Local inequities in the relative production of and exposure to vehicular air pollution in Los Angeles

Abstract

Vehicular air pollution has created an ongoing air quality and public health crisis. Despite growing knowledge of racial injustice in exposure levels, less is known about the relationship between the production of and exposure to such pollution. This study assesses pollution burden by testing whether local populations’ vehicular air pollution exposure is proportional to how much they drive. Through a Los Angeles, California, case study we examine how this relates to race, ethnicity and socio-economic status – and how these relationships vary across the region. We find that, all else equal, tracts whose residents drive less are exposed to more air pollution, as are tracts with a less-White population. Commuters from majority-White tracts disproportionately drive through non-White tracts, compared to the inverse. Decades of racially-motivated freeway infrastructure planning and residential segregation shape today’s disparities in who produces vehicular air pollution and who is exposed to it, but opportunities exist for urban planning and transport policy to mitigate this injustice.

Urban street network design and transport-related greenhouse gas emissions around the world

“…While measuring density in some form and including it as an explanatory variable is common across almost all studies, operationalizations of density -and what other variables are included -vary dramatically. Emissions themselves can be measured as fuel consumption (Curtis et al, 1984;Siew Yin and Chin Siong, 2010), carbon emissions (Mohajeri et al, 2015;Cao and Yang, 2017), or as a variety of other pollutants of interest such as ozone (Schweitzer and Zhou, 2010) or particulate matter (Boeing et al, 2023). Population density -that is, the number of residents in an urban area divided by its area -is almost always included as a variable, but land use mix and other built environment dimensions like accessibility are less common, particularly when using aggregate units of observation (Ewing and Cervero, 2010;Hong and Goodchild, 2014).…”

PM2.5 exposure disparities persist despite strict vehicle emissions controls in California

“…The first approach starts from the recognition that many major emitting sectors lead to disparate exposures for people of color (4). Thus, focusing on emissions reductions for sectors that especially impact people of color could have EJ cobenefits (16,(18)(19)(20)(21). This approach mirrors the policy structure in the U.S. and elsewhere, where environmental regulations are targeted to individual economic sectors (e.g., vehicles, industries, power plants) and tailored to relevant technology and infrastructure.…”

“…We focus on the transportation sector, which is often highlighted as having high potential to reduce disparities. Historically, racist urban planning and infrastructure decisions (e.g., redlining, freeway siting) have concentrated vehicle emissions in communities of color (4,6,9,18). Furthermore, people who are exposed to the highest levels of traffic-related air pollution often are not the communities who drive the most (19)(20)(21).…”

Rush hour-and-a-half: Traffic is spreading out post-lockdown

“…Roadway construction often displaces low-income residents and residents of color—both historically [ 9 ] and today [ 10 ]. Pollution from roadways disproportionately affects non-white communities [ 11 ].…”