Keywords:batteries electricity mix global warming industrial ecology life cycle inventory (LCI) transportation Supporting information is available on the JIE Web site SummaryElectric 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 problemshifting. 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.

Electric vehicles have no tailpipe emissions, but the production of their batteries leads to environmental burdens. In order to avoid problem-shifting, a life cycle perspective should be applied in the environmental assessment of traction batteries. The goal of this study is to provide a transparent inventory for a lithium-ion nickel-cobalt-manganese traction battery based on primary data and to report its cradle-to-gate impacts. The study was carried out as a processbased attributional life cycle assessment. The environmental impacts were analyzed using midpoint indicators. The global warming potential of the 26.6 kilowatt-hour (kWh), 253 kg battery pack was found to be 4.6 tonnes carbon dioxide equivalents. Regardless of impact category, the production impacts of the battery are caused mainly by the production chains of battery cell manufacture, the positive electrode paste, and the negative current collector. The robustness of the study was tested through sensitivity analysis, and results were compared with preceding studies. Sensitivity analysis indicates that the most effective approach to reduce climate change emissions would be to produce the battery cells with electricity from a cleaner energy mix. On a per-kWh basis, cradle-to-gate greenhouse gas emissions of the battery are within the range of those reported in preceding studies. Contribution and structural path analysis allowed for identification of the most impact-intensive processes and value chains. This article provides an inventory based mainly on primary data, which can easily be adapted to subsequent EV studies, and offers improved understanding of environmental burdens pertaining to lithium ion traction batteries.3

This study presents the life cycle assessment (LCA) of three batteries for plug-in hybrid and full performance battery electric vehicles. A transparent life cycle inventory (LCI) was compiled in a component-wise manner for nickel metal hydride (NiMH), nickel cobalt manganese lithium-ion (NCM), and iron phosphate lithium-ion (LFP) batteries. The battery systems were investigated with a functional unit based on energy storage, and environmental impacts were analyzed using midpoint indicators. On a per-storage basis, the NiMH technology was found to have the highest environmental impact, followed by NCM and then LFP, for all categories considered except ozone depletion potential. We found higher life cycle global warming emissions than have been previously reported. Detailed contribution and structural path analyses allowed for the identification of the different processes and value-chains most directly responsible for these emissions. This article contributes a public and detailed inventory, which can be easily be adapted to any powertrain, along with readily usable environmental performance assessments.

Life cycle assessments (LCA) and environmentally extended input-output (EEIO) analyses both strive to account for direct and indirect environmental impacts of goods and services. Different methods have been developed to hybridize these two techniques and minimize the impact of their respective shortcomings on final assessments. These weaknesses, however, have not been extensively studied in a quantitative manner, especially not for complete LCA and EEIO databases. To this end, we jointly analyzed process-based and input-output-based data sets. We first evaluated their complementarity. Though the LCA data was more detailed overall, some sectors of the economy were more precisely represented in the EEIO database. We then contrasted the representation of the different economic sectors in the LCA database with the economic, environmental, and structural importance of these sectors. The weakness of the correlation results led us to conclude that process-inventory efforts have not been systematically directed at the most important sectors of the economy. The LCA data was also used to evaluate the sensitivity of EEIO data to aggregation uncertainty. This sensitivity proved highly inhomogeneous. We conclude the presence of important research inefficiencies stemming from the lack of hybrid perspective in the compilation of LCA and EEIO data.

The divide between attributional and consequential research perspectives partly overlaps with the long-standing methodological discussions in the lifecycle assessment (LCA) and input-output analysis (IO) research communities on the choice of techniques and models for dealing with situations of coproduction.The recent harmonization of LCA allocations and IO constructs revealed a more diverse set of coproduction models than had previously been understood. This increased flexibility and transparency in inventory modeling warrants a re-evaluation of the treatment of coproduction in analyses with attributional and consequential perspectives.In the present article, the main types of coproductions situations and of coproduction models are reviewed, along with key desirable characteristics of attributional and consequential studies. A concordance analysis leads to clear recommendations, which call for important refinements to current guidelines for both LCA/IO practitioners and database developers. We notably challenge the simple association between, on the one hand, attributional LCA and partition allocation, and on the one hand, consequential LCA and substitution modeling.