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A Multi-Pollutant Air Quality Analysis with Environmental Justice Considerations: Case Study for Detroit

Author

Listed:
  • Hui Yuan

    (Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China)

  • Ji-Cheng Jang

    (Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China)

  • Shicheng Long

    (Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China)

  • Yun Zhu

    (Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China)

  • Shuxiao Wang

    (State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China)

  • Jia Xing

    (Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996, USA)

  • Bin Zhao

    (State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China)

Abstract

Over the last two decades, substantial studies have been conducted to assess the feasibility of a multi-pollutant strategy for managing air quality in the United States. Given the inherent complexity of multi-pollutant air quality challenges, including fine particulate matter (PM 2.5 ), ozone (O 3 ), and air toxics, this paper undertook a multi-pollutant analysis at both national and local levels. Our analysis incorporated O 3 and PM 2.5 concentrations, air toxics that increase the risk of cancer, environmental justice (EJ) data, emissions data, and monitoring data. Initially, we identified counties across the continental U.S. with heightened multi-pollutant exposures and EJ concerns. Subsequently, a case study within the Detroit metropolitan area was conducted, revealing a clear overlap between multi-pollutant and EJ issues, underscoring the disproportionate burden on disadvantaged communities. The analysis of detailed emissions data unveiled potential co-control benefits in this region. Lastly, employing a proximity analysis method, we assessed environmental issues surrounding points of interest such as monitoring sites and emissions sectors, in the Detroit metropolitan area. The results demonstrated that monitoring sites with the highest monitoring value, alongside top-ranked emissions sectors such as electric utilities, coke ovens, and iron and steel production, were likely to exhibit elevated air pollutant concentrations/risks and associated EJ concerns in their vicinity.

Suggested Citation

  • Hui Yuan & Ji-Cheng Jang & Shicheng Long & Yun Zhu & Shuxiao Wang & Jia Xing & Bin Zhao, 2024. "A Multi-Pollutant Air Quality Analysis with Environmental Justice Considerations: Case Study for Detroit," Sustainability, MDPI, vol. 16(16), pages 1-16, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:6931-:d:1455251
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    References listed on IDEAS

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    2. Jing Zhao & Laura Gladson & Kevin Cromar, 2018. "A Novel Environmental Justice Indicator for Managing Local Air Pollution," IJERPH, MDPI, vol. 15(6), pages 1-13, June.
    3. Aubree Driver & Crystal Mehdizadeh & Samuel Bara-Garcia & Coline Bodenreider & Jessica Lewis & Sacoby Wilson, 2019. "Utilization of the Maryland Environmental Justice Screening Tool: A Bladensburg, Maryland Case Study," IJERPH, MDPI, vol. 16(3), pages 1-21, January.
    4. Veronica J. Berrocal & Alan E. Gelfand & David M. Holland, 2012. "Space-Time Data fusion Under Error in Computer Model Output: An Application to Modeling Air Quality," Biometrics, The International Biometric Society, vol. 68(3), pages 837-848, September.
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