Life cycle assessment of greenhouse gas emissions from plug-in hybrid vehicles: implications for policy

Plug-in hybrid electric vehicles (PHEVs), which use electricity from the grid to power a portion of travel, could play a role in reducing greenhouse gas (GHG) emissions from the transport sector. However, meaningful GHG emissions reductions with PHEVs are conditional on low-carbon electricity sources. We assess life cycle GHG emissions from PHEVs and find that they reduce GHG emissions by 32% compared to conventional vehicles, but have small reductions compared to traditional hybrids. Batteries are an important component of PHEVs, and GHGs associated with lithium-ion battery materials and production account for 2-5% of life cycle emissions from PHEVs. We consider cellulosic ethanol use and various carbon intensities of electricity. The reduced liquid fuel requirements of PHEVs could leverage limited cellulosic ethanol resources. Electricity generation infrastructure is long-lived, and technology decisions within the next decade about electricity supplies in the power sector will affectthe potential for large GHG emissions reductions with PHEVs for several decades.     

Variability and uncertainty in life cycle assessment models for greenhouse gas emissions from Canadian oil sands production

Because of interest in greenhouse gas (GHG) emissions from transportation fuels production, a number of recent life cycle assessment (LCA) studies have calculated GHG emissions from oil sands extraction, upgrading, and refining pathways. The results from these studies vary considerably. This paper reviews factors affecting energy consumption and GHG emissions from oil sands extraction. It then uses publicly available data to analyze the assumptions made in the LCA models to better understand the causes of variability in emissions estimates. It is found that the variation in oil sands GHG estimates is due to a variety of causes. In approximate order of importance, these are scope of modeling and choice of projects analyzed (e.g., specific projects vs industry averages); differences in assumed energy intensities of extraction and upgrading; differences in the fuel mix assumptions; treatment of secondary noncombustion emissions sources, such as venting, flaring, and fugitive emissions; and treatment of ecological emissions sources, such as land-use change-associated emissions. The GHGenius model is recommended as the LCA model that is most congruent with reported industry average data. GHGenius also has the most comprehensive system boundaries. Last, remaining uncertainties and future research needs are discussed.     

Life cycle greenhouse gas emissions of current oil sands technologies: GHOST model development and illustrative application

A life cycle-based model, GHOST (GreenHouse gas emissions of current Oil Sands Technologies), which quantifies emissions associated with production of diluted bitumen and synthetic crude oil (SCO) is developed. GHOST has the potential to analyze a large set of process configurations, is based on confidential oil sands project operating data, and reports ranges of resulting emissions, improvements over prior studies, which primarily included a limited set of indirect activities, utilized theoretical design data, and reported point estimates. GHOST is demonstrated through application to a major oil sands process, steam-assisted gravity drainage (SAGD). The variability in potential performance of SAGD technologies results in wide ranges of "well-to-refinery entrance gate" emissions (comprising direct and indirect emissions): 18-41 g CO(2)eq/MJ SCO, 9-18 g CO(2)eq/MJ dilbit, and 13-24 g CO(2)eq/MJ synbit. The primary contributor to SAGD's emissions is the combustion of natural gas to produce process steam, making a project's steam-to-oil ratio the most critical parameter in determining GHG performance. The demonstration (a) illustrates that a broad range of technology options, operating conditions, and resulting emissions exist among current oil sands operations, even when considering a single extraction technology, and (b) provides guidance about the feasibility of lowering SAGD project emissions.     

Incorporating time-corrected life cycle greenhouse gas emissions in vehicle regulations

Beginning with model year 2012, light-duty vehicles sold in the U.S. are subject to new rules that regulate tailpipe greenhouse gas (GHG) emissions based on grams of CO(2)-equivalent per mile (gCO(2)e/mi). However, improvements in vehicle technology, lower-carbon fuels, and improvements in GHG accounting practices which account for distortions related to emissions timing all contribute to shifting a greater portion of life cycle emissions away from the vehicle use phase and toward the vehicle production phase. This article proposes methods for calculating time-corrected life cycle emissions intensity on a gCO(2)e/mi basis and explores whether regulating only tailpipe CO(2) could lead to an undesirable regulatory outcome, where technologies and vehicle architectures with higher life cycle GHGs are favored over technologies with lower life cycle emissions but with higher tailpipe GHG emissions. Two life cycle GHG assessments for future vehicles are presented in addition to time correction factors for production and end-of-life GHG emissions. Results demonstrate that, based on the vehicle designs considered here, there is a potential for favoring vehicles with higher life cycle emissions if only tailpipe emissions are regulated; moreover, the application of time correction factors amplifies the importance of production emissions and the potential for a perverse outcome.     

Land use greenhouse gas emissions from conventional oil production and oil sands

Debates surrounding the greenhouse gas (GHG) emissions from land use of biofuels production have created a need to quantify the relative land use GHG intensity of fossil fuels. When contrasting land use GHG intensity of fossil fuel and biofuel production, it is the energy yield that greatly distinguishes the two. Although emissions released from land disturbed by fossil fuels can be comparable or higher than biofuels, the energy yield of oil production is typically 2-3 orders of magnitude higher, (0.33-2.6, 0.61-1.2, and 2.2 5.1 PJ/ha) for conventional oil production, oil sands surface mining, and in situ production, respectively). We found that land use contributes small portions of GHGs to life cycle emissions of California crude and in situ oil sands production ( <0.4% or < 0.4 gCO?e/MJ crude refinery feedstock) and small to modest portions for Alberta conventional oil (0.1-4% or 0.1-3.4 gCO?e/MJ) and surface mining of oil sands (0.9-11% or 0.8-10.2 gCO?e/MJ).Our estimates are based on assumptions aggregated over large spatial and temporal scales and assuming 100% reclamation. Values on finer spatial and temporal scales that are relevant to policy targets need to account for site-specific information, the baseline natural and anthropogenic disturbance.     

Effects of nitrogen fertilizer application on greenhouse gas emissions and economics of corn production

Nitrogen fertilizer plays an important role in corn cultivation in terms of both economic and environmental aspects. Nitrogen fertilizer positively affects corn yield and the soil organic carbon level, but it also has negative environmental effects through nitrogen-related emissions from soil (e.g., N20, NOx, NO3(-) leaching, etc.). Effects of nitrogen fertilizer on greenhouse gas emissions associated with corn grain are investigated via life cycle assessment. Ecoefficiency analysis is also used to determine an economically and environmentally optimal nitrogen application rate (NAR). The ecoefficiency index in this study is defined as the ratio of economic return due to nitrogen fertilizer to the greenhouse gas emissions of corn cultivation. Greenhouse gas emissions associated with corn grain decrease as NAR increases at a lower NAR until a minimum greenhouse gas emission level is reached because corn yield and soil organic carbon level increase with NAR. Further increasing NAR after a minimum greenhouse gas emission level raises greenhouse gas emissions associated with corn grain. Increased greenhouse gas emissions of corn grain due to nitrous oxide emissions from soil are much higher than reductions of greenhouse gas emissions of corn grain due to corn yield and changes in soil organic carbon levels at a higher NAR. Thus, there exists an environmentally optimal NAR in terms of greenhouse gas emissions. The trends of the ecoefficiency index are similar to those of economic return to nitrogen and greenhouse gas emissions associated with corn grain. Therefore, an appropriate NAR could enhance profitability as well as reduce greenhouse gas emissions associated with corn grain.     

Uncertainty in life cycle greenhouse gas emissions from United States natural gas end-uses and its effects on policy

Increasing concerns about greenhouse gas (GHG) emissions in the United States have spurred interest in alternate low carbon fuel sources, such as natural gas. Life cycle assessment (LCA) methods can be used to estimate potential emissions reductions through the use of such fuels. Some recent policies have used the results of LCAs to encourage the use of low carbon fuels to meet future energy demands in the U.S., without, however, acknowledging and addressing the uncertainty and variability prevalent in LCA. Natural gas is a particularly interesting fuel since it can be used to meet various energy demands, for example, as a transportation fuel or in power generation. Estimating the magnitudes and likelihoods of achieving emissions reductions from competing end-uses of natural gas using LCA offers one way to examine optimal strategies of natural gas resource allocation, given that its availability is likely to be limited in the future. In this study, the uncertainty in life cycle GHG emissions of natural gas (domestic and imported) consumed in the U.S. was estimated using probabilistic modeling methods. Monte Carlo simulations are performed to obtain sample distributions representing life cycle GHG emissions from the use of 1 MJ of domestic natural gas and imported LNG. Life cycle GHG emissions per energy unit of average natural gas consumed in the U.S were found to range between -8 and 9% of the mean value of 66 g CO(2)e/MJ. The probabilities of achieving emissions reductions by using natural gas for transportation and power generation, as a substitute for incumbent fuels such as gasoline, diesel, and coal were estimated. The use of natural gas for power generation instead of coal was found to have the highest and most likely emissions reductions (almost a 100% probability of achieving reductions of 60 g CO(2)e/MJ of natural gas used), while there is a 10-35% probability of the emissions from natural gas being higher than the incumbent if it were used as a transportation fuel. This likelihood of an increase in GHG emissions is indicative of the potential failure of a climate policy targeting reductions in GHG emissions.     

Life cycle energy and greenhouse gas analysis of a large-scale vertically integrated organic dairy in the United States

In order to manage strategies to curb climate change, systemic benchmarking at a variety of production scales and methods is needed. This study is the first life cycle assessment (LCA) of a large-scale, vertically integrated organic dairy in the United States. Data collected at Aurora Organic Dairy farms and processing facilities were used to build a LCA model for benchmarking the greenhouse gas (GHG) emissions and energy consumption across the entire milk production system, from organic feed production to post-consumer waste disposal. Energy consumption and greenhouse gas emissions for the entire system (averaged over two years of analysis) were 18.3 MJ per liter of packaged fluid milk and 2.3 kg CO(2 )equiv per liter of packaged fluid milk, respectively. Methane emissions from enteric fermentation and manure management account for 27% of total system GHG emissions. Transportation represents 29% of the total system energy use and 15% of the total GHG emissions. Utilization of renewable energy at the farms, processing plant, and major transport legs could lead to a 16% reduction in system energy use and 6.4% less GHG emissions. Sensitivity and uncertainty analysis reveal that alternative meat coproduct allocation methods can lead to a 2.2% and 7.5% increase in overall system energy and GHG, respectively. Feed inventory data source can influence system energy use by -1% to +10% and GHG emission by -4.6% to +9.2%, and uncertainties in diffuse emission factors contribute -13% to +25% to GHG emission.     

Characterization factors for water consumption and greenhouse gas emissions based on freshwater fish species extinction

Human-induced changes in water consumption and global warming are likely to reduce the species richness of freshwater ecosystems. So far, these impacts have not been addressed in the context of life cycle assessment (LCA). Here, we derived characterization factors for water consumption and global warming based on freshwater fish species loss. Calculation of characterization factors for potential freshwater fish losses from water consumption were estimated using a generic species-river discharge curve for 214 global river basins. We also derived characterization factors for potential freshwater fish species losses per unit of greenhouse gas emission. Based on five global climate scenarios, characterization factors for 63 greenhouse gas emissions were calculated. Depending on the river considered, characterization factors for water consumption can differ up to 3 orders of magnitude. Characterization factors for greenhouse gas emissions can vary up to 5 orders of magnitude, depending on the atmospheric residence time and radiative forcing efficiency of greenhouse gas emissions. An emission of 1 ton of CO? is expected to cause the same impact on potential fish species disappearance as the water consumption of 10-1000 m3, depending on the river basin considered. Our results make it possible to compare the impact of water consumption with greenhouse gas emissions.     

Methodology to model the energy and greenhouse gas emissions of electronic software distributions

A new electronic software distribution (ESD) life cycle analysis (LCA) methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative, physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO(2)e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO(2)e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.     

Converting oil shale to liquid fuels: energy inputs and greenhouse gas emissions of the Shell in situ conversion process

Oil shale is a sedimentary rock that contains kerogen, a fossil organic material. Kerogen can be heated to produce oil and gas (retorted). This has traditionally been a CO2-intensive process. In this paper, the Shell in situ conversion process (ICP), which is a novel method of retorting oil shale in place, is analyzed. The ICP utilizes electricity to heat the underground shale over a period of 2 years. Hydrocarbons are produced using conventional oil production techniques, leaving shale oil coke within the formation. The energy inputs and outputs from the ICP, as applied to oil shales of the Green River formation, are modeled. Using these energy inputs, the greenhouse gas (GHG) emissions from the ICP are calculated and are compared to emissions from conventional petroleum. Energy outputs (as refined liquid fuel) are 1.2-1.6 times greater than the total primary energy inputs to the process. In the absence of capturing CO2 generated from electricity produced to fuel the process, well-to-pump GHG emissions are in the range of 30.6-37.1 grams of carbon equivalent per megajoule of liquid fuel produced. These full-fuel-cycle emissions are 21%-47% larger than those from conventionally produced petroleum-based fuels.     

Determining thresholds for mandatory reporting of greenhouse gas emissions

A number of countries are considering implementation of reporting requirements for greenhouse gases. Some reporting systems have been proposed that would require each entity or facility exceeding an annual emissions threshold to report their emissions to a governmental agency. The analysis presented here provides a first approximation of the number of facilities in selected U.S. economic sectors that would report under several different reporting thresholds. Results indicate that thresholds below 10,000 Mg of carbon dioxide equivalent (CO2E) per year may bring in relatively large numbers of facilities while minimally increasing the percentage of reported emissions. None of the reporting thresholds considered in this analysis would account for the majority of greenhouse gas emissions from the U.S. agricultural, transportation, or residential and commercial building sectors. If these sectors, in which large numbers of farms, vehicles, and buildings each emit relatively small amounts of greenhouse gases, are to be included in a reporting framework, additional or alternative approaches to reporting should be considered. Alternative approaches may include creating separate thresholds for individual greenhouse gases instead of using an aggregated CO2E unit, creating separate reporting thresholds for individual sectors, or combining sources of small emissions into a single reporting entity.     

Assessment of fuel-cycle energy use and greenhouse gas emissions for Fischer-Tropsch diesel from coal and cellulosic biomass

This study expands and uses the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model to assess the effects of carbon capture and storage (CCS) technology and cellulosic biomass and coal cofeeding in Fischer-Tropsch (FT) plants on energy use and greenhouse gas (GHG) emissions of FT diesel (FTD). To demonstrate the influence of the coproduct credit methods on FTD life-cycle analysis (LCA) results, two allocation methods based on the energy value and the market revenue of different products and a hybrid method are employed. With the energy-based allocation method, fossil energy use of FTD is less than that of petroleum diesel, and GHG emissions of FTD could be close to zero or even less than zero with CCS when forest residue accounts for 55% or more of the total dry mass input to FTD plants. Without CCS, GHG emissions are reduced to a level equivalent to that from petroleum diesel plants when forest residue accounts for 61% of the total dry mass input. Moreover, we show that coproduct method selection is crucial for LCA results of FTD when a large amount of coproducts is produced.     

Densified biomass can cost-effectively mitigate greenhouse gas emissions and address energy security in thermal applications

Regional supplies of biomass are currently being evaluated as feedstocks in energy applications to meet renewable portfolio (RPS) and low carbon fuel standards. We investigate the life cycle greenhouse gas (GHG) emissions and associated abatement costs resulting from using densified switchgrass for thermal and electrical energy. In contrast to the large and positive abatement costs for using biomass in electricity generation ($149/Mg CO(2)e) due to the low cost of coal and high feedstock and power plant operation costs, abatement costs for replacing fuel oil with biomass in thermal applications are large and negative (-$52 to -$92/Mg CO(2)e), resulting in cost savings. Replacing fuel oil with biomass in thermal applications results in least cost reductions compared to replacing coal in electricity generation, an alternative that has gained attention due to RPS legislation and the centralized production model most often considered in U.S. policy. Our estimates indicate a more than doubling of liquid fuel displacement when switchgrass is substituted for fuel oil as opposed to gasoline, suggesting that, in certain U.S. locations, such as the northeast, densified biomass would help to significantly decarbonize energy supply with regionally sourced feedstock, while also reducing imported oil. On the basis of supply projections from the recently released Billion Ton Report, there will be enough sustainably harvested biomass available in the northeast by 2022 to offset the entirety of heating oil demand in the same region. This will save NE consumers between $2.3 and $3.9 billion annually. Diverting the same resource to electricity generation would cost the region $7.7 billion per year. While there is great need for finding low carbon substitutes for coal power and liquid transportation fuels in the U.S., we argue that in certain regions it makes cost- (and GHG mitigation-) effective sense to phase out liquid heating fuels with locally produced biomass first.     

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.     

木薯燃料乙醇生产过程能量综合利用模式探讨

分析了现有木薯燃料乙醇生产工艺,重点介绍了降低木薯燃料乙醇生产过程中能耗的途径,并提出了木薯燃料乙醇生产过程中能量综合利用模式。     

Sustainability and energy development: influences of greenhouse gas emission reduction options on water use in energy production

Climate change mitigation strategies cannot be evaluated solely in terms of energy cost and greenhouse gas (GHG) mitigation potential. Maintaining GHGs at a "safe" level will require fundamental change in the way we approach energy production, and a number of environmental, economic, and societal factors will come into play. Water is an essential component of energy production, and water resource constraints will limit our options for meeting society's growing demand for energy while also reducing GHG emissions. This study evaluates these potential constraints from a global perspective by revisiting the climate wedges proposal of Pacala and Socolow (Science2004, 305 (5686), 968-972) and evaluating the potential water-use impacts of the wedges associated with energy production. GHG mitigation options that improve energy conversion or use efficiency can simultaneously reduce GHG emissions, lower energy costs, and reduce energy impacts on water resources. Other GHG mitigation options (e.g., carbon capture and sequestration, traditional nuclear, and biofuels from dedicated energy crops) increase water requirements for energy. Achieving energy sustainability requires deployment of alternatives that can reduce GHG emissions, water resource impacts, and energy costs.     

Calculator tool for determining greenhouse gas emissions for biosolids processing and end use

A greenhouse gas (GHG) calculator tool (Biosolids Emissions Assessment Model, BEAM) was developed for the Canadian Council of Ministers of the Environment to allow municipalities to estimate GHG emissions from biosolids management. The tool was developed using data from peer reviewed literature and municipalities. GHG emissions from biosolids processing through final end use/disposal were modeled. Emissions from nine existing programs in Canada were estimated using the model. The program that involved dewatering followed by combustion resulted in the highest GHG emissions (Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). The programs that had digestion followed by land application resulted in the lowest emissions (-26 and -23 Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). Transportation had relatively minor effects on overall emissions. The greatest areas of uncertainty in the model include N(2)O emissions from land application and biosolids processing. The model suggests that targeted use of biosolids and optimizing processes to avoid CH(4) and N(2)O emissions can result in significant GHG savings.