0%
0%
0%
2050
92.6%
92.6%
92.6%
0%
0%
0%
2051
92.4%
92.4%
92.4%
0%
0%
0%
2052
92.3%
92.3%
92.3%
0%
0%
0%
2053
92.2%
92.2%
92.2%
0%
0%
0%
2054
92.1%
92.1%
92.1%
0%
0%
0%
2055
91.9%
91.9%
91.9%
0%
0%
0%
834
-------
Table B-9 ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
20.0%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
53.3%
52.4%
0%
0%
0%
2032
57.1%
70.0%
57.1%
0%
0%
0%
2033
61.8%
70.0%
61.8%
0%
0%
0%
2034
66.5%
70.0%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
70.0%
69.8%
0%
0%
0%
2047
69.7%
70.0%
69.7%
0%
0%
0%
2048
69.7%
70.0%
69.7%
0%
0%
0%
2049
69.6%
70.0%
69.6%
0%
0%
0%
2050
69.5%
70.0%
69.5%
0%
0%
0%
2051
69.3%
70.0%
69.3%
0%
0%
0%
2052
69.2%
70.0%
69.2%
0%
0%
0%
2053
69.1%
70.0%
69.1%
0%
0%
0%
2054
69.0%
70.0%
69.0%
0%
0%
0%
2055
69.0%
70.0%
69.0%
0%
0%
0%
835
-------
Table B-10 ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0%
0%
0%
2028
19.2%
19.2%
19.2%
0%
0%
0%
2029
25.6%
25.6%
25.6%
0%
0%
0%
2030
31.8%
31.8%
31.8%
0%
0%
0%
2031
34.9%
34.9%
34.9%
0%
0%
0%
2032
38.0%
39.0%
38.0%
0%
0%
0%
2033
41.2%
41.2%
41.2%
0%
0%
0%
2034
44.3%
44.3%
44.3%
0%
0%
0%
2035
47.4%
47.4%
47.4%
0%
0%
0%
2036
47.3%
47.3%
47.3%
0%
0%
0%
2037
47.3%
47.3%
47.3%
0%
0%
0%
2038
47.2%
47.2%
47.2%
0%
0%
0%
2039
47.1%
47.1%
47.1%
0%
0%
0%
2040
47.0%
47.0%
47.0%
0%
0%
0%
2041
47.0%
47.0%
47.0%
0%
0%
0%
2042
46.9%
46.9%
46.9%
0%
0%
0%
2043
46.9%
46.9%
46.9%
0%
0%
0%
2044
46.8%
46.8%
46.8%
0%
0%
0%
2045
46.7%
46.7%
46.7%
0%
0%
0%
2046
46.6%
46.6%
46.6%
0%
0%
0%
2047
46.5%
46.5%
46.5%
0%
0%
0%
2048
46.4%
46.4%
46.4%
0%
0%
0%
2049
46.4%
46.4%
46.4%
0%
0%
0%
2050
46.3%
46.3%
46.3%
0%
0%
0%
2051
46.2%
46.2%
46.2%
0%
0%
0%
2052
46.1%
46.1%
46.1%
0%
0%
0%
2053
46.1%
46.1%
46.1%
0%
0%
0%
2054
46.0%
46.0%
46.0%
0%
0%
0%
2055
46.0%
46.0%
46.0%
0%
0%
0%
836
-------
Table B-ll ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) in ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
20.0%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
52.4%
52.4%
0%
0%
0%
2032
57.1%
57.1%
57.1%
0%
0%
0%
2033
61.8%
61.8%
61.8%
0%
0%
0%
2034
66.5%
66.5%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
69.8%
69.8%
0%
0%
0%
2047
69.7%
69.7%
69.7%
0%
0%
0%
2048
69.7%
69.7%
69.7%
0%
0%
0%
2049
69.6%
69.6%
69.6%
0%
0%
0%
2050
69.5%
69.5%
69.5%
0%
0%
0%
2051
69.3%
69.3%
69.3%
0%
0%
0%
2052
69.2%
69.2%
69.2%
0%
0%
0%
2053
69.1%
69.1%
69.1%
0%
0%
0%
2054
69.0%
69.0%
69.0%
0%
0%
0%
2055
69.0%
69.0%
69.0%
0%
0%
0%
837
-------
Table B-12 ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0%
0%
0%
2028
19.2%
19.2%
19.2%
0%
0%
0%
2029
25.6%
25.6%
25.6%
0%
0%
0%
2030
31.8%
31.8%
31.8%
0%
0%
0%
2031
34.9%
34.9%
34.9%
0%
0%
0%
2032
38.0%
39.0%
38.0%
0%
0%
0%
2033
41.2%
41.2%
41.2%
0%
0%
0%
2034
44.3%
44.3%
44.3%
0%
0%
0%
2035
47.4%
47.4%
47.4%
0%
0%
0%
2036
47.3%
47.3%
47.3%
0%
0%
0%
2037
47.3%
47.3%
47.3%
0%
0%
0%
2038
47.2%
47.2%
47.2%
0%
0%
0%
2039
47.1%
47.1%
47.1%
0%
0%
0%
2040
47.0%
47.0%
47.0%
0%
0%
0%
2041
47.0%
47.0%
47.0%
0%
0%
0%
2042
46.9%
46.9%
46.9%
0%
0%
0%
2043
46.9%
46.9%
46.9%
0%
0%
0%
2044
46.8%
46.8%
46.8%
0%
0%
0%
2045
46.7%
46.7%
46.7%
0%
0%
0%
2046
46.6%
46.6%
46.6%
0%
0%
0%
2047
46.5%
46.5%
46.5%
0%
0%
0%
2048
46.4%
46.4%
46.4%
0%
0%
0%
2049
46.4%
46.4%
46.4%
0%
0%
0%
2050
46.3%
46.3%
46.3%
0%
0%
0%
2051
46.2%
46.2%
46.2%
0%
0%
0%
2052
46.1%
46.1%
46.1%
0%
0%
0%
2053
46.1%
46.1%
46.1%
0%
0%
0%
2054
46.0%
46.0%
46.0%
0%
0%
0%
2055
46.0%
46.0%
46.0%
0%
0%
0%
838
-------
Table B-13 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks (sourceTypelD
52) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
25.6%
25.6%
25.6%
0%
0%
0%
2028
38.5%
38.5%
38.5%
0%
0%
0%
2029
51.2%
51.2%
51.2%
0%
0%
0%
2030
63.7%
63.7%
63.7%
0%
0%
0%
2031
69.8%
69.8%
69.8%
0%
0%
0%
2032
76.1%
76.1%
76.1%
0%
0%
0%
2033
82.4%
82.4%
82.4%
0%
0%
0%
2034
88.6%
88.6%
88.6%
0%
0%
0%
2035
94.8%
94.8%
94.8%
0%
0%
0%
2036
94.7%
94.7%
94.7%
0%
0%
0%
2037
94.6%
94.6%
94.6%
0%
0%
0%
2038
94.4%
94.4%
94.4%
0%
0%
0%
2039
94.2%
94.2%
94.2%
0%
0%
0%
2040
94.1%
94.1%
94.1%
0%
0%
0%
2041
94.0%
94.0%
94.0%
0%
0%
0%
2042
93.9%
93.9%
93.9%
0%
0%
0%
2043
93.8%
93.8%
93.8%
0%
0%
0%
2044
93.7%
93.7%
93.7%
0%
0%
0%
2045
93.4%
93.4%
93.4%
0%
0%
0%
2046
93.1%
93.1%
93.1%
0%
0%
0%
2047
93.0%
93.0%
93.0%
0%
0%
0%
2048
92.9%
92.9%
92.9%
0%
0%
0%
2049
92.7%
92.7%
92.7%
0%
0%
0%
2050
92.6%
92.6%
92.6%
0%
0%
0%
2051
92.4%
92.4%
92.4%
0%
0%
0%
2052
92.3%
92.3%
92.3%
0%
0%
0%
2053
92.2%
92.2%
92.2%
0%
0%
0%
2054
92.1%
92.1%
92.1%
0%
0%
0%
2055
91.9%
91.9%
91.9%
0%
0%
0%
839
-------
Table B-14 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
52) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
19.2%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
52.4%
52.4%
0%
0%
0%
2032
57.1%
57.1%
57.1%
0%
0%
0%
2033
61.8%
61.8%
61.8%
0%
0%
0%
2034
66.5%
66.5%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
69.8%
69.8%
0%
0%
0%
2047
69.7%
69.7%
69.7%
0%
0%
0%
2048
69.7%
69.7%
69.7%
0%
0%
0%
2049
69.6%
69.6%
69.6%
0%
0%
0%
2050
69.5%
69.5%
69.5%
0%
0%
0%
2051
69.3%
69.3%
69.3%
0%
0%
0%
2052
69.2%
69.2%
69.2%
0%
0%
0%
2053
69.1%
69.1%
69.1%
0%
0%
0%
2054
69.0%
69.0%
69.0%
0%
0%
0%
2055
69.0%
69.0%
69.0%
0%
0%
0%
840
-------
Table B-15 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
52) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0%
0%
0%
2028
19.2%
19.2%
19.2%
0%
0%
0%
2029
25.6%
25.6%
25.6%
0%
0%
0%
2030
31.8%
31.8%
31.8%
0%
0%
0%
2031
34.9%
34.9%
34.9%
0%
0%
0%
2032
38.0%
38.0%
38.0%
0%
0%
0%
2033
41.2%
41.2%
41.2%
0%
0%
0%
2034
44.3%
44.3%
44.3%
0%
0%
0%
2035
47.4%
47.4%
47.4%
0%
0%
0%
2036
47.3%
47.3%
47.3%
0%
0%
0%
2037
47.3%
47.3%
47.3%
0%
0%
0%
2038
47.2%
47.2%
47.2%
0%
0%
0%
2039
47.1%
47.1%
47.1%
0%
0%
0%
2040
47.0%
47.0%
47.0%
0%
0%
0%
2041
47.0%
47.0%
47.0%
0%
0%
0%
2042
46.9%
46.9%
46.9%
0%
0%
0%
2043
46.9%
46.9%
46.9%
0%
0%
0%
2044
46.8%
46.8%
46.8%
0%
0%
0%
2045
46.7%
46.7%
46.7%
0%
0%
0%
2046
46.6%
46.6%
46.6%
0%
0%
0%
2047
46.5%
46.5%
46.5%
0%
0%
0%
2048
46.4%
46.4%
46.4%
0%
0%
0%
2049
46.4%
46.4%
46.4%
0%
0%
0%
2050
46.3%
46.3%
46.3%
0%
0%
0%
2051
46.2%
46.2%
46.2%
0%
0%
0%
2052
46.1%
46.1%
46.1%
0%
0%
0%
2053
46.1%
46.1%
46.1%
0%
0%
0%
2054
46.0%
46.0%
46.0%
0%
0%
0%
2055
46.0%
46.0%
46.0%
0%
0%
0%
841
-------
Table B-16 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks (sourceTypelD
53) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
25.6%
25.6%
25.6%
0%
0%
0%
2028
38.5%
38.5%
38.5%
0%
0%
0%
2029
51.2%
51.2%
51.2%
0%
0%
0%
2030
63.7%
63.7%
63.7%
0%
0%
0%
2031
69.8%
69.8%
69.8%
0%
0%
0%
2032
76.1%
76.1%
76.1%
0%
0%
0%
2033
82.4%
82.4%
82.4%
0%
0%
0%
2034
88.6%
88.6%
88.6%
0%
0%
0%
2035
94.8%
94.8%
94.8%
0%
0%
0%
2036
94.7%
94.7%
94.7%
0%
0%
0%
2037
94.6%
94.6%
94.6%
0%
0%
0%
2038
94.4%
94.4%
94.4%
0%
0%
0%
2039
94.2%
94.2%
94.2%
0%
0%
0%
2040
94.1%
94.1%
94.1%
0%
0%
0%
2041
94.0%
94.0%
94.0%
0%
0%
0%
2042
93.9%
93.9%
93.9%
0%
0%
0%
2043
93.8%
93.8%
93.8%
0%
0%
0%
2044
93.7%
93.7%
93.7%
0%
0%
0%
2045
93.4%
93.4%
93.4%
0%
0%
0%
2046
93.1%
93.1%
93.1%
0%
0%
0%
2047
93.0%
93.0%
93.0%
0%
0%
0%
2048
92.9%
92.9%
92.9%
0%
0%
0%
2049
92.7%
92.7%
92.7%
0%
0%
0%
2050
92.6%
92.6%
92.6%
0%
0%
0%
2051
92.4%
92.4%
92.4%
0%
0%
0%
2052
92.3%
92.3%
92.3%
0%
0%
0%
2053
92.2%
92.2%
92.2%
0%
0%
0%
2054
92.1%
92.1%
92.1%
0%
0%
0%
2055
91.9%
91.9%
91.9%
0%
0%
0%
842
-------
Table B-17 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
53) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
19.2%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
52.4%
52.4%
0%
0%
0%
2032
57.1%
57.1%
57.1%
0%
0%
0%
2033
61.8%
61.8%
61.8%
0%
0%
0%
2034
66.5%
66.5%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
69.8%
69.8%
0%
0%
0%
2047
69.7%
69.7%
69.7%
0%
0%
0%
2048
69.7%
69.7%
69.7%
0%
0%
0%
2049
69.6%
69.6%
69.6%
0%
0%
0%
2050
69.5%
69.5%
69.5%
0%
0%
0%
2051
69.3%
69.3%
69.3%
0%
0%
0%
2052
69.2%
69.2%
69.2%
0%
0%
0%
2053
69.1%
69.1%
69.1%
0%
0%
0%
2054
69.0%
69.0%
69.0%
0%
0%
0%
2055
69.0%
69.0%
69.0%
0%
0%
0%
843
-------
Table B-18 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 53)
in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0%
0%
0%
2028
19.2%
19.2%
19.2%
0%
0%
0%
2029
25.6%
25.6%
25.6%
0%
0%
0%
2030
31.8%
31.8%
31.8%
0%
0%
0%
2031
34.9%
34.9%
34.9%
0%
0%
0%
2032
38.0%
39.0%
38.0%
0%
0%
0%
2033
41.2%
41.2%
41.2%
0%
0%
0%
2034
44.3%
44.3%
44.3%
0%
0%
0%
2035
47.4%
47.4%
47.4%
0%
0%
0%
2036
47.3%
47.3%
47.3%
0%
0%
0%
2037
47.3%
47.3%
47.3%
0%
0%
0%
2038
47.2%
47.2%
47.2%
0%
0%
0%
2039
47.1%
47.1%
47.1%
0%
0%
0%
2040
47.0%
47.0%
47.0%
0%
0%
0%
2041
47.0%
47.0%
47.0%
0%
0%
0%
2042
46.9%
46.9%
46.9%
0%
0%
0%
2043
46.9%
46.9%
46.9%
0%
0%
0%
2044
46.8%
46.8%
46.8%
0%
0%
0%
2045
46.7%
46.7%
46.7%
0%
0%
0%
2046
46.6%
46.6%
46.6%
0%
0%
0%
2047
46.5%
46.5%
46.5%
0%
0%
0%
2048
46.4%
46.4%
46.4%
0%
0%
0%
2049
46.4%
46.4%
46.4%
0%
0%
0%
2050
46.3%
46.3%
46.3%
0%
0%
0%
2051
46.2%
46.2%
46.2%
0%
0%
0%
2052
46.1%
46.1%
46.1%
0%
0%
0%
2053
46.1%
46.1%
46.1%
0%
0%
0%
2054
46.0%
46.0%
46.0%
0%
0%
0%
2055
46.0%
46.0%
46.0%
0%
0%
0%
844
-------
Table B-19 ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) in ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
25.6%
25.6%
25.6%
0%
0%
0%
2028
38.5%
38.5%
38.5%
0%
0%
0%
2029
51.2%
51.2%
51.2%
0%
0%
0%
2030
63.7%
63.7%
63.7%
0%
0%
0%
2031
69.8%
69.8%
69.8%
0%
0%
0%
2032
76.1%
76.1%
76.1%
0%
0%
0%
2033
82.4%
82.4%
82.4%
0%
0%
0%
2034
88.6%
88.6%
88.6%
0%
0%
0%
2035
94.8%
94.8%
94.8%
0%
0%
0%
2036
94.7%
94.7%
94.7%
0%
0%
0%
2037
94.6%
94.6%
94.6%
0%
0%
0%
2038
94.4%
94.4%
94.4%
0%
0%
0%
2039
94.2%
94.2%
94.2%
0%
0%
0%
2040
94.1%
94.1%
94.1%
0%
0%
0%
2041
94.0%
94.0%
94.0%
0%
0%
0%
2042
93.9%
93.9%
93.9%
0%
0%
0%
2043
93.8%
93.8%
93.8%
0%
0%
0%
2044
93.7%
93.7%
93.7%
0%
0%
0%
2045
93.4%
93.4%
93.4%
0%
0%
0%
2046
93.1%
93.1%
93.1%
0%
0%
0%
2047
93.0%
93.0%
93.0%
0%
0%
0%
2048
92.9%
92.9%
92.9%
0%
0%
0%
2049
92.7%
92.7%
92.7%
0%
0%
0%
2050
92.6%
92.6%
92.6%
0%
0%
0%
2051
92.4%
92.4%
92.4%
0%
0%
0%
2052
92.3%
92.3%
92.3%
0%
0%
0%
2053
92.2%
92.2%
92.2%
0%
0%
0%
2054
92.1%
92.1%
92.1%
0%
0%
0%
2055
91.9%
91.9%
91.9%
0%
0%
0%
845
-------
Table B-20 ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) in ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
19.2%
19.2%
19.2%
0%
0%
0%
2028
28.9%
28.9%
28.9%
0%
0%
0%
2029
38.4%
38.4%
38.4%
0%
0%
0%
2030
47.8%
47.8%
47.8%
0%
0%
0%
2031
52.4%
52.4%
52.4%
0%
0%
0%
2032
57.1%
57.1%
57.1%
0%
0%
0%
2033
61.8%
61.8%
61.8%
0%
0%
0%
2034
66.5%
66.5%
66.5%
0%
0%
0%
2035
71.1%
71.1%
71.1%
0%
0%
0%
2036
71.0%
71.0%
71.0%
0%
0%
0%
2037
70.9%
70.9%
70.9%
0%
0%
0%
2038
70.8%
70.8%
70.8%
0%
0%
0%
2039
70.7%
70.7%
70.7%
0%
0%
0%
2040
70.6%
70.6%
70.6%
0%
0%
0%
2041
70.5%
70.5%
70.5%
0%
0%
0%
2042
70.4%
70.4%
70.4%
0%
0%
0%
2043
70.4%
70.4%
70.4%
0%
0%
0%
2044
70.2%
70.2%
70.2%
0%
0%
0%
2045
70.0%
70.0%
70.0%
0%
0%
0%
2046
69.8%
69.8%
69.8%
0%
0%
0%
2047
69.7%
69.7%
69.7%
0%
0%
0%
2048
69.7%
69.7%
69.7%
0%
0%
0%
2049
69.6%
69.6%
69.6%
0%
0%
0%
2050
69.5%
69.5%
69.5%
0%
0%
0%
2051
69.3%
69.3%
69.3%
0%
0%
0%
2052
69.2%
69.2%
69.2%
0%
0%
0%
2053
69.1%
69.1%
69.1%
0%
0%
0%
2054
69.0%
69.0%
69.0%
0%
0%
0%
2055
69.0%
69.0%
69.0%
0%
0%
0%
846
-------
Table B-21 ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
12.8%
12.8%
12.8%
0%
0%
0%
2028
19.2%
19.2%
19.2%
0%
0%
0%
2029
25.6%
25.6%
25.6%
0%
0%
0%
2030
31.8%
31.8%
31.8%
0%
0%
0%
2031
34.9%
34.9%
34.9%
0%
0%
0%
2032
38.0%
38.0%
38.0%
0%
0%
0%
2033
41.2%
41.2%
41.2%
0%
0%
0%
2034
44.3%
44.3%
44.3%
0%
0%
0%
2035
47.4%
47.4%
47.4%
0%
0%
0%
2036
47.3%
47.3%
47.3%
0%
0%
0%
2037
47.3%
47.3%
47.3%
0%
0%
0%
2038
47.2%
47.2%
47.2%
0%
0%
0%
2039
47.1%
47.1%
47.1%
0%
0%
0%
2040
47.0%
47.0%
47.0%
0%
0%
0%
2041
47.0%
47.0%
47.0%
0%
0%
0%
2042
46.9%
46.9%
46.9%
0%
0%
0%
2043
46.9%
46.9%
46.9%
0%
0%
0%
2044
46.8%
46.8%
46.8%
0%
0%
0%
2045
46.7%
46.7%
46.7%
0%
0%
0%
2046
46.6%
46.6%
46.6%
0%
0%
0%
2047
46.5%
46.5%
46.5%
0%
0%
0%
2048
46.4%
46.4%
46.4%
0%
0%
0%
2049
46.4%
46.4%
46.4%
0%
0%
0%
2050
46.3%
46.3%
46.3%
0%
0%
0%
2051
46.2%
46.2%
46.2%
0%
0%
0%
2052
46.1%
46.1%
46.1%
0%
0%
0%
2053
46.1%
46.1%
46.1%
0%
0%
0%
2054
46.0%
46.0%
46.0%
0%
0%
0%
2055
46.0%
46.0%
46.0%
0%
0%
0%
847
-------
Table B-22 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
61) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
214%
21.4%
21.4%
0.0%
0.0%
0.0%
2028
27.9%
27.9%
27.9%
0.0%
0.0%
0.0%
2029
33.9%
33.9%
33.9%
0.0%
0.0%
0.0%
2030
29.8%
29.8%
29.8%
10.0%
10.0%
10.0%
2031
31.7%
31.7%
31.7%
10.7%
10.7%
10.7%
2032
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2033
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2034
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2035
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2036
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2037
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2038
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2039
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2040
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2041
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2042
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2043
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2044
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2045
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2046
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2047
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2048
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2049
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2050
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2051
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2052
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2053
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2054
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
2055
35.4%
35.4%
35.4%
11.9%
11.9%
11.9%
848
-------
Table B-23 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
61) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
214%
21.4%
21.4%
0.0%
0.0%
0.0%
2028
27.9%
27.9%
27.9%
0.0%
0.0%
0.0%
2029
33.9%
33.9%
33.9%
0.0%
0.0%
0.0%
2030
38.3%
38.3%
38.3%
1.5%
1.5%
1.5%
2031
40.8%
40.8%
40.8%
1.6%
1.6%
1.6%
2032
45.6%
45.6%
45.6%
1.8%
1.8%
1.8%
2033
45.6%
45.6%
45.6%
1.8%
1.8%
1.8%
2034
45.6%
45.6%
45.6%
1.8%
1.8%
1.8%
2035
45.6%
45.6%
45.6%
1.8%
1.8%
1.8%
2036
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2037
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2038
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2039
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2040
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2041
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2042
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2043
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2044
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2045
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2046
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2047
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2048
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2049
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2050
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2051
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2052
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2053
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2054
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
2055
45.5%
45.5%
45.5%
1.8%
1.8%
1.8%
849
-------
Table B-24 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
62) in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
2.0%
2.0%
2.0%
0.0%
0.0%
0.0%
2028
4.0%
4.0%
4.0%
0.0%
0.0%
0.0%
2029
7.0%
7.0%
7.0%
0.0%
0.0%
0.0%
2030
6.3%
6.3%
6.3%
3.7%
3.7%
3.7%
2031
12.6%
12.6%
12.6%
7.4%
7.4%
7.4%
2032
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2033
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2034
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2035
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2036
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2037
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2038
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2039
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2040
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2041
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2042
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2043
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2044
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2045
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2046
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2047
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2048
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2049
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2050
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2051
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2052
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2053
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2054
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2055
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
850
-------
Table B-25 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 62)
in ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
2.0%
2.0%
2.0%
0.0%
0.0%
0.0%
2028
4.0%
4.0%
4.0%
0.0%
0.0%
0.0%
2029
7.0%
7.0%
7.0%
0.0%
0.0%
0.0%
2030
6.3%
6.3%
6.3%
3.7%
3.7%
3.7%
2031
12.6%
12.6%
12.6%
7.4%
7.4%
7.4%
2032
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2033
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2034
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2035
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2036
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2037
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2038
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2039
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2040
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2041
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2042
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2043
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2044
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2045
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2046
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2047
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2048
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2049
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2050
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2051
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2052
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2053
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2054
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
2055
15.8%
15.8%
15.8%
9.2%
9.2%
9.2%
851
-------
B.2 ZEV Sales Percentages in non-ACT States
Table B-26 ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.9%
16.1%
10.5%
0%
0%
0%
2028
7.4%
15.9%
10.4%
0%
0%
0%
2029
9.8%
15.9%
10.4%
0%
0%
0%
2030
12.2%
16.0%
12.2%
0%
0%
0%
2031
13.4%
38.1%
14.9%
0%
0%
0%
2032
14.6%
60.1%
19.4%
0%
0%
0%
2033
16.5%
55.7%
16.5%
0%
0%
0%
2034
18.6%
51.4%
18.6%
0%
0%
0%
2035
20.9%
47.0%
20.9%
0%
0%
0%
2036
21.8%
47.2%
21.8%
0%
0%
0%
2037
22.7%
47.3%
22.7%
0%
0%
0%
2038
23.6%
47.4%
23.6%
0%
0%
0%
2039
24.5%
47.5%
24.5%
0%
0%
0%
2040
25.4%
47.6%
25.4%
0%
0%
0%
2041
26.3%
47.6%
26.3%
0%
0%
0%
2042
27.2%
47.7%
27.2%
0%
0%
0%
2043
28.1%
47.8%
28.1%
0%
0%
0%
2044
29.0%
47.9%
29.0%
0%
0%
0%
2045
29.9%
48.1%
29.9%
0%
0%
0%
2046
30.7%
48.2%
30.7%
0%
0%
0%
2047
31.6%
48.4%
31.6%
0%
0%
0%
2048
32.5%
48.4%
32.5%
0%
0%
0%
2049
33.4%
48.5%
33.4%
0%
0%
0%
2050
34.3%
48.6%
34.3%
0%
0%
0%
2051
35.1%
48.7%
35.1%
0%
0%
0%
2052
36.0%
48.8%
36.0%
0%
0%
0%
2053
36.9%
48.9%
36.9%
0%
0%
0%
2054
37.7%
49.0%
37.7%
0%
0%
0%
2055
38.6%
49.1%
38.6%
0%
0%
0%
852
-------
Table B-27 ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
12.6%
8.3%
0%
0%
0%
2028
5.5%
9.9%
6.4%
0%
0%
0%
2029
7.4%
7.4%
7.4%
0%
0%
0%
2030
9.2%
9.2%
9.2%
0%
0%
0%
2031
10.1%
10.1%
10.1%
0%
0%
0%
2032
11.0%
11.0%
11.0%
0%
0%
0%
2033
12.4%
12.4%
12.4%
0%
0%
0%
2034
14.0%
14.0%
14.0%
0%
0%
0%
2035
15.6%
15.6%
15.6%
0%
0%
0%
2036
16.3%
16.3%
16.3%
0%
0%
0%
2037
17.0%
17.0%
17.0%
0%
0%
0%
2038
17.7%
17.7%
17.7%
0%
0%
0%
2039
18.4%
18.4%
18.4%
0%
0%
0%
2040
19.1%
19.1%
19.1%
0%
0%
0%
2041
19.7%
19.7%
19.7%
0%
0%
0%
2042
20.4%
20.4%
20.4%
0%
0%
0%
2043
21.1%
21.1%
21.1%
0%
0%
0%
2044
21.8%
21.8%
21.8%
0%
0%
0%
2045
22.4%
22.4%
22.4%
0%
0%
0%
2046
23.0%
23.0%
23.0%
0%
0%
0%
2047
23.7%
23.7%
23.7%
0%
0%
0%
2048
24.4%
24.4%
24.4%
0%
0%
0%
2049
25.0%
25.0%
25.0%
0%
0%
0%
2050
25.7%
25.7%
25.7%
0%
0%
0%
2051
26.3%
26.3%
26.3%
0%
0%
0%
2052
27.0%
27.0%
27.0%
0%
0%
0%
2053
27.7%
27.7%
27.7%
0%
0%
0%
2054
28.3%
28.3%
28.3%
0%
0%
0%
2055
29.0%
29.0%
29.0%
0%
0%
0%
853
-------
Table B-28 ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0.0%
0.0%
0.0%
2028
1.8%
1.8%
1.8%
0.0%
0.0%
0.0%
2029
2.5%
2.5%
2.5%
0.0%
0.0%
0.0%
2030
2.5%
2.5%
2.5%
0.6%
0.6%
0.6%
2031
2.5%
2.5%
2.5%
0.9%
0.9%
0.9%
2032
2.5%
2.5%
2.5%
1.2%
1.2%
1.2%
2033
2.6%
2.6%
2.6%
1.6%
1.6%
1.6%
2034
2.7%
2.7%
2.7%
2.0%
2.0%
2.0%
2035
2.8%
2.8%
2.8%
2.4%
2.4%
2.4%
2036
2.9%
2.9%
2.9%
2.5%
2.5%
2.5%
2037
3.1%
3.1%
3.1%
2.6%
2.6%
2.6%
2038
3.2%
3.2%
3.2%
2.7%
2.7%
2.7%
2039
3.3%
3.3%
3.3%
2.8%
2.8%
2.8%
2040
3.5%
3.5%
3.5%
2.9%
2.9%
2.9%
2041
3.6%
3.6%
3.6%
3.0%
3.0%
3.0%
2042
3.7%
3.7%
3.7%
3.1%
3.1%
3.1%
2043
3.8%
3.8%
3.8%
3.2%
3.2%
3.2%
2044
4.0%
4.0%
4.0%
3.3%
3.3%
3.3%
2045
4.1%
4.1%
4.1%
3.4%
3.4%
3.4%
2046
4.2%
4.2%
4.2%
3.5%
3.5%
3.5%
2047
4.3%
4.3%
4.3%
3.6%
3.6%
3.6%
2048
4.5%
4.5%
4.5%
3.7%
3.7%
3.7%
2049
4.6%
4.6%
4.6%
3.7%
3.7%
3.7%
2050
4.7%
4.7%
4.7%
3.8%
3.8%
3.8%
2051
4.9%
4.9%
4.9%
3.9%
3.9%
3.9%
2052
5.0%
5.0%
5.0%
4.0%
4.0%
4.0%
2053
5.1%
5.1%
5.1%
4.1%
4.1%
4.1%
2054
5.2%
5.2%
5.2%
4.2%
4.2%
4.2%
2055
5.4%
5.4%
5.4%
4.3%
4.3%
4.3%
854
-------
Table B-29 ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.9%
16.1%
10.5%
0%
0%
0%
2028
7.4%
15.9%
10.4%
0%
0%
0%
2029
9.8%
15.9%
10.4%
0%
0%
0%
2030
12.2%
16.0%
12.2%
0%
0%
0%
2031
13.4%
38.1%
14.9%
0%
0%
0%
2032
14.6%
60.1%
19.4%
0%
0%
0%
2033
16.5%
55.7%
16.5%
0%
0%
0%
2034
18.6%
51.4%
18.6%
0%
0%
0%
2035
20.9%
47.0%
20.9%
0%
0%
0%
2036
21.8%
47.2%
21.8%
0%
0%
0%
2037
22.7%
47.3%
22.7%
0%
0%
0%
2038
23.6%
47.4%
23.6%
0%
0%
0%
2039
24.5%
47.5%
24.5%
0%
0%
0%
2040
25.4%
47.6%
25.4%
0%
0%
0%
2041
26.3%
47.6%
26.3%
0%
0%
0%
2042
27.2%
47.7%
27.2%
0%
0%
0%
2043
28.1%
47.8%
28.1%
0%
0%
0%
2044
29.0%
47.9%
29.0%
0%
0%
0%
2045
29.9%
48.1%
29.9%
0%
0%
0%
2046
30.7%
48.2%
30.7%
0%
0%
0%
2047
31.6%
48.4%
31.6%
0%
0%
0%
2048
32.5%
48.4%
32.5%
0%
0%
0%
2049
33.4%
48.5%
33.4%
0%
0%
0%
2050
34.3%
48.6%
34.3%
0%
0%
0%
2051
35.1%
48.7%
35.1%
0%
0%
0%
2052
36.0%
48.8%
36.0%
0%
0%
0%
2053
36.9%
48.9%
36.9%
0%
0%
0%
2054
37.7%
49.0%
37.7%
0%
0%
0%
2055
38.6%
49.1%
38.6%
0%
0%
0%
855
-------
Table B-30 ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
7.5%
4.4%
0%
0%
0%
2028
5.5%
6.6%
5.5%
0%
0%
0%
2029
7.4%
7.4%
7.4%
0%
0%
0%
2030
9.2%
9.2%
9.2%
0%
0%
0%
2031
10.1%
10.1%
10.1%
0%
0%
0%
2032
11.0%
12.8%
11.0%
0%
0%
0%
2033
12.4%
12.4%
12.4%
0%
0%
0%
2034
14.0%
14.0%
14.0%
0%
0%
0%
2035
15.6%
15.6%
15.6%
0%
0%
0%
2036
16.3%
16.3%
16.3%
0%
0%
0%
2037
17.0%
17.0%
17.0%
0%
0%
0%
2038
17.7%
17.7%
17.7%
0%
0%
0%
2039
18.4%
18.4%
18.4%
0%
0%
0%
2040
19.1%
19.1%
19.1%
0%
0%
0%
2041
19.7%
19.7%
19.7%
0%
0%
0%
2042
20.4%
20.4%
20.4%
0%
0%
0%
2043
21.1%
21.1%
21.1%
0%
0%
0%
2044
21.8%
21.8%
21.8%
0%
0%
0%
2045
22.4%
22.4%
22.4%
0%
0%
0%
2046
23.0%
23.0%
23.0%
0%
0%
0%
2047
23.7%
23.7%
23.7%
0%
0%
0%
2048
24.4%
24.4%
24.4%
0%
0%
0%
2049
25.0%
25.0%
25.0%
0%
0%
0%
2050
25.7%
25.7%
25.7%
0%
0%
0%
2051
26.3%
26.3%
26.3%
0%
0%
0%
2052
27.0%
27.0%
27.0%
0%
0%
0%
2053
27.7%
27.7%
27.7%
0%
0%
0%
2054
28.3%
28.3%
28.3%
0%
0%
0%
2055
29.0%
29.0%
29.0%
0%
0%
0%
856
-------
Table B-31 ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0%
0%
0%
2028
1.8%
10.3%
3.0%
0%
0%
0%
2029
2.5%
11.2%
3.9%
0%
0%
0%
2030
3.1%
12.1%
4.9%
0%
0%
0%
2031
3.4%
25.9%
7.8%
0%
0%
0%
2032
3.7%
39.0%
10.8%
0%
0%
0%
2033
4.1%
37.5%
8.6%
0%
0%
0%
2034
4.7%
35.2%
6.4%
0%
0%
0%
2035
5.2%
33.1%
5.2%
0%
0%
0%
2036
5.4%
33.1%
5.4%
0%
0%
0%
2037
5.7%
33.2%
5.7%
0%
0%
0%
2038
5.9%
33.2%
5.9%
0%
0%
0%
2039
6.1%
33.3%
6.1%
0%
0%
0%
2040
6.4%
33.3%
6.4%
0%
0%
0%
2041
6.6%
33.4%
6.6%
0%
0%
0%
2042
6.8%
33.4%
6.8%
0%
0%
0%
2043
7.0%
33.4%
7.0%
0%
0%
0%
2044
7.3%
33.5%
7.3%
0%
0%
0%
2045
7.5%
33.6%
7.5%
0%
0%
0%
2046
7.7%
33.7%
7.7%
0%
0%
0%
2047
7.9%
33.7%
7.9%
0%
0%
0%
2048
8.1%
33.8%
8.1%
0%
0%
0%
2049
8.3%
33.8%
8.3%
0%
0%
0%
2050
8.6%
33.8%
8.6%
0%
0%
0%
2051
8.8%
33.9%
8.8%
0%
0%
0%
2052
9.0%
34.0%
9.0%
0%
0%
0%
2053
9.2%
34.0%
9.2%
0%
0%
0%
2054
9.4%
34.0%
9.4%
0%
0%
0%
2055
9.7%
34.1%
9.7%
0%
0%
0%
857
-------
Table B-32 ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.9%
17.3%
12.4%
0%
0%
0%
2028
7.4%
18.7%
13.9%
0%
0%
0%
2029
9.8%
20.3%
15.5%
0%
0%
0%
2030
12.2%
21.9%
17.1%
0%
0%
0%
2031
13.4%
42.0%
21.8%
0%
0%
0%
2032
14.6%
62.1%
26.4%
0%
0%
0%
2033
16.5%
59.0%
23.4%
0%
0%
0%
2034
18.6%
56.0%
20.3%
0%
0%
0%
2035
20.9%
53.0%
20.9%
0%
0%
0%
2036
21.8%
53.1%
21.8%
0%
0%
0%
2037
22.7%
53.1%
22.7%
0%
0%
0%
2038
23.6%
53.2%
23.6%
0%
0%
0%
2039
24.5%
53.3%
24.5%
0%
0%
0%
2040
25.4%
53.4%
25.4%
0%
0%
0%
2041
26.3%
53.4%
26.3%
0%
0%
0%
2042
27.2%
53.5%
27.2%
0%
0%
0%
2043
28.1%
53.5%
28.1%
0%
0%
0%
2044
29.0%
53.6%
29.0%
0%
0%
0%
2045
29.9%
53.7%
29.9%
0%
0%
0%
2046
30.7%
53.8%
30.7%
0%
0%
0%
2047
31.6%
53.9%
31.6%
0%
0%
0%
2048
32.5%
54.0%
32.5%
0%
0%
0%
2049
33.4%
54.0%
33.4%
0%
0%
0%
2050
34.3%
54.1%
34.3%
0%
0%
0%
2051
35.1%
54.2%
35.1%
0%
0%
0%
2052
36.0%
54.2%
36.0%
0%
0%
0%
2053
36.9%
54.3%
36.9%
0%
0%
0%
2054
37.7%
54.4%
37.7%
0%
0%
0%
2055
38.6%
54.4%
38.6%
0%
0%
0%
858
-------
Table B-33 ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
20.0%
14.3%
0%
0%
0%
2028
5.5%
24.8%
18.6%
0%
0%
0%
2029
7.4%
29.5%
23.1%
0%
0%
0%
2030
9.2%
34.1%
27.7%
0%
0%
0%
2031
10.1%
53.3%
34.3%
0%
0%
0%
2032
11.0%
70.0%
40.6%
0%
0%
0%
2033
12.4%
70.0%
39.5%
0%
0%
0%
2034
14.0%
70.0%
38.4%
0%
0%
0%
2035
15.6%
69.7%
37.4%
0%
0%
0%
2036
16.3%
69.8%
37.4%
0%
0%
0%
2037
17.0%
69.8%
37.4%
0%
0%
0%
2038
17.7%
69.8%
37.4%
0%
0%
0%
2039
18.4%
69.8%
37.5%
0%
0%
0%
2040
19.1%
69.9%
37.5%
0%
0%
0%
2041
19.7%
69.9%
37.5%
0%
0%
0%
2042
20.4%
69.9%
37.5%
0%
0%
0%
2043
21.1%
69.9%
37.5%
0%
0%
0%
2044
21.8%
69.9%
37.6%
0%
0%
0%
2045
22.4%
70.0%
37.6%
0%
0%
0%
2046
23.0%
70.0%
37.7%
0%
0%
0%
2047
23.7%
70.0%
37.7%
0%
0%
0%
2048
24.4%
70.0%
37.7%
0%
0%
0%
2049
25.0%
70.0%
37.7%
0%
0%
0%
2050
25.7%
70.0%
37.7%
0%
0%
0%
2051
26.3%
70.0%
37.8%
0%
0%
0%
2052
27.0%
70.0%
37.8%
0%
0%
0%
2053
27.7%
70.0%
37.8%
0%
0%
0%
2054
28.3%
70.0%
37.8%
0%
0%
0%
2055
29.0%
70.0%
37.9%
0%
0%
0%
859
-------
Table B-34 ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0%
0%
0%
2028
1.8%
15.7%
7.3%
0%
0%
0%
2029
2.5%
16.3%
8.5%
0%
0%
0%
2030
3.1%
16.9%
9.5%
0%
0%
0%
2031
3.4%
28.3%
10.7%
0%
0%
0%
2032
3.7%
39.0%
12.6%
0%
0%
0%
2033
4.1%
37.7%
10.7%
0%
0%
0%
2034
4.7%
35.8%
8.8%
0%
0%
0%
2035
5.2%
34.0%
7.0%
0%
0%
0%
2036
5.4%
34.0%
7.0%
0%
0%
0%
2037
5.7%
34.1%
7.1%
0%
0%
0%
2038
5.9%
34.1%
7.1%
0%
0%
0%
2039
6.1%
34.2%
7.2%
0%
0%
0%
2040
6.4%
34.2%
7.2%
0%
0%
0%
2041
6.6%
34.2%
7.2%
0%
0%
0%
2042
6.8%
34.3%
7.3%
0%
0%
0%
2043
7.0%
34.3%
7.3%
0%
0%
0%
2044
7.3%
34.4%
7.4%
0%
0%
0%
2045
7.5%
34.4%
7.5%
0%
0%
0%
2046
7.7%
34.5%
7.7%
0%
0%
0%
2047
7.9%
34.6%
7.9%
0%
0%
0%
2048
8.1%
34.6%
8.1%
0%
0%
0%
2049
8.3%
34.6%
8.3%
0%
0%
0%
2050
8.6%
34.7%
8.6%
0%
0%
0%
2051
8.8%
34.7%
8.8%
0%
0%
0%
2052
9.0%
34.8%
9.0%
0%
0%
0%
2053
9.2%
34.8%
9.2%
0%
0%
0%
2054
9.4%
34.8%
9.4%
0%
0%
0%
2055
9.7%
34.9%
9.7%
0%
0%
0%
860
-------
Table B-35 ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
20.0%
14.0%
0%
0%
0%
2028
5.5%
20.0%
14.4%
0%
0%
0%
2029
7.4%
19.9%
14.6%
0%
0%
0%
2030
9.2%
19.8%
14.8%
0%
0%
0%
2031
10.1%
26.6%
14.1%
0%
0%
0%
2032
11.0%
33.5%
14.3%
0%
0%
0%
2033
12.4%
32.0%
12.8%
0%
0%
0%
2034
14.0%
30.6%
14.0%
0%
0%
0%
2035
15.6%
29.2%
15.6%
0%
0%
0%
2036
16.3%
29.2%
16.3%
0%
0%
0%
2037
17.0%
29.2%
17.0%
0%
0%
0%
2038
17.7%
29.3%
17.7%
0%
0%
0%
2039
18.4%
29.3%
18.4%
0%
0%
0%
2040
19.1%
29.3%
19.1%
0%
0%
0%
2041
19.7%
29.4%
19.7%
0%
0%
0%
2042
20.4%
29.4%
20.4%
0%
0%
0%
2043
21.1%
29.4%
21.1%
0%
0%
0%
2044
21.8%
29.4%
21.8%
0%
0%
0%
2045
22.4%
29.5%
22.4%
0%
0%
0%
2046
23.0%
29.6%
23.0%
0%
0%
0%
2047
23.7%
29.6%
23.7%
0%
0%
0%
2048
24.4%
29.6%
24.4%
0%
0%
0%
2049
25.0%
29.6%
25.0%
0%
0%
0%
2050
25.7%
29.7%
25.7%
0%
0%
0%
2051
26.3%
29.7%
26.3%
0%
0%
0%
2052
27.0%
29.7%
27.0%
0%
0%
0%
2053
27.7%
29.8%
27.7%
0%
0%
0%
2054
28.3%
29.8%
28.3%
0%
0%
0%
2055
29.0%
29.8%
29.0%
0%
0%
0%
861
-------
Table B-36 ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0%
0%
0%
2028
1.8%
12.7%
7.4%
0%
0%
0%
2029
2.5%
15.1%
9.8%
0%
0%
0%
2030
3.1%
17.4%
12.2%
0%
0%
0%
2031
3.4%
28.3%
15.1%
0%
0%
0%
2032
3.7%
39.0%
18.2%
0%
0%
0%
2033
4.1%
38.5%
17.4%
0%
0%
0%
2034
4.7%
37.7%
16.6%
0%
0%
0%
2035
5.2%
36.9%
15.9%
0%
0%
0%
2036
5.4%
37.0%
15.9%
0%
0%
0%
2037
5.7%
37.0%
15.9%
0%
0%
0%
2038
5.9%
37.0%
15.9%
0%
0%
0%
2039
6.1%
37.0%
15.9%
0%
0%
0%
2040
6.4%
37.0%
15.9%
0%
0%
0%
2041
6.6%
37.0%
16.0%
0%
0%
0%
2042
6.8%
37.1%
16.0%
0%
0%
0%
2043
7.0%
37.1%
16.0%
0%
0%
0%
2044
7.3%
37.1%
16.0%
0%
0%
0%
2045
7.5%
37.1%
16.0%
0%
0%
0%
2046
7.7%
37.2%
16.1%
0%
0%
0%
2047
7.9%
37.2%
16.1%
0%
0%
0%
2048
8.1%
37.2%
16.1%
0%
0%
0%
2049
8.3%
37.2%
16.1%
0%
0%
0%
2050
8.6%
37.2%
16.1%
0%
0%
0%
2051
8.8%
37.2%
16.2%
0%
0%
0%
2052
9.0%
37.3%
16.2%
0%
0%
0%
2053
9.2%
37.3%
16.2%
0%
0%
0%
2054
9.4%
37.3%
16.2%
0%
0%
0%
2055
9.7%
37.3%
16.2%
0%
0%
0%
862
-------
Table B-37 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks (sourceTypelD
52) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.9%
18.2%
13.9%
0%
0%
0%
2028
7.4%
21.0%
16.7%
0%
0%
0%
2029
9.8%
23.9%
19.6%
0%
0%
0%
2030
12.2%
26.7%
22.5%
0%
0%
0%
2031
13.4%
45.2%
27.3%
0%
0%
0%
2032
14.6%
63.7%
32.2%
0%
0%
0%
2033
16.5%
61.7%
30.2%
0%
0%
0%
2034
18.6%
59.8%
28.2%
0%
0%
0%
2035
20.9%
57.8%
26.3%
0%
0%
0%
2036
21.8%
57.9%
26.3%
0%
0%
0%
2037
22.7%
57.9%
26.4%
0%
0%
0%
2038
23.6%
58.0%
26.4%
0%
0%
0%
2039
24.5%
58.0%
26.5%
0%
0%
0%
2040
25.4%
58.1%
26.5%
0%
0%
0%
2041
26.3%
58.1%
26.5%
0%
0%
0%
2042
27.2%
58.1%
27.2%
0%
0%
0%
2043
28.1%
58.2%
28.1%
0%
0%
0%
2044
29.0%
58.2%
29.0%
0%
0%
0%
2045
29.9%
58.3%
29.9%
0%
0%
0%
2046
30.7%
58.4%
30.7%
0%
0%
0%
2047
31.6%
58.4%
31.6%
0%
0%
0%
2048
32.5%
58.4%
32.5%
0%
0%
0%
2049
33.4%
58.5%
33.4%
0%
0%
0%
2050
34.3%
58.5%
34.3%
0%
0%
0%
2051
35.1%
58.6%
35.1%
0%
0%
0%
2052
36.0%
58.6%
36.0%
0%
0%
0%
2053
36.9%
58.7%
36.9%
0%
0%
0%
2054
37.7%
58.7%
37.7%
0%
0%
0%
2055
38.6%
58.7%
38.6%
0%
0%
0%
863
-------
Table B-38 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
52) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
10.5%
6.8%
0%
0%
0%
2028
5.5%
11.1%
7.4%
0%
0%
0%
2029
7.4%
11.7%
8.1%
0%
0%
0%
2030
9.2%
12.4%
9.2%
0%
0%
0%
2031
10.1%
20.6%
10.5%
0%
0%
0%
2032
11.0%
28.7%
12.2%
0%
0%
0%
2033
12.4%
27.5%
12.4%
0%
0%
0%
2034
14.0%
26.2%
14.0%
0%
0%
0%
2035
15.6%
25.0%
15.6%
0%
0%
0%
2036
16.3%
25.0%
16.3%
0%
0%
0%
2037
17.0%
25.1%
17.0%
0%
0%
0%
2038
17.7%
25.1%
17.7%
0%
0%
0%
2039
18.4%
25.1%
18.4%
0%
0%
0%
2040
19.1%
25.2%
19.1%
0%
0%
0%
2041
19.7%
25.2%
19.7%
0%
0%
0%
2042
20.4%
25.2%
20.4%
0%
0%
0%
2043
21.1%
25.2%
21.1%
0%
0%
0%
2044
21.8%
25.2%
21.8%
0%
0%
0%
2045
22.4%
25.3%
22.4%
0%
0%
0%
2046
23.0%
25.3%
23.0%
0%
0%
0%
2047
23.7%
25.4%
23.7%
0%
0%
0%
2048
24.4%
25.4%
24.4%
0%
0%
0%
2049
25.0%
25.4%
25.0%
0%
0%
0%
2050
25.7%
25.7%
25.7%
0%
0%
0%
2051
26.3%
26.3%
26.3%
0%
0%
0%
2052
27.0%
27.0%
27.0%
0%
0%
0%
2053
27.7%
27.7%
27.7%
0%
0%
0%
2054
28.3%
28.3%
28.3%
0%
0%
0%
2055
29.0%
29.0%
29.0%
0%
0%
0%
864
-------
Table B-39 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
52) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0%
0%
0%
2028
1.8%
5.9%
2.1%
0%
0%
0%
2029
2.5%
6.9%
3.0%
0%
0%
0%
2030
3.1%
7.9%
4.0%
0%
0%
0%
2031
3.4%
16.2%
6.2%
0%
0%
0%
2032
3.7%
24.4%
8.2%
0%
0%
0%
2033
4.1%
23.4%
7.2%
0%
0%
0%
2034
4.7%
22.3%
6.1%
0%
0%
0%
2035
5.2%
21.3%
5.2%
0%
0%
0%
2036
5.4%
21.3%
5.4%
0%
0%
0%
2037
5.7%
21.3%
5.7%
0%
0%
0%
2038
5.9%
21.4%
5.9%
0%
0%
0%
2039
6.1%
21.4%
6.1%
0%
0%
0%
2040
6.4%
21.4%
6.4%
0%
0%
0%
2041
6.6%
21.4%
6.6%
0%
0%
0%
2042
6.8%
21.4%
6.8%
0%
0%
0%
2043
7.0%
21.5%
7.0%
0%
0%
0%
2044
7.3%
21.5%
7.3%
0%
0%
0%
2045
7.5%
21.5%
7.5%
0%
0%
0%
2046
7.7%
21.6%
7.7%
0%
0%
0%
2047
7.9%
21.6%
7.9%
0%
0%
0%
2048
8.1%
21.6%
8.1%
0%
0%
0%
2049
8.3%
21.6%
8.3%
0%
0%
0%
2050
8.6%
21.7%
8.6%
0%
0%
0%
2051
8.8%
21.7%
8.8%
0%
0%
0%
2052
9.0%
21.7%
9.0%
0%
0%
0%
2053
9.2%
21.7%
9.2%
0%
0%
0%
2054
9.4%
21.8%
9.4%
0%
0%
0%
2055
9.7%
21.8%
9.7%
0%
0%
0%
865
-------
Table B-40 ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks (sourceTypelD
53) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.9%
5.1%
4.9%
0%
0%
0%
2028
7.4%
7.4%
7.4%
0%
0%
0%
2029
9.8%
9.8%
9.8%
0%
0%
0%
2030
12.2%
12.2%
12.2%
0%
0%
0%
2031
13.4%
17.5%
13.4%
0%
0%
0%
2032
14.6%
28.7%
14.6%
0%
0%
0%
2033
16.5%
26.7%
16.5%
0%
0%
0%
2034
18.6%
24.8%
18.6%
0%
0%
0%
2035
20.9%
22.8%
20.9%
0%
0%
0%
2036
21.8%
22.9%
21.8%
0%
0%
0%
2037
22.7%
22.9%
22.7%
0%
0%
0%
2038
23.6%
23.6%
23.6%
0%
0%
0%
2039
24.5%
24.5%
24.5%
0%
0%
0%
2040
25.4%
25.4%
25.4%
0%
0%
0%
2041
26.3%
26.3%
26.3%
0%
0%
0%
2042
27.2%
27.2%
27.2%
0%
0%
0%
2043
28.1%
28.1%
28.1%
0%
0%
0%
2044
29.0%
29.0%
29.0%
0%
0%
0%
2045
29.9%
29.9%
29.9%
0%
0%
0%
2046
30.7%
30.7%
30.7%
0%
0%
0%
2047
31.6%
31.6%
31.6%
0%
0%
0%
2048
32.5%
32.5%
32.5%
0%
0%
0%
2049
33.4%
33.4%
33.4%
0%
0%
0%
2050
34.3%
34.3%
34.3%
0%
0%
0%
2051
35.1%
35.1%
35.1%
0%
0%
0%
2052
36.0%
36.0%
36.0%
0%
0%
0%
2053
36.9%
36.9%
36.9%
0%
0%
0%
2054
37.7%
37.7%
37.7%
0%
0%
0%
2055
38.6%
38.6%
38.6%
0%
0%
0%
866
-------
Table B-41 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
53) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
12.6%
8.4%
0%
0%
0%
2028
5.5%
13.6%
9.4%
0%
0%
0%
2029
7.4%
14.6%
10.5%
0%
0%
0%
2030
9.2%
15.6%
11.6%
0%
0%
0%
2031
10.1%
24.9%
13.6%
0%
0%
0%
2032
11.0%
34.2%
15.7%
0%
0%
0%
2033
12.4%
33.0%
14.4%
0%
0%
0%
2034
14.0%
31.8%
14.0%
0%
0%
0%
2035
15.6%
30.5%
15.6%
0%
0%
0%
2036
16.3%
30.6%
16.3%
0%
0%
0%
2037
17.0%
30.6%
17.0%
0%
0%
0%
2038
17.7%
30.6%
17.7%
0%
0%
0%
2039
18.4%
30.7%
18.4%
0%
0%
0%
2040
19.1%
30.7%
19.1%
0%
0%
0%
2041
19.7%
30.7%
19.7%
0%
0%
0%
2042
20.4%
30.7%
20.4%
0%
0%
0%
2043
21.1%
30.7%
21.1%
0%
0%
0%
2044
21.8%
30.8%
21.8%
0%
0%
0%
2045
22.4%
30.8%
22.4%
0%
0%
0%
2046
23.0%
30.9%
23.0%
0%
0%
0%
2047
23.7%
30.9%
23.7%
0%
0%
0%
2048
24.4%
30.9%
24.4%
0%
0%
0%
2049
25.0%
31.0%
25.0%
0%
0%
0%
2050
25.7%
31.0%
25.7%
0%
0%
0%
2051
26.3%
31.0%
26.3%
0%
0%
0%
2052
27.0%
31.0%
27.0%
0%
0%
0%
2053
27.7%
31.1%
27.7%
0%
0%
0%
2054
28.3%
31.1%
28.3%
0%
0%
0%
2055
29.0%
31.1%
29.0%
0%
0%
0%
867
-------
Table B-42 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 53)
in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0%
0%
0%
2028
1.8%
1.8%
1.8%
0%
0%
0%
2029
2.5%
3.8%
2.5%
0%
0%
0%
2030
3.1%
7.3%
3.6%
0%
0%
0%
2031
3.4%
23.3%
10.8%
0%
0%
0%
2032
3.7%
39.0%
16.7%
0%
0%
0%
2033
4.1%
38.3%
15.6%
0%
0%
0%
2034
4.7%
37.2%
14.6%
0%
0%
0%
2035
5.2%
36.2%
13.5%
0%
0%
0%
2036
5.4%
36.2%
13.6%
0%
0%
0%
2037
5.7%
36.2%
13.6%
0%
0%
0%
2038
5.9%
36.2%
13.6%
0%
0%
0%
2039
6.1%
36.3%
13.6%
0%
0%
0%
2040
6.4%
36.3%
13.7%
0%
0%
0%
2041
6.6%
36.3%
13.7%
0%
0%
0%
2042
6.8%
36.3%
13.7%
0%
0%
0%
2043
7.0%
36.3%
13.7%
0%
0%
0%
2044
7.3%
36.4%
13.7%
0%
0%
0%
2045
7.5%
36.4%
13.8%
0%
0%
0%
2046
7.7%
36.5%
13.8%
0%
0%
0%
2047
7.9%
36.5%
13.9%
0%
0%
0%
2048
8.1%
36.5%
13.9%
0%
0%
0%
2049
8.3%
36.5%
13.9%
0%
0%
0%
2050
8.6%
36.5%
13.9%
0%
0%
0%
2051
8.8%
36.6%
13.9%
0%
0%
0%
2052
9.0%
36.6%
14.0%
0%
0%
0%
2053
9.2%
36.6%
14.0%
0%
0%
0%
2054
9.4%
36.6%
14.0%
0%
0%
0%
2055
9.7%
36.7%
14.0%
0%
0%
0%
868
-------
Table B-43 ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.9%
4.9%
4.9%
0%
0%
0%
2028
7.4%
7.4%
7.4%
0%
0%
0%
2029
9.8%
9.8%
9.8%
0%
0%
0%
2030
12.2%
12.2%
12.2%
0%
0%
0%
2031
13.4%
13.4%
13.4%
0%
0%
0%
2032
14.6%
14.6%
14.6%
0%
0%
0%
2033
16.5%
16.5%
16.5%
0%
0%
0%
2034
18.6%
18.6%
18.6%
0%
0%
0%
2035
20.9%
20.9%
20.9%
0%
0%
0%
2036
21.8%
21.8%
21.8%
0%
0%
0%
2037
22.7%
22.7%
22.7%
0%
0%
0%
2038
23.6%
23.6%
23.6%
0%
0%
0%
2039
24.5%
24.5%
24.5%
0%
0%
0%
2040
25.4%
25.4%
25.4%
0%
0%
0%
2041
26.3%
26.3%
26.3%
0%
0%
0%
2042
27.2%
27.2%
27.2%
0%
0%
0%
2043
28.1%
28.1%
28.1%
0%
0%
0%
2044
29.0%
29.0%
29.0%
0%
0%
0%
2045
29.9%
29.9%
29.9%
0%
0%
0%
2046
30.7%
30.7%
30.7%
0%
0%
0%
2047
31.6%
31.6%
31.6%
0%
0%
0%
2048
32.5%
32.5%
32.5%
0%
0%
0%
2049
33.4%
33.4%
33.4%
0%
0%
0%
2050
34.3%
34.3%
34.3%
0%
0%
0%
2051
35.1%
35.1%
35.1%
0%
0%
0%
2052
36.0%
36.0%
36.0%
0%
0%
0%
2053
36.9%
36.9%
36.9%
0%
0%
0%
2054
37.7%
37.7%
37.7%
0%
0%
0%
2055
38.6%
38.6%
38.6%
0%
0%
0%
869
-------
Table B-44 ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.7%
3.7%
3.7%
0%
0%
0%
2028
5.5%
5.5%
5.5%
0%
0%
0%
2029
7.4%
7.4%
7.4%
0%
0%
0%
2030
9.2%
9.2%
9.2%
0%
0%
0%
2031
10.1%
10.1%
10.1%
0%
0%
0%
2032
11.0%
11.0%
11.0%
0%
0%
0%
2033
12.4%
12.4%
12.4%
0%
0%
0%
2034
14.0%
14.0%
14.0%
0%
0%
0%
2035
15.6%
15.6%
15.6%
0%
0%
0%
2036
16.3%
16.3%
16.3%
0%
0%
0%
2037
17.0%
17.0%
17.0%
0%
0%
0%
2038
17.7%
17.7%
17.7%
0%
0%
0%
2039
18.4%
18.4%
18.4%
0%
0%
0%
2040
19.1%
19.1%
19.1%
0%
0%
0%
2041
19.7%
19.7%
19.7%
0%
0%
0%
2042
20.4%
20.4%
20.4%
0%
0%
0%
2043
21.1%
21.1%
21.1%
0%
0%
0%
2044
21.8%
21.8%
21.8%
0%
0%
0%
2045
22.4%
22.4%
22.4%
0%
0%
0%
2046
23.0%
23.0%
23.0%
0%
0%
0%
2047
23.7%
23.7%
23.7%
0%
0%
0%
2048
24.4%
24.4%
24.4%
0%
0%
0%
2049
25.0%
25.0%
25.0%
0%
0%
0%
2050
25.7%
25.7%
25.7%
0%
0%
0%
2051
26.3%
26.3%
26.3%
0%
0%
0%
2052
27.0%
27.0%
27.0%
0%
0%
0%
2053
27.7%
27.7%
27.7%
0%
0%
0%
2054
28.3%
28.3%
28.3%
0%
0%
0%
2055
29.0%
29.0%
29.0%
0%
0%
0%
870
-------
Table B-45 ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) in non-ACT
states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
1.2%
1.2%
1.2%
0%
0%
0%
2028
1.8%
1.8%
1.8%
0%
0%
0%
2029
2.5%
2.5%
2.5%
0%
0%
0%
2030
3.1%
3.1%
3.1%
0%
0%
0%
2031
3.4%
3.4%
3.4%
0%
0%
0%
2032
3.7%
3.7%
3.7%
0%
0%
0%
2033
4.1%
4.1%
4.1%
0%
0%
0%
2034
4.7%
4.7%
4.7%
0%
0%
0%
2035
5.2%
5.2%
5.2%
0%
0%
0%
2036
5.4%
5.4%
5.4%
0%
0%
0%
2037
5.7%
5.7%
5.7%
0%
0%
0%
2038
5.9%
5.9%
5.9%
0%
0%
0%
2039
6.1%
6.1%
6.1%
0%
0%
0%
2040
6.4%
6.4%
6.4%
0%
0%
0%
2041
6.6%
6.6%
6.6%
0%
0%
0%
2042
6.8%
6.8%
6.8%
0%
0%
0%
2043
7.0%
7.0%
7.0%
0%
0%
0%
2044
7.3%
7.3%
7.3%
0%
0%
0%
2045
7.5%
7.5%
7.5%
0%
0%
0%
2046
7.7%
7.7%
7.7%
0%
0%
0%
2047
7.9%
7.9%
7.9%
0%
0%
0%
2048
8.1%
8.1%
8.1%
0%
0%
0%
2049
8.3%
8.3%
8.3%
0%
0%
0%
2050
8.6%
8.6%
8.6%
0%
0%
0%
2051
8.8%
8.8%
8.8%
0%
0%
0%
2052
9.0%
9.0%
9.0%
0%
0%
0%
2053
9.2%
9.2%
9.2%
0%
0%
0%
2054
9.4%
9.4%
9.4%
0%
0%
0%
2055
9.7%
9.7%
9.7%
0%
0%
0%
871
-------
Table B-46 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks (sourceTypelD
61) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
2.1%
4.3%
2.1%
0.0%
0.0%
0.0%
2028
2.7%
5.0%
2.7%
0.0%
0.0%
0.0%
2029
3.3%
5.8%
3.9%
0.0%
0.0%
0.0%
2030
2.9%
6.5%
4.5%
1.0%
2.2%
1.5%
2031
3.0%
12.1%
5.1%
1.0%
4.1%
1.7%
2032
3.4%
18.8%
6.5%
1.1%
6.4%
2.2%
2033
3.5%
18.8%
6.5%
1.2%
6.4%
2.2%
2034
3.7%
18.8%
6.5%
1.3%
6.4%
2.2%
2035
3.9%
18.8%
6.5%
1.3%
6.4%
2.2%
2036
4.1%
18.8%
6.5%
1.4%
6.4%
2.2%
2037
4.3%
18.8%
6.5%
1.4%
6.4%
2.2%
2038
4.4%
18.8%
6.5%
1.5%
6.4%
2.2%
2039
4.6%
18.8%
6.5%
1.6%
6.4%
2.2%
2040
4.8%
18.8%
6.5%
1.6%
6.4%
2.2%
2041
5.0%
18.8%
6.5%
1.7%
6.4%
2.2%
2042
5.1%
18.8%
6.5%
1.7%
6.4%
2.2%
2043
5.3%
18.8%
6.5%
1.8%
6.4%
2.2%
2044
5.5%
18.8%
6.5%
1.8%
6.4%
2.2%
2045
5.7%
18.8%
6.5%
1.9%
6.4%
2.2%
2046
5.8%
18.8%
6.5%
2.0%
6.4%
2.2%
2047
6.0%
18.9%
6.5%
2.0%
6.4%
2.2%
2048
6.2%
18.9%
6.5%
2.1%
6.4%
2.2%
2049
6.4%
18.9%
6.5%
2.1%
6.4%
2.2%
2050
6.5%
18.9%
6.5%
2.2%
6.4%
2.2%
2051
6.7%
18.9%
6.7%
2.3%
6.4%
2.3%
2052
6.9%
18.9%
6.9%
2.3%
6.4%
2.3%
2053
7.1%
18.9%
7.1%
2.4%
6.4%
2.4%
2054
7.3%
18.9%
7.3%
2.4%
6.4%
2.4%
2055
7.4%
18.9%
7.4%
2.5%
6.4%
2.5%
872
-------
Table B-47 ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks (sourceTypelD
61) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
2.1%
2.1%
2.1%
0.0%
0.0%
0.0%
2028
2.7%
5.5%
3.4%
0.0%
0.0%
0.0%
2029
3.3%
9.7%
7.3%
0.0%
0.0%
0.0%
2030
3.7%
13.8%
10.5%
0.1%
0.5%
0.4%
2031
3.9%
28.4%
15.2%
0.2%
1.1%
0.6%
2032
4.4%
43.2%
19.0%
0.2%
1.7%
0.8%
2033
4.6%
43.2%
19.0%
0.2%
1.7%
0.8%
2034
4.8%
43.2%
19.0%
0.2%
1.7%
0.8%
2035
5.0%
43.2%
19.0%
0.2%
1.7%
0.8%
2036
5.2%
43.2%
19.0%
0.2%
1.7%
0.8%
2037
5.5%
43.2%
19.0%
0.2%
1.7%
0.8%
2038
5.7%
43.2%
19.0%
0.2%
1.7%
0.8%
2039
5.9%
43.2%
19.0%
0.2%
1.7%
0.8%
2040
6.1%
43.2%
19.0%
0.2%
1.7%
0.8%
2041
6.4%
43.2%
19.0%
0.3%
1.7%
0.8%
2042
6.6%
43.2%
19.0%
0.3%
1.7%
0.8%
2043
6.8%
43.2%
19.0%
0.3%
1.7%
0.8%
2044
7.1%
43.2%
19.0%
0.3%
1.7%
0.8%
2045
7.3%
43.2%
19.0%
0.3%
1.7%
0.8%
2046
7.5%
43.2%
19.0%
0.3%
1.7%
0.8%
2047
7.7%
43.2%
19.0%
0.3%
1.7%
0.8%
2048
8.0%
43.2%
19.0%
0.3%
1.7%
0.8%
2049
8.2%
43.2%
19.0%
0.3%
1.7%
0.8%
2050
8.4%
43.2%
19.0%
0.3%
1.7%
0.8%
2051
8.6%
43.2%
19.0%
0.3%
1.7%
0.8%
2052
8.9%
43.2%
19.0%
0.4%
1.7%
0.8%
2053
9.1%
43.2%
19.0%
0.4%
1.7%
0.8%
2054
9.3%
43.2%
19.0%
0.4%
1.7%
0.8%
2055
9.5%
43.2%
19.0%
0.4%
1.7%
0.8%
873
-------
Table B-48 ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks (sourceTypelD
62) in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
0.2%
0.2%
0.2%
0.0%
0.0%
0.0%
2028
0.4%
0.4%
0.4%
0.0%
0.0%
0.0%
2029
0.7%
0.7%
0.7%
0.0%
0.0%
0.0%
2030
0.6%
3.6%
2.7%
0.4%
2.1%
1.6%
2031
1.2%
7.2%
5.5%
0.7%
4.2%
3.2%
2032
1.5%
15.8%
8.6%
0.9%
9.2%
5.0%
2033
1.6%
15.8%
8.6%
0.9%
9.2%
5.0%
2034
1.7%
15.8%
8.6%
1.0%
9.2%
5.0%
2035
1.7%
15.8%
8.6%
1.0%
9.2%
5.0%
2036
1.8%
15.8%
8.6%
1.1%
9.2%
5.0%
2037
1.9%
15.8%
8.6%
1.1%
9.2%
5.0%
2038
2.0%
15.8%
8.6%
1.2%
9.2%
5.0%
2039
2.1%
15.8%
8.6%
1.2%
9.2%
5.0%
2040
2.1%
15.8%
8.6%
1.2%
9.2%
5.0%
2041
2.2%
15.8%
8.6%
1.3%
9.2%
5.0%
2042
2.3%
15.8%
8.6%
1.3%
9.2%
5.0%
2043
2.4%
15.8%
8.6%
1.4%
9.2%
5.0%
2044
2.4%
15.8%
8.6%
1.4%
9.2%
5.0%
2045
2.5%
15.8%
8.6%
1.5%
9.2%
5.0%
2046
2.6%
15.8%
8.6%
1.5%
9.2%
5.0%
2047
2.7%
15.8%
8.6%
1.6%
9.2%
5.0%
2048
2.8%
15.8%
8.6%
1.6%
9.2%
5.0%
2049
2.8%
15.8%
8.6%
1.7%
9.2%
5.0%
2050
2.9%
15.8%
8.6%
1.7%
9.2%
5.0%
2051
3.0%
15.8%
8.6%
1.8%
9.2%
5.0%
2052
3.1%
15.8%
8.6%
1.8%
9.2%
5.0%
2053
3.2%
15.8%
8.6%
1.8%
9.2%
5.0%
2054
3.2%
15.8%
8.6%
1.9%
9.2%
5.0%
2055
3.3%
15.8%
8.6%
1.9%
9.2%
5.0%
874
-------
Table B-49 ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks (sourceTypelD 62)
in non-ACT states
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
0.2%
0.2%
0.2%
0.0%
0.0%
0.0%
2028
0.4%
0.4%
0.4%
0.0%
0.0%
0.0%
2029
0.7%
0.7%
0.7%
0.0%
0.0%
0.0%
2030
0.6%
3.7%
2.8%
0.4%
2.1%
1.6%
2031
1.2%
7.4%
5.6%
0.7%
4.3%
3.3%
2032
1.5%
15.8%
8.8%
0.9%
9.2%
5.1%
2033
1.6%
15.8%
8.8%
0.9%
9.2%
5.1%
2034
1.7%
15.8%
8.8%
1.0%
9.2%
5.1%
2035
1.7%
15.8%
8.8%
1.0%
9.2%
5.1%
2036
1.8%
15.8%
8.8%
1.1%
9.2%
5.1%
2037
1.9%
15.8%
8.8%
1.1%
9.2%
5.1%
2038
2.0%
15.8%
8.8%
1.2%
9.2%
5.1%
2039
2.1%
15.8%
8.8%
1.2%
9.2%
5.1%
2040
2.1%
15.8%
8.8%
1.2%
9.2%
5.1%
2041
2.2%
15.8%
8.8%
1.3%
9.2%
5.1%
2042
2.3%
15.8%
8.8%
1.3%
9.2%
5.1%
2043
2.4%
15.8%
8.8%
1.4%
9.2%
5.1%
2044
2.4%
15.8%
8.8%
1.4%
9.2%
5.1%
2045
2.5%
15.8%
8.8%
1.5%
9.2%
5.1%
2046
2.6%
15.8%
8.8%
1.5%
9.2%
5.1%
2047
2.7%
15.8%
8.8%
1.6%
9.2%
5.1%
2048
2.8%
15.8%
8.8%
1.6%
9.2%
5.1%
2049
2.8%
15.8%
8.8%
1.7%
9.2%
5.1%
2050
2.9%
15.8%
8.8%
1.7%
9.2%
5.1%
2051
3.0%
15.8%
8.8%
1.8%
9.2%
5.1%
2052
3.1%
15.8%
8.8%
1.8%
9.2%
5.1%
2053
3.2%
15.8%
8.8%
1.8%
9.2%
5.1%
2054
3.2%
15.8%
8.8%
1.9%
9.2%
5.1%
2055
3.3%
15.8%
8.8%
1.9%
9.2%
5.1%
875
-------
B.3 National ZEV Sales Percentages
Table B-50 National ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
13.4%
20.0%
16.7%
0%
0%
0%
2028
20.1%
25.2%
21.9%
0%
0%
0%
2029
26.8%
30.4%
27.1%
0%
0%
0%
2030
33.3%
35.6%
33.3%
0%
0%
0%
2031
36.6%
51.1%
37.5%
0%
0%
0%
2032
39.8%
66.7%
42.6%
0%
0%
0%
2033
43.5%
66.7%
43.5%
0%
0%
0%
2034
47.3%
66.7%
47.3%
0%
0%
0%
2035
51.2%
66.7%
51.2%
0%
0%
0%
2036
51.7%
66.7%
51.7%
0%
0%
0%
2037
52.2%
66.7%
52.2%
0%
0%
0%
2038
52.6%
66.7%
52.6%
0%
0%
0%
2039
53.1%
66.7%
53.1%
0%
0%
0%
2040
53.6%
66.7%
53.6%
0%
0%
0%
2041
54.1%
66.7%
54.1%
0%
0%
0%
2042
54.6%
66.7%
54.6%
0%
0%
0%
2043
55.1%
66.7%
55.1%
0%
0%
0%
2044
55.5%
66.7%
55.5%
0%
0%
0%
2045
55.9%
66.7%
55.9%
0%
0%
0%
2046
56.3%
66.7%
56.3%
0%
0%
0%
2047
56.8%
66.7%
56.8%
0%
0%
0%
2048
57.3%
66.7%
57.3%
0%
0%
0%
2049
57.7%
66.7%
57.7%
0%
0%
0%
2050
58.2%
66.7%
58.2%
0%
0%
0%
2051
58.6%
66.7%
58.6%
0%
0%
0%
2052
59.1%
66.7%
59.1%
0%
0%
0%
2053
59.6%
66.7%
59.6%
0%
0%
0%
2054
60.0%
66.7%
60.0%
0%
0%
0%
2055
60.5%
66.7%
60.5%
0%
0%
0%
876
-------
Table B-51 National ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
7.0%
14.0%
10.6%
0%
0%
0%
2028
10.6%
14.0%
11.3%
0%
0%
0%
2029
14.0%
14.0%
14.0%
0%
0%
0%
2030
17.5%
17.5%
17.5%
0%
0%
0%
2031
19.2%
19.2%
19.2%
0%
0%
0%
2032
20.9%
20.9%
20.9%
0%
0%
0%
2033
23.0%
23.0%
23.0%
0%
0%
0%
2034
25.3%
25.3%
25.3%
0%
0%
0%
2035
27.6%
27.6%
27.6%
0%
0%
0%
2036
28.1%
28.1%
28.1%
0%
0%
0%
2037
28.6%
28.6%
28.6%
0%
0%
0%
2038
29.1%
29.1%
29.1%
0%
0%
0%
2039
29.6%
29.6%
29.6%
0%
0%
0%
2040
30.1%
30.1%
30.1%
0%
0%
0%
2041
30.7%
30.7%
30.7%
0%
0%
0%
2042
31.2%
31.2%
31.2%
0%
0%
0%
2043
31.7%
31.7%
31.7%
0%
0%
0%
2044
32.2%
32.2%
32.2%
0%
0%
0%
2045
32.6%
32.6%
32.6%
0%
0%
0%
2046
33.1%
33.1%
33.1%
0%
0%
0%
2047
33.6%
33.6%
33.6%
0%
0%
0%
2048
34.1%
34.1%
34.1%
0%
0%
0%
2049
34.6%
34.6%
34.6%
0%
0%
0%
2050
35.1%
35.1%
35.1%
0%
0%
0%
2051
35.6%
35.6%
35.6%
0%
0%
0%
2052
36.1%
36.1%
36.1%
0%
0%
0%
2053
36.6%
36.6%
36.6%
0%
0%
0%
2054
37.1%
37.1%
37.1%
0%
0%
0%
2055
37.6%
37.6%
37.6%
0%
0%
0%
877
-------
Table B-52 National ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
6.0%
6.0%
6.0%
0.0%
0.0%
0.0%
2028
9.0%
9.0%
9.0%
0.0%
0.0%
0.0%
2029
12.0%
12.0%
12.0%
0.0%
0.0%
0.0%
2030
12.0%
12.0%
12.0%
2.9%
2.9%
2.9%
2031
12.0%
12.0%
12.0%
4.4%
4.4%
4.4%
2032
12.0%
12.0%
12.0%
5.9%
5.9%
5.9%
2033
12.1%
12.1%
12.1%
7.4%
7.4%
7.4%
2034
12.2%
12.2%
12.2%
8.9%
8.9%
8.9%
2035
12.2%
12.2%
12.2%
10.4%
10.4%
10.4%
2036
12.3%
12.3%
12.3%
10.5%
10.5%
10.5%
2037
12.4%
12.4%
12.4%
10.5%
10.5%
10.5%
2038
12.5%
12.5%
12.5%
10.5%
10.5%
10.5%
2039
12.5%
12.5%
12.5%
10.5%
10.5%
10.5%
2040
12.6%
12.6%
12.6%
10.6%
10.6%
10.6%
2041
12.7%
12.7%
12.7%
10.6%
10.6%
10.6%
2042
12.8%
12.8%
12.8%
10.7%
10.7%
10.7%
2043
12.8%
12.8%
12.8%
10.7%
10.7%
10.7%
2044
12.9%
12.9%
12.9%
10.7%
10.7%
10.7%
2045
13.0%
13.0%
13.0%
10.7%
10.7%
10.7%
2046
13.1%
13.1%
13.1%
10.7%
10.7%
10.7%
2047
13.1%
13.1%
13.1%
10.7%
10.7%
10.7%
2048
13.2%
13.2%
13.2%
10.8%
10.8%
10.8%
2049
13.3%
13.3%
13.3%
10.8%
10.8%
10.8%
2050
13.4%
13.4%
13.4%
10.8%
10.8%
10.8%
2051
13.4%
13.4%
13.4%
10.8%
10.8%
10.8%
2052
13.5%
13.5%
13.5%
10.9%
10.9%
10.9%
2053
13.6%
13.6%
13.6%
10.9%
10.9%
10.9%
2054
13.7%
13.7%
13.7%
10.9%
10.9%
10.9%
2055
13.7%
13.7%
13.7%
10.9%
10.9%
10.9%
878
-------
Table B-53 National ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
13.4%
20.0%
16.7%
0%
0%
0%
2028
20.1%
25.2%
21.9%
0%
0%
0%
2029
26.8%
30.4%
27.1%
0%
0%
0%
2030
33.3%
35.6%
33.3%
0%
0%
0%
2031
36.6%
51.1%
37.5%
0%
0%
0%
2032
39.8%
66.7%
42.6%
0%
0%
0%
2033
43.5%
66.7%
43.5%
0%
0%
0%
2034
47.3%
66.7%
47.3%
0%
0%
0%
2035
51.2%
66.7%
51.2%
0%
0%
0%
2036
51.7%
66.7%
51.7%
0%
0%
0%
2037
52.2%
66.7%
52.2%
0%
0%
0%
2038
52.6%
66.7%
52.6%
0%
0%
0%
2039
53.1%
66.7%
53.1%
0%
0%
0%
2040
53.6%
66.7%
53.6%
0%
0%
0%
2041
54.1%
66.7%
54.1%
0%
0%
0%
2042
54.6%
66.7%
54.6%
0%
0%
0%
2043
55.1%
66.7%
55.1%
0%
0%
0%
2044
55.5%
66.7%
55.5%
0%
0%
0%
2045
55.9%
66.7%
55.9%
0%
0%
0%
2046
56.3%
66.7%
56.3%
0%
0%
0%
2047
56.8%
66.7%
56.8%
0%
0%
0%
2048
57.3%
66.7%
57.3%
0%
0%
0%
2049
57.7%
66.7%
57.7%
0%
0%
0%
2050
58.2%
66.7%
58.2%
0%
0%
0%
2051
58.6%
66.7%
58.6%
0%
0%
0%
2052
59.1%
66.7%
59.1%
0%
0%
0%
2053
59.6%
66.7%
59.6%
0%
0%
0%
2054
60.0%
66.7%
60.0%
0%
0%
0%
2055
60.5%
66.7%
60.5%
0%
0%
0%
879
-------
Table B-54 National ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
7.0%
10.0%
7.6%
0%
0%
0%
2028
10.6%
11.4%
10.6%
0%
0%
0%
2029
14.0%
14.0%
14.0%
0%
0%
0%
2030
17.5%
17.5%
17.5%
0%
0%
0%
2031
19.2%
19.2%
19.2%
0%
0%
0%
2032
20.9%
22.3%
20.9%
0%
0%
0%
2033
23.0%
23.0%
23.0%
0%
0%
0%
2034
25.3%
25.3%
25.3%
0%
0%
0%
2035
27.6%
27.6%
27.6%
0%
0%
0%
2036
28.1%
28.1%
28.1%
0%
0%
0%
2037
28.6%
28.6%
28.6%
0%
0%
0%
2038
29.1%
29.1%
29.1%
0%
0%
0%
2039
29.6%
29.6%
29.6%
0%
0%
0%
2040
30.1%
30.1%
30.1%
0%
0%
0%
2041
30.7%
30.7%
30.7%
0%
0%
0%
2042
31.2%
31.2%
31.2%
0%
0%
0%
2043
31.7%
31.7%
31.7%
0%
0%
0%
2044
32.2%
32.2%
32.2%
0%
0%
0%
2045
32.6%
32.6%
32.6%
0%
0%
0%
2046
33.1%
33.1%
33.1%
0%
0%
0%
2047
33.6%
33.6%
33.6%
0%
0%
0%
2048
34.1%
34.1%
34.1%
0%
0%
0%
2049
34.6%
34.6%
34.6%
0%
0%
0%
2050
35.1%
35.1%
35.1%
0%
0%
0%
2051
35.6%
35.6%
35.6%
0%
0%
0%
2052
36.1%
36.1%
36.1%
0%
0%
0%
2053
36.6%
36.6%
36.6%
0%
0%
0%
2054
37.1%
37.1%
37.1%
0%
0%
0%
2055
37.6%
37.6%
37.6%
0%
0%
0%
880
-------
Table B-55 National ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
6.0%
6.0%
6.0%
0%
0%
0%
2028
9.0%
14.0%
9.7%
0%
0%
0%
2029
12.0%
17.1%
12.9%
0%
0%
0%
2030
15.0%
20.2%
16.0%
0%
0%
0%
2031
16.4%
29.6%
19.0%
0%
0%
0%
2032
17.9%
39.0%
22.1%
0%
0%
0%
2033
19.5%
39.0%
22.1%
0%
0%
0%
2034
21.1%
39.0%
22.1%
0%
0%
0%
2035
22.7%
39.0%
22.7%
0%
0%
0%
2036
22.8%
39.0%
22.8%
0%
0%
0%
2037
22.9%
39.0%
22.9%
0%
0%
0%
2038
23.0%
39.0%
23.0%
0%
0%
0%
2039
23.1%
39.0%
23.1%
0%
0%
0%
2040
23.2%
39.0%
23.2%
0%
0%
0%
2041
23.3%
39.0%
23.3%
0%
0%
0%
2042
23.4%
39.0%
23.4%
0%
0%
0%
2043
23.5%
39.0%
23.5%
0%
0%
0%
2044
23.6%
39.0%
23.6%
0%
0%
0%
2045
23.7%
39.0%
23.7%
0%
0%
0%
2046
23.8%
39.0%
23.8%
0%
0%
0%
2047
23.9%
39.0%
23.9%
0%
0%
0%
2048
24.0%
39.0%
24.0%
0%
0%
0%
2049
24.1%
39.0%
24.1%
0%
0%
0%
2050
24.2%
39.0%
24.2%
0%
0%
0%
2051
24.3%
39.0%
24.3%
0%
0%
0%
2052
24.4%
39.0%
24.4%
0%
0%
0%
2053
24.5%
39.0%
24.5%
0%
0%
0%
2054
24.6%
39.0%
24.6%
0%
0%
0%
2055
24.7%
39.0%
24.7%
0%
0%
0%
881
-------
Table B-56 National ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
11.7%
20.0%
16.7%
0%
0%
0%
2028
17.5%
25.2%
21.9%
0%
0%
0%
2029
23.3%
30.4%
27.1%
0%
0%
0%
2030
29.0%
35.6%
32.3%
0%
0%
0%
2031
31.8%
51.1%
37.5%
0%
0%
0%
2032
34.7%
66.7%
42.6%
0%
0%
0%
2033
38.0%
66.7%
42.6%
0%
0%
0%
2034
41.5%
66.7%
42.6%
0%
0%
0%
2035
45.0%
66.7%
45.0%
0%
0%
0%
2036
45.6%
66.7%
45.6%
0%
0%
0%
2037
46.1%
66.7%
46.1%
0%
0%
0%
2038
46.7%
66.7%
46.7%
0%
0%
0%
2039
47.3%
66.7%
47.3%
0%
0%
0%
2040
47.8%
66.7%
47.8%
0%
0%
0%
2041
48.4%
66.7%
48.4%
0%
0%
0%
2042
49.0%
66.7%
49.0%
0%
0%
0%
2043
49.6%
66.7%
49.6%
0%
0%
0%
2044
50.1%
66.7%
50.1%
0%
0%
0%
2045
50.6%
66.7%
50.6%
0%
0%
0%
2046
51.1%
66.7%
51.1%
0%
0%
0%
2047
51.6%
66.7%
51.6%
0%
0%
0%
2048
52.2%
66.7%
52.2%
0%
0%
0%
2049
52.8%
66.7%
52.8%
0%
0%
0%
2050
53.3%
66.7%
53.3%
0%
0%
0%
2051
53.8%
66.7%
53.8%
0%
0%
0%
2052
54.4%
66.7%
54.4%
0%
0%
0%
2053
54.9%
66.7%
54.9%
0%
0%
0%
2054
55.5%
66.7%
55.5%
0%
0%
0%
2055
56.0%
66.7%
56.0%
0%
0%
0%
882
-------
Table B-57 National ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
6.6%
20.0%
15.2%
0%
0%
0%
2028
9.9%
25.6%
20.5%
0%
0%
0%
2029
13.1%
31.1%
26.0%
0%
0%
0%
2030
16.4%
36.7%
31.4%
0%
0%
0%
2031
17.9%
53.3%
37.7%
0%
0%
0%
2032
19.5%
70.0%
43.6%
0%
0%
0%
2033
21.6%
70.0%
43.6%
0%
0%
0%
2034
23.7%
70.0%
43.6%
0%
0%
0%
2035
26.0%
70.0%
43.6%
0%
0%
0%
2036
26.5%
70.0%
43.6%
0%
0%
0%
2037
27.0%
70.0%
43.6%
0%
0%
0%
2038
27.6%
70.0%
43.6%
0%
0%
0%
2039
28.1%
70.0%
43.6%
0%
0%
0%
2040
28.6%
70.0%
43.6%
0%
0%
0%
2041
29.2%
70.0%
43.6%
0%
0%
0%
2042
29.7%
70.0%
43.6%
0%
0%
0%
2043
30.3%
70.0%
43.6%
0%
0%
0%
2044
30.8%
70.0%
43.6%
0%
0%
0%
2045
31.3%
70.0%
43.6%
0%
0%
0%
2046
31.8%
70.0%
43.6%
0%
0%
0%
2047
32.3%
70.0%
43.6%
0%
0%
0%
2048
32.8%
70.0%
43.6%
0%
0%
0%
2049
33.3%
70.0%
43.6%
0%
0%
0%
2050
33.8%
70.0%
43.6%
0%
0%
0%
2051
34.3%
70.0%
43.6%
0%
0%
0%
2052
34.9%
70.0%
43.6%
0%
0%
0%
2053
35.4%
70.0%
43.6%
0%
0%
0%
2054
35.9%
70.0%
43.6%
0%
0%
0%
2055
36.4%
70.0%
43.6%
0%
0%
0%
883
-------
Table B-58 National ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
5.6%
5.6%
5.6%
0%
0%
0%
2028
8.3%
17.0%
11.8%
0%
0%
0%
2029
11.1%
19.8%
14.9%
0%
0%
0%
2030
13.8%
22.5%
17.8%
0%
0%
0%
2031
15.1%
30.8%
19.7%
0%
0%
0%
2032
16.5%
39.0%
22.1%
0%
0%
0%
2033
17.9%
39.0%
22.1%
0%
0%
0%
2034
19.4%
39.0%
22.1%
0%
0%
0%
2035
20.9%
39.0%
22.1%
0%
0%
0%
2036
21.1%
39.0%
22.1%
0%
0%
0%
2037
21.2%
39.0%
22.1%
0%
0%
0%
2038
21.3%
39.0%
22.1%
0%
0%
0%
2039
21.4%
39.0%
22.1%
0%
0%
0%
2040
21.5%
39.0%
22.1%
0%
0%
0%
2041
21.6%
39.0%
22.1%
0%
0%
0%
2042
21.8%
39.0%
22.1%
0%
0%
0%
2043
21.9%
39.0%
22.1%
0%
0%
0%
2044
22.0%
39.0%
22.1%
0%
0%
0%
2045
22.1%
39.0%
22.1%
0%
0%
0%
2046
22.2%
39.0%
22.2%
0%
0%
0%
2047
22.3%
39.0%
22.3%
0%
0%
0%
2048
22.4%
39.0%
22.4%
0%
0%
0%
2049
22.5%
39.0%
22.5%
0%
0%
0%
2050
22.6%
39.0%
22.6%
0%
0%
0%
2051
22.7%
39.0%
22.7%
0%
0%
0%
2052
22.8%
39.0%
22.8%
0%
0%
0%
2053
23.0%
39.0%
23.0%
0%
0%
0%
2054
23.1%
39.0%
23.1%
0%
0%
0%
2055
23.2%
39.0%
23.2%
0%
0%
0%
884
-------
Table B-59 National ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
7.3%
20.0%
15.2%
0%
0%
0%
2028
11.0%
22.1%
17.8%
0%
0%
0%
2029
14.6%
24.2%
20.2%
0%
0%
0%
2030
18.2%
26.3%
22.6%
0%
0%
0%
2031
20.0%
32.7%
23.1%
0%
0%
0%
2032
21.8%
39.0%
24.3%
0%
0%
0%
2033
23.9%
39.0%
24.3%
0%
0%
0%
2034
26.3%
39.0%
26.3%
0%
0%
0%
2035
28.7%
39.0%
28.7%
0%
0%
0%
2036
29.2%
39.0%
29.2%
0%
0%
0%
2037
29.7%
39.0%
29.7%
0%
0%
0%
2038
30.1%
39.0%
30.1%
0%
0%
0%
2039
30.6%
39.0%
30.6%
0%
0%
0%
2040
31.1%
39.0%
31.1%
0%
0%
0%
2041
31.6%
39.0%
31.6%
0%
0%
0%
2042
32.1%
39.0%
32.1%
0%
0%
0%
2043
32.6%
39.0%
32.6%
0%
0%
0%
2044
33.1%
39.0%
33.1%
0%
0%
0%
2045
33.6%
39.0%
33.6%
0%
0%
0%
2046
34.0%
39.0%
34.0%
0%
0%
0%
2047
34.5%
39.0%
34.5%
0%
0%
0%
2048
35.0%
39.0%
35.0%
0%
0%
0%
2049
35.5%
39.0%
35.5%
0%
0%
0%
2050
36.0%
39.0%
36.0%
0%
0%
0%
2051
36.4%
39.0%
36.4%
0%
0%
0%
2052
36.9%
39.0%
36.9%
0%
0%
0%
2053
37.4%
39.0%
37.4%
0%
0%
0%
2054
37.9%
39.0%
37.9%
0%
0%
0%
2055
38.3%
39.0%
38.3%
0%
0%
0%
885
-------
Table B-60 National ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.5%
3.5%
3.5%
0%
0%
0%
2028
5.3%
14.0%
9.7%
0%
0%
0%
2029
7.0%
17.1%
12.9%
0%
0%
0%
2030
8.7%
20.2%
16.0%
0%
0%
0%
2031
9.6%
29.6%
19.0%
0%
0%
0%
2032
10.4%
39.0%
22.1%
0%
0%
0%
2033
11.4%
39.0%
22.1%
0%
0%
0%
2034
12.4%
39.0%
22.1%
0%
0%
0%
2035
13.5%
39.0%
22.1%
0%
0%
0%
2036
13.7%
39.0%
22.1%
0%
0%
0%
2037
13.8%
39.0%
22.1%
0%
0%
0%
2038
14.0%
39.0%
22.1%
0%
0%
0%
2039
14.2%
39.0%
22.1%
0%
0%
0%
2040
14.3%
39.0%
22.1%
0%
0%
0%
2041
14.5%
39.0%
22.1%
0%
0%
0%
2042
14.7%
39.0%
22.1%
0%
0%
0%
2043
14.9%
39.0%
22.1%
0%
0%
0%
2044
15.0%
39.0%
22.1%
0%
0%
0%
2045
15.2%
39.0%
22.1%
0%
0%
0%
2046
15.3%
39.0%
22.1%
0%
0%
0%
2047
15.5%
39.0%
22.1%
0%
0%
0%
2048
15.7%
39.0%
22.1%
0%
0%
0%
2049
15.8%
39.0%
22.1%
0%
0%
0%
2050
16.0%
39.0%
22.1%
0%
0%
0%
2051
16.1%
39.0%
22.1%
0%
0%
0%
2052
16.3%
39.0%
22.1%
0%
0%
0%
2053
16.5%
39.0%
22.1%
0%
0%
0%
2054
16.6%
39.0%
22.1%
0%
0%
0%
2055
16.8%
39.0%
22.1%
0%
0%
0%
886
-------
Table B-61 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks
(sourceTypelD 52)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
9.9%
20.0%
16.7%
0%
0%
0%
2028
14.8%
25.2%
21.9%
0%
0%
0%
2029
19.7%
30.4%
27.1%
0%
0%
0%
2030
24.5%
35.6%
32.3%
0%
0%
0%
2031
26.9%
51.1%
37.5%
0%
0%
0%
2032
29.3%
66.7%
42.6%
0%
0%
0%
2033
32.2%
66.7%
42.6%
0%
0%
0%
2034
35.3%
66.7%
42.6%
0%
0%
0%
2035
38.5%
66.7%
42.6%
0%
0%
0%
2036
39.2%
66.7%
42.6%
0%
0%
0%
2037
39.8%
66.7%
42.6%
0%
0%
0%
2038
40.5%
66.7%
42.6%
0%
0%
0%
2039
41.1%
66.7%
42.6%
0%
0%
0%
2040
41.8%
66.7%
42.6%
0%
0%
0%
2041
42.5%
66.7%
42.6%
0%
0%
0%
2042
43.1%
66.7%
43.1%
0%
0%
0%
2043
43.8%
66.7%
43.8%
0%
0%
0%
2044
44.4%
66.7%
44.4%
0%
0%
0%
2045
45.0%
66.7%
45.0%
0%
0%
0%
2046
45.6%
66.7%
45.6%
0%
0%
0%
2047
46.2%
66.7%
46.2%
0%
0%
0%
2048
46.9%
66.7%
46.9%
0%
0%
0%
2049
47.5%
66.7%
47.5%
0%
0%
0%
2050
48.2%
66.7%
48.2%
0%
0%
0%
2051
48.8%
66.7%
48.8%
0%
0%
0%
2052
49.4%
66.7%
49.4%
0%
0%
0%
2053
50.1%
66.7%
50.1%
0%
0%
0%
2054
50.7%
66.7%
50.7%
0%
0%
0%
2055
51.3%
66.7%
51.3%
0%
0%
0%
887
-------
Table B-62 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks
(sourceTypelD 52)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
6.9%
12.3%
9.4%
0%
0%
0%
2028
10.4%
14.8%
11.9%
0%
0%
0%
2029
13.8%
17.3%
14.4%
0%
0%
0%
2030
17.2%
19.8%
17.2%
0%
0%
0%
2031
18.9%
27.2%
19.2%
0%
0%
0%
2032
20.6%
34.6%
21.6%
0%
0%
0%
2033
22.7%
34.6%
22.7%
0%
0%
0%
2034
24.9%
34.6%
24.9%
0%
0%
0%
2035
27.2%
34.6%
27.2%
0%
0%
0%
2036
27.7%
34.6%
27.7%
0%
0%
0%
2037
28.3%
34.6%
28.3%
0%
0%
0%
2038
28.8%
34.6%
28.8%
0%
0%
0%
2039
29.3%
34.6%
29.3%
0%
0%
0%
2040
29.8%
34.6%
29.8%
0%
0%
0%
2041
30.3%
34.6%
30.3%
0%
0%
0%
2042
30.8%
34.6%
30.8%
0%
0%
0%
2043
31.4%
34.6%
31.4%
0%
0%
0%
2044
31.9%
34.6%
31.9%
0%
0%
0%
2045
32.3%
34.6%
32.3%
0%
0%
0%
2046
32.8%
34.6%
32.8%
0%
0%
0%
2047
33.3%
34.6%
33.3%
0%
0%
0%
2048
33.8%
34.6%
33.8%
0%
0%
0%
2049
34.3%
34.6%
34.3%
0%
0%
0%
2050
34.8%
34.8%
34.8%
0%
0%
0%
2051
35.3%
35.3%
35.3%
0%
0%
0%
2052
35.8%
35.8%
35.8%
0%
0%
0%
2053
36.3%
36.3%
36.3%
0%
0%
0%
2054
36.8%
36.8%
36.8%
0%
0%
0%
2055
37.3%
37.3%
37.3%
0%
0%
0%
888
-------
Table B-63 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks
(sourceTypelD 52)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.1%
4.1%
4.1%
0%
0%
0%
2028
6.2%
9.2%
6.4%
0%
0%
0%
2029
8.3%
11.6%
8.7%
0%
0%
0%
2030
10.3%
13.9%
11.0%
0%
0%
0%
2031
11.3%
20.9%
13.4%
0%
0%
0%
2032
12.3%
27.9%
15.7%
0%
0%
0%
2033
13.4%
27.9%
15.7%
0%
0%
0%
2034
14.6%
27.9%
15.7%
0%
0%
0%
2035
15.8%
27.9%
15.8%
0%
0%
0%
2036
16.0%
27.9%
16.0%
0%
0%
0%
2037
16.1%
27.9%
16.1%
0%
0%
0%
2038
16.3%
27.9%
16.3%
0%
0%
0%
2039
16.4%
27.9%
16.4%
0%
0%
0%
2040
16.6%
27.9%
16.6%
0%
0%
0%
2041
16.7%
27.9%
16.7%
0%
0%
0%
2042
16.9%
27.9%
16.9%
0%
0%
0%
2043
17.1%
27.9%
17.1%
0%
0%
0%
2044
17.2%
27.9%
17.2%
0%
0%
0%
2045
17.3%
27.9%
17.3%
0%
0%
0%
2046
17.5%
27.9%
17.5%
0%
0%
0%
2047
17.6%
27.9%
17.6%
0%
0%
0%
2048
17.8%
27.9%
17.8%
0%
0%
0%
2049
17.9%
27.9%
17.9%
0%
0%
0%
2050
18.1%
27.9%
18.1%
0%
0%
0%
2051
18.2%
27.9%
18.2%
0%
0%
0%
2052
18.3%
27.9%
18.3%
0%
0%
0%
2053
18.5%
27.9%
18.5%
0%
0%
0%
2054
18.6%
27.9%
18.6%
0%
0%
0%
2055
18.8%
27.9%
18.8%
0%
0%
0%
889
-------
Table B-64 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks
(sourceTypelD 53)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
9.9%
10.0%
9.9%
0%
0%
0%
2028
14.8%
14.8%
14.8%
0%
0%
0%
2029
19.7%
19.7%
19.7%
0%
0%
0%
2030
24.5%
24.5%
24.5%
0%
0%
0%
2031
26.9%
30.0%
26.9%
0%
0%
0%
2032
29.3%
40.0%
29.3%
0%
0%
0%
2033
32.2%
40.0%
32.2%
0%
0%
0%
2034
35.3%
40.0%
35.3%
0%
0%
0%
2035
38.5%
40.0%
38.5%
0%
0%
0%
2036
39.2%
40.0%
39.2%
0%
0%
0%
2037
39.8%
40.0%
39.8%
0%
0%
0%
2038
40.5%
40.5%
40.5%
0%
0%
0%
2039
41.1%
41.1%
41.1%
0%
0%
0%
2040
41.8%
41.8%
41.8%
0%
0%
0%
2041
42.5%
42.5%
42.5%
0%
0%
0%
2042
43.1%
43.1%
43.1%
0%
0%
0%
2043
43.8%
43.8%
43.8%
0%
0%
0%
2044
44.4%
44.4%
44.4%
0%
0%
0%
2045
45.0%
45.0%
45.0%
0%
0%
0%
2046
45.6%
45.6%
45.6%
0%
0%
0%
2047
46.2%
46.2%
46.2%
0%
0%
0%
2048
46.9%
46.9%
46.9%
0%
0%
0%
2049
47.5%
47.5%
47.5%
0%
0%
0%
2050
48.2%
48.2%
48.2%
0%
0%
0%
2051
48.8%
48.8%
48.8%
0%
0%
0%
2052
49.4%
49.4%
49.4%
0%
0%
0%
2053
50.1%
50.1%
50.1%
0%
0%
0%
2054
50.7%
50.7%
50.7%
0%
0%
0%
2055
51.3%
51.3%
51.3%
0%
0%
0%
890
-------
Table B-65 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks
(sourceTypelD 53)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
6.9%
14.0%
10.6%
0%
0%
0%
2028
10.4%
16.8%
13.5%
0%
0%
0%
2029
13.8%
19.6%
16.3%
0%
0%
0%
2030
17.2%
22.3%
19.1%
0%
0%
0%
2031
18.9%
30.7%
21.7%
0%
0%
0%
2032
20.6%
39.0%
24.3%
0%
0%
0%
2033
22.7%
39.0%
24.3%
0%
0%
0%
2034
24.9%
39.0%
24.9%
0%
0%
0%
2035
27.2%
39.0%
27.2%
0%
0%
0%
2036
27.7%
39.0%
27.7%
0%
0%
0%
2037
28.3%
39.0%
28.3%
0%
0%
0%
2038
28.8%
39.0%
28.8%
0%
0%
0%
2039
29.3%
39.0%
29.3%
0%
0%
0%
2040
29.8%
39.0%
29.8%
0%
0%
0%
2041
30.3%
39.0%
30.3%
0%
0%
0%
2042
30.8%
39.0%
30.8%
0%
0%
0%
2043
31.4%
39.0%
31.4%
0%
0%
0%
2044
31.9%
39.0%
31.9%
0%
0%
0%
2045
32.3%
39.0%
32.3%
0%
0%
0%
2046
32.8%
39.0%
32.8%
0%
0%
0%
2047
33.3%
39.0%
33.3%
0%
0%
0%
2048
33.8%
39.0%
33.8%
0%
0%
0%
2049
34.3%
39.0%
34.3%
0%
0%
0%
2050
34.8%
39.0%
34.8%
0%
0%
0%
2051
35.3%
39.0%
35.3%
0%
0%
0%
2052
35.8%
39.0%
35.8%
0%
0%
0%
2053
36.3%
39.0%
36.3%
0%
0%
0%
2054
36.8%
39.0%
36.8%
0%
0%
0%
2055
37.3%
39.0%
37.3%
0%
0%
0%
891
-------
Table B-66 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks
(sourceTypelD 53)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.1%
4.1%
4.1%
0%
0%
0%
2028
6.2%
6.2%
6.2%
0%
0%
0%
2029
8.3%
9.3%
8.3%
0%
0%
0%
2030
10.3%
13.5%
10.7%
0%
0%
0%
2031
11.3%
26.3%
16.8%
0%
0%
0%
2032
12.3%
39.0%
22.1%
0%
0%
0%
2033
13.4%
39.0%
22.1%
0%
0%
0%
2034
14.6%
39.0%
22.1%
0%
0%
0%
2035
15.8%
39.0%
22.1%
0%
0%
0%
2036
16.0%
39.0%
22.1%
0%
0%
0%
2037
16.1%
39.0%
22.1%
0%
0%
0%
2038
16.3%
39.0%
22.1%
0%
0%
0%
2039
16.4%
39.0%
22.1%
0%
0%
0%
2040
16.6%
39.0%
22.1%
0%
0%
0%
2041
16.7%
39.0%
22.1%
0%
0%
0%
2042
16.9%
39.0%
22.1%
0%
0%
0%
2043
17.1%
39.0%
22.1%
0%
0%
0%
2044
17.2%
39.0%
22.1%
0%
0%
0%
2045
17.3%
39.0%
22.1%
0%
0%
0%
2046
17.5%
39.0%
22.1%
0%
0%
0%
2047
17.6%
39.0%
22.1%
0%
0%
0%
2048
17.8%
39.0%
22.1%
0%
0%
0%
2049
17.9%
39.0%
22.1%
0%
0%
0%
2050
18.1%
39.0%
22.1%
0%
0%
0%
2051
18.2%
39.0%
22.1%
0%
0%
0%
2052
18.3%
39.0%
22.1%
0%
0%
0%
2053
18.5%
39.0%
22.1%
0%
0%
0%
2054
18.6%
39.0%
22.1%
0%
0%
0%
2055
18.8%
39.0%
22.1%
0%
0%
0%
892
-------
Table B-67 National ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
10.7%
10.7%
10.7%
0%
0%
0%
2028
16.1%
16.1%
16.1%
0%
0%
0%
2029
21.4%
21.4%
21.4%
0%
0%
0%
2030
26.7%
26.7%
26.7%
0%
0%
0%
2031
29.3%
29.3%
29.3%
0%
0%
0%
2032
31.9%
31.9%
31.9%
0%
0%
0%
2033
35.0%
35.0%
35.0%
0%
0%
0%
2034
38.3%
38.3%
38.3%
0%
0%
0%
2035
41.6%
41.6%
41.6%
0%
0%
0%
2036
42.2%
42.2%
42.2%
0%
0%
0%
2037
42.9%
42.9%
42.9%
0%
0%
0%
2038
43.5%
43.5%
43.5%
0%
0%
0%
2039
44.1%
44.1%
44.1%
0%
0%
0%
2040
44.7%
44.7%
44.7%
0%
0%
0%
2041
45.3%
45.3%
45.3%
0%
0%
0%
2042
45.9%
45.9%
45.9%
0%
0%
0%
2043
46.6%
46.6%
46.6%
0%
0%
0%
2044
47.2%
47.2%
47.2%
0%
0%
0%
2045
47.7%
47.7%
47.7%
0%
0%
0%
2046
48.2%
48.2%
48.2%
0%
0%
0%
2047
48.8%
48.8%
48.8%
0%
0%
0%
2048
49.5%
49.5%
49.5%
0%
0%
0%
2049
50.0%
50.0%
50.0%
0%
0%
0%
2050
50.6%
50.6%
50.6%
0%
0%
0%
2051
51.2%
51.2%
51.2%
0%
0%
0%
2052
51.8%
51.8%
51.8%
0%
0%
0%
2053
52.4%
52.4%
52.4%
0%
0%
0%
2054
53.0%
53.0%
53.0%
0%
0%
0%
2055
53.6%
53.6%
53.6%
0%
0%
0%
893
-------
Table B-68 National ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
7.5%
7.5%
7.5%
0%
0%
0%
2028
11.2%
11.2%
11.2%
0%
0%
0%
2029
14.9%
14.9%
14.9%
0%
0%
0%
2030
18.6%
18.6%
18.6%
0%
0%
0%
2031
20.4%
20.4%
20.4%
0%
0%
0%
2032
22.2%
22.2%
22.2%
0%
0%
0%
2033
24.4%
24.4%
24.4%
0%
0%
0%
2034
26.7%
26.7%
26.7%
0%
0%
0%
2035
29.2%
29.2%
29.2%
0%
0%
0%
2036
29.7%
29.7%
29.7%
0%
0%
0%
2037
30.1%
30.1%
30.1%
0%
0%
0%
2038
30.6%
30.6%
30.6%
0%
0%
0%
2039
31.1%
31.1%
31.1%
0%
0%
0%
2040
31.6%
31.6%
31.6%
0%
0%
0%
2041
32.1%
32.1%
32.1%
0%
0%
0%
2042
32.6%
32.6%
32.6%
0%
0%
0%
2043
33.1%
33.1%
33.1%
0%
0%
0%
2044
33.6%
33.6%
33.6%
0%
0%
0%
2045
34.0%
34.0%
34.0%
0%
0%
0%
2046
34.4%
34.4%
34.4%
0%
0%
0%
2047
34.9%
34.9%
34.9%
0%
0%
0%
2048
35.4%
35.4%
35.4%
0%
0%
0%
2049
35.9%
35.9%
35.9%
0%
0%
0%
2050
36.4%
36.4%
36.4%
0%
0%
0%
2051
36.8%
36.8%
36.8%
0%
0%
0%
2052
37.3%
37.3%
37.3%
0%
0%
0%
2053
37.8%
37.8%
37.8%
0%
0%
0%
2054
38.2%
38.2%
38.2%
0%
0%
0%
2055
38.7%
38.7%
38.7%
0%
0%
0%
894
-------
Table B-69 National ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
3.5%
3.5%
3.5%
0%
0%
0%
2028
5.2%
5.2%
5.2%
0%
0%
0%
2029
7.0%
7.0%
7.0%
0%
0%
0%
2030
8.7%
8.7%
8.7%
0%
0%
0%
2031
9.5%
9.5%
9.5%
0%
0%
0%
2032
10.4%
10.4%
10.4%
0%
0%
0%
2033
11.4%
11.4%
11.4%
0%
0%
0%
2034
12.4%
12.4%
12.4%
0%
0%
0%
2035
13.5%
13.5%
13.5%
0%
0%
0%
2036
13.6%
13.6%
13.6%
0%
0%
0%
2037
13.8%
13.8%
13.8%
0%
0%
0%
2038
14.0%
14.0%
14.0%
0%
0%
0%
2039
14.1%
14.1%
14.1%
0%
0%
0%
2040
14.3%
14.3%
14.3%
0%
0%
0%
2041
14.5%
14.5%
14.5%
0%
0%
0%
2042
14.6%
14.6%
14.6%
0%
0%
0%
2043
14.8%
14.8%
14.8%
0%
0%
0%
2044
15.0%
15.0%
15.0%
0%
0%
0%
2045
15.1%
15.1%
15.1%
0%
0%
0%
2046
15.3%
15.3%
15.3%
0%
0%
0%
2047
15.4%
15.4%
15.4%
0%
0%
0%
2048
15.6%
15.6%
15.6%
0%
0%
0%
2049
15.8%
15.8%
15.8%
0%
0%
0%
2050
15.9%
15.9%
15.9%
0%
0%
0%
2051
16.1%
16.1%
16.1%
0%
0%
0%
2052
16.2%
16.2%
16.2%
0%
0%
0%
2053
16.4%
16.4%
16.4%
0%
0%
0%
2054
16.6%
16.6%
16.6%
0%
0%
0%
2055
16.7%
16.7%
16.7%
0%
0%
0%
895
-------
Table B-70 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks
(sourceTypelD 61)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
5.1%
7.0%
5.1%
0.0%
0.0%
0.0%
2028
6.6%
8.6%
6.7%
0.0%
0.0%
0.0%
2029
8.1%
10.2%
8.6%
0.0%
0.0%
0.0%
2030
7.1%
10.2%
8.5%
2.4%
3.4%
2.8%
2031
7.5%
15.1%
9.3%
2.5%
5.1%
3.1%
2032
8.4%
21.4%
11.0%
2.8%
7.2%
3.7%
2033
8.6%
21.4%
11.0%
2.9%
7.2%
3.7%
2034
8.7%
21.4%
11.0%
2.9%
7.2%
3.7%
2035
8.8%
21.4%
11.0%
3.0%
7.2%
3.7%
2036
9.0%
21.4%
11.0%
3.0%
7.2%
3.7%
2037
9.1%
21.4%
11.0%
3.1%
7.2%
3.7%
2038
9.3%
21.4%
11.0%
3.1%
7.2%
3.7%
2039
9.4%
21.4%
11.0%
3.2%
7.2%
3.7%
2040
9.6%
21.4%
11.0%
3.2%
7.2%
3.7%
2041
9.7%
21.4%
11.0%
3.3%
7.2%
3.7%
2042
9.9%
21.4%
11.0%
3.3%
7.2%
3.7%
2043
10.0%
21.4%
11.0%
3.4%
7.2%
3.7%
2044
10.2%
21.4%
11.0%
3.4%
7.2%
3.7%
2045
10.3%
21.4%
11.0%
3.5%
7.2%
3.7%
2046
10.5%
21.4%
11.0%
3.5%
7.2%
3.7%
2047
10.6%
21.4%
11.0%
3.6%
7.2%
3.7%
2048
10.8%
21.4%
11.0%
3.6%
7.2%
3.7%
2049
10.9%
21.4%
11.0%
3.7%
7.2%
3.7%
2050
11.1%
21.4%
11.1%
3.7%
7.2%
3.7%
2051
11.2%
21.4%
11.2%
3.8%
7.2%
3.8%
2052
11.4%
21.4%
11.4%
3.8%
7.2%
3.8%
2053
11.5%
21.4%
11.5%
3.9%
7.2%
3.9%
2054
11.7%
21.4%
11.7%
3.9%
7.2%
3.9%
2055
11.8%
21.4%
11.8%
4.0%
7.2%
4.0%
896
-------
Table B-71 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks
(sourceTypelD 61)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
4.5%
4.5%
4.5%
0.0%
0.0%
0.0%
2028
5.9%
8.3%
6.5%
0.0%
0.0%
0.0%
2029
7.1%
12.7%
10.7%
0.0%
0.0%
0.0%
2030
8.1%
16.9%
14.0%
0.3%
0.7%
0.6%
2031
8.6%
30.0%
18.4%
0.3%
1.2%
0.7%
2032
9.6%
43.5%
22.4%
0.4%
1.7%
0.9%
2033
9.7%
43.5%
22.4%
0.4%
1.7%
0.9%
2034
9.9%
43.5%
22.4%
0.4%
1.7%
0.9%
2035
10.1%
43.5%
22.4%
0.4%
1.7%
0.9%
2036
10.3%
43.5%
22.4%
0.4%
1.7%
0.9%
2037
10.5%
43.5%
22.4%
0.4%
1.7%
0.9%
2038
10.7%
43.5%
22.4%
0.4%
1.7%
0.9%
2039
10.9%
43.5%
22.4%
0.4%
1.7%
0.9%
2040
11.1%
43.5%
22.4%
0.4%
1.7%
0.9%
2041
11.3%
43.5%
22.4%
0.5%
1.7%
0.9%
2042
11.5%
43.5%
22.4%
0.5%
1.7%
0.9%
2043
11.7%
43.5%
22.4%
0.5%
1.7%
0.9%
2044
11.9%
43.5%
22.4%
0.5%
1.7%
0.9%
2045
12.1%
43.5%
22.4%
0.5%
1.7%
0.9%
2046
12.3%
43.5%
22.4%
0.5%
1.7%
0.9%
2047
12.5%
43.5%
22.4%
0.5%
1.7%
0.9%
2048
12.7%
43.5%
22.4%
0.5%
1.7%
0.9%
2049
12.9%
43.5%
22.4%
0.5%
1.7%
0.9%
2050
13.1%
43.5%
22.4%
0.5%
1.7%
0.9%
2051
13.3%
43.5%
22.4%
0.5%
1.7%
0.9%
2052
13.5%
43.5%
22.4%
0.5%
1.7%
0.9%
2053
13.7%
43.5%
22.4%
0.5%
1.7%
0.9%
2054
13.9%
43.5%
22.4%
0.6%
1.7%
0.9%
2055
14.1%
43.5%
22.4%
0.6%
1.7%
0.9%
897
-------
Table B-72 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks
(sourceTypelD 62)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
0.4%
0.4%
0.4%
0.0%
0.0%
0.0%
2028
0.8%
0.8%
0.8%
0.0%
0.0%
0.0%
2029
1.4%
1.4%
1.4%
0.0%
0.0%
0.0%
2030
1.3%
3.9%
3.2%
0.8%
2.3%
1.8%
2031
2.6%
7.9%
6.3%
1.5%
4.6%
3.7%
2032
3.2%
15.8%
9.5%
1.9%
9.2%
5.5%
2033
3.3%
15.8%
9.5%
1.9%
9.2%
5.5%
2034
3.4%
15.8%
9.5%
2.0%
9.2%
5.5%
2035
3.4%
15.8%
9.5%
2.0%
9.2%
5.5%
2036
3.5%
15.8%
9.5%
2.0%
9.2%
5.5%
2037
3.6%
15.8%
9.5%
2.1%
9.2%
5.5%
2038
3.6%
15.8%
9.5%
2.1%
9.2%
5.5%
2039
3.7%
15.8%
9.5%
2.2%
9.2%
5.5%
2040
3.8%
15.8%
9.5%
2.2%
9.2%
5.5%
2041
3.8%
15.8%
9.5%
2.2%
9.2%
5.5%
2042
3.9%
15.8%
9.5%
2.3%
9.2%
5.5%
2043
4.0%
15.8%
9.5%
2.3%
9.2%
5.5%
2044
4.0%
15.8%
9.5%
2.4%
9.2%
5.5%
2045
4.1%
15.8%
9.5%
2.4%
9.2%
5.5%
2046
4.2%
15.8%
9.5%
2.4%
9.2%
5.5%
2047
4.3%
15.8%
9.5%
2.5%
9.2%
5.5%
2048
4.3%
15.8%
9.5%
2.5%
9.2%
5.5%
2049
4.4%
15.8%
9.5%
2.6%
9.2%
5.5%
2050
4.5%
15.8%
9.5%
2.6%
9.2%
5.5%
2051
4.5%
15.8%
9.5%
2.6%
9.2%
5.5%
2052
4.6%
15.8%
9.5%
2.7%
9.2%
5.5%
2053
4.7%
15.8%
9.5%
2.7%
9.2%
5.5%
2054
4.7%
15.8%
9.5%
2.8%
9.2%
5.5%
2055
4.8%
15.8%
9.5%
2.8%
9.2%
5.5%
898
-------
Table B-73 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks
(sourceTypelD 62)
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Reference
Final
Standards
Alternative
Reference
Final
Standards
Alternative
2027
0.4%
0.4%
0.4%
0.0%
0.0%
0.0%
2028
0.7%
0.7%
0.7%
0.0%
0.0%
0.0%
2029
1.3%
1.3%
1.3%
0.0%
0.0%
0.0%
2030
1.2%
3.9%
3.2%
0.7%
2.3%
1.8%
2031
2.4%
7.9%
6.3%
1.4%
4.6%
3.7%
2032
2.9%
15.8%
9.5%
1.7%
9.2%
5.5%
2033
3.0%
15.8%
9.5%
1.7%
9.2%
5.5%
2034
3.1%
15.8%
9.5%
1.8%
9.2%
5.5%
2035
3.1%
15.8%
9.5%
1.8%
9.2%
5.5%
2036
3.2%
15.8%
9.5%
1.9%
9.2%
5.5%
2037
3.3%
15.8%
9.5%
1.9%
9.2%
5.5%
2038
3.4%
15.8%
9.5%
2.0%
9.2%
5.5%
2039
3.4%
15.8%
9.5%
2.0%
9.2%
5.5%
2040
3.5%
15.8%
9.5%
2.0%
9.2%
5.5%
2041
3.6%
15.8%
9.5%
2.1%
9.2%
5.5%
2042
3.6%
15.8%
9.5%
2.1%
9.2%
5.5%
2043
3.7%
15.8%
9.5%
2.2%
9.2%
5.5%
2044
3.8%
15.8%
9.5%
2.2%
9.2%
5.5%
2045
3.9%
15.8%
9.5%
2.2%
9.2%
5.5%
2046
3.9%
15.8%
9.5%
2.3%
9.2%
5.5%
2047
4.0%
15.8%
9.5%
2.3%
9.2%
5.5%
2048
4.1%
15.8%
9.5%
2.4%
9.2%
5.5%
2049
4.1%
15.8%
9.5%
2.4%
9.2%
5.5%
2050
4.2%
15.8%
9.5%
2.5%
9.2%
5.5%
2051
4.3%
15.8%
9.5%
2.5%
9.2%
5.5%
2052
4.3%
15.8%
9.5%
2.5%
9.2%
5.5%
2053
4.4%
15.8%
9.5%
2.6%
9.2%
5.5%
2054
4.5%
15.8%
9.5%
2.6%
9.2%
5.5%
2055
4.6%
15.8%
9.5%
2.7%
9.2%
5.5%
899
-------
B.4 Reference Case ZEV Adoption Sensitivity Sales Percentages
In the reference case HD ZEV adoption sensitivity analysis (presented in RIA Chapter 4.10),
we analyzed HD ZEV adoption only at the national level, instead of grouping states into ACT or
non-ACT states.
Table B-74 National ZEV sales percentages for Class 4-5 (regClassID 42) other buses (sourceTypelD 41) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
10.5%
20.0%
0%
0%
2028
15.8%
25.2%
0%
0%
2029
21.0%
30.4%
0%
0%
2030
26.1%
35.6%
0%
0%
2031
28.6%
51.1%
0%
0%
2032
31.2%
66.7%
0%
0%
2033
33.8%
66.7%
0%
0%
2034
36.4%
66.7%
0%
0%
2035
38.9%
66.7%
0%
0%
2036
38.8%
66.7%
0%
0%
2037
38.8%
66.7%
0%
0%
2038
38.7%
66.7%
0%
0%
2039
38.7%
66.7%
0%
0%
2040
38.6%
66.7%
0%
0%
2041
38.6%
66.7%
0%
0%
2042
38.5%
66.7%
0%
0%
2043
38.5%
66.7%
0%
0%
2044
38.4%
66.7%
0%
0%
2045
38.3%
66.7%
0%
0%
2046
38.2%
66.7%
0%
0%
2047
38.1%
66.7%
0%
0%
2048
38.1%
66.7%
0%
0%
2049
38.0%
66.7%
0%
0%
2050
38.0%
66.7%
0%
0%
2051
37.9%
66.7%
0%
0%
2052
37.9%
66.7%
0%
0%
2053
37.8%
66.7%
0%
0%
2054
37.8%
66.7%
0%
0%
2055
37.7%
66.7%
0%
0%
900
-------
Table B-75 National ZEV sales percentages for Class 6-7 (regClassID 46) other buses (sourceTypelD 41) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.1%
14.0%
0%
0%
2028
6.2%
14.0%
0%
0%
2029
8.3%
14.0%
0%
0%
2030
10.3%
14.0%
0%
0%
2031
11.3%
14.0%
0%
0%
2032
12.3%
14.0%
0%
0%
2033
13.3%
14.0%
0%
0%
2034
14.3%
14.3%
0%
0%
2035
15.3%
15.3%
0%
0%
2036
15.3%
15.3%
0%
0%
2037
15.3%
15.3%
0%
0%
2038
15.2%
15.2%
0%
0%
2039
15.2%
15.2%
0%
0%
2040
15.2%
15.2%
0%
0%
2041
15.2%
15.2%
0%
0%
2042
15.1%
15.1%
0%
0%
2043
15.1%
15.1%
0%
0%
2044
15.1%
15.1%
0%
0%
2045
15.1%
15.1%
0%
0%
2046
15.0%
15.0%
0%
0%
2047
15.0%
15.0%
0%
0%
2048
15.0%
15.0%
0%
0%
2049
15.0%
15.0%
0%
0%
2050
14.9%
14.9%
0%
0%
2051
14.9%
14.9%
0%
0%
2052
14.9%
14.9%
0%
0%
2053
14.9%
14.9%
0%
0%
2054
14.8%
14.8%
0%
0%
2055
14.8%
14.8%
0%
0%
901
-------
Table B-76 National ZEV sales percentages for Class 8 (regClassID 47) other buses (sourceTypelD 41) in the
reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
5.3%
5.3%
0.0%
0.0%
2028
8.0%
8.0%
0.0%
0.0%
2029
10.6%
10.6%
0.0%
0.0%
2030
10.6%
10.6%
2.6%
2.6%
2031
10.6%
10.6%
3.9%
3.9%
2032
10.6%
10.6%
5.2%
5.2%
2033
10.6%
10.6%
6.5%
6.5%
2034
10.6%
10.6%
7.8%
7.8%
2035
10.6%
10.6%
9.0%
9.0%
2036
10.6%
10.6%
9.0%
9.0%
2037
10.6%
10.6%
9.0%
9.0%
2038
10.6%
10.6%
8.9%
8.9%
2039
10.6%
10.6%
8.9%
8.9%
2040
10.6%
10.6%
8.9%
8.9%
2041
10.6%
10.6%
8.9%
8.9%
2042
10.6%
10.6%
8.8%
8.8%
2043
10.6%
10.6%
8.8%
8.8%
2044
10.6%
10.6%
8.8%
8.8%
2045
10.6%
10.6%
8.7%
8.7%
2046
10.6%
10.6%
8.7%
8.7%
2047
10.6%
10.6%
8.6%
8.6%
2048
10.6%
10.6%
8.6%
8.6%
2049
10.6%
10.6%
8.6%
8.6%
2050
10.6%
10.6%
8.6%
8.6%
2051
10.6%
10.6%
8.5%
8.5%
2052
10.6%
10.6%
8.5%
8.5%
2053
10.6%
10.6%
8.5%
8.5%
2054
10.6%
10.6%
8.5%
8.5%
2055
10.6%
10.6%
8.4%
8.4%
902
-------
Table B-77 National ZEV sales percentages for Class 4-5 (regClassID 42) transit buses (sourceTypelD 42) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
10.5%
20.0%
0%
0%
2028
15.8%
25.2%
0%
0%
2029
21.0%
30.4%
0%
0%
2030
26.1%
35.6%
0%
0%
2031
28.6%
51.1%
0%
0%
2032
31.2%
66.7%
0%
0%
2033
33.8%
66.7%
0%
0%
2034
36.4%
66.7%
0%
0%
2035
38.9%
66.7%
0%
0%
2036
38.8%
66.7%
0%
0%
2037
38.8%
66.7%
0%
0%
2038
38.7%
66.7%
0%
0%
2039
38.7%
66.7%
0%
0%
2040
38.6%
66.7%
0%
0%
2041
38.6%
66.7%
0%
0%
2042
38.5%
66.7%
0%
0%
2043
38.5%
66.7%
0%
0%
2044
38.4%
66.7%
0%
0%
2045
38.3%
66.7%
0%
0%
2046
38.2%
66.7%
0%
0%
2047
38.1%
66.7%
0%
0%
2048
38.1%
66.7%
0%
0%
2049
38.0%
66.7%
0%
0%
2050
38.0%
66.7%
0%
0%
2051
37.9%
66.7%
0%
0%
2052
37.9%
66.7%
0%
0%
2053
37.8%
66.7%
0%
0%
2054
37.8%
66.7%
0%
0%
2055
37.7%
66.7%
0%
0%
903
-------
Table B-78 National ZEV sales percentages for Class 6-7 (regClassID 46) transit buses (sourceTypelD 42) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.1%
10.0%
0%
0%
2028
6.2%
11.4%
0%
0%
2029
8.3%
12.7%
0%
0%
2030
10.3%
14.1%
0%
0%
2031
11.3%
18.2%
0%
0%
2032
12.3%
22.3%
0%
0%
2033
13.3%
22.3%
0%
0%
2034
14.3%
22.3%
0%
0%
2035
15.3%
22.3%
0%
0%
2036
15.3%
22.3%
0%
0%
2037
15.3%
22.3%
0%
0%
2038
15.2%
22.3%
0%
0%
2039
15.2%
22.3%
0%
0%
2040
15.2%
22.3%
0%
0%
2041
15.2%
22.3%
0%
0%
2042
15.1%
22.3%
0%
0%
2043
15.1%
22.3%
0%
0%
2044
15.1%
22.3%
0%
0%
2045
15.1%
22.3%
0%
0%
2046
15.0%
22.3%
0%
0%
2047
15.0%
22.3%
0%
0%
2048
15.0%
22.3%
0%
0%
2049
15.0%
22.3%
0%
0%
2050
14.9%
22.3%
0%
0%
2051
14.9%
22.3%
0%
0%
2052
14.9%
22.3%
0%
0%
2053
14.9%
22.3%
0%
0%
2054
14.8%
22.3%
0%
0%
2055
14.8%
22.3%
0%
0%
904
-------
Table B-79 National ZEV sales percentages for urban buses (regClassID 48 and sourceTypelD 42) in the
reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
5.3%
5.3%
0%
0%
2028
8.0%
14.0%
0%
0%
2029
10.6%
17.1%
0%
0%
2030
13.2%
20.3%
0%
0%
2031
14.4%
29.6%
0%
0%
2032
15.7%
39.0%
0%
0%
2033
17.0%
39.0%
0%
0%
2034
18.3%
39.0%
0%
0%
2035
19.6%
39.0%
0%
0%
2036
19.6%
39.0%
0%
0%
2037
19.6%
39.0%
0%
0%
2038
19.5%
39.0%
0%
0%
2039
19.5%
39.0%
0%
0%
2040
19.5%
39.0%
0%
0%
2041
19.4%
39.0%
0%
0%
2042
19.4%
39.0%
0%
0%
2043
19.4%
39.0%
0%
0%
2044
19.4%
39.0%
0%
0%
2045
19.3%
39.0%
0%
0%
2046
19.3%
39.0%
0%
0%
2047
19.2%
39.0%
0%
0%
2048
19.2%
39.0%
0%
0%
2049
19.2%
39.0%
0%
0%
2050
19.2%
39.0%
0%
0%
2051
19.1%
39.0%
0%
0%
2052
19.1%
39.0%
0%
0%
2053
19.1%
39.0%
0%
0%
2054
19.0%
39.0%
0%
0%
2055
19.0%
39.0%
0%
0%
905
-------
Table B-80 National ZEV sales percentages for Class 4-5 (regClassID 42) school buses (sourceTypelD 43) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
8.4%
20.0%
0%
0%
2028
12.6%
25.2%
0%
0%
2029
16.7%
30.4%
0%
0%
2030
20.8%
35.6%
0%
0%
2031
22.8%
51.1%
0%
0%
2032
24.8%
66.7%
0%
0%
2033
26.9%
66.7%
0%
0%
2034
28.9%
66.7%
0%
0%
2035
30.9%
66.7%
0%
0%
2036
30.9%
66.7%
0%
0%
2037
30.9%
66.7%
0%
0%
2038
30.8%
66.7%
0%
0%
2039
30.7%
66.7%
0%
0%
2040
30.7%
66.7%
0%
0%
2041
30.7%
66.7%
0%
0%
2042
30.6%
66.7%
0%
0%
2043
30.6%
66.7%
0%
0%
2044
30.6%
66.7%
0%
0%
2045
30.5%
66.7%
0%
0%
2046
30.4%
66.7%
0%
0%
2047
30.3%
66.7%
0%
0%
2048
30.3%
66.7%
0%
0%
2049
30.3%
66.7%
0%
0%
2050
30.2%
66.7%
0%
0%
2051
30.2%
66.7%
0%
0%
2052
30.1%
66.7%
0%
0%
2053
30.1%
66.7%
0%
0%
2054
30.0%
66.7%
0%
0%
2055
30.0%
66.7%
0%
0%
906
-------
Table B-81 National ZEV sales percentages for Class 6-7 (regClassID 46) school buses (sourceTypelD 43) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
3.6%
20.0%
0%
0%
2028
5.4%
25.6%
0%
0%
2029
7.1%
31.1%
0%
0%
2030
8.9%
36.7%
0%
0%
2031
9.7%
53.3%
0%
0%
2032
10.6%
70.0%
0%
0%
2033
11.5%
70.0%
0%
0%
2034
12.4%
70.0%
0%
0%
2035
13.2%
70.0%
0%
0%
2036
13.2%
70.0%
0%
0%
2037
13.2%
70.0%
0%
0%
2038
13.2%
70.0%
0%
0%
2039
13.1%
70.0%
0%
0%
2040
13.1%
70.0%
0%
0%
2041
13.1%
70.0%
0%
0%
2042
13.1%
70.0%
0%
0%
2043
13.1%
70.0%
0%
0%
2044
13.1%
70.0%
0%
0%
2045
13.0%
70.0%
0%
0%
2046
13.0%
70.0%
0%
0%
2047
13.0%
70.0%
0%
0%
2048
13.0%
70.0%
0%
0%
2049
12.9%
70.0%
0%
0%
2050
12.9%
70.0%
0%
0%
2051
12.9%
70.0%
0%
0%
2052
12.9%
70.0%
0%
0%
2053
12.9%
70.0%
0%
0%
2054
12.8%
70.0%
0%
0%
2055
12.8%
70.0%
0%
0%
907
-------
Table B-82 National ZEV sales percentages for Class 8 (regClassID 47) school buses (sourceTypelD 43) in the
reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.8%
4.8%
0%
0%
2028
7.2%
17.0%
0%
0%
2029
9.5%
19.7%
0%
0%
2030
11.9%
22.5%
0%
0%
2031
13.0%
30.8%
0%
0%
2032
14.2%
39.0%
0%
0%
2033
15.3%
39.0%
0%
0%
2034
16.5%
39.0%
0%
0%
2035
17.7%
39.0%
0%
0%
2036
17.6%
39.0%
0%
0%
2037
17.6%
39.0%
0%
0%
2038
17.6%
39.0%
0%
0%
2039
17.6%
39.0%
0%
0%
2040
17.5%
39.0%
0%
0%
2041
17.5%
39.0%
0%
0%
2042
17.5%
39.0%
0%
0%
2043
17.5%
39.0%
0%
0%
2044
17.4%
39.0%
0%
0%
2045
17.4%
39.0%
0%
0%
2046
17.3%
39.0%
0%
0%
2047
17.3%
39.0%
0%
0%
2048
17.3%
39.0%
0%
0%
2049
17.3%
39.0%
0%
0%
2050
17.3%
39.0%
0%
0%
2051
17.2%
39.0%
0%
0%
2052
17.2%
39.0%
0%
0%
2053
17.2%
39.0%
0%
0%
2054
17.1%
39.0%
0%
0%
2055
17.1%
39.0%
0%
0%
908
-------
Table B-83 National ZEV sales percentages for Class 6-7 (regClassID 46) refuse trucks (sourceTypelD 51) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.5%
20.0%
0%
0%
2028
6.8%
22.1%
0%
0%
2029
9.0%
24.2%
0%
0%
2030
11.2%
26.3%
0%
0%
2031
12.3%
32.7%
0%
0%
2032
13.4%
39.0%
0%
0%
2033
14.5%
39.0%
0%
0%
2034
15.6%
39.0%
0%
0%
2035
16.7%
39.0%
0%
0%
2036
16.6%
39.0%
0%
0%
2037
16.6%
39.0%
0%
0%
2038
16.6%
39.0%
0%
0%
2039
16.6%
39.0%
0%
0%
2040
16.5%
39.0%
0%
0%
2041
16.5%
39.0%
0%
0%
2042
16.5%
39.0%
0%
0%
2043
16.5%
39.0%
0%
0%
2044
16.5%
39.0%
0%
0%
2045
16.4%
39.0%
0%
0%
2046
16.4%
39.0%
0%
0%
2047
16.3%
39.0%
0%
0%
2048
16.3%
39.0%
0%
0%
2049
16.3%
39.0%
0%
0%
2050
16.3%
39.0%
0%
0%
2051
16.2%
39.0%
0%
0%
2052
16.2%
39.0%
0%
0%
2053
16.2%
39.0%
0%
0%
2054
16.2%
39.0%
0%
0%
2055
16.2%
39.0%
0%
0%
909
-------
Table B-84 National ZEV sales percentages for Class 8 (regClassID 47) refuse trucks (sourceTypelD 51) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
2.5%
2.5%
0%
0%
2028
3.8%
14.0%
0%
0%
2029
5.0%
17.1%
0%
0%
2030
6.3%
20.3%
0%
0%
2031
6.9%
29.6%
0%
0%
2032
7.5%
39.0%
0%
0%
2033
8.1%
39.0%
0%
0%
2034
8.7%
39.0%
0%
0%
2035
9.3%
39.0%
0%
0%
2036
9.3%
39.0%
0%
0%
2037
9.3%
39.0%
0%
0%
2038
9.3%
39.0%
0%
0%
2039
9.3%
39.0%
0%
0%
2040
9.2%
39.0%
0%
0%
2041
9.2%
39.0%
0%
0%
2042
9.2%
39.0%
0%
0%
2043
9.2%
39.0%
0%
0%
2044
9.2%
39.0%
0%
0%
2045
9.2%
39.0%
0%
0%
2046
9.1%
39.0%
0%
0%
2047
9.1%
39.0%
0%
0%
2048
9.1%
39.0%
0%
0%
2049
9.1%
39.0%
0%
0%
2050
9.1%
39.0%
0%
0%
2051
9.1%
39.0%
0%
0%
2052
9.1%
39.0%
0%
0%
2053
9.1%
39.0%
0%
0%
2054
9.0%
39.0%
0%
0%
2055
9.0%
39.0%
0%
0%
910
-------
Table B-85 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit short-haul trucks
(sourceTypelD 52) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
6.1%
20.0%
0%
0%
2028
9.2%
25.2%
0%
0%
2029
12.2%
30.4%
0%
0%
2030
15.2%
35.6%
0%
0%
2031
16.6%
51.1%
0%
0%
2032
18.1%
66.7%
0%
0%
2033
19.6%
66.7%
0%
0%
2034
21.1%
66.7%
0%
0%
2035
22.6%
66.7%
0%
0%
2036
22.6%
66.7%
0%
0%
2037
22.5%
66.7%
0%
0%
2038
22.5%
66.7%
0%
0%
2039
22.5%
66.7%
0%
0%
2040
22.4%
66.7%
0%
0%
2041
22.4%
66.7%
0%
0%
2042
22.4%
66.7%
0%
0%
2043
22.4%
66.7%
0%
0%
2044
22.3%
66.7%
0%
0%
2045
22.3%
66.7%
0%
0%
2046
22.2%
66.7%
0%
0%
2047
22.2%
66.7%
0%
0%
2048
22.1%
66.7%
0%
0%
2049
22.1%
66.7%
0%
0%
2050
22.1%
66.7%
0%
0%
2051
22.0%
66.7%
0%
0%
2052
22.0%
66.7%
0%
0%
2053
22.0%
66.7%
0%
0%
2054
21.9%
66.7%
0%
0%
2055
21.9%
66.7%
0%
0%
911
-------
Table B-86 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks
(sourceTypelD 52) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.0%
12.3%
0%
0%
2028
6.0%
14.8%
0%
0%
2029
8.0%
17.3%
0%
0%
2030
10.0%
19.8%
0%
0%
2031
10.9%
27.2%
0%
0%
2032
11.9%
34.6%
0%
0%
2033
12.9%
34.6%
0%
0%
2034
13.9%
34.6%
0%
0%
2035
14.8%
34.6%
0%
0%
2036
14.8%
34.6%
0%
0%
2037
14.8%
34.6%
0%
0%
2038
14.8%
34.6%
0%
0%
2039
14.7%
34.6%
0%
0%
2040
14.7%
34.6%
0%
0%
2041
14.7%
34.6%
0%
0%
2042
14.7%
34.6%
0%
0%
2043
14.7%
34.6%
0%
0%
2044
14.6%
34.6%
0%
0%
2045
14.6%
34.6%
0%
0%
2046
14.6%
34.6%
0%
0%
2047
14.5%
34.6%
0%
0%
2048
14.5%
34.6%
0%
0%
2049
14.5%
34.6%
0%
0%
2050
14.5%
34.6%
0%
0%
2051
14.4%
34.6%
0%
0%
2052
14.4%
34.6%
0%
0%
2053
14.4%
34.6%
0%
0%
2054
14.4%
34.6%
0%
0%
2055
14.4%
34.6%
0%
0%
912
-------
Table B-87 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks
(sourceTypelD 52) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
3.2%
3.2%
0%
0%
2028
4.8%
9.2%
0%
0%
2029
6.4%
11.6%
0%
0%
2030
8.0%
13.9%
0%
0%
2031
8.8%
20.9%
0%
0%
2032
9.6%
27.9%
0%
0%
2033
10.4%
27.9%
0%
0%
2034
11.1%
27.9%
0%
0%
2035
11.9%
27.9%
0%
0%
2036
11.9%
27.9%
0%
0%
2037
11.9%
27.9%
0%
0%
2038
11.9%
27.9%
0%
0%
2039
11.8%
27.9%
0%
0%
2040
11.8%
27.9%
0%
0%
2041
11.8%
27.9%
0%
0%
2042
11.8%
27.9%
0%
0%
2043
11.8%
27.9%
0%
0%
2044
11.8%
27.9%
0%
0%
2045
11.7%
27.9%
0%
0%
2046
11.7%
27.9%
0%
0%
2047
11.7%
27.9%
0%
0%
2048
11.7%
27.9%
0%
0%
2049
11.7%
27.9%
0%
0%
2050
11.6%
27.9%
0%
0%
2051
11.6%
27.9%
0%
0%
2052
11.6%
27.9%
0%
0%
2053
11.6%
27.9%
0%
0%
2054
11.6%
27.9%
0%
0%
2055
11.6%
27.9%
0%
0%
913
-------
Table B-88 National ZEV sales percentages for Class 4-5 (regClassID 42) single-unit long-haul trucks
(sourceTypelD 53) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
6.1%
10.0%
0%
0%
2028
9.2%
13.3%
0%
0%
2029
12.2%
16.7%
0%
0%
2030
15.2%
20.0%
0%
0%
2031
16.6%
30.0%
0%
0%
2032
18.1%
40.0%
0%
0%
2033
19.6%
40.0%
0%
0%
2034
21.1%
40.0%
0%
0%
2035
22.6%
40.0%
0%
0%
2036
22.6%
40.0%
0%
0%
2037
22.5%
40.0%
0%
0%
2038
22.5%
40.0%
0%
0%
2039
22.5%
40.0%
0%
0%
2040
22.4%
40.0%
0%
0%
2041
22.4%
40.0%
0%
0%
2042
22.4%
40.0%
0%
0%
2043
22.4%
40.0%
0%
0%
2044
22.3%
40.0%
0%
0%
2045
22.3%
40.0%
0%
0%
2046
22.2%
40.0%
0%
0%
2047
22.2%
40.0%
0%
0%
2048
22.1%
40.0%
0%
0%
2049
22.1%
40.0%
0%
0%
2050
22.1%
40.0%
0%
0%
2051
22.0%
40.0%
0%
0%
2052
22.0%
40.0%
0%
0%
2053
22.0%
40.0%
0%
0%
2054
21.9%
40.0%
0%
0%
2055
21.9%
40.0%
0%
0%
914
-------
Table B-89 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks
(sourceTypelD 53) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.0%
14.0%
0%
0%
2028
6.0%
16.8%
0%
0%
2029
8.0%
19.6%
0%
0%
2030
10.0%
22.3%
0%
0%
2031
10.9%
30.7%
0%
0%
2032
11.9%
39.0%
0%
0%
2033
12.9%
39.0%
0%
0%
2034
13.9%
39.0%
0%
0%
2035
14.8%
39.0%
0%
0%
2036
14.8%
39.0%
0%
0%
2037
14.8%
39.0%
0%
0%
2038
14.8%
39.0%
0%
0%
2039
14.7%
39.0%
0%
0%
2040
14.7%
39.0%
0%
0%
2041
14.7%
39.0%
0%
0%
2042
14.7%
39.0%
0%
0%
2043
14.7%
39.0%
0%
0%
2044
14.6%
39.0%
0%
0%
2045
14.6%
39.0%
0%
0%
2046
14.6%
39.0%
0%
0%
2047
14.5%
39.0%
0%
0%
2048
14.5%
39.0%
0%
0%
2049
14.5%
39.0%
0%
0%
2050
14.5%
39.0%
0%
0%
2051
14.4%
39.0%
0%
0%
2052
14.4%
39.0%
0%
0%
2053
14.4%
39.0%
0%
0%
2054
14.4%
39.0%
0%
0%
2055
14.4%
39.0%
0%
0%
915
-------
Table B-90 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks
(sourceTypelD 53) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
3.2%
3.2%
0%
0%
2028
4.8%
5.0%
0%
0%
2029
6.4%
9.3%
0%
0%
2030
8.0%
13.5%
0%
0%
2031
8.8%
26.3%
0%
0%
2032
9.6%
39.0%
0%
0%
2033
10.4%
39.0%
0%
0%
2034
11.1%
39.0%
0%
0%
2035
11.9%
39.0%
0%
0%
2036
11.9%
39.0%
0%
0%
2037
11.9%
39.0%
0%
0%
2038
11.9%
39.0%
0%
0%
2039
11.8%
39.0%
0%
0%
2040
11.8%
39.0%
0%
0%
2041
11.8%
39.0%
0%
0%
2042
11.8%
39.0%
0%
0%
2043
11.8%
39.0%
0%
0%
2044
11.8%
39.0%
0%
0%
2045
11.7%
39.0%
0%
0%
2046
11.7%
39.0%
0%
0%
2047
11.7%
39.0%
0%
0%
2048
11.7%
39.0%
0%
0%
2049
11.7%
39.0%
0%
0%
2050
11.6%
39.0%
0%
0%
2051
11.6%
39.0%
0%
0%
2052
11.6%
39.0%
0%
0%
2053
11.6%
39.0%
0%
0%
2054
11.6%
39.0%
0%
0%
2055
11.6%
39.0%
0%
0%
916
-------
Table B-91 National ZEV sales percentages for Class 4-5 (regClassID 42) motor homes (sourceTypelD 54) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
7.2%
7.2%
0%
0%
2028
10.8%
10.8%
0%
0%
2029
14.4%
14.4%
0%
0%
2030
17.9%
17.9%
0%
0%
2031
19.6%
19.6%
0%
0%
2032
21.4%
21.4%
0%
0%
2033
23.1%
23.1%
0%
0%
2034
24.9%
24.9%
0%
0%
2035
26.6%
26.6%
0%
0%
2036
26.6%
26.6%
0%
0%
2037
26.5%
26.5%
0%
0%
2038
26.5%
26.5%
0%
0%
2039
26.5%
26.5%
0%
0%
2040
26.4%
26.4%
0%
0%
2041
26.4%
26.4%
0%
0%
2042
26.4%
26.4%
0%
0%
2043
26.3%
26.3%
0%
0%
2044
26.3%
26.3%
0%
0%
2045
26.2%
26.2%
0%
0%
2046
26.1%
26.1%
0%
0%
2047
26.1%
26.1%
0%
0%
2048
26.1%
26.1%
0%
0%
2049
26.0%
26.0%
0%
0%
2050
26.0%
26.0%
0%
0%
2051
25.9%
25.9%
0%
0%
2052
25.9%
25.9%
0%
0%
2053
25.9%
25.9%
0%
0%
2054
25.8%
25.8%
0%
0%
2055
25.8%
25.8%
0%
0%
917
-------
Table B-92 National ZEV sales percentages for Class 6-7 (regClassID 46) motor homes (sourceTypelD 54) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
4.7%
4.7%
0%
0%
2028
7.0%
7.0%
0%
0%
2029
9.3%
9.3%
0%
0%
2030
11.6%
11.6%
0%
0%
2031
12.8%
12.8%
0%
0%
2032
13.9%
13.9%
0%
0%
2033
15.0%
15.0%
0%
0%
2034
16.2%
16.2%
0%
0%
2035
17.3%
17.3%
0%
0%
2036
17.3%
17.3%
0%
0%
2037
17.3%
17.3%
0%
0%
2038
17.2%
17.2%
0%
0%
2039
17.2%
17.2%
0%
0%
2040
17.2%
17.2%
0%
0%
2041
17.2%
17.2%
0%
0%
2042
17.1%
17.1%
0%
0%
2043
17.1%
17.1%
0%
0%
2044
17.1%
17.1%
0%
0%
2045
17.1%
17.1%
0%
0%
2046
17.0%
17.0%
0%
0%
2047
17.0%
17.0%
0%
0%
2048
17.0%
17.0%
0%
0%
2049
16.9%
16.9%
0%
0%
2050
16.9%
16.9%
0%
0%
2051
16.9%
16.9%
0%
0%
2052
16.9%
16.9%
0%
0%
2053
16.8%
16.8%
0%
0%
2054
16.8%
16.8%
0%
0%
2055
16.8%
16.8%
0%
0%
918
-------
Table B-93 National ZEV sales percentages for Class 8 (regClassID 47) motor homes (sourceTypelD 54) in
the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
2.5%
2.5%
0%
0%
2028
3.8%
3.8%
0%
0%
2029
5.0%
5.0%
0%
0%
2030
6.2%
6.2%
0%
0%
2031
6.8%
6.8%
0%
0%
2032
7.4%
7.4%
0%
0%
2033
8.0%
8.0%
0%
0%
2034
8.6%
8.6%
0%
0%
2035
9.3%
9.3%
0%
0%
2036
9.2%
9.2%
0%
0%
2037
9.2%
9.2%
0%
0%
2038
9.2%
9.2%
0%
0%
2039
9.2%
9.2%
0%
0%
2040
9.2%
9.2%
0%
0%
2041
9.2%
9.2%
0%
0%
2042
9.2%
9.2%
0%
0%
2043
9.2%
9.2%
0%
0%
2044
9.1%
9.1%
0%
0%
2045
9.1%
9.1%
0%
0%
2046
9.1%
9.1%
0%
0%
2047
9.1%
9.1%
0%
0%
2048
9.1%
9.1%
0%
0%
2049
9.0%
9.0%
0%
0%
2050
9.0%
9.0%
0%
0%
2051
9.0%
9.0%
0%
0%
2052
9.0%
9.0%
0%
0%
2053
9.0%
9.0%
0%
0%
2054
9.0%
9.0%
0%
0%
2055
9.0%
9.0%
0%
0%
919
-------
Table B-94 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit short-haul trucks
(sourceTypelD 61) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
3.4%
7.0%
0.0%
0.0%
2028
4.4%
8.6%
0.0%
0.0%
2029
5.3%
10.2%
0.0%
0.0%
2030
4.7%
10.2%
1.6%
3.4%
2031
5.0%
15.1%
1.7%
5.1%
2032
5.6%
21.4%
1.9%
7.2%
2033
5.6%
21.4%
1.9%
7.2%
2034
5.6%
21.4%
1.9%
7.2%
2035
5.6%
21.4%
1.9%
7.2%
2036
5.6%
21.4%
1.9%
7.2%
2037
5.6%
21.4%
1.9%
7.2%
2038
5.6%
21.4%
1.9%
7.2%
2039
5.6%
21.4%
1.9%
7.2%
2040
5.6%
21.4%
1.9%
7.2%
2041
5.6%
21.4%
1.9%
7.2%
2042
5.6%
21.4%
1.9%
7.2%
2043
5.6%
21.4%
1.9%
7.2%
2044
5.6%
21.4%
1.9%
7.2%
2045
5.6%
21.4%
1.9%
7.2%
2046
5.6%
21.4%
1.9%
7.2%
2047
5.6%
21.4%
1.9%
7.2%
2048
5.6%
21.4%
1.9%
7.2%
2049
5.6%
21.4%
1.9%
7.2%
2050
5.6%
21.4%
1.9%
7.2%
2051
5.6%
21.4%
1.9%
7.2%
2052
5.6%
21.4%
1.9%
7.2%
2053
5.6%
21.4%
1.9%
7.2%
2054
5.6%
21.4%
1.9%
7.2%
2055
5.6%
21.4%
1.9%
7.2%
920
-------
Table B-95 National ZEV sales percentages for Class 8 (regClassID 47) single-unit short-haul trucks
(sourceTypelD 61) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
2.7%
4.0%
0.0%
0.0%
2028
3.5%
8.3%
0.0%
0.0%
2029
4.3%
12.7%
0.0%
0.0%
2030
4.8%
16.9%
0.2%
0.7%
2031
5.1%
30.0%
0.2%
1.2%
2032
5.8%
43.5%
0.2%
1.7%
2033
5.8%
43.5%
0.2%
1.7%
2034
5.8%
43.5%
0.2%
1.7%
2035
5.8%
43.5%
0.2%
1.7%
2036
5.8%
43.5%
0.2%
1.7%
2037
5.8%
43.5%
0.2%
1.7%
2038
5.8%
43.5%
0.2%
1.7%
2039
5.8%
43.5%
0.2%
1.7%
2040
5.8%
43.5%
0.2%
1.7%
2041
5.7%
43.5%
0.2%
1.7%
2042
5.7%
43.5%
0.2%
1.7%
2043
5.7%
43.5%
0.2%
1.7%
2044
5.7%
43.5%
0.2%
1.7%
2045
5.7%
43.5%
0.2%
1.7%
2046
5.7%
43.5%
0.2%
1.7%
2047
5.7%
43.5%
0.2%
1.7%
2048
5.7%
43.5%
0.2%
1.7%
2049
5.7%
43.5%
0.2%
1.7%
2050
5.7%
43.5%
0.2%
1.7%
2051
5.7%
43.5%
0.2%
1.7%
2052
5.7%
43.5%
0.2%
1.7%
2053
5.7%
43.5%
0.2%
1.7%
2054
5.7%
43.5%
0.2%
1.7%
2055
5.7%
43.5%
0.2%
1.7%
921
-------
Table B-96 National ZEV sales percentages for Class 6-7 (regClassID 46) single-unit long-haul trucks
(sourceTypelD 62) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
0.2%
0.2%
0.0%
0.0%
2028
0.5%
0.5%
0.0%
0.0%
2029
0.8%
0.8%
0.0%
0.0%
2030
0.8%
3.9%
0.4%
2.3%
2031
1.5%
7.9%
0.9%
4.6%
2032
1.9%
15.8%
1.1%
9.2%
2033
1.9%
15.8%
1.1%
9.2%
2034
1.9%
15.8%
1.1%
9.2%
2035
1.9%
15.8%
1.1%
9.2%
2036
1.9%
15.8%
1.1%
9.2%
2037
1.9%
15.8%
1.1%
9.2%
2038
1.9%
15.8%
1.1%
9.2%
2039
1.9%
15.8%
1.1%
9.2%
2040
1.9%
15.8%
1.1%
9.2%
2041
1.9%
15.8%
1.1%
9.2%
2042
1.9%
15.8%
1.1%
9.2%
2043
1.9%
15.8%
1.1%
9.2%
2044
1.9%
15.8%
1.1%
9.2%
2045
1.9%
15.8%
1.1%
9.2%
2046
1.9%
15.8%
1.1%
9.2%
2047
1.9%
15.8%
1.1%
9.2%
2048
1.9%
15.8%
1.1%
9.2%
2049
1.9%
15.8%
1.1%
9.2%
2050
1.9%
15.8%
1.1%
9.2%
2051
1.9%
15.8%
1.1%
9.2%
2052
1.9%
15.8%
1.1%
9.2%
2053
1.9%
15.8%
1.1%
9.2%
2054
1.9%
15.8%
1.1%
9.2%
2055
1.9%
15.8%
1.1%
9.2%
922
-------
Table B-97 National ZEV sales percentages for Class 8 (regClassID 47) single-unit long-haul trucks
(sourceTypelD 62) in the reference case ZEV adoption sensitivity analysis
Model
Year
BEV Sales Percentage
FCEV Sales Percentage
Sensitivity
Reference
Sensitivity
Control
Sensitivity
Reference
Sensitivity
Control
2027
0.2%
0.2%
0.0%
0.0%
2028
0.4%
0.4%
0.0%
0.0%
2029
0.7%
0.7%
0.0%
0.0%
2030
0.6%
3.9%
0.4%
2.3%
2031
1.3%
7.9%
0.7%
4.6%
2032
1.6%
15.8%
0.9%
9.2%
2033
1.6%
15.8%
0.9%
9.2%
2034
1.6%
15.8%
0.9%
9.2%
2035
1.6%
15.8%
0.9%
9.2%
2036
1.6%
15.8%
0.9%
9.2%
2037
1.6%
15.8%
0.9%
9.2%
2038
1.6%
15.8%
0.9%
9.2%
2039
1.6%
15.8%
0.9%
9.2%
2040
1.6%
15.8%
0.9%
9.2%
2041
1.6%
15.8%
0.9%
9.2%
2042
1.6%
15.8%
0.9%
9.2%
2043
1.6%
15.8%
0.9%
9.2%
2044
1.6%
15.8%
0.9%
9.2%
2045
1.6%
15.8%
0.9%
9.2%
2046
1.6%
15.8%
0.9%
9.2%
2047
1.6%
15.8%
0.9%
9.2%
2048
1.6%
15.8%
0.9%
9.2%
2049
1.6%
15.8%
0.9%
9.2%
2050
1.6%
15.8%
0.9%
9.2%
2051
1.6%
15.8%
0.9%
9.2%
2052
1.6%
15.8%
0.9%
9.2%
2053
1.6%
15.8%
0.9%
9.2%
2054
1.6%
15.8%
0.9%
9.2%
2055
1.6%
15.8%
0.9%
9.2%
923
-------
Appendix C - Additional Benefits
This Appendix C presents the climate benefits of the final standards using the interim Social
Cost of Greenhouse Gas (SC-GHG) values used in the NPRM. We have updated the interim
values to 2022 dollars for the analysis in this RIA. The updated interim SC-GHG values are
presented in Table C-l. The climate benefits using these values are presented in Table C-2
through Table C-5 for the reductions in CO2, CH4, N2O and all GHGs, respectively. Table C-6
presents the summary of cost and benefits of the final standards using the 3% average benefits
across the GHGs.
924
-------
Table C-l Interim Social Cost of GHG Values, 2027-2055 (2022 $/metric ton)
CY
CO2
CH4
N2O
5%
Avg
3%
Avg
2.5%
Avg
3%
95th
pctile
5%
Avg
3%
Avg
2.5%
Avg
3%
95th
pctile
5%
Avg
3%
Avg
2.5%
Avg
3%
95th
pctile
2027
$20
$66
$96
$197
$959
$2,030
$2,621
$5,379
$8,053
$24,029
$34,734
$63,484
2028
$21
$67
$97
$201
$989
$2,083
$2,683
$5,523
$8,279
$24,518
$35,358
$64,836
2029
$21
$68
$99
$205
$1,020
$2,135
$2,745
$5,667
$8,505
$25,008
$35,981
$66,188
2030
$22
$69
$100
$209
$1,050
$2,188
$2,807
$5,810
$8,731
$25,497
$36,604
$67,540
2031
$22
$70
$102
$213
$1,089
$2,250
$2,879
$5,983
$9,008
$26,048
$37,288
$69,062
2032
$23
$72
$103
$218
$1,127
$2,312
$2,950
$6,155
$9,285
$26,598
$37,973
$70,583
2033
$24
$73
$105
$222
$1,165
$2,374
$3,022
$6,327
$9,563
$27,149
$38,657
$72,105
2034
$24
$74
$106
$226
$1,204
$2,436
$3,093
$6,499
$9,840
$27,700
$39,342
$73,626
2035
$25
$76
$108
$230
$1,242
$2,498
$3,165
$6,671
$10,117
$28,250
$40,026
$75,148
2036
$26
$77
$109
$235
$1,281
$2,560
$3,236
$6,843
$10,395
$28,801
$40,711
$76,669
2037
$26
$78
$111
$239
$1,319
$2,622
$3,308
$7,015
$10,672
$29,352
$41,395
$78,191
2038
$27
$79
$112
$243
$1,358
$2,684
$3,379
$7,188
$10,949
$29,902
$42,079
$79,712
2039
$28
$81
$114
$248
$1,396
$2,746
$3,451
$7,360
$11,227
$30,453
$42,764
$81,234
2040
$28
$82
$115
$252
$1,435
$2,808
$3,522
$7,532
$11,504
$31,004
$43,448
$82,755
2041
$29
$83
$117
$256
$1,477
$2,870
$3,593
$7,694
$11,829
$31,596
$44,169
$84,349
2042
$30
$85
$118
$260
$1,519
$2,933
$3,663
$7,856
$12,154
$32,189
$44,891
$85,944
2043
$30
$86
$120
$264
$1,561
$2,996
$3,734
$8,018
$12,479
$32,781
$45,612
$87,538
2044
$31
$87
$121
$267
$1,603
$3,058
$3,804
$8,180
$12,803
$33,374
$46,333
$89,132
2045
$32
$88
$123
$271
$1,645
$3,121
$3,875
$8,342
$13,128
$33,967
$47,054
$90,727
2046
$33
$90
$124
$275
$1,687
$3,183
$3,946
$8,504
$13,453
$34,559
$47,775
$92,321
2047
$33
$91
$126
$279
$1,729
$3,246
$4,016
$8,666
$13,778
$35,152
$48,496
$93,915
2048
$34
$92
$127
$283
$1,771
$3,309
$4,087
$8,828
$14,103
$35,745
$49,217
$95,510
2049
$35
$93
$129
$287
$1,813
$3,371
$4,157
$8,990
$14,428
$36,337
$49,939
$97,104
2050
$35
$95
$130
$291
$1,855
$3,434
$4,228
$9,152
$14,753
$36,930
$50,660
$98,698
2051
$36
$95
$132
$292
$1,887
$3,478
$4,276
$9,204
$15,141
$37,548
$51,366
$99,533
2052
$37
$96
$133
$293
$1,913
$3,513
$4,314
$9,243
$15,500
$38,141
$52,071
$101,081
2053
$38
$97
$135
$294
$1,939
$3,548
$4,352
$9,282
$15,859
$38,735
$52,775
$102,629
2054
$38
$99
$136
$295
$1,965
$3,584
$4,390
$9,320
$16,219
$39,329
$53,480
$104,177
2055
$39
$100
$137
$298
$1,991
$3,619
$4,428
$9,359
$16,578
$39,922
$54,184
$105,724
Note: The 2027-2055 values are identical to those reported in the 2016 TSD (IWG 2016a) adjusted to 2022 dollars
using the annual GDP Implicit Price Deflator values used elsewhere in the analysis presented in this RIA. This
table displays the values rounded to the nearest dollar; the annual unrounded values used in the calculations in this
analysis are available on OMB's website: https://www.whitehouse.gov/omb/information-regulatory-
affairs/regulatory-matters/#scghgs. The estimates were extended for the period 2051 to 2055 using methods,
assumptions, and parameters identical to the 2020-2050 estimates. The values are stated in $/metric ton and vary
depending on the year.
925
-------
Table C-2 Benefits of reduced C02 emissions from the final standards using the interim SC-GHG values
(Millions of 2022 dollars)
CY
Discount Rate
5% Avg
3% Avg
2.5% Avg
3%
95th percentile
2027
$5.7
$19
$27
$56
2028
$12
$40
$59
$120
2029
$20
$64
$93
$190
2030
$25
$79
$110
$240
2031
$38
$120
$170
$360
2032
$54
$170
$240
$520
2033
$69
$210
$310
$650
2034
$81
$250
$360
$760
2035
$89
$270
$380
$820
2036
$240
$710
$1,000
$2,200
2037
$440
$1,300
$1,800
$4,000
2038
$680
$2,000
$2,800
$6,200
2039
$970
$2,800
$4,000
$8,700
2040
$1,300
$3,800
$5,300
$12,000
2041
$1,400
$4,000
$5,700
$12,000
2042
$1,500
$4,200
$5,900
$13,000
2043
$1,600
$4,400
$6,100
$14,000
2044
$1,600
$4,500
$6,300
$14,000
2045
$1,700
$4,600
$6,500
$14,000
2046
$1,800
$4,800
$6,700
$15,000
2047
$1,800
$5,000
$6,900
$15,000
2048
$1,900
$5,100
$7,100
$16,000
2049
$2,000
$5,300
$7,300
$16,000
2050
$2,000
$5,400
$7,500
$17,000
2051
$2,100
$5,500
$7,600
$17,000
2052
$2,100
$5,600
$7,700
$17,000
2053
$2,200
$5,600
$7,800
$17,000
2054
$2,200
$5,700
$7,900
$17,000
2055
$2,300
$5,800
$7,900
$17,000
PV
$12,000
$48,000
$73,000
$150,000
AV
$780
$2,500
$3,600
$7,600
Note: Climate benefits are based on changes (reductions) in CO2
emissions and are calculated using the IWG interim SC-GHG
estimates from (IWG 2021). Climate benefits include changes in
vehicle, EGU, and refinery CO2 emissions.
926
-------
Table C-3 Benefits of reduced CH4 emissions from the final standards using the interim SC-GHG values
(Millions of 2022 dollars)
CY
Discount Rate
5% Avg
3% Avg
2.5% Avg
3%
95th percentile
2027
$0.0062
$0,013
$0,017
$0,035
2028
$0,043
$0,091
$0.12
$0.24
2029
$0,076
$0.16
$0.21
$0.42
2030
$0,074
$0.15
$0.2
$0.41
2031
$0,071
$0.15
$0.19
$0.39
2032
$0,023
$0,048
$0,061
$0.13
2033
-$0,031
-$0,063
-$0.08
-$0.17
2034
-$0,039
-$0,078
-$0,099
-$0.21
2035
-$0,052
-$0.1
-$0.13
-$0.28
2036
$0.39
$0.79
$1
$2.1
2037
$1.1
$2.2
$2.8
$6
2038
$2.2
$4.3
$5.4
$11
2039
$3.4
$6.6
$8.3
$18
2040
$4.7
$9.3
$12
$25
2041
$5.6
$11
$14
$29
2042
$6.5
$13
$16
$34
2043
$7.4
$14
$18
$38
2044
$8.4
$16
$20
$43
2045
$9.4
$18
$22
$47
2046
$10
$19
$24
$52
2047
$11
$21
$26
$56
2048
$12
$22
$28
$60
2049
$13
$24
$30
$64
2050
$14
$26
$32
$69
2051
$15
$27
$34
$72
2052
$16
$29
$35
$76
2053
$17
$30
$37
$79
2054
$18
$32
$39
$83
2055
$18
$34
$41
$87
PV
$65
$190
$260
$490
AV
$4.3
$9.7
$13
$26
Note: Climate benefits are based on changes (reductions) in
CH4 emissions and are calculated using the IWG interim SC-
GHG estimates from (IWG 2021). Climate benefits include
changes in vehicle, EGU, and refinery CH4 emissions.
927
-------
Table C-4 Benefits of reduced N2O emissions from the final standards using the interim SC-GHG values
(Millions of 2022 dollars)
CY
Discount Rate
5% Avg
3% Avg
2.5% Avg
3%
95th percentile
2027
$0.44
$1.3
$1.9
$3.5
2028
$1.2
$3.5
$5
$9.2
2029
$2.2
$6.5
$9.3
$17
2030
$4.2
$12
$18
$33
2031
$8.9
$26
$37
$68
2032
$18
$50
$72
$130
2033
$27
$76
$110
$200
2034
$36
$100
$140
$270
2035
$45
$130
$180
$340
2036
$55
$150
$220
$410
2037
$65
$180
$250
$470
2038
$74
$200
$280
$540
2039
$83
$230
$320
$600
2040
$92
$250
$350
$660
2041
$100
$270
$380
$720
2042
$110
$290
$400
$770
2043
$120
$310
$420
$810
2044
$120
$320
$440
$860
2045
$130
$330
$460
$890
2046
$130
$340
$480
$920
2047
$140
$350
$490
$950
2048
$140
$360
$500
$970
2049
$150
$370
$510
$990
2050
$150
$380
$520
$1,000
2051
$160
$390
$530
$1,000
2052
$160
$400
$540
$1,000
2053
$160
$400
$550
$1,100
2054
$170
$410
$560
$1,100
2055
$170
$420
$560
$1,100
PV
$1,000
$3,800
$5,800
$10,000
AV
$67
$200
$280
$530
Note: Climate benefits are based on changes (reductions) in
N20 emissions and are calculated using the IWG interim SC-
GHG estimates from (IWG 2021). Climate benefits include
changes in vehicle, EGU, and refinery N20 emissions.
928
-------
Table C-5 Benefits of reduced GHG emissions from the final standards using the interim SC-GHG values
(Millions of 2022 dollars)
CY
Discount Rate
5% Avg
3% Avg
2.5% Avg
3%
95th percentile
2027
$6.1
$20
$29
$59
2028
$14
$44
$64
$130
2029
$22
$71
$100
$210
2030
$29
$92
$130
$270
2031
$46
$140
$210
$430
2032
$72
$220
$320
$650
2033
$96
$290
$420
$850
2034
$120
$350
$500
$1,000
2035
$130
$400
$560
$1,200
2036
$290
$870
$1,200
$2,600
2037
$500
$1,500
$2,100
$4,400
2038
$760
$2,200
$3,100
$6,700
2039
$1,100
$3,100
$4,300
$9,300
2040
$1,400
$4,000
$5,700
$12,000
2041
$1,500
$4,300
$6,000
$13,000
2042
$1,600
$4,500
$6,300
$14,000
2043
$1,700
$4,700
$6,600
$14,000
2044
$1,800
$4,900
$6,800
$15,000
2045
$1,800
$5,000
$6,900
$15,000
2046
$1,900
$5,200
$7,200
$16,000
2047
$2,000
$5,400
$7,400
$16,000
2048
$2,000
$5,500
$7,600
$17,000
2049
$2,100
$5,700
$7,800
$17,000
2050
$2,200
$5,800
$8,000
$18,000
2051
$2,300
$5,900
$8,200
$18,000
2052
$2,300
$6,000
$8,300
$18,000
2053
$2,400
$6,100
$8,400
$18,000
2054
$2,400
$6,100
$8,500
$18,000
2055
$2,500
$6,200
$8,500
$18,000
PV
$13,000
$52,000
$79,000
$160,000
AV
$850
$2,700
$3,900
$8,100
Note: Climate benefits are based on changes (reductions) in
GHG emissions and are calculated using the IWG interim SC-
GHG estimates from (IWG 2021). Climate benefits include
changes in vehicle, EGU, and refinery GHG emissions.
929
-------
Table C-6 Summary of costs, fuel savings and benefits of the final standards (billions of 2022 dollars)
CY 2055
PV, 2%
PV, 3%
PV, 7%
AV, 2%
AV, 3%
AV, 7%
Vehicle Technology Package RPE
-$0.59
-$4.2
-$3.2
-$1
-$0.19
-$0.17
-$0,083
EVSE RPE
$1.1
$28
$25
$15
$1.3
$1.3
$1.3
Sum of Vehicle Costs
$0.55
$24
$22
$14
$1.1
$1.1
$1.2
Pre-tax Fuel Savings
-$0.35
-$9.5
-$7.9
-$3.9
-$0.43
-$0.41
-$0.31
Diesel Exhaust Fluid Savings
$1.8
$21
$17
$8.7
$0.95
$0.9
$0.71
Repair & Maintenance Savings
$6.9
$73
$60
$30
$3.3
$3.1
$2.4
Insurance Savings
$0.25
$1.3
$1
$0.46
$0.06
$0,055
$0,038
Vehicle Replacement Savings
$0.14
$1.9
$1.5
$0.72
$0,086
$0.08
$0,058
EVSE Replacement Savings
-$1.3
-$11
-$8.7
-$3.7
-$0.5
-$0.45
-$0.3
Sum of Operating Savings
$7.4
$76
$63
$32
$3.5
$3.3
$2.6
Energy Security Benefits
$0.8
$9.8
$8.2
$4.2
$0.45
$0.43
$0.34
Climate Benefits - 3% Average3
$6.2
$52
$52
$52
$2.7
$2.7
$2.7
PM2 5 Health Benefits'3
$1.9
$6.5
$4.2
-$0.4
$0.3
$0.22
-$0,032
Sum of Benefits0
$8.7
$68
$64
$55
$3.4
$3.3
$3
Net Benefits0
$16
$120
$110
$73
$5.8
$5.5
$4.4
" k 0 See footnotes to Table 8-8 in Chapter 8 of this RIA.
930
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Appendix D - List of Abbreviations, Acronyms, and Symbols
Acronym
Definition
°C
Degrees Celsius
ug
Microgram
um
Micrometers
20xx$
U.S. Dollars in calendar year 20xx
A/C
Air Conditioning
ABTC
American Battery Technology Company
AC
Alternating Current
ACT
California Advanced Clean Truck
AEO
Annual Energy Outlook
AFDC
Alternative Fuels Data Center
AHS
American Housing Survey
ANL
Argonne National Laboratory
APU
Auxiliary Power Unit
ARCHES
Alliance for Regional Clean Hydrogen Energy Systems
ARPA
Advanced Research Projects Agency
ATR
Autothermal Reforming
ATRI
American Transportation Research Institute
ATSDR
Agency for Toxic Substances and Disease Registry
AV
Annualized value
Avg
Average
BEA
Bureau of Economic Analysis
BenMAP
Benefits Mapping and Analysis Program
BenMAP-CE
Benefits Mapping and Analysis Program-Community Edition
BEV
Battery Electric Vehicle
bhp
Brake Horsepower
bhp-hr
Brake Horsepower Hour
BIL
Bipartisan Infrastructure Law
BLS
Bureau of Labor Statistics
BNEF
Bloomberg New Energy Finance
BOP
Balance of Plant
BP
British Petroleum
BPT
Benefit Per Ton
BTU
British Thermal Unit
CAA
Clean Air Act
CAFE
Corporate Average Fuel Economy
CARB
California Air Resources Board
CASAC
Clean Air Scientific Advisory Committee
CCS
Combined Charging System
CDC
Center for Disease Control
CEC
California Energy Commission
CFI
Charging and Fueling Infrastructure
CFR
Code of Federal Regulations
ch4
Methane
CHPS
Clean Hydrogen Production Standard
CI
Compression-Ignition
CMI
Critical Minerals Institute
CNG
Compressed Natural Gas
CO
Carbon Monoxide
C02
Carbon Dioxide
931
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Acronym
Definition
CCheq
CO2 Equivalent
COI
Cost-of-illness
CONUS
Contiguous US
COP
Coefficient of Performance
COPD
Chronic Obstructive Pulmonary Disease
CRC
Coordinating Research Council
CSB
Clean School Bus
CY
Calendar Year
DC
Direct Current
DCFC
Direct Current Fast Charger
DEF
Diesel Exhaust Fluid
DER
Distributed Energy Resources
DFH
Direct Fired Heaters
DHHS
Department of Health and Human Services
DICE
Dynamic Integrated Climate and Economy
DMC
Direct Manufacturing Costs
DOC
Diesel Oxidation Catalyst
DOE
Department of Energy
DOT
Department of Transportation
DPA
Defense Production Act
DPF
Diesel Particulate Filter
DRIA
Draft Regulatory Impact Analysis
DSCIM
Data-driven Spatial Climate Impact Model
DTNA
Daimler Truck North America
EC
Elemental Carbon
EDF
Environmental Defense Fund
EEAC
Environmental Economics Advisory Committee
EER
Energy Efficiency Ratio
EGR
Exhaust Gas Recirculation
EGU
Electricity Generation Unit
EIA
Energy Information Administration
EJ
Environmental Justice
EMF
Energy Modeling Forum
EPA
Environmental Protection Agency
EPRI
Electric Power Research Institute
ERM
Employment Requirements Matrix
EV
Electric Vehicle
EVSE
Electric Vehicle Supply Equipment
FAF
Freight Analysis Framework
FaIR
Finite Amplitude Impulse Response
FCEV
Fuel Cell Electric Vehicle
FCT
Fuel Cell Truck
FEL
Family Emission Limit
FERC
Federal Energy Regulatory Commission
FET
Federal Excise Tax
FHWA
Federal Highway Administration
FMVSS
Federal Motor Vehicle Safety Standards
FOH
Fuel Operated Heaters
FR
Federal Register
FrEDI
Framework for Evaluating Damages and Impacts
FRM
Final Rulemaking
932
-------
Acronym
Definition
FTA
Federal Transit Administration
FTP
Federal Test Procedure
FUND
Framework for Uncertainty, Negotiation, and Distribution
FY
Fiscal Year
g
Gram
g/s
Gram-per-second
g/ton-mile
Grams emitted to move one ton (2000 pounds) of freight over one mile
gal
Gallon
gal/1000 ton-mile
Gallons of fuel used to move one ton of payload (2,000 pounds) over 1000 miles
GAO
Government Accountability Office
GDP
Gross Domestic Product
GE
General Electric
GEM
Greenhouse Gas Emissions Model
GHG
Greenhouse Gas
GIVE
Greenhouse Gas Impact Value Estimator
GM
General Motors
GREET
Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation
GTP
Global Temperature Potential
GTR
Global Technical Regulation
GVWR
Gross Weight Vehicle Rating
GW
Gigawatt
GWP
Global Warming Potential
HAD
Health Assessment Document
HCM
Hosting Capacity Maps
HH
Heavy-haul
HD
Heavy-duty
HDV
Heavy-duty Vehicle
HEI
Health Effects Institute
HEV
Hybrid Electric Vehicle
HFC
Hydrofluorocarbon
HHD
Heavy Heavy-duty
HHDV
Heavy Heavy-duty vehicle
hrs
Hours
HVAC
Heating, Ventilation, Air Conditioning
HVTP
Hybrid Voucher Incentives Project
hz
Hertz
IAM
Integrated Assessment Model
IARC
International Agency for Research on Cancer
ICCT
International Council for Clean Transportation
ICE
Internal Combustion Engine
IEA
International Energy Agency
IEC
International Electrotechnical Commission
IIHS
Insurance Institute for Highway Safety
IPCC
Intergovernmental Panel on Climate Change
IPM
Integrated Planning Model
IRA
Inflation Reduction Act
IRIS
Integrated Risk Information System
ISA
Integrated Science Assessment
ISO
International Standards Organization
IWG
Interagency Working Group
JOET
Joint Office of Energy and Transportation
933
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Acronym
Definition
K
Potassium
kg
Kilogram
km
Kilometer
km/h
Kilometers per Hour
lb
Pound
LBNL
Lawrence Berkeley National Laboratory
LD
Light-duty
LDT
Light-duty truck
LDV
Light-duty vehicle
LHDV
Light heavy-duty vehicle
LFP
Lithium Iron-Phosphate
LHD
Light Heavy-duty
Li
Lithium
LLC
Limited Liability Company
Light- and Medium-Duty Vehicle (rule), which is a reference to the Multi-Pollutant
LMDV
Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty
Vehicles
LNG
Liquefied natural gas
m2
Square Meters
m3
Cubic Meters
m3
Cubic Meters
MARAD
Maritime Administration
MCS
Megawatt Charging System
MD
Medium-duty
MEA
Membrane Electrode Assemblies
MFR
Manufacturer
Mg
Magnesium
MH
Medium Heavy
MHD
Medium Heavy-duty
MHDV
Medium Heavy-duty vehicle
MINER
Mining Innovations for Negative Emissions Resource Recovery
MMBD
Million barrels of oil per day
MMT
Million metric tons
Mn
Manganese
MOU
Memorandum of Understanding
MOVES
Motor Vehicle Emission Simulator
MP
Multi-Purpose
MRL
Minimal Risk Level
MSP
Minerals Security Partnership
MW
Megawatt
MY
Model Year
NAAQS
National Ambient Air Quality Standards
NACS
North American Charging Standard
NAICS
North American Industry Classification System
NASA
National Aeronautics and Space Administration
NCA
Nickel-Cobalt-Aluminum
NCA4
4th National Climate Assessment
NEC
National Electric Code
NEI
National Emissions Inventory
NEMS
National Energy Modeling System
NERC
North American Electric Reliability Corporation
934
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Acronym
Definition
NESCAUM
Northeast States for Coordinated Air Use Management
NEVI
National Electric Vehicle Infrastructure
NHFN
National Highway Freight Network
NHIS
National Health Interview Survey
NHTSA
National Highway Traffic Safety Administration
NMC
Nickel-Manganese-Cobalt
NO
Nitric Oxide
no2
Nitrogen Dioxide
NOx
Nitrogen Oxides
NPRM
Notice of Proposed Rulemaking
NRC
National Research Council
NREL
National Renewable Energy Laboratory
NTP
National Toxicology Program
NYC
New York City
NZEV
Near Zero-emission Vehicle
03
Ozone
OECD
Organisation for Economic Co-operation and Development
OEM
Original Equipment Manufacturers
OMB
Office of Management Budget
OMEGA
Optimization Model for reducing Emissions of Greenhouse Gases from Automobiles
OPEC
Organization of Petroleum Exporting Countries
ORNL
Oak Ridge National Laboratory
OSHA
Occupational Safety and Health Administration
PAGE
Policy Analysis of the Greenhouse Gas Effect
PBPK
Physiologically based pharmacokinetic
PEM
Polymer Electrolyte Membrane
PEV
Plug-in Electric Vehicle
PFC
Perfluorocarbon
PFG
Performance Food Group
PHEV
Plug-in Hybrid Electric Vehicles
PM
Particulate Matter
PM10
Coarse Particulate Matter (diameter of 10 um or less)
PM2.5
Fine Particulate Matter (diameter of 2.5 um or less)
PNNL
Pacific Northwest National Laboratory
PNW
Pacific Northwest
PPE
Personal Protection Equipment
PTC
Production Tax Credit
PTO
Power Takeoff
PV
Present Values
RFA
Regulatory Flexibility Act
RFF-SPs
Resources for the Future socioeconomic projections
RFS
Renewable Fuel Standard
RIA
Regulatory Impact Analysis
RPE
Retail Price Equivalent
RTC
Response to Comment (Document)
SAB
Science Advisory Board
SABERS
Solid-state Architecture Batteries for Enhanced Rechargeability and Safety
SAE
Society of Automotive Engineers
SAFE
Securing America's Future Energy
SBA
Small Business Administration
SBREFA
Small Business Regulatory Enforcement Fairness Act
935
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Acronym
Definition
SC-GHG
Social Cost of Greenhouse Gases
SCR
Selective Catalytic Reduction
SES
Socioeconomic status
SET
Supplemental Emission Test
sf6
Sulfur Hexafluoride
SI
Spark-Ignition
SMR
Steam Methane Reforming
S02
Sulfur Dioxide
SOH
State-of-health
SOx
Oxides of Sulfur
SOX
Sulfur Oxides
SPR
Strategic Petroleum Reserve
T3CO
NREL's Transportation Technology Total Cost of Ownership
TCO
Total Cost of Ownership
TEIS
Multi-State Transportation Electrification Impact Study
TEMPO
NREL's Transportation Energy & Mobility Pathway Options Model
TIGER
Topological^ Integrated Geographic Encoding and Referencing system
TOU
Time of use
TPRD
Thermally activated pressure relief device
TRUCS
Technology Resource Use Case Scenario
TSD
Technical Support Document
TW
Terawatt
U.S.
United States
UAW
United Auto Workers
UFP
Ultrafine Particles
UN
United Nations
UNECE
United Nations Economic Commission for Europe
UNFCCC
United Nations Framework Convention on Climate Change
URE
Unit Risk Estimate
USA
United States of America
USABC
US Automotive Battery Consortium
use
Unites States Code
USD
United States Dollars
USDOT
United States Department of Transportation
USGCRP
Unites States Global Change Research Program
USGS
United States Geological Survey
USPS
United States Postal Service
VIN
Vehicle Identification Number
VIUS
Vehicle Inventory Use Survey
VMT
Vehicle Miles Traveled
voc
Volatile Organic Compound
VPP
Virtual Power Plant
VSL
Value of Statistical Life
WTI
West Texas Intermediate
WTP
Willingness To Pay
ZEP
Zero Emission Powertrain
ZETI
Zero-Emission Technology Inventory
ZEV
Zero-Emission Vehicles
936
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