Linking air quality, health, and economic effect models for use in air pollution epidemiology studies with uncertain factors

Abstract

Epidemiological studies have shown that premature mortality, hospital admission, and outpatient visits are closely related to particulate matter (PM) pollution. The modelling of air quality, assessment of human health impact, and estimation of health impact models are useful tools for assessing the impact of air pollution on health. This study proposes a model framework for assessing air pollution damage, including air quality simulation for PM10, assessment of human health impacts, and estimation of health impact models that meet the requirements of actual monitoring data. The novel contribution of this study is a proposal for the application of the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality Modeling System (CMAQ) model and the epidemiological coefficient β of concentration–response functions (CRFs), which were determined from epidemiological studies and selected in accordance with the study area conditions under limited conditions related to the field measurement data, to calculate the health impacts and economic losses caused by PM10. Calculation results for a typical month in 2017 showed that economic losses were approximately 125.119 million Vietnamese Dong (95% CI: −26.841, 272.633), in which the highest number of mortality and morbidity due to PM10 dust pollution exposure was identified on October 24, 2017. The WRF/CMAQ simulation results were calibrated and validated to improve the efficiency of the estimation. These validated results were mainly based on the measured data, which played a significant role in enhancing the accuracy of the quantification of air pollution effects.