二次有机气溶胶（SOA）在灰霾天气形成过程中具有重要作用，其中生物源挥发性有机物（BVOCs）对二元羧酸类SOA的贡献占主导地位。然而，目前关于BVOCs在二元羧酸类SOA的形成中的作用机制尚不清楚。本项目拟以华北地区典型高山森林（泰山）和地表城市（泰安）大气为研究对象，在夏季通过开展PM2.5同步采样，获得高山和地表大气中SOA的空间分布数据；分析高山自由对流层BVOCs的分子组成及浓度水平，阐明生物源对二元羧酸类SOA的贡献率及形成机制；利用后向轨迹与源解析模型，揭示地表城市人为污染物经长距离传输对高山自由对流层大气SOA分子组成的影响及其机理；通过对比灰霾天与清洁天二元羧酸类SOA的浓度与形成机制，查明不同污染条件下（灰霾天、清洁天）人为污染物对BVOCs形成二元羧酸类SOA的影响。为正确认识我国夏季灰霾的发生机理和科学治理提供依据，同时为全球SOA模式研究提供重要的基础数据资料。

Secondary organic aerosol (SOA) plays an important role in the process of haze. SOA derived from biogenic volatile organic compounds (BVOCs) dominates the atmospheric dicarboxylic acids and related SOA load. However, the forming mechanisms of dicarboxylic acids and related SOA derived from BVOCs are less well known to date. This proposed research will choose the mountainous background (Mt. Tai) atmosphere and surficial urban ( Tai’an City) atmosphere as an object in North China. This project will synchronously collect PM2.5 samples at forested and urban areas during the summer to investigate the spatial distribution of SOA in surficial and mountainous aerosol. The molecular compositions and concentration levels of BVOCs in the mountainous free tropospheric aerosol will be analyzed to elucidate the contribution rate and mechanisms of dicarboxylic acidsfrom biogenic sources. In addition, the effects and mechanisms of anthropogenic emissions in surficial urban areas by long-range transport on the molecular compositions of SOA of mountainous free tropospheric aerosol will be investigated using backward trajectory analysis and source analytical model. Also, the concentration levels and forming mechanisms of dicarboxylic acids and related SOA in haze days will be compared with those in clean days so as to pinpoint the effects of anthropogenic pollutants on the formation of dicarboxylic acids from BVOCs under different pollutional conditions (e.g. haze days, clean days). This project will provide new datasets for haze study and consulting information for scientific management in the summer in China as well as important theoretical and data information for modeling study of global SOA.