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Big mobility data reveals hyperlocal air pollution exposure disparities in the Bronx, New York

Nature Cities volume 1, pages 512–521 (2024)Cite this article

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Abstract

Air pollution disproportionately affects socially disadvantaged populations. Our study bridges the existing gap in quantifying mobility-based exposure and its associated disparity issues. We combined the granular mobility of over 500,000 unique anonymized users daily and hyperlocal air pollution data in 100 × 100-m grid cells to quantify disparities in particulate matter exposure in a racially diverse and dense urban area of New York City. Our approach advances the study of exposure and its disparity from individualized exposure tracking to a population-representative scale. We observed apparently different spatial patterns between personal exposure and exposure disparities, noting that people from Hispanic-majority and low-income neighborhoods were those most severely and disproportionately exposed to fine particulate matter (PM2.5) pollution. We reveal that race and ethnicity are much stronger indicators of exposure disparity than income. Our study further demonstrates that within-group variation contributes a major portion to exposure disparities, suggesting more granular mitigation plans are needed to target high-exposure individuals from socially disadvantaged groups in addition to generic air quality improvement.

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Fig. 1: Spatial distribution of predicted PM2.5 concentrations and number of trips destined in the Bronx.
Fig. 2: Street-level mean exposure in the Bronx and their cumulative distributions by income and race and/or ethnicity.
Fig. 3: The comparison between mobility- and residence-based exposure.
Fig. 4: Distributions of absolute and relative exposure disparities.

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Data availability

The air quality predictions, exposure by street segment, exposure by individual trajectory and exposure disparity measures data are publicly available via Zenodo at https://doi.org/10.5281/zenodo.11044847 (ref. 54). The personal mobility data were obtained from Cuebiq through their social impact and Data for Good program. They were analyzed under a strict data privacy agreement between the authors and the company and, therefore, are not publicly available. Interested parties can request access to this mobility dataset, with more information, from https://spectus.ai/social-impact/.

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Acknowledgements

This study was funded by the MIT Senseable City Lab Consortium (Dubai Future Foundation, Toyota, UnipolTech, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Volkswagen Group America, FAE Technology, MipMap, GoAigua, Shell, ENEL Foundation, Kyoto University, SMART – Singapore-MIT Alliance for Research and Technology, Weizmann Institute of Science, Universidad Autónoma de Occidente, Instituto Politecnico Nacional, Imperial College London, Università di Pisa, KTH Royal Institute of Technology and the AMS Institute). The study was conducted with the support of the Center for Climate-Smart Transportation, Johns Hopkins University, the NYC Office of Technology and Innovation, NYC Department of Health, NYC Department of Citywide Administrative Services, and the Spectus Social Impact team. Specifically, we thank S. Johnson from the New York City Department of Health, and E. Ilten and B. Lake from Cuebiq for their continuous help in air quality and mobility data acquisition and usage.

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  1. These authors contributed equally: Iacopo Testi, An Wang.

Authors and Affiliations

  1. Senseable City Lab, Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA

    Iacopo Testi, An Wang, Sanjana Paul, Simone Mora, Fábio Duarte, Paolo Santi & Carlo Ratti

  2. Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China

    An Wang

  3. Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway

    Simone Mora

  4. School of Public Health, Brown University, Providence, RI, USA

    Erica Walker

  5. School of Engineering and Architecture, University College Cork, Cork, Ireland

    Marguerite Nyhan

  6. Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa, Italy

    Paolo Santi

  7. ABC Department, Politecnico di Milano, Milan, Italy

    Carlo Ratti

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Contributions

I.T. was involved in the conceptualization, writing of the paper, methodology and data acquisition. A.W. was involved in conceptualization, writing of the paper, methodology, data acquisition and supervision. S.P. was involved in the writing of the paper. S.M. was involved in supervision and project management. E.W. was involved in the methodology and writing of the paper. M.N. was involved in the methodology and writing of the paper. F.D. was involved in writing of the paper and supervision. P.S. was involved in the methodology, writing of the paper and supervision. C.R. was involved in supervision and funding acquisition.

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Correspondence to An Wang or Simone Mora.

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Nature Cities thanks Yuzhou Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Testi, I., Wang, A., Paul, S. et al. Big mobility data reveals hyperlocal air pollution exposure disparities in the Bronx, New York. Nat Cities 1, 512–521 (2024). https://doi.org/10.1038/s44284-024-00093-x

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