Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale

Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricity produced by individual gas‐ and oil‐fired power plants across the world. The regression model uses power plant characteristics as predictors, including capacity, age, fuel type (fuel oil or natural gas), and technology type (single or combined cycle) of the plant. The predictive power of the model was relatively high (R² = 81% for predictions). Fuel and technology type were identified as the most important predictors. Estimated emission factors ranged from 0.45 to 1.16 kilograms carbon dioxide equivalents per kilowatt‐hour (kg CO₂‐eq/kWh) and were clearly different between natural gas combined cycle (0.45 to 0.57 kg CO₂‐eq/kWh), natural gas single cycle (0.66 to 0.85 kg CO₂‐eq/kWh), oil combined cycle power plants (0.63 to 0.79 kg CO₂‐eq/kWh), and oil single cycle (0.94 to 1.16 kg CO₂‐eq/kWh). Our results thus indicate that emission data averaged by fuel and technology type can be profitably used to estimate the emissions of individual plants.     

Exploring the Use of Ecological Footprint in Life Cycle Impact Assessment

Ecological footprint (EF) is a metric that estimates human consumption of biological resources and products, along with generation of waste greenhouse gas (GHG) emissions in terms of appropriated productive land. There is an opportunity to better characterize land occupation and effects on the carbon cycle in life cycle assessment (LCA) models using EF concepts. Both LCA and EF may benefit from the merging of approaches commonly used separately by practitioners of these two methods. However, few studies have compared or integrated EF with LCA. The focus of this research was to explore methods for improving the characterization of land occupation within LCA by considering the EF method, either as a complementary tool or impact assessment method. Biofuels provide an interesting subject for application of EF in the LCA context because two of the most important issues surrounding biofuels are land occupation (changes, availability, and so on) and GHG balances, two of the impacts that EF is able to capture. We apply EF to existing fuel LCA land occupation and emissions data and project EF for future scenarios for U.S. transportation fuels. We find that LCA studies can benefit from lessons learned in EF about appropriately modeling productive land occupation and facilitating clear communication of meaningful results, but find limitations to the EF in the LCA context that demand refinement and recommend that EF always be used along with other indicators and metrics in product‐level assessments.     

Sources of variability in greenhouse gas and energy balances for biofuel production: a systematic review

Across the energy sector, alternatives to fossil fuels are being developed, in response to the dual drivers of climate change and energy security. For transport, biofuels have the greatest potential to replace fossil fuels in the short‐to medium term. However, the ecological benefits of biofuels and the role that their deployment can play in mitigating climate change are being called into question. Life Cycle Assessment (LCA) is a widely used approach that enables the energy and greenhouse gas (GHG) balance of biofuel production to be calculated. Concerns have nevertheless been raised that published data show widely varying and sometimes contradictory results. This review describes a systematic review of GHG emissions and energy balance data from 44 LCA studies of first‐ and second‐generation biofuels. The information collated was used to identify the dominant sources of GHG emissions and energy requirements in biofuel production and the key sources of variability in published LCA data. Our analysis revealed three distinct sources of variation: (1) ‘real’ variability in parameters e.g. cultivation; (2) ‘methodological’ variability due to the implementation of the LCA method; and (3) ‘uncertainty’ due to parameters rarely included and poorly quantified. There is global interest in developing a sustainability assessment protocol for biofuels. Confidence in the results of such an assessment can only be assured if these areas of uncertainty and variability are addressed. A more defined methodology is necessary in order to allow effective and accurate comparison of results. It is also essential that areas of uncertainty such as impacts on soil carbon stocks and fluxes are included in LCA assessments, and that further research is conducted to enable a robust calculation of impacts under different land‐use change scenarios. Without the inclusion of these parameters, we cannot be certain that biofuels are really delivering GHG savings compared with fossil fuels.     

Life cycle analysis of biochemical cellulosic ethanol under multiple scenarios

Cellulosic ethanol is widely believed to offer substantial environmental advantages over petroleum fuels and grain‐based ethanol, particularly in reducing greenhouse gas emissions from transportation. The environmental impacts of biofuels are largely caused by precombustion activities, feedstock production and conversion facility operations. Life cycle analysis (LCA) is required to understand these impacts. This article describes a field‐to‐blending terminal LCA of cellulosic ethanol produced by biochemical conversion (hydrolysis and fermentation) using corn stover or switchgrass as feedstock. This LCA develops unique models for most elements of the biofuel production process and assigns environmental impact to different phases of production. More than 30 scenarios are evaluated, reflecting a range of feedstock, technology and scale options for near‐term and future facilities. Cellulosic ethanol, as modeled here, has the potential to significantly reduce greenhouse gas (GHG) emissions compared to petroleum‐based liquid transportation fuels, though substantial uncertainty exists. Most of the conservative scenarios estimate GHG emissions of approximately 45–60 g carbon dioxide equivalent per MJ of delivered fuel (g CO₂e MJ^?1) without credit for coproducts, and 20–30 g CO₂e MJ^?1 when coproducts are considered. Under most scenarios, feedstock production, grinding and transport dominate the total GHG footprint. The most optimistic scenarios include sequestration of carbon in soil and have GHG emissions below zero g CO₂e MJ^?1, while the most pessimistic have life‐cycle GHG emissions higher than petroleum gasoline. Soil carbon changes are the greatest source of uncertainty, dominating all other sources of GHG emissions at the upper bound of their uncertainty. Many LCAs of biofuels are narrowly constrained to GHG emissions and energy; however, these narrow assessments may miss important environmental impacts. To ensure a more holistic assessment of environmental performance, a complete life cycle inventory, with over 1100 tracked material and energy flows for each scenario is provided in the online supplementary material for this article.     

Life Cycle Greenhouse Gas Emissions Reduction From Rigid Thermal Insulation Use in Buildings

Thermal insulation is a strategic product for reducing energy consumption and related greenhouse gas (GHG) emissions from the building sector. This study examines from a life cycle perspective the changes in GHG emissions resulting from the use of two rigid thermal insulation products manufactured and installed from 1971 to 2025. GHG emissions related to insulation production and fugitive releases of blowing agents are modeled and compared with GHG savings from reduced heating loads in North America, Europe, and Asia. Implementation of alternative blowing agents has greatly improved the carbon dioxide 100‐year equivalent (CO₂‐eq) emission performance of thermal insulation. The net average CO₂‐eq savings to emissions ratio for current extruded polystyrene (XPS) and polyisocyanurate (PIR) insulation studied was 48:1, with a broad range from 3 to 1,800. Older insulation products manufactured with chlorofluorocarbons (CFCs) can result in net cumulative GHG emissions. Reduction of CO₂‐eq emissions from buildings is governed by complex interactions between insulation thickness and placement, climate, fuel type, and heating system efficiencies. A series of charts mapping both emissions payback and net savings demonstrate the interactions between these factors and provide a basis for specific policy recommendations to guide effective insulation investments and placement.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

Dry Matter Losses and Methane Emissions During Wood Chip Storage: the Impact on Full Life Cycle Greenhouse Gas Savings of Short Rotation Coppice Willow for Heat

A life cycle assessment (LCA) approach was used to examine the greenhouse gas (GHG) emissions and energy balance of short rotation coppice (SRC) willow for heat production. The modelled supply chain includes cutting multiplication, site establishment, maintenance, harvesting, storage, transport and combustion. The relative impacts of dry matter losses and methane emissions from chip storage were examined from a LCA perspective, comparing the GHG emissions from the SRC supply chain with those of natural gas for heat generation. The results show that SRC generally provides very high GHG emission savings of over 90 %. The LCA model estimates that a 1, 10 and 20 % loss of dry matter during storage causes a 1, 6 and 11 % increase in GHG emissions per MWh. The GHG emission results are extremely sensitive to emissions of methane from the wood chip stack: If 1 % of the carbon within the stack undergoes anaerobic decomposition to methane, then the GHG emissions per MWh are tripled. There are some uncertainties in the LCA results, regarding the true formation of methane in wood chip stacks, non-CO₂ emissions from combustion, N₂O emissions from leaf fall and the extent of carbon sequestered under the crop, and these all contribute a large proportion of the life cycle GHG emissions from cultivation of the crop.     

Beyond Global Warming Potential: A Comparative Application of Climate Impact Metrics for the Life Cycle Assessment of Coal and Natural Gas Based Electricity

In the ongoing debate about the climate benefits of fuel switching from coal to natural gas for power generation, the metrics used to model climate impacts may be important. In this article, we evaluate the life cycle greenhouse gas emissions of coal and natural gas used in new, advanced power plants using a broad set of available climate metrics in order to test for the robustness of results. Climate metrics included in the article are global warming potential, global temperature change potential, technology warming potential, and cumulative radiative forcing. We also used the Model for the Assessment of Greenhouse‐gas Induced Climate Change (MAGICC) climate‐change model to validate the results. We find that all climate metrics suggest a natural gas combined cycle plant offers life cycle climate benefits over 100 years compared to a pulverized coal plant, even if the life cycle methane leakage rate for natural gas reaches 5%. Over shorter time frames (i.e., 20 years), plants using natural gas with a 4% leakage rate have similar climate impacts as those using coal, but are no worse than coal. If carbon capture and sequestration becomes available for both types of power plants, natural gas still offers climate benefits over coal as long as the life cycle methane leakage rate remains below 2%. These results are consistent across climate metrics and the MAGICC model over a 100‐year time frame. Although it is not clear whether any of these metrics are better than the others, the choice of metric can inform decisions based on different societal values. For example, whereas annual temperature change reported may be a more relevant metric to evaluate the human health effects of increased heat, the cumulative temperature change may be more relevant to evaluate climate impacts, such as sea‐level rise, that will result from the cumulative warming.     

The biofuel potential of municipal solid waste

The world in the 21st century is facing a dual crisis of increasing waste and global climate change. Substituting fossil fuels with waste biomass‐derived cellulosic ethanol is a promising strategy to simultaneously meet part of our energy needs, mitigate greenhouse gas (GHG) emissions, and manage municipal solid waste (MSW). However, the global potential of MSW as an energy source is as yet unquantified. Here, we report increasing trends of MSW generation, and waste biomass‐derived cellulosic ethanol potentials in relation to socio‐economic development across 173 countries, and show that globally, up to 82.9 billion litres of waste paper‐derived cellulosic ethanol can be produced worldwide, replacing 5.36% of gasoline consumption, with accompanying GHG emissions savings of between 29.2% and 86.1%.     

Regional variations in life cycle greenhouse gas emissions of canola‐derived jet fuel produced in western Canada

This study investigates the life cycle GHG emissions of jet fuel produced via the hydroprocessed esters and fatty acids (HEFA) pathway from canola grown in western Canada, with a focus on characterizing regional influences on emissions. We examine the effects of geographic variations in soil type, agricultural inputs, farming practices, and direct land use changes on life cycle GHG emissions. We utilize GREET 2016 but replace default feedstock production inputs with geographically representative data for canola production across eight western Canadian regions (representing 99% of Canada's canola production) and replace the default conversion process with data from a novel process model previously developed in ASPEN in our research group wherein oil extraction is integrated with the HEFA‐based fuel production process. Although canola production inputs and yields vary across the regions, resulting life cycle GHG emissions are similar if effects of land use and land management changes (LMC) are not included; 44–48 g CO₂e/MJ for the eight regions (45%–50% reduction compared to petroleum jet fuel). Results are considerably more variable, 16–58 g CO₂e/MJ, when including effects of land use and LMC directly related to conversion of lands from other uses to canola production (34%–82% reduction compared to petroleum jet fuel). We establish the main sources of emissions in the life cycle of canola jet fuel (N‐fertilizer and related emissions, fuel production), identify that substantially higher emissions may occur when using feedstock sourced from regions where conversion of forested land to cropland had occurred, and identify benefits of less intense tillage practices and increased use of summerfallow land. The methods and findings are relevant in jurisdictions internationally that are incorporating GHG emissions reductions from aviation fuels in a low carbon fuel market or legislating carbon intensity reduction requirements.     

Bioethanol Potentials and Life-Cycle Assessments of Biofuel Feedstocks

A wide range of bioenergy crops has been proposed as feedstocks that can serve as renewable and ecologically sound substitutes to fossil fuels. In the United States, corn grain (Zea mays) ethanol is the primary biofuel, with over 49 billion liters produced in 2010. Along with the Energy Independence and Security Act (EISA) of 2007 mandate, concerns about competition for food, land availability, nutrient and water requirements, energy balances, and greenhouse gas (GHG) emissions have prompted researchers to investigate other potential feedstocks. These include second-generation lignocellulosic feedstock and third-generation biodiesel from microalgae and cyanobacteria. However, each feedstock option has associated benefits and consequences for its use. One technique used to evaluate the energy efficiency of bioenergy production systems is the life-cycle assessment (LCA), where system inputs and outputs are computed in terms of either C or energy equivalents to assess the net gains in energy or C offsets. This article collates and synthesizes information about feedstock production options. Results show a wide range of calculated energy and GHG balances, even for the same feedstock species. Discrepancies in LCA and uncertainty thus make direct comparisons difficult and prevent a consensus in determining feedstock suitability. Recommendations must be based upon LCA model assumptions, crop species, cultivation methods, management practices, and energy conversion choices. Currently lignocellulosic feedstock, while a better alternative than corn grain, is not a long-term viable energy source. New feedstocks and technologies are necessary if bioenergy is to be C-neutral and efficient in energy production and land use. Although C fluxes are considered in LCA, one important ecosystem C stock that has previously been left out of many LCA models is changes to soil organic carbon (SOC). Future research, developments, and priorities are discussed for options to produce low C fuel sources and stabilize the climate.     

Recycle,Bury, or Burn Wood Waste Biomass?: LCA Answer Depends on Carbon Accounting,Emissions Controls,Displaced Fuels,and Impact Costs

This study extends existing life cycle assessment (LCA) literature by assessing seven environmental burdens and an overall monetized environmental score for eight recycle, bury, or burn options to manage clean wood wastes generated at construction and demolition activity sites. The study assesses direct environmental impacts along with substitution effects from displacing fossil fuels and managed forest wood sourcing activities. Follow‐on effects on forest carbon stocks, land use, and fuel markets are not assessed. Sensitivity analysis addresses landfill carbon storage and biodegradation rates, atmospheric emissions controls, displaced fuel types, and two alternative carbon accounting methods commonly used for waste management LCAs. Base‐case carbon accounting considers emissions and uptakes of all biogenic and fossil carbon compounds, including biogenic carbon dioxide. Base‐case results show that recycling options (recycling into reconstituted wood products or into wood pulp for papermaking) rank better than all burning or burying options for overall monetized score as well as for climate impacts, except that wood substitution for coal in industrial boilers is slightly better than recycling for the climate. Wood substitution for natural gas boiler fuel has the highest environmental impacts. Sensitivity analysis shows the overall monetized score rankings for recycling options to be robust except for the carbon accounting method, for which all options are highly sensitive. Under one of the alternative methods, wood substitution for coal boiler fuel and landfill options with high methane capture efficiency are the best for the overall score; recycling options are next to the worst. Under the other accounting alternative, wood substitution for coal and waste‐to‐energy are the best, followed by recycling options.     

Life cycle assessment of biofuels: Energy and greenhouse gas balances

The promotion of biofuels as energy for transportation in the industrialized countries is mainly driven by the perspective of oil depletion, the concerns about energy security and global warming. However due to sustainability constraints, biofuels will replace only 10 to 15% of fossil liquid fuels in the transport sector. Several governments have defined a minimum target of GHG emissions reduction for those biofuels that will be eligible to public incentives, for example a 35% emissions reduction in case of biofuels in Members States of the European Union. This article points out the significant biases in estimating GHG balances of biofuels stemming from modelling choices about system definition and boundaries, functional unit, reference systems and allocation methods. The extent to which these choices influence the results is investigated. After performing a comparison and constructive criticism of various modelling choices, the LCA of wheat-to-bioethanol is used as an illustrative case where bioethanol is blended with gasoline at various percentages (E5, E10 and E85). The performance of these substitution options is evaluated as well. The results show a large difference in the reduction of the GHG emissions with a high sensitivity to the following factors: the method used to allocate the impacts between the co-products, the type of reference systems, the choice of the functional unit and the type of blend. The authors come out with some recommendations for basing the estimation of energy and GHG balances of biofuels on principles such as transparency, consistency and accuracy.     

Contribution of N2O to the greenhouse gas balance of first-generation biofuels

In this study, we analyze the impact of fertilizer‐ and manure‐induced N₂O emissions due to energy crop production on the reduction of greenhouse gas (GHG) emissions when conventional transportation fuels are replaced by first‐generation biofuels (also taking account of other GHG emissions during the entire life cycle). We calculate the nitrous oxide (N₂O) emissions by applying a statistical model that uses spatial data on climate and soil. For the land use that is assumed to be replaced by energy crop production (the ‘reference land‐use system’), we explore a variety of options, the most important of which are cropland for food production, grassland, and natural vegetation. Calculations are also done in the case that emissions due to energy crop production are fully additional and thus no reference is considered. The results are combined with data on other emissions due to biofuels production that are derived from existing studies, resulting in total GHG emission reduction potentials for major biofuels compared with conventional fuels. The results show that N₂O emissions can have an important impact on the overall GHG balance of biofuels, though there are large uncertainties. The most important ones are those in the statistical model and the GHG emissions not related to land use. Ethanol produced from sugar cane and sugar beet are relatively robust GHG savers: these biofuels change the GHG emissions by −103% to −60% (sugar cane) and −58% to −17% (sugar beet), compared with conventional transportation fuels and depending on the reference land‐use system that is considered. The use of diesel from palm fruit also results in a relatively constant and substantial change of the GHG emissions by −75% to −39%. For corn and wheat ethanol, the figures are −38% to 11% and −107% to 53%, respectively. Rapeseed diesel changes the GHG emissions by −81% to 72% and soybean diesel by −111% to 44%. Optimized crop management, which involves the use of state‐of‐the‐art agricultural technologies combined with an optimized fertilization regime and the use of nitrification inhibitors, can reduce N₂O emissions substantially and change the GHG emissions by up to −135 percent points (pp) compared with conventional management. However, the uncertainties in the statistical N₂O emission model and in the data on non‐land‐use GHG emissions due to biofuels production are large; they can change the GHG emission reduction by between −152 and 87 pp.     

Improvements in Life Cycle Energy Efficiency and Greenhouse Gas Emissions of Corn-Ethanol

Corn-ethanol production is expanding rapidly with the adoption of improved technologies to increase energy efficiency and profitability in crop production, ethanol conversion, and coproduct use. Life cycle assessment can evaluate the impact of these changes on environmental performance metrics. To this end, we analyzed the life cycles of corn-ethanol systems accounting for the majority of U.S. capacity to estimate greenhouse gas (GHG) emissions and energy efficiencies on the basis of updated values for crop management and yields, biorefinery operation, and coproduct utilization. Direct-effect GHG emissions were estimated to be equivalent to a 48% to 59% reduction compared to gasoline, a twofold to threefold greater reduction than reported in previous studies. Ethanol-to-petroleum output/input ratios ranged from 10:1 to 13:1 but could be increased to 19:1 if farmers adopted high-yield progressive crop and soil management practices. An advanced closed-loop biorefinery with anaerobic digestion reduced GHG emissions by 67% and increased the net energy ratio to 2.2, from 1.5 to 1.8 for the most common systems. Such improved technologies have the potential to move corn-ethanol closer to the hypothetical performance of cellulosic biofuels. Likewise, the larger GHG reductions estimated in this study allow a greater buffer for inclusion of indirect-effect land-use change emissions while still meeting regulatory GHG reduction targets. These results suggest that corn-ethanol systems have substantially greater potential to mitigate GHG emissions and reduce dependence on imported petroleum for transportation fuels than reported previously.     

Evaluation and Allocation of Greenhouse Gas Reductions in Industrial Symbiosis

Industrial symbiosis (IS) exchanges have been recognized to reduce greenhouse gas (GHG) emission, though methods for quantification of GHG emissions in IS exchanges are varied, and no standardized methods are available. This article proposes a practical approach to quantify total and allocated GHG emissions from IS exchanges by integrating the GHG protocol and life cycle assessment. The proposed method expands the system boundaries to include all IS companies, and the functional flow is set to be the sum of the main products. The total impact of a company is allocated to the main product. Three by‐product impact allocation methods of cutoff, avoidance, and 50/50 are proposed, and the total and distributed impacts of the IS systems in an industrial park are theoretically derived. The proposed method was tested to quantify GHG reduction in a real IS exchange developed between Korea Zinc (a zinc smelter) and Hankook Paper (a paper mill company) in the Ulsan Eco‐Industrial Park initiative. The total reduction of GHG emissions in this IS exchange, 60,522 tonnes of carbon dioxide per year, was the same in the GHG protocol, whereas GHG distribution between two companies depended on the allocation method. Given that the reduction of GHG emissions from IS exchanges is the product of the collaboration of giving companies and receiving companies, the 50/50 allocation method is best from an equivalent‐responsibility and benefit‐sharing perspective. However, this study suggests a more practical implementation approach based on a flexible and negotiable method of allocating the total GHG reduction between stakeholders.     

Uncertainty and Variability in Product Carbon Footprinting

Recent years have seen increasing interest in life cycle greenhouse gas emissions accounting, also known as carbon footprinting, due to drivers such as transportation fuels policy and climate‐related eco‐labels, sometimes called carbon labels. However, it remains unclear whether applications of greenhouse gas accounting, such as carbon labels, are supportable given the level of precision that is possible with current methodology and data. The goal of this work is to further the understanding of quantitative uncertainty assessment in carbon footprinting through a case study of a rackmount electronic server. Production phase uncertainty was found to be moderate (±15%), though with a high likelihood of being significantly underestimated given the limitations in available data for assessing uncertainty associated with temporal variability and technological specificity. Individual components or subassemblies showed varying levels of uncertainty due to differences in parameter uncertainty (i.e., agreement between data sets) and variability between production or use regions. The use phase displayed a considerably higher uncertainty (±50%) than production due to uncertainty in the useful lifetime of the server, variability in electricity mixes in different market regions, and use profile uncertainty. Overall model uncertainty was found to be ±35% for the whole life cycle, a substantial amount given that the method is already being used to set policy and make comparative environmental product declarations. Future work should continue to combine the increasing volume of available data to ensure consistency and maximize the credibility of the methods of life cycle assessment (LCA) and carbon footprinting. However, for some energy‐using products it may make more sense to increase focus on energy efficiency and use phase emissions reductions rather than attempting to quantify and reduce the uncertainty of the relatively small production phase.     

Fuel Economy and Greenhouse Gas Emissions Labeling for Plug‐In Hybrid Vehicles from a Life Cycle Perspective

Fuel economy has been an effective indicator of vehicle greenhouse gas (GHG) emissions for conventional gasoline‐powered vehicles due to the strong relationship between fuel economy and vehicle life cycle emissions. However, fuel economy is not as accurate an indicator of vehicle GHG emissions for plug‐in hybrid (PHEVs) and pure battery electric vehicles (EVs). Current vehicle labeling efforts by the U.S. Environmental Protection Agency (EPA) and Department of Transportation have been focused on providing energy and environmental information to consumers based on U.S. national average data. This article explores the effects of variations in regional grids and regional daily vehicle miles traveled (VMT) on the total vehicle life cycle energy and GHG emissions of electrified vehicles and compare these results with information reported on the label and on the EPA's fuel economy Web site. The model results suggest that only 25% of the life cycle emissions from a representative PHEV are reflected on current vehicle labeling. The results show great variation in total vehicle life cycle emissions due to regional grid differences, including an approximately 100 gram per mile life cycle GHG emissions difference between the lowest and highest electric grid regions and up to a 100% difference between the state‐specific emission values within the same electric grid regions. Unexpectedly, for two regional grids the life cycle GHG emissions were higher in electric mode than in gasoline mode. We recommend that labels include stronger language on their deficiencies and provide ranges for GHG emissions from vehicle charging in regional electricity grids to better inform consumers.     

Life Cycle Greenhouse Gas Emissions of Electricity Generated from Conventionally Produced Natural Gas

This research provides a systematic review and harmonization of the life cycle assessment (LCA) literature of electricity generated from conventionally produced natural gas. We focus on estimates of greenhouse gases (GHGs) emitted in the life cycle of electricity generation from natural gas‐fired combustion turbine (NGCT) and combined‐cycle (NGCC) systems. The smaller set of LCAs of liquefied natural gas power systems and natural gas plants with carbon capture and storage were also collected, but analyzed to a lesser extent. A meta‐analytical process we term “harmonization” was employed to align several system boundaries and technical performance parameters to better allow for cross‐study comparisons, with the aim of clarifying central tendency and reducing variability in estimates of life cycle GHG emissions. Of over 250 references identified, 42 passed screens for technological relevance and study quality, providing a total of 69 estimates for NGCT and NGCC. Harmonization increased the median estimates in each category as a result of several factors not typically considered in the previous research, including the regular clearing of liquids from a well, and consolidated the interquartile range for NGCC to 420 to 480 grams of carbon dioxide equivalent per kilowatt‐hour (g CO₂‐eq/kWh) and for NGCT to 570 to 750 g CO₂‐eq/kWh, with medians of 450 and 670 CO₂‐eq/kWh, respectively. Harmonization of thermal efficiency had the largest effect in reducing variability; methane leakage rate is likely similarly influential, but was unharmonized in this assessment as a result of the significant current uncertainties in its estimation, an area that is justifiably receiving significant research attention.     

Patterns in CH4 and CO2 concentrations across boreal rivers: Major drivers and implications for fluvial greenhouse emissions under climate change scenarios

It is now widely accepted that boreal rivers and streams are regionally significant sources of carbon dioxide (CO₂), yet their role as methane (CH₄) emitters, as well as the sensitivity of these greenhouse gas (GHG) emissions to climate change, are still largely undefined. In this study, we explore the large‐scale patterns of fluvial CO₂ and CH₄ partial pressure (pCO₂, pCH₄) and gas exchange (k) relative to a set of key, climate‐sensitive river variables across 46 streams and rivers in two distinct boreal landscapes of Northern Québec. We use the resulting models to determine the direction and magnitude of C‐gas emissions from these boreal fluvial networks under scenarios of climate change. River pCO₂ and pCH₄ were positively correlated, although the latter was two orders of magnitude more variable. We provide evidence that in‐stream metabolism strongly influences the dynamics of surface water pCO₂ and pCH₄, but whereas pCO₂ is not influenced by temperature in the surveyed streams and rivers, pCH₄ appears to be strongly temperature‐dependent. The major predictors of ambient gas concentrations and exchange were water temperature, velocity, and DOC, and the resulting models indicate that total GHG emissions (C‐CO₂ equivalent) from the entire network may increase between by 13 to 68% under plausible scenarios of climate change over the next 50 years. These predicted increases in fluvial GHG emissions are mostly driven by a steep increase in the contribution of CH₄ (from 36 to over 50% of total CO₂‐equivalents). The current role of boreal fluvial networks as major landscape sources of C is thus likely to expand, mainly driven by large increases in fluvial CH₄ emissions.