摘要
自2013年起中国空气质量虽改善,但华北平原(NCP)重污染仍存在且二次污染加剧,而人们对其成因和变化了解有限.本研究利用2018-2022年数据,借助CMAQ模型探讨此污染响应.结果显示,在2018-2022年间,PM_(2.5)浓度显著下降31%-37%,O_(3)和NO_(2)的年下降速率分别为1%和0.5%SIA和SOA也显著减少,每年分别减少9%和6%PM_(2.5)主要因排放减少而下降,而O_(3)则受气象影响而波动.硫酸盐和铵下降的主因是减排,而硝酸盐对气象变化敏感排放和气象变化对SOA的总体减少同样重要,但人为SOA对排放控制敏感生物SOA易受气象变化影响.研究强调了控制人为排放对缓解NCP地区夏季二次污染的重要性.
Air quality in China has continued to improve since 2013,although severe pollution events still occur over the North China Plain(NCP).It is noticeable that contributions from secondary pollutants have increased,but understanding of their formation and variations with changing emissions and meteorological conditions remains limited.In this study,the warm season of May to September from 2018 to 2022 was selected to explore the response of secondary pollutants to meteorology and emissions using the Community Multi-scale Air Quality model(CMAQ).Fine particulate matter(PM_(2.5))concentrations over the NCP decreased significantly by 31%-37%from 2018 to 2022,while ozone(O_(3))and nitrogen dioxide(NO_(2))generally showed decreasing trends by 1%and 0.5%per year,respectively.Secondary inorganic aerosol(including sulfate,nitrate,and ammonium)and secondary organic aerosol(SOA)also decreased significantly,by 9%and 6%per year,respectively.The results showed that emissions contributed 96%to the decreases in PM_(2.5) concentrations,while O_(3) fluctuated due to meteorological changes.Although the decreases in sulfate and ammonium were mainly associated with emission reductions,that of nitrate was more sensitive to meteorological changes.Meteorological and emission changes were similarly important for the overall decrease in SOA,with anthropogenic SOA being more sensitive to emissions control,while biogenic SOA was more easily attributed to meteorological changes.This research emphasizes the importance of controlling anthropogenic emissions in relieving summer secondary pollution in the NCP region.
基金
This work was supported by the National Key R&D Program of China[grant number 2022YFC370110]
the National Natural Science Foundation of China[grant numbers 42077194,42061134008,and 42377098]
the Shanghai International Science and Technology Partnership Project[grant number 21230780200]
the Shanghai General Project[grant number 23ZR1406100].
