Previous air pollution control strategies didn’t pay enough attention to regional collaboration and the spatial response sensitivities,resulting in limited control effects in China.This study proposed an effective PM_(2.5)and O_(3) control strategy scheme with the integration of Self-Organizing Map(SOM),Genetic Algorithm(GA)and WRF-CAMx,emphasizing regional collaborative control and the strengthening of control in sensitive areas.This scheme embodies the idea of hierarchical management and spatial-temporally differentiated management,with SOM identifying the collaborative subregions,GA providing the optimized subregion-level priority of precursor emission reductions,and WRF-CAMx providing response sensitivities for grid-level priority of precursor emission reductions.With Beijing-Tianjin-Hebei and the surrounding area(BTHSA,“2+26”cities)as the case study area,the optimized strategy required that regions along Taihang Mountains strengthen the emission reductions of all precursors in PM_(2.5)-dominant seasons,and strengthen VOCs reductions but moderate NOx reductions in O_(3)-dominant season.The spatiotemporally differentiated control strategy,without additional emission reduction burdens than the 14th Five-Year Plan proposed,reduced the average annual PM_(2.5)and MDA8 O_(3) concentrations in 28 cities by 3.2%-8.2% and 3.9%-9.7% respectively in comparison with non-differential control strategies,with the most prominent optimization effects occurring in the heavily polluted seasons(6.9%-18.0%for PM_(2.5)and 3.3%-14.2% for MDA8 O_(3),respectively).This study proposed an effective scheme for the collaborative control of PM_(2.5)and O_(3) in BTHSA,and shows important methodological implications for other regions suffering from similar air quality problems.
