Quantitative estimation of air pollutant emission rate based on urban atmospheric load index
MEI Mei1,2,3, XU Da-hai4, ZHU Rong3, WANG Zong-shuang5
1. Chinese Academy of Meteorological Sciences, Beijing 100081, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. National Climate Center, Laboratory for Climate Studies of China Meteorological Administration, Beijing 100081, China;
4. State Key Laboratory of Severe Weather&Key Laboratory of Atmospheric Chemistry of China Meteorological Administration, Chinese Academy of Meteorological Sciences, Beijing 100081, China;
5. Enviromental Standard Institute, China Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Based on observed PM2.5 concerntration data and atmospheric self-cleaning ability index (ASI) calculated by meteorological observation data, the change of pollutant emission rate per capita during two periods by applying urban atmospheric load index was analyzed. Meanwhile, the effects of meteorological condition and emission reduction on the change of air pollutant concentration during Sep. 2013 to Feb. 2019 were investigated. The emission reduction in autumn and winter was more obvious than that in spring and summer. The effect initially appeared in autumn and winter of 2014 due to emission reductions occurred in 74.5% cities, and on average emission reduction was 12.6% in this area. Emission reduced substantially in the autumn and winter of 2017 and 2018 in major cities of Beijing-Tianjin-Hebei and its surrounding areas, with emission reduction rate being 54.0% and 47.7% respectively relative to the baseline. Emission of autumn-winter in Changzhi during 2014~2017 was more than that in baseline, and started to decline in 2018. The change of emission rate in Shijiazhuang presented large fluctuation, and it in winter of 2016 was 68.2% more than that in 2014. Hence, special attention should be paid to these two cities. Urban atmospheric load index can objectively and quantitatively reflect the direction and magnitude of the change of emission rate in typical emission reduction periods, so it is an effective method to evaluate the effects of meteorological conditions and emission control measures on pollutant concentration change.
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