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Uncertainty in Life Cycle Greenhouse Gas Emissions from United States Coal Aranya Venkatesh,*,† Paulina Jaramillo,‡ W. Michael Griffin,‡,§ and H. Scott Matthews†,‡ †

Civil and Environmental Engineering Department, ‡Department of Engineering and Public Policy, and §Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213-3890, United States S Supporting Information *

ABSTRACT: Coal is an abundant energy resource, consumed in the United States chiefly by the power generation sector. Due to potential energy security benefits, it has also been considered as an alternate source for gasoline and diesel production. Life cycle assessment (LCA) studies have previously estimated the greenhouse gas emissions associated with coal combustion as well as upstream activities such as mining and transport, to compare its environmental impact with other fuels. Until recent years, LCA studies predominantly ignored the uncertainty and variability inherent in life cycle assessment. More recent work has estimated the uncertainty in the life cycle inventories of fossil fuels, but the use of these uncertainty ranges to model system-wide impacts has been limited. As shown by previous studies, uncertainty often affects the conclusions of comparative life cycle assessments, especially when differences in average environmental impacts between two competing fuels/products are small. This study builds upon an existing deterministic life cycle framework for coal and develops uncertainty estimates of associated greenhouse gas emissions, with the objective of supporting more robust decision-making in comparative energy systems analyses involving coal. Greenhouse gas emissions from fuel use and methane releases at coal mines, fuel use for coal transport and combustion of coal, based on publicly available data are included in the life cycle framework. Mean life cycle GHG emissions from coal are estimated to be 96 g CO2e/MJ, while the 90% confidence interval ranged between 89 and 106 g CO2e/MJ. Life cycle greenhouse gas emissions from Fischer−Tropsch (FT) coal-based gasoline are stochastically compared to emissions from petroleum-based gasoline. In the base case modeled, emissions from coal-based FT gasoline were found to be higher than emissions from petroleum-based gasoline with a probability of 80%, while they are lower with a probability of 20%. Results suggest that incorporating uncertainty in life cycle estimates is important, especially if these estimates are to be used within policy frameworks.

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INTRODUCTION The U.S. Energy Information Administration (EIA)1 estimates that 20 quadrillion btu (21 EJ) or 1000 million short tons of coal were consumed domestically in 2009, contributing to about 190 million metric tons of carbon dioxide due to combustion and 3.5 million metric tons of methane emissions. Close to 95% of domestic coal was consumed by the electricity sector. Coal has been the subject of many life cycle assessment (LCA) studies that estimate greenhouse gas (GHG) emissions from combustion as well as upstream activities such as mining and transport. These include Jaramillo et al.,2 a National Energy Technology Laboratory (NETL) report,3 Burnham et al.,4 Howarth et al.,5 and a study by the Deutsche Bank Group, Worldwatch Institute, and ICF International.6 Besides being used in the electricity sector, coal is also considered a potential alternate, domestic source for gasoline or diesel production via the Fischer−Tropsch (FT) process, with potential energy security benefits. Previous studies suggest that life cycle GHG emissions from FT-gasoline are about twice as high as emissions from petroleum-based gasoline without carbon capture and storage (CCS), while they are approximately the same if CCS is included.7−9 None of these studies include a detailed quantitative analysis of uncertainty and variability of emissions from all life cycle stages of coal production and use. Burnham et al.4 only characterized the uncertainty of coal mining methane emissions © 2012 American Chemical Society

to update Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model10 life cycle emissions estimates. Uncertainty affects the results of comparative life cycle assessments: for example, see Mullins et al.,11 comparing emissions from gasoline to that from corn- and switchgrass-ethanol, and Venkatesh et al.,12 comparing emissions from gasoline and diesel to those of compressed natural gas. The effects of using LCA results that incorporate uncertainty in climate policies supporting the use of “lower” carbon fuel substitutes (ethanol and compressed natural gas, respectively) were discussed in both studies. In Mullins et al.,11 the life cycle GHG emissions from biobased ethanol were estimated to span almost an order of magnitude, which considerably affected the result of whether ethanol could be shown to have 20% lower GHG emissions than gasoline, as required by the Energy Independence and Security Act (EISA).13 In Venkatesh et al.,12 although uncertainty in life cycle GHG emissions from compressed natural gas was estimated to be 17% of the mean value, this range was significant when compared to the difference in emissions between compressed natural gas and gasoline/diesel in vehicles. Both studies identify a risk of policy failure, which is Received: April 24, 2012 Revised: July 7, 2012 Published: July 9, 2012 4917

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An example of raw data and the corresponding fitted distribution is presented in Figure S1 in the Supporting Information (SI). When data were limited (only two or three data points), either uniform or triangular distributions were chosen, consistent with approaches suggested and/or used in previous studies such as Sonneman et al.,20 Weber,22 and Huijbregts et al.14 Energy UseCoal Production. Total energy used (electricity, coal, distillate fuel, residual fuel oil, natural gas, and gasoline) by the U.S. underground and surface coal mining sectors is reported in the U.S. Census for 1997, 2002, and 2007.23−25 For a few fuels, actual consumption volumes are not reportedonly expenditure data are available. In such cases, fuel prices from the U.S. Energy Information Administration (EIA)26,27 were used to estimate quantities of fuel consumed at coal mines in the U.S. Based on these data, total emissions were estimated for the underground and surface coal mining sectors for 1997, 2002, and 2007 and normalized by annual U.S. coal production quantities from underground and surface mines1 for those years. Previous LCA studies2,3,6 estimating energy use GHG emissions from producing U.S. coal have also used U.S Census data, albeit for single years. GHG emissions associated with energy consumption at coal mines ranged between 11 and 18 kg CO2e/metric ton coal produced in underground mines and between 8 and 14 kg CO2e/ metric ton of coal produced in surface mines. These values were used as the parameters (a, b) of two uniform distributions, weighted by the fractions of coal produced in underground and surface mines in 20101 in a probability mixture model. In other words, the probability distribution of resulting mining fuel use emissions is a convex combination of the probability distribution functions representing underground and surface mining fuel use emissions, weighted by the fractions of coal produced from each type of mine. For more details on such use of probability mixture models, see Venkatesh et al.12,28 A Monte Carlo simulation based on the probability mixture model was used to estimate the GHG emissions from energy use at U.S. coal mines. Note that this may underestimate the total uncertainty and/or variability in fuel use emissions at U.S. coal mines, due to the lack of more disaggregated data. Methane EmissionsCoal Production. Methane emissions due to coal mining contribute to a significant portion of GHG emissions from the coal life cycle.2 The U.S. EPA’s State Inventory and Projection Tool29 reports methane emissions factors of underground and surface mining by state, including emissions from postmining activities and from abandoned underground mines. Underground mining methane emissions range between 4 and 60 m3/metric tons of coal produced and surface mining methane emissions range between 0.3 and 5 m3/metric tons of coal produced across all states. Underground postmining methane emissions range between 0.2 and 4 m3/metric tons of coal and surface postmining methane emissions range between 0.1 and 0.8 m3/metric tons of coal across all states. Abandoned mine methane emissions reported on a yearly basis in the State Inventory and Projection Tool were normalized by annual coal production. In 2009, these emissions ranged between 0 and 2 m3/ metric tons of coal across all states. Although 2009 data were used because it was latest available, abandoned mine methane emissions for the years between 2005 and 08 were compared and found to be reasonably close to 2009 values. The U.S. EPA’s 2011 Inventory of Greenhouse Gas Emissions and Sinks30 suggests that postmining emissions (for both underground and surface mines) may vary between −22% and 25% of the mean value, surface mining emissions may vary ±50% of mean value, and abandoned mine emissions can vary between −27% and 32% of the mean value. No specific ranges were reported for underground mining emissions. However, the Inventory suggests that total uncertainty in methane emissions from coal mining ranges between −13% and 16% and is driven by uncertainty in methane emissions from underground mining. Hence, this uncertainty range was assumed to be applicable to state-level methane emissions factors from underground mining. The ranges were used as the parameters of uniform distributions representing methane emissions factors due to coal mining (surface, underground, postmining activities, and abandoned mines), by state. State-level production quantities of coal from underground and surface

quantified by the probability that life cycle GHG emissions could increase by the introduction of ‘lower’ carbon alternatives through climate policy. Other studies such as Huijbregts et al.,14 Williams et al.,15 Lloyd and Ries16 and Plevin et al.17 also emphasize the importance of including uncertainty in life cycle assessment. There have been increased efforts to better understand and incorporate uncertainty quantitatively in life cycle assessment frameworks, which is especially important when used to inform decisions in the public and private sectors.16 Depending upon the author/study, uncertainty in life cycle inventories has been classified and addressed in different ways. Lloyd and Ries16 and Huijbregts et al.18 categorize of uncertainty and variability in reference to LCA as parameter uncertainty, which refers to the uncertainties in input data; scenario uncertainty, which refers to normative modeling choices; and model uncertainty, due to model structure and relationships. Huijbregts et al.14 add spatial variability, temporal variability, and variability between objects/ sources due to technology differences to this list. In a later study, Huijbregts et al.19 more broadly divided data uncertainty in LCA into (1) data gaps (lack of data/representative data) and (2) data inaccuracy. Williams et al.15 also divided uncertainties as being due to data, cutoff and aggregation errors, and geographic and temporal variability. Depending on the type of uncertainty, various modeling methods have been employed in practice that range from stochastic and scenario modeling (for example, Sonneman et al.20) to fuzzy data sets (for example, Tan et al.21) In this study, a prior life cycle analysis2 is expanded to include the uncertainty in life cycle GHG emissions from average U.S. coal. Life cycle activities modeled include fuel use for coal mining, methane emissions from coal mines, coal transport, and combustion. A case study was developed to highlight the importance of including this uncertainty when analyzing the effects of energy pathways. Using the range of life cycle GHG emissions estimated for coal in this study, the implications of uncertainty were explored in a scenario where coal is used to produce transportation fuels meant to displace petroleum-based fuels. Fischer−Tropsch production of coalbased gasoline and diesel is used as an example to illustrate the effects of uncertainty in LCAs by identifying the risks of an overall increase in GHG emissions. This study predominantly deals with parameter uncertainty (including spatial and temporal variability), through the use of probability distributions to represent model inputs and Monte Carlo simulations to estimate output uncertainty in life cycle GHG emissions of U.S. coal. Scenario uncertainty is briefly examined through the application of two alternate life cycle configurations and the comparison of resulting emissions (1) base case with average coal mining methane emissions and (2) scenario with low coal mining methane emissions. The goal of this effort is to support more robust uncertainty-based energy comparisons involving coal. In addition, a comparison of this study with the Burnham et al.4 study updating the GREET model is presented in the Discussion section.

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METHODS

This study builds upon the coal life cycle framework developed by Jaramillo et al.2 and includes GHG emissions from coal mining, transport, and combustion. Data from 2010 were used wherever possible. The distributions for different life cycle input parameters were selected on the basis of those that best-fit available data, using goodness-of-fit tests, such as the Akaike Information Criterion (AIC). 4918

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mines in 2010 were obtained from U.S. EIA’s Annual Coal Report.31 These quantities were used as fractions in a probability mixture model, to weight the state-level methane emissions from coal mining within a Monte Carlo simulation. For methane, 100-year global warming potentials (GWP) were used. Energy UseCoal Transport. Coal is transported from mines to end-users (mostly electric utilities) via rail, road, waterways, tramways, conveyers, and slurry pipelines. The U.S. EIA Annual Coal Distribution Report for 2010 was used to determine the tonnage of coal transported between states by mode. Next, straight-line interstate distances were estimated using state centroid latitudes and longitudes32 along with the great circle equation. In Elia et al.,33 U.S. states were divided into approximately equal sized hypothetical octants, and their centroids were reported. The average distance between octant centroids in a state and the corresponding state centroid was estimated using the great circle equation and was assumed to be the intrastate distance over which coal is transported. Circuity factors were applied to the straight-line distances between states −1.23 for truck, 1.52 for rail, 1.83 for barges, and 1.1 for pipelines, based on a Congressional Budget Office report.34 The product of the quantities of coal transported between states and the corresponding distances was estimated, in tonmiles. Ranges of emissions factors per ton-mile for rail, truck, and barge modes from Nealer et al.35 (summarizing ranges from other literature) were used. Delucchi36 reports electricity used (250 btuelectric/ton-mile) for coal transport via tramways, conveyers, and slurry pipelines, which was converted to emissions using an appropriate conversion (deterministic) factor for electricity based on Jaramillo et al.2 These emissions factors per ton-mile of coal transported were used along with estimated inter- and intrastate distances, to approximate the total emissions per ton of coal transported between states. These emissions factors were weighted by the fraction of coal transported between corresponding states by different modes in a probability mixture model within a Monte Carlo simulation. The output representing GHG emissions from coal transport in the U.S. was approximated as a Weibull distribution with parameters a = 31, b = 1.39, with a mean value of 30 kg CO2e/ ton coal. This data-fitting is shown graphically in Figure S1 in the SI. Combustion. Emissions from combustion vary depending on coal type. Mean combustion emissions are reported to be 89 g CO2e/MJ (HHV) for bituminous coal and 92 g CO2e/MJ (HHV) for subbituminous and lignite coal by the American Petroleum Institute.37 According to the 2006 IPCC guidelines,38 combustion emissions range between −6 and 7% of the mean for bituminous coal, −4 and 5% for sub-bituminous coal, and −15 and 8% for lignite. Mean combustion emissions and these ranges were used as the parameters of triangular distributions representing combustion emissions from the three coal types. The three types account for almost 100% of total coal consumed in the U.S.31 with bituminous coal contributing 45%, sub-bituminous 47%, and lignite 7%. These fractions were used along with the fitted triangular distributions in a probability mixture model to estimate the range of emissions from the combustion of average U.S. coal.

Figure 1. Output probability distribution of upstream coal greenhouse gas emissions.

for the U.S. are about 12 m3/metric ton, the value reported for Alabama is 60 m3/metric tons, five times higher than the average. Alabama coal contributed to about 3% of all coal in the U.S. from underground mines in 2010. Of the upstream GHG emissions, 17% is due to energy use during coal production, 51% due to methane emissions during coal production, and 32% due to energy use during coal transport on average. Methane emissions ranged between 0.02 and 0.5 g CH4/MJ of coal, with a mean value of 0.15 g CH4/MJ. Statistics for emissions from upstream stages in the coal life cycle are presented in Table 1. For individual distributions representing Table 1. Summary Statistics for Coal Upstream and Life Cycle GHG Emissions life cycle stages energy usecoal production methane emissions coal production energy usecoal transport combustion total coal life cycle

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mean (g CO2e/MJ)

5th percentile (g CO2e/MJ)

0.6

0.4

3.8

0.4

1.3

0.2

91 96

86 89

95th percentile (g CO2e/MJ) 0.7 12 3.2 95 106

emissions from fuel use, mining methane releases, coal transport, as well as the cumulative upstream emissions from the coal life cycle, refer to the SI. Histograms representing methane emissions from underground and surface coal mines are also presented in the SI. Mean life cycle GHG emissions from coal (including combustion) were estimated to be 96 g CO2e/MJ, while the 90% confidence interval ranged between 89 and 106 g CO2e/ MJ (HHV), that is, between −8 and 11% of the mean value, as shown in Table 1. The sample output probability distribution for life cycle emissions is presented in Figure 2 and appears to be trimodal, similar to the coal upstream results. While a mixture model could theoretically be used to fit model results, a (unimodal) shifted log−logistic distribution was fit to the data for convenience. The parameters of the fitted shifted log− logistic distribution are θ = 74, μ = 3.05, σ = 0.14. The fitted distribution is also represented in red in Figure 2. The mean and 90% confidence interval values of the fitted distribution

RESULTS Coal Life Cycle GHG Emissions. The total upstream emissions from U.S. based coal were calculated as the sum of emissions distributions from fuel use and methane emissions at coal mines and from fuel use in coal transport. The mean value of upstream emissions from U.S. coal was 6 g CO2e/MJ (HHV), while the 90% confidence interval ranged between 1.7 and 15 g CO2e/MJ (−70 and 150% of the mean value). The sample output probability distribution for upstream GHG emissions from coal is presented in Figure 1. The overtly bimodal distribution for coal is mainly due to the difference in methane emissions from underground and surface mines. A third mode, at about 50 g CO2e/MJ, results because of the unusually high methane emissions from underground mining reported in the State Inventory Tool29 for Alabama. While the weighted average methane emissions from underground mining 4919

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dominated by the combustion emissions that have lower variability compared to emissions from upstream life cycle stages. On the other hand, combustion emissions are not included in the biofuel life cycle, and the total variability in emissions is due to upstream life cycle stages only. For a graphical depiction of the breakdown of average GHG emissions by life cycle stage, refer to Jaramillo et al. As seen in Figure 3, there is a considerable overlap of the probability distributions representing life cycle GHG emissions

Figure 2. Output probability distribution life cycle coal greenhouse gas emissions (model results and shifted log−logistic distribution to which the data are fit).

were found to match closely with the corresponding statistics of the life cycle model results. Upstream GHG emissions contributed to only 6% of the coal life cycle on average, while this value ranged between 2 and 14%. Coal-Based FT-fuels vs Petroleum-Based Fuels. In Jaramillo et al.,7 gasoline produced via the Fischer−Tropsch process using CCS and a low carbon source of electricity (optimistic case) was estimated to have 4% lower GHG emissions compared to petroleum-based gasoline, when compared deterministically. In this section, life cycle GHG emissions from the two fuel types are compared probabilistically, with base-case model process parameters used in Jaramillo et al.,7 including CCS and a low carbon source of electricity (assumed to have zero GHG emissions). For a coal input of 16 875 metric tons/day and electricity input ranging between 3230 and 4630 MWh/day for 90% CCS, 7 TJ/day of propane, 109 TJ/day of gasoline, and 133 TJ/day of diesel are produced. This is consistent with the base-case modeled in Jaramillo et al. who obtained input and output parameters from previous reports by the Bechtel Corporation39 and the National Energy Technology Laboratory.40 Using these parameters, and allocating total GHG emissions by energy to the products, mean emissions from coal-based FT gasoline amounts to about 96 g CO2e/MJ (LHV), with the 90% confidence interval ranging between 89 and 107 g CO2e/MJ (LHV). Note that although coal life cycle GHG emissions were estimated for 1 MJ HHV of coal, emissions from FT coal-based fuels were estimated on an LHV basis, since transportation fuels are usually compared on an LHV basis. Emissions for petroleumbased gasoline were obtained from Venkatesh et al.28 and are also represented by a probability distribution. The mean value for petroleum-based gasoline is found to be 89 g CO2e/MJ (LHV) while the 90% confidence interval ranges between 85 and 97 g CO2e/MJ (LHV). In comparison, Jaramillo et al. reported FT-coal based life cycle GHG emissions of 88−95 g CO2e/MJ (LHV), and petroleum-based gasoline emissions of 89−92 g CO2e/MJ (LHV). The range of uncertainty in coalbased FT gasoline is comparable to the ranges for other fossil fuels (natural gas and petroleum-based fuels) reported in Venkatesh et al.12,28 but is significantly smaller than the range for corn- and switchgrass-based ethanol reported in Mullins et al.11 This is because emissions from the coal life cycle are

Figure 3. Output probability distributions of petroleum-based and FT coal-based gasoline.

of the two fuel types, although emissions from FT coal-based gasoline is about 7% higher on average. Results for the comparison between petroleum- and FT coal-based diesel are almost identical and are presented in the SI. Similar comparisons where no CCS and average U.S. electricity was assumed (worst case in Jaramillo et al.) are also presented in the SI. In these comparisons, there is no significant overlap of the probability distributions (i.e., the probability that emissions from FT gasoline are lower than petroleum-based gasoline approaches zero). Since uncertainty plays no significant role, these results are not discussed in detail. To determine the extent of overlap of the distributions, a distribution of the difference in life cycle GHG emissions from FT coal- and petroleum-based gasoline was calculated using the distributions of the individual fuels. The cumulative distribution function for the resulting difference is shown in Figure 4. As seen in the figure, emissions from coal-based FT gasoline are higher than emissions from petroleum-based gasoline with probability 80%, while they are lower with a probability of 20% (represented by the dashed lines). Results for the comparison between petroleum- and FT coal-based diesel are almost identical and are presented in the SI. As shown in Table 1, methane emissions from mining contribute significantly to coal life cycle GHG emissions. These emissions are, in turn, dominated by the methane emissions from underground mining, which are higher than emissions from surface mines. If methane emissions from underground mines were reduced, for instance through higher methane recovery at underground coal mines, coal life cycle emissions will consequently decrease. As part of a sensitivity analysis to examine the consequences of such a scenario, methane emissions from all mines were assumed to be reduced to the level of surface mining methane emissions in North Dakota 4920

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Figure 4. Difference in life cycle GHG emissions from FT coal- and petroleum-based gasoline and corresponding probabilities.

Figure 6. Difference in life cycle GHG emissions from FT coal (with low mining methane emissions)- and petroleum-based gasoline and corresponding probabilities.

(0.25 g CO2e/MJ, as shown in Figure S3 in the SI), which is the state with the lowest surface mining methane emissions and significant contribution to national coal production (4% of all surface-mined coal). Note that this scenario is probably unlikely in the near-term due to current cost and regulatory limitations, but it could be possible with more aggressive methane capture programs. Hence, this was modeled to estimate a possible lower bound on emissions from FT fuels. As a result, coal life cycle emissions decreased to an average of 93 g CO2e/MJ, ranging between 87 and 97 g CO2e/MJ. Consequently, life cycle GHG emissions from FT coal-based gasoline are 90 g CO2e/MJ (LHV) on average, less than 1% higher than petroleum-based gasoline. The sample output probability distributions for petroleum- and FT-coal-based (with low methane mining emissions) gasoline are presented in Figure 5. The cumulative distribution function for the resulting difference is shown in Figure 6. Even with the conservative assumption of low methane emissions, there is still a significant probability (of 70%) that life cycle GHG emissions from coal-based FT gasoline are higher than emissions from petroleum-based gasoline, as shown in Figure 6. Results for the corresponding

comparison between coal- and petroleum-based diesel (with low mining methane emissions) are identical, and are presented in the SI.

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DISCUSSION In comparison, Jaramillo et al.2 report an average of 94 g CO2e/ MJ for coal life cycle GHG emissions. The NETL report3 estimates an average value of 95 g CO2e/MJ for bituminous coal life cycle GHG emissions specifically. The study by the Deutsche Bank Group, Worldwatch Institute, and ICF International6 also estimates this value to be 95 g CO2e/MJ for U.S. average coal. Values reported by Burnham et al.4 range between 93 g CO2e/MJ of coal from surface mines and 102 g CO2e/MJ of coal from underground mines (the Burnham study reports emissions based on the lower heating value of coal, which were used to estimate emissions based on the higher heating value of coal and reported here for consistency). All of these estimates in recent literature lie within the 90% confidence interval estimated in this study. A few key differences exist between the Burnham study and this study, outlined as follows. First, their study estimates uncertainty in methane emissions from coal mining only, while the existing GREET model is referred to for all other life cycle activities. Second, while the Burnham study includes some effects of uncertainty in methane mining emissions, their uncertainty estimates are based on national average data, instead of more disaggregated data, such as state-level data used in this study. Third, the Burnham study assumes that either Normal or Weibull distributions best represent input parameters to their life cycle model, whereas this study uses appropriate distributions that best fit available data. Finally, Burnham et al. use the results of their life cycle model to compare emissions from coal and natural gas use in power plants, not repeated in this analysis. As shown in Venkatesh et al.,12 the difference between emissions from coal and natural gas use in power plants is much larger than the uncertainty ranges of emissions from the two fuels and hence is not likely to affect results significantly. However, the uncertainty is likely to play a more important role when it has the same order of magnitude as the difference in emissions between two fuels, as

Figure 5. Output probability distributions of petroleum-based and FT coal-based (with low mining methane emissions) gasoline. 4921

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evident from the analysis comparing emissions from coal-based FT gasoline to petroleum-based gasoline, shown in Figures 4 and 6. Output probability distributions representing life cycle GHG emissions estimated for average U.S. coal, such as those developed in this study, can be incorporated into other life cycle assessment/energy system studies. As an example, the results from this study have been used in two studies modeling the displacement of coal by natural gas in the U.S. electricity sector.41,42 One study41 examined the increased use of natural gas due to low supply prices and showed that life cycle GHG emissions in the Midwest Independent System Operator (MISO) region could reduce by 10% on average. If the effects of uncertainty due to fossil fuel emissions are included this reduction could lie between 7 and 13% (based on the 90% confidence interval). Ranges such as these can be incorporated into policy design frameworks to determine the both the magnitude and risk of increased emissions or other environmental impacts. The results developed in this study can be used in comparative assessments involving coal, to provide potentially more robust conclusions that incorporate the impacts of uncertainty, as also shown in the authors’ previous work.12,28 Life cycle GHG emissions from coal- (assuming a set of specific process parameters) and petroleum-based gasoline were found to be approximately equal. If coal-based FT fuels were introduced in the interest of supporting energy independence in the U.S., there exists a significant probability that overall GHG emissions would increase, even if the mean values were almost equal. This is clear in the best-case scenario where CCS, low carbon electricity and reduced mining methane emissions are assumed. In this scenario, the mean value for FT-fuels is about the same as the mean value of petroleum fuels, but the uncertainty range shows a 70% probability that emissions could also be higher. It is therefore important to account for uncertainty in life cycle estimates, especially if they are to be used in decision-making processes within policy frameworks. It is emphasized that only parameter uncertainty in coal life cycle model inputs is examined in some detail in this study. This is consistent with Lloyd and Ries’16 observation that parameter uncertainty appears to be the most commonly addressed form of uncertainty in life cycle assessment. A limited application of modeling scenario uncertainty has been developed with two alternate scenarios where the sensitivity of most significant source of coal upstream GHG emissions (mining methane emissions) is analyzed. In this example, further variation in results can be observed; that is, depending on the effectiveness on the control of mining methane emissions, the probability of achieving reductions could vary between 20 and 30%. While other sources of uncertainty are not included in this analysis, the scenarios modeled are intended to be illustrative examples to emphasize the effects of uncertainty and provide some approaches to address it quantitatively.

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AUTHOR INFORMATION

Corresponding Author

*Phone: (412) 268-2940. Fax: (412) 268-7813. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This material is based upon work supported by the Energy Foundation. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the Energy Foundation.

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REFERENCES

(1) U.S. Energy Information Administration. Annual Energy Review 2010; http://www.eia.gov/totalenergy/data/annual/pdf/aer.pdf (accessed Mar 6, 2012). (2) Jaramillo, P.; Griffin, W. M.; Matthews, H. S. Comparative LifeCycle Air Emissions of Coal, Domestic Natural Gas, LNG, and SNG for Electricity Generation. Environ. Sci. Technol. 2007, 41, 6290−6296. (3) National Energy Technology Laboratory. Petroleum-Based Fuels Life Cycle Greenhouse Gas Analysis 2005 Baseline Model; National Energy Technology Laboratory: Pittsburgh, PA, 2009. (4) Burnham, A.; Han, J.; Clark, C. E.; Wang, M.; Dunn, J. B.; PalouRivera, I. Life-Cycle Greenhouse Gas Emissions of Shale Gas, Natural Gas, Coal, and Petroleum. Environ. Sci. Technol. 2012, 46, 619−627. (5) Howarth, R. W.; Santoro, R.; Ingraffea, A. Methane and the Greenhouse Gas Footprint of Natural Gas from Shale Formations. Climatic Change 2011, 106, 679−690. (6) Fulton, M.; Mellquist, N.; Kitasei, S.; Bluestein, J. Comparing LifeCycle Greenhouse Gas Emissions from Natural Gas and Coal; Worldwatch Institute/Deustche Bank: Washington, DC, 2011. (7) Jaramillo, P.; Griffin, W. M.; Matthews, H. S. Comparative Analysis of the Production Costs and Life-Cycle GHG Emissions of FT Liquid Fuels from Coal and Natural Gas. Environ. Sci. Technol. 2008, 42, 7559−7565. (8) Xie, X.; Wang, M.; Han, J. Assessment of Fuel-Cycle Energy Use and Greenhouse Gas Emissions for Fischer−Tropsch Diesel from Coal and Cellulosic Biomass. Environ. Sci. Technol. 2011, 45, 3047−53. (9) Katzer, J. The Future of Coal. Massachusetts Institute of Technology: Canbridge, MA, 2007. (10) Wang, M. The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) Model; Argonne National Laboratory: Lemont, IL, 2009. (11) Mullins, K.; Griffin, W. M.; Matthews, H. S. Policy Impacts of Uncertainty in Modeling Life-Cycle Greenhouse Gas Emissions of Biofuels. Environ. Sci. Technol. 2010, 45, 132−138. (12) Venkatesh, A.; Jaramillo, P.; Griffin, W. M.; Matthews, H. S. Uncertainty in Life Cycle Greenhouse Gas Emissions from United States Natural Gas End-Uses and Its Effects on Policy. Environ. Sci. Technol. 2011, 45, 8182−8189. (13) Energy Independence and Security Act of 2007. Public Law 110140; 2007. (14) Huijbregts, M. Application of Uncertainty and Variability in LCA. Int. J. Life Cycle Assess. 1998, 3, 273−280. (15) Williams, E. D.; Weber, C. L.; Hawkins, T. R. Hybrid Framework for Managing Uncertainty in Life Cycle Inventories. J. Ind. Ecol. 2009, 13, 928−944. (16) Lloyd, S. M.; Ries, R. Characterizing, Propagating, and Analyzing Uncertainty in Life-Cycle Assessment. J. Ind. Ecol. 2007, 11, 161−179. (17) Plevin, R. J.; O’Hare, M.; Jones, A. D.; Torn, M. S.; Gibbs, H. K. Greenhouse Gas Emissions from Biofuels’ Indirect Land Use Change Are Uncertain but May Be Much Greater than Previously Estimated. Environ. Sci. Technol. 2010, 44, 8015−21. (18) Huijbregts, M. A. J.; Gilijamse, W.; Ragas, A. M. J.; Reijnders, L. Evaluating Uncertainty in Environmental Life-Cycle Assessment. A

ASSOCIATED CONTENT

S Supporting Information *

Intermediate and supplementary figures pertaining to additional scenarios modeled. This information is available free of charge via the Internet at http://pubs.acs.org/. 4922

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dx.doi.org/10.1021/ef300693x | Energy Fuels 2012, 26, 4917−4923