PM2.5 Exposure and Associated Premature Mortality to 2100 in China Under Climate and Socioeconomic Change Scenarios

Abstract

Abstract Reducing PM2.5‐related premature mortality is essential for health‐related sustainable development. China, one of the most populated and PM2.5 polluted developing countries in the world, is striving to be in the vanguard for meeting this target. However, the global chemical transport methods for future PM2.5 projections are difficult to use and computationally expensive and may import measurement uncertainty into regional exposure assessments, thus bringing challenges to policy making. Here, we proposed an integrated PM2.5 projection model framework based on regional land use, emission, climate and population simulations. The ambient PM2.5 exposure and associated premature mortality to 2100 in China at a scale of 10 × 10 km were projected and compared under different development pathways. Ambient PM2.5 exposure is expected to peak in recent decades (2030–2060) with mean values ranging from 32.72 to 35.11 μg/m3 for different pathways, while associated premature mortality are projected to decrease (2273.9–778.59) (in thousands) over time (2030–2100). The change in the emission scenario with significant CH4 and NMVOC increases could lead to the greatest increase in average PM2.5 exposure (4.03 μg/m3), while the decrease (−0.90 μg/m3) was linked to BC, SO2, CH4, and NMVOC decreases. Meanwhile, premature deaths decrease (15–226,424) for most projection periods when land use, emissions, and population data were separately replaced with RCP2.6‐SSP1 data. Land use impacts in socioeconomic change scenarios could be moderate in certain regions. Therefore, the sustainable development pathway of the RCP2.6‐SSP1 scenario should be prioritized in China for future development considering both environmental protection and health sustainability.

Keywords

• particulate matter
• health burden
• scenario simulation
• manageable factors
• sensitivity analysis