不同排放源对华东地区PM2.5影响的数值模拟

使用中尺度气象-化学耦合模式WRF-Chem针对MEIC源清单中五大部门来源（工业源、电力源、民用源、交通源和农业源）对华东地区PM_2.5的影响进行了模拟研究，主要得到以下结论：春夏秋季PM_2.5约40%~60%来源于工业源，冬季由于采暖供热燃用大量散烧煤，导致民用源对PM_2.5的贡献最大，在山东、安徽和江苏省等高值区贡献率超过50%；农业源、电力源和交通源对PM_2.5影响的季节差异不大，农业源贡献约20%~30%，交通源和火电源贡献约10%.因此冬季需主要控制民用源排放，春夏秋季主要控制工业源排放，其次是农业源排放.一次PM_2.5在工业、电力和民用源贡献的PM_2.5中所占比例可达50%~60%；NO₃^-和NH+4在交通源贡献的PM_2.5中总比例可达53%，在农业源中总比例高达93%；由于模式对SO₄^2-模拟偏低，SO₄^2-在工业源和电力源贡献的PM_2.5中占比约5%~15%；OC对来自民用源的PM_2.5有30%的贡献，BC对来自交通源的PM_2.5有15%的贡献；Na⁺和Cl^-对PM_2.5的贡献在各大来源中均低于3%.

Impact of different emission sources on PM2.5 over East China based on numerical study

The meso-scale meteorology-chemistry coupled model WRF-Chem was used to simulate the contribution of different emission sources in MEIC inventory (industry, power, residential, transportation and agricultural) to PM_2.5 over east China. The conclusions are as follows:Industry contributed about 40%~60% PM_2.5 in spring, summer and autumn, while residential contributes the largest in winter due to the use of scattered coal for heating, with over 50% in the areas such as Shandong, Anhui and Jiangsu province. The contributions from agriculture, power and transportation to PM_2.5 have minor seasonal differences, in which about 20%~30% from agriculture, about 10% from transportation and power plant. It may indicate that we should mainly regulate residential source in winter, and limit the emission of industry and agriculture in other seasons. The contribution of primary PM_2.5 from coal-based industry, residential and power plant are about 50%~60%, and the contribution of NO₃^- and NH₄⁺ from transportation and agriculture could be up to 53% and 93%, respectively. The contribution of SO₄^2- from industry and power plant is only about 5%~15% which is possibly underestimated due to under-predicted sulfate by the model. The contribution of OC from residential, BC from transportation and Na⁺ and Cl^- from all major sources to the total PM_2.5 is about 30%, 15%, and less than 3%, respectively.