新颗粒生成和大气细颗粒物污染过程中的有机酸作用机制

目前，二次有机气溶胶（SOA）参与新颗粒生成和灰霾事件的机制仍然很不清楚。本项目拟以有机酸作为SOA的典型代表，研究长三角地区新颗粒生成和大气细颗粒物污染机制。通过持续采样和化学表征，研究有机酸及其相关前体物的分子分布和季节变化特征，并利用正矩阵因子分解法进行源解析。在线分析PM2.5有机酸含量和离线表征核模和凝结模颗粒物并重，进一步明确有机酸参与新颗粒形成和增长的机制。在秋冬季强化观测中，以TDMA在线测定亚微米颗粒物的真实含水率，回答ISORRPIA模型的“稳态”和“亚稳态”争论。以观测数据为基础开展实验室模拟研究，考察有机酸对大气细颗粒物吸湿性的影响。通过秋冬季城市站和背景站的强化观测和样品的理化表征，研究有机酸的来源和二次演化机制。结合气象条件和后向轨迹，探讨一次排放和二次转化、大气光氧化和液相反应、本地积累和长途传输的贡献。所得结果有助于深入揭示长三角大气细颗粒物污染的形成机制。

The role of secondary organic aerosol (SOA) during new particle formation events and PM2.5 pollution episodes remains unclear. As typical representatives of SOA, organic acids are measured in this project to investigate the role of organic acid in nucleation and initial growth of new particles in the Yangtze River Delta region, and in typical PM2.5 pollution episodes. Molecular distributions of organic acids and their related precursors are obtained through continuous sampling and characterization for all years. Seasonal variation of size-fractionated organic acid molecular distribution is discussed. Source apportionment of organic acids is analyzed by method of positive matrix factor. The mechanism of organic acids participating in the nucleation and initial growth of new particles is studied by online determination of PM2.5 and laboratory characterization of nucleation and condensation mode particles. During field campaign of autumn and winter, the water content of sub-micrometer particles is determined online using a TDMA to evaluate the assumption of "Metastable State" in the ISORRPIA model. Based on the observation data, hygroscopicity of mixture of inorganic salts and organic acids similar to the field samples is investigated in laboratory. The sources and secondary formation mechanism of organic acids in autumn and winter are investigated based on intensive campaigns in urban and background sites. The contributions of primary emissions and secondary formation, atmospheric photooxidation and aqueous-phase reaction, local accumulation and long-range transport are discussed in combined with meteorological parameters and backward trajectory. Our results will help to understand the formation mechanism of PM pollution episodes.