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Quantifying the Health Burden Misclassification from the Use of Different PM 2.5 Exposure Tier Models: A Case Study of London

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  • Vasilis Kazakos

    (School of Built Environment, University of Reading, Reading RG6 6DF, UK)

  • Zhiwen Luo

    (School of Built Environment, University of Reading, Reading RG6 6DF, UK)

  • Ian Ewart

    (School of Built Environment, University of Reading, Reading RG6 6DF, UK)

Abstract

Exposure to PM 2.5 has been associated with increased mortality in urban areas. Hence, reducing the uncertainty in human exposure assessments is essential for more accurate health burden estimates. Here, we quantified the misclassification that occurred when using different exposure approaches to predict the mortality burden of a population using London as a case study. We developed a framework for quantifying the misclassification of the total mortality burden attributable to exposure to fine particulate matter (PM 2.5 ) in four major microenvironments (MEs) (dwellings, aboveground transportation, London Underground (LU) and outdoors) in the Greater London Area (GLA), in 2017. We demonstrated that differences exist between five different exposure Tier-models with incrementally increasing complexity, moving from static to more dynamic approaches. BenMap-CE, the open source software developed by the U.S. Environmental Protection Agency, was used as a tool to achieve spatial distribution of the ambient concentration by interpolating the monitoring data to the unmonitored areas and ultimately estimating the change in mortality on a fine resolution. Indoor exposure to PM 2.5 is the largest contributor to total population exposure concentration, accounting for 83% of total predicted population exposure, followed by the London Underground, which contributes approximately 15%, despite the average time spent there by Londoners being only 0.4%. After incorporating housing stock and time-activity data, moving from static to most dynamic metric, Inner London showed the highest reduction in exposure concentration (i.e., approximately 37%) and as a result the largest change in mortality (i.e., health burden/mortality misclassification) was observed in central GLA. Overall, our findings showed that using outdoor concentration as a surrogate for total population exposure but ignoring different exposure concentration that occur indoors and time spent in transit, led to a misclassification of 1174–1541 mean predicted mortalities in GLA. We generally confirm that increasing the complexity and incorporating important microenvironments, such as the highly polluted LU, could significantly reduce the misclassification of health burden assessments.

Suggested Citation

  • Vasilis Kazakos & Zhiwen Luo & Ian Ewart, 2020. "Quantifying the Health Burden Misclassification from the Use of Different PM 2.5 Exposure Tier Models: A Case Study of London," IJERPH, MDPI, vol. 17(3), pages 1-21, February.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:3:p:1099-:d:318447
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    References listed on IDEAS

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    1. Dan Zhao & Parham Azimi & Brent Stephens, 2015. "Evaluating the Long-Term Health and Economic Impacts of Central Residential Air Filtration for Reducing Premature Mortality Associated with Indoor Fine Particulate Matter (PM 2.5 ) of Outdoor Origin," IJERPH, MDPI, vol. 12(7), pages 1-32, July.
    2. Daniela Dias & Oxana Tchepel, 2018. "Spatial and Temporal Dynamics in Air Pollution Exposure Assessment," IJERPH, MDPI, vol. 15(3), pages 1-23, March.
    3. Stuart Batterman & Janet Burke & Vlad Isakov & Toby Lewis & Bhramar Mukherjee & Thomas Robins, 2014. "A Comparison of Exposure Metrics for Traffic-Related Air Pollutants: Application to Epidemiology Studies in Detroit, Michigan," IJERPH, MDPI, vol. 11(9), pages 1-25, September.
    4. Wenjing Ji & Bin Zhao, 2015. "Estimating Mortality Derived from Indoor Exposure to Particles of Outdoor Origin," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
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    Cited by:

    1. Nuno Canha & Evangelia Diapouli & Susana Marta Almeida, 2021. "Integrated Human Exposure to Air Pollution," IJERPH, MDPI, vol. 18(5), pages 1-6, February.

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