8:30am - 8:50am
Life Cycle Greenhouse Gas Emissions of Long-Range and Shared-Use Electric Vehicles
University of California Davis, United States of America
Battery electric Vehicles (BEVs) have become a key greenhouse gas and pollution mitigation strategy; a number of policies have been proposed or enacted to provide a variety of incentives to BEVs. Rapid growth in the market for on-demand ride hailing and shared ride services, combined with the looming arrival of increasing levels of vehicle automation, are trends that could mitigate or compound emissions from light duty vehicles. While a large body of literature has examined the Life Cycle Greenhouse Gas Emissions of BEVs, a majority of studies have focused on efficiency-oriented vehicle designs with limited battery capacities (i.e. the early Nissan Leaf) as the exemplar BEV.
Given the evolution of BEV designs and model availability, declining prices for traction batteries, and changing applications for BEVs, previous life cycle assessments (LCAs) may not be representative of current and future BEV performance, vehicle specifications, or patterns of use. This study aims to: (1) quantify the life cycle GHG emissions of evolving BEV designs and use-cases, and (2) identify unanticipated consequences of larger battery capacities and vehicle design choices, such as significant improvements in battery life or increased use in service fleets. A model was developed that simulates three archetypal vehicle designs based on current market trends: an efficiency-oriented vehicle with significantly increased range; a high performance luxury sedan with long range and high performance; and a sport utility vehicle (SUV) with increased use of light-weighting materials and long range. For each vehicle scenario, we consider a set of 2025 vehicle models with improved battery systems.
We then compared these future vehicle scenarios to both current market BEVs and conventional internal combustion vehicles under a range of operations assumptions. For the operation phase, vehicle fuel demands were estimated for two primary applications: private personal passenger vehicle, and shared-use or on-demand ride hailing vehicle. The study also considered a range of scenarios evaluating regional differences in electricity generation by fuel source and the potential effects of decarbonization in the electricity sector in the United States.
Life cycle GHG emissions for BEVs were found to range from 78 – 193 gCO2-eq/km over an average 12 year vehicle lifetime; a 45% – 65% reduction in life cycle GHG emissions per mile when moving from a conventional ICEV (234 to 308 gCO2-eq/km). While only 11% to 16% of life cycle GHG emissions for ICEVs are attributable to vehicle production, production of vehicle and battery systems cause approximately half of life cycle emissions for BEVs (34 to 71 gCO2-eq/km). Larger battery systems combined with the low utilization of average passenger vehicles could result in higher per mile emissions for BEVs even when including expected reductions in GHG emissions associated with electricity generation for vehicle charging. These trends could be exacerbated by a market shift favoring larger cross-overs and SUVs. Larger battery systems could improve the performance of BEVs in on-demand ride sharing or shared ride hailing fleets. High-mileage (and highly utilized) BEVs could result in lower per km life cycle emissions, but significantly increase the total life cycle emissions per vehicle.
8:50am - 9:10am
Health and Climate Benefits of EV Deployment in the Greater Toronto and Hamilton Area
University of Toronto, Canada
The transportation sector is Canada’s second largest greenhouse gas (GHG) emitter (i.e. accounting for 24% of total GHG emissions in 2015). Meanwhile, this sector is a large contributor to criteria air contaminant (CAC) emissions (e.g., the transportation and mobile equipment category contributed 52% of nitrogen oxides (NOx) emissions in 2016). Thus, traffic emissions can cause both environmental and health impacts, including climate change and higher risks of mortality and morbidity due to air pollution exposure. Since electric vehicles (EVs) do not generate exhaust emissions, vehicle electrification can potentially bring health and climate co-benefits to the society. However, from a life cycle assessment perspective, it is important to account for emissions from electricity generation while evaluating the actual benefits of EV deployment. This is because a large-scale EV penetration will increase GHG and CAC emissions from power plants.
To investigate the impacts of EV deployment from a system-scale perspective, we developed an integrated method to evaluate the environmental, health and economic impacts of deploying EVs in the Greater Toronto and Hamilton Area (GTHA) – the largest metropolitan area in Canada. Considering different EV penetration rates, we used a travel demand model to simulate EV energy use and charging demand. These vehicle adoption scenarios were then coupled with historical electricity generation and power plant emission data, along with scenarios for the future electric grid, to simulate hourly emissions from power plants in and around the GTHA (primarily those in Ontario and New York state). Hourly traffic operating emissions from internal combustion vehicles were estimated by combing regional travel demand simulation and traffic assignment. With the hourly emissions as the inputs, Polyphemus, a chemical transport model, was used to generate concentrations of various air pollutants by modeling air dispersion with meteorological data. To evaluate the impacts of different scenarios, we: 1) characterized spatial-temporal changes of population exposure to air pollutants, 2) assessed health impacts in terms of Disability-adjusted life years (DALYs) using the comparative risk assessment approach, and 3) estimated the economic costs and benefits due to changes in health impacts and GHG emissions. Based on the results of the evaluation, policy suggestions are provided to enhance EV deployment in the GTHA.
Example scenarios evaluated include: 1) a bounding scenario that assumed 100% EV penetration and (as a worst case) the electricity demand for EV charging is only supported by the within domain natural gas power plants (as Ontario does not have any coal plants) and 2) a more realistic scenario that predicted an EV penetration rate based on proposed policies and electricity generation mixes based on Ontario long-term energy plan. With a relatively clean electricity system, even for the worst-case scenario, we observed positive overall changes in air pollution exposure and health impacts. This is because there is a substantial reduction in air pollution exposure in high population areas (due to the removal of internal combustion vehicles) and a trivial increment in lower population areas close to the power plants. Results from additional scenarios will be included in the final presentation.
9:10am - 9:30am
Green Principles for Vehicle Lightweighting: Guidance for Reducing Transportation Impact, With Examples
1University of Michigan; 2Argonne National Lab; 3Oak Ridge National Lab
A large portion of life cycle transportation impacts occur during vehicle operation, and key improvement strategies include increasing powertrain efficiency, vehicle electrification and lightweighting vehicles by reducing their mass. The potential energy benefits of vehicle lightweighting is are large, given that 29.5 EJ was used in all modes of U.S. transportation in 2016 and roughly half of the energy spent in wheeled transportation and the majority of energy spent in aircraft is used to move vehicle mass. We collect and review previous work on lightweighting, identify key parameters affecting vehicle environmental performance (e.g., vehicle mode, fuel type, material type and recyclability), and propose a set of ten principles, with examples, to guide environmental improvement of vehicle systems through lightweighting. These principles, based on a life cycle perspective and taken as a set, allow a wide range of stakeholders (designers, policy-makers, and vehicle manufacturers and their material and component suppliers) to evaluate the tradeoffs inherent in these complex systems. This set of principles can be used to evaluate tradeoffs between impact categories, and help to help avoid shifting of burdens to other life cycle phases in the process of improving use phase environmental performance.
9:30am - 9:50am
Achieving greenhouse gas emission reduction targets in the U.S. light-duty fleet
Department of Civil & Mineral Engineering, University of Toronto
Introduction and research objectives:
Strategies exist to reduce the greenhouse gas (GHG) emissions of light-duty vehicles but none is a silver-bullet. Deployments of biofuels, such as ethanol, alternative powertrain vehicles, such as electric vehicles, or lightweighted vehicles, such as aluminum-intensive vehicles, reduce the direct use of fossil fuels but require more energy elsewhere in the vehicle life cycle. These strategies are regularly assessed with a vehicle-based life cycle approach. However, vehicles possess their own dynamics in fleets and many factors affect the scaling of the results at the fleet level, such as the interactions between the strategies (Milovanoff et al. 2019) or the behavioural changes associated with technological development (Font Vivanco et al. 2014). The aim of our work is to outline potential pathways to achieve U.S. light-duty fleet GHG emission reduction targets to stabilize atmospheric GHG concentrations and their respective challenges.
We first set GHG emission targets for the U.S. light-duty fleet from the U.S. nationally determined contributions (NDC) of the Paris Agreement (United States of America 2015), and from Global Carbon Emissions pathways of GHG concentration stabilization (Grimes-Casey et al. 2009). Then, our study expands on our FLAME model (Fleet Life Cycle Assessment and Material-Flow Estimation) to calculate the U.S. light-duty fleet GHG emissions (introduced in Milovanoff et al. (2019)). FLAME establishes the vehicle characteristics by vehicle type, the annual fleet stock and fleet kilometers traveled by model year and fuel type, the quantities of recovered materials available from scrapped vehicles, along with consumption of primary and secondary (recycled) materials for new vehicle production, and the associated life cycle GHG emissions. In this expansion, we improve on the behavioural realism of FLAME by including the short-term direct rebound effects of changes in marginal operating costs in new model-year vehicles on vehicle travel demand. We develop several pathways to reduce the fleet GHG emissions: electric vehicle, lightweighting and higher ethanol-content fuel blend (e.g., mid-level ethanol blends) deployments. In the near future, we will explore the influences of changes in fleet attributes, such as average horsepower and acceleration time, and of rebound effect levels on the light-duty fleet GHG emissions. In addition, we will develop an autonomous vehicle deployment scenario. Finally, we will build parametric analysis to assess the mix of scenarios that can achieve the targets.
The preliminary results show that the U.S. GHG emission target pledge for 2025 would require 227 Mt CO2 eq. of GHG emission reductions compared to the baseline fleet GHG emissions, due to an expected rise in baseline fleet GHG emissions. The Safer Affordable Fuel Efficient (SAFE) Vehicles Proposed Rule (2018), the expected electric vehicle deployment of the U.S. Energy Information Administration (2018) and the current trends in vehicle lightweighting could provide 40 Mt CO2 eq. of GHG emission reductions, or 18% of the target. We expect, in the near future, to outline the deployment levels for the different strategies to achieve GHG emission targets and to conclude on the implications for automotive policies in the U.S.
Font Vivanco, D., J. Freire-González, R. Kemp, and E. Van Der Voet. 2014. The remarkable environmental rebound effect of electric cars: A microeconomic approach. Environmental Science and Technology 48(20): 12063–12072.
Grimes-Casey, H.G., G.A. Keoleian, and B. Willcox. 2009. Carbon Emission Targets for Driving Sustainable Mobility with US Light-Duty Vehicles. Environmental Science & Technology 43(3): 585–590.
Milovanoff, A., H.C. Kim, R.D. De Kleine, T.J. Wallington, I.D. Posen, and H.L. MacLean. 2019. A dynamic fleet model of U.S light-duty vehicle lightweighting and associated greenhouse gas emissions from 2016-2050. Environmental Science & Technology: acs.est.8b04249. http://pubs.acs.org/doi/10.1021/acs.est.8b04249.
National Highway Traffic Safety Administration and Environmental Protection Agency. 2018. The Safer Affordable Fuel Efficient (SAFE) Vehicles Proposed Rule for Model Years 2021-2026. https://www.epa.gov/regulations-emissions-vehicles-and-engines/safer-affordable-fuel-efficient-safe-vehicles-proposed#rule-summary.
U.S. Energy Information Administration. 2018. Annual Energy Outlook 2018 with projections to 2050. https://www.eia.gov/outlooks/aeo/.
United States of America. 2015. U.S. Cover notes, INDC and Accompanying Information. http://www4.unfccc.int/Submissions/INDC/Published Documents/United States of America/1/U.S. Cover Note INDC and Accompanying Information.pdf.