Assessing public health and economic loss associated with black carbon exposure using monitoring and MERRA-2 data

Abstract

Black carbon (BC) exposure in China continues to be relatively high, prompting researchers to assess BC exposure levels using data from monitoring sites, satellite remote sensing, and models. However, data regarding the application of a combined strategy comprising the analysis of monitoring data and various types of data to simulate BC exposure levels are lacking. Hence, the current study seeks to estimate short- and long-term BC exposure levels by combining national monitoring data with data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2). Furthermore, this study attempts to improve the spatio-temporal resolution of BC exposure levels using Bayesian maximum entropy (BME). The BME model performed well in terms of estimating short- (R2 = 0.74 and RMSE = 1.76 μg/m3) and long-term (R2 = 0.76 and RMSE = 1.3 μg/m3) exposure. Premature mortalities and economic losses were also assessed by applying localised concentration–response coefficients simulated in China. A total of 74,500 (95% confidence interval (CI): 23,900–124,500) and 538,400 (95% CI: 495,000–581,300) all-cause premature mortality cases were found to be associated with short- and long-term BC exposure, respectively. Meanwhile, short-term BC exposure was associated with economic losses ranging from 7.5 to 13.2 billion US dollars (USD) (1 USD = 6.36 RMB on January 19, 2022) based on amended human capital (AHC) and willingness to pay (WTP), accounting for 0.06%–0.1% of China's total gross domestic product (GDP) in 2017 (1.2 × 104 billion USD), respectively. The economic losses for long-term exposure varied from 53 to 93.2 billion USD based on AHC and WTP, accounting for 0.4%–0.8% of China's total GDP in 2017, respectively.