Using monte carlo simulation in life cycle assessment for electric and internal combustion vehicles

1 Background

The U.S. Government has encouraged shifting from internal combustion engine vehicles (ICEVs) to alternatively fueled vehicles such as electric vehicles (EVs) for three primary reasons: reducing oil dependence, reducing greenhouse gas emissions, and reducing Clean Air Act criteria pollutant emissions. In comparing these vehicles, there is uncertainty and variability in emission factors and performance variables, which cause wide variation in reported outputs.

2 Objectives

A model was developed to demonstrate the use of Monte Carlo simulation to predict life cycle emissions and energy consumption differences between the ICEV versus the EV on a per kilometer (km) traveled basis. Three EV technologies are considered: lead-acid, nickel-cadmium, and nickel metal hydride batteries.

3 Methods

Variables were identified to build life cycle inventories between the EVs and ICEV. Distributions were selected for each of the variables and input to Monte Carlo Simulation soft-ware called Crystal Ball 2000®.

4 Results and Discussion

All three EV options reduce U.S. oil dependence by shifting to domestic coal. The life cycle energy consumption per kilometer (km) driven for the EVs is comparable to the ICEV; however, there is wide variation in predicted energy values. The model predicts that all three EV technologies will likely increase oxides of sulfur and nitrogen as well as particulate matter emissions on a per km driven basis. The model shows a high probability that volatile organic compounds and carbon monoxide emissions are reduced with the use of EVs. Lead emissions are also predicted to increase for lead-acid battery EVs. The EV will not reduce greenhouse gas emissions substantially and may even increase them based on the current U.S. reliance on coal for electricity generation. The EV may benefit public health by relocating air pollutants from urban centers, where traffic is concentrated, to rural areas where electricity generation and mining generally occur. The use of Monte Carlo simulation in life cycle analysis is demonstrated to be an effective tool to provide further insight on the likelihood of emission outputs and energy consumption.     

Environmental impacts of hybrid and electric vehicles—a review

Purpose

A literature review is undertaken to understand how well existing studies of the environmental impacts of hybrid and electric vehicles (EV) address the full life cycle of these technologies. Results of studies are synthesized to compare the global warming potential (GWP) of different EV and internal combustion engine vehicle (ICEV) options. Other impacts are compared; however, data availability limits the extent to which this could be accomplished.

Method

We define what should be included in a complete, state-of-the-art environmental assessment of hybrid and electric vehicles considering components and life cycle stages, emission categories, impact categories, and resource use and compare the content of 51 environmental assessments of hybrid and electric vehicles to our definition. Impact assessment results associated with full life cycle inventories (LCI) are compared for GWP as well as emissions of other pollutants. GWP results by life cycle stage and key parameters are extracted and used to perform a meta-analysis quantifying the impacts of vehicle options.

Results

Few studies provide a full LCI for EVs together with assessment of multiple impacts. Research has focused on well to wheel studies comparing fossil fuel and electricity use as the use phase has been seen to dominate the life cycle of vehicles. Only very recently have studies begun to better address production impacts. Apart from batteries, very few studies provide transparent LCIs of other key EV drivetrain components. Estimates of EV energy use in the literature span a wide range, 0.10?C0.24?kWh/km. Similarly, battery and vehicle lifetime plays an important role in results, yet lifetime assumptions range between 150,000?C300,000?km. CO₂ and GWP are the most frequently reported results. Compiled results suggest the GWP of EVs powered by coal electricity falls between small and large conventional vehicles while EVs powered by natural gas or low-carbon energy sources perform better than the most efficient ICEVs. EV results in regions dependant on coal electricity demonstrated a trend toward increased SO _x emissions compared to fuel use by ICEVs.

Conclusions

Moving forward research should focus on providing consensus around a transparent inventory for production of electric vehicles, appropriate electricity grid mix assumptions, the implications of EV adoption on the existing grid, and means of comparing vehicle on the basis of common driving and charging patterns. Although EVs appear to demonstrate decreases in GWP compared to conventional ICEVs, high efficiency ICEVs and grid-independent hybrid electric vehicles perform better than EVs using coal-fired electricity.     

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.     

Well-to-wheel GHG emissions and mitigation potential from light-duty vehicles in Macau

Purpose

The rapid growth of vehicle sales and usage has highlighted the need for greenhouse gas (GHG) emission reduction in Macau, a special administrative region (SAR) of China. As the most primary vehicle type, light-duty vehicles (LDV, including light-duty gasoline vehicles (LDGVs) and light-duty diesel vehicles (LDDVs)) play a key role in promoting the GHG reduction and development of green transportation system in Macau.

Methods

This study, on the basis of real-world tested and statistical data, firstly performed a streamlined life-cycle assessment (SLCA) on LDVs, to evaluate the potential GHG emissions and reduction through shifting to hybrid electric vehicles (HEVs) and electric vehicles (EVs).

Results and discussion

The results show that the mean GHG emissions from the LDGVs, LDDVs, and HEVs per 100 km were 25.16, 20.30, and 15.00 kg CO₂ eq, respectively. Under the current electricity mix in Macau, EVs with the emissions of 12.39 kg CO₂ eq/100 km can achieve a significant GHG emission reduction of LDVs in Macau. The total GHG emissions from LDVs increased from 124.99 to 247.82 thousand metric tons over the periods 2001–2014, with a 5.42% annual growth rate. A scenario analysis indicated that the development of HEVs and EVs—especially EVs—has the potential to control the GHG emissions from LDVs. Under the electricity mix of natural gas (NG) and solar energy (SE), the GHG emissions from EVs would drop by about 22 and 28%, respectively, by 2030.

Conclusions

This study develops a useful approach to evaluate the potential GHG emissions and its reduction strategies in Macau. All the obtained results could be useful for decision makers, providing robust support for drawing up an appropriate plan for improving green transportation systems in Macau.

     

Comparative Environmental Life Cycle Assessment of Conventional and Electric Vehicles

Electric vehicles (EVs) coupled with low‐carbon electricity sources offer the potential for reducing greenhouse gas emissions and exposure to tailpipe emissions from personal transportation. In considering these benefits, it is important to address concerns of problem‐shifting. In addition, while many studies have focused on the use phase in comparing transportation options, vehicle production is also significant when comparing conventional and EVs. We develop and provide a transparent life cycle inventory of conventional and electric vehicles and apply our inventory to assess conventional and EVs over a range of impact categories. We find that EVs powered by the present European electricity mix offer a 10% to 24% decrease in global warming potential (GWP) relative to conventional diesel or gasoline vehicles assuming lifetimes of 150,000 km. However, EVs exhibit the potential for significant increases in human toxicity, freshwater eco‐toxicity, freshwater eutrophication, and metal depletion impacts, largely emanating from the vehicle supply chain. Results are sensitive to assumptions regarding electricity source, use phase energy consumption, vehicle lifetime, and battery replacement schedules. Because production impacts are more significant for EVs than conventional vehicles, assuming a vehicle lifetime of 200,000 km exaggerates the GWP benefits of EVs to 27% to 29% relative to gasoline vehicles or 17% to 20% relative to diesel. An assumption of 100,000 km decreases the benefit of EVs to 9% to 14% with respect to gasoline vehicles and results in impacts indistinguishable from those of a diesel vehicle. Improving the environmental profile of EVs requires engagement around reducing vehicle production supply chain impacts and promoting clean electricity sources in decision making regarding electricity infrastructure.     

Evaluation of a Regional Approach to Standards for Plug‐in Battery Electric Vehicles in Future Light‐Duty Vehicle Greenhouse Gas Regulations

Representing the greenhouse gas (GHG) emissions attributable to plug‐in electric vehicles (PEV) in vehicle GHG emissions regulations is complex because of spatial and temporal variation in fueling sources and vehicle use. Previous work has shown that the environmental performance of PEVs significantly varies depending on the characteristics of the electricity grid and how the vehicle is driven. This article evaluates the U.S. Environmental Protection Agency's (EPA's) GHG emissions accounting methodology in current and future standards for new electrified vehicles. The current approach employed by the EPA in their 2017–2025 model year light‐duty vehicle GHG regulation is compared with an accounting mechanism where the actual regional sales of PEVs, and the regional electricity emission factor in the year sold, are used to determine vehicle compliance value. Changes to the electricity grid over time and regional vehicle sales are included in the modeling efforts. A projection of a future GHG regulation past the 2017–2025 rule is used to observe the effect of such a regional regulation. The results showed that the complexity involved in tracking and accounting for regional PEV sales will not dramatically increase the effectiveness of the regulations to capture PEV electricity‐related GHG emissions in the absence of a major policy shift. A discussion of the feasibility and effectiveness of a regional standard for PEVs, and notable examples of region‐specific regulations instated in past energy policies, is also addressed.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part I: Analytical Framework and Baseline Results

This first article of a two‐article series describes a framework and life cycle–based model for typical almond orchard production systems for California, where more than 80% of commercial almonds on the world market are produced. The comprehensive, multiyear, life cycle–based model includes orchard establishment and removal; field operations and inputs; emissions from orchard soils; and transport and utilization of co‐products. These processes are analyzed to yield a life cycle inventory of energy use, greenhouse gas (GHG) emissions, criteria air pollutants, and direct water use from field to factory gate. Results show that 1 kilogram (kg) of raw almonds and associated co‐products of hulls, shells, and woody biomass require 35 megajoules (MJ) of energy and result in 1.6 kg carbon dioxide equivalent (CO₂‐eq) of GHG emissions. Nitrogen fertilizer and irrigation water are the dominant causes of both energy use and GHG emissions. Co‐product credits play an important role in estimating the life cycle environmental impacts attributable to almonds alone; using displacement methods results in net energy and emissions of 29 MJ and 0.9 kg CO₂‐eq/kg. The largest sources of credits are from orchard biomass and shells used in electricity generation, which are modeled as displacing average California electricity. Using economic allocation methods produces significantly different results; 1 kg of almonds is responsible for 33 MJ of energy and 1.5 kg CO₂‐eq emissions. Uncertainty analysis of important parameters and assumptions, as well as temporary carbon storage in orchard trees and soils, are explored in the second article of this two‐part article series.     

Integrated environmental and economic assessment of current and future fuel cell vehicles

Purpose

Light-duty vehicles contribute considerably to global greenhouse gas emissions. Fuel cell vehicles (FCVs) may play a key role in mitigating these emissions without facing the same limitations in range and refueling time as battery electric vehicles (BEVs). In this study, we assess the environmental impacts and costs of a polymer electrolyte membrane fuel cell system (FCS) for use in light-duty FCVs and integrate these results into a comparative evaluation between FCVs, BEVs, and internal combustion engine vehicles (ICEVs).

Methods

We conduct a detailed life cycle assessment (LCA) and cost assessment for the current state of the technology and two future scenarios for technological development. We compile a detailed and consistent inventory for the FCS by systematically disassembling and integrating information found in cost studies. For the vehicle-level comparison, we use models to ensure that vehicle size, performance, and fuel consumption are unbiased between vehicle types and consistent with the scenarios for technological development.

Results and discussion

Our results show that FCVs can decrease life cycle greenhouse gas emissions by 50 % compared to gasoline ICEVs if hydrogen is produced from renewable electricity, thus exhibiting similar emission levels as BEVs that are charged with the same electricity mix. If hydrogen is produced by natural gas reforming, FCVs are found to offer no greenhouse gas reductions, along with higher impacts in several other environmental impact categories. A major contributor to these impacts is the FCS, in particular the platinum in the catalyst and the carbon fiber in the hydrogen tank. The large amount of carbon fiber used in the tank was also the reason why we found that FCVs may not become fully cost competitive with ICEVs or BEVs, even when substantial technological development and mass production of all components is assumed.

Conclusions

We conclude that FCVs only lead to lower greenhouse gas emissions than ICEVs if their fuel is sourced from renewable energy, as is the case with BEVs. FCVs are an attractive alternative to ICEVs in terms of vehicle performance criteria such as range and refueling time. However, the technological challenges associated with reducing other environmental impacts and costs of FCVs seem to be as large, if not larger, than those associated with the capacity and costs of batteries for BEVs—even when not taking into account the efforts required to build a hydrogen infrastructure network for road transportation.

     

Increasing Precision in Greenhouse Gas Accounting Using Real‐Time Emission Factors

For many companies, the greenhouse gas (GHG) emissions associated with their purchased and consumed electricity form one of the largest contributions to the GHG emissions that result from their activities. Currently, hourly variations in electricity grid emissions are not considered by standard GHG accounting protocols, which apply a national grid emission factor (EF), potentially resulting in erred estimates for the GHG emissions. In this study, a method is developed that calculates GHG emissions based on real‐time data, and it is shown that the use of hourly electricity grid EFs can significantly improve the accuracy of the GHG emissions that are attributed to the purchased and consumed electricity of a company. A model analysis for the electricity delivered to the Spanish grid in 2012 reveals that, for companies operating during the day, GHG emissions calculated by the real‐time method are estimated to be up to 5% higher (and in some special cases up to 9% higher) than the emissions calculated by the conventional method in which a national grid EF is applied, whereas for companies operating during nightly hours, GHG emissions are estimated to be as low as 3% below the GHG emissions determined by the conventional method. A significant error can therefore occur in the organizational carbon footprint (CF) of a company and, consequently, also in the product CF. It is recommended that hourly EFs be developed for other countries and power grids.     

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.     

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.     

Economic Assessment of Greenhouse Gas Emissions Reduction by Vehicle Lightweighting Using Aluminum and High‐Strength Steel

The life cycle greenhouse gas (GHG) reduction benefits of vehicle lightweighting (LW) were evaluated in a companion article. This article provides an economic assessment of vehicle LW with aluminum and high‐strength steel. Relevant cost information taken from the literature is synthesized, compiled, and formed into estimates of GHG reduction costs through LW. GHG emissions associated with vehicle LW scenarios between 6% and 23% are analyzed alongside vehicle life cycle costs to achieve these LW levels. We use this information to estimate the cost to remove GHG emissions per metric ton by LW, and we further calculate the difference between added manufacturing cost and fuel cost savings from LW. The results show greater GHG savings derived from greater LW and added manufacturing costs as expected. The associated production costs are, however, disproportionately higher than the fuel cost savings associated with higher LW options. A sensitivity analysis of different vehicle classes confirms that vehicle LW is more cost‐effective for larger vehicles. Also, the cost of GHG emissions reductions through lightweighting is compared with alternative GHG emissions reduction technologies for passenger vehicles, such as diesel, hybrid, and plug‐in hybrid electric powertrains. The results find intensive LW to be a competitive and complementary approach relative to the technological alternatives within the automotive industry but more costly than GHG mitigation strategies available to other industries.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part II: Uncertainty Analysis through Sensitivity Analysis and Scenario Testing

This is the second part of a two‐article series examining California almond production. The part I article describes development of the analytical framework and life cycle–based model and presents typical energy use and greenhouse gas (GHG) emissions for California almonds. This part II article builds on this by exploring uncertainty in the life cycle model through sensitivity and scenario analysis, and by examining temporary carbon storage in the orchard. Sensitivity analysis shows life cycle GHG emissions are most affected by biomass fate and utilization, followed by nitrous oxide emissions rates from orchard soils. Model sensitivity for net energy consumption is highest for irrigation system parameters, followed by biomass fate and utilization. Scenario analysis shows utilization of orchard biomass for electricity production has the greatest potential effect, assuming displacement methods are used for co‐product allocation. Results of the scenario analysis show that 1 kilogram (kg) of almond kernel and associated co‐products are estimated to cause between ?3.12 to 2.67 kg carbon dioxide equivalent (CO₂‐eq) emissions and consume between 27.6 to 52.5 megajoules (MJ) of energy. Co‐product displacement credits lead to avoided emissions of between ?1.33 to 2.45 kg CO₂‐eq and between ?0.08 to 13.7 MJ of avoided energy use, leading to net results of ?1.39 to 3.99 kg CO₂‐eq and 15.3 to 52.6 MJ per kg kernel (net results are calculated by subtracting co‐product credits from the results for almonds and co‐products). Temporary carbon storage in orchard biomass and soils is accounted for by using alternative global warming characterization factors and leads to a 14% to 18% reduction in CO₂‐eq emissions. Future studies of orchards and other perennial cropping systems should likely consider temporary carbon storage.     

Carbon Footprint Assessment of a Paperback Book

This study presents the carbon footprint of a paperback book for which the cover and inside papers were produced in the United States and printed in Canada. The choice of paper mills for both cover and page papers was based on criteria such as percentage of recycled content in the pulp mix, transport distances (pulp mill to paper mill, paper mill to print), and technologies. The cradle‐to‐gate assessment of greenhouse gas (GHG) emissions follows recognized guidelines for carbon footprint assessment. The results show that the production of 400,000 books, mainly distributed in North America, would generate 1,084 tonnes carbon dioxide equivalent (CO₂‐eq), or 2.71 kilograms (kg) CO₂‐eq per book. The impact of using deinked market pulp (DMP) is shown here to be detrimental, accounting for 54% of total GHG emissions and being 32% higher than reference virgin Kraft pulp. This supports findings that DMP mill GHG emissions strongly correlate with the carbon intensity of the power grid supplying the pulp mill and that virgin Kraft mills that reuse wood residue and black liquor to produce heat and electricity can achieve lower GHG emissions per tonne of pulp produced. Although contrary to common thinking, this is consistent with the Paper Task Force 2002 conclusion for office paper (the closest paper grade to writing paper or fine paper) (EDF 2002a). To get a cradle‐to‐grave perspective, three different end‐of‐life (EOL) scenarios were analyzed, all of which included a harvested wood product (HWP) carbon storage benefit for 25 years. The GHG offset concept within the context of the book editor's “carbon‐neutral” paper claims is also discussed.     

Life Cycle Inventory Analysis of the Wood Pallet Repair Process in the United States

This study developed gate‐to‐gate life cycle inventory (LCI) data for the repair of 48 by 40 inch (1,219 by 1,016 millimeter [mm]) stringer‐class wood pallets in the United States. Data were collected from seven wood pallet repair facilities. Approximately 1.98 FBM (foot, board measure) (4.67E‐03 cubic meters) of lumber were used for repairing each 48 by 40 inch (1,219 by 1,016 mm) stringer‐class wood pallet, the majority (97%) recovered from damaged pallets received by the pallet repair facilities. Repair equipment powered by electricity made the largest contribution to greenhouse gas (GHG) emissions. Steel nails used for the pallet repair had the largest contribution to GHG emissions among the material inputs, while use of recovered lumber yielded the largest GHG emissions credits. Overall, the repair process for a 48 by 40 inch (1,219 by 1,016 mm) stringer‐class wood pallet had GHG credits rather than a positive GHG emission due to the GHG offsets from co‐products.     

Contribution of Urban Water Supply to Greenhouse Gas Emissions in China

Greenhouse gas (GHG) emissions from energy use in the water sector in China have not received the same attention as emissions from other sectors, but interest in this area is growing. This study uses 2011 data to investigate GHG emissions from electricity use for urban water supply in China. The objective is to measure the climate cobenefit of water conservation, compare China with other areas on a number of emissions indicators, and assist in development of policy that promotes low‐emission water supply. Per capita and per unit GHG emissions for water supplied to urban areas in China in 2011 were 24.5 kilograms carbon dioxide equivalent (kg CO₂‐eq) per capita per year and 0.213 kg CO₂‐eq per cubic meter, respectively. Comparison of provinces within China revealed that GHG emissions for urban water supply as a percentage of total province‐wide emissions from electricity use correlate directly with the rate of leakage and water loss within the water distribution system. This highlights controlling leakage as a possible means of reducing the contribution of urban water supply to GHG emissions. An inverse correlation was established between GHG emissions per unit water and average per capita daily water use, which implies that water demand tends to be higher when per unit emissions are lower. China's high emission factor for electricity generation inflates emissions for urban water supply. Shifting from emissions‐intensive electricity sources is crucial to reducing emissions in the water supply sector.     

Greenhouse Gas Emissions Payback for Lightweighted Vehicles Using Aluminum and High‐Strength Steel

In this article we consider interactions between life cycle emissions and materials flows associated with lightweighting (LW) automobiles. Both aluminum and high‐strength steel (HSS) lightweighting are considered, with LW ranging from 6% to 23% on the basis of literature references and input from industry experts. We compare the increase in greenhouse gas (GHG) emissions associated with producing lightweight vehicles with the saved emissions during vehicle use. This yields a calculation of how many years of vehicle use are required to offset the added GHG emissions from the production stage. Payback periods for HSS are shorter than for aluminum. Nevertheless, achieving significant LW with HSS comparable to aluminum‐intensive vehicles requires not only material substitution but also the achievement of secondary LW by downsizing of other vehicle components in addition to the vehicle structure. GHG savings for aluminum LW varies strongly with location where the aluminum is produced and whether secondary aluminum can be utilized instead of primary. HSS is less sensitive to these parameters. In principle, payback times for vehicles lightweighted with aluminum can be shortened by closed‐loop recycling of wrought aluminum (i.e., use of secondary wrought aluminum). Over a 15‐year time horizon, however, it is unlikely that this could significantly reduce emissions from the automotive industry, given the challenges involved with enabling a closed‐loop aluminum infrastructure without downcycling automotive body structures.     

Wood pellets,what else? Greenhouse gas parity times of European electricity from wood pellets produced in the south‐eastern United States using different softwood feedstocks

Several EU countries import wood pellets from the south‐eastern United States. The imported wood pellets are (co‐)fired in power plants with the aim of reducing overall greenhouse gas (GHG) emissions from electricity and meeting EU renewable energy targets. To assess whether GHG emissions are reduced and on what timescale, we construct the GHG balance of wood‐pellet electricity. This GHG balance consists of supply chain and combustion GHG emissions, carbon sequestration during biomass growth and avoided GHG emissions through replacing fossil electricity. We investigate wood pellets from four softwood feedstock types: small roundwood, commercial thinnings, harvest residues and mill residues. Per feedstock, the GHG balance of wood‐pellet electricity is compared against those of alternative scenarios. Alternative scenarios are combinations of alternative fates of the feedstock materials, such as in‐forest decomposition, or the production of paper or wood panels like oriented strand board (OSB). Alternative scenario composition depends on feedstock type and local demand for this feedstock. Results indicate that the GHG balance of wood‐pellet electricity equals that of alternative scenarios within 0–21 years (the GHG parity time), after which wood‐pellet electricity has sustained climate benefits. Parity times increase by a maximum of 12 years when varying key variables (emissions associated with paper and panels, soil carbon increase via feedstock decomposition, wood‐pellet electricity supply chain emissions) within maximum plausible ranges. Using commercial thinnings, harvest residues or mill residues as feedstock leads to the shortest GHG parity times (0–6 years) and fastest GHG benefits from wood‐pellet electricity. We find shorter GHG parity times than previous studies, for we use a novel approach that differentiates feedstocks and considers alternative scenarios based on (combinations of) alternative feedstock fates, rather than on alternative land uses. This novel approach is relevant for bioenergy derived from low‐value feedstocks.     

Greenhouse Gas Emission Estimates of U.S. Dietary Choices and Food Loss

Dietary behavioral choices have a strong effect on the environmental impact associated with the food system. Here, we consider the greenhouse gas (GHG) emissions associated with production of food that is lost at the retail and consumer level, as well as the potential effects on GHG emissions of a shift to dietary recommendations. Calculations are based on the U.S. Department of Agriculture's (USDA) food availability data set and literature meta‐analysis of emission factors for various food types. Food losses contribute 1.4 kilograms (kg) carbon dioxide equivalents (CO₂‐eq) capita^?1day^?1 (28%) to the overall carbon footprint of the average U.S. diet; in total, this is equivalent to the emissions of 33 million average passenger vehicles annually. Whereas beef accounts for only 4% of the retail food supply by weight, it represents 36% of the diet‐related GHG emissions. An iso‐caloric shift from the current average U.S. diet to USDA dietary recommendations could result in a 12% increase in diet‐related GHG emissions, whereas a shift that includes a decrease in caloric intake, based on the needs of the population (assuming moderate activity), results in a small (1%) decrease in diet‐related GHG emissions. These findings emphasize the need to consider environmental costs of food production in formulating recommended food patterns.     

The integration of long-term marginal electricity supply mixes in the ecoinvent consequential database version 3.4 and examination of modeling choices

Purpose

The long-term marginal electricity supply mixes of 40 countries were generated and integrated into version 3.4 of the ecoinvent consequential database. The total electricity production originating from these countries accounts for 77% of the current global electricity generation. The goal of this article is to provide an overview of the methodology used to calculate the marginal mixes and to evaluate the influence of key parameters and methodological choices on the results.

Methods

The marginal mixes are based on public energy projections from national and international authorities and reflect the accumulated effect of changes in demand for electricity on the installation and operation of new-generation capacities. These newly generated marginal mixes are first examined in terms of their compositions and environmental impacts. They are then compared to several sets of alternative electricity supply mixes calculated using different methodological choices or data sources.

Results and discussion

Renewable energy sources (RES) as well as natural gas power plants show the highest growth rates and usually dominate the marginal mixes. Nevertheless, important variations may exist between the marginal mixes of the different countries in terms of their technological compositions and environmental impacts. The examination of the modeling choices reveals substantial variations between the marginal mixes integrated into the ecoinvent consequential database version 3.4 and marginal mixes generated using alternative modeling options. These different modeling possibilities include changes in the methodology, temporal parameters, and the underlying energy scenarios. Furthermore, in most of the impact categories, average (i.e., attributional) mixes cause higher impact scores than marginal mixes due to higher shares of RES in marginal mixes.

Conclusions

Accurate and consistent data for electricity supply is integrated into a consequential database providing a strong basis for the development of consequential Life Cycle Assessments. The methodology adopted in this version of the database eliminates several shortcomings from the previous approach which led to unrealistic marginal mixes in several countries. The use of energy scenarios allows the evolution of the electricity system to be considered within the definition of the marginal mixes. The modeling choices behind the electricity marginal mix should be adjusted to the goal and scope of individual studies and their influence on the results evaluated.