Modeling Urban-Rural health disparities using a Taxi-Based mobile atmospheric monitoring system

Abstract

The disparities of pollutant exposures and health burdens exists among regions. To capture the spatio-temporal variability of PM2.5 and analyze the inequity between urban and rural areas, this study developed a health impact assessment (HIA) model, which incorporates hyper-localized roadside PM2.5 concentration collected by a taxi-based mobile monitoring system. High-resolution pollutant concentrations, health risks, and PM2.5-related deaths were mapped to illustrate the spatio-temporal patterns among regions. The results showed that the average PM2.5 concentrations in some rural counties were higher than urban areas. 7.85%, 3.72%, 8.74%, and 0.97% of individuals were exposed to environment higher than the maximum concentration of central districts in winter, spring, summer, and autumn, respectively. The application of refined HIA model was discussed and grid cells with high risks of all-cause mortality, cardiovascular disease, respiratory disease, and lung cancer were identified. Establishing the comprehensive pollutant monitoring system facilitates targeted interventions and realization of health equity.