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Environmental inequality in the neighborhood networks of urban mobility in US cities

Author

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  • Noli Brazil

    (a Department of Human Ecology, University of California, Davis, CA 95616)

Abstract

Exposure to air pollution within one’s residential neighborhood has detrimental consequences on health and well-being. Yet, this effect may be mitigated or exacerbated because individuals spend much of their time outside of their residential neighborhood to travel to neighborhoods across a city for work, errands, and leisure. Using mobile phone data to track neighborhood mobility in large US cities, I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. These results reveal that minority and poor residents face environmental inequalities at three geographic scales: the neighborhoods they live in, their bordering neighborhoods, and the neighborhoods they visit.

Suggested Citation

  • Noli Brazil, 2022. "Environmental inequality in the neighborhood networks of urban mobility in US cities," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(17), pages 2117776119-, May.
    • Handle: RePEc:nas:journl:v:119:y:2022:p:e2117776119
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    Cited by:

    1. Vladimir Shepelev & Aleksandr Glushkov & Ivan Slobodin & Yuri Cherkassov, 2023. "Measuring and Modelling the Concentration of Vehicle-Related PM2.5 and PM10 Emissions Based on Neural Networks," Mathematics, MDPI, vol. 11(5), pages 1-23, February.
    2. Leanne M. Brown & Ryan A. Hagenson & Tilen Koklič & Iztok Urbančič & Lu Qiao & Janez Strancar & Jason M. Sheltzer, 2024. "An elevated rate of whole-genome duplications in cancers from Black patients," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Bakkensen, Laura A. & Ma, Lala & Muehlenbachs, Lucija & Benitez, Lina, 2024. "Cumulative impacts in environmental justice: Insights from economics and policy," Regional Science and Urban Economics, Elsevier, vol. 107(C).
    4. Ran Xu & Xiao Huang & Kai Zhang & Weixuan Lyu & Debarchana Ghosh & Zhenlong Li & Xiang Chen, 2023. "Integrating human activity into food environments can better predict cardiometabolic diseases in the United States," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

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