Population-weighted exposure to PM2.5 pollution in China: An integrated approach

Environ Int. 2018 Nov:120:111-120. doi: 10.1016/j.envint.2018.07.042. Epub 2018 Aug 2.

Abstract

Fine particulate matter air pollution (PM2.5) is a major risk factor for premature death globally. Studies of the PM2.5 health burden usually treat exposure to ambient air pollution (AAP) and household air pollution from solid fuels (HAP) as separate risk factors. AAP and HAP can, however, be closely interrelated. Taking as the starting point that the total exposure to PM2.5 is what matters for health, and recognizing the curvilinear form of exposure-response functions for important health effects, we develop a method for estimating the total annual mean population-weighted personal exposure, denoted integrated population-weighted exposure (IPWE). To establish the IPWE in China, we used recent emission inventories, Chemical Transport Models, China Census data on population and residential fuel use, and estimates of the PM2.5 exposure among solid fuel users. We found an IPWE of 151 [123-179] μg/m3, of which 62-74% was attributable to residential solid fuels through HAP exposure and the residential sector emissions' contribution to AAP. We found large disparities in the PM2.5 exposure burden, with an estimated IPWE in rural populations nearly twice the level in urban populations. Using the IPWE metric, we estimated that 1.15 [1.09-1.19] million premature deaths were attributable to PM2.5 exposure annually in the period 2010-2013. Using the same data set, but calculating premature deaths from AAP and HAP in isolation, the estimated number was nearly 50% higher. The IPWE metric enables integration across AAP and HAP in policy analyses and could mitigate the concern of a potential double counting of the health burden that may arise from treating AAP and HAP as separate health risk factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants / analysis*
  • Air Pollution* / analysis
  • Air Pollution* / statistics & numerical data
  • China / epidemiology
  • Environmental Exposure* / analysis
  • Environmental Exposure* / statistics & numerical data
  • Humans
  • Particulate Matter / analysis*
  • Rural Population / statistics & numerical data
  • Urban Population / statistics & numerical data

Substances

  • Air Pollutants
  • Particulate Matter