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Inhalation intake of ambient air pollution in California's South Coast Air Basin

Author

Listed:
  • Marshall, Julian D.
  • Granvold, Patrick W.
  • Hoats, Abigail S.
  • McKone, Thomas E.
  • Deakin, Elizabeth
  • Nazaroff, William W.

Abstract

Reliable estimates of inhalation intake of air pollution and its distribution among a specified population are important for environmental epidemiology, health risk assessment, urban planning, and environmental policy. We computed distributional characteristics of the inhalation intake of five pollutants for a group of ~25,000 people (~29,000 person-days) living in California’s South Coast Air Basin. Our approach incorporates four main inputs: temporally resolved information about people’s location (latitude and longitude), microenvironment, and activity level; temporally and spatially explicit model determinations of ambient concentrations; stochastically determined microenvironmental adjustment factors relating the exposure concentration to the ambient concentration; and, age-, gender-, and activity-specific breathing rates. Our study is restricted to pollutants of outdoor origin, i.e. it does not incorporate intake in a microenvironment from direct emissions into that microenvironment. Median estimated inhalation intake rates (μgd-1) are 53 for benzene, 5.1 for 1,3-butadiene, 8.7x10-4 for hexavalent chromium in fine particulate matter (Cr-PM2.5), 30 for diesel fine particulate matter (DPM2.5), and 68 for ozone. For the four primary pollutants studied, estimated median intake rates are higher for non-whites and for individuals in low-income households than for the population as a whole. For ozone, a secondary pollutant, the reverse is true. Accounting for microenvironmental adjustment factors, population mobility and temporal correlations between pollutant concentrations and breathing rates affects the estimated inhalation intake by 40% on average. The approach presented here could be extended to quantify the impact on intakes and intake distributions of proposed changes in emissions, air quality, and urban infrastructure.

Suggested Citation

  • Marshall, Julian D. & Granvold, Patrick W. & Hoats, Abigail S. & McKone, Thomas E. & Deakin, Elizabeth & Nazaroff, William W., 2006. "Inhalation intake of ambient air pollution in California's South Coast Air Basin," University of California Transportation Center, Working Papers qt92w972mb, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt92w972mb
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    References listed on IDEAS

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    1. Manuel Pastor & James L. Sadd & Rachel Morello‐Frosch, 2004. "Waiting to Inhale: The Demographics of Toxic Air Release Facilities in 21st‐Century California," Social Science Quarterly, Southwestern Social Science Association, vol. 85(2), pages 420-440, June.
    2. Marshall, Julian David, 2005. "Inhalation of Vehicle Emissions in Urban Environments," University of California Transportation Center, Working Papers qt97b7s3cs, University of California Transportation Center.
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    2. Margaux Sanchez & Albert Ambros & Maëlle Salmon & Santhi Bhogadi & Robin T. Wilson & Sanjay Kinra & Julian D. Marshall & Cathryn Tonne, 2017. "Predictors of Daily Mobility of Adults in Peri-Urban South India," IJERPH, MDPI, vol. 14(7), pages 1-16, July.
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    4. Houston, Douglas & Ong, Paul & Jaimes, Guillermo & Winer, Arthur, 2011. "Traffic exposure near the Los Angeles-Long Beach port complex: using GPS-enhanced tracking to assess the implications of unreported travel and locations," University of California Transportation Center, Working Papers qt17w613sw, University of California Transportation Center.
    5. Raoul S. Liévanos, 2019. "Racialized Structural Vulnerability: Neighborhood Racial Composition, Concentrated Disadvantage, and Fine Particulate Matter in California," IJERPH, MDPI, vol. 16(17), pages 1-24, September.
    6. Zhaoping Hu & Le Huang & Xi Zhai & Tao Yang & Yaohui Jin & Yanyan Xu, 2023. "Quantifying Individual PM 2.5 Exposure with Human Mobility Inferred from Mobile Phone Data," Sustainability, MDPI, vol. 16(1), pages 1-15, December.
    7. Houston, Douglas & Ong, Paul & Jaimes, Guillermo & Winer, Arthur, 2011. "Traffic exposure near the Los Angeles–Long Beach port complex: using GPS-enhanced tracking to assess the implications of unreported travel and locations," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1399-1409.
    8. Davis, Coray & Jha, Manoj K., 2011. "A dynamic modeling approach to investigate impacts to protected and low-income populations in highway planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(7), pages 598-610, August.
    9. Martina S. Ragettli & Ming-Yi Tsai & Charlotte Braun-Fahrländer & Audrey De Nazelle & Christian Schindler & Alex Ineichen & Regina E. Ducret-Stich & Laura Perez & Nicole Probst-Hensch & Nino Künzli & , 2014. "Simulation of Population-Based Commuter Exposure to NO 2 Using Different Air Pollution Models," IJERPH, MDPI, vol. 11(5), pages 1-20, May.
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