A new scheme of PM_(2.5)and O_(3) control strategies with the integration of SOM,GA and WRF-CAMx

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.

A monitoring-modeling approach to SO_4^(2-) and NO_3^- secondary conversion ratio estimation during haze periods in Beijing, China

SO_4^(2-) and NO_3^- are important chemical components of fine particulate matter(PM_(2.5)),especially during haze periods.This study selected two haze episodes in Beijing,China with similar meteorological conditions.A monitoring-modeling approach was developed to estimate the secondary conversion ratios of sulfur and nitrogen based on monitored and simulated concentrations.Measurements showed that in Episode 1(24th–25th October,2014),the concentrations(proportions)of SO_4^(2-) and NO_3^- reached 35.1μg/m^3(14.9%) and 55.0μg/m^3(22.9%),while they reached 14.4μg/m^3(9.3%) and 59.1μg/m^3(38.1%)in Episode 2(26th–27th October,2017).A modeling system was applied to apportion Beijing's SO_4^(2-) and NO_3^- in primary and secondary SO_4^(2-)/NO_3^- emitted from local and regional sources.Thus,secondary conversion contributions considering the local and regional level were defined.The former primarily focused on Beijing atmospheric oxidation ability and the latter mainly considered the existence form of Beijing SO_4^(2-)/NO_3^- under the regional transport impacts.Finally,secondary oxidation ratios were estimated through combining secondary conversion contribution coefficients for simulated and monitored concentrations.At regional level,sulfur oxidation ratios in polluted(clean)days during two sampling periods were0.57–0.72(0.07–0.52)and 0.74–0.80(0.08–0.61),nitrogen oxidation ratios were 0.20–0.29(0.05–0.15)and 0.34–0.38(0.02–0.29),indicating that atmospheric oxidation was enhanced when considering regional transport through 2014–2017.At the local level,sulfur oxidation ratios were 0.66–0.71(0.04–0.48)in haze(clean)days,while nitrogen oxidation ratios were0.16–0.29(0.02–0.16).The atmospheric oxidation ability markedly increased in PM_(2.5)pollution days,but changed only slightly between the two periods.