PM_2.5 Exposure and Associated Premature Mortality to 2100 in China Under Climate and Socioeconomic Change Scenarios

Reducing PM_2.5-related premature mortality is essential for health-related sustainable development. China, one of the most populated and PM_2.5 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 PM_2.5 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 PM_2.5 projection model framework based on regional land use, emission, climate and population simulations. The ambient PM_2.5 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 PM_2.5 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 PM_2.5 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.