Estimating short-term mortality and economic benefit attributable to PM10 exposure in China based on BenMAP

Abstract

With the rapidly booming economy, China has been suffering from serious particulate matter (PM) pollution in recent years. In order to improve the air quality, Chinese government issued a new China National Ambient Air Quality Standard (No. GB3095-2012) in 2012. In this study, PM exposure level was simulated based on the data of 912 newly constructed monitoring sites and Voronoi Neighborhood Averaging (VNA) interpolation method. It is widely accepted that PM can cause short-term health effects. We calculated the short-term health benefit due to decreasing PM concentration to the levels of China National Ambient Air Quality Standard based on Environmental Benefits Mapping and Analysis Program (BenMAP). Our results indicated that if the daily average concentration of PM reduced to the daily Grade II standard (150 μg/m), the avoided deaths for all cause, cardiovascular disease, and respiratory disease would be 82,000 (95%CI: 49,000-120,000), 56,000 (95%CI: 34,000-78,000), and 16,000 (95%CI: 10,000-22,000) in 2014, respectively. The economic benefits of avoiding deaths due to all cause for rolling back the concentration of PM to the level of 50 μg/m were estimated to be 240 billion CNY and 16 billion CNY using willingness to pay (WTP) and human capital (HC) methods, respectively, which accounted for 0.38% (95%CI: 0.11-0.64%) and 0.03% (95%CI: 0.02-0.03%) of the total annual gross domestic product (GDP) of China in 2014.

Estimation of health risk and economic loss attributable to PM2.5 and O3 pollution in Jilin Province, China

“…Moreover, we estimated the spatial distribution of health burden and economic losses with a 10-km resolution using GIS. In this process, PM 2.5 and population data with a 1-km resolution were converted to an identical resolution, which may potentially obscure or overestimate the benefit estimates 69 . Finally, when calculating health burden and economic losses, we assumed a static population in the study region even though actual exposure is typically dynamic, which may result in underestimated results 70 .…”