The establishment of Air Quality Health Index in China: A comparative analysis of methodological approaches

Abstract

Background: The Air Quality Index (AQI) has been criticized because it does not adequately account for the health effect of multi-pollutants. Although the developed Air Quality Health Index (AQHI) is a more effective communication tool, little is known about the best method to construct AQHI on long time and large spatial scales.

Objectives: To further evaluate the validity of existing approaches to the establishment of AQHI on both long time and larger spatial scales.

Methods: By introducing 3 approaches addressing multi-pollutant exposures: cumulative risk index (CRI), supervised principal component analysis (SPCA), and Bayesian multi-pollutants weighted model (BMP), we constructed CRI-AQHI, SPCA-AQHI, BMP-AQHI and standard-AQHI on cardiovascular mortality in China from 2015 to 2019 at both the national and geographic regional levels. We further assessed the performance of the four methods in estimating the joint effect of multi-pollutants by simulations under various scenarios of pollution effect.

Results: The results of national China showed that the BMP-AQHI improved the goodness of fit of the standard-AQHI by 108.24%, followed by CRI-AQHI (5.02%), and all AQHIs performed better than AQI, consistent with 6 geographic regional results. In addition, the simulation result showed that the BMP method provided stable and relatively accurate estimations of the short-term combined effect of exposure to multi-pollutants.

Conclusions: AQHI based on BMP could communicate the air pollution risk to the public more effectively than the current AQHI and AQI.

Keywords: Air quality health index; Air quality index; Bayesian multipollutant weighted model; Cumulative risk index; Supervised principal component analysis.