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The sixth Coupled Model Intercomparison Project (CMIP6) scenarios provide opportunities to explore global climate and pollution mitigation pathways with socioeconomic features, but they might be limited on regional-scale projections due to inadequate consideration of local policies. Here, we simulated China's PM2.5 air quality with local policy-based scenarios (Dynamic Projection for Emissions in China (DPEC)) and the CMIP6 scenarios. We found both emission inventories can reproduce China's base-year PM2.5 and chemical aerosols while using DPEC emissions could better match in-situ observations. In addition, DPEC mitigation scenarios can better capture China's PM2.5 decline during 2015-2019 (22% under SSP2-45-policy and 30% under SSP1-26-best) with observations (~28%) than CMIP6 emissions. With the effects of current-year bias and inadequate considerations of pollution control policies, PM2.5 projections in 2030 and 2050 with CMIP6 mitigation scenarios are 42%-48% (9-13 µg/m3) and 59%-73% (8-12 µg/m3) higher than projections with DEPC. Our study suggests the community should incorporate more region-specific environmental policy in future scenario designs. Plain Language Summary Global emission scenarios might be limited on regional-scale air quality projections because of inadequate consideration of local environmental policy. Here, we simulated China's air quality variations through 2050 with global emission data sets and local policy-based emission scenarios. Both global and local emissions can reasonably estimate China's air quality; however, estimations with local emission scenarios are more correlated with surface observations and can better capture China's rapid air quality improvement during 2015-2019. Local policy deficiencies and current year bias further make future air quality projections driven by global emission scenarios 42%-73% higher than driven by local policy-based scenarios. Our findings could offer insights for the research community to incorporate more detailed regional information in future global scenario designs, which might help to better investigate the climate change impacts and improve global scenario applicability to regional scales. [ABSTRACT FROM AUTHOR]