Leveraging integrated modeling methods to assess key technologies and predict air quality for synergistic pollution and carbon reduction in Beijing

Abstract As China’s capital, Beijing has significantly improved its air quality, yet the synergistic reduction of atmospheric pollutants and greenhouse gases remains a critical challenge. This study develops and applies a novel integrated modeling framework that couples the long-range energy alternatives planning system (Beijing), marginal abatement cost analysis, and the WRF-Chem air quality model. This approach simulates Beijing’s energy-emission pathways from 2030 to 2050, techno-economically evaluates 37 mitigation technologies, and quantifies their resultant air quality impacts. Our findings identify an enhanced energy mix scenario as optimal, achieving reductions of 59.29% in CO₂ and 81.34% in NO x . Key measures included battery-electric trucks (transportation), building envelope retrofits (buildings), and photovoltaic power expansion (electricity). The comprehensive implementation of selected technologies could lead to reductions in both PM 2.5 and NO 2 concentrations by 6% and 24%, respectively, although wintertime ozone levels would increase by 10%. The findings highlight the need to strengthen targeted end-of-pipe control measures for dust and volatile organic compounds alongside carbon reduction efforts, in order to maximize the co-benefits of climate change mitigation and air quality improvement.