Hybrid- and battery-electric vehicles offer low-cost climate benefits in China

Car ownership in China is expected to grow dramatically in the coming decades. If growing personal vehicle demand is met with conventional cars, the increase in greenhouse gas emissions will be substantial. One way to mitigate carbon dioxide (CO₂) emissions from passenger travel is to meet growing demand for cars with alternative vehicles such as hybrid- and battery-electric vehicles (HEVs and BEVs). Our study examines the cost-effectiveness of transitioning from conventional cars to HEVs and BEVs, by calculating their marginal abatement cost (MAC) of carbon in the long-run. We find that transitioning from conventional to hybrid and battery electric light-duty, four-wheel vehicles can achieve carbon emissions reductions at a negative cost (i.e. at a net benefit) in China. In 2030, the average MAC is estimated to be about −$140/ton CO₂ for HEVs and −$515/ton CO₂-saved for BEVs, varying by key parameters. The total mitigation potential of each vehicle technology is estimated to be 1.38 million tons for HEVs and 0.75 million tons for BEVs.     

Well-to-wheel costs,primary energy demand,and greenhouse gas emissions for the production and operation of conventional and alternative vehicles

This study provides a comprehensive comparison of well-to-wheel (WTW) energy demand, WTW GHG emissions, and costs for conventional ICE and alternative passenger car powertrains, including full electric, hybrid, and fuel cell powertrains. Vehicle production, operation, maintenance, and disposal are considered, along with a range of hydrogen production processes, electricity mixes, ICE fuels, and battery types. Results are determined based on a reference vehicle, powertrain efficiencies, life cycle inventory data, and cost estimations. Powertrain performance is measured against a gasoline ICE vehicle. Energy carrier and battery production are found to be the largest contributors to WTW energy demand, GHG emissions, and costs; however, electric powertrain performance is highly sensitive to battery specific energy. ICE and full hybrid vehicles using alternative fuels to gasoline, and fuel cell vehicles using natural gas hydrogen production pathways, are the only powertrains which demonstrate reductions in all three evaluation categories simultaneously (i.e., WTW energy demand, emissions, and costs). Overall, however, WTW emission reductions depend more on the energy carrier production pathway than on the powertrain; hence, alternative energy carriers to gasoline for an ICE-based fleet (including hybrids) should be emphasized from a policy perspective in the short-term. This will ease the transition towards a low-emission fleet in Switzerland.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Predicting market potential and environmental benefits of deploying electric taxis in Nanjing,China

This paper investigates the market potential and environmental benefits of replacing internal combustion engine (ICE) vehicles with battery electric vehicles (BEVs) in the taxi fleet in Nanjing, China. Vehicle trajectory data collected by onboard global positioning system (GPS) units are used to study the travel patterns of taxis. The impacts of charger power, charging infrastructure coverage, and taxi apps on the feasibility of electric taxis are quantified, considering taxi drivers’ recharging behavior and operating activities. It is found that (1) depending on the charger power and coverage, 19% (with AC Level 2 chargers and 20% charger network coverage) to 56% (with DC chargers and 100% charger network coverage) of the ICE vehicles can be replaced by electric taxis without driving pattern changes; (2) by using taxi apps to find nearby passengers and charging stations, drivers could utilize the empty cruising time to charge the battery, which may increase the acceptance of BEVs by up to 82.6% compared to the scenario without taxi apps; and (3) tailpipe emissions in urban areas could be significantly reduced with taxi electrification: a mixed taxi fleet with 46% compressed-natural-gas-powered (CNG) and 54% electricity-powered vehicles can reduce the tailpipe emissions by 48% in comparison with the fleet of 100% CNG taxis.     

Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China

We model consumer preferences for conventional, hybrid electric, plug-in hybrid electric (PHEV), and battery electric (BEV) vehicle technologies in China and the U.S. using data from choice-based conjoint surveys fielded in 2012–2013 in both countries. We find that with the combined bundle of attributes offered by vehicles available today, gasoline vehicles continue in both countries to be most attractive to consumers, and American respondents have significantly lower relative willingness-to-pay for BEV technology than Chinese respondents. While U.S. and Chinese subsidies are similar, favoring vehicles with larger battery packs, differences in consumer preferences lead to different outcomes. Our results suggest that with or without each country’s 2012–2013 subsidies, Chinese consumers are willing to adopt today’s BEVs and mid-range PHEVs at similar rates relative to their respective gasoline counterparts, whereas American consumers prefer low-range PHEVs despite subsidies. This implies potential for earlier BEV adoption in China, given adequate supply. While there are clear national security benefits for adoption of BEVs in China, the local and global social impact is unclear: With higher electricity generation emissions in China, a transition to BEVs may reduce oil consumption at the expense of increased air pollution and/or greenhouse gas emissions. On the other hand, demand from China could increase global incentives for electric vehicle technology development with the potential to reduce emissions in countries where electricity generation is associated with lower emissions.     

Eco-driver training within the City of Calgary’s municipal fleet: Monitoring the impact

This article highlights eco-driving as an available policy option to reduce climate altering GHG emissions. Recognizing the need to reduce the environmental impact of its fleet operations, the City of Calgary is a leader in developing programs and policies that aim to reduce GHG emissions and associated pollutants resulting from the use of fossil fuels. Among local action taken against climate change, the City sought to quantify CO₂ emissions reductions from their municipal fleet as a result of eco-driver training, with a specific focus on engine idling. Fifteen drivers from the Development & Building Approvals Business Unit had in-vehicle monitoring technology (CarChips®) installed into their vehicles as part of a three-phase research process. The results show that gasoline and hybrid vehicles decreased average idling between 4% and 10% per vehicle per day, leading to an average emissions decrease of 1.7 kg of CO₂ per vehicle per day.     

A comparison of technologies for carbon-neutral passenger transport

In this study, the use of energy carriers based on renewable energy sources in battery-powered electric vehicles (BPEVs), fuel-cell electric vehicles (FCEVs), hybrid electric vehicles (HEVs) and internal combustion engine vehicles (ICEVs) is compared regarding energy efficiency, emission and cost. There is the potential to double the primary energy compared with the current level by utilising vehicles with electric drivetrains. There is also major potential to increase the efficiency of conventional ICEVs. The energy and environmental cost of using a passenger car can be reduced by 50% solely by using improved ICEVs instead of ICEVs with current technical standard. All the studied vehicles with alternative powertrains (HEVs, FCEVs, and BPEVs) would have lower energy and environmental costs than the ICEV. The HEVs, FCEVs and BPEVs have, however, higher costs than the future methanol-fuelled ICEV, if the vehicle cost is added to the energy and environmental costs, even if significant cost reductions for key technologies such as fuel cells, batteries and fuel storages are assumed. The high-energy efficiency and low emissions of these vehicles cannot compensate for the high vehicle cost. The study indicates, however, that energy-efficiency improvements, combined with the use of renewable energy, would reduce the cost of CO₂ reduction by 40% compared with a strategy based on fuel substitution only.     

Life cycle ownership cost and environmental externality of alternative fuel options for transit buses

This paper assesses alternative fuel options for transit buses. We consider the following options for a 40-foot and a 60-foot transit bus: a conventional bus powered by either diesel or a biodiesel blend (B20 or B100), a diesel hybrid-electric bus, a sparking-ignition bus powered by Compressed Natural Gas (CNG) or Liquefied Natural Gas (LNG), and a battery electric bus (BEB) (rapid or slow charging). We estimate life cycle ownership costs (for buses and infrastructure) and environmental externalities caused by greenhouse gases (GHGs) and criteria air pollutants (CAPs) emitted from the life cycle of bus operations. We find that all alternative fuel options lead to higher life cycle ownership and external costs than conventional diesel. When external funding is available to pay for 80% of vehicle purchase expenditures (which is usually the case for U.S. transit agencies), BEBs yield large reductions (17–23%) in terms of ownership and external costs compared to diesel. Furthermore, BEBs’ advantages are robust to changes in operation and economic assumptions when external funding is available. BEBs are able to reduce CAP emissions significantly in Pittsburgh’s hotspot areas, where existing bus fleets contribute to 1% of particulate matter emissions from mobile sources. We recognize that there are still practical barriers for BEBs, e.g. range limits, land to build the charging infrastructure, and coordination with utilities. However, favorable trends such as better battery performance and economics, cleaner electricity grid, improved technology maturity, and accumulated operation experience may favor use of BEBs where feasible.     

Environmental assessment of electrification of road transport in Norway: Scenarios and impacts

The study develops scenarios regarding the introduction of electric vehicles to the passenger vehicle fleet of Norway to reach the 2020 Norwegian greenhouse gas reduction target and a more extreme target to limit global temperature increase to two degrees. A process-based life cycle assessment approach is integrated with a temporally variable inventory model to evaluate the environmental impacts of these scenarios. We find that greenhouse gases in the reference scenario increase by 10% in 2020 in comparison to 2012; while for the more intensive improvements in conventional vehicles, this increase is reduced to 2%. For electric vehicles deployment scenarios, although the fleet share will reduce the tailpipe greenhouse gas emissions by 8–26%, with the upper end representing the two-degree reduction target, emissions reductions over the entire life cycle are only 3–15%. Electric vehicles also reduce emissions of NO_x, SO₂ and particulates reducing acidification, smog formation and particulate formation impacts, however, with addition of large numbers of electric vehicles significant trade-offs in toxicity impacts are found.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Trends in life cycle greenhouse gas emissions of future light duty electric vehicles

The majority of previous studies examining life cycle greenhouse gas (LCGHG) emissions of battery electric vehicles (BEVs) have focused on efficiency-oriented vehicle designs with limited battery capacities. However, two dominant trends in the US BEV market make these studies increasingly obsolete: sales show significant increases in battery capacity and attendant range and are increasingly dominated by large luxury or high-performance vehicles. In addition, an era of new use and ownership models may mean significant changes to vehicle utilization, and the carbon intensity of electricity is expected to decrease. Thus, the question is whether these trends significantly alter our expectations of future BEV LCGHG emissions.To answer this question, three archetypal vehicle designs for the year 2025 along with scenarios for increased range and different use models are simulated in an LCGHG model: an efficiency-oriented compact vehicle; a high performance luxury sedan; and a luxury sport utility vehicle. While production emissions are less than 10% of LCGHG emissions for today’s gasoline vehicles, they account for about 40% for a BEV, and as much as two-thirds of a future BEV operated on a primarily renewable grid. Larger battery systems and low utilization do not outweigh expected reductions in emissions from electricity used for vehicle charging. These trends could be exacerbated by increasing BEV market shares for larger vehicles. However, larger battery systems could reduce per-mile emissions of BEVs in high mileage applications, like on-demand ride sharing or shared vehicle fleets, meaning that trends in use patterns may countervail those in BEV design.     

To save money or to save time: Intelligent routing design for plug-in hybrid electric vehicle

Electric vehicles (EVs) are promising alternative to conventional vehicles, due to their low fuel cost and low emissions. As a subset of EVs, plug-in hybrid electric vehicles (PHEVs) backup batteries with combustion engines, and thus have a longer traveling range than battery electric vehicles (BEVs). However, the energy cost of a PHEV is higher than a BEV because the gasoline price is higher than the electricity price. Hence, choosing a route with more charging opportunities may result in less fuel cost than the shortest route. Different with the traditional shortest-path and shortest-time routing methods, we propose a new routing choice with the lowest fuel cost for PHEV drivers. Existing algorithms for gasoline vehicles cannot be applied because they never considered the regenerative braking which may result in negative energy consumption on some road segments. Existing algorithms for BEVs are not competent too because PHEVs have two power sources. Thus, even if along the same route, different options of power source will lead to different energy consumption. This paper proposes a cost-optimal algorithm (COA) to deal with the challenges. The proposed algorithm is evaluated using real-world maps and data. The results show that there is a trade-off between traveling cost and time consumed when driving PHEVs. It is also observed that the average detour rate caused by COA is less than 14%. Significantly, the algorithm averagely saves more than 48% energy cost compared to the shortest-time routing.     

Greenhouse gas emission benefits of vehicle lightweighting: Monte Carlo probabalistic analysis of the multi material lightweight vehicle glider

Vehicle lightweighting reduces fuel cycle greenhouse gas (GHG) emissions but may increase vehicle cycle (production) GHG emissions because of the GHG intensity of lightweight material production. Life cycle GHG emissions are estimated and sensitivity and Monte Carlo analyses conducted to systematically examine the variables that affect the impact of lightweighting on life cycle GHG emissions. The study uses two real world gliders (vehicles without powertrain or battery) to provide a realistic basis for the analysis. The conventional and lightweight gliders are based on the Ford Fusion and Multi Material Lightweight Vehicle, respectively. These gliders were modelled with internal combustion engine vehicle (ICEV), hybrid electric vehicle (HEV), and battery electric vehicle (BEV) powertrains. The probability that using the lightweight glider in place of the conventional (steel-intensive) glider reduces life cycle GHG emissions are: ICEV, 100%; HEV, 100%, and BEV, 74%.The extent to which life cycle GHG emissions are reduced depends on the powertrain, which affects fuel cycle GHG emissions. Lightweighting an ICEV results in greater base case GHG emissions mitigation (10 t CO₂eq.) than lightweighting a more efficient HEV (6 t CO₂eq.). BEV lightweighting can result in higher or lower GHG mitigation than gasoline vehicles, depending largely on the source of electricity.     

A consumer-oriented total cost of ownership model for different vehicle types in Germany

In Germany, market penetration by alternative powertrains has been generally processing at a slow pace. Therefore, reaching the 2020 target of one million registered electric vehicles (EVs) is a major challenge. We analyze the German market by advancing and refining existing consumer-oriented total cost of ownership (TCO_C) models and demonstrate the validity of our model by comparing the cost-efficiency of EVs and internal combustion engine vehicles (ICEVs) including the battery resale value for second use and second life. The TCO_C model was calculated for the ten most frequently registered battery electric vehicles (BEVs) and hybrid electric vehicles (HEVs) and compared with ICEVs in the same vehicle segments. The results are further validated through applying three typical annual mileage driver profiles and by Monte Carlo simulations under various scenarios. Results reveal that only a few BEVs and HEVs are economical without subsidies when compared with ICEVs in all considered scenarios. The subsidies only barely change the results. The mini and the medium vehicle segment remain uneconomical in all tested scenarios. Overall, we conclude that subsidies support the competitiveness of BEVs, but fail to lead to favorable TCO_C within several vehicle segments and several tested annual mileages.     

Fuel economy,cost, and greenhouse gas results for alternative fuel vehicles in 2011

This paper presents in-service data collected from over 300 alternative fuel vehicles and over 80 fueling stations to help fleets determine what types of applications and alternative fuels may help them reduce their environmental impacts and fuel costs. The data were compiled in 2011 by over 30 organizations in New York State using a wide variety of commercial vehicle types and technologies. Fuel economy, incremental vehicle purchase cost, fueling station purchase cost, greenhouse gas reductions, and fuel cost savings data clarifies the performance of alternative fuel vehicles and fuel stations. Data were collected from a range of vehicle types, including school buses, delivery trucks, utility vans, street sweepers, snow plows, street pavers, bucket trucks, paratransit vans, and sedans. CNG, hybrid, LPG, and electric vehicles were tracked.     

Impacts of replacement of engine powered vehicles by electric vehicles on energy consumption and CO2 emissions

This paper evaluates the impacts on energy consumption and carbon dioxide (CO₂) emissions from the introduction of electric vehicles into a smart grid, as a case study. The AVL Cruise software was used to simulate two vehicles, one electric and the other engine-powered, both operating under the New European Driving Cycle (NEDC), in order to calculate carbon dioxide (CO₂) emissions, fuel consumption and energy efficiency. Available carbon dioxide data from electric power generation in Brazil were used for comparison with the simulated results. In addition, scenarios of gradual introduction of electric vehicles in a taxi fleet operating with a smart grid system in Sete Lagoas city, MG, Brazil, were made to evaluate their impacts. The results demonstrate that CO₂ emissions from the electric vehicle fleet can be from 10 to 26 times lower than that of the engine-powered vehicle fleet. In addition, the scenarios indicate that even with high factors of CO₂ emissions from energy generation, significant reductions of annual emissions are obtained with the introduction of electric vehicles in the fleet.     

Optimizing charging station locations for urban taxi providers

Recently, electric vehicles are gaining importance which helps to reduce dependency on oil, increases energy efficiency of transportation, reduces carbon emissions and noise, and avoids tail pipe emissions. Because of short daily driving distances, high mileage, and intermediate waiting time, fossil-fuelled taxi vehicles are ideal candidates for being replaced by battery electric vehicles (BEVs). Moreover, taxi BEVs would increase visibility of electric mobility and therefore encourage others to purchase an electric vehicle. Prior to replacing conventional taxis with BEVs, a suitable charging infrastructure has to be established. This infrastructure consists of a sufficiently dense network of charging stations taking into account the lower driving ranges of BEVs.In this case study we propose a decision support system for placing charging stations in order to satisfy the charging demand of electric taxi vehicles. Operational taxi data from about 800 vehicles is used to identify and estimate the charging demand for electric taxis based on frequent origins and destinations of trips. Next, a variant of the maximal covering location problem is formulated and solved to satisfy as much charging demand as possible with a limited number of charging stations. Already existing fast charging locations are considered in the optimization problem. In this work, we focus on finding regions in which charging stations should be placed rather than exact locations. The exact location within an area is identified in a post-optimization phase (e.g., by authorities), where environmental conditions are considered, e.g., the capacity of the power network, availability of space, and legal issues.Our approach is implemented in the city of Vienna, Austria, in the course of an applied research project that has been conducted in 2014. Local authorities, power network operators, representatives of taxi driver guilds as well as a radio taxi provider participated in the project and identified exact locations for charging stations based on our decision support system.     

Life cycle emissions and cost model for urban light duty vehicles

The growth of vehicle sales and use internationally requires the consumption of significant quantities of energy and materials, and contributes to the deterioration of air-quality and climate conditions. Advanced propulsion systems and electric drive vehicles have substantially different characteristics and impacts. They require life cycle assessments and detailed comparisons with gasoline powered vehicles which, in turn, should lead to critical updates of traditional models and assumptions. For a comprehensive comparison of advanced and traditional light duty vehicles, a model is developed that integrates external costs, including emissions and time losses, with societal and consumer life cycle costs. Life cycle emissions and time losses are converted into costs for seven urban light duty vehicles. The results, which are based on vehicle technology characteristics and transportation impacts on environment, facilitate vehicle comparisons and support policy making in transportation. Substantially, more sustainable urban transportation can be achieved in the short-term by promoting policies that increase vehicle occupancy; in the intermediate-term by increasing the share of hybrid vehicles in the car market and in the long-term by the widespread use of electric vehicles. A sensitivity-analysis of life cost results revealed that vehicle costs change significantly for different geographical areas depending on vehicle taxation, pricing of gasoline, electric power and pollution. Current practices in carbon and air quality pricing favor oil and coal based technologies. However, increasing the cost of electricity from coal and other fossil fuels would increase the variable cost for electric vehicles, and tend to favor the variable cost of hybrid vehicles.     

Electric versus conventional vehicles: social costs and benefits in France

This article compares the social costs of electric vehicles with those of conventional, thermal vehicles for typical passenger use in the Ile-de-France region (Greater Paris), a case of particular interest because nearly 80% of the electricity is generated by nuclear power plants. A four-seat electric car is compared to a new conventional car of the same make and model; for the latter both the gasoline and the diesel version are considered because almost half of new car sales in France are diesel. These results are also compared to typical existing diesel and gasoline vehicles in the current French fleet. The methodology developed by the ExternE (External Costs of Energy) Project of the European Commission is used to estimate the costs associated with atmospheric pollution due to power plants, refineries and tail pipe emissions. Our discussion of externalities is limited to air pollution thus excluding others such as costs associated with noise or accidents. Our results imply that the external costs are large and significant, even when one considers the uncertainties. If internalized by government regulations, these externalities can render the total cost of an electric vehicle more competitive with that of currently available thermal vehicles in large urban centers if the electricity is produced by sources with low pollution. However, the current generation electric vehicles are so expensive that internalization of pollution damage would not give it a very clear advantage.     

Effects of battery chemistry and performance on the life cycle greenhouse gas intensity of electric mobility

Lithium traction batteries are a key enabling technology for plug-in electric vehicles (PEVs). Traction battery manufacture contributes to vehicle production emissions, and battery performance can have significant effects on life cycle greenhouse gas (GHG) emissions for PEVs. To assess emissions from PEVs, a life cycle perspective that accounts for vehicle production and operation is needed. However, the contribution of batteries to life cycle emissions hinge on a number of factors that are largely absent from previous analyses, notably the interaction of battery chemistry alternatives and the number of electric vehicle kilometers of travel (e-VKT) delivered by a battery. We compare life cycle GHG emissions from lithium-based traction batteries for vehicles using a probabilistic approach based on 24 hypothetical vehicles modeled on the current US market. We simulate life-cycle emissions for five commercial lithium chemistries. Examining these chemistries leads to estimates of emissions from battery production of 194–494 kg CO₂ equivalent (CO₂e) per kWh of battery capacity. Combined battery production and fuel cycle emissions intensity for plug-in hybrid electric vehicles is 226–386 g CO₂e/e-VKT, and for all-electric vehicles 148–254 g CO₂e/e-VKT. This compares to emissions for vehicle operation alone of 140–244 g CO₂e/e-VKT for grid-charged electric vehicles. Emissions estimates are highly dependent on the emissions intensity of the operating grid, but other upstream factors including material production emissions, and operating conditions including battery cycle life and climate, also affect life cycle GHG performance. Overall, we find battery production is 5–15% of vehicle operation GHG emissions on an e-VKT basis.