Fast optimization of the emission reduction pathways of major air pollutants in China: From the perspective of different decision preferences

Abstract

To address the concern of optimization problem of China’s PM_2.5 control and the limitation of computational efficiencies for traditional air quality models, we developed an integrated analysis framework to efficiently establish the identification and cost-benefit assessment of PM_2.5 control pathways in China by constructing a rapid PM_2.5 exposure response method based on the high-order decoupled direct method (HDDM) and coupling the sequential least square algorithm (SLSQP) and health impact assessment model. Six emission reduction scenarios with varying decision preferences were analyzed. Our study provides a methodological approach for the rapid optimization of emission pathways of major air pollutants in China with flexible options in terms of objectives and constraints, fully considering the diverse differences in environmental, health, and economic impacts among different pollution sources simultaneously. Our findings based on the multi-scenario analysis strengthen the understanding of the importance of diverse species and regions for emission reduction among various decision preferences in China, confirm the necessity of implementing differentiated control strategies for distinct pollution sources from both cost and cost-effectiveness perspectives, and indicate that accelerating PM_2.5 control process in the early stage is a beneficial choice for achieving more health benefits.