| Summary: | Summary: Background: Air pollution and its adverse effects on public health remain a considerable problem in China, where policies have been implemented to improve the situation. We aimed to estimate the disease burden associated with particulate matter (PM)2·5 across China for 2020 and 2030 to identify the populations and regions most at risk, quantify the health benefits of air quality improvement targets, and determine the effect of population growth and ageing on this disease burden. Methods: In this modelling study, we investigated premature deaths associated with PM2·5 across China on the basis of air quality scenarios proposed by the expert group involved in the formulation of the 13th Five-Year Plan for Eco-Environmental Protection and population scenarios based on the Shared Socioeconomic Pathways of the Intergovernmental Panel on Climate Change. We used the integrated exposure–response model used for the Global Burden of Disease Study to estimate the number of PM2·5-related premature deaths under each scenario. Findings: The projected health benefits of the air-quality-improving targets are substantial, and could reduce the number of PM2.5-related premature deaths in China by approximately 129 278 by 2020 and 217 988 by 2030, compared with 2010. However, since China's population is increasing and ageing, the number of PM2.5-related premature deaths was estimated to increase by 84 102 by 2020 and by 244 191 by 2030, indicating that the health benefits induced by air quality improvements could be offset by the effect of the population increasing in size and ageing. Interpretation: To reduce the future disease burden in China, targets that are stricter than the interim target and stringent policies to improve air quality and protect public health are needed, especially for at-risk population groups, such as older individuals (aged >55 years) and patients with cardiovascular diseases, particularly in regions with a high disease burden. Funding: National Key Research and Development Program of China, National Natural Science Foundation of China, Beijing Natural Science Foundation, National High-level Talents Special Support Plan of China for Young Talents, and Special Foundation of Basic Science and Technology Resources Survey of Ministry of Science and Technology of China.
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