From Watts to Wheels: A Life Cycle Assessment Study of Electricity Mix Influence on Electric Vehicle Emissions in the United States

Description
Battery Electric Vehicles (BEV) are on the rise in the United States as an alternative to heavily-polluting Internal Combustion Engine Vehicles (ICEV). However, BEV greenhouse gas (GHG) emissions are influenced by the electricity mix that the vehicle is produced in

Battery Electric Vehicles (BEV) are on the rise in the United States as an alternative to heavily-polluting Internal Combustion Engine Vehicles (ICEV). However, BEV greenhouse gas (GHG) emissions are influenced by the electricity mix that the vehicle is produced in and operated in. This study uses Life Cycle Assessment (LCA) to model the variability of BEV emissions across eleven different U.S. regions to determine which energy resources contribute the most to BEV lifetime emissions and in which lifecycle stages these emissions are most prevalent. Results suggest that BEV emissions are correlated with the share of highly emission-intensive resources (coal and residual oil), meaning that regions with the highest shares of coal and residual oil have the highest BEV emissions. With the Biden Administration’s aggressive BEV adoption goals and implementation of the 2022 Inflation Reduction Act, it is crucial that government resources are allocated to regions with higher emissions-intense resources to encourage the reduction of GHG emissions nationwide.
Date Created
2024-05
Agent

Challenges for Equitable Air Quality Monitoring in Urban, Low-Income Neighborhoods: A Comparison of Maricopa County, Arizona and the Metropolitan Region of Santiago, Chile

164818-Thumbnail Image.png
Description

Low-income areas are more likely to be exposed to poor air quality and hazardous levels of criteria pollutants, including particulate matter. While this relationship is well documented in environmental justice and equity literature, there is less discussion of how it

Low-income areas are more likely to be exposed to poor air quality and hazardous levels of criteria pollutants, including particulate matter. While this relationship is well documented in environmental justice and equity literature, there is less discussion of how it is addressed by regulatory air quality departments and their monitoring networks. Socioeconomic clustering in highly polluted areas presents a challenge for local regulatory agencies as it may result in over- or under-monitoring of certain income brackets. This is significant because, for regulatory bodies, what is monitored determines where environmental regulations are enforced. In this study, I look at the spatial concentrations of low-income neighborhoods and their proximity to regulatory fine particulate matter monitoring stations in Maricopa County, Arizona and Santiago Metropolitan Region, Chile. This study also evaluates which monitors are most often in exceedance of air quality standards for PM2.5. Using census data, individual monitor readings, and monitoring network assessment data to create tables and maps, I illustrate that, in both case studies, regulatory PM2.5 monitors are frequently positioned in proximity to very low-income or highly impoverished communities. The monitors most often and furthest past exceedance of federal air quality standards are those in (or closest) to the poorest parts of the urban center of the region. In both cases, these populations and monitors are heavily concentrated to the south and west of the region’s primary city. This is likely due to compounding factors attributed to urban geography and zoning that should be explored in future studies. I use these findings to suggest that income and poverty level should be evaluated as an environmental justice factor and as an area for improvement in assessments of regulatory monitoring networks, and to provide further evidence in the debate about equitable air quality monitoring.

Date Created
2022-05
Agent