摘要
气态二甲胺(DMA)是大气新粒子生成的关键前体物,然而对其来源与空气和气候效应仍存在巨大争议.本研究率先对中国大气DMA浓度开展了南北跨区域与城市内部的走航观测.发现亚热带森林植物的DMA排放浓度可能南方远高于北方,同时记录到由工业脉冲排放所导致的全球最高大气DMA浓度.在高度城市化的上海地区,DMA浓度自市中心向外围逐渐降低且与人口密度关联.源排放的直接测试进一步表明中国区域和城市内部的大气二甲胺都深受非农业源排放的影响.大气化学传输模式也证实,居民DMA排放主导了上海城市大气颗粒物数浓度的贡献.该研究将外场观测、源排放测试与模型模拟相结合,呈现了中国大气二甲胺的全生命周期,为颗粒物污染防治和气候变化评估提供了有用参考.
Gas-phase dimethylamine(DMA)has recently been identified as one of the most important vapors to initiate new particle formation(NPF),even in China's polluted atmosphere.Nevertheless,there remains a fundamental need for understanding the atmospheric life cycle of DMA,particularly in urban areas.Here we pioneered large-scale mobile observations of the DMA concentrations within cities and across two pan-region transects of north-to-south(~700 km)and west-to-east(~2000 km)in China.Unexpectedly,DMA concentrations(mean±1σ)in South China with scattered croplands(0.018±0.010 ppbv,1 ppbv=10~(-9)L/L)were over three times higher than those in the north with contiguous croplands(0.005±0.001 ppbv),suggesting that nonagricultural activities may be an important source of DMA.Particularly in non-rural regions,incidental pulsed industrial emissions led to some of the highest DMA concentration levels in the world(2.3 ppbv).Besides,in highly urbanized areas of Shanghai,supported by direct source-emission measurements,the spatial pattern of DMA was generally correlated with population(R~2=0.31)due to associated residential emissions rather than vehicular emissions.Chemical transport simulations further show that in the most populated regions of Shanghai,residential DMA emissions can contribute for up to 78%of particle number concentrations.Shanghai is a case study for populous megacities,and the impacts of nonagricultural emissions on local DMA concentration and nucleation are likely similar for other major urban regions globally.
作者
常运华
凌清扬
盖鑫磊
袁相洋
周升钱
程凯
毛鉴炯
黄丹丹
胡磬遥
鲁君
崔世杰
高雅琴
陆轶群
朱亮
谭稳
郭松
胡敏
王红丽
黄成
黄汝锦
张远航
胡建林
Yunhua Chang;Qingyang Ling;Xinlei Ge;Xiangyang Yuan;Shengqian Zhou;Kai Cheng;Jianjiong Mao;Dandan Huang;Qingyao Hu;Jun Lu;Shijie Cui;Yaqing Gao;Yiqun Lu;Liang Zhu;Wen Tan;Song Guo;Min Hu;Hongli Wang;Cheng Huang;Ru-Jin Huang;Yuanhang Zhang;Jianlin Hu(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,NUIST Center on Atmospheric Environment,Nanjing University of Information Science&Technology(NUIST),Nanjing 210044,China;Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control,Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science&Technology,Nanjing 210044,China;State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China;Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention,Department of Environmental Science and Engineering,Fudan University,Shanghai 200433,China;State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex,Shanghai Academy of Environmental Sciences,Shanghai 200233,China;TOFWERK China,Nanjing 211800,China;State Key Joint Laboratory of Environmental Simulation and Pollution Control,College of Environmental Sciences and Engineering,Peking University,Beijing 100871,China;State Key Laboratory of Loess and Quaternary Geology,Center for Excellence in Quaternary Science and Global Change,Key Laboratory of Aerosol Chemistry&Physics,Institute of Earth and Environment,Chinese Academy of Sciences,Xi’an 710061,China)
基金
supported by the National Key Research&Development Program of China(2022YFC3701000)
the National Natural Science Foundation of China(41975166 and 42175135)
Jiangsu Natural Science Fund for Excellent Young Scholars(BK20211594)
the Science and Technology Commission of the Shanghai Municipality(20ZR1447800)。