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Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use
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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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 different 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 production, 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 components. 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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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 operational emission factors were used in combination with GREET feedstock and fuel production factors to create life-cycle inventories for several different 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 production, operation, and vehicle-manufacturing factors for light-duty vehicles 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 appendix. For all vehicles, energy inputs, CO2, CH4, N2O, VOC, CO, NOx, PM10, PM2.5, and SOx emissions are determined for the life-cycle components. 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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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, powertrain 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 assessment, so process changes from 2005 through 2030 are not captured. Energy and emission factors are determined for the vehicle size, powerdelivery 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 resulting 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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TABLE D-1 GREET 2.7a Vehicle-Manufacturing Results for Cars
ICEV: Conventional Material
ICEV: Light-Weight Material
HEV: Conventional Material
HEV: Light-Weight Material
FCV: Conventional Material
FCV: Light-Weight Material
Lifetime VMT
160,000
160,000
160,000
160,000
160,000
160,000
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
N2O
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: Conventional Material
ICEV: Light-Weight Material
HEV: Conventional Material
HEV: Light-Weight Material
FCV: Conventional Material
FCV: Light-Weight Material
Lifetime VMT
180,000
180,000
180,000
180,000
180,000
180,000
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
N2O
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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line vehicles, GREET’s share of reformulated gasoline in total gasoline factor 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 ethanol 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 factors 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 gallon 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 economies 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 reduced 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
Total Energy
Petroleum
CO2
CO2e
VOC
NOx
PM2.5
SOx
Btu/VMT
Btu/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
RFG SI Autos (Conventional Oil)
Feedstock
232
64
6
18
0.02
0.15
0.01
0.05
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 (Tar Sands)
Feedstock
853
62
50
64
0.02
0.14
0.01
0.06
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 (Conventional Oil)
Feedstock
236
65
17
29
0.02
0.15
0.01
0.05
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 (Tar Sands)
Feedstock
865
63
62
76
0.02
0.14
0.01
0.06
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 (Conventional Oil)
Feedstock
202
55
5
16
0.02
0.13
0.00
0.05
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 (Tar Sands)
Feedstock
742
54
44
56
0.02
0.12
0.01
0.05
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 (Low Sulfur)
Feedstock
193
53
19
29
0.02
0.12
0.00
0.04
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 (Fischer Tropsch)
Feedstock
280
18
22
35
0.02
0.11
0.00
0.05
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 (Soy BD20)
Feedstock
427
213
−30
−13
0.03
0.23
0.01
0.13
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 (Dry Corn)
Feedstock
822
229
−225
−173
0.06
0.42
0.02
0.19
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 (Wet Corn)
Feedstock
898
498
−212
−144
−0.14
0.58
0.03
0.29
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 (Herbaceous)
Feedstock
570
216
−282
−237
0.06
0.29
0.02
0.06
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
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Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use
Total Energy
Petroleum
CO2
CO2e
VOC
NOx
PM2.5
SOx
Btu/VMT
Btu/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
E85 (Corn Stover)
Feedstock
407
229
−263
−261
0.03
0.24
0.02
0.11
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 (Dry Corn)
Feedstock
287
79
1
17
0.02
0.17
0.01
0.06
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 (Wet Corn)
Feedstock
294
103
2
19
0.01
0.19
0.01
0.07
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 (Herbaceous)
Feedstock
265
78
−4
11
0.02
0.16
0.01
0.05
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 (Corn Stover)
Feedstock
251
79
−2
9
0.02
0.16
0.01
0.06
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 (Gaseous)
Feedstock
180
10
13
27
0.01
0.07
0.00
0.03
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 SI HEV
Feedstock
159
44
11
20
0.01
0.10
0.00
0.04
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 HEV
Feedstock
159
48
12
21
0.02
0.09
0.04
0.04
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
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TABLE D-4 GREET Energy and Emission Factors for Light-Duty Trucks 1 in 2005
Total Energy
Petroleum
CO2
CO2e
VOC
NOx
PM2.5
SOx
Btu/VMT
Btu/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
RFG SI Autos (Conventional Oil)
Feedstock
297
82
7
23
0.02
0.19
0.01
0.07
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 (Tar Sands)
Feedstock
1090
79
65
82
0.03
0.18
0.01
0.08
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 (Conventional Oil)
Feedstock
301
83
22
37
0.02
0.19
0.01
0.07
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 (Tar Sands)
Feedstock
1106
80
80
97
0.03
0.18
0.01
0.08
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 (Conventional Oil)
Feedstock
258
71
6
20
0.02
0.16
0.01
0.06
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 (Tar Sands)
Feedstock
948
69
56
71
0.02
0.16
0.01
0.07
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 (Low Sulfur)
Feedstock
363
66
33
46
0.02
0.12
0.01
0.04
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 (Fischer-Tropsch)
Feedstock
353
23
27
44
0.03
0.09
0.00
0.06
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 (Soy BD20)
Feedstock
631
262
−30
−8
0.03
0.19
0.01
0.13
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 (Dry Corn)
Feedstock
1014
288
−284
−226
0.06
0.31
0.01
0.15
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 (Wet Corn)
Feedstock
1024
555
−275
−203
−0.17
0.47
0.02
0.26
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 (Herbaceous)
Feedstock
663
234
−351
−302
0.05
0.22
0.01
0.04
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
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Total Energy
Petroleum
CO2
CO2e
VOC
NOx
PM2.5
SOx
BTU/VMT
BTU/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
g/VMT
E85 (Corn Stover)
Feedstock
475
236
−332
−329
0.03
0.15
0.01
0.09
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 (Dry Corn)
Feedstock
487
98
11
31
0.03
0.16
0.01
0.06
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 (Wet Corn)
Feedstock
488
121
12
33
0.01
0.17
0.01
0.07
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 (Herbaceous)
Feedstock
456
93
6
24
0.03
0.15
0.01
0.05
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 (Corn Stover)
Feedstock
440
93
7
22
0.02
0.15
0.01
0.05
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 (Gaseous)
Feedstock
232
13
16
34
0.02
0.06
0.00
0.03
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 (Liquid)
Feedstock
233
13
16
34
0.02
0.06
0.00
0.03
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 SI HEV
Feedstock
305
56
13
24
0.02
0.10
0.00
0.04
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 SIHEV
Feedstock
272
59
14
27
0.02
0.09
0.05
0.04
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
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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 Mobile6.2’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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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 Exhaust
VOC Evap
NOx
PM2.5 Exhaust
PM2.5 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 Exhaust
NOx
PM2.5 Exhaust
PM2.5 TBW
GREET
0.09
0.3
0.07
0.007
Mobile6.2
0.33
1.3
0.15
0.007
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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 parameters. 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 vehicle 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 formation, 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 supplement the Mobile6.2 heavy-duty-vehicle operational emissions. Because Mobile6.2 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 assessment. 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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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 lifecycle 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 emitted) 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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identification of feedstock production locations is not transparent. Feedstock 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 production 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 geographic areas of the United States for petroleum production and consumption 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 refinery 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 production. 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 multiplied by the APEEPFUEL ethanol factor and the remainder by the APEEP FUEL 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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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 locations 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 estimates 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 disaggregated 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 information 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 (further 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 production, 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 manufacturing emission factors (in grams of VOC, NOX, PM2.5, and SO2 per VMT)
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are multiplied by the APEEP county and pollutant factors (dollar damages per gram of pollutant, which may be weighted averages for the PADD region). Furthermore, the APEEP factors are reported in dollars of damage of emission for mortality, morbidity, and other damages (for example, agricultural 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 vehicles (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 average 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 follows: 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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ages for GD-HEVs. However, no more than 35% of energy supplied to GD-HEVs was estimated to come from the grid.
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