'^vSmartWay Transport Partnership U.S. Environmental Protection Agency 2018 SmartWay Logistics Company Partner Tool: Technical Documentation U.S. Version 2.0.17 (Data Year 2017) ggEES www.epa.gov/smartway SmartWayy .SmartWay^ vSmarlWuyj vvEPA United States Environmental Protection Agency ------- "^^SmartWay Transport Partnership U.S. Environmental Protection Agency 2018 SmartWay Logistics Company Partner Tool: Technical Documentation U.S. Version 2.0.17 (Data Year 2017) Transportation and Climate Division Office of Transportation and Air Quality U.S. Environmental Protection Agency United States Environmental Protection ^1 Agency Office ofTransportation and Air Quality EPA-420-B-18-030 July 2018 ------- 1.0 Overview The SmartWay Logistics Tool is intended to help logistics companies estimate and assess their carbon, PM, and NOx emission performance levels as well as their total emissions associated with goods movement in the U.S. freight rail, barge, air and trucking sectors.1 The new SmartWay truck, air and barge carrier emissions performance data that EPA has included in the Tool, along with publicly available Class I rail data, will allow logistics companies to generate more accurate emissions performance estimates and mass emissions inventories. The Tool will allow logistics companies to track their freight- related emissions performance from year to year, and also help optimize their emissions performance by allowing them to better estimate the emissions impact of individual carriers. 2.0 Tool Inputs and Calculations After logistics companies enter their company and contact information, they provide basic information about each company they operate, including name, SCAC, MCN, NSC, and US DOT Number. Logistics companies then identify each carrier that they use for each logistics business unit. Next, users proceed to input activity data for each carrier specified. Emission Inventory and Performance Metric Calculations After inputting the required mileage and/or ton-mile information for each carrier used, the Tool will calculate the associated total mass emissions (i.e., an emissions inventory) based on the mileage-related activity data entered, as well as various emission performance metrics (e.g., composite grams/mile and grams/ton-mile - see below). The Tool offers two options for calculating mass emissions, based on either the annual mileage or ton-mileage data that logistics companies enter for each carrier. We encourage logistics companies to select the unit of activity data that is most appropriate for characterizing each carrier type (e.g., use grams per mile for TL and grams per ton- mile for LTL, package, and multimodal / rail). The emissions inventory for each carrier/mode combination displayed on the Emissions Summary, Carrier Performance, and SmartWay Category Details screens is calculated by multiplying the appropriate unit of activity data (i.e., truck, air or barge miles, railcar-miles, or ton-miles) by the corresponding carrier emissions performance data. To calculate composite, business unit-wide emissions performance metrics on the Carrier Performance screen (i.e., overall g/mile and g/ton-mile performance), the Tool weights the emissions performance of each of the logistics 1 While this Tool is primarily focused on freight movements in the U.S. rail, air, barge and trucking freight sectors, SmartWay anticipates providing performance data for ocean-going marine freight in the future as well. 3 ------- business unit's carriers by the percentage of the business unit's overall freight activity that the carrier moves. An example composite performance calculation is provided below. Table 1. Example Compositing Calculation CO2 g/mi Mi/yr Weighting Factor Weighted CO2 g/mi Carrier 1 1,700 2,000,000 0.667 1,134 (0.667 x 1,700) Carrier 2 1,500 1,000,000 0.333 500 (0.333 x 1,500) Weighted composite g/mi 1,633(1,134 + 500) This compositing process proceeds in an identical fashion for ton-miles. Note that the composite emissions performance values are the numbers that will be used to place logistics partners into performance bins within the logistics category. Ton-Mile Calculation Correctly calculating Ton-Miles is critically important for the accurate determination of your carbon foot-print. You can calculate your business unit's ton-miles as follows. Determine the ton-miles hauled per year attributable to each carrier. A ton-mile is one ton moving one mile. DO NOT ESTIMATE TON-MILES BY SIMPLY MULTIPLYING TOTAL MILES BY TOTAL TONS - this calculation effectively assumes your entire tonnage is transported on EACH AND EVERY truck, railcar, aircraft, or barge, and will clearly overstate your ton-miles. Many companies track their ton-miles and can report them directly without further calculation. For example, logistics company systems are typically set up to associate a payload with the mileage traveled on each trip by carrier, and are then summed at the end of the year. If such information is not available, there are two ways to calculate ton- miles: 1) Companies can determine their average payload per carrier, multiply the average payload by the total miles per carrier, and sum the results for all carriers for the reporting year; or (total miles per carrier x total tons per carrier) 2) Set Ton-miles per carrier = total # of trips per carrier NOTE: Empty miles are not included in the ton-mile calculation, but the fuel used to 4 ------- move those empty miles are included in the overall g/ton-mile calculations. To check your estimate, divide ton-miles by miles. The result is your fleet-average payload. If this number is not reasonable, please check your calculations. Carrier Emissions Performance Data The current SmartWay program provides CO2, NOx and PM gram per mile and gram per ton-mile emission factors for truck, barge, air, and rail freight transport providers. These data are provided in the SmartWayCarrierData2017.xls file, which should be downloaded to the user's computer using the appropriate button on the Tool's Home page. Performance data for truck, barge, air,2 and multimodal partners correspond to data submittals for the 2017 calendar year, while current Logistics partner performance may correspond to submittals for 2016, depending on whether the 2017 data year performance information for logistics companies has been released at the time of tool download. (Within a given data year, logistics tools are released after the multimodal tool.) Performance for Rail companies are modal averages, based on publicly available R-1 data. Truck Carrier Performance Truck carrier performance data utilized by the Logistics Tool is based on 2017 Truck Partner Tool submittals. Performance data includes g/mile and g/ton-mile for each truck carrier by SmartWay Category, with a top ranking indicating the top 20 percent performance level for a given pollutant/performance category. Note that g/mile and g/ton-mile values represent midpoints for the appropriate SmartWay Category, rather than exact performance levels for a given carrier. Truck SmartWay Categories include: TL Dry Van LTL Dry Van Refrigerated Flatbed Tanker Dray Heavy/Bulk Package Auto Carrier Moving Specialized Mixed Expedited The following provides an overview of the truck carrier ranking process used to estimate the carrier-specific performance bins. 2 As of 5-25-2018 no air carrier data had been approved by SmartWay. 5 ------- Truck Performance Ranking In the SmartWay Truck Tool, data is collected at the individual company fleet level. Fleets are characterized by A.) business type: for-hire or private, B.) operational type: truckload/expedited, less than truckload, dray, package delivery, or expedited, and C.) equipment type: dry van, refrigerated van, flatbed, tanker, heavy/bulk, chassis (container), auto carrier, moving, utility, or specialized (e.g., hopper, livestock, other). The possible categories are shown below. For-Hire Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk Auto Carrier Moving Specialized TL LTL PD Expedited Dray Private Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk Auto Carrier Moving Specialized TL LTL PD Expedited Dray Note that while Specialized fleets have disparate operations/equipment types and thus do not compare well, they are also unlikely to compete with one another, so it was deemed acceptable to aggregate these disparate fleets into one category. For-hire and private fleets are combined in SmartWay categories. There are relatively few private fleets compared to for-hire fleets. Because owners of private fleets generally hire their own fleets exclusively, it was determined that ranking for-hire and private fleets together would not be detrimental to for-hire fleets, and the simplicity of one for- hire and private category outweighed the benefits of listing fleets separately. Ranking for-hire and private separately would have doubled the number of categories. Therefore the fleets can thus be categorized as shown below. 6 ------- For Hire / Private Dry Van Reefer Flatbed Tanker Chassis Heavy/Bulk Auto Carrier Moving Specialized TL LTL PD Expedited Dray To be categorized in a particular category, a fleet must have at least 75% of its operations by mileage in a single category, otherwise it is classified as a "Mixed" fleet. Fleets could be mixed via their operational or equipment type. Fleets are generally segregated by their operational type, but some mixing does occur via equipment type, especially with smaller carriers that do not differentiate their fleet. Fleets that do not have 75% of their operations in a specific category are placed in the Mixed category. Individual fleets were then placed into categories. The following graphic illustrates the population of the various categories. The darker the shade of the intersection, the higher the number of fleets in that category. Dry Reefer Flatbed Tanker Chassis Heavy Auto Moving Specialized Mixed Van /Bulk Carrier TL LTL PD Expedited Dray Mixed SmartWay then looked at combining categories that exhibited similar characteristics for simplification purposes. One prerequisite was that there needed to be a minimum number of fleets in each category. SmartWay determined that a category needed a minimum of 25 fleets to be created. It was also determined that dry van and chassis (intermodal container) functioned primarily as dry van transport, so these categories were combined. While most refrigerated carriers were truckload, a few less than truckload refrigerated fleets exist, so these two categories were combined. A similar situation was identified with flatbed, and flatbed truckload and less than truckload were combined. Although no less than truckload tanker fleets were identified, tanker truckload and less than truckload were combined into one category so that no intersections would be left undefined. Similar aggregations were made for the remaining, less common body types including heavy/bulk, auto carrier, moving and specialized. All dray was collapsed into one category, and package delivery was restricted to dry van body types. Any fleet that had mixed operation and/or mixed equipment was placed into a single mixed category. Finally, logistics and multimodal fleets were also included and retained as unique categories. 7 ------- The final performance categories for the 2017 Data Year are illustrated below. The solid colors indicate how operation and equipment type assignments vary by performance category. For example, if 75% or more of a fleet's mileage is associated with reefer trucks, the fleet is assigned to the Reefer category regardless of the operation percentage across truckload, expedited, LTL, and package categories. However, the Reefer category assignment is overridden if the operation category is greater than or equal to 75% dray, logistics, or multimodal. Similar assignment rules apply to flatbed, tanker, heavy/bulk, auto carrier, moving, and specialized equipment types. Only the Dry Van/Chassis equipment category is subdivided by the truckload, expedited, LTL, and package operation categories, meaning that the 75% threshold must be met for both equipment and operation type in these cases. All other equipment/operation type percentage distributions are assigned to the Mixed category. Figure 1. SmartWay Carrier Categories and Data Specificity - 2017 Calendar Year TRUCK Dry Van Heavy Auto Specialized & Chassis Reefer Flatbed Tanker & Bulk Carrier Moving & Utility Mixed Dray Dray 5 Performance Levels Truckload Truckload DryVan 5 Performance Levels Reefer Flatbed Tanker Heavy Auto Moving Specialized Mixed Expedited Expedited & Bulk Carrier & Utility 5 Performance Levels 5 5 5 5 5 5 5 5 LTL LTL Performance Performance Performance Performance Performance Performance Performance Performance 5 Performance Levels Levels Levels Levels Levels Levels Levels Levels Levels Package Package Delivery 5 Performance Levels Less than 75% Mixed Mixed in any category Rail Single Modal Average for All Rail (No company differentiation allowed per Association of American Railroads) Barge Company Specific Data Air Company Specific Data Logistics 5 Performance Levels Emission Factor Data Only (No 5 Performance Level Ranking) Multimodal Marine To Be Determined (Proposed availability in 2016 calendar year) It is possible that SmartWay will expand these categories based on in-use experience or as a result of further data analysis, and/or requests from industry. 8 ------- Companies within a category have been ranked from lowest emission factor (best) to highest emission factor (worst) for each of the following metrics: CO2 g/mile, CO2 g/ton- mile, NOx g/mile, NOx g/ton-mile, PM10 g/mile and PM10 g/ton-mile. Companies within a category were then separated into five groups (rankings) such that an equal number of companies were in each. Each ranking category thus represents a range of emission factors. This range, and associated cutpoints (transition points from one ranking category to the next) were then modified so that each bin had an equal range, and the new ranking category cutpoints remained as close to the originals as possible. The new range cutpoint is displayed as a number with significant digits appropriate to emission factors in that category. The midpoint of the range is used as the emission factor for all companies in a ranking category. It would be simpler and more straightforward to use company-specific emission factors, however the trucking industry expressed concern with revealing exact data that could be used to back-calculate mile per gallon numbers. The above described methodology prevents a determination of an exact mpg figure, while at the same time attributing an emission factor much more exact than a modal default number. Given the large number of trucking companies, and thus opportunity for companies to be very close to each other in performance (for example 0.001 g/mile of CO2), SmartWay believes it is acceptable and appropriate to break truck fleets into 5 performance rankings. The table below illustrates the ranking results for the For Hire/Private Truckload/Expedited Dry Van/Container category, using 2010 truck partner data. The table below illustrates the ranges in the For Hire/Private Truckload/Expedited Dry Van SmartWay Category, using 2013 Truck Partner data as an example. Table 2. Emission Factor Ranges for One Performance Category (2013 Data) For-Hire/Private Truckload/ Dry Van CO2 g / mile Group ID Fleets Per Bin Grams Per Mile Min Grams Per Mile Max Grams Per Mile Avg Grams Per Mile Midpoint Grams Per Mile Std Dev 1 186 944 1,549 1,452 1,500 118 2 227 1,551 1,650 1,601 1,600 28 3 194 1,651 1,749 1,692 1,700 29 4 140 1,751 1,848 1,798 1,800 29 5 115 1,851 5,090 2,010 1,900 359 Similar tables were developed for all categories. The midpoint of each ranking category is the data that a logistics company will download into their SmartWay Logistics Tool to represent the emission performance of a specific carrier fleet that is in the associated rank category. Once the categories and ranks have been established, the carrier fleets of any new companies joining SmartWay will fall into one of the predefined categories/ranks. SmartWay expects to update the category/ranks structure approximately every three years. 9 ------- The Non-SmartWay performance metrics were calculated by taking the standard performance rank range delta (m in/max) for each ranking category, and using the delta to calculate a non-SmartWay carrier midpoint for each category. This midpoint was the midpoint for Rank 5 plus the standard range delta. For example, if the Rank 5 midpoint was 10.5 and the Ranking Categories standard delta was 1, then the non-SmartWay midpoint was calculated to be 11.5. Once the non-SmartWay midpoints for each pollutant were calculated for all SmartWay Categories, the non-SmartWay performance metric was calculated by using the average value of these mid-points, weighted by the number of fleets in each category. This approach does not require the shipper to identify the appropriate SmartWay Category for their Non-SmartWay carrier(s), which they may not know, while still ensuring that the performance of their non-SmartWay carriers reflects the distribution of the different categories within the truck population. Depending upon the type of data available for a given carrier, the user may input ton- miles or miles, and rely on carrier data to back-calculate the other value. For example, providing ton-miles and average payload allows the tool to estimate total miles, by dividing the former by the latter. Alternatively, freight density and cargo volume utilization information can also be used to estimate average payloads. For this reason, average payload and volume information are provided for each carrier in the SmartWayCarrierData2017.xls file.3 For Non-SmartWay truck carriers, the values for average payload (18.7 tons) and average volume (3,260 cubic feet) were derived from the average values for all Truck Partners (2011 data), weighted by miles. Logistics and Multimodal Carrier Performance Logistic and multimodal carriers have their own performance bins based on the carrier tool submittals for the most recent available calendar year (2016 for logistics, and 2017 for multimodal). Multimodal carrier categories are also differentiated by mode combinations, including Surface;4 Surface-Air; Surface-Marine; and Surface-Air-Marine. Multimodal composite fleets with 10% or more of their ton-miles coming from air or marine carriers are designated Surface-Air/Marine.5 Non-SmartWay carrier performance for these SmartWay Categories is estimated in the same way as is done for non- SmartWay Truck carriers (i.e., averaging the bin midpoints to calculate a fleet average value). If a composite fleet does not meet the above Multimodal designation criteria, and if it has 75% of its ton-miles derived from one or more Logistics component fleets, then the composite fleet is binned as a Logistics fleet. Alternatively, if the composite fleet does not meet either of the two above criteria, then it is binned as a Truck fleet. 3 The Logistics Tool also calculates average payload and average volume for each logistics fleet defined by the user, weighting carrier payloads and volumes by the miles assigned on the Tool Activity screen. The resulting average payload and volume figures will be included in subsequent updates to the SmartWay Carrier file for use by Shippers and Logistics companies. 4 Surface multimodal carriers utilize road and rail modes. 5 Air and/or marine carriers may be utilized directly by the multimodal carrier, or may be utilized indirectly by logistics business units hired by the multimodal carrier. 10 ------- Air and Barge Carrier Performance Air and barge carriers have agreed to have their actual emissions results made public, and, barge performance values used in the Logistics Tool are carrier-specific. The gram per mile performance values for barge carriers correspond to individual barge (nautical) miles travelled, rather than miles travelled by a string of barges or the associated tug(s). Non-SmartWay barge carrier gram per mile and gram per ton-mile performance is set to be 25% higher than the worst performing SmartWay barge carrier. Since no air carrier data submittals have been approved as of this date, performance levels for non-SmartWay air freight are based on publicly available data. First upper bound estimates for grams of CO2 per ton-mile were obtained for short and long-haul air freight (~4,236 g/t-mi and ~1,461 g/t-mi, respectively).6 7 Values for CO2 g/mile were calculated by multiplying the g/t-mi value by an average cargo payload value of 22.9 short tons. The average payload value was estimated by dividing total airfreight tonnage in 2012 (15M tons)8 by the total number of cargo departures in the same year (654,956 LTOs).9 Corresponding performance metrics for NOx and PM10 were based on the ratio of these pollutants to C02from the EDMS 5.1.4.1 model (0.009 for NOx and 0.000059 for PM10).10 The resulting performance metrics are shown in Table 3 below. An average cargo volume estimate was also obtained for inclusion in the SmartWay carrier data file based on the volume for a typical freight aircraft, the Boeing 747 200 series (5,123 cubic feet).11 Table 3. Assumed Performance Metrics for Non-SmartWay Air Carriers C02/tmi C02/mi NOx/mi NOx/tmi PM/mi PM/tmi Short-haul 4,236 96,998 873.2713 38.1341 5.743247 0.250797 Long-haul 1,461 33,448 301.1280 13.1497 1.980430 0.086482 6 Short haul air freight assumed to be less than 3,000 miles, covering most domestic air routes in the U.S. 7 Estimates from Figure 8.6 in Sims R., R. Schaeffer, F. Creutzig, X. Cruz-Nunez, M. D'Agosto, D. Dimitriu, M. J. Figueroa Meza, L. Fulton, S. Kobayashi, O. Lah, A. McKinnon, P. Newman, M. Ouyang, J. J. Schauer, D. Sperling, and G. Tiwari, 2014: Transport. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlomer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 8 U.S. DOT Bureau of Transportaion Statistics, Freight Facts and Figures 2013. http://www.ops.fhwa.dot.gov/freight/freight analvsis/nat freight stats/docs/13factsfigures/pdfs/ITOO 13 highres.pdf . Accessed 5-25-18. 9 U.S. DOT, Bureau of Transportation Statistics, U.S. Air Carrier Traffic Statistics.: https://www.transtats.bts.gov/TRAFFIC/. Accessed 5-25-18. 10 EDMS outputs for take-off mode, assumed to be equal to cruising mode. (Cruise emissions are not output by EDMS). Take-off mode emission rates were averaged across all aircraft/engine combinations in the Heavy (Max Takeoff Weight over 255,000 lbs) and Large (Max Takeoff Weight 41,001 to 255,000 lbs) weight classes. 11 Aircraft Cargo Plane Specifications, http://www.airgroup.com/standalonc.php?action=air spec. Accessed 5-25- 18. 11 ------- Rail Carrier Performance All rail carriers are assumed to have the same industry modal average performance levels in the Logistics Tool, regardless of Partnership status. Rail carrier performance data are collected and displayed in the Logistics Tool at the industry average level derived from Class 1 rail company data. Gram per ton-mile factors were determined by dividing total fuel use by total ton-miles and multiplied by a rail diesel CO2 factor (10,084 g C02/gal diesel fuel), from publicly available data submitted in the 2010 railroad R-1 reports to the Department of Transportation. 2010 R-1 data was also used to obtain total railcar-miles per year for all Class 1 carriers, in order to estimate gram per railcar- mile factors. Industry average values are currently assumed for all rail carriers in the carrier data file. Specific rail companies may have an opportunity to provide company- specific data in the future. The R-1 data and corresponding CO2 performance data are presented in Table 4 below. Table 4. Rail Carrier Performance Metric Calculation Inputs and Results (2010 R-1 Data) Gal/Yr Freight Ton- Railcar-Mi/Yr g CCVrailcar- g CCVshort ('OOO)Sch. 750 Line 4 Mi/Yr ('000) Sch .755 line 110 ('000) Sch. 755 sum of lines 30, 46, mile ton-mile Rail Company 64 & 82 BNSF Railway 1,295,147 646,549,059 11,230,994 1,163 20.20 CSX Transportation 490,050 230,507,431 4,720,293 1,047 21.44 Grand Trunk 88,290 50,586,328 1,206,818 738 17.60 Kansas City Southern 62,354 31,025,588 609,929 1,031 20.76 Norfolk Southern* 440,159 183,104,320 4,081,893 1,087 24.24 Soo Line 65,530 33,473,544 771,033 857 19.74 Union Pacific 1,063,201 525,297,747 10,336,081 1,037 20.41 Total - Industry 3,504,731 1,700,544,017 32,957,041 1,072 20.78 Average * and combined subsidiaries NOx and PM emission factors for rail carriers are based on industry averages. Freight rail gC02/ton-mile factors were developed using 2008 inventory data from EPA's Inventory of U. S. Greenhouse Gas Emissions and Sinks (1990-2008),12 which is based on Class I rail fuel consumption data from the Association of American Railroads and estimates of Class II and III rail fuel consumption by the American Short Line and Regional Railroad Association. This emissions inventory was divided by the rail ton-mile data (2007) presented in Table 1-46b in the Bureau of Transportation Statistics' (BTS) 12 U.S. EPA, 2010. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990- 200&, WashingtonDC (EPA 430-R-10-006). Total freight rail GHG emissions are presented in Table A-l 10 of the inventory. Table 10 in this document presents CCh-only data. In order to isolate the CCh-only emissions data, we accessed spreadsheets that are not publicly available. 12 ------- National Transportation Statistics,13 which is intended to encompass all freight rail ton- miles, including Classes I, II, and III. The freight rail g NOx/ton-mile and g PM2.5/ton-mile factors were developed with 2010 inventory data from Tables 3-82 and 3-83, respectively, in EPA's 2008 Regulatory Impact Analysis for a locomotive diesel engine rule.14 This inventory data represents 2010 emission projections for all U.S. rail except for passenger and commuter rail (i.e., large line-haul, large switch, and small railroads), which EPA determined would very closely align with the freight rail sector. This emissions inventory data was then divided by the 2007 R-1 ton-mile data. EPA developed the industry average freight rail g/mile factors by using 2008 railcar mileage data from lines 15 through 81 of R-1 forms that Class I railroad companies submitted to the Surface Transportation Board.15 The railcar miles were then converted into "truck-equivalent" railcar miles by estimating the average volume capacity of Class I railcars and dividing that by an average freight truck volume capacity. This results in a very crude estimate that does not take into consideration the utilized volume of railcars or the comparative freight truck, but EPA determined that this was the best available data and method to estimate modal average truck-equivalent railcar miles. To estimate the industry average volume capacity of Class I railcars, the railcar miles reported by each company for each railcar type in their respective 2008 R-1 reports (lines 15-81) were multiplied by the volume-per-railcar assumptions in Table 8 below to obtain total Class I TEU-miles. EPA then divided the total railcar TEU-miles by the total railcar miles to estimate the industry average railcar volume capacity. Finally EPA divided this average railcar volume capacity (3.92) by the average freight truck volume capacity (2.78 TEUs) to develop the conversion factor -1.41 railcar-miles-to-truck-miles. EPA developed the NOx and PM emission estimates using the average 2010 locomotive g PMio/gal and g NOx/gal factors from EPA's 2009 Technical Highlights: Emissions Factors for Locomotives (see Tables 5 and 6, respectively).16 To calculate g PIVte.s/gal, we assumed 95% of PM10 is PM2.5, which we determined was a good approximation of the share of overall PM10 emissions represented by particulate matter that is 2.5 micrometers in diameter or smaller. Table 5 below presents the industry-average freight rail NOx and PM emissions factors in the tool and Table 6 presents the key underlying data. 13 U.S. DOT, Research and Innovative Technology Administration, Bureau of Transportation Statistics, 2009. National Transportation Statistics, Table l-46b - U.S. Ton-Miles of Freight (BTS Special Tabulation) (Updated September 2009). https://www.bts.gov/bts-publications/national-transportation-statistics/national-transpoitation- statistics-previous. Accessed 5-25-18. 13 ------- Table 5. Illustrative U.S. Freight Rail Industry Average Factors NOx PM2.5 gram/short ton-mile 0.4270 0.0120 gram/truck-equivalent mile 13.19 0.3569 gram/TEU-mile 4.745 0.1284 Table 6. Underlying Emissions Inventories and Activity Data for Illustrative U.S. Freight Rail Industry Average Factors short ton-miles 1,819,633,000,000 Class l-only railcar miles (total) 34,611,843,000 50' and Larger Box Plain + Box Equipped 2,223,402,000 40' Box Plain 22,000 Flat TOFC/COFC, General, and Other 5,057,466,000 Flat Multi Level 1,725,998,000 Gondola Plain and Equipped 7,893,684,000 Refrigerated Mechanical and Non-Mechanical 495,311,000 Open Top Hopper General and Special Service 5,913,012,000 Covered Hopper 7,210,656,000 Tank under 22,000 gallons 1,295,482,000 Tank 22,000 gallons and over 2,394,565,000 All Other Car Types 402,245,000 Average payload per loaded railcar were calculated for all Class 1 carriers by dividing the value for annual ton-miles hauled by an estimate for loaded railcar-miles, based on 2008 R-1 data. The calculation uses the Total Revenue and Non-Revenue Ton-Miles as listed In the R-1 Report on line 114 of schedule 755 divided by the Total loaded Railcar- Miles (the sum of lines 30 and 64 of schedule 755) along with the factor for fuel gallons consumed for loaded freight that is created based on the percentage of loaded freight to total freight multiplied by the total diesel fuel value listed on schedule 750 Line 4. The following table summarizes the estimated average payload per railcar, by carrier. Table 7. Rail Carrier Average Payload Carrier Avg Payload/Loaded Railcar (tons) BNSF Railway 108 CSX Transportation 85 Grand Trunk 80 Kansas City Southern 91 Norfolk Southern 76 Soo Line 77 Union Pacific 91 Industry Average 93 14 ------- Average railcar volumes were calculated for all carriers by first estimating an average volume for each major railcar type listed in the R-1 forms (schedule 755, lines 15-81). The assumptions used to estimate these volumes are provided in Table 8 below. The railcar-miles reported for each railcar type were multiplied by these average volumes to estimate annual cubic foot-miles travelled by car type for each company and for the industry average. The distribution of cubic foot-miles across car types was used as the weighting factor to estimate a single average railcar volume for each company. These values and the resulting volume estimates are presented in Table 9 below. Table 8. Railcar Volume Assumptions and Sources Railcar Type Cubic Feet Source/Method Boxcar 50 ft and longer including equipped boxcars 7,177 Based on the average of the following boxcar types: 50ft assumed to be 5694 [reflecting the average of 5355 (NS), 5431 (UP), 5238 (CSX), 6175 (BSNF), 6269 (GTRC)]. 60ft assumed to be 6,648 [reflecting the average of 6618 (NS), 6389 (UP), 6085 (CSX), 7500 (BNSF)]. 50ft hiah cube assumed to be 6.304 Treflectina the averaae of 6339 (NS) and 6269 (CSX)]. 60 ft hiah cube assumed to be 6917 Treflectina the averaae of 7499 (NS). 6646 (CSX), and 6607 (GTRC)]. 86ft assumed to be 9999 (NS). Autoparts assumed to be 7499 (NS). Boxcar 40ft 4,555 Based on estimate of 50ft boxcar volume described above. Assumed 40ft length would result in 20% reduction in volume. Flat car - all types except for multi-level 6,395 Based on the average of the following flat car types: 60ft assumed to be 6739 (BNSF). 89ft assumed to be 9372(BNSF). Coil assumed to be 3387(NS). Covered coil assumed to be 5294 Treflectina the averaae of 8328 (NS) and 2260 (BNSF)]. Centerbeam assumed to be 6546 Treflectina the averaae of 5857 (UP) and 7236 (BNSF)]. Bulkhead assumed to be 7030 (BNSF). Multi-level flat car 13,625 Based on the average of the following multi-level flat car types: Unilevel (that carrv verv larae carao. such as vehicles/tractors) assumed to be 12183 (NS). Bi-level assumed to be 1438KNS). Tri-level assumed to be 14313 (based on averaae of 15287 (NS) and 13339 (BNSF). Flat Car - all types- including multi-level [not used in analysis, except for estimating volume of "All Other Cars"] 7,428 Based on the average volumes of the flatcar types described above including multi-level as a single flat car type. Gondola - all types Including equipped 5,190 Based on the average of the following gondola car types: 52-53ft assumed to be 2626 Tbased on averaae of 2665 (NS). 2743 (CSX). 2400 (BNSF), and 2697(CRLC)]. 60-66ft assumed to be 3372 Tbased on averaae of 3281 (NS). 3242 (CSX). 3350 (BNSF), CRCL-3670, and 3366 (GTRC)]. Municipal Waste assumed to be 7999 (NS). WoodchiD assumed to be 7781 Tbased on averaae of 7862 (NS) and 7700 (CRCL)]. Coal assumed to be 4170 [based on average of 3785 (NS) and 4556 (BNSF)]. 15 ------- Railcar Type Cubic Feet Source/Method Refrigerated - Mechanical /non- Mechanical 6,202 Based on the average of the following refrigerated car types: 48-72ft assumed to be 6963 Tbased on averaqe of 6043 (UP) and 7883 (BNSF)]. 50ft assumed to be 5167(GTRC). 40-90 ft. assumed to be 6476 Tbased on averaae of 6952 (UP) and 6000 (BNSF)l. Open Top Hopper 4,220 Based on the average of the following open top hopper car types: 42ft assumed to be 3000 (UP). 54ft assumed to be 3700 (UP). 60ft assumed to be 5188 [based on average of 5125 (UP) and 5250 (GTRC)]. 45ft+ assumed to be 4105 Tbased on averaae of 4500 (UP) and 3710 (BNSF). WoodchiD assumed to be 7075 Tbased on averaae of 7525 (NS). 5999 (UP), and 7700 (CRCL)]. Small Aaareaate assumed to be 2252 Tbased on averaae of 2150 (NS). 2106 (BNSF), and 2500 (CRCL)l. Covered Hopper 4,188 Based on the average of the following covered top hopper car types: 45ft assumed to be 5250 (GTRC). Aaareaate assumed to be 2575 Tbased on averaae of 2150 (NS) and 3000 (CRCL)]. Small Cube Gravel assumed to be 2939 Tbased on averaae of 2655 (NS). 3100 (CSX), and 3063 (BNSF). Med-Larae Cube Ores and Sand assumed to be 4169 Tbased on averaae of 3750 (NS) and 4589 (BNSF)]. Jumbo assumed to be 5147 fbased on averaae of 4875 (NS). 4462 (CSX). 5175 (BNSF), and 6075 (CRCL)]. Pressure Differential (flour) assumed to be 5050 Tbased on averaae of 5124 (NS) and 4975 (CRCL)l. Tank Cars under 22,000 gallons 2,314 Assumes 1 gallon=0.1337 cubic foot (USDA). Based on small tank car average volume of 17304 gallons, which is the average of the following currently manufactured tank car volume design capacities of 13470, 13710, 15100, 15960, 16410,17300,,19900, 20000, 20590, and 20610 gallons (GTRC). Tank Cars over 22,000 gallons 3,857 Assumes 1 gallon=0.1337 (USDA). Based on large tank car volume of 28851 gallons, which is the average of the following currently manufactured tank car volume design capacities of 23470, 25790, 27200, 28700, 30000, 33000, and 33800 gallons (GTRC). All Other Cars 5,014 Based on average volume presented above for each of the nine railcar types (all flatcars are represented by the line item that includes multi-level flatcars - 7428). Key: Norfolk Southern Railroad (NS)17, Union Pacific Railroad (UP)18, Burlington Northern Santa Fe Railroad (BNSF)19, CSX Transportation Railroad (CSX)20, World Trade Press Guide to Railcars (GTRC)21, Chicago Rail Car Leasing (CRCL)22, Union Tank Car Company (UTCC)23, U.S Department of Agriculture (USDA)24 17 Norfolk Southern Shipping Tools/Equipment Guide/Merchandise Equipment. http://www.nscorp.com/content/nscorp/en/shipping-tools/equipment-guide/merchandise-equipment.html. Accessed 5-25-18. 18 UP Rail Equipment Descriptions, https://www.uprr.com/customers/eauip-resources/cartvpes/index.shtml. Accessed 5-25-18. 19 BNSF Individual Railcar Equipment, http://www.bnsf.com/ship-with-bnsf/ways-of-shipping/individual- railcar.html#subtabs-3. Accessed 5-25-18. 20 CSX Railroad Equipment, https://www.csx.com/index.cfm/customers/resources/eauipment/railroad-eauipment/. Accessed 5-25-18. 21 World Trade Press, World Trade Resources Guide to Railcars 2010. 22 Chicago Freight Car Leasing Company, Railcar Types. http://www.crdx.com/Services/Railcar. Accessed 5-25-18. 23 UTLX Tank Car Designs and Descriptions, http://www.utlx.com/bdd tank.html. Accessed 5-25-18. 24 U.S. Department of Agriculture (USDA), 1992, Weights, Measures, and Conversion Factors for Agricultural Commodities and Their Products, Agricultural Handbook Number 697, Economic Research Service, Washington, DC. https://www.ers.usda.gov/webdocs/publications/41880/33132 ah697 002.pdf?v=42487. Accessed 5-25-18. 16 ------- Table 9. Rail Carrier Average Volume Determination BNSF Freight Car Types (R1 - Schedule 755) Avg. Cu Ft. Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 4,555 1 4,555 Box-Plain 50-Foot & Longer 7,177 9,338 67,018,826 Box-Equipped 7,177 147,226 1,056,641,002 Gondola-Plain 5,190 379,762 1,970,964,780 Gondola-Equipped 5,190 75,894 393,889,860 Hopper-Covered 4,188 758,442 3,176,355,096 Hopper-Open Top-General Service 4,220 65,077 274,624,940 Hopper-Open Top-Special Service 4,220 137,449 580,034,780 Refrigerator-Mechanical 6,202 19,272 119,524,944 Refrigerator-Non-Mechanical 6,202 32,910 204,107,820 Flat-TOFC/COFC 6,395 520,521 3,328,731,795 Flat-Multi-Level 13,625 38,624 526,252,000 Flat-General Service 6,395 357 2,283,015 Flat-All Other 6,395 71,826 459,327,270 All Other Car Types-Total 5,772 20,146 116,282,712 Average Railcar Cubic Feet 5,811 17 ------- CSX Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot - - Box-Plain 50-Foot & Longer 6,987 50,145,699 Box-Equipped 144,631 1,038,016,687 Gondola-Plain 137,256 712,358,640 Gondola-Equipped 64,532 334,921,080 Hopper-Covered 153,315 642,083,220 Hopper-Open Top-General Service 78,412 330,898,640 Hopper-Open Top-Special Service 35,451 149,603,220 Refrigerator-Mechanical 17,117 106,159,634 Refrigerator-Non-Mechanical 11,923 73,946,446 Flat-TOFC/COFC 125,828 804,670,060 Flat-Multi-Level 29,956 408,150,500 Flat-General Service 162 1,035,990 Flat-All Other 31,913 204,083,635 All Other Car Types-Total 19,861 114,637,692 Average Railcar Cubic Feet 6,389 18 ------- Grand Trunk Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 0 - Box-Plain 50-Foot & Longer 2,119 15,208,063 Box-Equipped 66,110 474,471,470 Gondola-Plain 6,467 33,563,730 Gondola-Equipped 19,201 99,653,190 Hopper-Covered 44,239 185,272,932 Hopper-Open Top-General Service 9,114 38,461,080 Hopper-Open Top-Special Service 32,621 137,660,620 Refrigerator-Mechanical 312 1,935,024 Refrigerator-Non-Mechanical 205 1,271,410 Flat-TOFC/COFC 2,779 17,771,705 Flat-Multi-Level 4,831 65,822,375 Flat-General Service 20 127,900 Flat-All Other 31,744 203,002,880 All Other Car Types-Total 4,755 27,445,860 Average Railcar Cubic Feet 6,309 19 ------- Kansas City Southern Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 0 - Box-Plain 50-Foot & Longer 3,383 24,279,791 Box-Equipped 39,792 285,587,184 Gondola-Plain 16,628 86,299,320 Gondola-Equipped 11,150 57,868,500 Hopper-Covered 50,346 210,849,048 Hopper-Open Top-General Service 626 2,641,720 Hopper-Open Top-Special Service 943 3,979,460 Refrigerator-Mechanical 21 130,242 Refrigerator-Non-Mechanical 52 322,504 Flat-TOFC/COFC 10,736 68,656,720 Flat-Multi-Level 629 8,570,125 Flat-General Service 12 76,740 Flat-All Other 2,321 14,842,795 All Other Car Types-Total 247 1,425,684 Average Railcar Cubic Feet 5,938 20 ------- Norfolk Southern Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 0 - Box-Plain 50-Foot & Longer 7,622 54,703,094 Box-Equipped 136,745 981,418,865 Gondola-Plain 193,214 1,002,780,660 Gondola-Equipped 111,320 577,750,800 Hopper-Covered 116,848 489,359,424 Hopper-Open Top-General Service 84,557 356,830,540 Hopper-Open Top-Special Service 30,078 126,929,160 Refrigerator-Mechanical 3,512 21,781,424 Refrigerator-Non-Mechanical 5,392 33,441,184 Flat-TOFC/COFC 114,928 734,964,560 Flat-Multi-Level 20,349 277,255,125 Flat-General Service 145 927,275 Flat-All Other 24,563 157,080,385 All Other Car Types-Total 212,408 1,226,018,976 Average Railcar Cubic Feet 6,065 21 ------- Soo Line Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 0 - Box-Plain 50-Foot & Longer 725 5,203,325 Box-Equipped 17,972 128,985,044 Gondola-Plain 1,203 6,243,570 Gondola-Equipped 8,856 45,962,640 Hopper-Covered 94,146 394,283,448 Hopper-Open Top-General Service 3,077 12,984,940 Hopper-Open Top-Special Service 20 84,400 Refrigerator-Mechanical 159 986,118 Refrigerator-Non-Mechanical 742 4,601,884 Flat-TOFC/COFC 11,178 71,483,310 Flat-Multi-Level 2,973 40,507,125 Flat-General Service 12 76,740 Flat-All Other 10,068 64,384,860 All Other Car Types-Total 428 2,470,416 Average Railcar Cubic Feet 5,667 22 ------- Union Pacific Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 0 - Box-Plain 50-Foot & Longer 12,311 88,356,047 Box-Equipped 238,241 1,709,855,657 Gondola-Plain 206,370 1,071,060,300 Gondola-Equipped 91,775 476,312,250 Hopper-Covered 370,929 1,553,450,652 Hopper-Open Top-General Service 188,027 793,473,940 Hopper-Open Top-Special Service 104,969 442,969,180 Refrigerator-Mechanical 82,874 513,984,548 Refrigerator-Non-Mechanical 27,009 167,509,818 Flat-TOFC/COFC 1,026,251 6,562,875,145 Flat-Multi-Level 46,889 638,862,625 Flat-General Service 350 2,238,250 Flat-All Other 72,371 462,812,545 All Other Car Types-Total 16,769 96,790,668 Average Railcar Cubic Feet 6,248 23 ------- Total (for Industry Average) Freight Car Types (R1 - Schedule 755) Railcar Miles (xlK) Cu Ft Miles (xlK) Box-Plain 40-Foot 1 4,555 Box-Plain 50-Foot & Longer 42,485 304,914,845 Box-Equipped 790,717 5,674,975,909 Gondola-Plain 940,900 4,883,271,000 Gondola-Equipped 382,728 1,986,358,320 Hopper-Covered 1,588,265 6,651,653,820 Hopper-Open Top-General Service 428,890 1,809,915,800 Hopper-Open Top-Special Service 341,531 1,441,260,820 Refrigerator-Mechanical 123,267 764,501,934 Refrigerator-Non-Mechanical 78,233 485,201,066 Flat-TOFC/COFC 1,812,221 11,589,153,295 Flat-Multi-Level 144,251 1,965,419,875 Flat-General Service 1,058 6,765,910 Flat-All Other 244,806 1,565,534,370 All Other Car Types-Total 274,614 1,585,072,008 Average Railcar Cubic Feet 6,091 Other Carrier Modes and Metrics SmartWay plans to incorporate emission factors for ocean-going marine freight for all modes in the near future. % SmartWay Value The % SmartWay screen tracks the portion of goods that shippers move with SmartWay Partners (expressed as a percentage between 0 and 100). You may select either ton-miles or total miles as the basis for determining your % SmartWay Value. Note that the Tool will automatically populate the % SmartWay screen with any carrier activity data entered in the Activity Data screen. In addition, the metric selected for the first business unit (miles or ton-miles) will be chosen as the basis for your other business units as well, so that a company-level % SmartWay Value can be calculated. To see your company-level % SmartWay Value, calculated across all business units, go to the % SmartWay Report in the Reports Menu via the Home page. 3.0 Data Validation The Logistics Tool also contains data validation checks designed to identify missing and potentially erroneous data. At this time the only validation involves payload checks and total ton-mile checks, on the Activity Data screen. 24 ------- Pavload Validation Payload validation outpoints were set with the intention of identifying those payloads that are somewhat outside typical industry values (yellow flag warnings) and those that are far outside industry averages (red flag warnings). The payload check only apples to Data Availability selections a, b, and c where payloads are either entered by the user, or calculated based on other inputs. Checks are applied at the carrier (row) level. Payload checks are specific to the truck SmartWay Category, which is specified for each carrier in the Carrier Data File. For Truck carriers, the payload checks are consistent with the Class 8b payload checks currently in the Truck Tool, and are shown below in Table 10. (See the Truck Tool Technical Documentation for additional information.) Note that Ranges 1 and 5 are colored red in the Tool, and require explanations before proceeding. Ranges 2 and 4 are colored yellow, and explanations are optional. Table 10. Truck Carrier Payload Validation Ranges Truck Bin Category Range 1 Low Range 1 High / 2 Low Range 2 High / 3 Low Range 3 High / 4 Low Range 4 High / 5 Low Range 5 High (Max) LTL Dry Van (from Dry Van Single - LTL-Moving- Package)25 0.0 0.0 0.0 13.5 20.8 150.0 Package (from Dry Van Single - LTL-Moving- Package) 0.0 0.0 0.0 13.5 20.8 150.0 TL Dry Van (from Dry Van Single - other bins) 0.0 10.5 14.5 22.4 26.4 150.0 Refrigerated 0.0 14.5 17.3 22.9 25.7 82.5 Flatbed 0.0 14.0 18.3 26.7 31.0 99.9 Tanker 0.0 19.1 22.0 27.8 30.7 103.8 Moving (from Dry Van Single - LTL-Moving- Package) 0.0 6.9 11.0 19.1 23.2 83.7 Specialized (from Specialty - Other bins) 0.0 20.2 22.9 28.3 31.1 111.0 Dray (from Chassis) 0.0 11.2 16.5 27.1 32.4 73.5 Auto Carrier 0.0 5.7 11.0 21.4 26.6 73.5 Heavy-Bulk 0.0 2.7 16.5 44.0 57.8 120.0 25 Since LTL and package shipments can be very small, no lower-bound "red/yellow" ranges are designated for LTL and package carrier payloads. Upper bound yellow and red ranges for LTL and package (and multi-modal) carriers were set equal to the average payload (6.20) plus twice the standard deviation (7.33) for logistics companies using these carrier types (n=991 for 2013 data). 25 ------- Truck Bin Category Range 1 Low Range 1 High / 2 Low Range 2 High / 3 Low Range 3 High / 4 Low Range 4 High / 5 Low Range 5 High (Max) Utility (from Specialty - Other bins) 0.0 20.2 22.9 28.3 31.1 111.0 Mixed (from Other - Heavy- Flatbed-Mixed bins) 0.0 14.7 21.1 33.8 40.1 99.3 Expedited (from Dry Van Single - other bins) 0.0 10.5 14.5 22.4 26.4 150.0 With the exception of the LTL and package categories (which are based on 2013 data), all other logistic carrier payload validations are based on 2011 Logistics Partner data, and use simple cutoffs from the cumulative payload distribution shown in Figure 1 below. Figure 1. Logistics Partner Payload Distribution Cumulative Payload Distribution - 2011 Logistics i 0.9 I 08 '+Ļģ "§ 0.7 Q. O CL 0.6 i- 0) t 0.5 ra I 0.3 +Ļģ u 0.1 0 0 10 20 30 40 50 60 70 80 90 100 Short Tons As can be seen in the figure, the payload distribution is highly non-normal, so use of validation cutoffs based on standard deviation is not appropriate. However, rough inflection points appear at approximately 10%, 20%, 80%, and 90%. As such, these values were used to specify the following payload validation cutoffs for logistics carriers. Range 1 Red: 0-12.0 tons Range 2 Yellow: 12.0 - 16.7 tons 26 ------- Range 3: 16.7 - 21.0 tons Range 4 Yellow: 21.0 - 27.2 tons Range 5 Red: 27.2 - 150 tons (150 absolute max) Validation levels for rail and surface multimodal carriers are summarized below. The upper bound outpoints for surface multimodal payloads are based on a qualitative review of 2011 multimodal carrier tool submittals. The upper bound cutpoints for rail payloads are based on the distribution of average values estimated for Class 1 carriers (see Table 7 above). Average surface multimodal payloads less than 9.4 tons (error - red) Average surface multimodal payloads greater than 95 tons (error - red) Average railcar payloads less than 9.4 tons or greater than 125 tons (error - red) Average surface multimodal payloads between 9.4 and 15.5 tons (warning - yellow) Average surface multimodal payloads between 60 and 95 tons (warning - yellow) In addition, the absolute upper bound for rail and surface multimodal carriers have both been set at 200 tons. Multimodal carriers with an air component have their maximum allowable average payload set to 58 tons, corresponding to the maximum payload capacity for the largest aircraft make/model specified by SmartWay partners. Any payload value less than or equal to zero will be flagged as an error and must be changed. Finally, barge carrier payloads are flagged for verification if their density is greater than 0.6 tons per cubic foot or less than 0.003 tons per cubic foot, consistent with the payload validation used in the Barge Tool. Ton-Mile Validation 2011 Logistics Partner data was evaluated to establish absolute upper bounds for ton- mile inputs. The ton-mile validation applies at the carrier (row) and total fleet (summation of rows) level, with the same values applied to both. The maximum allowable ton-mile value was set to twice the observed maximum value in the 2011 data set: 209,207,446,000 ton-miles. 27 ------- |