D
Description of GREET and Mobile6 Models and Their Applications

BACKGROUND

The Need for Emissions Data in the National Research Council Study

To evaluate the per vehicle miles traveled (VMT) total damages from transportation, the APEEP1 county emission-unit-damage costs must be evaluated against vehicle emissions. Although the passenger and freight fleets are diverse, particular vehicle and fuel combinations dominated in 2005, and certain vehicles and fuels are of particular interest for 2030. It is important to acknowledge life-cycle considerations related to both the vehicles and the fuels. In particular, feedstock production, fuel production, and vehicle manufacturing could have significant emissions contributions in the life-cycle inventory. The vehicle-fuel inventory should include these life-cycle components in addition to vehicle operation.

Available Options for Constructing Emissions Estimates

Although tools and data are available to evaluate the many vehicle and fuel operational emissions, GREET2 stands as one of the few resources to evaluate life-cycle component emissions (Argonne National Laboratory 2009). The GREET life-cycle factors cover a range of light-duty vehicles and the fuels they consume. GREET evaluates the many processes involved from

1

Air Pollution Emission Experiments and Policy.

2

Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation.



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D Description of GREET and Mobile6 Models and Their Applications BACKGROUND The Need for Emissions Data in the National Research Council Study To evaluate the per vehicle miles traveled (VMT) total damages from transportation, the APEEP1 county emission-unit-damage costs must be evaluated against vehicle emissions. Although the passenger and freight fleets are diverse, particular vehicle and fuel combinations dominated in 2005, and certain vehicles and fuels are of particular interest for 2030. It is important to acknowledge life-cycle considerations related to both the vehicles and the fuels. In particular, feedstock production, fuel production, and vehicle manufacturing could have significant emissions contributions in the life-cycle inventory. The vehicle-fuel inventory should include these life-cycle components in addition to vehicle operation. Available Options for Constructing Emissions Estimates Although tools and data are available to evaluate the many vehicle and fuel operational emissions, GREET2 stands as one of the few resources to evaluate life-cycle component emissions (Argonne National Laboratory 2009). The GREET life-cycle factors cover a range of light-duty vehicles and the fuels they consume. GREET evaluates the many processes involved from 1 Air Pollution Emission Experiments and Policy. 2 Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation. 432

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433 APPENDIX D feedstock production through vehicle operation. Without using GREET, individual process assessments throughout the supply chain would need to be performed and combined for each vehicle and fuel of interest. EMISSIONS DATA AND MODELING The GREET Model The Argonne GREET model is used to determine emissions from light- duty autos and trucks. The GREET model is a vehicle operation and fuel production life-cycle assessment tool, which captures fuel feedstock production, fuel refining, vehicle operation, and vehicle manufacturing. Feedstock production, fuel refining, and vehicle operation are estimated with the GREET 1.8b model; vehicle manufacturing is determined with GREET 2.7a. The version designations (1.8b and 2.7a) do not imply differ- ent generations of GREET but distinguish between a version developed for the fuel cycle (1.8b) versus a version developed for the vehicle cycle (2.7). The strength of the GREET model lies in its ability to estimate a variety of fuel inputs and vehicle combinations and their associated well-to-wheel life-cycle components. GREET allows for specification of critical inputs to these components (for example, emission factors, combustion technologies, energy efficiencies, and fuel types). GREET evaluates several life-cycle components for the feedstock pro- duction, fuel production, and vehicle-manufacturing emissions inventory. For the feedstock and fuel production cycle, GREET captures extraction and creation of raw feedstock, transport to refineries, refinery processes, and transport to fueling stations. These constitute the well-to-pump com- ponents. On the vehicle-cycle side, GREET performs a materials-based life- cycle assessment capturing raw material extraction, processing, transport, and ultimately assembly into an automobile or light-duty truck. GREET does not estimate heavy-duty vehicle life-cycle factors, so additional data sources were needed to evaluate these vehicle classes. GREET allows for the adjustment of many feedstock, fuel, and vehicle operation input parameters; however, particular inputs were targeted for the vehicle and fuel combinations evaluated. The evaluation year was toggled for the 2005 and 2030 scenarios to capture changes in both vehicle operational performance as well as efficiency changes in other devices, such as engines and turbines. The fraction of crude oil that comes from tar sands and the amount of reformulated gasoline were adjusted on the basis of the vehicle and fuel combination. For ethanol, GREET inputs for feedstocks (corn, herbaceous, and corn stover) and milling processes (dry or wet) were changed. Another critical input parameter for the assessment is the fraction of low-sulfur diesel. Last, the electricity mix for 2005 and 2030 were ad-

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434 APPENDIX D justed on the basis of the U.S. Energy Information Administration’s Annual Energy Outlook, which reports historical mixes as well as future forecasts (EIA 2006, 2009a). Mobile6.2 To evaluate heavy-duty vehicle emissions, EPA’s Mobile6.2 on-road emissions modeling tool was used (EPA 2009). Unlike GREET, Mobile6.2 is designed to evaluate the many different conditions under which vehicles may operate, and not feedstock production, fuel production, or vehicle- manufacturing life-cycle emissions. Mobile6.2 heavy-duty vehicle opera- tional emission factors were used in combination with GREET feedstock and fuel production factors to create life-cycle inventories for several dif- ferent vehicle classes. GREET does not evaluate ammonia emissions, so Mobile6.2 is used to capture this pollutant for both light- and heavy-duty vehicles. Ammonia emissions, which result in secondary particle formation, were determined by Mobile6.2 for a set of vehicles that overlap with the vehicle and fuel combinations evaluated in GREET. Ammonia emissions were estimated for the vehicle operation component only; they were not estimated for the feedstock, fuel, and vehicle manufacturing components. THE EMISSIONS MODELING PROCESS Model Framework The emissions model utilized GREET to generate feedstock, fuel pro- duction, operation, and vehicle-manufacturing factors for light-duty vehi- cles and Mobile6.2 to generate operational factors for heavy-duty vehicles. GREET feedstock and fuel production factors were applied to the heavy- duty vehicle Mobile6.2 operational factors, as described later in this ap- pendix. For all vehicles, energy inputs, CO2, CH4, N2O, VOC, CO, NOx, PM10, PM2.5, and SOx emissions are determined for the life-cycle compo- nents. APEEP county unit damages are based on emissions of VOCs, NOx, PM2.5, and SOx. GREET Temporal Boundaries GREET can evaluate vehicles and life-cycle processes from 1990 through 2020. The tool has many time series for engines, turbines, and critical parameters that capture changes in efficiencies, emissions, and other parameters (for example, ethanol yields from corn and fuel sulfur levels) historically and up to 2020. GREET also makes the assumption that fleet age is 5 years. When evaluating life-cycle emissions in a year, GREET as-

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43 APPENDIX D sumes that vehicles are 5 years older and assigns them the corresponding emissions. When using GREET to evaluate vehicles in 2005, emissions from vehicles correspond to year 2000. However, all other values in GREET’s assessment (such as fuel sulfur levels or electricity mixes) correspond to 2005. The 2030 assessment is outside the GREET temporal upper range, so 2020 is used as a baseline (although adjustments are made and described later in this section). GREET Vehicle-Manufacturing Emissions The GREET 2.7a model was used to determine vehicle-manufacturing emissions. The model performs a life-cycle assessment from vehicle material inputs to determine emissions from manufacturing for cars and SUVs. The model distinguishes between internal-combustion-engine vehicles, hybrid electric vehicles, and fuel-cell electric vehicles from both conventional and light-weight materials. The material inputs are evaluated for the body, pow- ertrain system, transmission system, chassis, battery, fluids, paint, traction motor, generator, electronic controller, and fuel-cell auxiliary system. These components are assessed from material extraction through assembly, and emissions are determined at each stage. Disposal is included. There is no time dependency with GREET’s vehicle-manufacturing as- sessment, so process changes from 2005 through 2030 are not captured. Energy and emission factors are determined for the vehicle size, power- delivery systems, and material-composition combinations, as shown in Table D-1 and Table D-2. The car conventional-material factors are used for all light-duty autos, and the SUV conventional-material factors are used for light-duty trucks class 1 and 2. GREET Light-Duty Auto and Truck Energy and Emissions Factors Light-duty automobile and truck life-cycle energy inputs and emissions are determined from GREET. GREET distinguishes between light-duty trucks class 1 and 2 to capture the increased energy requirements and re- sulting emissions of the larger vehicles. Class 1 trucks are between zero and 6,000 lb gross-vehicle-weight rating (GVWR) and less than 3,750 lb loaded vehicle weight (LVW), and class 2 trucks have the same GVWR and greater than 3,750 LVW. For each vehicle and fuel combination, GREET is used to determine feedstock, fuel, and operational factors for light-duty autos, trucks in class 1 (LDT1), and trucks in class 2 (LDT2). GREET allows for the adjustment of many vehicle and fuel parameters; however, certain critical parameters are adjusted some of the vehicle and fuel combinations to estimate life-cycle emissions. For reformulated gaso-

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436 APPENDIX D TABLE D-1 GREET 2.7a Vehicle-Manufacturing Results for Cars ICEV: HEV: FCV: ICEV: Light- HEV: Light- FCV: Light- Conventional Weight Conventional Weight Conventional Weight Material Material Material Material Material Material Lifetime 160,000 160,000 160,000 160,000 160,000 160,000 VMT Total energy 633 619 645 669 792 797 Fossil fuels 592 573 600 618 732 735 Coal 223 164 235 190 264 218 Natural gas 243 226 243 241 308 298 Petroleum 126 183 122 187 160 219 CO2 47 46 50 50 62 60 CH4 0.082 0.077 0.083 0.083 0.102 0.099 N 2O 0.001 0.001 0.001 0.001 0.001 0.001 GHGs 50 48 52 52 65 63 VOC 0.206 0.205 0.206 0.205 0.205 0.205 CO 0.250 0.093 0.226 0.098 0.217 0.089 NOx 0.075 0.080 0.077 0.085 0.094 0.099 PM10 0.082 0.066 0.080 0.071 0.092 0.081 PM2.5 0.033 0.028 0.031 0.029 0.036 0.033 SOx 0.137 0.147 0.228 0.213 0.286 0.259 TABLE D-2 GREET 2.7a Vehicle-Manufacturing Results for SUVs ICEV: HEV: FCV: ICEV: Light- HEV: Light- FCV: Light- Conventional Weight Conventional Weight Conventional Weight Material Material Material Material Material Material Lifetime 180,000 180,000 180,000 180,000 180,000 180,000 VMT Total energy 730 728 840 833 1030 970 Fossil fuels 683 672 780 766 951 890 Coal 263 194 316 244 350 271 Natural gas 280 266 318 299 399 361 Petroleum 140 212 146 223 203 259 CO2 54 54 65 62 80 73 CH4 0.095 0.090 0.108 0.103 0.132 0.120 N 2O 0.001 0.001 0.001 0.001 0.001 0.001 GHGs 57 56 68 65 84 76 VOC 0.308 0.307 0.308 0.307 0.308 0.307 CO 0.298 0.105 0.316 0.116 0.297 0.103 NOx 0.085 0.092 0.096 0.102 0.118 0.117 PM10 0.095 0.078 0.107 0.089 0.121 0.100 PM2.5 0.038 0.033 0.041 0.036 0.047 0.041 SOx 0.151 0.166 0.297 0.267 0.373 0.317

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43 APPENDIX D line vehicles, GREET’s share of reformulated gasoline in total gasoline fac- tor was set to 100%. For conventional and reformulated gasoline vehicles using petroleum derived from tar sands oil, GREET’s share of oil sands products in crude oil refineries was set to 100%. GREET assumes that in 2005 an 80% share of dry mill corn ethanol production (this increases to 90% by 2020). In evaluating E10 and E85 fueled vehicles from corn etha- nol feedstock, this percentage was adjusted. For E10 and E85 from dry corn this was set to 100% while from wet corn, to 0% (or 100% wet milling plants). To evaluate the compression ignition direct injection low-sulfur diesel combination, the share of low-sulfur diesel in total diesel use was specified as 100% for 2005. For the other vehicle and fuel combinations, default GREET values were left unchanged. The ethanol yield factors were verified against existing literature and electricity mixes for the two time periods received slight adjustments based on the U.S. Energy Information Administration’s Annual Energy Outlook. The energy and emission fac- tors for the different vehicle types (LDA, LDT1, and LDT2) in 2005 are shown in Table D-3, Table D-4, and Table D-5 and for 2020 in Table D-6, Table D-7, and Table D-8. 2030 Fuel Economy and Emission-Factor Adjustments The implementation of 35 miles per gallon fuel economy standards for 2030 requires an adjustment to GREET default 2020 emission factors. The GREET model assumes fuel economies between 20 and 30 miles per gal- lon for conventional gasoline and E85 light-duty automobiles in 2020. For light-duty trucks the fuel economy ranges are even lower (20-24 miles per gallon for LDT1 and 17-20 miles per gallon for LDT2). For 2030, all energy and emission factors are adjusted based on the GREET default fuel econo- mies and the expected 35 miles per gallon standard. Fuel and feedstock factors from GREET are reduced by the percentage reduction of default and 35 mile per gallons economies (for example, if the 2020 fuel economy is specified as 24 miles per gallon then the fuel and feedstock emission factors for 2020 are multiplied by 24/35 to determine the adjusted 2030 factors). This is based on the assumption that with an increase in fuel economy, a proportional reduction is needed in fuel production, which results in lower feedstock requirements. Vehicle operation combustion factors are also re- duced using the same methodology. VOC evaporative losses and PM tire and brake wear factors were left unchanged from GREET default values as well as vehicle manufacturing. Both automobiles and light-duty trucks were assessed the adjusted factors. Trucks show the largest changes from default to the 35 miles per gallon standard due to relatively low GREET estimated 2020 fuel economies. All vehicles that had fuel economies greater than 35 miles per gallon in GREET in 2020 were not adjusted.

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TABLE D-3 GREET Energy and Emission Factors for Light-Duty Autos in 2005 438 Total Energy Petroleum VOC CO2 CO2e NOx PM2.5 SOx Btu/VMT Btu/VMT g/VMT g/VMT g/VMT g/VMT g/VMT g/VMT RFG SI Autos Feedstock 232 64 6 18 0.02 0.15 0.01 0.05 (Conventional Oil) Fuel 1241 457 72 77 0.13 0.17 0.02 0.11 Operation 5259 5038 404 408 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 RFG SI Autos Feedstock 853 62 50 64 0.02 0.14 0.01 0.06 (Tar Sands) Fuel 1295 457 72 78 0.13 0.17 0.02 0.11 Operation 5259 5038 404 408 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 CG SI Autos Feedstock 236 65 17 29 0.02 0.15 0.01 0.05 (Conventional Oil) Fuel 1007 447 68 71 0.13 0.14 0.02 0.10 Operation 5334 5257 410 414 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 CG SI Autos Feedstock 865 63 62 76 0.02 0.14 0.01 0.06 (Tar Sands) Fuel 1059 447 68 72 0.13 0.14 0.02 0.10 Operation 5334 5257 410 414 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 RFG SIDI Autos Feedstock 202 55 5 16 0.02 0.13 0.00 0.05 (Conventional Oil) Fuel 1080 397 62 67 0.12 0.15 0.02 0.10 Operation 4573 4381 351 355 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 RFG SIDI Autos Feedstock 742 54 44 56 0.02 0.12 0.01 0.05 (Tar Sands) Fuel 1126 397 63 68 0.12 0.15 0.02 0.10 Operation 4573 4381 351 355 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14

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Diesel Feedstock 193 53 19 29 0.02 0.12 0.00 0.04 (Low Sulfur) Fuel 613 309 46 48 0.02 0.09 0.01 0.07 Operation 4383 4383 347 350 0.09 0.30 0.07 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 Diesel Feedstock 280 18 22 35 0.02 0.11 0.00 0.05 (Fischer Tropsch) Fuel 2882 68 106 114 0.03 0.25 0.06 0.09 Operation 4383 0 334 338 0.09 0.30 0.07 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 Diesel Feedstock 427 213 –30 –13 0.03 0.23 0.01 0.13 (Soy BD20) Fuel 9433 14 12 5 0.28 –0.03 0.00 –0.06 Operation 4383 3555 344 348 0.09 0.30 0.07 0.04 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 CNG Feedstock 436 24 31 64 0.03 0.16 0.00 0.07 Fuel 415 20 35 36 0.00 0.05 0.01 0.12 Operation 5615 0 333 342 0.15 0.30 0.02 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E85 Feedstock 822 229 –225 –173 0.06 0.42 0.02 0.19 (Dry Corn) Fuel 6277 345 72 82 0.26 0.50 0.05 0.18 Operation 5334 1412 402 406 0.22 0.30 0.02 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E85 Feedstock 898 498 –212 –144 –0.14 0.58 0.03 0.29 (Wet Corn) Fuel 6386 201 221 233 0.25 0.41 0.12 0.40 Operation 5334 1412 402 406 0.22 0.30 0.02 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E85 Feedstock 570 216 –282 –237 0.06 0.29 0.02 0.06 (Herbaceous) Fuel 4618 179 3 15 0.19 0.45 0.03 –0.02 Operation 5334 1412 402 406 0.22 0.30 0.02 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 43 continued

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TABLE D-3 Continued 440 Total Energy Petroleum VOC CO2 CO2e NOx PM2.5 SOx Btu/VMT Btu/VMT g/VMT g/VMT g/VMT g/VMT g/VMT g/VMT E85 Feedstock 407 229 –263 –261 0.03 0.24 0.02 0.11 (Corn Stover) Fuel 4206 179 3 14 0.19 0.43 0.03 –0.02 Operation 5334 1412 402 406 0.22 0.30 0.02 0.00 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E10 Feedstock 287 79 1 17 0.02 0.17 0.01 0.06 (Dry Corn) Fuel 1343 430 66 69 0.13 0.16 0.02 0.11 Operation 5334 4990 409 413 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E10 Feedstock 294 103 2 19 0.01 0.19 0.01 0.07 (Wet Corn) Fuel 1352 417 79 82 0.13 0.15 0.03 0.12 Operation 5334 4990 409 413 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E10 Feedstock 265 78 –4 11 0.02 0.16 0.01 0.05 (Herbaceous) Fuel 1197 416 60 63 0.13 0.15 0.02 0.09 Operation 5334 4990 409 413 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E10 Feedstock 251 79 –2 9 0.02 0.16 0.01 0.06 (Corn Stover) Fuel 1161 416 60 63 0.13 0.15 0.02 0.09 Operation 5334 4990 409 413 0.23 0.30 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 Electric Feedstock 159 56 12 25 0.03 0.08 0.13 0.04 Fuel 2734 81 380 381 0.01 0.53 0.02 1.31 Operation 1778 84 0 0 0.00 0.00 0.01 0.00 Vehicle 645 122 50 52 0.21 0.08 0.03 0.23

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Hydrogen Feedstock 180 10 13 27 0.01 0.07 0.00 0.03 (Gaseous) Fuel 1539 29 243 250 0.01 0.14 0.04 0.16 Operation 2319 0 0 0 0.00 0.00 0.01 0.00 Vehicle 792 160 62 65 0.21 0.09 0.04 0.29 Grid-Independent Feedstock 159 44 11 20 0.01 0.10 0.00 0.04 SI HEV Fuel 680 302 46 48 0.09 0.10 0.01 0.07 Operation 3604 3552 277 281 0.16 0.25 0.02 0.00 Vehicle 645 122 50 52 0.21 0.08 0.03 0.23 Grid-Dependent SI Feedstock 159 48 12 21 0.02 0.09 0.04 0.04 HEV Fuel 1358 229 156 158 0.06 0.24 0.01 0.48 Operation 3002 2408 185 188 0.10 0.17 0.01 0.00 Vehicle 645 122 50 52 0.21 0.08 0.03 0.23 441

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TABLE D-4 GREET Energy and Emission Factors for Light-Duty Trucks 1 in 2005 442 Total Energy Petroleum VOC CO2 CO2e NOx PM2.5 SOx Btu/VMT Btu/VMT g/VMT g/VMT g/VMT g/VMT g/VMT g/VMT RFG SI Autos Feedstock 297 82 7 23 0.02 0.19 0.01 0.07 (Conventional Oil) Fuel 1587 584 92 98 0.17 0.22 0.03 0.15 Operation 6722 6439 516 520 0.32 0.52 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 RFG SI Autos Feedstock 1090 79 65 82 0.03 0.18 0.01 0.08 (Tar Sands) Fuel 1655 584 93 99 0.17 0.22 0.03 0.15 Operation 6722 6439 516 520 0.32 0.52 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 CG SI Autos Feedstock 301 83 22 37 0.02 0.19 0.01 0.07 (Conventional Oil) Fuel 1287 572 87 91 0.16 0.18 0.02 0.13 Operation 6818 6719 524 528 0.32 0.52 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 CG SI Autos Feedstock 1106 80 80 97 0.03 0.18 0.01 0.08 (Tar Sands) Fuel 1353 572 87 92 0.16 0.18 0.02 0.13 Operation 6818 6719 524 528 0.32 0.52 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 RFG SIDI Autos Feedstock 258 71 6 20 0.02 0.16 0.01 0.06 (Conventional Oil) Fuel 1380 508 80 86 0.15 0.19 0.02 0.13 Operation 5845 5599 449 453 0.32 0.52 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 RFG SIDI Autos Feedstock 948 69 56 71 0.02 0.16 0.01 0.07 (Tar Sands) Fuel 1439 508 80 86 0.15 0.19 0.02 0.13 Operation 5845 5599 449 453 0.32 0.52 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15

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Diesel Feedstock 363 66 33 46 0.02 0.12 0.01 0.04 (Low Sulfur) Fuel 778 387 58 60 0.02 0.09 0.01 0.06 Operation 5504 5504 435 439 0.07 0.17 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 Diesel Feedstock 353 23 27 44 0.03 0.09 0.00 0.06 (Fischer-Tropsch) Fuel 3259 84 118 127 0.04 0.27 0.08 0.11 Operation 5504 0 420 424 0.07 0.17 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 Diesel Feedstock 631 262 –30 –8 0.03 0.19 0.01 0.13 (Soy BD20) Fuel 11895 92 25 16 0.32 –0.07 0.00 –0.10 Operation 5504 4472 436 440 0.07 0.17 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 CNG Feedstock 489 27 35 72 0.04 0.13 0.00 0.07 Fuel 461 20 38 40 0.00 0.04 0.01 0.07 Operation 6290 0 373 381 0.18 0.14 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 E85 Feedstock 1014 288 –284 –226 0.06 0.31 0.01 0.15 (Dry Corn) Fuel 7810 369 85 97 0.31 0.48 0.05 0.13 Operation 6605 1730 498 502 0.20 0.14 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 E85 Feedstock 1024 555 –275 –203 –0.17 0.47 0.02 0.26 (Wet Corn) Fuel 8018 253 278 293 0.31 0.35 0.12 0.18 Operation 6605 1730 498 502 0.20 0.14 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 E85 Feedstock 663 234 –351 –302 0.05 0.22 0.01 0.04 (Herbaceous) Fuel 4337 227 7 20 0.23 0.49 0.03 0.00 Operation 6605 1730 498 502 0.20 0.14 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 4 continued

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TABLE D-8 Continued 460 Total Energy Petroleum VOC CO2 CO2e NOx PM2.5 SOx BTU/VMT BTU/VMT g/VMT g/VMT g/VMT g/VMT g/VMT g/VMT E85 Feedstock 475 236 –332 –329 0.03 0.15 0.01 0.09 (Corn Stover) Fuel 3898 227 7 20 0.23 0.47 0.03 0.00 Operation 6605 1730 498 502 0.20 0.14 0.02 0.00 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 E10 Feedstock 487 98 11 31 0.03 0.16 0.01 0.06 (Dry Corn) Fuel 1667 527 81 84 0.17 0.15 0.02 0.08 Operation 6605 6178 507 511 0.22 0.14 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 E10 Feedstock 488 121 12 33 0.01 0.17 0.01 0.07 (Wet Corn) Fuel 1685 517 98 101 0.17 0.14 0.03 0.08 Operation 6605 6178 507 511 0.22 0.14 0.02 0.01 Vehicle 633 126 47 50 0.21 0.08 0.03 0.14 E10 Feedstock 456 93 6 24 0.03 0.15 0.01 0.05 (Herbaceous) Fuel 1363 514 74 78 0.16 0.15 0.02 0.07 Operation 6605 6178 507 511 0.22 0.14 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 E10 Feedstock 440 93 7 22 0.02 0.15 0.01 0.05 (Corn Stover) Fuel 1325 514 74 78 0.16 0.15 0.02 0.07 Operation 6605 6178 507 511 0.22 0.14 0.02 0.01 Vehicle 730 140 54 57 0.31 0.08 0.04 0.15 Electric Feedstock 176 56 13 27 0.03 0.06 0.12 0.04 Fuel 2863 73 394 396 0.01 0.32 0.01 0.74 Operation 1887 80 0 0 0.00 0.00 0.01 0.00 Vehicle 840 146 65 68 0.31 0.10 0.04 0.30

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Hydrogen Feedstock 232 13 16 34 0.02 0.06 0.00 0.03 (Gaseous) Fuel 1875 33 305 314 0.02 0.13 0.05 0.12 Operation 2989 0 0 0 0.00 0.00 0.01 0.00 Vehicle 1030 203 80 84 0.31 0.12 0.05 0.37 Hydrogen Feedstock 233 13 16 34 0.02 0.06 0.00 0.03 (Liquid) Fuel 4750 154 540 559 0.04 0.35 0.13 0.56 Operation 2989 0 0 0 0.00 0.00 0.01 0.00 Vehicle 1030 203 80 84 0.31 0.12 0.05 0.37 Grid-Independent Feedstock 305 56 13 24 0.02 0.10 0.00 0.04 SI HEV Fuel 1094 399 62 67 0.11 0.11 0.01 0.06 Operation 4619 4424 354 358 0.20 0.11 0.02 0.01 Vehicle 840 146 65 68 0.31 0.10 0.04 0.30 Grid-Dependent SI Feedstock 272 59 14 27 0.02 0.09 0.05 0.04 HEV Fuel 1835 295 193 197 0.08 0.20 0.01 0.32 Operation 3821 2995 238 240 0.13 0.07 0.02 0.00 Vehicle 840 146 65 68 0.31 0.10 0.04 0.30 461

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462 APPENDIX D Mobile6.2 Heavy-Duty Truck Energy and Emissions Factors The operational factors for heavy-duty vehicles were determined with Mobile6.2 and are shown in Table D-9 and Table D-10. Default Mobile6.2 values were used for these vehicles. GREET and Mobile6.2 Comparison The GREET vehicle operation factors can be compared against Mo- bile6.2’s to evaluate the accuracy of particular vehicles. GREET assumes default emission factors for conventional gasoline and diesel vehicles and the operating conditions of the vehicles is not transparent. Mobile6.2 is designed to model emissions from conventional fuel vehicles and low level ethanol blends and provides the ability to adjust many vehicle operation and fuel characteristics in determining emission factors. Table D-11 and Table D-12 compare the GREET default conventional gasoline and diesel vehicle emissions against Mobile6.2. The lack of transparency in the vehicle and operating characteristics used to generate GREET factors results in some difficulty in verification using Mobile6.2. In 2005, GREET assumes low-sulfur concentrations of 26 ppm in gasoline and 200 ppm in conven- TABLE D-9 Mobile6.2 Energy and Emission Factors for Heavy-Duty Vehicles in 2005 Total Energy CO2 VOC NOx PM2.5 SOx Btu/VMT g/VMT g/VMT g/VMT g/VMT g/VMT HDGV2A 12500 888 1.79 4.13 0.07 0.05 HDGV2B 12500 888 1.79 4.13 0.07 0.05 HDGV3 13587 963 2.47 4.71 0.08 0.06 HDGV4 14205 1005 5.30 5.90 0.07 0.06 HDGV5 15823 1124 3.10 5.40 0.06 0.06 HDGV6 15823 1119 2.91 5.30 0.07 0.07 HDGV7 17123 1217 3.43 6.09 0.07 0.07 HDGV8A 18382 1296 4.05 6.79 0.00 0.00 HDDV2A 10195 795 0.23 3.99 0.12 0.01 HDDV2B 10195 795 0.23 3.99 0.12 0.01 HDDV3 11250 879 0.25 4.44 0.13 0.01 HDDV4 12921 1004 0.31 5.41 0.11 0.01 HDDV5 13316 1036 0.32 5.68 0.25 0.01 HDDV6 15000 1176 0.47 7.99 0.26 0.01 HDDV7 17400 1354 0.58 9.94 0.33 0.01 HDDV8A 20077 1561 0.56 12.89 0.36 0.02 HDDV8B 21048 1647 0.66 15.10 0.36 0.02

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463 APPENDIX D TABLE D-10 Mobile6.2 Energy and Emission Factors for Heavy-Duty Vehicles in 2030 Total Energy CO2 VOC NOx PM2.5 SOx Btu/VMT g/VMT g/VMT g/VMT g/VMT g/VMT HDGV2A 12376 876 0.35 0.18 0.02 0.02 HDGV2B 12376 876 0.35 0.18 0.02 0.02 HDGV3 13298 945 0.76 0.23 0.02 0.02 HDGV4 13298 949 0.82 0.21 0.02 0.02 HDGV5 15625 1107 0.91 0.24 0.02 0.02 HDGV6 15432 1090 0.90 0.24 0.02 0.02 HDGV7 16779 1191 0.95 0.27 0.03 0.02 HDGV8A 17606 1255 1.00 0.28 0.00 0.00 HDDV2A 10038 785 0.10 0.25 0.01 0.01 HDDV2B 10038 785 0.10 0.25 0.01 0.01 HDDV3 11154 873 0.12 0.26 0.02 0.01 HDDV4 12794 998 0.14 0.41 0.02 0.01 HDDV5 13182 1030 0.15 0.44 0.02 0.01 HDDV6 15000 1169 0.19 0.47 0.02 0.01 HDDV7 17400 1352 0.23 0.58 0.03 0.01 HDDV8A 19773 1544 0.26 0.64 0.03 0.02 HDDV8B 20714 1616 0.29 0.75 0.03 0.02 TABLE D-11 Comparison of Emission Factors (g/VMT) for a Light-Duty Gasoline Automobile in 2005 VOC VOC PM2.5 PM2.5 Exhaust Evap NOx Exhaust TBW SOx GREET 0.15 0.07 0.3 0.008 0.007 0.01 Mobile6.2 0.27 0.87 0.8 0.005 0.007 0.02 TABLE D-12 Comparison of Emission Factors (g/VMT) for a Light-Duty Diesel Automobile in 2005 VOC PM2.5 PM2.5 Exhaust NOx Exhaust TBW GREET 0.09 0.3 0.07 0.007 Mobile6.2 0.33 1.3 0.15 0.007

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464 APPENDIX D tional diesel. GREET further specifies sulfur contents for low-sulfur diesel. Outside of fuel sulfur levels, vehicle emission factors are fixed based on inputs and assumptions from 1990 through 2020. The differences between GREET and Mobile6.2 emission factors are most likely due to the variations in vehicle operation and fuel input param- eters. These differences could be from cold start and warm running, fuel vapor pressure, summer or winter fuel mix, and vehicle model assumptions. While the Mobile6.2 factors tend to be larger than the GREET factors. The GREET factors are assumed to be reasonable, given the uncertainty in ve- hicle and fuel parameters and that they are within the bounds of Mobile6.2 estimates for the year. EPA Mobile6 Ammonia Emissions Factors Ammonia emissions, which ultimately contribute to particulate forma- tion, are evaluated by APEEP but not included in the default transportation damage assessment. GREET does not evaluate ammonia emissions but Mobile6.2 does for a subset of vehicle and fuel combinations included in GREET. Table D-13 summarizes the Mobile6.2 ammonia emission factors for 2005 and 2030. For light-duty gasoline vehicles, the ammonia factors are about 0.1 g/VMT; for light-duty diesel vehicles, they range from 0.01 to 0.03 g/VMT for both years. The heavy-duty gasoline and diesel vehicle factors are 0.05 and 0.03 g/VMT. Applying GREET Feedstock and Fuel Production Factors to Heavy-Duty Vehicles Feedstock and fuel production factors from GREET are used to supple- ment the Mobile6.2 heavy-duty-vehicle operational emissions. Because Mo- bile6.2 evaluates only the operational phase of heavy-duty vehicles, there is a need to supplement this component with feedstock and fuel production requirements so that results are commensurate with light-duty vehicles evaluated in GREET. To do this, the GREET feedstock and fuel production factors from reformulated gasoline and low-sulfur diesel light-duty vehicles are used. Using the energy content of gasoline or diesel consumed during vehicle operation, the corresponding GREET feedstock and fuel production factors are prorated and assessed to the heavy-duty vehicles. This procedure is done across all of the energy and emissions factors for each of the heavy- duty vehicles assessed with Mobile6.2. Heavy-duty vehicle-manufacturing factors are not included in the as- sessment. Unlike feedstock and fuel production processes that are specific to a fuel (which is the same for both light- and heavy-duty vehicles), vehicle-

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46 APPENDIX D TABLE D-13 Mobile6.2 Ammonia Emissions (g/VMT) 2005 2030 HDGV2B 0.045 0.045 HDGV3 0.045 0.045 HDGV4 0.045 0.045 HDGV5 0.045 0.045 HDGV6 0.045 0.045 HDGV7 0.045 0.045 HDDV2B 0.027 0.027 HDDV3 0.027 0.027 HDDV4 0.027 0.027 HDDV5 0.027 0.027 HDDV6 0.027 0.027 HDDV7 0.027 0.027 HDDV8A 0.027 0.027 HDDV8B 0.027 0.027 LDGV 0.100 0.102 LDGT1 0.100 0.102 LDGT2 0.097 0.102 LDGT3 0.097 0.102 LDDV 0.007 0.007 LDDT 0.027 0.027 LDDT12 0.007 0.007 manufacturing processes are unique. There is no known information that estimates the energy requirements and resulting emissions of manufacturing heavy-duty gasoline and diesel fuels of different classes. As a result, this component was excluded from the assessment. COUNTY-LEVEL DAMAGE CALCULATIONS The vehicle feedstock, fuel, operation, and manufacturing per VMT emission factors are used in conjunction with APEEP county unit-damage factors to determine county resolution total damages. For each of the life- cycle components, particular assumptions were made in performing the calculations. APEEP has county-level pollutant-unit damages for all states except Alaska and Hawaii. For every county, APEEP reports ground levels and various heights of emission-unit damages (dollar per metric tonne emit- ted) for VOCs, NOx, PM2.5, SO2, and NH3 (ammonia). Feedstock Production Damages The location of feedstock production and associated emissions is not clear for the various fuel energy inputs. From crude oil to corn to coal, the

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466 APPENDIX D identification of feedstock production locations is not transparent. Feed- stock can be produced internationally (for example, conventional crude oil from overseas or tar sands crude oil from Canada) or domestically (for example, coal or corn), and transport of raw energy inputs can occur along the fuel production pathway. The difficulty of estimating feedstock produc- tion and transport locations resulted in the assignment of these emissions to the county where travel occurs. The feedstock emissions are assessed the lowest level above ground-level height in APEEP. Fuel Production Damages Fuel production damages are assessed to particular geographic regions based on petroleum refinery and ethanol plant locations. PADD (Petroleum Administration for Defense Districts) regions are used to identify five geo- graphic areas of the United States for petroleum production and consump- tion statistics. The regions are East Coast, Midwest, Gulf Coast, Rocky Mountain, and West Coast and serve as a common resolution for petroleum data. The U.S. Energy Information Administration reports petroleum refin- ery locations and production capacity (EIA 2009b). Using these locations, associated counties could be determined for assessment of APEEP damage factors for conventional fueled vehicles. Without knowing which refinery produces the fuel for a VMT in another county, PADD resolution was used to assess fuel production unit damages. For each PADD, a weighted-average APEEP fuel factor (further referred to as APEEPFUEL) was determined from the percentage of PADD fuel production capacity for each refinery and the corresponding county. The result produced five APEEPFUEL pollutant damage factors, one for each PADD. The APEEPFUEL damage factors were assessed to each county in the United States based on its PADD location. The fuel production life-cycle emissions were used in conjunction with the APEEPFUEL factors to determine fuel production damages for each county given a specific vehicle’s per VMT emissions. A PADD-based resolution approach was also used for ethanol fuel pro- duction. Using ethanol refinery locations (RFA 2009), APEEPFUEL factors were determined for ethanol production for each of the five PADD regions. Given the mix of ethanol in the fuel (10% or 85%), this fraction was multi- plied by the APEEPFUEL ethanol factor and the remainder by the APEEPFUEL gasoline factor. For example, for an E10 vehicle operating in a county in PADD 1, 10% × APEEPFUEL,ETHANOL and 90% × APEEPFUEL,GASOLINE are added and assessed to that county. This mixed APEEPFUEL factor for each pollutant is then multiplied by the corresponding fuel production emissions for an E10 vehicle. Similar to feedstock production, the fuel production APEEP factors are based on the lowest level height above ground level. For electric vehicles, power-plant emissions were assumed to occur ac-

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46 APPENDIX D cording to petroleum PADD locations. Given the complexity of modeling electricity-generation emissions associated with specific driving locations, fuel production emissions were assigned to the petroleum production loca- tions within relevant PADD regions. Vehicle Operation Damages Vehicle operation VMT are based on county populations, which are assumed to be a reasonable metric for disaggregation of total state VMT. Given the GREET and Mobile6.2 per VMT emissions factors, VMT esti- mates are needed for each U.S. county to determine total emissions in that county. State-level VMT is available but not any higher resolution (FDA 2008). Using U.S. census population estimates, state-level VMT is disaggre- gated to each county by the fraction of population. These county VMT are then multiplied by the GREET and Mobile6.2 vehicle operational emission factors to determine total emissions for each county. The emissions of each pollutant are then joined with the APEEP ground-level-pollutant county factors to determine total damages. Vehicle-Manufacturing Damages PADD regions are used to aggregate vehicle-manufacturing APEEP costs, similar to fuel production. Census data were examined for informa- tion on vehicles, parts, and tire manufacturing facilities (including number of facilities, employee counts, and county). The census data details the location and employee count for over 8,000 facilities. For each county in the United States, the total number of employees from these industries was determined. A weighted-average vehicle-manufacturing APEEP factor (fur- ther referred to as APEEPMANUFACTURING) was determined for each PADD based on the percentage of employees and the APEEP factor foreach county in a PADD. Again, this process was done because of the lack of information that identifies whether a vehicle is driven in a particular county where it was manufactured. The PADD-based approach assumes that for a vehicle driven in a particular county, the manufacturing took place in that county’s PADD and the weighted-average APEEPMANUFACTURING factor is applied. Total Life-Cycle Damages Total damages are determined from feedstock production, fuel produc- tion, vehicle operation, and vehicle-manufacturing factors. This assessment was performed for each vehicle and fuel combination. Given a specific vehicle and fuel combination, the feedstock, fuel, operation, and manufac- turing emission factors (in grams of VOC, NOX, PM2.5, and SO2 per VMT)

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468 APPENDIX D are multiplied by the APEEP county and pollutant factors (dollar damages per gram of pollutant, which may be weighted averages for the PADD re- gion). Furthermore, the APEEP factors are reported in dollars of damage of emission for mortality, morbidity, and other damages (for example, ag- ricultural or visibility impairment). For each vehicle and fuel combination, the life-cycle emission factors are joined with the APEEP pollutant damage factors for mortality, morbidity, and other to determine total damages for each county. The result is a mortality-morbidity-and-other dollar damages for each county and each vehicle type (light-duty autos, truck 1, and truck 2) in both 2005 and 2030. Damages Related to Electric Vehicles and Grid-Dependent Hybrids For the vehicle-manufacturing component and the fuel feedstock (for example, coal or natural gas) component of the life cycles of electric ve- hicles (EVs) and grid-dependent hybrid vehicles (GD-HVs), the GREET model’s estimates of emissions per VMT were paired with results from the APEEP model, a process that provided estimates of the physical health and other nonclimate-change-related effects and monetary damages per ton of emissions that form criteria air pollutants. However, the allocation of electric-utility-related damages to the vehicle operations and electricity production components of the life cycles were approximated by applying a GREET-generated kWh/VMT and applying that to the estimated aver- age national damages per kWh from the electricity analysis presented in Chapter 2. The committee used 1.59 cents/kWh for 2005 and 0.79 cents/kWh for 2030 for the damages due to producing (not consuming) electricity for both EVs and GD-HEVs. Those values were obtained by determining the aggregate marginal damages for coal-fired and natural gas plants based on their shares of net generation and the average marginal damages for each type of plant. For example, for 2005: [0.485 (coal share of net generation) × 3.2 cents/kWh] + [0.213 (natural gas share of net generation) × 0.16 cents/kWh] = 1.59 cents/kWh. We estimated the fuel (electricity generation) component damages based on the damages associated with producing electricity at the rate of 0.52 kWh/VMT, and the fuel damages for 2005 were calculated as fol- lows: 0.52 kWh/VMT × 1.59 cents/kWh = 0.83 cents/VMT. For 2030, the estimate for fuel damage is 0.31 cents/VMT. For the vehicle operation component, we estimated damage associated with a 10% loss of electricity over transmission and distribution lines (for example, 0.05 kWh/VMT for 2005) (DOE 2009). A similar approach was used for estimating the electricity-related dam-

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46 APPENDIX D ages for GD-HEVs. However, no more than 35% of energy supplied to GD-HEVs was estimated to come from the grid. REFERENCES Argonne National Laboratory. 2009. The Greenhouse Gases, Regulated Emissions, and Energy Use on Transportation (GREET) Model. U.S. Department of Energy, Argonne National Laboratory [online]. Available: http://www.transportation.anl.gov/modeling_simulation/ GREET/ [accessed Oct. 12, 2009]. DOE (U.S. Department of Energy). 2009. Overview of the Electric Grid. Office of Electricity Delivery and Energy Reliability, U.S. Department of Energy [online]. Available: http:// sites.energetics.com/gridworks/grid.html [accessed Sept. 4, 2009]. EIA (Energy Information Administration). 2006. Annual Energy Outlook 2007, With Projec- tions to 2030. DOE/EIA-0383(2007). Energy Information Administration, Office of Integrated Analysis and Forecasting, U.S. Department of Energy, Washington, DC. Feb- ruary 2006 [online]. Available: http://tonto.eia.doe.gov/ftproot/forecasting/0383(2007). pdf [accessed Nov. 19, 2009]. EIA (Energy Information Administration). 2009a. Annual Energy Outlook 2009, With Pro- jections to 2030. DOE/EIA-0383(2009). Energy Information Administration, Office of Integrated Analysis and Forecasting, U.S. Department of Energy, Washington, DC. March 2009 [online]. Available: http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2009).pdf [accessed Apr. 22, 2009]. EIA (Energy Information Administration). 2009b. Ranking of U.S. Refineries. Energy Informa- tion Administration [online]. Available: http://www.eia.doe.gov/neic/rankings/refineries. htm [accessed Nov. 19, 2009]. EPA (U.S. Environmental Protection Agency). 2009. Mobile6 Vehicle Emission Modeling Software. U.S. Environmental Protection Agency [online]. Available: http://www.epa. gov/OMS/m6.htm [accessed Nov. 13, 2009]. FDA (Federal Highway Administration). 2008. Highway Statistics Series. Policy Information. U.S. Department of Transportation, Federal Highway Administration [online]. Available: http://www.fhwa.dot.gov/policy/ohpi/hss/index.cfm [accessed Nov. 13, 2009]. RFA (Renewable Fuel Association). 2009. Biorefinery Locations. Renewable Fuel Associa- tion, Washington, DC [online]. Available: http://www.ethanolrfa.org/industry/locations/ [accessed Nov. 13, 2009].