Effects of using different exposure data to estimate changes in premature mortality attributable to PM and O in China.

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM) and ozone (O) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM and O in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM and O using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142-159) to 308 (CI95: 213-241) thousands from 2014 to 2018 by using different concentration data, while O-related premature mortality increases by 67 (CI95: 26-104) to 103 (CI95: 40-163) thousands. The estimated mean changes are up to 40% different for the PM-related mortality, and up to 30% for the O-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 10 people/km, mostly located in Central China, for both PM and O. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.