Global Effect Factors for Exposure to Fine Particulate Matter.

Peter Fantke,Joshua S Apte,Thomas E McKone,Nicole Illner,Ernani F Choma,John S Evans,Marko Tainio,Julian D Marshall,Olivier Jolliet,Katerina S Stylianou

doi:10.1021/acs.est.9b01800

Abstract

We evaluate fine particulate matter (PM2.5) exposure–response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure–response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure–response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure–response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

Highlights

We evaluate fine particulate matter (PM2.5) exposure− response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments
We evaluate fine particulate matter (PM2.5) exposure− response models to propose a consistent set of global effect factors across spatial scales and across urban and rural environments for use in product and policy assessments, such as life cycle impact assessment (LCIA) and health impact assessment (HIA)
We proposed a consistent set of global effect factors that can be combined with human intake fractions[39] in support of comparative assessments that are relevant to a broad range of emission and related exposure situations, applicable to a diverse number of populations, cities, and countries, and applicable for different levels of spatial aggregation

Summary

Introduction

Exposure to PM2.5 is the leading environmental contributor to human disease burden, with more than seven million deaths globally attributed to ambient and household PM2.5 exposure in 2015.1 The influence of exposure to PM2.5 on mortality rates became clear with the “Harvard Six Cities” study in 1993.2 The effect seen was so large that a second, larger, study was conducted involving more than 500 000 subjects from 151 communities within the United States. This American Cancer Society (ACS) study,[3] published in 1995, confirmed the relationship between exposure to PM2.5 and mortality rates for concentrations and composition of PM2.5 in the United States with an effect size roughly one-third as large as that found in the Six Cities study.

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Conclusion