10098_2016_1260_moesm1_esm.docx - springer …10.1007... · web viewfigure 4 shows the life cycle...

A Comparison of Major Petroleum Life Cycle Models – Online Resources

Donald Vineyard1 and Wesley W. Ingwersen2*

1ORISE Research Participant, National Risk Management Research Laboratory, United States

Environmental Protection Agency, 26 W. Martin Luther King Drive, Cincinnati, OH 45268.2Environmental Engineer, National Risk Management Research Laboratory, United States Environmental

Protection Agency, 26 W. Martin Luther King Drive, Cincinnati, OH 45268.*Corresponding Author: [email protected], (513) 569-7602

Table of ContentsBackground on Petroleum in the US....................................................................................................................1

Numerical DQI......................................................................................................................................................1

Processed Used.....................................................................................................................................................4

Diesel Results........................................................................................................................................................6

Expanded Model Results......................................................................................................................................7

Sengupta Processes..............................................................................................................................................9

Products by Model..............................................................................................................................................13

Brief History of Regulatory Changes...................................................................................................................14

Background on Petroleum in the US

Petroleum is the largest energy source in the United States, supplying roughly 36% of its total energy (EIA 2012)

and is used either directly or indirectly in every sector of the US economy. Petroleum products result in

approximately 43% of the US energy-related carbon dioxide emissions (EIA 2011). In the United States, gasoline is

the most demanded petroleum product; the US uses 8.7 million barrels of gasoline per day along with 1.4 million

barrels of jet fuel and 3.8 million barrels of diesel (EIA 2012). Over 1.1 billion metric tons of carbon dioxide (20.9%

of the US CO2 load) are produced annually from motor gasoline usage (EIA 2011). Petroleum fuels are vital to the

US economy, facilitating both the transportation of goods and the transportation of workers over long distances. In

the US, at least 75% of domestic freight tonnage is transported by truck (as opposed to 10% by rail and 3% by

water) (FHA 2013) and the population drives over 10,000 miles per capita per year (FHA 2007). In addition to fuel,

approximately 17% of petroleum products are used as feedstock for a variety of products ranging from plastics to

asphalt to pharmaceuticals (EIA 2011). The combustion and decomposition of petroleum products produces a

variety of pollutants in addition to carbon dioxide. These pollutants include carbon monoxide, particulate matter,

volatile organic compounds, methane, and oxides of sulfur and nitrogen. These emissions can have a wide range of

harmful effects on both the environment and human health, from causing acid rain and global warming to increasing

rates of respiratory disease and cancer in humans. Still more emissions are created before the products are ever

burned or processed, during the extraction, refining, and distribution of crude oil and finished products (Hsu 2011).

Numerical DQI

A summary of flow-level data quality indicators for the five gasoline life cycle models can be found in Table 5

while more complete reporting is in Table 6; these indicators are created by averaging the flow-level indicators of all

inputs with indicators of outputs relevant to this study.

Table 5 Flow-Level data quality indicators. Scale: 1 is the highest quality; 5 is the lowest.

Category Sengupta ecoinvent USLCI GREET NETLTemporal Representativeness 3.9 5 3. 8 3.1 3.1

Geographical Representativeness 2.2 5 1 2 1.3Technological Relevance 2.2 3.5 1 1. 7 1.2

Sampling Correlation 2.6 3.7 1.3 2.2 1.6

Table 6 Flow-level DQI markers of criteria pollutant outputs from refining stage unit processes. These scores use

the same methodology applied previously with one exception: in these cases, the primary data source(s) for each

pollutant is assessed rather than the model as a whole. Scale: 1 is the highest quality; 5 is the lowest.

Pollutant Model Temporal Correlation

Geographical Correlation

Technological Correlation

Sampling Correlation

1

Ammonia

Sengupta 3 1 1 2ecoinvent 5 5 3 4USLCI 4 1 1 2GREET 2.8 1.6 1.3 1.9NETL 3 1 1 2

CO

Sengupta 3 1 1 2ecoinvent - - - -USLCI 4 1 1 2GREET 2.8 1.6 1.3 1.9NETL 3 1 1 2

CO2

Sengupta 3 1 1 1ecoinvent - - - -USLCI 2 1 1 1GREET 5 5 5 5NETL 3.8 2.5 2 2.8

Methane

Sengupta 3 1 1 1ecoinvent 5 5 3 5USLCI 2 1 1 1GREET 2.8 1.6 1.3 1.9NETL 3.8 2.5 2 2.8

N2O

Sengupta 3 1 1 3ecoinvent 5 5 3 3USLCI - - - -GREET 2.8 1.6 1.3 1.9NETL 3.8 2.5 2 2.8

NOx

Sengupta 3 1 1 2ecoinvent - - - -USLCI 4 1 1 2GREET 2.8 1.6 1.3 1.9NETL 3 1 1 2

PM10

Sengupta 3 1 1 2ecoinvent - - - -USLCI 4 1 1 2GREET 2.8 1.6 1.3 1.9NETL - - - -

PM2.5

Sengupta 3 1 1 2ecoinvent - - - -USLCI 4 1 1 2GREET 2.8 1.6 1.3 1.9NETL - - - -

SOx Sengupta 3 1 1 2

2

ecoinvent 5 5 5 5USLCI 4 1 1 2GREET 2.8 1.6 1.3 1.9NETL 3 1 1 2

VOC

Sengupta - - - -ecoinvent 5 5 3 3USLCI 4 1 1 1GREET 2.8 1.6 1.3 1.9NETL 3 1 1 1

Table 7 contains a categorical assessment of flows in the five models’ third stages. This scoring system was

developed for assessing the completeness of LCA models in a publication to be released by Edelen and Ingwersen

(2016). The method checks for the tracking of different likely areas of impact by the system and compares contents

between models. According to this rubric, the NETL and ecoinvent refinery models are the most complete, primarily

due to the tracking of flows such as solid waste, land transformation, and emissions to soil and water, which other

models overlook. The Sengupta, USLCI, and GREET models have the third, fourth, and fifth scores, respectively,

for progressively tracking fewer material flows and coproducts. None of the models appears to assess the harmful

impacts of petroleum spills in their upstream models, as is currently typical in petroleum LCI.

Table 7 Flow Completeness Scoring for Model Refinery Emissions.

Flow Type Sengupta ecoinvent USLCI GREET NETL Out of

Co-products 10 6.1 5.6 8.3 3.9 10Intermediate inputs 18 20 18 18 18 20

Land occupied/transformed 0 5 0 0 0 5Raw material inputs 3 4 3 3 4 4Raw energy inputs 1 1 1 1 1 1

Water input 5 5 0 5 5 5Waste to treatment

Solid and hazardous waste 0 5 0 0 5 5Liquid waste 0 0 0 0 0 5

Emissions to airGHGs 5 5 5 5 5 5

Criteria Air Pollutants 5 2 4 4 5 5Toxics + Other 5 5 5 1 5 5

Water 0 0 0 0 0 5Emissions to water

Nutrients 0 5 2 0 5 5Toxics + Other 0 5 5 0 5 5

Emissions to soilNutrients 0 0 0 0 3 5

3

Toxics + Other 0 0 0 0 5 5

TOTAL 57.0 73.1 53.6 50.3 74.9 100

Processed Used

Tables 8 and 9 list processes important to each stage of gasoline and diesel production, respectively, for each model.

Table 8 Processes by life cycle stages in the major gasoline life cycle models. Sources of unit process data are

included in parenthesis if not original.

Sengupta Ecoinvent (EI) USLCI GREET NETL

Raw Material Acquisition

Crude oil, extracted (Modified USLCI)

crude oil, at productioncrude oil, at

production on shorea

crude oil, at production off

shorea

Crude oil, extracted

Conventional Crude Recovery

Bitumen Extraction and Upgrading-In-

Situ Production + SCO

Bitumen Extraction and Separation-In-

SituProduction + BitumenBitumen

Extraction and Separation-

Surface Mining + Bitumen

Gasoline, Production,

Transport, and Refining

Raw Material Transport

transport, barge tanker/RER

(EI)transport,

barge/RER (EI)transport,

freight, rail, diesel/US (EI)

Truck transport, fuel tanker, diesel,

short haul, load factor 0.5

(modified EI)

crude oil, production XX, at long distance

transporta

Transport, barge, diesel

powered – USTransport,

barge, residual fuel oil

powered – USTransport,

ocean freighter, diesel powered

– USTransport,

ocean freighter, residual fuel oil powered – US

Transport, pipeline,

Conventional Crude Oil for

Use in US RefineryCrude Oil Storage

Synthetic Crude Oil Storage

Synthetic Crude Oil (SCO)

Transportation to U.S. RefineriesDilbit (diluted

bitumen) Transportation to U.S. Refineries



4

unspecified petroleum

products - US

RefiningPetroleum

refining, US average

Petrol, unleaded, at

refinery – RERpetrol, low-sulphur, at

refinery - RER

Petroleum refining, at

refineryCG Refining



Refined Product

Transport

transport, transoceanic tanker – OCE

Transport, crude oil pipeline,

onshore – RERRegional

distribution, oil products – RER

Transport, barge tnaker –

RERTransport,

freight, rail, diesel - US

transport, lorry >16t, fleet

average – RERTransport, crude oil pipeline,

onshore – RERRegional

distribution, oil products – RER

Transport, transoceanic tanker – OCE

Transport, freight, rail –

RERTransport,

barge tanker - RER

Transport, ocean freighter,

average fuel mix - US Transport,

train, diesel powered - US

Transport, pipeline,

unspecified petroleum

products - US Transport,

combination truck, average fuel mix - US

Transport, barge, average fuel mix - US

station.S. Conventional Gasoline – to bulk terminal

U.S. Conventional Gasoline - to

refueling station

Bulk Storage Facility, Gasoline, Operation

Fuel Storage and Dispensing

Gasoline, dispensed at

pump (modified EI)

petrol, low-sulphur, at regional storage

N/A N/ARefueling

Station, Ethanol, Operation

a A mix of processes with the same name and different location code is used by Ecoinvent to represent equivalent

actitivities in different regions. Those mixes were not altered.

Table 9 Unit processes used to analyze diesel models

Sengupta Ecoinvent (EI) USLCI GREET NETL

Raw Material Acquisition

Petroleum Refining, US

average

Crude oil, at production

Crude oil, extracted

Crude Oil Average for Use

in U.S. Refineries

Diesel, Production,


Raw Material Transport

Petroleum Refining, US

average

Crude oil, production XX, at long distance

transport,


refinery

Crude Oil Average for Use

in U.S. Refineries

Diesel, Production,


RefiningPetroleum

Refining, US average

diesel, low-sulphur, at

refinery - RER


refinery

Conv. Diesel Refining

Diesel, Production,


5

Refined Product

Transport

Diesel, at storage terminal

diesel, low-sulphur, at regional

storage - RER

Transport, passenger car, diesel powered

- US

U.S. Conventional

Diesel

Bulk Storage Facility, Diesel,

Operation

Fuel Storage and Dispensing

Diesel, dispensed at

pump

diesel, low-sulphur, at regional

storage - RER

Conv. Diesel Storage

Refueling Station, Ethanol,

Operation

Diesel Results

To determine whether gasoline relationships would hold for other fuel types, we performed the same procedure for

diesel fuel as used for gasoline. Figure 4 shows the life cycle predictions of our five models on the production of

diesel fuel while Figure 5 shows the same figures with the addition of a combustion emission from the USLCI

process “Transport, combination truck, long-haul, diesel powered.” Overall, the differences between models are

largely the same as they are for gasoline, but the relationship between the pre and post-combustion emissions are

slightly altered. The expansion of the scope to include combustion emissions for diesel reduces variance between the

model results more than this same scope expansion does for gasoline.

Ammonia CO CO2 Methane N2O NOx PM10 PM2.5 SOx VOC0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sengupta EcoInvent USLCI GREET NETL

Figure 4 Cradle to Gate Impacts of Diesel Production by model. Models show wide variance in almost all tracked

emissions, with no clear trend between models across emissions

6

Figure 5 Comparison of predicted emissions between five major diesel pre-combustion models from the Well-to-

Wheel perspective. Differences between models are more subdued for diesel than for gasoline.

Expanded Model Results

Table 10 Calculated outputs of criteria pollutant and GHG emissions from the five pre-combustion life cycle stages

of gasoline as predicted by five major fuel models

Crude Oil Crude Transport

Refinery Refined Transport

Regional Storage

Ammonia

Sengupta 1.27E-06 2.80E-08 2.30E-05 3.14E-06 1.76E-06EcoInvent 1.46E-06 3.19E-06 1.78E-06 3.19E-06 7.02E-08USLCI 3.17E-08 9.62E-08 3.91E-06 1.59E-07 0.00E+0

0GREET 0.00E+00 0.00E+00 0.00E+0

00.00E+00 0.00E+0

0NETL 2.01E-06 1.01E-06 3.94E-06 0.00E+00 0.00E+0

0

CO


0GREET 2.46E-04 8.61E-05 3.53E-04 3.30E-05 0.00E+0

0NETL 4.03E-04 2.80E-05 1.62E-04 3.20E-11 0.00E+0

0

CO2Sengupta 1.18E-01 1.76E-03 3.06E-01 2.20E-02 4.30E-02EcoInvent 1.59E-01 4.93E-02 4.22E-01 4.48E-02 4.44E-03

7

USLCI 1.12E-01 9.72E-02 2.28E-01 1.72E-01 0.00E+00

GREET 1.31E-01 7.63E-02 5.20E-01 2.20E-02 0.00E+00

NETL 1.86E-01 5.34E-02 3.93E-01 0.00E+00 0.00E+00

Methane


0GREET 4.66E-03 1.27E-04 1.44E-03 3.90E-05 0.00E+0

0NETL 3.63E-03 2.90E-05 4.79E-04 0.00E+00 0.00E+0

0

N2O


0GREET 9.80E-07 1.31E-06 6.71E-06 1.00E-06 0.00E+0

0NETL 5.01E-06 1.08E-06 6.34E-06 0.00E+00 0.00E+0

0

NOx


0GREET 3.53E-04 6.77E-04 8.29E-04 1.54E-04 0.00E+0

0NETL 5.81E-04 1.11E-04 3.19E-04 1.28E-11 0.00E+0

0

PM10


0GREET 2.64E-05 5.90E-05 1.62E-04 9.00E-06 0.00E+0

0NETL 0.00E+00 4.49E-05 0.00E+0

00.00E+00 0.00E+0

0

PM2.5


0GREET 1.94E-05 5.00E-05 9.56E-05 7.00E-06 0.00E+0

0NETL 9.75E-06 1.39E-06 3.03E-06 0.00E+00 0.00E+0

0SOx Sengupta 1.60E-04 0.00E+00 4.00E-04 9.00E-05 2.30E-04

EcoInvent 2.24E-03 5.67E-04 2.78E-03 2.04E-04 1.37E-05USLCI 2.56E-04 3.14E-04 8.95E-04 5.47E-04 0.00E+0

0GREET -7.79E-04 1.33E-03 6.09E-04 5.50E-05 0.00E+0

0

8

NETL 9.31E-04 8.54E-04 5.45E-04 0.00E+00 0.00E+00

VOC


0GREET 7.62E-05 9.41E-05 9.84E-04 8.21E-04 0.00E+0

0NETL 7.84E-04 7.63E-04 1.76E-04 1.08E-03 1.25E-04

Water Vapor

Sengupta 9.13E+01 2.93E-03 1.23E+02

1.49E+01 2.12E-01

EcoInvent 2.45E-03 1.26E-03 2.69E-03 8.40E-04 1.88E-04USLCI 3.87E-05 1.33E-05 1.38E-04 6.67E-05 0.00E+0

0GREET 0.00E+00 0.00E+00 0.00E+0

00.00E+00 0.00E+0

0NETL 0.00E+00 0.00E+00 0.00E+0

00.00E+00 0.00E+0

0

Sengupta Processes

The oil-extraction and post-refinery unit processes for the Sengupta model are not documented in the 2015

publication. Therefore, data and descriptions for those models are provided in this section. The Stage 1 Crude Oil

extraction process contains inputs and outputs as shown in Table 11. This process relies primarily on USLCI data,

but uses altered electricity and petroleum sources along with other modifications.

Table 11 Sengupta Crude Oil Extraction process

Flow Category Unit Amount Uncertainty

Inpu

ts

electricity, at industrial user kWh 0.039007761 noneOil, crude, 43.7 MJ per kg, in ground

resource/fossil- kg 1.035 none

Dummy_Disposal, solid waste, unspecified, to sanitary landfill

kg 0.026145465 none

Diesel, combusted in industrial equipment (USLCI) l 0.001292841 noneResidual fuel oil, combusted in industrial boiler (USLCI) l 7.98E-04 noneNatural gas, combusted in industrial boiler (USLCI) m3 0.032773193 noneGasoline, combusted in equipment (USLCI) l 6.84E-04 none

Out

puts

Carbon dioxide, fossil air/unspecified kg 0.0011 noneSodium, ion water/unspecified kg 0.001477 noneSuspended solids, unspecified water/unspecified kg 0.002324 noneMethane air/unspecified kg 0.0053 none

9

Chloride water/unspecified kg 0.006074 noneDissolved solids water/unspecified kg 0.006472 noneCrude oil, extracted (USLCI) kg 1 noneSulfate water/unspecified kg 1.06E-05 noneFluorene water/unspecified kg 1.15E-09 noneXylene water/unspecified kg 1.16E-07 noneLead water/unspecified kg 1.18E-07 noneStrontium water/unspecified kg 1.20E-05 noneDodecane water/unspecified kg 1.21E-08 noneSurfactants water/unspecified kg 1.21E-07 noneAntimony water/unspecified kg 1.32E-08 noneHexadecane water/unspecified kg 1.33E-08 noneBenzene, ethyl- water/unspecified kg 1.45E-08 none2-Hexanone water/unspecified kg 1.45E-09 noneManganese water/unspecified kg 1.46E-07 noneYttrium water/unspecified kg 1.48E-09 noneLithium, ion water/unspecified kg 1.56E-07 nonePhenanthrene water/unspecified kg 1.76E-10 noneMethane, monochloro-, R-40 water/unspecified kg 1.83E-12 none4-Methyl-2-pentanone water/unspecified kg 1.91E-10 noneTitanium, ion water/unspecified kg 2.02E-07 noneAluminium water/unspecified kg 2.10E-05 noneBenzoic acid water/unspecified kg 2.25E-07 noneLead-210/kg water/unspecified kg 2.301E-17 noneMercury water/unspecified kg 2.31E-10 nonep-Xylene water/unspecified kg 2.33E-09 noneo-Xylene water/unspecified kg 2.33E-09 noneToluene water/unspecified kg 2.42E-07 noneFluorenes, alkylated, unspecified water/unspecified kg 2.49E-09 noneBOD5, Biological Oxygen Demand water/unspecified kg 2.53E-05 noneSelenium water/unspecified kg 2.54E-09 noneBenzene water/unspecified kg 2.61E-07 noneThallium water/unspecified kg 2.77E-09 noneAmmonia water/unspecified kg 2.78E-06 noneBiphenyl water/unspecified kg 2.78E-09 noneBarium water/unspecified kg 2.85E-04 noneBeryllium water/unspecified kg 2.87E-09 nonePhenanthrenes, alkylated, unspecified

water/unspecified kg 2.92E-10 none

Hexacosane water/unspecified kg 3.04E-11 noneBromide water/unspecified kg 3.11E-05 noneSilver water/unspecified kg 3.11E-07 noneCyanide water/unspecified kg 3.29E-12 none

10

Octadecane water/unspecified kg 3.30E-09 noneNaphthalene, 2-methyl- water/unspecified kg 3.31E-09 noneIcosane water/unspecified kg 3.32E-09 noneBenzene, pentamethyl- water/unspecified kg 3.41E-12 noneMethyl ethyl ketone water/unspecified kg 3.67E-12 noneIron water/unspecified kg 3.93E-05 noneNaphthalene water/unspecified kg 3.96E-09 noneRadium-228/kg water/unspecified kg 4.10E-17 noneCOD, Chemical Oxygen Demand water/unspecified kg 4.18E-05 noneOils, unspecified water/unspecified kg 4.26E-06 noneBenzenes, alkylated, unspecified water/unspecified kg 4.29E-08 noneAcetone water/unspecified kg 4.55E-10 noneBenzene, 1-methyl-4-(1-methylethyl)-

water/unspecified kg 4.55E-12 none

Arsenic, ion water/unspecified kg 4.64E-08 noneHexanoic acid water/unspecified kg 4.65E-08 noneZinc water/unspecified kg 4.79E-07 noneDocosane water/unspecified kg 4.87E-11 noneCobalt water/unspecified kg 4.90E-09 noneCalcium, ion water/unspecified kg 5.01E-04 noneTetradecane water/unspecified kg 5.07E-09 noneMolybdenum water/unspecified kg 5.08E-09 noneTin water/unspecified kg 5.17E-08 noneFluorene, 1-methyl- water/unspecified kg 5.18E-12 noneSulfur water/unspecified kg 5.27E-07 noneNickel water/unspecified kg 5.40E-08 noneChromium water/unspecified kg 5.62E-07 noneVanadium water/unspecified kg 5.73E-09 noneCopper, ion water/unspecified kg 6.17E-08 nonePhenol, 2,4-dimethyl- water/unspecified kg 6.20E-09 nonem-Xylene water/unspecified kg 6.27E-09 noneCresol, o- water/unspecified kg 6.37E-09 noneDecane water/unspecified kg 6.39E-09 noneCresol, p- water/unspecified kg 6.87E-09 noneBoron water/unspecified kg 6.91E-07 noneDibenzothiophene water/unspecified kg 7.01E-12 noneNaphthalenes, alkylated, unspecified water/unspecified kg 7.04E-10 noneCadmium, ion water/unspecified kg 7.11E-09 nonePhenol water/unspecified kg 7.24E-08 noneRadium-226/kg water/unspecified kg 8.01E-15 noneDibenzofuran water/unspecified kg 8.66E-12 noneMagnesium water/unspecified kg 9.92E-05 none

11

The Stage 4 Sengupta process “Gasoline, at storage terminal – US” uses the ecoinvent process “petrol, low-sulphur,

at regional storage – RER” from ecoinvent2.2 as its foundation. The following changes have been made to

customize the process beyond what was described in Sengupta et al. (2015):

The electricity process was altered to match the US representative process used in the refinery process, with

quantity increased to include the blending of ethanol (Hsu et al. 2010).

Transport distances were changed, presumably to match US rates, with truck transport removed.

Waste disposal and wastewater treatment processes were removed.

Usage of a liquid chemical storage tank was added.

Table 12 contains inputs and outputs from the process.

Table 12 Input Modifications from Sengupta Stage 4

Flow Flow property Unit Amount Uncertainty

Inpu

ts

electricity, at industrial user Energy kWh 0.00756 log-normalliquid storage tank, chemicals, organics Number of items p 8.5E-11 log-normal

tap water, at user Mass kg 0.000689 log-normaltransport, barge tanker Goods transport t*km 0.033474 log-normal

transport, crude oil pipeline, onshore Goods transport t*km 0.46905 log-normaltransport, freight, rail, diesel Goods transport t*km 0.090123 log-normaltransport, transoceanic tanker Goods transport t*km 0.45552 log-normal

The Stage 5 Sengupta process “Gasoline, dispensed at pump – US” was created from scratch. It includes inputs of

fuel, pump electricity, and storage tank usage and outputs of many soil pollutants, but no air or water emissions. The

process captures often overlooked fuel leaks at point of use from storage tanks estimated by (Consulting 2003).

These fuel leaks are broken down into the different chemical species that characterize gasoline. Inputs and outputs

from the process can be found in Table 13.

Table 13 Inputs and Outputs from Sengupta Stage 5

Flow Category Flow property Unit Amount Uncertainty

Inpu

ts

electricity, at industrial user Energy MJ 0.052 undefinedGasoline, at storage terminal Mass kg 1.0015 log-normal

liquid storage tank, chemicals, organics

Number of items p 9.5E-12 log-normal

1,2,3-TRIMETHYL BENZENE soil/industrial Mass kg 0.00996 log-normal1,2,4-TRIMETHYLBENZENE soil/industrial Mass kg 0.04232 log-normal

1,2-DIMETHYL-4-ETHYL BENZENE soil/industrial Mass kg 0.00679 log-normal

1,3,5-TRIMETHYLBENZENE soil/industrial Mass kg 0.01348 log-normal1,3-DIMETHYL-5-ETHYL

BENZENEsoil/industrial Mass kg 0.00547 log-normal

12

Outputs

1-METHYL-3-N-PROPYL BENZENE soil/industrial Mass kg 0.00669 log-normal

2,2,4-Trimethylpentane soil/industrial Mass kg 0.08499 log-normal2,2,5-TRIMETHYL HEXANE soil/industrial Mass kg 0.01068 log-normal

2,2-DIMETHYL BUTANE soil/industrial Mass kg 0.01003 log-normal2,3,4-TRIMETHYL PENTANE soil/industrial Mass kg 0.03559 log-normal

2,3-DIMETHYL BUTANE soil/industrial Mass kg 0.01289 log-normal2,3-DIMETHYL HEXANE soil/industrial Mass kg 0.00997 log-normal2,4-DIMETHYL HEXANE soil/industrial Mass kg 0.01085 log-normal2,4-DIMETHYL PENTANE soil/industrial Mass kg 0.01053 log-normal2,5-DIMETHYL HEXANE soil/industrial Mass kg 0.01034 log-normal

2-METHYL HEPTANE soil/industrial Mass kg 0.0065 log-normal2-METHYL HEXANE soil/industrial Mass kg 0.02497 log-normal

2-Methyl pentane soil/industrial Mass kg 0.03386 log-normal2-Methyl-1-butene soil/industrial Mass kg 0.00572 log-normal2-Methyl-2-butene soil/industrial Mass kg 0.01195 log-normal

3-METHYL HEPTANE soil/industrial Mass kg 0.00724 log-normal3-METHYL HEXANE soil/industrial Mass kg 0.01708 log-normal3-METHYL PENTANE soil/industrial Mass kg 0.02209 log-normal

Arsenic Compounds soil/industrial Mass kg 5E-09 log-normal

Benzene Elementary flows/soil/industrial Mass kg 0.01456 log-normal

Chromium 3+ soil/industrial Mass kg 1.8E-09 log-normalChromium 6+ soil/industrial Mass kg 8.3E-09 log-normal

Cumene Elementary flows/soil/industrial Mass kg 0.00501 log-normal

Cyclohexane Elementary flows/soil/industrial Mass kg 0.00607 log-normal

Cyclopentane soil/industrial Mass kg 0.00501 log-normalEthyl Benzene soil/industrial Mass kg 0.02239 log-normal

Fenpropathrin Elementary flows/soil/industrial Mass kg 0.00507 log-normal

Gasoline, dispensed at pump Mass kg 1 undefined

Heptane Elementary flows/soil/industrial Mass kg 0.01378 log-normal

Hexane Elementary flows/soil/industrial Mass kg 0.02369 log-normal

INDAN soil/industrial Mass kg 0.00539 log-normalISOPENTANE soil/industrial Mass kg 0.0645 log-normal

LEAD(II) soil/industrial Mass kg 6.9E-09 log-normalM-ETHYL TOLUENE soil/industrial Mass kg 0.02612 log-normal

m-Xylene Elementary flows/soil/industrial Mass kg 0.04336 log-normal

METHYLCYCLOHEXANE soil/industrial Mass kg 0.01 log-normalNapthalene soil/industrial Mass kg 0.00501 log-normal

Nickel Compounds soil/industrial Mass kg 7.1E-09 log-normal

13

O-ETHYL TOLUENE soil/industrial Mass kg 0.00973 log-normal

o-Xylene Elementary flows/soil/industrial Mass kg 0.02369 log-normal

Octane Elementary flows/soil/industrial Mass kg 0.00653 log-normal

P-ETHYL TOLUENE soil/industrial Mass kg 0.01216 log-normalP-XYLENE soil/industrial Mass kg 0.019 log-normal

Pentane Elementary flows/soil/industrial Mass kg 0.04081 log-normal

Styrene Elementary flows/soil/industrial Mass kg 0.00501 log-normal

Toluene Elementary flows/soil/industrial Mass kg 0.14251 log-normal

TRANS-2-PENTENE soil/industrial Mass kg 0.00805 log-normalVOC, volatile organic

compounds, unspecified origin soil/industrial Mass kg 0.05348 log-normal

Products by Model

Table 14 shows the different products represented by each model. Because of the differences in scope between the

models, they are not all suited for modeling all petroleum-based products. However, they all overlap in modeling

gasoline, diesel, and kerosene/aviation fuel.

Table 14 Petroleum products represented by the five refinery models

Products Sengupta ecoinvent USLCI GREET NETLGasoline X X X X X

Diesel X X X X XKerosene/Jet Fuel X X X X X

Bitumen X X X XHeavy Fuel Oil X X XLight Fuel Oil X

Naphtha X X XPetroleum Coke X X X XPropane/Butane X X X

Refinery Gas/Electricity X X XSulphur X

Gasoline Blending Components XLubricants X

Other Oils for Feedstock Use XMiscellaneous Petroleum Products X

Special Naphthas XAviation Gasoline X

Waxes XAviation Gasoline Blending Components X

Unspecified Coproduct X

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Brief History of Regulatory Changes

Table 15 Brief list of relevant fuel regulations that may differ between models

Year

Regulation

1998 [FRL–5903–3] Reformulated Gasoline Program, impacts VOCs and Toxics.2000 [AMS–FRL–6516–2] Tier 2 Vehicle Sulfur Program.2001 [AMS–FRL–6924–1] MSAT- gasoline produced/imported in/after 2002 must be at least as clean as

1998-2000. Concerns VOCs and Particulates primarily.2005 [EPA-HQ-OAR-2002-0042] MSAT rule updated with year 2000 data.

[OAR–2003–0019 FRL–8006–5] Correct technical errors, clarify certain provisions, and codify EPA. guidance. Likely to affect VOCs and Toxics.

2006 [EPA–HQ–OAR–2003–0216; EPA–HQ–OAR–2005–0149; FRL–8178–5] Allows different methods of quality assurance. Requires transmix processors to comply with the same regulations as other downstream entities. Slightly adjusts oxygenate requirements.[EPA-HQ-OAR-2005-0170] Removes oxygen requirements in gas.

2007 [EPA–HQ–OAR–2003–0010 FRL–8487–2] Alaska, Hawaii, and Caribbean territories granted ability to modify climate components of Complex Model to calculate emissions.

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