城市边界层NO3自由基垂直分布探测及其时空梯度效应研究

作为大气氧化性的核心物种，NO3自由基对痕量气体去除、二次气溶胶生成和日间自由基源汇等关键大气化学过程均有重要意义。虽已普遍认识到NO3浓度随高度有显著差异，但由于观测资料匮乏，目前关于我国真实大气条件下NO3自由基浓度及反应体系的高度依赖特征的探讨十分有限，其在大气氧化性与复合污染中的角色作用如何亟待研究。本项目以北京城区为典型环境，开展以多光路主动DOAS技术为基础的塔基观测，量化表征NO3浓度垂直分布特征与时间变化规律；结合曙暮光时段的柱浓度信息，探讨日出/落前后关键时段边界层结构变化与NO3浓度梯度的作用关系；基于化学模型计算，识别不同高度上NO3生成与损耗的关键路径，揭示其浓度梯度结构及时间演化对二次污染过程的影响，旨在回答城市群大气复合污染成因中关于夜间化学的共性基础问题。该研究可有效弥补NO3垂直梯度资料的空白，并在完善大气自由基化学、污染防治的科学决策中发挥积极重要作用。

As the core substance of atmospheric oxidation capacity, NO3 radical is important for the critical chemical processes in the atmosphere, such as the removal of trace gases, formations of secondary aerosol, and budgets of daytime radicals. Although it is widely recognized that the concentration of NO3 varies significantly with altitude, due to lack of observational data, the altitude-dependent characteristics of NO3 concentration and related reaction system for the real atmospheric conditions in China are very rarely discussed, while its role in the atmospheric oxidation capacity and complex air pollution is urgent to be investigated..In this study, the tower-based field measurements utilizing multi-paths active DOAS technique will be carried out in the urban area of Beijing city as the typical environment. Afterwards, the vertical distribution of NO3 concentration and its temporal variations should be quantitatively characterized. Combined the information of column density during twilight period, the impacts of the evolution of boundary layer structure on the NO3 concentration gradients during the critical period before and after sunrise/fall will be explored. Based on the chemical model calculation, the key paths of NO3 production and loss are identified for different heights, and the influences of the concentration gradients structure and temporal evolution on the secondary pollution processes will be further revealed, which is aiming to answer the common basic question on nighttime chemistry in the causes of atmospheric complex pollution in urban agglomeration areas. This study can effectively fill the gap in NO3 vertical gradient data, and also play an important role in the better knowledge of atmospheric radical chemistry and the scientific decision-making of pollution prevention.