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In Pursuit of Local Solutions for Climate Resilience: Sensing Microspatial Inequities in Heat and Air Pollution within Urban Neighborhoods in Boston, MA

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  • Daniel T. O’Brien

    (School of Public Policy and Urban Affairs, Northeastern University, Boston, MA 02115, USA
    School of Criminology and Criminal Justice, Northeastern University, Boston, MA 02115, USA
    Boston Area Research Initiative, Northeastern and Harvard Universities, Boston, MA 02115, USA)

  • Amy V. Mueller

    (Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA
    Department of Marine and Environmental Sciences, Northeastern University, Boston, MA 02115, USA)

Abstract

Environmental hazards vary locally and even street to street resulting in microspatial inequities , necessitating climate resilience solutions that respond to specific hyperlocal conditions. This study uses remote sensing data to estimate two environmental hazards that are particularly relevant to community health: land surface temperature (LST; from LandSat) and air pollution (AP; from motor vehicle volume via cell phone records). These data are analyzed in conjunction with land use records in Boston, MA to test (1) the extent to which each hazard concentrates on specific streets within neighborhoods, (2) the infrastructural elements that drive variation in the hazards, and (3) how strongly hazards overlap in space. Though these data rely on proxies, they provide preliminary evidence. Substantial variations in LST and AP existed between streets in the same neighborhood (40% and 70–80% of variance, respectively). The former were driven by canopy, impervious surfaces, and albedo. The latter were associated with main streets and zoning with tall buildings. The correlation between LST and AP was moderate across census tracts ( r = 0.4) but modest across streets within census tracts ( r = 0.16). The combination of results confirms not only the presence of microspatial inequities for both hazards but also their limited coincidence, indicating that some streets suffer from both hazards, some from neither, and others from only one. There is a need for more precise, temporally-dynamic data tracking environmental hazards (e.g., from environmental sensor networks) and strategies for translating them into community-based solutions.

Suggested Citation

  • Daniel T. O’Brien & Amy V. Mueller, 2023. "In Pursuit of Local Solutions for Climate Resilience: Sensing Microspatial Inequities in Heat and Air Pollution within Urban Neighborhoods in Boston, MA," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:2984-:d:1060234
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    References listed on IDEAS

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    1. Raj Chetty & Nathaniel Hendren, 2018. "The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(3), pages 1163-1228.
    2. Seth E. Spielman & Joseph Tuccillo & David C. Folch & Amy Schweikert & Rebecca Davies & Nathan Wood & Eric Tate, 2020. "Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(1), pages 417-436, January.
    3. Harlan, Sharon L. & Brazel, Anthony J. & Prashad, Lela & Stefanov, William L. & Larsen, Larissa, 2006. "Neighborhood microclimates and vulnerability to heat stress," Social Science & Medicine, Elsevier, vol. 63(11), pages 2847-2863, December.
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