Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California

Tianjun Lu, Yisi Liu, Armando Garcia, Meng Wang, Yang Li, German Bravo-villasenor, Kimberly Campos, Jia Xu and Bin Han
Additional contact information
Tianjun Lu: Department of Earth Science and Geography, California State University, Dominguez Hills, Carson, CA 90747, USA
Yisi Liu: Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
Armando Garcia: Department of Earth Science and Geography, California State University, Dominguez Hills, Carson, CA 90747, USA
Meng Wang: Department of Epidemiology and Environmental Health, School of Public and Health Professions, University at Buffalo, Buffalo, NY 14214, USA
Yang Li: Department of Environmental Science, Baylor University, Waco, TX 76798, USA
German Bravo-villasenor: Department of Earth Science and Geography, California State University, Dominguez Hills, Carson, CA 90747, USA
Kimberly Campos: Department of Earth Science and Geography, California State University, Dominguez Hills, Carson, CA 90747, USA
Jia Xu: State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Bin Han: State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

IJERPH, 2022, vol. 19, issue 14, 1-16

Abstract: Assessing exposure to fine particulate matter (PM 2.5 ) across disadvantaged communities is understudied, and the air monitoring network is inadequate. We leveraged emerging low-cost sensors (PurpleAir) and engaged community residents to develop a community-based monitoring program across disadvantaged communities (high proportions of low-income and minority populations) in Southern California. We recruited 22 households from 8 communities to measure residential outdoor PM 2.5 concentrations from June 2021 to December 2021. We identified the spatial and temporal patterns of PM 2.5 measurements as well as the relationship between the total PM 2.5 measurements and diesel PM emissions. We found that communities with a higher percentage of Hispanic and African American population and higher rates of unemployment, poverty, and housing burden were exposed to higher PM 2.5 concentrations. The average PM 2.5 concentrations in winter (25.8 µg/m 3 ) were much higher compared with the summer concentrations (12.4 µg/m 3 ). We also identified valuable hour-of-day and day-of-week patterns among disadvantaged communities. Our results suggest that the built environment can be targeted to reduce the exposure disparity. Integrating low-cost sensors into a citizen-science-based air monitoring program has promising applications to resolve monitoring disparity and capture “hotspots” to inform emission control and urban planning policies, thus improving exposure assessment and promoting environmental justice.

Keywords: exposure assessment; low-cost sensing; public engagement; traffic-related air pollution; environmental inequality (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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