Uncertainty in the Life Cycle Greenhouse Gas Emissions from U.S. Production of Three Biobased Polymer Families.

Interest in biobased products has been motivated, in part, by the claim that these products have lower life cycle greenhouse gas (GHG) emissions than their fossil counterparts. This study investigates GHG emissions from U.S. production of three important biobased polymer families: polylactic acid (PLA), polyhydroxybutyrate (PHB) and bioethylene-based plastics. The model incorporates uncertainty into the life cycle emission estimates using Monte Carlo simulation. Results present a range of scenarios for feedstock choice (corn or switchgrass), treatment of coproducts, data sources, end of life assumptions, and displaced fossil polymer. Switchgrass pathways generally have lower emissions than corn pathways, and can even generate negative cradle-to-gate emissions if unfermented residues are used to coproduce energy. PHB (from either feedstock) is unlikely to have lower emissions than fossil polymers once end of life emissions are included. PLA generally has the lowest emissions when compared to high emission fossil polymers, such as polystyrene (mean GHG savings up to 1.4 kg CO2e/kg corn PLA and 2.9 kg CO2e/kg switchgrass PLA). In contrast, bioethylene is likely to achieve the greater emission reduction for ethylene intensive polymers, like polyethylene (mean GHG savings up to 0.60 kg CO2e/kg corn polyethylene and 3.4 kg CO2e/kg switchgrass polyethylene).

Life cycle assessment of lignocellulosic ethanol: a review of key factors and methods affecting calculated GHG emissions and energy use.

Lignocellulosic ethanol has potential for lower life cycle greenhouse gas emissions compared to gasoline and conventional grain-based ethanol. Ethanol production 'pathways' need to meet economic and environmental goals. Numerous life cycle assessments of lignocellulosic ethanol have been published over the last 15 years, but gaps remain in understanding life cycle performance due to insufficient data, and model and methodological issues. We highlight key aspects of these issues, drawing on literature and a case study of corn stover ethanol. Challenges include the complexity of feedstock/ecosystems and market-mediated aspects and the short history of commercial lignocellulosic ethanol facilities, which collectively have led to uncertainty in GHG emissions estimates, and to debates on LCA methods and the role of uncertainty in decision making.

Life cycle greenhouse gas emissions from U.S. liquefied natural gas exports: implications for end uses.

This study analyzes how incremental U.S. liquefied natural gas (LNG) exports affect global greenhouse gas (GHG) emissions. We find that exported U.S. LNG has mean precombustion emissions of 37 g CO2-equiv/MJ when regasified in Europe and Asia. Shipping emissions of LNG exported from U.S. ports to Asian and European markets account for only 3.5-5.5% of precombustion life cycle emissions, hence shipping distance is not a major driver of GHGs. A scenario-based analysis addressing how potential end uses (electricity and industrial heating) and displacement of existing fuels (coal and Russian natural gas) affect GHG emissions shows the mean emissions for electricity generation using U.S. exported LNG were 655 g CO2-equiv/kWh (with a 90% confidence interval of 562-770), an 11% increase over U.S. natural gas electricity generation. Mean emissions from industrial heating were 104 g CO2-equiv/MJ (90% CI: 87-123). By displacing coal, LNG saves 550 g CO2-equiv per kWh of electricity and 20 g per MJ of heat. LNG saves GHGs under upstream fugitive emissions rates up to 9% and 5% for electricity and heating, respectively. GHG reductions were found if Russian pipeline natural gas was displaced for electricity and heating use regardless of GWP, as long as U.S. fugitive emission rates remain below the estimated 5-7% rate of Russian gas. However, from a country specific carbon accounting perspective, there is an imbalance in accrued social costs and benefits. Assuming a mean social cost of carbon of $49/metric ton, mean global savings from U.S. LNG displacement of coal for electricity generation are $1.50 per thousand cubic feet (Mcf) of gaseous natural gas exported as LNG ($.028/kWh). Conversely, the U.S. carbon cost of exporting the LNG is $1.80/Mcf ($.013/kWh), or $0.50-$5.50/Mcf across the range of potential discount rates. This spatial shift in embodied carbon emissions is important to consider in national interest estimates for LNG exports.

Changing the renewable fuel standard to a renewable material standard: bioethylene case study.

The narrow scope of the U.S. renewable fuel standard (RFS2) is a missed opportunity to spur a wider range of biomass use. This is especially relevant as RFS2 targets are being missed due to demand-side limitations for ethanol consumption. This paper examines the greenhouse gas (GHG) implications of a more flexible policy based on RFS2, which includes credits for chemical use of bioethanol (to produce bioethylene). A Monte Carlo simulation is employed to estimate the life-cycle GHG emissions of conventional low-density polyethylene (LDPE), made from natural gas derived ethane (mean: 1.8 kg CO2e/kg LDPE). The life-cycle GHG emissions from bioethanol and bio-LDPE are examined for three biomass feedstocks: U.S. corn (mean: 97g CO2e/MJ and 2.6 kg CO2e/kg LDPE), U.S. switchgrass (mean: -18g CO2e/MJ and -2.9 kg CO2e/kg LDPE), and Brazilian sugar cane (mean: 33g CO2e/MJ and -1.3 kg CO2e/kg LDPE); bioproduct and fossil-product emissions are compared. Results suggest that neither corn product (bioethanol or bio-LDPE) can meet regulatory GHG targets, while switchgrass and sugar cane ethanol and bio-LDPE likely do. For U.S. production, bioethanol achieves slightly greater GHG reductions than bio-LDPE. For imported Brazilian products, bio-LDPE achieves greater GHG reductions than bioethanol. An expanded policy that includes bio-LDPE provides added flexibility without compromising GHG targets.

Implications of near-term coal power plant retirement for SO2 and NOX and life cycle GHG emissions.

Regulations monitoring SO(2), NO(X), mercury, and other metal emissions in the U.S. will likely result in coal plant retirement in the near-term. Life cycle assessment studies have previously estimated the environmental benefits of displacing coal with natural gas for electricity generation, by comparing systems that consist of individual natural gas and coal power plants. However, such system comparisons may not be appropriate to analyze impacts of coal plant retirement in existing power fleets. To meet this limitation, simplified economic dispatch models for PJM, MISO, and ERCOT regions are developed in this study to examine changes in regional power plant dispatch that occur when coal power plants are retired. These models estimate the order in which existing power plants are dispatched to meet electricity demand based on short-run marginal costs, with cheaper plants being dispatched first. Five scenarios of coal plant retirement are considered: retiring top CO(2) emitters, top NO(X) emitters, top SO(2) emitters, small and inefficient plants, and old and inefficient plants. Changes in fuel use, life cycle greenhouse gas emissions (including uncertainty), and SO(2) and NO(X) emissions are estimated. Life cycle GHG emissions were found to decrease by less than 4% in almost all scenarios modeled. In addition, changes in marginal damage costs due to SO(2), and NO(X) emissions are estimated using the county level marginal damage costs reported in the Air Pollution Emissions Experiments and Policy (APEEP) model, which are a proxy for measuring regional impacts of SO(2) and NO(X) emissions. Results suggest that location specific parameters should be considered within environmental policy frameworks targeting coal plant retirement, to account for regional variability in the benefits of reducing the impact of SO(2) and NO(X) emissions.

Inventory development and input-output model of U.S. land use: relating land in production to consumption.

As populations and demands for land-intensive products, e.g., cattle and biofuels, increase the need to understand the relationship between land use and consumption grows. This paper develops a production-based inventory of land use (i.e., the land used to produce goods) in the U.S. With this inventory an input-output analysis is used to create a consumption-based inventory of land use. This allows for exploration of links between land used in production to the consumption of particular goods. For example, it is possible to estimate the amount of cropland embodied in processed foods or healthcare services. As would be expected, agricultural and forestry industries are the largest users of land in the production-based inventory. Similarly, we find that processed foods and forest products are the largest users of land in the consumption-based inventory. Somewhat less expectedly this work finds that the majority of manufacturing and service industries, not typically associated with land use, require substantial amounts of land to produce output due to the purchase of food and other agricultural and wood-based products in the supply chain. The quantitative land use results of this analysis could be integrated with qualitative metrics such as weighting schemes designed to reflect environmental impact or life cycle impact assessment methods.

Uncertainty analysis of life cycle greenhouse gas emissions from petroleum-based fuels and impacts on low carbon fuel policies.

The climate change impacts of U.S. petroleum-based fuels consumption have contributed to the development of legislation supporting the introduction of low carbon alternatives, such as biofuels. However, the potential greenhouse gas (GHG) emissions reductions estimated for these policies using life cycle assessment methods are predominantly based on deterministic approaches that do not account for any uncertainty in outcomes. This may lead to unreliable and expensive decision making. In this study, the uncertainty in life cycle GHG emissions associated with petroleum-based fuels consumed in the U.S. is determined using a process-based framework and statistical modeling methods. Probability distributions fitted to available data were used to represent uncertain parameters in the life cycle model. Where data were not readily available, a partial least-squares (PLS) regression model based on existing data was developed. This was used in conjunction with probability mixture models to select appropriate distributions for specific life cycle stages. Finally, a Monte Carlo simulation was performed to generate sample output distributions. As an example of results from using these methods, the uncertainty range in life cycle GHG emissions from gasoline was shown to be 13%-higher than the typical 10% minimum emissions reductions targets specified by low carbon fuel policies.

Policy implications of uncertainty in modeled life-cycle greenhouse gas emissions of biofuels.

Biofuels have received legislative support recently in California's Low-Carbon Fuel Standard and the Federal Energy Independence and Security Act. Both present new fuel types, but neither provides methodological guidelines for dealing with the inherent uncertainty in evaluating their potential life-cycle greenhouse gas emissions. Emissions reductions are based on point estimates only. This work demonstrates the use of Monte Carlo simulation to estimate life-cycle emissions distributions from ethanol and butanol from corn or switchgrass. Life-cycle emissions distributions for each feedstock and fuel pairing modeled span an order of magnitude or more. Using a streamlined life-cycle assessment, corn ethanol emissions range from 50 to 250 g CO(2)e/MJ, for example, and each feedstock-fuel pathway studied shows some probability of greater emissions than a distribution for gasoline. Potential GHG emissions reductions from displacing fossil fuels with biofuels are difficult to forecast given this high degree of uncertainty in life-cycle emissions. This uncertainty is driven by the importance and uncertainty of indirect land use change emissions. Incorporating uncertainty in the decision making process can illuminate the risks of policy failure (e.g., increased emissions), and a calculated risk of failure due to uncertainty can be used to inform more appropriate reduction targets in future biofuel policies.

Economic and environmental transportation effects of large-scale ethanol production and distribution in the United States.

The combination of current and planned 2007 U.S. ethanol production capacity is 50 billion L/yr, one-third of the Energy Independence and Security Act of 2007 (EISA) target of 136 billion L of biofuels by 2022. In this study, we evaluate transportation impacts and infrastructure requirements for the use of E85 (85% ethanol, 15% gasoline) in light-duty vehicles using a combination of corn and cellulosic ethanol. Ethanol distribution is modeled using a linear optimization model. Estimated average delivered ethanol costs, in 2005 dollars, range from $0.29 to $0.62 per liter ($1.3-2.8 per gallon), depending on transportation distance and mode. Emissions from ethanol transport estimated in this work are up to 2 times those in previous ethanol LCA studies and thus lead to larger total life cycle effects. Long-distance transport of ethanol to the end user can negate ethanol's potential economic and environmental benefits relative to gasoline. To reduce costs, we recommend regional concentration of E85 blends for future ethanol production and use.

Comparative analysis of the production costs and life-cycle GHG emissions of FT liquid fuels from coal and natural gas.

Liquid transportation fuels derived from coal and natural gas could helpthe United States reduce its dependence on petroleum. The fuels could be produced domestically or imported from fossil fuel-rich countries. The goal of this paper is to determine the life-cycle GHG emissions of coal- and natural gas-based Fischer-Tropsch (FT) liquids, as well as to compare production costs. The results show that the use of coal- or natural gas-based FT liquids will likely lead to significant increases in greenhouse gas (GHG) emissions compared to petroleum-based fuels. In a best-case scenario, coal- or natural gas-based FT-liquids have emissions only comparable to petroleum-based fuels. In addition, the economic advantages of gas-to-liquid (GTL) fuels are not obvious: there is a narrow range of petroleum and natural gas prices at which GTL fuels would be competitive with petroleum-based fuels. CTLfuels are generally cheaper than petroleum-based fuels. However, recent reports suggest there is uncertainty about the availability of economically viable coal resources in the United States. If the U.S. has a goal of increasing its energy security, and at the same time significantly reducing its GHG emissions, neither CTL nor GTL consumption seem a reasonable path to follow.

National-level infrastructure and economic effects of switchgrass cofiring with coal in existing power plants for carbon mitigation.

We update a previously presented Linear Programming (LP) methodology for estimating state level costs for reducing CO2 emissions from existing coal-fired power plants by cofiring switchgrass, a biomass energy crop, and coal. This paper presents national level results of applying the methodology to the entire portion of the United States in which switchgrass could be grown without irrigation. We present incremental switchgrass and coal cofiring carbon cost of mitigation curves along with a presentation of regionally specific cofiring economics and policy issues. The results show that cofiring 189 million dry short tons of switchgrass with coal in the existing U.S. coal-fired electricity generation fleet can mitigate approximately 256 million short tons of carbon-dioxide (CO2) per year, representing a 9% reduction of 2005 electricity sector CO2 emissions. Total marginal costs, including capital, labor, feedstock, and transportation, range from $20 to $86/ton CO2 mitigated,with average costs ranging from $20 to $45/ton. If some existing power plants upgrade to boilers designed for combusting switchgrass, an additional 54 million tons of switchgrass can be cofired. In this case, total marginal costs range from $26 to $100/ton CO2 mitigated, with average costs ranging from $20 to $60/ton. Costs for states east of the Mississippi River are largely unaffected by boiler replacement; Atlantic seaboard states represent the lowest cofiring cost of carbon mitigation. The central plains states west of the Mississippi River are most affected by the boiler replacement option and, in general, go from one of the lowest cofiring cost of carbon mitigation regions to the highest. We explain the variation in transportation expenses and highlight regional cost of mitigation variations as transportation overwhelms other cofiring costs.

State-level infrastructure and economic effects of switchgrass cofiring with coal in existing power plants for carbon mitigation.

This paper presents a linear programming (LP) methodology for estimating the cost of reducing a state's coal-fired power plant carbon dioxide emissions by cofiring switchgrass and coal. LP modeling allows interplay between regionally specific switchgrass production forecasts, coal plant locations, and individual coal plant historic performance data to determine an allocation of switchgrass minimizing cost or maximizing carbon reduction. The LP methodology is applied to two states, Pennsylvania (PA) and Iowa (IA), and results are presented with a discussion of modeling assumptions, techniques, and carbon mitigation policy implications. The LP methodology estimates that, in PA, 4.9 million tons of CO2/year could be mitigated at an average cost of less than $34/ton of CO2 and that, in IA, 7 million tons of CO2/year could be mitigated at an average Cost of Mitigation of $27/ton of CO2. Because the factors determining the cofiring costs vary so much between the two states, results suggest that cofiring costs will also vary considerably between different U.S. regions. A national level analysis could suggest a lowest-cost cofiring region. This paper presents techniques and assumptions that can simplify biomass energy policy analysis with little effect on analysis conclusions.

Comparative life-cycle air emissions of coal, domestic natural gas, LNG, and SNG for electricity generation.

The U.S. Department of Energy (DOE) estimates that in the coming decades the United States' natural gas (NG) demand for electricity generation will increase. Estimates also suggest that NG supply will increasingly come from imported liquefied natural gas (LNG). Additional supplies of NG could come domestically from the production of synthetic natural gas (SNG) via coal gasification-methanation. The objective of this study is to compare greenhouse gas (GHG), SOx, and NOx life-cycle emissions of electricity generated with NG/LNG/SNG and coal. This life-cycle comparison of air emissions from different fuels can help us better understand the advantages and disadvantages of using coal versus globally sourced NG for electricity generation. Our estimates suggest that with the current fleet of power plants, a mix of domestic NG, LNG, and SNG would have lower GHG emissions than coal. If advanced technologies with carbon capture and sequestration (CCS) are used, however, coal and a mix of domestic NG, LNG, and SNG would have very similar life-cycle GHG emissions. For SOx and NOx we find there are significant emissions in the upstream stages of the NG/ LNG life-cycles, which contribute to a larger range in SOx and NOx emissions for NG/LNG than for coal and SNG.