京津冀地区硝酸盐气溶胶形成机理模式研究

Fine particulate nitrate aerosol, which is the major chemical composition of PM2.5 (Particulate matter with aerodynamic diameter equal or less than 2.5μm), plays a more and more important role in the formation and evolution of the regional haze. It is a difficult task for the Chinese government to effectively reduce the PM2.5 concentrations because the conversion mechanism of gaseous precursors to particulate nitrate is still unclear. The Beijing-Tianjin-Hebei region is famous for its big reaction vessel of nitrate formation, due to the enhanced nitrogen oxides emissions from mobiles and high oxidant concentrations of ozone, nitrogen peroxide, and OH radical. This project tries to improve the CAMx model and use it to research the chemical conversion mechanism of fine particulate nitrate aerosols. The CAMx model is updated by including additional HONO sources, improved VOCs emissions by OMI (Ozone Monitoring Instrument) measurements from satellite, and coupled with detailed chemical conversion modules including both homogeneous and heterogenous reactions for nitrate formation. Field measurement data would be used to evaluate the simulated skill for nitrate. The whole year of 2010 is selected as modeling period to evaluate the spatial evolution, seasonal and diurnal change, transformation process, and the impact factors during the formation of nitrate aerosols over the Beijing-Tianjin-Hebei region. The contributions of each related chemical reactions to nitrate aerosols under typical conditions are quantified by a probing tools named process analysis. The implement of this project would be helpful to enhance the accuracy of air quality numerical prediction, deepen the understanding of the formation mechanism of nitrate aerosols, and provide scientific support to effectively solve the problem of heavy haze pollution for the government.

硝酸盐气溶胶是大气细颗粒物PM2.5的重要化学组分，在区域性霾发生、发展过程中发挥着越来越重要的作用，而气态前体物向颗粒态硝酸盐化学转化机制认识不全面成为国家有效控制PM2.5污染的关键科学问题。本项目拟在NOx、NH3及O3浓度较高的京津冀地区，基于高时空分辨率CAMx模式，采用WRF模拟的气象场资料，引入HONO新增源，使用OMI卫星资料订正VOCs排放源；耦合更为精细的硝酸盐均相、非均相化学转化模块；采用观测资料评估CAMx模式改进效果；基于改进的CAMx模式研究京津冀地区颗粒态硝酸盐的时空演变规律、转化途径、转化过程及影响因素；运用过程分析技术，量化春夏秋冬、昼夜、霾演变过程中各转化途径对大气中颗粒态硝酸盐的贡献量。研究成果有助于深化对硝酸盐化学转化规律的认识，提高空气质量数值预报的准确性，为国家有效解决大气霾污染问题提供科学支撑。

硝酸盐气溶胶是大气细颗粒物PM2.5的重要化学组分，在区域性霾发生、发展过程中发挥着重要作用，而气态前体物向颗粒态硝酸盐化学转化机制认识不全面成为国家有效控制PM2.5污染的关键科学问题。本项目在NOx、NH3及O3浓度较高的京津冀地区，使用OMI卫星资料订正了VOCs排放源，并成功实现了HONO新增源模块(包括直接排放和非均相化学反应生成)、氮氧化物非均相化学反应模块与原有空气质量模式的耦合。通过与外场观测数据比对，对新增模块中的相关敏感因子参数化，使模式结果更好地反应真实大气中的情况。利用气象、空气质量监测数据对模式模拟的气象场和浓度场进行了有效评估，表明更新后的空气质量模式模拟大气OH自由基浓度的能力进一步提升，增强了模式中大气的化学反应活性；改变了以往数值模式普遍低估硝酸盐的情况。基于更新后的空气质量模式，分析了京津冀地区硝酸盐的空间及季节分布特征，研究了HONO新增源与N2O5非均相反应对硝酸盐生成的影响。针对PM2.5高污染事件研究了在PM2.5达到极值前的6小时内硝酸盐的化学转化途径、转化过程及地域、季节变化特征，并定量给出了各化学转化途径的贡献量。结果表明HONO新增源对硝酸盐的影响冬季最大，夏季最小。N2O5非均相反应对硝酸盐的影响正好相反，夏季最大，冬季最小。PM2.5浓度急剧升高的6小时内，北京南部、河北西南部地区冬季硝酸盐浓度快速增长主要来自于HONO新增源的贡献。PM2.5浓度急剧升高的初级阶段，河北西南部地区由HONO光解生成的OH自由基生成率超过1.5 μg m-3 h-1，导致了硝酸盐的快速增长。本研究结果有助于深化对硝酸盐化学转化规律的认识，提高空气质量数值预报的准确性，为国家有效解决大气霾污染问题提供科学支撑。