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

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 disadvanta...

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Autores principales: Lu, Tianjun, Liu, Yisi, Garcia, Armando, Wang, Meng, Li, Yang, Bravo-villasenor, German, Campos, Kimberly, Xu, Jia, Han, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322770/
https://www.ncbi.nlm.nih.gov/pubmed/35886628
http://dx.doi.org/10.3390/ijerph19148777
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author Lu, Tianjun
Liu, Yisi
Garcia, Armando
Wang, Meng
Li, Yang
Bravo-villasenor, German
Campos, Kimberly
Xu, Jia
Han, Bin
author_facet Lu, Tianjun
Liu, Yisi
Garcia, Armando
Wang, Meng
Li, Yang
Bravo-villasenor, German
Campos, Kimberly
Xu, Jia
Han, Bin
author_sort Lu, Tianjun
collection PubMed
description 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.
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spelling pubmed-93227702022-07-27 Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California Lu, Tianjun Liu, Yisi Garcia, Armando Wang, Meng Li, Yang Bravo-villasenor, German Campos, Kimberly Xu, Jia Han, Bin Int J Environ Res Public Health Article 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. MDPI 2022-07-19 /pmc/articles/PMC9322770/ /pubmed/35886628 http://dx.doi.org/10.3390/ijerph19148777 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lu, Tianjun
Liu, Yisi
Garcia, Armando
Wang, Meng
Li, Yang
Bravo-villasenor, German
Campos, Kimberly
Xu, Jia
Han, Bin
Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California
title Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California
title_full Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California
title_fullStr Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California
title_full_unstemmed Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California
title_short Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California
title_sort leveraging citizen science and low-cost sensors to characterize air pollution exposure of disadvantaged communities in southern california
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322770/
https://www.ncbi.nlm.nih.gov/pubmed/35886628
http://dx.doi.org/10.3390/ijerph19148777
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