&EPA Unite* Lrwcnnicntel P*fltsctio Ag«rey PROCEDURES FOR DEVELOPING BASE YEAR AND FUTURE YEAR MASS EMISSION INVENTORIES FOR THE NONROAD DIESEL ENGINE RULEMAKING ------- EPA-454/R-03-009 April 2003 PROCEDURES FOR DEVELOPING BASE YEAR AND FUTURE YEAR MASS EMISSION INVENTORIES FOR THE NONROAD DIESEL ENGINE RULEMAKING Prepared by: Alpine Geophysics, LLC 387 Pollard Mine Road Burnsville, NC 28714 and E.H. Pechan & Associates, Inc. 3622 Lyckan Parkway, Suite 2002 Durham, NC 27707) Prepared for Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, NC 27711 Contract No. 68-D7-0067 Work Assignment No.5-10 U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Emissions Monitoring and Analysis Division Emission Factor and Inventory Group Research Triangle Park, North Carolina 27711 ------- ACRONYMS AND ABBREVIATIONS AAMA ASTM BEA CAA CI CNG CO DOE EGU EIA EPA F FAA FCM FIPS ft ft/min g/bhp-hr GSP HC HDD HDDV HDGV HON hp HPMS I/M IPM LDDT LDDV LDGT1 LDGT2 LDGV LEV LNB LPG LTOs m American Automobile Manufacturers Association American Society for Testing and Materials Bureau of Economic Analysis Clean Air Act compression-ignition compressed natural gas carbon monoxide U.S. Department of Energy electric generating unit Energy Information Administration U.S. Environmental Protection Agency Fahrenheit Federal Aviation Administration Fuel Consumption Model Federal Information Processing Standard feet feet per minute grams per brake horsepower-hour Gross State Product hydrocarbon heavy-duty diesel heavy-duty diesel vehicle heavy-duty gasoline vehicle Hazardous Organic NESHAP horsepower Highway Performance Monitoring System Inspection and Maintenance Integrated Planning Model light-duty diesel truck light-duty diesel vehicle light-duty gasoline truck (less than 6,000 pounds in weight) light-duty gasoline truck (6,000 to 8,500 pounds in weight) light-duty gasoline vehicle Low-Emission Vehicle low-NOx burner liquid petroleum gas Landing-Takeoff Operations meter ------- ACRONYMS AND ABBREVIATIONS (continued) MACT MC MMBtu NAAQS NESHAP NET NH3 NLEV NMHC NMOG NOX OBD OTAG OTAQ OTC OTR PM PM10 PM25 POTWs ppm psi RACT REMSAD RFG RSD RVP SCCs SCR SI SIC SIP SNCR SO2 SOCMI SOX SSD TLEV tpd tpy TSDFs maximum achievable control technology motorcycle million British thermal units National Ambient Air Quality Standards National Emission Standards for Hazardous Air Pollutants National Emission Trends ammonia National Low Emission Vehicle nonmethane hydrocarbon Nonmethane Organic Gas oxides of nitrogen on-board diagnostic Ozone Transport Assessment Group Office of Transportation and Air Quality Ozone Transport Commission Ozone Transport Region particulate matter primary particulate matter with an aerodynamic diameter less than or equal to 10 micrometers primary particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers Publicly-Owned Treatment Works parts per million pounds per square inch reasonably available control technology Regulatory Modeling System for Aerosols and Deposition reformulated gasoline Regulatory Support Document Reid vapor pressure Source Classification Codes selective catalytic reduction spark-ignition Standard Industrial Classification State Implementation Plan Selective Noncatalytic Reduction sulfur dioxide Synthetic Organic Chemical Manufacturing Industry oxides of sulfur summer season daily transitional LEV tons per day tons per year treatment, storage, and disposal facilities ------- ACRONYMS AND ABBREVIATIONS (continued) UAM-V ULEV U.S. USDA UTM VMT VOC Urban Airshed Model Ultra-Low Emission Vehicle United States U.S. Department of Agriculture Universal Transverse Mercator vehicle miles traveled volatile organic compound ------- CHAPTER I BACKGROUND To assist future State and Federal implementation of the Nonroad Diesel mobile source emission standards, the United States (U.S.) Environmental Protection Agency (EPA) is developing national annual and temporal emission inventories and applying the Comprehensive Air Quality Model with Extensions (CAMx)and Regulatory Modeling System for Aerosols and Deposition (REMSAD) to examine the regional ozone and particulate matter (PM) concentration response to a series of emission control strategies. The purpose of this report is to describe the procedures and assumptions used to develop the mass emissions inventories modeled in this analysis. The emission inventories developed to support the nonroad rulemaking include the following: 1996 Base Year; 2020 Base Case; 2020 Control Case; 2030 Base Case; and 2030 Control Case. These national inventories are prepared for the 48 contiguous States at the county-level for on-highway mobile, electric generating unit (EGU), non-EGU point, stationary area, and nonroad sources. The inventories do not include Alaska and Hawaii. The inventories contain annual and typical summer season day emissions for the following pollutants: oxides of nitrogen (NOX), volatile organic compounds (VOC), carbon monoxide (CO), oxides of sulfur (SOX), primary particulate matter with an aerodynamic diameter less than or equal to 10 micrometers and 2.5 micrometers (PM10 and PM25), and ammonia (NH3). The 2020 and 2030 Base Case inventories are prepared by applying growth and control assumptions to the 1996 Base Year inventory. The 2020 and 2030 Control Case inventories are developed from the 2020 and 2030 Base Case inventories, respectively, by applying nonroad diesel control assumptions to the nonroad emission source sectors. The growth and control assumptions used to prepare the 2020 and 2030 inventories are documented in this report. Chapters II through VI of this report document the inventories for the EGU, non-EGU point, stationary area, nonroad, and on-highway vehicle source sectors. The chapter for each sector documents the procedures and assumptions applied to prepare the mass emissions inventories for the 1996 Base Year; 2020 and 2030 Base Cases; and 2020 and 2030 Control Cases. ------- CHAPTER II ELECTRICITY GENERATING UNITS (EGUs) A. 1996 BASE YEAR MASS EMISSIONS INVENTORY The 1996 base year emissions inventory for EGUs is the 1996 National Emission Trends (NET) point source inventory version 3.12 (EPA, 2000a). This inventory includes both annual and typical summer season day (SSD) emissions forNOx, VOC, CO, SOX, PM10, PM25, andNH3. Inventory records with Source Classification Codes (SCCs) of lOlxxxxx and 201xxxxx were extracted from the NET inventory to develop the 1996 EGU inventory. B. 2020 AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES Projection year unit-level output files from the EPA Modeling Applications (v.2.1) of the Integrated Planning Model (IPM) were provided to Pechan by EPA for the EGU sector for 2020. These were the same files as modeled in the base case emission scenarios of the Clear Skies Initiative and includes a court remanded version of the Regional Transport NOx SIP Call reductions which excluded the additional control of emissions in Georgia and Missouri. The 2020 IPM output file was also used to represent EGU projections for 2030. This file includes heat input, sulfur dioxide (SO2) emissions, NOX emissions, and unit characteristics such as prime mover (boiler, gas turbine), primary fuel, bottom type, and firing type. . This section focuses on the steps used to create the future year mass emissions inventories for 2020 and 2030, by adding to the IPM files emissions for VOC, CO, PM10, PM2 5, and NH3, as well as data elements needed for modeling (e.g., county codes, coordinates, and stack parameters). Note that the 2030 mass emissions file is identical to the 2020 file. The data elements included in the original IPM parsed data sets are shown in Table II-1. The data sets include unit-level information for all existing or known planned units. For new units (additional capacity needed to meet generation demands), state-level estimates by plant type (prime mover) and fuel type are provided. Details about the additional or updated items for the final 2020 and 2030 emission files are discussed below. 1. ORISID AND BLRID Unique utility plant (ORISID) and unit (BLRID) identifiers are provided in the original IPM parsed data set. These two variables were included in the emission inventories but were not reviewed for accuracy because of time and resource constraints associated with preparing the inventories for all sectors. II-1 ------- Table 11-1 Data Elements Provided in EGU Projection Files IPM Parsed Data Sets Data Elements Description Unit ID IPM Unit ID Plant Name Plant name Plant Type Combined cycle, coal steam, oil/gas steam, turbine, other State Name State name State Code Federal Information Processing Standard (FIPS) State code County Name County name (sometimes missing) County Code FIPS county code (sometimes missing) ORIS Code ORIS plant code for those units assigned codes, IPM plant code otherwise Blr ORIS boiler or unit code where available, otherwise IPM unit code Capacity Boiler/unit capacity (MW) July Day Heat July day heat input (109 Btu/day) Fuel Type Primary fuel burned: coal, gas, natural gas, none, refuse, waste coal, wood waste Bottom Boiler bottom type: dry, wet, other, unknown, or blank Firing Firing type: cell, cyclone, tangential, vertical, well, wet, other, or unknown Existing SO2/NOX Controls Existing control for SO2 and/or NOX - scrubbed, unscrubbed, or blank Retrofit SO2/NOX Controls Indicator of unit retrofit controls; coal to combined cycle, gas reburn, oil/gas selective noncatalytic reduction (SNCR), oil/gas to combined cycle, retirement, coal selective catalytic reduction (SCR), coal scrubber, coal SNCR, or blank Typical July Day NOX1 Typical July day NOX emissions (tons/day) Ash Content Coal ash content (for fuel type - coal only) Fuel Sum 5-month summer heat input (1012 Btu) Fuel Tot Annual heat input (1012 Btu) NOX Sum 5-month NOX emissions (103 Ton) NOX Tot Annual NOX emissions (103 Ton) SO7 Tot Annual SO7 emissions (103 Ton) 1 Not used in developing modeling files. II-2 ------- 2. County Identifiers For those units with no county identifiers, counties available in cross-reference files developed for the NOX State Implementation Plan (SIP) Call EGU file and other prior analyses were utilized to identify and assign the county code. Plants were matched to other inventories by State and plant name in some cases. Others were matched to Energy Information Administration (EIA)-860 planned unit files or to North American Electric Reliability Council reports to identify the county. 3. Latitude and Longitude Latitude and longitude coordinates were assigned at the plant level and were taken from a data base file developed by Pechan. This file includes coordinates from other inventories, including the NET inventory and the Ozone Transport Assessment Group (OTAG) inventory, where units were matched to these inventories at the boiler or plant level. For units that have ORIS IDs that did not match to this file, county centroids were assigned. 4. SCC The SCC is needed to determine the appropriate emission rates to use for the additional pollutants and to incorporate default stack parameters for units that do not match to existing inventories. SCCs were assigned by first matching plant (ORISID) and unit (BLRID) identifiers to existing inventories and then by assigning SCCs based on the unit, fuel, firing, and bottom types. In cases where SCCs taken from other inventories indicate a fuel other than that specified in the IPM unit-level file, SCCs were updated based on the indicated fuel, unit, bottom, and firing types. 5. Stack Parameters Stack parameters were added to the EGU file by matching to other inventories. For units where matches to other inventories could not be made, default parameters were assigned by SCC. These default parameters are shown in Table II-2. Stack flow rate, temperature, diameter, height, and velocity were quality assured using the ranges supplied by EPA (Stella, 2000); all stack flow values were then recalculated using the algorithm specified in a technical memorandum to EPA (Pechan-Avanti, 2000). 6. Emissions Emissions of VOC, CO, PM10, PM25, and NH3 were added to the inventory by applying average fuel-specific heat content and updated emission rates (based on updated AP-42 II-: ------- Table 11-2 Default Stack Parameters for Utility Boilers sec 10100101 10100201 10100202 10100203 10100204 10100212 10100217 10100221 10100222 10100223 10100226 10100301 10100302 10100303 10100401 10100404 10100601 10100604 10101201 20100201 20100202 Stack Temp. (degrees F) 175 175 175 175 175 175 175 175 175 175 175 175 175 175 300 300 300 300 175 300 300 Stack Height (feet) 570 570 570 570 570 570 570 570 570 570 570 570 570 570 290 290 280 280 570 280 280 Stack Diameter (feet) 24 24 24 24 24 24 24 24 24 24 24 24 24 24 12 12 12 12 24 12 12 Stack Flow (ft3/sec) 16286 16286 16286 16286 16286 16286 16286 16286 16286 16286 16286 16286 16286 16286 3619 3619 2601 2601 16286 2601 2601 uncontrolled emission factors) to the reported heat input for each unit. For PM10 and PM2 5, the reported ash content was also utilized along with control efficiency data obtained from other inventories. Condensible PM was not included in the estimate of PM10 or PM2 5 emissions. A default PM control efficiency of 90 percent was applied to all coal-fired units which did not match to other inventories. II-4 ------- 7. New Units The IPM data sets provide projected heat input from new units by prime mover and fuel type. This projected heat input was divided into individual new units based on the model plant parameters shown in Table II-3. New units were then allocated to existing unit sites based on a hierarchy that avoids ozone nonattainment areas (Pechan-Avanti, 1997'a). After siting the units, SCCs were assigned based on prime mover and fuel type. Default stack parameters and emissions were added using the same methods applied for existing units. Since the new units are defined as "new" after 1996, and more recent data for new units were available, some new units could be matched to the newer data to obtain SCCs. C. MASS EMISSIONS INVENTORY FILES After adding the additional parameters to the IPM unit-level file, the final mass emission inventories were prepared. The 5-month (May through September) heat input was allocated to the month and then divided by the number of days in the month. Typical SSD emissions were calculated using the same procedure, assuming that the emission rate remained the same across these 5 months. Because the 2020 IPM output file was used to represent EGU projections for 2030, the mass and modeling files for 2020 and 2030 are identical. The structure for the base year and projection year mass emission inventories is shown in Tables II-4 and II-5. The structures differ since the base year inventory was taken directly from the NET, while the projection year inventory was based on the IPM data set, which provides different information in some cases. Table 11-3 Model Plant Parameters for Projected New Utility Units by Type Plant Parameters Fuel Type Unit Capacity (megawatts) sec Stack Height [feet (ft)] Stack Diameter (ft) Stack Temperature (F) Exhaust Gas Flow Rate (ft3/sec) Stack Gas Velocity (ft/sec) Combined Cycle Natural Gas 225 20100201 280 12 300 2,601 23 Gas Turbine Natural Gas 80 20100201 280 12 300 2,601 23 Coal Coal 500 10100201 570 24 175 16,286 36 II-5 ------- Table 11-4 Structure for 1996 EGU Mass Emissions File Variable FIPSST FIPSCNTY PLANTID POINTID STACKID SEGMENT PLANT sec STKHGT STKDIAM STKTEMP STKFLOW STKVEL BOILCAP WINTHRU SPRTHRU SUMTHRU FALTHRU HOURS DAYS WEEKS THRUPUT MAXRATE HEATCON SULFCON ASHCON NETDC SIC LATC LONG VOC_CE NOX_CE CO_CE SO2_CE PM10_CE PM25_CE NH3_CE VOC_CPRI NOX_CPRI Type C C C C C C C C N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N Length 2 3 15 15 12 2 40 10 4 6 4 10 9 8 3 3 3 3 2 1 2 11 12 8 5 5 9 4 9 9 7 7 7 7 7 7 7 3 3 Decimals 0 0 0 0 0 0 0 0 0 2 0 2 2 2 0 0 0 0 0 0 0 1 3 2 2 2 3 0 4 4 2 2 2 2 2 2 2 0 0 Description FIPS State Code FIPS County Code State Plant ID Point ID Stack ID Segment ID Plant Name sec Stack Height (ft) Stack Diameter (ft) Stack Temperature (degrees F) Stack Flow Rate (cubic feet per second) Stack Velocity (ft/sec) Boiler Design Capacity Winter Thruput (%) Spring Thruput (%) Summer Thruput (%) Fall Thruput (%) Hours per Day Days per Week Weeks per Year Throughput Rate (SCC units/year) Maximum Ozone Season Rate (units/day) Heat Content (MMBtu/SCC unit) Sulfur Content (mass percent) Ash Content (mass percent) Maximum Nameplate Capacity (MW) Standard Industrial Classification (SIC) Code Latitude (degrees) Longitude (degrees) VOC Control Efficiency (%) NOX Control Efficiency (%) CO Control Efficiency (%) SO2 Control Efficiency (%) PM10 Control Efficiency (%) PM25 Control Efficiency (%) NH3 Control Efficiency (%) VOC Primary Control Equipment Code NOX Primary Control Equipment Code 11-6 ------- Table II-IV (continued) Variable CO_CPRI SO2_CPRI PM10_CPRI PM25_CPRI NH3_CPRI VOC_CSEC NOX_CSEC CO_CSEC S02_CSEC PM10_CSEC PM25_CSEC NH3_CSEC VOC_ANN NOX_ANN CO_ANN SO2_ANN PM10_ANN PM25_ANN NH3_ANN VOC_OSD NOX_OSD COJDSD SO2_OSD PM10_OSD PM25_OSD NH3_OSD VOC_RE NOX_RE CO_RE S02_RE PM10_RE PM25_RE NH3 RE Type N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N Length 3 3 3 3 3 3 3 3 3 3 3 3 13 13 13 13 13 13 13 13 13 13 13 13 13 13 3 3 3 3 3 3 3 Decimals 0 0 0 0 0 0 0 0 0 0 0 0 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 0 0 0 0 0 0 Description CO Primary Control Equipment Code SO2 Primary Control Equipment Code PM10 Primary Control Equipment Code PM25 Primary Control Equipment Code NH3 Primary Control Equipment Code VOC Secondary Control Equipment Code NOX Secondary Control Equipment Code CO Secondary Control Equipment Code SO2 Secondary Control Equipment Code PM10 Secondary Control Equipment Code PM25 Secondary Control Equipment Code NH3 Secondary Control Equipment Code Annual VOC (tons) Annual NOX (tons) Annual CO (tons) Annual SO2 (tons) Annual PM10 (tons) Annual PM25 (tons) Annual NH3 (tons) Summer Day VOC (tons) Summer Day NOX (tons) Summer Day CO (tons) Summer Day SO2 (tons) Summer Day PM10 (tons) Summer Day PM25 (tons) Summer Day NH3 (tons) VOC Rule Effectiveness (%) NOX Rule Effectiveness (%) CO Rule Effectiveness (%) SO2 Rule Effectiveness (%) PM10 Rule Effectiveness (%) PM25 Rule Effectiveness (%) NH3 Rule Effectiveness (%) II-7 ------- Table 11-5 Structure for 2020 and 2030 EGU Mass Emissions Files Variable FIPSST FIPSCNTY PLANTID POINTID STACKID SEGMENT PLANT sec STKHGT STKDIAM STKTEMP STKFLOW LAT LON VOC_WIN VOC_SUM NOX_WIN NOX_SUM CO_WIN CO_SUM SO2_WIN SO2_SUM PM10_WIN PM10_SUM PM25_WIN PM25_SUM NH3_WIN NH3 SUM Type C C C C C C C C N N N N N N N N N N N N N N N N N N N N Length 2 3 15 15 12 2 40 10 4 6 4 10 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 Decimals 0 0 0 0 0 0 0 0 0 2 0 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 Description FIPS State Code FIPS County Code State Plant ID Point ID Stack ID Segment ID Plant Name sec Stack Height (ft) Stack Diameter (ft) Stack Temperature (degrees F) Stack Flow Rate (cubic feet per second) Latitude (degrees) Longitude (degrees) 7-Month Winter VOC (tons) 5-Month Summer VOC (tons) 7-Month Winter NOX (tons) 5-Month Summer NOX (tons) 7-Month Winter CO (tons) 5-Month Summer CO (tons) 7-Month Winter SO2 (tons) 5-Month Summer SO2 (tons) 7-Month Winter PM10 (tons) 5-Month Summer PM10 (tons) 7-Month Winter PM25 (tons) 5-Month Summer PM25 (tons) 7-Month Winter NH3 (tons) 5-Month Summer NH3 (tons) II-8 ------- CHAPTER III NON-EGU POINT SOURCES A. 1996 BASE YEAR MASS EMISSIONS INVENTORY The 1996 base year inventory for non-EGUs is the 1996 NET point source inventory Version 3.12 (EPA, 2000a). This inventory includes both annual and typical summer season day (SSD) emissions for NOX, VOC, CO, SOX, PM10, PM25, and NH3. Inventory records with SCCs of lOlxxxxx and 201xxxxx were excluded from the non-EGU inventory because they are included in the EGU inventory. Latitude and longitude coordinates and stack parameters were corrected for several sources. For some sources, multiple SCCs were listed under a single point, stack, and segment. New non- duplicate segment IDs were created for the mass emissions file to ensure that each record had a unique identification code for inclusion in the emissions processor input files. B. 2020 AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES Future year base case emissions for 2020 and 2030 were grown from the 1996 base year mass emission inventory utilizing Bureau of Economic Analysis (BEA) Gross State Product (GSP) growth factors at the State level by 2-digit Standard Industrial Classification (SIC) code. Control measures reflecting Clean Air Act (CAA) requirements were then incorporated. Two separate mass emissions inventories were created for each year to reflect emissions without and with the effects of the NOX SIP Call control requirements. 1. Growth Assumptions The 1995 BEA GSP projections (BEA, 1995) by 2-digit SIC code were applied to estimate changes in activity between 1996 and 2020 and 2030 for the non-EGU point source sector. For fuel combustion sectors, energy adjustment factors were also applied to the base year emission inventory. After applying the changes in activity, additional controls were added to reflect the alternative scenarios. EPA guidance for projecting emissions (EPA, 1991) lists the following economic variables (in order of preference) for projecting emissions: product output; • value added; • earnings; and • employment. III-l ------- In the absence of product output projections, EPA guidance recommends value added projections. Value added is the difference between the value of industry outputs and inputs. BEA GSP projections represent a measure of value added, and are a fuller measure of growth than BEA's earnings projections because earnings represents only one component of GSP. GSP reflects the difference between revenues from selling a product and the amounts paid for inputs from other industries. By incorporating inputs to production, GSP reflects future changes in production processes, efficiency, and technological changes. A comparison of BEA's 1995 GSP projections and BEA's 1990 earnings projections indicates that GSP growth factors are slightly higher than the earnings data. This is most often true for capital-intensive industries (e.g., manufacturing) than for labor-intensive industries (e.g., services). Components of GSP include payments to capital. This is an important distinction to make because it implicitly reflects the effect of factor substitution in production. As discussed in EPA's projections guidance, factor substitution should be included in growth projections, making value added data preferable to earnings data for projecting emissions. The 1995 BEA industry GSP projections by State are available at the 2-digit SIC code level. For each record in the non-EGU point source 1996 base year inventory, a link was established between the State FIPS code, the SIC code, and the applicable BEA GSP growth factor. National BEA GSP annually compounded growth rates by industry are listed in Table III-l. For fuel combustion sources, factors were applied to the 1996 base year emissions to account for improvements in energy efficiency between 1996 and 2020 and 2030. These factors, developed from the U.S. Department of Energy (DOE) publication Annual Energy Outlook 1999, account for increases in fuel and process efficiency in future years (DOE, 1998). Basically, less fuel will be needed to provide the same amount of energy (generally in the form of steam) to an industrial process and the amount of energy needed per unit output will also decrease as processes become more efficient. For example, DOE projects natural gas consumption in the commercial sector to rise from 3.392 quadrillion Btu in 1996 to 3.997 quadrillion Btu in 2020. Over this same time-frame, DOE projects commercial building square footage to increase from 59.5 billion square feet to 72.9 billion square feet. To reflect the projected change in natural gas consumed per square foot of commercial building space, natural gas energy intensity factors were calculated for 1996 and each projection year. For example, 0.2475 quadrillion Btu/square foot of natural gas is projected to be consumed in 2020 versus 0.2551 quadrillion Btu/square foot in 1996. For all commercial sector natural gas source categories, the BEA commercial sector growth factors are multiplied by 0.97, which represents the ratio of the 2020 energy intensity factor for commercial sector natural gas to the 1996 energy intensity factor for commercial natural gas. Similar ratios were calculated and applied for other fuels used in the commercial sector, and for all fuels used in the residential and industrial energy sectors. These adjustments were based on those used in the NET inventory projections (EPA, 2000a). III-2 ------- Table 111-1 BEA National GSP Growth Forecasts Industry (SIC Code) All-Industry Total Farm (01) Nonfarm (02) Agricultural services (07, 08, 09) Mining (10, 12, 13, 14) Metal mining (10) Coal mining (12) Oil and gas extraction (13) Nonmetallic minerals (14) Construction (15, 16, 17) Manufacturing (20 - 39) Durable goods Lumber and wood products (24) Furniture and fixtures (25) Stone, clay, and glass products (32) Primary metals (33) Fabricated metals (34) Industrial machinery (35) Electronic equipment (36) Motor vehicles and equipment (371) Other transportation equipment (37, excluding 371) Instruments and related products (38) Miscellaneous manufacturing (39) Nondurable Goods Food and kindred products (20) Tobacco products (21) Textile mill products (22) Apparel and other textile products (23) Paper products (26) Printing and publishing (27) Chemicals and allied products (28) Petroleum and coal products (29) Rubber and plastics products (30) Leather and leather products (31) Annual Growth (% per year) 1996 to 2020 1.5 1.5 3.2 2.7 2.1 0.2 1.2 1.1 0.7 1.4 0.9 0.5 0.8 2.6 1.9 1.0 2.0 1.3 1.6 1.1 -2.5 1.0 1.4 1.8 0.7 1.3 1.1 2.5 -0.1 Annual Growth (% per year) 1996 to 2030 1.2 1.2 2.7 2.3 1.7 0.3 1.1 1.0 0.7 1.3 0.9 0.5 0.8 2.1 1.6 1.0 1.8 1.3 1.4 1.1 -2.2 1.0 1.2 1.6 0.7 1.3 1.1 2.2 -0.1 III-: ------- Table 111-1 (continued) Industry (SIC Code) Transportation and Public Utilities (40 - 49) Railroad transportation (40) Local and interurban transit (41) Trucking and warehousing (42) Water transportation (44) Transportation by air (45) Pipelines (46) Transportation services (47) Communications (48) Utilities (49) [for non-EGU source types] Wholesale and Retail Trade (50 - 59) Wholesale trade (50, 51) Retail trade (52 - 59) Finance, Insurance, and Real Estate (60 - 67) Banks and investment (60, 61 , 62, 67) Insurance (63, 64) Real estate (65) Services (70 - 89) Hotels and other lodging (70) Personal services (72) Business services (73) Auto repair and parking (75) Amusement (79) Health services (80) Legal services (81) Educational services (82) Social services (83) Private households (88) Other services (84, 86, 89) Government Federal, civilian Federal, military State and local Population Annual Growth (% per year) 1996 to 2020 2.4 1.3 1.8 0.3 2.8 0.9 2.4 2.4 1.7 2.1 1.8 2.3 1.7 1.8 1.9 0.9 2.4 1.5 2.4 2.0 1.3 1.6 2.3 0.8 2.3 0.4 0.2 1.3 0.8 Annual Growth (% per year) 1996 to 2030 2.0 1.3 1.6 0.4 2.4 0.8 2.1 2.1 1.5 1.8 1.6 2.0 1.6 1.6 1.7 0.9 2.0 1.3 2.1 1.8 1.2 1.5 2.0 0.8 2.0 0.5 0.4 1.2 0.8 SOURCE: Developed from BEA, 1995. III-4 ------- 2. Control Assumptions Since the base year inventory for this effort is 1996, VOC and NOx reasonably available control technology (RACT) requirements were assumed to have already been implemented in 1- hr ozone nonattainment areas. So, for stationary sources, CAA controls include Federal initiatives as shown in Table III-2 for point sources. Maximum achievable control technology (MACT) controls were also applied to identified source categories as shown in Tables III-3 and III-4. NOX emissions for the 20 States (22 original SIP Call States plus the District of Columbia, minus Wisconsin, Georgia, and Missouri) covered by the NOX SIP Call were also reduced to reflect the NOX SIP Call requirements. The NOX SIP Call controls were applied to a 2007 base case inventory. For the 2020 and 2030 base case inventories, sources affected by the NOX SIP Call were capped at 2007 emission levels. The NOX SIP Call was modeled by first identifying the sources in the 1996 NET inventory which are large, and are within the source categories covered under the SIP Call (EPA, 1999a). This procedure was performed by first matching the non-EGU point sources in the 1996 NET inventory file with the large sources in the NOX SIP Call data base. This was computer matching that required that the numeric identifiers in each file be identical at the State, county, plant, and point level. After this exercise was performed, there were 633 sources in the 1996 NET inventory that were identified as large sources affected by the NOX SIP Call. Because this included less than 30 percent of the 2,216 large sources in the NOX SIP Call control region, additional steps were taken to identify the remaining large, affected sources in the 1996 NET non-EGU point source file. These steps were applied separately to the four major source categories that are affected by the SIP Call, as follows: 1. For boilers, all sources in the SIP Call-affected States with a boiler design capacity in the 1996 NET file greater than or equal to 250 million British thermal units (MMBtu) were deemed to be large sources. 2. For turbines, all sources in the SIP Call-affected States with a boiler design capacity in the 1996 NET file greater than or equal to 250 MMBtu were tagged as large sources. 3. For 1C engines, all sources with 1996 NOX emissions greater than 1 ton per day were tagged as large sources. 4. For cement manufacturing, all sources with 1996 NOX emissions greater than 1 ton per day were tagged as large sources. Once the large sources were determined, the following percentages were applied according to the source category affected: Industrial Boilers 60% Gas Turbines 60% Internal Combustion Engines 90% Cement Manufacturing 30% Two estimates of NOX emissions were calculated for non-EGU point sources to reflect ozone versus non-ozone season emission differences for the NOX controls expected to be operating only m-5 ------- during the 5-month ozone season. The typical SSD emission estimates incorporate the effects of NOX SIP Call controls. Annual NOX emission estimates are the sum of 5-month ozone season NOX emissions, plus 7-month (October-April) NOX emissions. Table III-5 shows the source types affected by the NOX SIP Call and describes which controls were applied to each source type. For the source categories that are affected by the NOX SIP Call, non-ozone season emissions were estimated using the same control percentages listed above if the dominant source type for that control device is expected to be one that provides year-round emission reductions. For seasonal controls, such as selective catalytic reduction (SCR) or selective non-catalytic reduction (SNCR) applications to industrial boilers and cement kilns, NOX controls were not applied during the 7-month non-ozone season when NOX emissions were estimated. Table III-5 lists the primary NOX control technology assumed for each category. Table 111-2 Point Source CAA Baseline Control Assumptions Source Category Pollutant Control Efficiency (%)* National Rules Marine vessel loading: petroleum liquids VOC 80 Treatment, storage, and disposal facilities (TSDFs) VOC 96 Municipal solid waste landfills VOC 82 NOTE: *From uncontrolled levels. If NET96 control efficiencies were reported as lower than the applied control efficiency assumptions, an uncontrolled emission value was first calculated by removing this NET96 reported value and then a new emission estimate was calculated by applying the new control efficiency. If the NET96 control efficiency was higher than the applied control efficiency assumptions, no control efficiency changes were made to the source in the projection. 111-6 ------- Table 111-3 Point Source MACT Control Assumptions VOC Control Source Category Efficiency (%)* Benzene National Emission Standards for Hazardous Air Pollutants (NESHAP) (national) By-product coke mfg 85 By-product coke - flushing-liquor circulation tank 95 By-product coke - excess-NH3 liquor tank 98 By-product coke mfg. - tar storage 98 By-product coke mfg. - light oil sump 98 By-product coke mfg. - light oil dec/cond vents 98 By-product coke mfg. - tar bottom final cooler 81 By-product coke mfg. - naphthalene processing 100 By-product coke mfg. - equipment leaks 83 By-product coke manufacture - other 94 By-product coke manufacture - oven charging 94 Coke ovens - door and topside leaks 94 Coke oven by-product plants 94 2-Year MACT (national) Synthetic Organic Chemical Manufacturing Industry (SOCMI) Hazardous Organic NESHAP (HON) -SOCMI processes 79 - Volatile organic liquid storage 95 - SOCMI fugitives (equipment leak detection and repair) 60 - SOCMI wastewater 0 - Ethylene oxide manufacture 98 - Phenol manufacture 98 - Acrylonitrile manufacture 98 - Polypropylene manufacture 98 - Polyethylene manufacture 98 - Ethylene manufacture 98 Dry Cleaning - Perchloroethylene 95 - Other 70 4^-Year MACT (national) TSDFs (offsite waste operations) 96 Shipbuilding and repair 24 Polymers and resins II 78 Polymers and resins IV 70 Styrene-butadiene rubber manufacture (polymers & resins group I) 70 Wood furniture surface coating 30 Aircraft surface coating (aerospace) 60 Petroleum Refineries: other sources - Fixed roof petroleum product tanks 98 - Fixed roof gasoline tanks 96 - External floating roof petroleum product tanks 90 - External floating roof gasoline tanks 95 - Petroleum refinery wastewater treatment 72 - Petroleum refinery fugitives 72 - Petroleum refineries - Slowdown w/o control 78 -Vacuum distillation 72 m-7 ------- Table 111-3 (continued) VOC Control Source Category Efficiency (%)* Halogenated Solvent Cleaners - Open top degreasing - halogenated 63 - In-line (conveyorized) degreasing - halogenated 39 Printing - Flexographic 32 - Gravure 27 Gasoline Marketing - Storage 5 -Splash loading 99 - Balanced loading 87 -Submerged loading 99 - Transit 5 - Leaks 39 7/10-Year MACT (national) Paint and varnish manufacture 35 Rubber tire manufacture 70 Green tire spray 90 Automobile surface coating 79 Beverage can surface coating 57 Paper surface coating 78 Flatwood surface coating 90 Fabric printing 80 Metal surface coating 90 Plastic parts surface coating 45 Pulp and paper production 70 Agricultural chemical production 79 Pharmaceutical production 79 Polyesters 70 Fabric coating 70 Petroleum refineries - fluid catalytic cracking 70 Oil and natural gas production 90 Explosives 70 Plywood/particle board 70 Reinforced plastics 70 Publicly-Owned Treatment Works (POTWs) 70 Phthalate plasticizers 70 Polymers and resins III 78 Rayon production 70 Polyvinyl chloride 70 Spandex production 70 Nylon 6 production 70 Alkyd resins 70 Polyester resins 70 Chelating agents 70 NOTE: *From uncontrolled levels. If NET96 control efficiencies were reported as lower than the applied control efficiency assumptions, an uncontrolled emission value was first calculated by removing this NET96 reported value and then a new emission estimate was calculated by applying the new control efficiency. If the NET96 control efficiency was higher than the applied control efficiency assumptions, no control efficiency changes were made to the source in the projection. m-8 ------- Table 111-3 (continued) m-9 ------- Table 111-4 Non-VOC Related MACT Assumptions Source Category Municipal Waste Combustors Cement Manufacturing Secondary Aluminum Medical Waste Incineration Hazardous Waste Incineration Pollutant PM S02 PM PM PM NOx SO2 PM Percentage Reduction (%)* 30 50 90 90 88 20 20 36 NOTE: *From uncontrolled levels. If NET96 control efficiencies were reported as lower than the applied control efficiency assumptions, an uncontrolled emission value was first calculated by removing this NET96 reported value and then a new emission estimate was calculated by applying the new control efficiency. If the NET96 control efficiency was higher than the applied control efficiency assumptions, no control efficiency changes were made to the source in the projection. Ill-10 ------- Table 111-5 NOX SIP Call Control Application Source Type Description Industrial Boilers (non-coal) Turbines Cement Kilns (wet) Reciprocating 1C Engines Cement Kilns (dry) Industrial Boilers (coal) Cement Kilns (coal) NOX Control Year-round application LNB and LNB plus flue gas recirculation LNB plus water injection Mid-kiln firing Low emission combustion Mid-kiln firing 5-month ozone season application SCRorSNCR SCRorSNCR Cost Pod Number 15 16 17 41 42 43 23 24 50 34 21 22 46 33 11 12 13 14 81 Cost Pod Name ICI Boilers ICI Boilers ICI Boilers ICI Boilers ICI Boilers ICI Boilers Gas Turbines Gas Turbines Gas Turbines Cement Mfg. (wet) 1C Engines 1C Engines 1C Engines Cement Mfg. (dry) ICI Boilers ICI Boilers ICI Boilers ICI Boilers Cement Kiln Cost Pod Fuel Type Residual Oil Distillate Oil Natural Gas Process Gas Coke LPG Oil Natural Gas Jet Fuel NA Oil Gas Gas, Diesel, LPG NA Coal/Wall Coal/FBC Coal/Stoker Coal/Cyclone Coal Notes: LNB = low-NOx burners; ICI = industrial, commercial, and institutional; LPG = liquified petroleum gas; NA = not applicable; SCR = selective catalytic reduction; and SNCR = selective non-catalytic reduction. ------- C. MASS EMISSIONS INVENTORY FILES The structures for the mass emission inventories are detailed in Tables III-7 and III-8, as the base year and future year inventories differed. Data elements included in the base year inventory and excluded from the future year inventories include the pollutant emission factor (-EMF), primary control equipment code (-CPRI), and secondary control equipment code (-CSEC). Ill-12 ------- Table 111-7 Structure for 1996 Base Year Non-EGU Mass Emissions File Variable FIPSST FIPSCNTY PLANTID POINTID STACKID SEGMENT PLANT sec STKHGT STKDIAM STKTEMP STKFLOW STKVEL BOILCAP CAP UNITS WINTHRU SPRTHRU SUMTHRU FALTHRU HOURS DAYS WEEKS THRUPUT MAXRATE HEATCON SULFCON ASHCON NETDC SIC LATC LONG VOC CE NOX_CE CO CE S02 CE PM10_CE PM25 CE NH3_CE VOC CPRI NOX CPRI CO_CPRI SO2 CPRI PM10_CPRI PM25_CPRI NH3 CPRI VOC_CSEC NOX CSEC CO CSEC S02 CSEC Type C C C C C C C C N N N N N N C N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N Lenqth 2 3 15 15 12 2 40 10 4 6 4 10 9 8 1 3 3 3 3 2 1 2 11 12 8 5 5 9 4 9 9 7 7 7 7 7 7 7 3 3 3 3 3 3 3 3 3 3 3 Decimals 0 0 0 0 0 0 0 0 0 2 0 2 2 2 0 0 0 0 0 0 0 0 1 3 2 2 2 3 0 4 4 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 Description FIPS State Code FIPS County Code State Plant ID Point ID Stack ID Segment ID Plant Name sec Stack Height (ft) Stack Diameter (ft) Stack Temperature (degrees F) Stack Flow Rate (cubic feet per second) Stack Velocity (ft/see) Boiler Design Capacity (MMBtu/hour) Capacity Unit Code Winter Thruput (%) Spring Thruput (%) Summer Thruput (%) Fall Thruput (%) Hours per Day Days per Week Weeks per Year Throughput Rate (SCC units/year) Maximum Ozone Season Rate (units/day) Heat Content (MMBtu/SCC unit) Sulfur Content (mass percent) Ash Content (mass percent) Maximum Nameplate Capacity (MW) SIC Code Latitude (degrees) Longitude (degrees) VOC Control Efficiency (%) NOX Control Efficiency (%) CO Control Efficiency (%) SO2 Control Efficiency (%) PM10 Control Efficiency (%) PM25 Control Efficiency (%) NH3 Control Efficiency (%) VOC Primary Control Equipment Code NOX Primary Control Equipment Code CO Primary Control Equipment Code SO2 Primary Control Equipment Code PM10 Primary Control Equipment Code PM25 Primary Control Equipment Code NH3 Primary Control Equipment Code VOC Secondary Control Equipment Code NOX Secondary Control Equipment Code CO Secondary Control Equipment Code SO2 Secondary Control Equipment Code III-13 ------- Table 111-7 (continued) Variable Type Length Decimals Description PM10_CSEC PM25_CSEC NH3_CSEC VOC_ANN NOX_ANN CO_ANN SO2_ANN PM10_ANN PM25_ANN NH3_ANN VOC_OSD NOX_OSD COJDSD S02_OSD PM10_OSD PM25_OSD NH3_OSD VOC_RE NOX_RE CO_RE S02_RE PM10_RE PM25_RE NH3 RE N N N N N N N N N N N N N N N N N N N N N N N N 3 3 3 13 13 13 13 13 13 13 13 13 13 13 13 13 13 3 3 3 3 3 3 3 0 0 0 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 0 0 0 0 0 0 PM10 Secondary Control Equipment Code PM25 Secondary Control Equipment Code NH3 Secondary Control Equipment Code Annual VOC (tons) Annual NOX (tons) Annual CO (tons) Annual SO2 (tons) Annual PM10 (tons) Annual PM25 (tons) Annual NH3 (tons) Summer Season Daily VOC (tons) Summer Season Daily NOX (tons) Summer Season Daily CO (tons) Summer Season Daily SO2 (tons) Summer Season Daily PM10 (tons) Summer Season Daily PM25 (tons) Summer Season Daily NH3 (tons) VOC Rule Effectiveness (%) NOX Rule Effectiveness (%) CO Rule Effectiveness (%) SO2 Rule Effectiveness PM,n Rule Effectiveness (% ''10 PM25 Rule Effectiveness (%; NH, Rule Effectiveness (%) III-14 ------- Table 111-8 Structure for 2020 and 2030 Future Year Non-EGU Mass Emissions Files Variable FIPSST FIPSCNTY PLANTID POINTID STACKID SEGMENT PLANT sec STKHGT STKDIAM STKTEMP STKFLOW STKVEL BOILCAP WINTHRU SPRTHRU SUMTHRU FALTHRU HOURS DAYS WEEKS THRUPUT MAXRATE HEATCON SULFCON ASHCON NETDC SIC LATC LONG VOC_CE NOX_CE CO_CE SO2_CE PM10_CE PM25_CE NH3_CE VOC_CPRI NOX_CPRI CO_CPRI S02_CPRI PM10_CPRI PM25_CPRI NH3_CPRI Type C C C C C C C C N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N Length 2 3 15 15 12 2 40 10 4 6 4 10 9 8 3 3 3 3 2 1 2 11 12 8 5 5 9 4 9 9 7 7 7 7 7 7 7 3 3 3 3 3 3 3 Decimals 0 0 0 0 0 0 0 0 0 2 0 2 2 2 0 0 0 0 0 0 0 1 3 2 2 2 3 0 4 4 2 2 2 2 2 2 2 0 0 0 0 0 0 0 Description FIPS State Code FIPS County Code State Plant ID Point ID Stack ID Segment ID Plant Name sec Stack Height (ft) Stack Diameter (ft) Stack Temperature (degrees F) Stack Flow Rate (cubic feet per second) Stack Velocity (ft/see) Boiler Design Capacity Winter Thruput (%) Spring Thruput (%) Summer Thruput (%) Fall Thruput (%) Hours per Day Days per Week Weeks per Year Throughput Rate (SCC units/year) Maximum Ozone Season Rate (units/day) Heat Content (MMBtu/SCC unit) Sulfur Content (mass percent) Ash Content (mass percent) Maximum Nameplate Capacity (MW) SIC Code Latitude (degrees) Longitude (degrees) VOC Control Efficiency (%) NOX Control Efficiency (%) CO Control Efficiency (%) SO2 Control Efficiency (%) PM10 Control Efficiency (%) PM25 Control Efficiency (%) NH3 Control Efficiency (%) VOC Primary Control Equipment Code NOX Primary Control Equipment Code CO Primary Control Equipment Code SO2 Primary Control Equipment Code PM10 Primary Control Equipment Code PM25 Primary Control Equipment Code NH3 Primary Control Equipment Code III-15 ------- Table 111-8 (continued) Variable VOC_CSEC NOX_CSEC CO_CSEC SO2_CSEC PM10_CSEC PM25_CSEC NH3_CSEC VOC_ANN NOX_ANN CO_ANN S02_ANN PM10_ANN PM25_ANN NH3_ANN VOC_OSD NOX_OSD COJDSD S02_OSD PM10_OSD PM25_OSD NH3_OSD NOX_5MON NOX_7MON VOC_RE NOX_RE CO_RE S02_RE PM10_RE PM25_RE NH3 RE Type N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N Length 3 3 3 3 3 3 3 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 3 3 3 3 3 3 3 Decimals 0 0 0 0 0 0 0 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 0 0 0 0 0 0 Description VOC Secondary Control Equipment Code NOX Secondary Control Equipment Code CO Secondary Control Equipment Code SO2 Secondary Control Equipment Code PM10 Secondary Control Equipment Code PM25 Secondary Control Equipment Code NH3 Secondary Control Equipment Code Annual VOC (tons) Annual NOX (tons) Annual CO (tons) Annual SO2 (tons) Annual PM10 (tons) Annual PM25 (tons) Annual NH3 (tons) Summer Season Daily VOC (tons) Summer Season Daily NOX (tons) Summer Season Daily CO (tons) Summer Season Daily SO2 (tons) Summer Season Daily PM10 (tons) Summer Season Daily PM25 (tons) Summer Season Daily NH3 (tons) 5-month Summer NOX, May-September (tons) 7-month NOX, October-April (tons) VOC Rule Effectiveness (%) NOX Rule Effectiveness (%) CO Rule Effectiveness (%) SO2 Rule Effectiveness (%) PM10 Rule Effectiveness (%) PM25 Rule Effectiveness (%) NH3 Rule Effectiveness (%) III-16 ------- CHAPTER IV STATIONARY AREA SOURCES A. 1996 BASE YEAR EMISSIONS The 1996 base year inventory for stationary area sources is the 1996 NET area source inventory Version 3.11 (EPA, 2000a). Version 3.11 was at the time of this work the most current version that reflects corrections to wildfire emission estimates for Kansas and removal of area source electric utility emissions to avoid double counting with point source EGU emissions. Additionally, residential, on-site incineration emissions were removed from all States in the inventory and commercial wood combustion emissions were removed from Maryland and Maine. B. 2020 AND 2030 FUTURE YEAR EMISSIONS Projection year emissions are a function of projected changes (growth or decline) in activity as well as changes in control levels. The following sections describe the growth and control assumptions utilized for this analysis. 1. Growth Assumptions The BEA GSP growth, including population and combinations of industries (e.g., durable goods manufacturing, total manufacturing) were used to project emissions from 1996 to 2020 and 2030 for the area source sector. The surrogates used for each category were based on the same cross-reference list used in the Ozone/PM National Ambient Air Quality Standard (NAAQS) analysis (Pechan-Avanti, 1997b). Updated non-BEA growth factors were applied to estimate future year activity for prescribed burning (projections of acres of public land burned from EPA and Federal land managers), agricultural sources (acres planted projections), and unpaved road emissions based on work completed for EPA's Section 812 Prospective Analysis (Pechan-Avanti, 1998). Livestock emissions growth was also updated for this analysis, utilizing extrapolations of Census of Agriculture data. Pechan matched area source categories with surrogate activity indicators (e.g., GSP by industry, population, or broader BEA categories) in order to utilize the BEA data. The variable chosen as a proxy for emissions growth is shown by source category in Table IV-1. For broad industrial categories such as Industrial Fuel Combustion and Miscellaneous Industrial Processes, BEA GSP growth for the manufacturing sector represents the activity level for projecting emissions. Population was used as a surrogate growth indicator for area source categories such as Dry Cleaning, Household Solvent Use, and Residential Fuel Combustion. Projected emissions for each State/area source SCC combination were calculated by multiplying base year emissions by the growth factor for the BEA growth indicator. IV-1 ------- Table IV-1 BEA Growth Categories Assigned by Major Source Category: Area Sources Source Category BEA Growth Category* Stationary Source Fuel Combustion: Industrial Commercial/Institutional Residential Industrial Processes: Process Emissions: Synthetic Fiber Process Emissions: Pharmaceuticals SOCMI Fugitives Food & Kindred Products - Bakeries Petroleum Refining Oil & Gas Production Miscellaneous Industrial Processes Surface Coating: Architectural Auto Refinishing Traffic Markings Flat Wood Coating Wood and Metal Furniture Paper Coating Metal Can & Coating Electrical Insulation Appliances Machinery Motor Vehicles (New) Aircraft Coating Marine Paints Rail Equipment Coating Miscellaneous Manufacturing Industrial Maintenance Aerosols, Specific Purpose Degreasing (Vapor and Cold Cleaning): Furniture Metallurgical Process Fabricated Metals Industrial Machinery Electrical Equipment Transportation Equipment Instrument Manufacturing Miscellaneous Manufacturing Automobile Dealers & Repair Other Degreasing Sources Total Manufacturing Government and Government Enterprises Population Textile Mill Products (SIC 22) Chemicals and Allied Products (SIC 28) Chemicals and Allied Products (SIC 28) Food and Kindred Products (SIC 20) Petroleum and Coal Products (SIC 29) Oil and Gas Extraction (SIC 13) Total Manufacturing Construction (SIC 15, 16, and 17) Auto Repair, Services, and Garages (SIC 75) Construction (SIC 15, 16, and 17) Lumber and Wood Products (SIC 24) Furniture and Fixtures (SIC 25) Printing and Publishing (SIC 27) Fabricated Metal Products (SIC 34) Machinery, except Electrical (SIC 35) Fabricated Metal Products (SIC 34) Electric and Electronic Equipment (SIC 36) Motor Vehicles and Equipment (SIC 371) Transportation Equipment, excl. Motor Vehicles (SIC 37) Transportation Equipment, excl. Motor Vehicles (SIC 37) Transportation Equipment, excl. Motor Vehicles (SIC 37) Misc. Manufacturing Industries (SIC 39) Misc. Manufacturing Industries (SIC 39) Misc. Manufacturing Industries (SIC 39) Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Durable Durable Durable Durable Durable Durable Durable Durable Durable Durable Goods Goods Goods Goods Goods Goods Goods Goods Goods Goods IV-2 ------- Table IV-1 (continued) Source Category BEA Growth Category* Solvent Use: Dry Cleaning (all types) Graphic Arts Rubber and Plastics Industrial Adhesives Cutback Asphalt Pesticides - Farm Personal, Household and Automotive Products Commercial Adhesives Petroleum & Petroleum Product Storage & Transport: Bulk Stations/Terminals Gasoline Service Stations (Stage I and II) Gasoline Service Stations (Underground Tank) Waste Disposal, Treatment, & Recovery: On-Site Incineration - Industrial On-Site Incineration - Commercial/Institutional On-Site Incineration - Residential Open Burning - Industrial Open Burning - Commercial/Institutional Open Burning - Residential Wastewater Treatment - Public Owned TSDFs Miscellaneous Area Sources: Agriculture Production (field burning, tilling) Agricultural Livestock Prescribed burning Wildfires Unpaved Roads Paved Roads Population Printing and Publishing (SIC 27) Rubber and Misc. Plastics Products (SIC 30) Total Manufacturing Local/lnterurban Passenger Transit (SIC 41) Population Population Population Trucking and Warehousing (SIC 42) Gasoline Consumption** Gasoline Consumption** Total Manufacturing Government and Government Enterprises Population Total Manufacturing Government and Government Enterprises Population Electric, Gas, and Sanitary Services (SIC 49) Total Manufacturing USDA-Agricultural Baseline Projections Extrapolated from historical Census of Agriculture data Reflects expected increases in Federal prescribed burning activity on public lands Zero Growth Extrapolated from 1984 to 1996 trend in unpaved road mileage Vehicle miles traveled (VMT) from MOBILE4.1 Fuel Consumption Model (FCM) NOTES: *BEA growth category refers to GSP projections for each industry, unless "Population" is indicated. **Gasoline consumption projections are from the MOBILE FCM. IV-3 ------- The U.S. Department of Agriculture (USD A) has developed baseline projections of farm acres planted (USDA, 1998). These data, combined with historical data back to 1990, for eight major crop types shows an expected average annual growth of only 0.38 percent per year from 1990 to 2007. The BEA GSP projections for farms result in an annual average growth of 2.0 percent per year. Projections of acres planted represent better predictors of future activity than GSP for agricultural tilling, so the 0.38 percent per year value was used in this analysis to calculate emission estimates for 2020 and 2030. During an interagency (Department of the Interior/USD A) satellite conference held in April 1998, public forest land managers discussed an annual prescribed burning target of 5 million acres for 2010. However, as specific areas for burning were not identified, emission estimates for 2020 and 2030 were assumed to remain the same as the base year 1996 in this analysis. Unpaved road emission projections reflect the historical downward trend in miles of unpaved roads. The States were divided into three geographic groups: East, Central, and West. East was defined as EPA Regions 1 through 4, Central as EPA Regions 5 through 8, and West as EPA Regions 9 and 10. Linear regression was used to estimate the continued decline in unpaved road miles to 2030. For the emission projections, 2030 unpaved road emissions were estimated by applying the average annual change between 1984 and 1996 out to the projection year. For fuel combustion sources, energy adjustment factors were also applied to the baseline inventory. These factors, developed from the DOE publication Annual Energy Outlook 1999, account for increases in fuel and process efficiency in future years (DOE, 1998). Basically, less fuel will be needed to provide the same amount of energy (generally in the form of steam) to an industrial process and the amount of energy needed per unit output will also decrease as processes become more efficient. For example, DOE projects natural gas consumption in the commercial sector to rise from 3.392 quadrillion Btu in 1996 to 3.997 quadrillion Btu in 2020. Over this same time-frame, DOE projects commercial square footage to increase from 59.5 billion square feet to 72.9 billion square feet. To reflect the projected change in natural gas consumed per square foot of commercial building space, natural gas energy intensity factors were calculated for 1996 and each projection year. For example, 0.2475 quadrillion Btu/square foot of natural gas is projected to be consumed in 2020 versus 0.2551 quadrillion Btu/square foot in 1996. For all commercial sector natural gas source categories, the BEA commercial sector growth factors are multiplied by 0.97, which represents the ratio of the 2020 energy intensity factor for commercial sector natural gas to the 1996 energy intensity factor for commercial natural gas. Similar ratios were calculated and applied for other fuels used in the commercial sector, and for all fuels used in the residential and industrial energy sectors. These adjustments are based on those used in the NET projections (EPA, 2000a). For the animal husbandry SCCs displayed in Table IV-2, alternative methods were used to project emissions growth. For the majority of these SCCs (all except SCCs 2805001000, 2805020000, and 2805025000), emissions growth was based on projections of the number of animals in each category that were developed based on national data from the 1987, 1992, and 1997 Census of Agriculture (USDA, 1997). For these SCCs, growth factors are based on the increase in the number of animals between the base year and 2020 and 2030 as estimated from linear extrapolations of the Census data. Because linear extrapolation of the Census' number of sheep and lambs yielded negative growth factors that were believed to be unrealistic, the number IV-4 ------- of these animals was projected using an exponential trend function that provided more realistic growth factors. The growth factor for total livestock production (SCC 2805000000) was computed as the median of the growth factors for the individual SCCs that comprise this total category. For the following three animal husbandry source categories, growth factors were based on more comprehensive historical and projections data available from the USDA: Beef Cattle Feedlots (SCC 2805001000); Total Cattle/Calves (SCC 2805020000); and Hogs and Pigs (SCC 2805025000). For this effort, animal population data specific to each of these source categories were compiled for 1970-1999. The USDA publishes estimates of the total number of cattle/calves; total number of hogs and pigs; and total cattle in feedlots for historical years (USDA, 2000a). The USDA also projects the inventory of total cattle, total beef cows, and total hogs for each year over the 1998-2009 period (USDA, 2000b). It is important to note that the categories included in the USDA projections series do not match the emission source categories as closely as the categories in the USDA historical data series. For example, USDA projections are available for total beef cows, not cattle in feedlots. Because the USDA projections data represent somewhat different animal categories than the emission source categories and available historical data, the future animal counts were normalized on the same basis as the historic animal counts by computing the ratio of a source category's animal count in each future year to the animal count for 1999 as reported in the USDA's projections series. To estimate the future number of animals in each source category, these ratios are applied to the actual animal count for 1999, which is the latest year for which USDA historical data are available. After projecting these animal counts through 2009, the historical and forecast series for each source category were graphed to determine the functional form that best represented the data. Because the major fluctuations in the historical data for each category contradicted the clear trend in the USDA projection series for each category, the post-2009 trend in each category was identified based on the normalized projected animal counts for 2000-2009. The 2020 and 2030 animal counts were estimated by extrapolating to each year based on the following functional forms identified from the 2000-2009 data: Beef Cattle Feedlots-linear (stable slow decline in number); Total Cattle/Calves-linear (stable slow increase in number); and • Hogs and Pigs-logarithmic (declining rate of increase in number). To compute the growth factors for each source category, the estimated animal counts in 2020 and 2030 were divided by the actual animal counts in 1996. Because all growth rates for agricultural livestock operations were applied nationally, the projection method assumes no shifts in regional patterns after 1996. Table IV-2 Animal Husbandry Categories and Growth Assumptions IV-5 ------- Source Classification Code (SCC) 2710020030 2805000000 2805001000 2805020000 2805025000 2805030000 2805040000 2805045001 SCC Description Natural Sources Biogenic Horses and Ponies Misc. Area Sources Agric. Prod. -Livestock Total Misc. Area Sources Agric. Prod. - Livestock Beef Cattle Feedlots Total Misc. Area Sources Agric. Prod. -Animal Husbandry Cattle and Calves Composite Misc. Area Sources Agric. Prod. -Animal Husbandry Hogs and Pigs Composite Misc. Area Sources Agric. Prod. -Animal Husbandry Poultry -Chickens Composite Misc. Area Sources Agric. Prod. -Animal Husbandry Sheep and Lambs Composite Misc. Area Sources Agric. Prod. -Animal Husbandry Goats Composite Growth Function Linear extrapolation Median of growth factors from individual SCCs below Linear extrapolation Linear extrapolation Logarithmic extrapolation Linear extrapolation Exponential extrapolation Linear extrapolation Reference: USDA, 1997. 2. Control Assumptions VOC area source controls were applied for federal initiatives, such as VOC content limits for consumer solvents, Title III MACT assumptions, and Title IRACT assumptions that were not applied in the 1996 base year inventory. These controls are listed in Table IV-3. Additional controls were applied for residential wood combustion and Stage II VOC for gasoline service stations. Table IV-4 shows the control efficiencies applied for residential wood combustion by pollutant (VOC, PM10, PM25, and CO) for each of the future year inventories. Residential wood combustion control efficiencies were derived from emission factors obtained from AP-42, a 4 percent per year growth rate for catalytic wood stoves starting in 1988, and an estimate of the control efficiencies applied in the 1996 base year inventory. Table IV-5 shows the control efficiencies applied to account for VOC reductions associated with onboard vapor recovery systems and Stage II controls at gasoline service stations. Vehicle refueling VOC emissions were estimated using different methods for counties required to have Stage II VOC controls versus counties not required to have Stage II VOC controls. Serious and above ozone nonatttainment areas are required to implement Stage II (at the nozzle) vapor recovery systems under Title I of the CAA. Table IV-6 shows the 227 counties required to have Stage II controls. Onboard vapor recovery systems on gasoline-fueled vehicles are required in 1998 and later vehicles in all areas, independent of attainment status. However, slightly higher control efficiencies are estimated for counties where Stage II refueling controls are required. Control efficiencies were calculated using weighted gram per gallon emission factors determined using a series of MOBILESa runs. These runs also accounted for the expected effect of onboard vapor recovery systems on future year evaporative emissions from gasoline-powered vehicles. IV-6 ------- The Stage II control efficiencies used depended on both county and projection year. A cross- reference that contained the counties assumed to have Stage II controls at the pump in 1996 was developed and it was assumed that counties with base year Stage II controls did receive additional reductions in the future because of on-board vapor recovery systems being phased in over time. IV-7 ------- Table IV-3 Area Source VOC Control Measure Assumptions Control Measure and Affected SCCs VOC Percentage Reduction VOC Rule Effectiveness Federal Control Measures (National) Consumer Solvents 25 2465000000, 2465100000, 2465200000, 2465600000, 2456800000 Architectural and Industrial Maintenance Coatings 25 2401001000,2401001999,2401100000,2401008000 Residential Wood Combustion See Table 2104008000,2104008001, 2104008010, 2104008030, IV-4 2104008050,2104008051 Onboard Vapor Recovery Systems; and Stage II for Gasoline See Table Service Stations IV-5 2501060100,2501060101,2501060102 100 100 Title III MACT (National) Wood Furniture Surface Coating 30 2401020000 Aerospace Surface Coating 60 2401075000 Marine Vessel Surface Coating (Shipbuilding) 24 2401080000 Halogenated Solvent Cleaners (Cold Cleaning) 43 ** 2415300000,2415305000,2415310000,2415320000, 2415325000,2415330000,2415335000,2415340000, 2415345000,2415355000, 2415360000, 2415365000 Autobody Refinishing 37 2401005000 Petroleum Refinery Fugitives 60 *** 2306000000 Synthetic Organic Chemical Manufacturing Industry (SOCMI) 37 **** Fugitives (Hazardous Organic NESHAP) 2301040000 Motor Vehicle Surface Coating 36 2401070000 Metal Product Surface Coating 36 2401040000,2401045000,2401050000 100 100 100 100 100 100 100 100 100 IV-8 ------- Table IV-3 (continued) voc Percentage VOC Rule Control Measure and Affected SCCs Reduction Effectiveness Wood Product Surface Coating 36 100 2401015000 Open Top & Conveyorized Degreasing 31 100 2415100000,2415105000,2415110000,2415120000, 2415125000,2415130000,2415135000,2415140000, 2415145000,2415199000, 2415200000 Publicly Owned Treatment Works (POTWs) 80 100 2630000000 to 2630020000 Metal Furniture & Appliances Surface Coating 36 100 2401025000,2401060000 Machinery, Railroad Surface Coating 36 100 2401055000,2401085000,2401090000 Electronic Coating 36 100 2401065000 Title I RACT Petroleum Dry Cleaning 44 80 2420000370,2420010370 Paper Surface Coating 78 80 2401030000 NOTES: * The efficiency of onboard vapor recovery systems varies depending on whether stage II vapor recovery systems are in place. It is determined based on MOBILESb emission factors. ** Overall control efficiency of 63% with 35% already applied in base year. *** Overall control efficiency of 78% with 43% already applied in base year. **** Overall control efficiency of 60% with 37% already applied in base year. IV-9 ------- Table IV-4 Residential Wood Combustion Control Efficiency Assumptions by Pollutant and Future Year Inventory Pollutant 2020 Percent Reduction 2030 Percent Reduction VOC 72 72 PM10 and 51 51 PM25a CO 55 55 a All residential wood combustion PM emissions are assumed to be less than or equal to PM2 5. Table IV-5 Vehicle Refueling VOC Control Efficiency Assumptions Included in the Future Year Inventories Does County Have Stage II Controls in 1996? 2020 Percent Reduction 2030 Percent Reduction No 82.4 85.8 Yes 87.6 88.3 IV-10 ------- Table IV-6 Counties with Stage II Controls State Arizona California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Delaware Delaware Delaware Dist. Columbia Florida Florida Florida Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia County Maricopa Alameda Contra Costa El Dorado Fresno Kern Kings Los Angeles Madera Marin Merced Monterey Napa Orange Placer Riverside Sacramento San Benito San Bernardino San Diego San Joaquin San Mateo Santa Barbara Santa Clara Santa Cruz Solano Sonoma Stanislaus Sutler Tulare Ventura Yolo Fairfield Hartford Litchfield Middlesex New Haven New London Tolland Windham Kent New Castle Sussex Washington B reward Dade Palm Beach Cherokee Clayton Cobb Coweta De Kalb Douglas Fayette Forsyth Fulton Gwinnett Henry Paulding Rockdale State FIPS Code 04 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 09 09 09 09 09 09 09 09 10 10 10 11 12 12 12 13 13 13 13 13 13 13 13 13 13 13 13 13 County FIPS Code 013 001 013 017 019 029 031 037 039 041 047 053 055 059 061 065 067 069 071 073 077 081 083 085 087 095 097 099 101 107 111 113 001 003 005 007 009 011 013 015 001 003 005 001 011 025 099 057 063 067 077 089 097 113 117 121 135 151 223 247 IV-11 ------- Table IV-6 (continued) State Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Indiana Indiana Indiana Indiana Kentucky Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Missouri Missouri Missouri Missouri Missouri Nevada Nevada County Cook Du Page Grundy Kane Kendall Lake McHenry Will Clark Floyd Lake Porter Jefferson Ascension Parish East Baton Rouge Parish Iberville Parish Livingston Parish Pointe Coupee Parish West Baton Rouge Parish Anne Arundel Baltimore Calvert Carroll Cecil Charles Frederick Harford Howard Montgomery Prince Georges Baltim Barnstable Berkshire Bristol Dukes Essex Franklin Hampden Hampshire Middlesex Nantucket Norfolk Plymouth Suffolk Worcester Kent Livingston Macomb Monroe Oakland Ottawa St. Clair Washtenaw Wayne Franklin Jefferson St. Charles St. Louis St. Lo Clark Washoe State FIPS Code 17 17 17 17 17 17 17 17 18 18 18 18 21 22 22 22 22 22 22 24 24 24 24 24 24 24 24 24 24 24 24 25 25 25 25 25 25 25 25 25 25 25 25 25 25 26 26 26 26 26 26 26 26 26 29 29 29 29 29 32 32 County FIPS Code 031 043 063 089 093 097 111 197 019 043 089 127 111 005 033 047 063 077 121 003 005 009 013 015 017 021 025 027 031 033 510 001 003 005 007 009 011 013 015 017 019 021 023 025 027 081 093 099 115 125 139 147 161 163 071 099 183 189 510 003 031 IV-12 ------- Table IV-6 (continued) State New Hampshire New Hampshire New Hampshire New Hampshire New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New York New York New York New York New York New York New York New York New York New York Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Rhode Island Rhode Island Rhode Island Rhode Island Rhode Island Tennessee Tennessee County Hillsborough Merrimack Rockingham Strafford Atlantic Bergen Burlington Camden Cape May Cumberland Essex Gloucester Hudson Hunterdon Mercer Middlesex Monmouth Morris Ocean Passaic Salem Somerset Sussex Union Warren Bronx Kings Nassau New York Orange Queens Richmond Rockland Suffolk Westchester Ashtabula Clark Cuyahoga Geauga Greene Lake Lorain Lucas Medina Miami Montgomery Portage Summit Wood Bucks Chester Delaware Montgomery Philadelphia Bristol Kent Newport Providence Washington Davidson Rutherford State FIPS Code 33 33 33 33 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 36 36 36 36 36 36 36 36 36 36 39 39 39 39 39 39 39 39 39 39 39 39 39 39 42 42 42 42 42 44 44 44 44 44 47 47 County FIPS Code 011 013 015 017 001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 005 047 059 061 071 081 085 087 103 119 007 023 035 055 057 085 093 095 103 109 113 133 153 173 017 029 045 091 101 001 003 005 007 009 037 149 IV-13 ------- Table IV-6 (continued) State Tennessee Tennessee Tennessee Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin County Sumner Williamson Wilson Brazoria Chambers Collin Dallas Denton El Paso Fort Bend Galveston Hardin Harris Jefferson Liberty Montgomery Orange Tarrant Waller Arlington Charles City Chesterfield Fairfax Hanover Henrico Loudoun Prince William Stafford Alexandria Colonial Heights Fairfax Falls Church Hopewell Manassas Manassas Park Richmond Kenosha Kewaunee Manitowoc Milwaukee Ozaukee Racine Sheboygan Washington Waukesha State FIPS Code 47 47 47 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 55 55 55 55 55 55 55 55 55 County FIPS Code 165 187 189 039 071 085 113 121 141 157 167 199 201 245 291 339 361 439 473 013 036 041 059 085 087 107 153 179 510 570 600 610 670 683 685 760 059 061 071 079 089 101 117 131 133 IV-14 ------- C. MASS EMISSIONS INVENTORY FILES The structure for the area source mass emission inventory files is shown in Table IV-7. A change to emissions is the application of the crustal PM factor. This factor accounts for the fact that only a portion of the crustal PM emissions are transportable. For the emission files, a factor of 25 percent was applied to PM10 and PM25 emissions for the SCCs listed in Table IV-8 to simulate the transportable component of these emissions. In addition, PM10 and PM25 emissions from wind erosion of natural geogenic sources (SCCs 2730100000 [total] and 2730100001 [dust devils]) were excluded from the modeling files. IV-15 ------- Table IV-7 Area Mass Emissions Inventory File Structure Variable FIPSST FIPSCNTY sec VOC_ANN NOX_ANN CO_ANN SO2_ANN PM10_ANN PM25_ANN NH3_ANN VOC_OSD NOXJDSD CO_OSD S02_OSD PM10_OSD PM25_OSD NH3JDSD VOC_EMF NOX_EMF CO_EMF S02_EMF PM10_EMF PM25_EMF NH3_EMF VOC_CE NOX_CE CO_CE S02_CE PM10_CE PM25_CE NH3_CE VOC_RE NOX_RE CO RE Type C C C N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N Length 2 3 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 7 7 7 7 7 7 7 3 3 3 Decimals 0 0 0 4 4 4 4 4 4 4 4 4 4 4 4 4 6 4 4 4 4 4 4 4 2 2 2 2 2 2 2 0 0 0 Description FIPS State code FIPS county code sec Annual VOC [tons per year (tpy)] Annual NOX (tpy) Annual CO (tpy) Annual SO2 (tpy) Annual PM10 (tpy) Annual PM25 (tpy) Annual NH3 (tpy) OSD VOC (tpd) OSD NOX (tpd) OSD CO (tpd) OSD S02 (tpd) OSD PM10 (tpd) OSD PM25 (tpd) OSD NH3 (tpd) VOC Emission Factor NOX Emission Factor CO Emission Factor SO2 Emission Factor PM10 Emission Factor PM25 Emission Factor NH3 Emission Factor VOC Control Efficiency NOX Control Efficiency CO Control Efficiency SO2 Control Efficiency PM10 Control Efficiency PM25 Control Efficiency NH3 Control Efficiency VOC Rule Effectiveness NOX Rule Effectiveness CO Rule Effectiveness IV-16 ------- Table IV-7 (continued) Variable Type Length Decimals Description SO2_RE PM10_RE PM25_RE NH3_RE VOC_RP NOX_RP CO_RP SO2_RP PM10_RP PM25_RP NH3 RP N N N N N N N N N N N 3 3 3 3 6 6 6 6 6 6 6 0 SO2 Rule Effectiveness 0 PM10 Rule Effectiveness 0 PM2 5 Rule Effectiveness 0 NH3 Rule Effectiveness 2 VOC Rule Penetration 2 NOX Rule Penetration 2 CO Rule Penetration 2 SO2 Rule Penetration 2 PM10 Rule Penetration 2 PM25 Rule Penetration 2 NH, Rule Penetration IV-17 ------- Table IV-8 Sources to which Crustal Factor was Applied to PM10 and PM25 Emissions Sector/SCC Source Category Description Mobile Sources/Aircraft 227508xxxx Unpaved Airstrips Mobile Sources/Paved Roads 2294xxxxxx Paved Roads Mobile Sources/Unpaved Roads 2296xxxxxx Unpaved Roads Industrial Processes/Construction (SIC codes 15-17) 23110001xx All Processes: Wind Erosion 23110101xx General Building Construction: Wind Erosion 23110201xx Heavy Construction: Wind Erosion 23110301xx Road Construction: Wind Erosion 23110401xx Special Trade Construction: Wind Erosion Miscellaneous Area Sources/Agriculture Production - Crops 28010xxxxx Agriculture - Crops 28017xxxxx Fertilizer Application Miscellaneous Area Sources/Agriculture Production - Livestock 2805xxxxxx Agriculture Production - Livestock IV-18 ------- CHAPTER V NONROAD SOURCES A. 1996 BASE YEAR MASS EMISSIONS INVENTORY County-level emission estimates for 1996 for the majority of nonroad sources were developed using EPA's March 2002 draft NONROAD model. Emission estimates for VOC, NOX, CO, SO2, PM10, and PM2 5 are reported by the model. The NONROAD model does not estimate NH3 emissions; therefore, these emissions were calculated outside the model. Aircraft, commercial marine, and locomotives are not presently included in the NONROAD model, and the procedures to develop emission estimates for these categories are discussed separately. 1. NONROAD Model Equipment Categories The NONROAD model estimates pollutant emissions for the following general equipment categories: (1) agricultural; (2) airport service; (3) light commercial; (4) construction and mining; (5) industrial; (6) lawn and garden; (7) logging; (8) pleasure craft; (9) railway maintenance; and (10) recreational equipment. These applications are further classified according to fuel and engine type [diesel, gasoline 2-stroke, gasoline 4-stroke, compressed natural gas (CNG), and liquified petroleum gas (LPG)]. The base year nonroad mass emissions inventory for the Nonroad Compression-Ignition (C- I) rulemaking was developed from two emission inventories including: (1) a 1996 county-level inventory, based on EPA's October 2001 draft NONROAD model; and (2) an updated national inventory, based on EPA's latest draft of the NONROAD model, dated March 2002. Using the county-level emission estimates referenced in (1), seasonal and daily county-to-national ratios were then developed for application to updated national estimates per season referenced in (2). To develop an updated county-level inventory for 1996, NONROAD model input files were prepared for each State to account for the average statewide temperatures and Reid vapor pressure (RVP) for four seasons, including summer, fall, winter, and spring. Input files were also generated to account for county-level differences in RVP, fuel characteristics due to reformulated gasoline (RFG) and oxygenated fuel programs, and Stage II controls. The statewide seasonal default RVP values used as input to the NONROAD model runs are presented in Table V-l. For areas subject to Phase I of the Federal RFG program, separate RVP values were modeled in the 1996 NONROAD inputs for May through September (values not shown). The areas and counties modeled with RFG are shown in Table VI-4 of Chapter VI "On-Highway Vehicle Sources." Oxygenated fuel was modeled in the areas participating in this program in 1996, as presented in Table VI-6. For all States except California, a diesel fuel sulfur level of 3300 parts per million (ppm) was used in the modeling runs. For California, a diesel fuel sulfur content of 120 ppm was used. V-l ------- Emissions calculated for counties with fuel characteristic and control data that varied from statewide average values replaced emissions for these same counties generated by running the default input files. Pechan calculated seasonal, county-to-national emissions ratios for each 10-digit SCC and pollutant based on county emissions divided by the sum total of county-level emissions for the nation. This was done for each of the four seasons and a typical summer weekday. This ensured that the fractions calculated for county-to-national emissions all added up to 1 at the national level. Fractions representing county-to-national fuel consumption were also developed in the same manner as the emission ratios, for use as activity to estimate NH3 emissions. Fuel consumption was available for gasoline and diesel-fueled engines, as well as LPG and CNG engines. The 1996 county-level emissions inventory was then updated to reflect revisions made to the NONROAD model since the October 2001 version. Using the March 2002 NONROAD model, national, seasonal emissions were generated at the SCC level for the following pollutants: VOC, NOX, SO2, CO, PM10, and PM2 5. Emission estimates were developed for 4 seasons, as well as for a typical summer weekday. To account for lower diesel fuel sulfur levels in California, separate runs were performed for this State for diesel-fueled equipment SCCs. Tables V-2a and V-2b present a summary of the input values used for the national NONROAD model runs. These national RVP input values were taken from the Procedures Document for National Emission Inventory, Criteria Air Pollutants 1985-1999 (EPA, 1999c). The diesel fuel sulfur input values were provided to Pechan in personal communication with the Office of Air Quality and Transportation (OTAQ) staff. National, SCC-level emissions for each of the four seasons (i.e., summer, winter, fall, and spring) were then multiplied by the season-specific county-to-national emissions ratios. The following formula represents how an updated 1996 (or alternate year) county-level annual emissions inventory was developed for a given SCC and pollutant. EAnn, Cty, y = ^ [(Es, Cty,1996 + Es, N,1996) * Es, N, y] Where: E = Emissions, tons Ann = Annual S = Season (winter, spring, summer, fall) Cty = County N = National y = year of inventory (e.g., 1996, 2020, or 2030) V-2 ------- Table V-1. Seasonal RVP Values Modeled for 1996 NONROAD Model Runs Seasonal RVP (psi)1 FIPS2 State State Code AL AK AZ AR CA (Los Angeles Region) CA (San Francisco Region) CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA Ml MN MS MO MT NE NV NH NJ NM 01 02 04 05 06 06 08 09 10 11 12 13 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Winter 12.4 14.1 8.2 13.7 11.9 11.7 12.5 13.0 13.5 12.0 11.8 12.4 10.0 12.8 14.1 14.5 14.9 12.7 13.4 12.4 13.2 13.2 12.9 14.1 14.9 13.7 12.6 13.8 13.9 9.6 12.9 13.7 11.7 Spring Summer Autumn 9.3 13.7 7.1 9.5 9.3 10.8 10.1 9.8 10.0 8.1 7.4 9.3 10.0 10.4 10.2 10.9 11.2 8.9 9.5 9.4 10.3 9.7 9.7 9.9 11.4 9.5 10.0 10.4 10.6 8.0 9.7 10.5 9.2 7.5 13 6.8 6.8 6.9 6.9 7.8 7.9 7.9 7.0 7.4 7.4 9.8 8.6 7.8 8.8 9.0 7.6 8.4 7.6 9.0 7.5 7.8 7.4 9.0 7.1 7.2 8.7 8.6 7.6 7.8 8.8 7.8 8.8 13.7 6.9 10.1 7.6 7.6 9.4 9.8 9 8.1 7.4 8.7 10 9.1 9 9.8 11.2 8.2 9.5 8.9 10.3 8.6 9.7 9.9 10.4 8.8 9.4 10.4 9.2 7.8 9.7 10.5 9.0 V-3 ------- Table V-1 (Continued) Seasonal RVP (psi)1 State NY NC ND OH OK OR PA Rl SC SD TN TX UT VT VA WA WV Wl WY FIPS2 State Code 36 37 38 39 40 41 42 44 45 46 47 48 49 50 51 53 54 55 56 Winter 14.3 12.4 14.9 14.6 13.9 12.3 14.4 12.9 12.4 14.4 12.7 12.2 12.5 14.9 11.8 14.0 14.6 14.6 13.0 Spring Summer Autumn 10.9 10.3 11.9 11.0 9.1 9.8 10.9 9.7 10.3 11.2 10.4 9.7 10.6 11.4 8.2 10.6 11.0 11.1 10.4 8.8 7.4 9.0 8.7 7.2 7.7 8.8 7.8 7.4 9.0 7.3 7.8 7.8 9.0 7.2 8.5 8.8 9.0 8.8 10.9 9.7 11.2 9.8 8.2 8.7 10.9 9.7 9.7 9.9 9.8 8.7 9.4 11.4 8.2 9.5 9.9 10.1 9.3 Notes: For areas receiving reformulated gasoline May through September, RVP values were modeled in place of the values shown here. 1 pounds per square inch 2 Federal Information Processing Standards Pechan also generated state-level, seasonal emissions at the SCC level for California. County-to-state ratios were developed and applied in a manner similar to the county-to-national ratios to produce an updated diesel equipment inventory for California. These California results replace the diesel equipment emissions generated from prior application of county-to-national ratios. In addition to the seasonal runs, typical summer weekday (SSD) NONROAD model runs were performed at the national level and for California. Updated county-level typical summer weekday emissions were developed by applying county-to-national daily emissions ratios (or county-to-state emission ratios for California) to the national daily results. The emissions inputs developed for the air quality modeling and reported in this document are required early in the analytical process and therefore was based on a preliminary set of base and control scenario parameters. Since the preliminary scenario was developed, more V-4 ------- information has been gathered regarding the technical feasibility of the standards. As a result minor changes have been made to the final baseline and control case fuel sulfur levels (EPA, 2003). Table V-2a Temperature and RVP Inputs for National NONROAD Model Runs1 Season Summer Fall/Spring Winter Typical Summer Weekday Input2 RVP (psi) Min Temp (°F) Max Temp (°F) Average Temp (°F) RVP (psi) Min Temp (°F) Max Temp (°F) Average Temp (°F) RVP (psi) Min Temp (°F) Max Temp (°F) Average Temp (°F) RVP (psi) Min Temp (°F) Max Temp (°F) Average Temp (°F) Value 8.1 62 82 72 9.7 43 63 53 13.1 24 44 34 8.1 62 82 72 1 The input values presented were the same for both base and control cases and for all years. The control case input values were the same for all three projection years (no control case was developed for 1996). 2 Values for minimum, maximum, and average temperature are expressed in degrees Fahrenheit (°F). Table V-2b Diesel Fuel Sulfur Input Values for National NONROAD Model Runs1 Year 1996 Fuel Sulfur, ppm Base case2 2700 Control case3 Not applicable 1 Diesel fuel sulfur does not change seasonally. 2 For 1996 California base case runs, a diesel fuel sulfur content of 120 ppm was used for all seasons. 3 For 1996 California control case runs, a diesel fuel sulfur content of 120 ppm was used for all seasons. V-5 ------- 2. Emission Estimates for Aircraft, Commercial Marine Vessels, and Locomotives Base year aircraft, locomotive and distillate commercial marine vessel (CMV) emissions were taken from the existing 1996 HDDV inventory (Pechan, 2000). Adjustments were made to PM10 and SO2 emissions for locomotive source categories and SO2 emissions for CMV source categories using 49-State and California SO2 and PM10 emissions supplied by OTAQ (Wilcox, 2002). 49-State and California locomotive SO2 emissions are based on new estimates of activity corresponding to 1996 locomotive fuel usage. The activity data were calculated by subtracting the 1996 railroad distillate consumption obtained from the Energy Information Administration (EIA) "Fuel Oil and Kerosene Sales 2000" report to the total rail maintenance source category fuel consumption obtained from the NONROAD model (EIA, 2000). The locomotive fuel usage was multiplied by the appropriate sulfur level and necessary conversion factors. Base and control case sulfur levels in parts per million for both 49-State and California are listed in Table V-3. CMV SO2 emissions are based on activity data corresponding to 1996 commercial marine fuel usage. The activity data were calculated by subtracting the 1996 vessel bunkering distillate consumption obtained from the EIA "Fuel Oil and Kerosene Sales 2000" report to the total recreational marine diesel source category fuel consumption obtained from the NONROAD model. The CMV fuel usage was multiplied by the appropriate sulfur level. The 1996 PM10 emissions for both locomotive and CMV were estimated using the same activity data as SO2 emissions. The PM10 emission factor applied to fuel usage is listed in Table V-3. 49-State and California SSD SO2 and PM10 emissions were estimated by dividing the annual emissions, supplied by OTAQ, by 365 days. Table V-3 Sulfur Concentrations and PM10 Emission Factors for Locomotive and CMV Emission Calculations Year 1996 Area 49-State California Sulfur Concentration (ppm) 2700 120 PM10 Emission Factor1 (g/gai) 6.8 1 PM10 Emission Factor is for locomotives only. Locomotive and distillate CMV emissions from the 1996 HDDV inventory were first summed up to the 49-State and California level. A ratio adjustment factor was calculated by dividing the sums from the 1996 HDDV inventory by the appropriate SO2 and PM10 emissions supplied by OTAQ. The adjustment factor was then applied back to the SO2 and PM10 annual and SSD emissions in the county-level inventory to generate updated PM10 and SO2 emissions. PM25 emissions were estimated by multiplying the updated PM10 emissions by a factor of 0.92. V-6 ------- 3. Methodologies for NH3 Ammonia emissions were estimated based on updated national, SCC-level fuel consumption estimates, as reported by the March 2002 NONROAD model. As with the criteria pollutant emission estimates, SCC-specific ratios were developed by dividing county-level fuel consumption values by national fuel consumption values estimated with the October 2001 draft NONROAD model. NH3 emissions for California were also recalculated using updated diesel fuel consumption values generated for California-specific runs. Once a county-level data base of fuel consumption was developed, emission factors provided by OTAQ were then applied to these activity data to estimate NH3 emissions. The emission factors were derived primarily from light- duty on-road vehicle emission measurements, and extrapolated to nonroad engines on a fuel consumption basis. NH3 emissions for diesel engines were calculated by multiplying diesel fuel consumption by an emission factor of 165.86 milligrams/gallon. NH3 emissions from gasoline engines (without catalysts) were calculated by multiplying gasoline consumption by an emission factor of 153.47 milligrams/gallon. Base year locomotive and distillate CMV NH3 emissions were taken from the existing 1996 HDDV inventory (Pechan, 2000). For aircraft categories, jet fuel and aviation gasoline consumption for general aviation and commercial aircraft were obtained from the "FAA Aviation Forecasts Fiscal Years, 1998-2009," (FAA, 1998a). For the aircraft categories, NH3 emission factors developed for diesel engines were applied to all fuel consumption estimates, since aviation gasoline consumption was determined to be relatively small compared to jet fuel, and the aircraft SCCs are not broken down by fuel type. B. 2020 AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES The methods for developing base case and control scenario projection year inventories for nonroad sources are described in this section. Table V-4 provides a summary of the projection methods, as well as growth indicators, used for each nonroad equipment category. 1. Nonroad Model Equipment Categories For NONROAD model categories, emission estimates for projection years were developed using a method comparable to that for the base year. First, four seasonal NONROAD model runs were performed at the national level for both 2020 and 2030. Seasonal runs accounted for differences in average seasonal temperature, as well as RVP. Second, updated county-level estimates were then calculated for 2020 and 2030 by multiplying national, seasonal SCC-level emissions by the 1996 season-specific county-to-national emissions ratios. Seasonal county- level emissions are then summed up to estimate annual emissions. In this manner, the county- level distribution assumed for the 1996 inventory is normalized to the updated national, SCC- level totals for each projection year. As with the base year, separate NONROAD model runs were done for California diesel- fueled SCCs. County-to-state ratios were developed and applied in a manner similar to the county-to-national ratios to produce an updated diesel equipment inventory for California. Additional runs were also performed to estimate typical summer weekday emissions for each projection year. V-7 ------- In addition to a base case scenario, control case emission inventories were developed for each projection year to account for the effects of the proposed NONROAD C-I emission standards that are the subject of this rulemaking as well as proposed reductions in diesel sulfur content. Table V-5 presents the diesel fuel sulfur values assumed for the modeling base case and control case scenarios. Separate runs were performed for California to account for the lower diesel fuel sulfur content in this State (i.e., 120 ppm for the base case, and 11 ppm for the control scenario). Table V-4 Growth Indicators/Projection Methods for Nonroad Sources Nonroad SCC 2260xxxxxx 2265xxxxxx 2267xxxxxx 2268xxxxxx 2270xxxxxx 2282xxxxxx 2285xxx015 SCC Description 2-stroke gasoline 4-stroke gasoline CNG LPG Diesel Recreational marine Railway maintenance Growth Indicator Not applicable1 2275050000, 2275060000 2275020000, 2275070000 General Aviation and Air Taxis Commercial Aircraft and Auxiliary Power Units Landing-Takeoff Operations (LTOs) for total aircraft operations 2275001xxx Military Aircraft 992 - Federal, Military 2275085xxx Unpaved Airstrips SIC 45 - Air Transportation 2275900XXX Aircraft Refueling SIC 45 - Air Transportation 2280002XXX Commercial Marine - Diesel Vessels SIC 44 - Water Transportation2 2280001xxx, 2280003xxx, Commercial Marine - Coal, Residual 2280004xxx Oil, and Gas-fired Vessels SIC 44 - Water Transportation 2283xxxxxx Military Marine Vessels 992 - Federal, Military 2285xxxxxx Locomotives No growth3 1 Projection year emission estimates were derived from national NONROAD model runs allocated to counties based on the geographic distribution of a 1996 county-level inventory, developed from the October2001 draft version of NONROAD. 2 NH3 emissions were projected using growth factors; projection year estimates for all other pollutants provided by OTAQ and allocated to counties using ratios from the 1996 inventory. 3 NH3 emissions for projection years assumed to remain constant at 1996 uncontrolled levels; controlled projection year estimates for all other pollutants provided by OTAQ. As discussed earlier in this document, the emissions inputs for the air quality modeling are required early in the analytical process in order to be able to conduct the air quality modeling and present the results in this proposal. The air quality modeling was based on a preliminary control scenario. Since the preliminary control scenario was developed, more information was gathered regarding the technical feasibility of the standards. As a result, both the base and control case scenarios were modified. Detailed information on these modifications can be found in the associated Regulatory Impact Analysis Technical Support Document (EPA, 2003). V-8 ------- Table V-5 Diesel Fuel Sulfur Input Values for National NONROAD Model Runs1 Year 2020 2030 Fuel Sulfur, ppm Base case2 2700 2700 Control case3 11 11 1 Diesel fuel sulfur does not change seasonally. 2 For 1996 California base case runs, a diesel fuel sulfur content of 120 ppm was used for all seasons. For 2020 and 2030 California base case runs, a diesel fuel sulfur content of 11 ppm was used for all seasons. 3 For 1996 California control case runs, a diesel fuel sulfur content of 120 ppm was used for all seasons. For 2020 and 2030 California control case runs, a diesel fuel sulfur content of 11 ppm was used for all seasons. a. Growth Assumptions Nonroad category emissions have typically been projected using economic indicators that are believed to correlate to nonroad equipment activity. For example, nonroad agricultural equipment emissions have been grown in the past using BEA GSP projections for SIC code 01, which corresponds to the farm industry. However, instead of using economic indicators to project emissions or nonroad activity, the current version of the NONROAD model predicts future year nonroad equipment populations by extrapolating from a linear regression of historical equipment populations. Because total activity is never directly measured, the historical trend in population must be used as a surrogate. A time-series analysis using historic equipment populations is believed to better reflect market trends within each sector (e.g., a shift from gasoline-fueled equipment to diesel-fueled equipment). Accurately estimating the relative distribution of different engine types in the future is important since diesel and gasoline engines have distinct emission characteristics. This approach, however, is not planned to be used for all equipment types in the final version of the NONROAD model. Some exceptions include oil field equipment and aircraft ground support equipment, which will rely on BEA GSP data and Federal Aviation Administration (FAA) LTO data, respectively. b. Control Assumptions The NONROAD model accounts for the effect of Federal nonroad engine emission standards which were final at the time of model formulation, or proposed standards expected to be final soon after. The emission levels associated with compression-ignition (CI) and spark- ignition (SI) engine standards are incorporated into emission factors, which are then applied to future year nonroad equipment populations. The control programs already in place accounted for in the base case inventories by the NONROAD model include: (1) Tier 1, Tier 2 and Tier 3 CI standards for diesel engines ranging from 50 horsepower (hp) to 750 hp; (2) Tier 1 and Tier 2 CI standards for diesel engines below 50 hp and greater than 750 hp; (3) Phase I and Phase 2 of the SI standards for gasoline engines less than 25 hp; and (4) recreational SI marine engine controls. The control case inventories also account for the effects of proposed CI standards covering all hp categories. The proposed CI standards as designated as Tier 4 standards. V-9 ------- Pre-controlled and controlled steady-state emission factors for various horsepower ranges of CI engines prior to control and subject to the current and proposed standards are presented in Table V-6. Pre-controlled and controlled steady-state emission factors for SI engines below 25 hp (19 kilowatts) are presented in Table V-7. Additional details for these categories, as well as SI engines greater than 25 hp and SI recreational marine engines, are presented in technical reports that serve as supporting documentation for NONROAD model inputs (EPA, 2002a and EPA, 2002b). Compression-ignition engine emission factor values listed in Table V-6 reflect revisions made to the NONROAD model since the June 2000 draft version. The impact of RFG in the appropriate counties is reflected in the 1996 base year county- level inventory, in that the fuel RVP and percent oxygen were adjusted, as described in section V.A.I, for counties subject to RFG and oxygenated fuels requirements. No further adjustments were made to the NONROAD inputs to account for the use of RFG in future years. V-10 ------- Table V-6 Steady-State Emission Factors for Cl Engines in the NONROAD Model Engine Power (hp) >0 to 1 1 >1 1 to 25 >25 to 50 >50to 100 >100to 175 >1 75 to 300 Model Year 88-99 00-04 05-09 10-11 12- 88-99 00-04 05-09 10-11 12- 88-98 99-03 04-09 10-11 12- 88-97 98-03 04-07 08-09 10-11 12- 88-96 97-02 03-06 07-09 10-11 12- 88-95 96-02 03-05 06-08 09-10 11- Regulation - TieM Tier 2 Transitional Tier42 Final Tier42 - TieM Tier 2 Transitional Tier42 Final Tier42 - TieM Tier 2 Transitional Tier42 Final Tier42 - TieM Tier 2 TierS Transitional Tier42 Final Tier42 - Tierl Tier 2 TierS Transitional Tier42 Final Tier42 - Tierl Tier 2 TierS Transitional Tier42 Final Tier42 Emission Factors (g/hp-hr) HC 1.5 0.7628 0.5508 0.1314 0.1314 1.7 0.4380 0.4380 0.1314 0.1314 1.8 0.2789 0.2789 0.1314 0.1314 0.99 0.5213 0.3672 0.1836 0.1314 0.1314 0.68 0.3384 0.3384 0.1836 0.1314 0.1314 0.68 0.3085 0.3085 0.1836 0.1314 0.1314 CO 5.0 4.1127 4.1127 0.411 0.411 5.0 2.1610 2.1610 0.216 0.216 5.0 1.5323 1.5323 0.153 0.153 3.49 2.3655 2.3655 2.3655 0.237 0.237 2.7 0.8667 0.8667 0.8667 0.087 0.087 2.7 0.7475 0.7475 0.7475 0.075 0.075 NOX 10.0 5.2298 4.3 4.3 0.276 8.5 4.4399 4.4399 4.4399 0.276 6.9 4.7279 4.7279 4.7279 0.276 6.9 5.5988 4.7 3.0 3.0 0.276 8.38 5.6523 4.1 2.5 2.5 0.276 8.38 5.5772 4.0 2.5 2.5 0.276 PM1 1.0 0.4474 0.50 0.0092 0.0092 0.9 0.2665 0.2665 0.0092 0.0092 0.8 0.3389 0.3389 0.0092 0.0092 0.722 0.4730 0.24 0.30 0.0092 0.0092 0.402 0.2799 0.18 0.22 0.0092 0.0092 0.402 0.2521 0.1316 0.15 0.0092 0.0092 V-ll ------- Table V-6 (continued) Engine Power (hp) >300 to 600 >600 to 750 >750 Model Year 88-95 96-00 01-05 06-08 09-10 11- 88-95 96-01 02-05 06-08 09-10 11- 88-99 00-05 06-08 09-10 11- Regulation - Tierl Tier 2 TierS Transitional Tier42 Final Tier42 - Tierl Tier 2 TierS Transitional Tier42 Final Tier42 - Tierl Tier 2 Transitional Tier42 Final Tier42 Emission Factors (g/hp-hr) HC 0.68 0.2025 0.1669 0.1669 0.1314 0.1314 0.68 0.1473 0.1669 0.1669 0.1314 0.1314 0.68 0.2861 0.1669 0.1314 0.1314 CO 2.7 1.3060 0.8425 0.8425 0.084 0.084 2.7 1 .3272 1 .3272 1 .3272 0.133 0.133 2.7 0.7642 0.7642 0.076 0.076 NOX 8.38 6.0153 4.3351 2.5 2.5 0.276 8.38 5.8215 4.1 2.5 2.5 0.276 8.38 6.1525 4.1 4.1 0.276 PM1 0.402 0.2008 0.1316 0.15 0.0092 0.0092 0.402 0.2201 0.1316 0.15 0.0092 0.0092 0.402 0.1934 0.1316 0.0092 0.0092 1 PM10 is assumed to be equivalent to PM. 2 The Tier 4 emission factors are considered to be transient. V-12 ------- Table V-7 Emission Factors for SI Engines Below 25 hp Engine Tech Type Emission Factors (g/hp-hr) HC CO NOX PM1 Class III Handheld New Engine Emissions (<20cc)2 Gas 2-stroke handheld Class III, baseline Phase 1 Phase 1 with catalyst Phase 2 Phase 2 with catalysts 261.00 219.99 219.99 33.07 26.87 718.87 480.31 480.31 283.37 141.69 0.97 0.78 0.78 0.91 1.49 7.7 7.7 7.7 7.7 7.7 Class IV Handheld New Engine Emissions (z20cc and <50cc) Gas 2-stroke handheld Class IV, baseline Phase 1 Phase 1 with catalyst Phase 1 4-stroke Phase 2 Phase 2 with catalysts Phase 2 4-stroke 261.00 179.72 179.72 22.37 33.07 26.87 25.83 718.87 407.38 407.38 533.42 283.37 141.69 432.51 0.94 0.51 0.51 1.79 0.91 1.49 1.13 7.7 7.7 7.7 0.06 7.7 7.7 0.06 Class V Handheld New Engine Emissions (>50cc) Gas 2-stroke handheld Class V, baseline Phase 1 Phase 1 with catalyst Phase 2 Phase 2 with catalysts 159.58 120.06 120.06 47.98 40.15 519.02 351.02 351.02 283.37 141.69 0.97 1.82 1.82 0.91 1.49 7.7 7.7 7.7 7.7 7.7 Class I Nonhandheld New Engine Emissions (<225cc) Gas 2-stroke nonhandheld Class I, baseline Gas, side-valved, 4-stroke nonhandheld Class I, baseline Gas, overhead-valved, 4-stroke nonhandheld Class I, baseline 2-stroke, Phase 1 Phase 1 side-valved, 4-stroke Phase 1 overhead valved 4-stroke Phase 1 side-valved, 4-stroke with catalyst Phase 2 side-valved Phase 2 overhead valved 207.92 38.99 13.39 120.06 8.40 8.40 8.40 7.93 6.13 485.81 430.84 408.84 449.66 353.69 351.16 353.69 353.69 351.16 0.29 2.00 1.80 4.00 3.60 3.24 3.60 2.37 1.83 7.7 0.06 0.06 7.7 0.06 0.06 0.06 0.06 0.06 Class II Nonhandheld New Engine Emissions (*225cc) Gas 2-stroke nonhandheld Class II, baseline Gas, side-valved, 4-stroke nonhandheld Class II, baseline Gas, overhead-valved, 4-stroke nonhandheld Class II, baseline Phase 1 side-valved, 4-stroke Phase 1 overhead valved 4-stroke Phase 2 side-valved Phase 2 overhead valved 207.92 9.66 5.20 5.50 5.20 5.50 4.16 485.81 430.84 408.84 387.02 352.57 387.02 352.57 0.29 2.06 3.50 4.50 3.50 4.50 2.77 7.7 0.06 0.06 0.06 0.06 0.06 0.06 1 PM10 is assumed to be equivalent to PM. 2 Assigned NONROAD hp ranges: Class IIK20cc: 0-1 hp; Class IV>20cc and <50cc: 1-3 hp; Class V>50cc: 3-6 hp; Class I <225cc: 3-6hp; Class II >225cc: 6-25hp V-13 ------- 2. Emission Estimates for Aircraft, Commercial Marine Vessels, and Locomotives Military aircraft were projected from 1996 using BEA GSP growth factors. Aircraft estimates for the years 2020 and 2030 were based on 1996 NET emission estimates and developed with commercial and general aviation growth rates from the FAA. Forecasts were only available up to the year 2020 in "Long Range Aviation Forecasts Fiscal Years 2010, 2015, and 2020," (FAA, 1998b). The annual average growth rate for the period 2015 to 2020 was assumed for estimating growth out to the year 2030. Military aviation activity was assumed to remain constant starting in 2010 so BEA GSP-based projections to 2010 were used for 2020 and 2030 for this category. The EPA has promulgated NOX and CO emission standards for commercial aircraft, but the impacts from these standards are not accounted for in this analysis. Locomotive and distillate CMV emissions were taken from the existing 2020 and 2030 control case HDDV inventory (Pechan, 2000). Adjustments were made to PM10 and SO2 emissions for locomotive source categories and SO2 emissions for CMV source categories using 49-State and California SO2 and PM10 emissions supplied by OTAQ. 49-State and California locomotive SO2 emissions are based on activity data corresponding to 2020 or 2030 locomotive fuel usage. The activity data were calculated by subtracting the 2000 railroad distillate consumption obtained from the EIA "Fuel Oil and Kerosene Sales 2000" report to the total rail maintenance source category fuel consumption obtained from the NONROAD model. The activity data were then multiplied by a growth factor representing rail energy use. The locomotive fuel usage was multiplied by the appropriate sulfur level, listed in Table V-8. CMV SO2 emissions are based on activity data corresponding to 2020 and 2030 commercial marine fuel usage. The activity data were calculated by subtracting the 2000 vessel bunkering distillate consumption obtained from the EIA "Fuel Oil and Kerosene Sales 2000" report to the total recreational marine diesel source category fuel consumption obtained from the NONROAD model. The activity data were then multiplied by a growth factor. The CMV fuel usage was multiplied by the appropriate sulfur level, listed in Table V-8. The 2020 and 2030 PM10 emissions for locomotives were estimated using the same activity data as SO2 emissions. PM10 emission factors for 2020 and 2030 are listed in Table V-8. 49- State and California SSD SO2 and PM10 emissions were estimated by dividing the annual emissions, supplied by OTAQ, by 365 days. Locomotive and distillate CMV emissions from the 2020 and 2030 control case FtDDV inventories were first summed up to the 49-State and California level. A ratio adjustment factor was calculated by dividing the sums from the 2020 and 2030 FtDDV inventories by the appropriate SO2 and PM10 emissions supplied by OTAQ. The adjustment factor was then applied back to the SO2 and PM10 annual and SSD emissions in the county-level inventories to generate updated PM10 and SO2 emissions. PM2 5 emissions were estimated by multiplying the updated PM10 emissions by a factor of 0.92. Distillate CMV PM10 emissions were adjusted for only the control cases. The PM10 emissions were first summed up to the 49-State and California level in both the 2020 and 2030 control case FtDDV emission inventories. Total PM10 emissions from the FtDDV inventories were reduced by the appropriate CMV sulfate PM "benefit" emissions supplied by OTAQ. The V-14 ------- sulfate PM "benefit" emissions were generated by subtracting the control from the base case CMV sulfate PM emissions. The PM sulfate emissions are based on 2020 and 2030 commercial marine fuel usage multiplied by the appropriate sulfur level, listed in Table V-8. A ratio adjustment factor was calculated by dividing the PM10 sums from the 2020 and 2030 control case HDDV inventories by the CMV sulfate PM "benefit" emissions supplied by OTAQ. The adjustment factor was then applied to the PM10 county-level emissions in the inventories to estimate updated PM10 emissions. PM2 5 emissions were estimated by multiplying the updated PM10 emissions by a factor of 0.92. Table V-8 Sulfur Concentrations and PM10 Emission Factors for Locomotive and CMV Emission Calculations Year 2020 base 2020 control 2030 base 2030 control Area 49-State California 49-State California 49-State California 49-State California Sulfur Concentration (ppm) 2700 120 11 11 2700 120 11 11 PM10 Emission Factor1 (g/gai) 4.9 4.2 1 PM10 Emission Factor is for locomotives only. 3. Methodologies for NH3 Updated values for national diesel and gasoline fuel consumption, as well as California diesel fuel consumption, were obtained from the June 2000 draft version of the NONROAD model for 2020 and 2030. Fuel consumption was distributed to counties using the 1996 county- level distribution. County-level fuel consumption estimates were then multiplied by the appropriate emission factor to estimate NH3 emissions for the projection years. For aircraft, 1996 base year NH3 emissions were projected to future years using the growth indicators listed in Table V-5. Locomotive and commercial marine vessel (CMV) NH3 emissions were taken from the existing 2020 and 2030 control case HDDV inventories (Pechan, 2000). C. MASS EMISSIONS INVENTORY FILES Mass emissions for NONROAD model sources were maintained in a separate data base from emissions for diesel commercial marine and locomotive categories. Table V-9 presents the nonroad mass emissions inventory file structure. V-15 ------- Table V-9 Nonroad Mass Emissions Inventory File Structure Variable FIPSST FIPSCNTY sec VOC_ANN NOX_ANN CO_ANN SO2_ANN PM10_ANN PM25_ANN NH3_ANN VOC_OSD NOXJDSD CO_OSD S02_OSD PM10_OSD PM25_OSD NH3 OSD Type C C C N N N N N N N N N N N N N N Length 2 3 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 Decimals 0 0 0 4 4 4 4 4 4 4 4 4 4 4 4 4 6 Description FIPS State code FIPS county code sec Annual VOC [tons per year (tpy)] Annual NOX (tpy) Annual CO (tpy) Annual SO2 (tpy) Annual PM10 (tpy) Annual PM25 (tpy) Annual NH3 (tpy) OSD VOC (tpd) OSD NOX (tpd) OSD CO (tpd) OSD S02 (tpd) OSD PM10 (tpd) OSD PM25 (tpd) OSD NH, (tpd) V-16 ------- CHAPTER VI ON-HIGHWAY VEHICLE SOURCES A. 1996 BASE YEAR MASS EMISSIONS INVENTORY This section summarizes the inputs and control programs that were modeled and adjustments that were made to the 1996 on-highway vehicle emissions inventory. The starting point for the 1996 on-highway vehicle emission inventory was the 1996 National Emission Trends highway vehicle emission factor database created in 1998 that was also used in support of EPA's Tier 2 rulemaking. The procedures document for the National Emissions Inventory provides more detail on the inputs contained in that analysis, but some of the key elements of that inventory are summarized here (EPA, 1998b). The 1996 vehicle miles traveled (VMT) used in this analysis also uses the corresponding Trends VMT file as the starting point, with the updates discussed below. The 1996 VMT data is based on historical 1996 Highway Performance Monitoring System (HPMS) data obtained from the Federal Highway Administration (FHWA, 1997). The HPMS database contains state-level summaries of average annual daily VMT by roadway type and by rural, small urban, and individual urban areas. The small urban and individual urban area VMT combined to make up the total urban VMT. Based on population data from the Bureau of Census (BOC, 1992), the HPMS data were distributed to counties at the roadway type level. A conversion was then made at the national roadway type level to convert the national VMT from the HPMS vehicle categories to the MOBILESb vehicle type categories. EPA's OTAQ provided a new mapping of the HPMS VMT by vehicle category to the MOBILES vehicle categories. This was an update from the VMT mapping used in the 1996 Trends VMT data base. Table VI- 1 shows this new HPMS to MOBILES VMT allocation by vehicle type. Using the data in the table, national 1996 HPMS VMT, by rural and urban categories, were converted to total fraction of VMT by MOBILES vehicle type for rural roads and urban roads. These fractions were then multiplied by the 1996 VMT distributed by county and roadway type to create the new 1996 VMT file by county, roadway type, and vehicle type. Table VI-2 summarizes the resulting VMT data by vehicle type and shows the fraction of VMT in each of the MOBILES vehicle categories. Speeds modeled in this analysis, both in 1996 and the projection years, were constant by vehicle class and functional road class throughout the nation. In other words, the same speeds were modeled in all analysis years, and the speeds depended upon the vehicle type and road type. The origin of these speed data is an analysis performed on output from the HPMS impact analysis for 1990 (FHWA, 1990). Speeds from this analysis year were consistent with speeds from earlier analysis years. Table VI-3 shows the speeds modeled. VI-1 ------- Table VI-1 HPMS to MOBILES VMT Vehicle Category Assignments HPMS VMT Vehicle Category Motorcycle Passenger Car Buses Other 2-axle, 4-tire vehicles Single-unit 2-axle 6-tire or more trucks Combination trucks MOBILES VMT Vehicle Category MC LDGV LDDV HDGV HDDV LDGT1 LDGT2 LDDT HDGV HDDV HDGV HDDV HDGV HDDV 1996 VMT Fraction 1.0000 0.9945 0.0055 0.3077 0.6923 0.6621 0.2284 0.0054 0.0759 0.0282 0.2925 0.7075 0.0000 1.0000 Table VI-2 National 1996 VMT by Vehicle Type for Nonroad Analysis Vehicle Type 1996 VMT (million miles) 1996 VMT Fractions LDGV 1,455,403 0.5880 LDGT1 538,255 0.2175 LDGT2 185,684 0.0750 HDGV 82,355 0.0333 LDDV 8,054 0.0033 LDDT 4,388 0.0018 HDDV 190,994 0.0772 JVIC 9,872 0.0040 Total 2.475.004 1.0000 VI-2 ------- Table VI-3 Average Speeds by Road Type and Vehicle Type (Miles per Hour) Rural Roadway Types LDV LOT HDV Interstate 60 55 40 Principal Arterial 45 45 35 Minor Arterial 40 40 30 Major Collector 35 35 25 Minor Collector 30 30 25 Local 30 30 25 Urban Roadway Types Interstate Other Freeways & Expressways Principal Minor Arterial Arterial Collector Local LDV LOT HDV 45 45 35 45 45 35 20 20 15 20 20 15 20 20 15 20 20 15 Vehicle registration distributions by vehicle age used in the 1996 NET include distributions provided by States through OTAG and the NOX SIP Call. Areas with no specified registration distribution were modeled with registration distributions by vehicle type developed based on national sales and registration data for 1996. The same registration distributions used in 1996 were also applied in both projection years. These registration distributions by age differ by the MOBILESb vehicle categories. Temperatures for 1996 were based on the average historical 1996 monthly maximum and minimum daily temperatures reported in a city selected to be representative of temperatures within a given State. Emission factors were calculated at the monthly level using these monthly temperatures. Monthly RVP data were also used in the MOBILESb inputs. These inputs were based on January and July RVP data from American Automobile Manufacturers Association's (AAMA's) fuel surveys (AAMA, 1996), and then allocated by month and area. More details on the temperature inputs and the RVP allocation procedures can be found in the Trends procedures document (EPA, 1998b). In addition to the inputs described above, control programs were modeled in 1996, as discussed below. 1. Inspection and Maintenance (I/M) Programs Inspection and maintenance (I/M) programs were modeled in areas with such programs in place in 1996. The actual I/M inputs and the counties included in these programs were based on VI-3 ------- data collected in the OTAG process, as well as from state-level I/M program summary information provided by OTAQ (Somers, 1997a). The vehicle types affected by these programs vary by area but can include light-duty gasoline vehicles (LDGVs) and trucks (LDGTls and LDGT2s) and heavy-duty gasoline vehicles (HDGVs). The counties that were modeled with I/M programs in the base year are shown in Table VI-4. 2. RFC Phase 1 of the Federal RFG program was modeled in the 1996 MOBILESb inputs. The areas and counties that were modeled with RFG are shown in Table VI-5. Data on the RFG coverage was provided by OTAQ. The summertime RFG benefits were applied from May through September, while the winter RFG benefits were applied in the remaining months. California was modeled with the benefits of the Federal RFG program applied Statewide. 3. Oxygenated Gasoline Oxygenated gasoline was modeled in the areas participating in this program in 1996. A listing of these areas was provided by OTAQ (Somers, 1997b), along with the months that the oxygenated gasoline program was in place in these areas and the market share of ether and alcohol blends. The average oxygen content of ether blend fuels was assumed to be 2.7 percent in all oxygenated gasoline areas and the average oxygen content of alcohol blend fuels was assumed to be 3.5 percent in all oxygenated gasoline areas. Table VI-6 lists the counties modeled with oxygenated gasoline and the corresponding fuel parameters. 4. Low Emission Vehicle (LEV) Programs In the 1996 analysis year, LEV programs were modeled in California, Massachusetts, and New York. The California program was modeled with a 1994 start year, using the MOBILES default LEV schedule. The LEV programs in Massachusetts and New York were modeled with start years of 1995 and 1996, respectively, with 15 percent of 1995 model year new vehicle sales (in Massachusetts only) meeting the intermediate Transitional LEV (TLEV) emission standards, 20 percent of 1996 model year new vehicle sales meeting the TLEV emission standards, and the remaining new vehicle sales meeting the Federal Tier I emission standards. The LEV programs affect LDGVs and LDGTls. Table VI-4 Counties Modeled with Inspection and Maintenance (I/M) Programs VI-4 ------- Table VI-4 (continued) State Arizona Arizona California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Connecticut Connecticut Connecticut State County Maricopa Co Pima Co Alameda Co Butte Co Contra Costa Co El Dorado Co Madera Co Merced Co Orange Co Placer Co Riverside Co San Bernardino Co San Joaquin Co Santa Clara Co Solano Co Stanislaus Co Tulare Co Ventura Co Yolo Co Marin Co Monterey Co San Luis Obispo Co San Mateo Co Santa Barbara Co Santa Cruz Co Sonoma Co Fresno Co Kern Co Los Angeles Co Napa Co Sacramento Co San Diego Co San Francisco Co Adams Co Arapahoe Co Boulder Co Douglas Co Jefferson Co Denver Co Pitkin Co El Paso Co Larimer Co Weld Co Fairfield Co Hartford Co Litchfield Co County Connecticut Connecticut Connecticut Connecticut Connecticut Delaware Delaware Delaware DC Florida Florida Florida Florida Florida Florida Georgia Georgia Georgia Georgia Idaho Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Indiana Indiana Indiana Indiana Kentucky Kentucky Kentucky Kentucky Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Maryland State Maryland Middlesex Co New Haven Co New London Co Tolland Co Windham Co Kent Co New Castle Co Sussex Co Washington Broward Co Dade Co Duval Co Hillsborough Co Palm Beach Co Pinellas Co Cobb Co De Kalb Co Fulton Co Gwinnett Co Ada Co Cook Co Du Page Co Lake Co Grundy Co Kane Co Kendall Co McHenry Co Will Co Madison Co St. Clair Co Clark Co Floyd Co Lake Co Porter Co Boone Co Campbell Co Kenton Co Jefferson Co Ascension Par Calcasieu Par East Baton Rouge Par Iberville Par Livingston Par Pointe Coupee Par West Baton Rouge Par Anne Arundel Co County Baltimore Co VI-5 ------- Table VI-4 (continued) Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Missouri Missouri Missouri Missouri Missouri Nevada Nevada New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey State Carroll Co Harford Co Howard Co Baltimore Calvert Co Cecil Co Queen Annes Co Charles Co Frederick Co Montgomery Co Prince Georges Co Washington Co Barnstable Co Berkshire Co Bristol Co Dukes Co Essex Co Franklin Co Hampden Co Hampshire Co Middlesex Co Nantucket Co Norfolk Co Plymouth Co Suffolk Co Worcester Co Anoka Co Carver Co Dakota Co Hennepin Co Ramsey Co Scott Co Washington Co Wright Co Franklin Co Jefferson Co St. Charles Co St. Louis Co St. Louis Clark Co Washoe Co Atlantic Co Cape May Co Warren Co Bergen Co Essex Co Hudson Co County New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Mexico New York New York New York New York New York New York New York New York New York North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Hunterdon Co Mercer Co Middlesex Co Monmouth Co Morris Co Ocean Co Passaic Co Somerset Co Sussex Co Union Co Burlington Co Camden Co Cumberland Co Gloucester Co Salem Co Bernalillo Co Bronx Co Kings Co Nassau Co New York Co Queens Co Richmond Co Rockland Co Suffolk Co Westchester Co Davidson Co Davie Co Forsyth Co Guilford Co Durham Co Granville Co Gaston Co Mecklenburg Co Wake Co Clark Co Clermont Co Geauga Co Greene Co Medina Co Montgomery Co Portage Co Summit Co Warren Co Butler Co Hamilton Co Lake Co Lorain Co Cuyahoga Co VI-6 ------- Table VI-4 (continued) State Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oregon Oregon Oregon Oregon Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Rhode Island Rhode Island Rhode Island Rhode Island Rhode Island Tennessee Tennessee Tennessee Tennessee County Canadian Co Cleveland Co Kingfisher Co Lincoln Co Logan Co McClain Co Oklahoma Co Pottawatomie Co Creek Co Osage Co Rogers Co Tulsa Co Wagoner Co Clackamas Co Jackson Co Multnomah Co Washington Co Allegheny Co Beaver Co Washington Co Westmoreland Co Lehigh Co Northampton Co Bucks Co Chester Co Delaware Co Montgomery Co Philadelphia Co Bristol Co Kent Co Newport Co Providence Co Washington Co Rutherford Co Sumner Co Williamson Co Wilson Co State Tennessee Tennessee Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Washington Washington Washington Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Utah Utah Utah Utah County Davidson Co Shelby Co Collin Co Denton Co Dallas Co Tarrant Co Ellis Co Johnson Co Kaufman Co Parker Co Rockwall Co El Paso Co Harris Co Arlington Co Fairfax Co Fairfax Prince William Co Alexandria Manassas Manassas Park Falls Church King Co Snohomish Co Spokane Co Kenosha Co Milwaukee Co Ozaukee Co Racine Co Washington Co Waukesha Co Sheboygan Co Davis Co Salt Lake Co Weber Co Utah Co VI-7 ------- Table VI-5 Counties Modeled with Federal Reformulated Gasoline (RFG) State/ Nonattainment Area County State/ Nonattainment Area County Arizona (Southern RFG) Phoenix Maricopa Co Connecticut (Northern RFG) Greater Connecticut Hartford Co Litchfield Co Middlesex Co New Haven Co New London Co Tolland Co Windham Co New York-Northern New Jersey-Long Island Fairfield Co District of Columbia (Southern RFG) Washington DC Washington Delaware (Northern RFG) Philadelphia-Wilmington-Trenton Kent Co New Castle Co Sussex County Sussex Co Illinois (Northern RFG) Chicago-Gary-Lake County Cook Co Du Page Co Grundy Co Kane Co Kendall Co Lake Co McHenry Co Will Co Indiana (Northern RFG) Chicago-Gary-Lake County Lake Co Porter Co Kentucky (Northern RFG) Cincinnati-Hamilton Boone Co Campbell Co Kenton Co Louisville Bullitt Co Jefferson Co Oldham Co Maine (Northern RFG) Knox & Lincoln Counties Knox Co Lincoln Co Lewiston-Auburn Androscoggin Co Kennebec Co Portland Cumberland Co Sagadahoc Co York Co Maryland (Southern RFG) Baltimore Anne Arundel Co Baltimore Baltimore Co Carroll Co Harford Co Howard Co Kent & Queen Annes Counties Kent Co Queen Annes Co Philadelphia-Wilmington-Trenton Cecil Co Washington DC Calvert Co Charles Co Frederick Co Montgomery Co Prince Georges Co Massachusetts (Northern RFG) Boston-Lawrence-Worcester-Eastern MA Barnstable Co Bristol Co Dukes Co Essex Co Middlesex Co Nantucket Co Norfolk Co Plymouth Co Suffolk Co Worcester Co Springfield/Pittsfield-Western MA Berkshire Co Franklin Co Hampden Co VI-8 ------- Table VI-5 (continued) State/ Nonattainment Area County State/ Nonattainment Area County New Hampshire (Northern RFC) Manchester Hillsborough Co Merrimack Co Portsmouth-Dover-Rochester Rockingham Co Strafford Co New Jersey (Northern RFC) Allentown-Bethlehem-Easton Warren Co Atlantic City Atlantic Co Cape May Co New York-Northern New Jersey-Long Island Bergen Co Essex Co Hudson Co Hunterdon Co Middlesex Co Monmouth Co Morris Co Ocean Co Passaic Co Somerset Co Sussex Co Union Co Philadelphia-Wilmington-Trenton Burlington Co Camden Co Cumberland Co Gloucester Co Mercer Co Salem Co New York (Northern RFC) New York-Northern New Jersey-Long Island Bronx Co Kings Co Nassau Co New York Co Orange Co Queens Co Richmond Co Rockland Co Suffolk Co Westchester Co Hampshire Co New York (Northern RFC) Poughkeepsie Dutchess Co Putnam Co Pennsylvania (Northern RFC) Philadelphia-Wilmington-Trenton Bucks Co Chester Co Delaware Co Montgomery Co Philadelphia Co Rhode Island (Northern RFC) Providence Bristol Co Kent Co Newport Co Providence Co Washington Co Texas (Southern RFC) Dallas-Fort Worth Collin Co Dallas Co Denton Co Tarrant Co Houston-Galveston-Brazoria Brazoria Co Chambers Co Fort Bend Co Galveston Co Harris Co Liberty Co Montgomery Co Waller Co Virginia (Southern RFC) Norfolk-Virginia Beach-Newport News Chesapeake Hampton James City Co Newport News Norfolk Poquoson Portsmouth Suffolk Virginia Beach Williamsburg York Co VI-9 ------- Table VI-5 (continued) State/ Nonattainment Area County State/ Nonattainment Area County Virginia (Southern RFC) Richmond-Petersburg Washington DC Charles City Co Chesterfield Co Colonial Heights Hanover Co Henrico Co Hopewell Richmond Alexandria Arlington Co Fairfax Fairfax Co Falls Church Loudoun Co Manassas Manassas Park Prince William Co Stafford Co Wisconsin (Northern RFC) Milwaukee-Racine Kenosha Co Milwaukee Co Ozaukee Co Racine Co Washington Co Waukesha Co NOTE: Federal reformulated gasoline was modeled statewide in California. Certain RFC fuel property requirements differ depending on whether an area receives Northern or Southern RFC. VI-10 ------- Table VI-6 Oxygenated Gasoline Modeling Parameters Market Shares (%) State Alaska Alaska Arizona Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Connecticut Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Montana Nevada Nevada New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Mexico New York New York County Anchorage Ed Anchorage Ed Maricopa Co Adams Co Arapahoe Co Boulder Co Douglas Co Jefferson Co Denver Co El Paso Co Larimer Co Fairfield Co Anoka Co Carver Co Dakota Co Hennepin Co Ramsey Co Scott Co Washington Co Wright Co Chisago Co Isanti Co Missoula Co Clark Co Washoe Co Bergen Co Essex Co Hudson Co Hunterdon Co Mercer Co Middlesex Co Monmouth Co Morris Co Ocean Co Passaic Co Somerset Co Sussex Co Union Co Bernalillo Co Bronx Co Kings Co MTBE 0 0 80 75 75 75 75 75 75 75 75 90 10 10 10 10 10 10 10 10 10 10 0 0 95 95 95 95 95 95 95 95 95 95 95 95 95 95 15 95 95 Oxygen Content (%) Alcohol Blends MTBE Alcohol Blends 100 100 20 25 25 25 25 25 25 25 25 10 90 90 90 90 90 90 90 90 90 90 100 100 5 5 5 5 5 5 5 5 5 5 5 5 5 5 85 5 5 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 Oxygenated Gasoline Season NOV-FEB (2020 & 2030) NOV-DEC (1996 only) OCT-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB OCT-JAN OCT-JAN OCT-JAN OCT-JAN OCT-JAN OCT-JAN OCT-JAN OCT-JAN OCT-JAN OCT-JAN NOV-FEB OCT-MAR OCT-JAN NOV-FEB NOV-FEB NOV-FEB NOV-FEB JAN-FEB (1996 only) NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB JAN-FEB (1996 only) NOV-FEB NOV-FEB VI-11 ------- Table VI-6 (continued) Market Shares (%) State New York New York New York New York New York New York New York New York New York Oregon Oregon Oregon Oregon Oregon Oregon Oregon Texas Utah Washington Washington Washington Washington Wisconsin County Nassau Co New York Co Queens Co Richmond Co Rockland Co Suffolk Co Westchester Co Orange Co Putnam Co Clackamas Co Jackson Co Multnomah Co Washington Co Josephine Co Klamath Co Yamhill Co El Paso Co Utah Co Clark Co King Co Snohomish Co Spokane Co St. Croix Co Oxygen Content (%) MTBE Alcohol Blends MTBE Alcohol Blends 95 95 95 95 95 95 95 95 95 1 1 1 1 1 1 1 15 20 1 1 1 1 10 5 5 5 5 5 5 5 5 5 99 99 99 99 99 99 99 85 80 99 99 99 99 90 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 Oxygenated Gasoline Season NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB NOV-FEB JAN-FEB (1996 only) JAN-FEB (1996 only) SEP-FEB OCT-JAN 5. MOBILES to MOBILES Adjustment Factors VOC, NOX, and CO on-highway vehicle emission factors were calculated using the above inputs and EPA's MOBILESb emission factor model. Emission factors for on-highway SO2, PM10, and PM2 5 were calculated using EPA's PARTS model and NH3 emission factors for on- highway vehicles were calculated using national vehicle-specific emission factors (Harvey, 1983). Various adjustment factors were then applied to the MOBILESb VOC and NOX emission factors to simulate emission factors that would result from using MOBILE6, as well as accounting for issues not included in MOBILESb. Each of these adjustments are discussed below. All of the adjustment factors discussed in these sections were provided by OTAQ. a. VOC and NOX Exhaust Adjustments Adjustment factors to convert the MOBILESb emission factors to MOBILE6 emission factors were applied to the VOC exhaust and NOX MOBILESb output emission factors for LDGVs, LDGTls, LDGT2s, HDGVs, LDDVs, and LDDTs. These factors varied by vehicle type and by control combination. The control combination included one of three fuel types VI-12 ------- (conventional gasoline, western gasoline, and reformulated gasoline) and one of three I/M categories (no I/M, I/M, and appropriate I/M). (An appropriate I/M program is defined as one that meets EPA's requirements to be modeled with the maximum LEV benefits.) Each county in the nation was assigned one of these control combinations. The corresponding adjustment factor was then applied to each monthly, vehicle type emission factor for each county in the nation. Table VI-7 lists the exhaust VOC MOBILESb to MOBILE6 adjustment factors applied in 1996 and the projection years and Table VI-8 lists the NOX MOBILESb to MOBILE6 adjustment factors. Both tables are by vehicle type and control combination. b. Air Conditioning Usage Factors An additional adjustment was applied to the NOX LDGV, LDGT1, and LDGT2 emission factors (already adjusted, as above to MOBILE6 emission rates) in 1996. This adjustment accounted for the additional NOX emissions that would occur with air conditioning usage that is not included in the MOBILES emission factors. The air conditioning usage factors consist of two components: a factor simulating full air conditioning usage and a temperature dependent factor that adjusts the full usage factor for usage at the given temperature. These two factors were multiplied and then added to the MOBILE6-adjusted NOX emission factors. The full usage factor is dependent upon vehicle type and the same control combinations listed with the MOBILE6 adjustments (with the exception that areas with both I/M and appropriate I/M are categorized together for this adjustment). Table VI-9 lists the full usage NOX air conditioning usage factors. The air conditioning adjustment becomes 0 below temperatures of 68°F. Above temperatures of 109°F, the full usage factor is applied directly. The temperatures used to calculate this adjustment were the ambient temperatures calculated by MOBILESb and included in the MOBILESb output files. The temperature dependent equation is as follows: Temp Adj = -3.631541 + 0.072465 * AMBTEMP - 0.000276 * (AMBTEMPA2) This temperature adjustment was then multiplied by the corresponding full usage factor and the result was added to the MOBILE6-adjusted NOX emission factors. c. HDDV Adjustment Factors The final set of adjustment factors applied to the 1996 on-highway vehicle emission inventories is the set of HDDV adjustment factors. These factors account for the emission factor updates from data collected by OTAQ for MOBILE6 for VOC, NOX, CO, SO2, PM10, and PM2 5 as well as the NOX emission changes due to the use of the HDDV defeat devices. The factors vary by roadway type, as shown in Table VI-10. VI-13 ------- Table VI-7 Exhaust VOC MOBILESb to MOBILES Adjustment Factors Year 1996 2020 2030 Control Combination APR IM CG APR IM RFC APP IM WEST IMCG IMRFG IM WEST NO IM CG NO IM RFC NO IM WEST APP IM CG APP IM RFC APP IM WEST IMCG IMRFG IMWEST NO IM CG NO IM RFC NO IM WEST APP IM CG APP IM RFC APP IM WEST IMCG IMRFG IMWEST NO IM CG NO IM RFC NO IM WEST Adjustment Factor by Vehicle Type (unitless) LDGV 0.880 0.969 0.880 0.880 0.969 0.880 0.787 0.870 0.787 1.496 1.751 1.499 0.297 0.344 0.297 0.277 0.337 0.278 1.644 1.925 1.645 0.273 0.321 0.274 0.263 0.324 0.263 LDGT1 0.896 0.973 0.896 0.896 0.973 0.896 0.834 0.905 0.834 1.233 1.443 1.235 0.282 0.327 0.282 0.284 0.346 0.284 1.509 1.766 1.511 0.258 0.303 0.258 0.268 0.330 0.268 LDGT2 1.132 1.203 1.132 1.132 1.203 1.132 1.020 1.084 1.020 0.302 0.347 0.303 0.302 0.347 0.303 0.263 0.309 0.264 0.201 0.241 0.202 0.201 0.241 0.202 0.200 0.249 0.200 LDDV 1.231 1.231 1.231 1.231 1.231 1.231 1.231 1.231 1.231 0.319 0.288 0.319 0.319 0.288 0.319 0.386 0.440 0.386 0.285 0.253 0.285 0.285 0.253 0.285 0.355 0.422 0.355 LDDT 1.385 1.385 1.385 1.385 1.385 1.385 1.385 1.385 1.385 0.271 0.229 0.271 0.271 0.229 0.271 0.476 0.409 0.476 0.266 0.222 0.266 0.266 0.222 0.266 0.494 0.424 0.494 HDGV 0.574 0.574 0.574 0.574 0.574 0.574 0.574 0.574 0.574 0.191 0.191 0.191 0.191 0.191 0.191 0.191 0.191 0.191 0.165 0.165 0.165 0.165 0.165 0.165 0.165 0.165 0.165 VI-14 ------- Table VI-8 NOX MOBILESb to MOBILES Adjustment Factors Year 1996 2020 2030 Control Combination APR IM CG APR IM RFC APP IM WEST IMCG IMRFG IM WEST NO IM CG NO IM RFC NO IM WEST APP IM CG APP IM RFC APP IM WEST IMCG IMRFG IM WEST NO IM CG NO IM RFC NO IM WEST APP IM CG APP IM RFC APP IM WEST IMCG IMRFG IM WEST NO IM CG NO IM RFC NO IM WEST Adjustment Factor by Vehicle Type (unitless) LDGV 0.948 0.965 0.948 0.948 0.965 0.948 0.885 0.901 0.885 0.550 0.583 0.556 0.184 0.195 0.186 0.235 0.250 0.238 0.474 0.505 0.476 0.148 0.157 0.149 0.207 0.220 0.207 LDGT1 0.948 0.961 0.948 0.948 0.961 0.948 0.875 0.886 0.875 0.471 0.497 0.476 0.212 0.224 0.214 0.283 0.300 0.286 0.424 0.450 0.428 0.176 0.187 0.178 0.252 0.267 0.254 LDGT2 1.037 1.045 1.037 1.037 1.045 1.037 0.976 0.984 0.976 0.300 0.314 0.303 0.300 0.314 0.303 0.306 0.321 0.309 0.180 0.189 0.184 0.180 0.189 0.184 0.222 0.233 0.225 LDDV 1.104 1.104 1.104 1.104 1.104 1.104 1.104 1.104 1.104 0.144 0.143 0.144 0.144 0.143 0.144 0.234 0.226 0.234 0.118 0.116 0.118 0.118 0.116 0.118 0.219 0.210 0.219 LDDT 1.152 1.152 1.152 1.152 1.152 1.152 1.152 1.152 1.152 0.158 0.155 0.158 0.158 0.155 0.158 0.285 0.280 0.285 0.161 0.159 0.161 0.161 0.159 0.161 0.303 0.298 0.303 HDGV 0.908 0.908 0.908 0.908 0.908 0.908 0.908 0.908 0.908 0.288 0.288 0.288 0.288 0.288 0.288 0.288 0.288 0.288 0.208 0.208 0.208 0.208 0.208 0.208 0.208 0.208 0.208 VI-15 ------- Table VI-9 NOX Full Usage Air Conditioning Adjustment Factors Year 1996 2020 2030 Control Combination IMCG IMRFG IMWEST NO IM CG NO IM RFC NO IM WEST IMCG IMRFG IMWEST NO IM CG NO IM RFC NO IM WEST IMCG IMRFG IMWEST NO IM CG NO IM RFC NO IM WEST Adjustment Factor by Vehicle Type (grams/mile) LDGV 0.321 0.321 0.321 0.347 0.347 0.347 0.063 0.062 0.063 0.093 0.092 0.094 0.055 0.054 0.055 0.085 0.084 0.085 LDGT1 0.194 0.194 0.194 0.207 0.207 0.207 0.047 0.046 0.047 0.073 0.072 0.073 0.041 0.040 0.041 0.068 0.067 0.068 LDGT2 0.252 0.252 0.252 0.266 0.266 0.266 0.072 0.071 0.073 0.099 0.097 0.099 0.054 0.053 0.055 0.083 0.082 0.084 VI-16 ------- Table VI-10 HDDV Adjustment Factors Adjustment Factor (unitless) Year 1996 2020 2030 Facility Interstate Interstate Interstate Interstate Arterial Arterial Arterial Arterial Urban Urban Urban Urban Interstate Interstate Interstate Interstate Arterial Arterial Arterial Arterial Urban Urban Urban Urban Interstate Interstate Interstate Interstate Arterial Arterial Arterial Arterial Urban Urban Urban Urban Description Rural Rural Urban Urban Rural Rural Rural Rural Urban Urban Urban Urban Rural Rural Urban Urban Rural Rural Rural Rural Urban Urban Urban Urban Rural Rural Urban Urban Rural Rural Rural Rural Urban Urban Urban Urban Interstate Other Prin Arterial Interstate Other Freeways Minor Arterial Major Collector Minor Collector Local Other Prin Arterial Minor Arterial Collector Local Interstate Other Prin Arterial Interstate Other Freeways Minor Arterial Major Collector Minor Collector Local Other Prin Arterial Minor Arterial Collector Local Interstate Other Prin Arterial Interstate Other Freeways Minor Arterial Major Collector Minor Collector Local Other Prin Arterial Minor Arterial Collector Local voc 0.6858 0.6858 0.6858 0.6858 0.5712 0.5712 0.5712 0.5712 0.5916 0.5916 0.5916 0.5916 0.3229 0.3229 0.3229 0.3229 0.2499 0.2499 0.2499 0.2499 0.2351 0.2351 0.2351 0.2351 0.3103 0.3103 0.3103 0.3103 0.2394 0.2394 0.2394 0.2394 0.2251 0.2251 0.2251 0.2251 0, 0, 0, 0, 0, 0, 0, 0 0, 0, 0 0 0, 0, 0, 0, 0, 0, 0, 0 0, 0, 0 0 0, 0, 0, 0, 0, 0, 0, 0 0, 0, 0 0 CO .8030 .8030 .8030 .8030 .6106 .6106 .6106 .6106 .6275 .6275 .6275 .6275 .3721 .3721 .3721 .3721 .2852 .2852 .2852 .2852 .2786 .2786 .2786 .2786 .3658 .3658 .3658 .3658 .2809 .2809 .2809 .2809 .2746 .2746 .2746 .2746 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 NO, .2973 .2973 .2973 .2973 .2723 .2723 .2723 .2723 .0240 .0240 .0240 .0240 .7099 .7099 .7099 .7099 .3144 .3144 .3144 .3144 .3130 .3130 .3130 .3130 .7078 .7078 .7078 .7078 .3586 .3586 .3586 .3586 .3713 .3713 .3713 .3713 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, PM .8666 .8666 .8666 .8666 .7110 .7110 .7110 .7110 .7549 .7549 .7549 .7549 .9220 .9220 .9220 .9220 .7506 .7506 .7506 .7506 .7262 .7262 .7262 .7262 .9131 .9131 .9131 .9131 .7411 .7411 .7411 .7411 .7161 .7161 .7161 .7161 SO, 0.7063 0.7063 0.7063 0.7063 0.6085 0.6085 0.6085 0.6085 0.6268 0.6268 0.6268 0.6268 0.6506 0.6506 0.6506 0.6506 0.5799 0.5799 0.5799 0.5799 0.6005 0.6005 0.6005 0.6005 0.5948 0.5948 0.5948 0.5948 0.5390 0.5390 0.5390 0.5390 0.5606 0.5606 0.5606 0.5606 VI-17 ------- B. 2020 AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES This section summarizes the growth assumptions made and control programs applied to calculate the 2020 and 2030 on-highway vehicle emission inventories. As discussed above, the registration distributions and speeds modeled in 1996 were also used in the projection years. The temperatures modeled in the projection years represented State-specific average monthly maximum and minimum daily temperatures averaged from 1970 through 1997 using data from the National Climatic Data Center. The same temperatures were modeled in 2020 and 2030. 1. Growth Assumptions The VMT used in 2020 and 2030 were projected from 1996, using VMT projection data from EPA's Tier 2 rulemaking (EPA, 1999d). First, VMT from the Tier 2 analysis were totaled by county and vehicle type for 1996 and the projection years. Next, each VMT record from the 1996 data base (at the county, vehicle type, and roadway type level of detail) developed for this analysis and discussed earlier in this chapter was multiplied by the ratio of the corresponding Tier 2 projection year VMT to the 1996 Tier 2 VMT (both at the county and vehicle type level of detail). In this manner, the 1996 VMT shifts by vehicle class from the Tier 2 analysis to the analysis were projected to the future using the area and vehicle type-specific growth factors from the Tier 2 analysis. The resulting projection year VMT and the corresponding VMT fractions by vehicle type are shown in Table VI-11. Table VI-11 National VMT Projections Fractions by Vehicle Type for Nonroad Analysis Vehicle Type LDGV LDGT1 LDGT2 HDGV LDDV LDDT HDDV MC Total Annual VMT 2020 1,283,189 1,670,987 371,876 165,884 0 5,112 384,106 19,885 3,901,040 (10x6 Miles) 2030 1,311,807 2,027,426 451,534 201,948 0 5,885 467,480 24,208 4,490,287 VMT 2020 0.329 0.428 0.095 0.043 0.000 0.001 0.098 0.005 1.000 Fractions 2030 0.292 0.452 0.101 0.045 0.000 0.001 0.104 0.005 1.000 2. Control Assumptions This section summarizes the control programs that were modeled for highway vehicles in 2020 and 2030. VI-18 ------- a. I/M Programs I/M program inputs were the same in all of the projection years. The default program parameters for counties expected to have I/M programs in place in the projection years are the EPA performance standard I/M program inputs. The specific inputs modeled for each of the I/M program performance standards are shown in Table VI-12. I/M program coverage by county or area was based on data collected by EPA and Pechan for the OTAG and Section 812 emission projections. During this data collection process, each State was contacted to confirm which counties in that State would be implementing an I/M program in the future. Each State was also asked to indicate which of the EPA I/M program types the program would most closely resemble - high enhanced, low enhanced, basic, or Ozone Transport Region (OTR) low enhanced. Responses were collected from each State with a planned CAA I/M program. Any additional I/M-specific information collected during comment periods for EPA's NOX SIP Call, and accepted by EPA, superseded the default and OTAG I/M data. The counties that were modeled with I/M programs in the projection years are shown in Table VI-13. b. RFC Phase II of this Federal RFG program was modeled in the projection years. Coverage of RFG in the projection years was the same as that in 1996, with the following exceptions: all Maine counties and Orange County, NY were removed from the 1996 list, shown in Table VI-4. The entire State of California was modeled with Federal Phase II RFG (ASTM Class B) in the projection years. Areas not participating in the RFG program were modeled during the ozone season months with Phase IIRVP values of either 8.7 pounds per square inch (psi) or 7.8 psi depending on their ASTM Class and hence the applicable federal RVP requirements. Areas that provided SIP Call comments documenting the presence of a low RVP program were modeled at that RVP during the ozone season. c. Oxygenated Fuel The oxygenated fuel program inputs and county coverages modeled are the same as those described for 1996, with the specific changes listed in Table VI-6 for several of the areas for 2020 and 2030. VI-19 ------- TableVI-12 I/M Performance Standard Program Inputs I/M Program Name I/M Program Parameters Program Start Year Stringency Level (Percent) Model Years Covered Waiver Rate For Pre-1981 Model Years (%) Waiver Rate For 1981 and Later Models (%) Compliance Rate (%) Program Type Inspection Frequency Vehicle Types Inspected LDGV LDGT1 LDGT2 HDGV Test Type I/M Cutpoints Effectiveness Rates (% hydrocarbon (HC)/CO/NOX) Program Start Year Stringency Level (Percent) Model Years Covered Waiver Rate For Pre-1981 Model Years (%) Waiver Rate For 1981 and Later Models (%) Compliance Rate (%) Program Type Inspection Frequency Vehicle Types Inspected LDGV LDGT1 LDGT2 HDGV Test Type I/M Cutpoints (g/mi HC/CO/NOX) Effectiveness Rates (% HC/CO/NOX) Anti-Tampering Program Parameters Program Start Year Model Years Covered Vehicle Types Inspected LDGV LDGT1 LDGT2 HDGV Program Type Effectiveness Rate Inspection Frequency Compliance Rate (%) Basic I/M Performance Standard 1983 20 1968-2020 0 0 100 TO Annual YES NO NO NO IdleTest 220/1.2/999 1.00/1.00/1.00 Low Enhanced I/M Performance Standard 1983 20 1968-2020 3 3 96 TO Annual YES YES YES NO IdleTest 220/1.2/999 1.00/1.00/1.00 1995 1972-2020 YES YES YES NO TO 1.00 Annual 96 High Enhanced I/M Performance Standard 1983 20 1968-1985 3 3 96 TO Annual YES YES YES NO 2500/ldleTest 220/1 .2/999 1.00/1.00/1.00 1983 20 1986-2020 3 3 96 TO Annual YES YES YES NO TransientTest 0.80/20.0/2.00 1.00/1.00/1.00 1995 1984-2020 YES YES YES NO TO 1.00 Annual 96 VI-20 ------- Table VI-12 (continued) I/M Program Name Basic I/M Performance Standard Low Enhanced I/M Performance Standard High Enhanced I/M Performance Standard I/M Program Parameters Inspections Performed Air Pump System Catalyst Fuel Inlet Restrictor Tailpipe Lead Deposit Test EGR System Evaporative Emission Control System PCV System Gas Cap Functional Pressure Test Program Parameters Program Start Year Model Years Covered Effectiveness Rate Vehicle Types Tested LDGV LDGT1 LDGT2 HDGV Program Type Inspection Frequency Compliance Rate (%) Purge Test Program Parameters Program Start Year Model Years Covered Effectiveness Rate Vehicle Types Tested LDGV LDGT1 LDGT2 HDGV Program Type Inspection Frequency Compliance Rate (%) NO NO NO NO YES NO NO NO NO YES YES NO NO NO NO NO 1995 1983-2020 1.00 YES YES YES NO TO Annual 96 1995 1986-2020 1.00 YES YES YES NO TO Annual 96 NOTES: TO=Test Only TRC=Test And Repair (Computerized) VI-21 ------- TableVI-13 Counties Modeled with Inspection and Maintenance (I/M) Programs State Arizona Arizona California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California Colorado Colorado Colorado Colorado County Maricopa Co Pima Co Alameda Co Butte Co Colusa Co Contra Costa Co El Dorado Co Glenn Co Kings Co Madera Co Merced Co Nevada Co Orange Co Placer Co Riverside Co San Benito Co San Bernardino Co San Joaquin Co Santa Clara Co Shasta Co Solano Co Stanislaus Co Sutter Co Tehama Co Tulare Co Ventura Co Yolo Co Yuba Co Marin Co Monterey Co San Luis Obispo Co San Mateo Co Santa Barbara Co Santa Cruz Co Sonoma Co Fresno Co Kern Co Los Angeles Co Napa Co Sacramento Co San Diego Co San Francisco Co Adams Co Arapahoe Co Boulder Co Douglas Co State Colorado Colorado Colorado Colorado Colorado Colorado Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Delaware Delaware Delaware DC Florida Florida Florida Florida Florida Florida Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Idaho Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois County Jefferson Co Denver Co Pitkin Co El Paso Co Larimer Co Weld Co Fairfield Co Hartford Co Litchfield Co Middlesex Co New Haven Co New London Co Tolland Co Windham Co Kent Co New Castle Co Sussex Co Washington B reward Co Dade Co Duval Co Hillsborough Co Palm Beach Co Pinellas Co Cherokee Co Clayton Co Coweta Co Douglas Co Fayette Co Forsyth Co Henry Co Paulding Co Rockdale Co Cobb Co De Kalb Co Fulton Co Gwinnett Co Ada Co Cook Co Du Page Co Lake Co Grundy Co Kane Co Kendall Co McHenry Co Will Co VI-22 ------- Table VI-13 (continued) State Illinois Illinois Illinois Indiana Indiana Indiana Indiana Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Maine Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts County Madison Co St. ClairCo Monroe Co Clark Co Floyd Co Lake Co Porter Co Boyd Co Greenup Co Boone Co Campbell Co Kenton Co Jefferson Co Ascension Par East Baton Rouge Par Iberville Par Livingston Par Pointe Coupee Par West Baton Rouge Par Cumberland Co Anne Arundel Co Baltimore Co Carroll Co Harford Co Howard Co Baltimore Calvert Co Cecil Co Queen Annes Co Charles Co Frederick Co Montgomery Co Prince Georges Co Washington Co Barnstable Co Berkshire Co Bristol Co Dukes Co Essex Co Franklin Co Hampden Co Hampshire Co Middlesex Co Nantucket Co Norfolk Co Plymouth Co Suffolk Co Massachusetts State Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Missouri Missouri Missouri Missouri Missouri Nevada Nevada New Hampshire New Hampshire New Hampshire New Hampshire New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Mexico New York New York New York New York New York New York Worcester Co County Anoka Co Carver Co Dakota Co Hennepin Co Ramsey Co Scott Co Washington Co Franklin Co Jefferson Co St. Charles Co St. Louis Co St. Louis Clark Co Washoe Co Hillsborough Co Rockingham Co Merrimack Co Strafford Co Atlantic Co Cape May Co Warren Co Burlington Co Camden Co Cumberland Co Gloucester Co Salem Co Bergen Co Essex Co Hudson Co Hunterdon Co Middlesex Co Monmouth Co Morris Co Ocean Co Passaic Co Somerset Co Sussex Co Union Co Mercer Co Bernalillo Co Albany Co Allegany Co Broome Co Cattaraugus Co Cayuga Co Chautauqua Co VI-23 ------- Table VI-13 (continued) New York New York State New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York Chemung Co Chenango Co County Clinton Co Columbia Co Cortland Co Delaware Co Erie Co Essex Co Franklin Co Fulton Co Genesee Co Greene Co Hamilton Co Herkimer Co Jefferson Co Lewis Co Livingston Co Madison Co Monroe Co Montgomery Co Niagara Co Oneida Co Onondaga Co Ontario Co Orleans Co Oswego Co Otsego Co Rensselaer Co St. Lawrence Co Saratoga Co Schenectady Co Schoharie Co Schuyler Co Seneca Co Steuben Co Sullivan Co Tioga Co Tompkins Co Ulster Co Warren Co Washington Co Wayne Co Wyoming Co Yates Co Bronx Co Kings Co Nassau Co New York New York New York State New York New York New York New York New York New York North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Oregon Oregon Oregon Oregon Oregon Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania New York Co Queens Co Richmond Co County Rockland Co Suffolk Co Westchester Co Dutchess Co Orange Co Putnam Co Cabarrus Co Union Co Orange Co Forsyth Co Guilford Co Durham Co Gaston Co Mecklenburg Co Wake Co Clark Co Clermont Co Geauga Co Medina Co Montgomery Co Portage Co Summit Co Warren Co Butler Co Hamilton Co Lake Co Lorain Co Cuyahoga Co Clackamas Co Jackson Co Multnomah Co Washington Co Josephine Co Berks Co Blair Co Cambria Co Centre Co Cumberland Co Dauphin Co Lackawanna Co Lancaster Co Lebanon Co Luzerne Co Lycoming Co VI-24 ------- Table VI-13 (continued) Pennsylvania Pennsylvania Pennsylvania Pennsylvania State Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Rhode Island Rhode Island Rhode Island Rhode Island Rhode Island Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Texas Texas Texas Texas Utah Utah Utah Utah Vermont Vermont Vermont York Co Allegheny Co Beaver Co Washington Co County Westmoreland Co Bucks Co Chester Co Delaware Co Montgomery Co Philadelphia Co Erie Co Mercer Co Lehigh Co Northampton Co Bristol Co Kent Co Newport Co Providence Co Washington Co Rutherford Co Sumner Co Williamson Co Wilson Co Davidson Co Shelby Co Dallas Co Tarrant Co El Paso Co Harris Co Davis Co Salt Lake Co Utah Co Weber Co Addison Co Bennington Co Caledonia Co Vermont Vermont State Vermont Vermont Vermont Vermont Vermont Vermont Vermont Vermont Vermont Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Washington Washington Washington Washington Washington Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Chittenden Co Essex Co County Franklin Co Grand Isle Co Lamoille Co Orange Co Orleans Co Rutland Co Washington Co Windham Co Windsor Co Arlington Co Fairfax Co Loudoun Co Prince William Co Stafford Co Alexandria Manassas Manassas Park Fairfax Falls Church Pierce Co Clark Co King Co Snohomish Co Spokane Co Kenosha Co Milwaukee Co Ozaukee Co Racine Co Washington Co Waukesha Co Sheboygan Co VI-25 ------- d. National LEV (NLEV) Program The NLEV program was included for all States in the projection year modeling. This program starts with the 2001 model year nationwide, and in 1999 in the Northeast Ozone Transport Commission (OTC) States. The implementation schedule of the NLEV program in the OTC States is shown below. Model Year 1999 2000 2001 and later Federal Tier I Standards 30% Transitional LEV Standards 40% 40% LEV Standards 30% 60% 100% States in the OTC that have adopted a LEV program on their own were modeled with the characteristics of their programs. These States include Massachusetts, New York, Vermont, and Maine. California's LEV program began in 1994. This was modeled using the MOBILESb default LEV implementation schedule, along with a start year of 1994 for this program. The following table shows the emission standards of the Federal Tier I program, the transitional LEV (TLEV) standards, the LEV standards, and the Ultra-Low Emission Vehicle (ULEV) standards. These standards apply to the LDGV and LDGTla classes of vehicles. The LDGTlb category is also included in the NLEV program, but the emission standards for these vehicles are slightly less stringent than those listed below for the lighter vehicles. Nonmethane Organic Emission Standard Gas (NMOG) CO NOX Federal Tier 1 TLEV LEV ULEV 0.250 grams/mile nonmethane hydrocarbon (NMHC) 0.125 grams/mile 0.075 grams/mile 0.040 grams/mile 3.4 grams/mile 3.4 grams/mile 3.4 grams/mile 1 .7 grams/mile 0.40 grams/mile 0.40 grams/mile 0.20 grams/mile 0.20 grams/mile e. 2004 NOX Standard for Heavy-Duty Diesel Engines The EPA promulgated a new NOX plus NMHC standard for Heavy Duty Vehicles of 2.5 grams per brake horsepower-hour (g/bhp-hr). This standard was modeled in the MOBILESb input files following the guidance provided in "MOBILES Information Sheet #5, Inclusion of New 2004 NOX Standard for Heavy-Duty Diesel Engines in MOBILESa and MOBILESb Modeling" issued on January 30, 1998. (http://www.epa.gov/oms/models/mobile5/m5info5.pdf) In effect, this modeling reduces the HDDV emission factors starting with the 2004 model year to be consistent with the new standard, and is applied nationally. VI-26 ------- f. Tier 2/Low Sulfur Gasoline Controls and 2020 and 2030 Adjustment Factors The 1996 section of this chapter discusses the VOC exhaust and NOX MOBILESb to MOBILE 6 adjustment factors, the air conditioning usage adjustment factors, and the HDDV NOX defeat device adjustment factors. The actual factors applied, including those applied in 2020 and 2030 were shown in Tables VI-7 through VI-10. The adjustment factors applied in the projection years include the effect of the Tier 2 emission standards and low sulfur gasoline, in addition to MOBILE6 adjustments. Although the appropriate I/M category was included in the 1996 adjustment tables, the non-I/M adjustments were the same as those for I/M. For the projection years, these two categories have different adjustment factors in most cases. In general, areas modeled with the EPA enhanced performance standard, or an equivalent I/M program, were grouped in the "APP IM" category. Several exceptions to this general rule occurred for areas that indicated through comments to the NOX SIP Call that were accepted by EPA specifically indicating that the area should or should not be modeled with the maximum LEV benefits. i. VOC Evaporative Adjustments An additional set of MOBILESb to MOBILE6 adjustment factors was applied to the VOC evaporative emission factors in 2020 and 2030 that were not applied in 1996. These adjustments result from the Tier 2 and low sulfur fuel controls. These factors were applied to the evaporative portion of the VOC emission factors for LDGVs, LDGTls, and LDGT2s, and are shown in Table VI-14. ii. On-board Diagnostics To simulate the effects of on-board diagnostic (OBD) devices in the projection years, adjustments were made to the MOBILESb input files for areas modeled with an I/M program. This was modeled by adding or modifying pressure and purge test input lines, such that 1996 and later model year LDGVs and LDGTs would receive the full benefits of a test-only pressure test and purge test. iii. PM and SO2 Adjustment Factors An additional set of factors was applied to PM and gasoline-fueled vehicle SO2 emission factors in the projection years. The PM factors are shown in Table VI-15 and were applied only to the exhaust portion of the PM10 and PM25 emission factors for LDGVs, LDGTs, HDGVs, LDDVs, and LDDTs. The brake wear and tire wear portions of the PM factors were not adjusted. Table VI-16 lists the SO2 factors applied. These factors apply to all gasoline vehicle types and account for the lower levels of sulfur in gasoline under EPA's final Tier 2/1 ow sulfur fuel rulemaking. g. Heavy Duty Diesel Emission Reductions Emission reduction percentages simulating the Heavy Duty Diesel regulation were supplied by OTAQ as national reduction percentages. Table VI-17 lists these reduction percentages for the vehicle types and pollutants whose emissions were reduced from the Base Case to the VI-27 ------- Control Case. For HDDVs, the controls were applied to VOC, NOX, CO, exhaust PM10, exhaust PM2 5, and SO2. Exhaust and evaporative VOC emissions and NOX emissions were reduced from HDGVs. SO2 emissions were reduced from LDDVs and LDDTs (as well as HDDVs) due to the lower diesel fuel sulfur content included in the HDD proposal. C. MASS EMISSIONS INVENTORY FILES The format of the final mass emissions file, which contain annual and SSD emissions for each pollutant are shown in Table VI-18. It should be noted that the SSD values for the on- highway vehicle emissions are calculated by dividing July emissions by 31. VI-28 ------- TableVI-14 Evaporative VOC MOBILESb to MOBILES Adjustment Factors Year 2020 2030 Control Combination IMCG IMRFG IM WEST NO IM CG NO IM RFC NO IM WEST IMCG IMRFG IMWEST NO IM CG NO IM RFC NO IM WEST Adjustment Factors by Vehicle Type (unitless) LDGV 0.883 0.846 0.883 0.945 0.919 0.945 0.874 0.842 0.874 0.941 0.913 0.941 LDGT1 0.880 0.855 0.880 0.954 0.935 0.954 0.860 0.830 0.860 0.948 0.926 0.948 LDGT2 0.941 0.915 0.941 0.978 0.967 0.978 0.915 0.884 0.915 0.974 0.959 0.974 VI-29 ------- TableVI-15 PM Adjustment Factors Year 2007 2020 2030 Control Combination CG RFC WEST CG RFC WEST CG RFC WEST Adjustment Factor by Vehicle Type (unitless) LDGV 0.416 0.624 0.416 0.416 0.625 0.416 0.417 0.625 0.417 LDGT1 0.342 0.563 0.342 0.337 0.559 0.337 0.333 0.556 0.333 LDGT2 0.370 0.591 0.370 0.349 0.571 0.349 0.333 0.556 0.333 HDGV 0.767 0.848 0.767 0.767 0.848 0.767 0.767 0.848 0.767 LDDV 0.826 0.826 0.826 0.421 0.421 0.421 0.109 0.109 0.109 LDDT 0.800 0.800 0.800 0.408 0.408 0.408 0.107 0.107 0.107 MC 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 TableVI-16 SO2 Adjustment Factors Year 2007 2020 2030 Control Combination CG RFC WEST CG RFC WEST CG RFC WEST Adjustment Factor by Vehicle Type (unitless) LDGV 0.088 0.224 0.088 0.088 0.224 0.088 0.088 0.224 0.088 LDGT1 0.088 0.224 0.088 0.088 0.224 0.088 0.088 0.224 0.088 LDGT2 0.088 0.224 0.088 0.088 0.224 0.088 0.088 0.224 0.088 HDGV 0.088 0.224 0.088 0.088 0.224 0.088 0.088 0.224 0.088 LDDV 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 LDDT 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 MC 0.088 0.224 0.088 0.088 0.224 0.088 0.088 0.224 0.088 VI-30 ------- TableVI-17 HDD Emission Reduction Percentages Calendar Year 2007 2020 2030 2007 2020 2030 2007 2020 2030 2007 2020 2030 Vehicle Type HDDV HDDV HDDV HDGV HDGV HDGV LDDV LDDV LDDV LDDT LDDT LDDT National Reduction Exhaust VOC 4.82% 80.64% 89.43% 0.45% 17.17% 24.29% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Evaporative VOC 0.00% 0.00% 0.00% 0.60% 8.78% 9.78% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% NOX 1 .08% 75.21% 89.50% 1 .02% 33.43% 53.88% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% CO 5.84% 82.40% 89.99% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Exhaust PM10 1 1 .96% 83.89% 92.43% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Exhaust PM25 1 1 .96% 83.89% 92.43% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% S02 97.64% 97.65% 97.65% 0.00% 0.00% 0.00% 97.88% 97.88% 97.88% 97.88% 97.88% 97.88% ------- TableVI-18 Structure for On-Highway Mobile Source Mass Emissions Data Files Variable FIPSST FIPSCNTY sec VOC_ANN NOX_ANN CO_ANN SO2_ANN PM10_ANN PM25_ANN NH3_ANN VOC_OSD NOX_OSD CO_OSD SO2_OSD PM10JDSD PM25_OSD NH3_OSD Type C C C N N N N N N N N N N N N N N Length 2 3 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 Decimals 0 0 0 4 4 4 4 4 4 4 4 4 4 4 4 4 4 Description FIPS State code FIPS county code Source Category Classification Code Annual VOC emissions (tons per year) Annual NOX emissions (tpy) Annual CO emissions (tpy) Annual SO2 emissions (tpy) Annual PM10 emissions (tpy) Annual PM25 emissions (tpy) Annual NH3 emissions (tpy) Summer season day VOC emissions [tons per day (tpd)] Summer season day NOX emissions (tpd) Summer season day CO emissions (tpd) Summer season day SO2 emissions (tpd) Summer season day PM10 emissions (tpd) Summer season day PM25 emissions (tpd) Summer season day NH3 emissions (tpd) VI-32 ------- CHAPTER VII EMISSION FILE DESCRIPTION Year Source Sector 1996 ECU Non-EGU Point Stationary Area Highway Mobile Nonroad Mobile 2020 ECU Non-EGU Point Stationary Area Highway Mobile Nonroad Mobile Filename egu96nr.dbf pt96nr.dbf ar96nr.dbf mv96nr.dbf nr96b3.dbf egu20nr.dbf pt20nr.dbf ar20nr.dbf mv20nr.dbf nr20b3.dbf Description Electric generating utility (ECU) annual and summer season daily (SSD) emissions. Non-EGU point source annual and SSD emissions. Stationary area source annual and SSD emissions. Highway mobile source annual and SSD emissions. Nonroad mobile source annual and SSD emissions. Electric generating utility (ECU) winter and summer season emissions. Non-EGU point source annual and SSD emissions. Stationary area source annual and SSD emissions. Highway mobile source annual and SSD emissions. Nonroad mobile source base case annual and SSD emissions. 2030 ECU Non-EGU Point Stationary Area Highway Mobile Nonroad Mobile nr20c3.dbf Nonroad mobile source preliminary control annual and SSD emissions. eguSOnr.dbf Electric generating utility (ECU) winter and summer season emissions. ptSOnr.dbf Non-EGU point source annual and SSD emissions. arSOnr.dbf Stationary area source annual and SSD emissions. mvSOnr.dbf Highway mobile source annual and SSD emissions. nrSObS.dbf Nonroad mobile source base case annual and SSD emissions. nrSOcS.dbf Nonroad mobile source preliminary case annual and SSD emissions. 1 Final control case scenario emission summaries are available in the Nonroad RIA (EPA, 2003). VII-1 ------- CHAPTER VIM REFERENCES AAMA, 1996: American Automobile Manufacturers Association, "Fuel Volatility Survey 1996," Washington, DC, 1996. 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VIII-4 ------- United States Office of Air Quality Planning and Standards Publication No. EPA-454/R-03-009 Environmental Protection Air Quality Strategies and Standards Division April 2003 Agency Research Triangle Park, NC ------- |