基于被动DOAS网的我国东部大气污染物时空演变、输送及区域性特征研究

Regional air pollution formation is closely related to the three-dimensional distribution, accumulation and regional transport of the tropospheric pollutants. By now, due to the limitation of the three-dimensional detection technology, the long-term and systemic data of the temporal and spatial distribution of atmospheric pollutants is insufficient. Based on the ground-based passive DOAS monitoring network, some subjects will be researched as followed. The parameterized inversion method of temporal and spatial distribution of atmospheric pollution gases and aerosol as well as the network-based observation method of regional pollution transport are researched. Tropospheric column density of atmospheric trace pollution gases (such as SO2, NO2, HCHO) and aerosol as well as their vertical distribution will be observing for a long time in eastern China including the pan-yangtze river delta and the cities of Beijing, Guangzhou. By means of this observation, seasonal and annual variation of atmospheric pollutions as well as their spatial distribution, regional characteristics and evolution regularity will be researched. Through the combination of observation, simulation and analysis, some purposes will be accomplished, which include systematically acknowledging the regularity of atmospheric pollution regional transport, analyzing the relationship between regional pollution formation and the aspects like meteorological condition, transport pathway and emission source, recognizing the interaction of local and regional pollutions and its impact to local environment. The Research results will be not only conducive to identify temporal and spatial distribution of atmospheric pollution and its development tendency, further estimate its impact to regional environment, human health and ecological system in eastern China, but also provide basic scientific data for our national researches such as tropospheric chemistry, pollution model, satellite validation and emissions inventory.

区域大气污染的形成与对流层大气污染物立体分布、积累和区域输送有密切关系，目前由于立体探测手段的限制，十分缺乏长期系统的大气污染物时空分布数据。本研究利用已建立的地基被动DOAS网，突破并建立大气污染气体和气溶胶垂直总量/分布、区域污染输送的组网观测方法；在长三角、北京、广州等我国东部地区，开展目前尚缺乏的关键气态污染物SO2、NO2、HCHO、HONO等以及气溶胶对流层柱浓度及垂直分布观测，揭示东部地区大气污染物的日/周/季节/年际时间演变规律、空间/区域性特征;分析典型污染过程下污染物的垂直结构特征及影响因素；通过观测、卫星和模型相结合，阐明区域污染形成与污染排放、输送、气象条件间的关系，揭示局地与区域间的相互作用。研究结果不仅为我国对流层化学、污染模型、卫星遥感校验等研究提供坚实的科学数据基础，而且有助于认识我国东部地区污染时空特征和发展趋势，为政府制定大气污染治理政策提供科学支撑。

区域大气污染的形成与对流层大气污染物立体分布、积累和区域输送有密切关系，本项目基于自主研发的被动DOAS技术建立了我国东部地区大气痕量成分立体观测网，着重研究我国东部地区大气污染物的时空演变、输送及区域性特征。研发了具有自主知识产权基于最优估算的反演算法—PriAM，实现了对痕量气体及气溶胶立体信息的稳定、灵敏和快速反演；针对我国重霾污染，攻克了云层和高浓度气溶胶污染影响DOAS观测路径及大气质量因子的难题，建立了可鉴别低空云和气溶胶类型的方法，PriAM算法已成为国际上MAX-DOAS数据处理的主要算法之一，国际对比表明与德国HRIPRO等算法反演的廓线相关性达0.97以上；基于通量模型和误差理论，建立了污染气体输送通量方法及通量误差评估模型，解决了区域输送定量获取的难题；通过京津冀、长三角、CINDI-2等综合外场实验，验证了设备稳定性及反演算法的可靠性。基于上述方法率先建立我国东部地区被动DOAS立体观测网并开展了长期观测，建立了2016-2020年覆盖京津冀、长三角、珠三角和沿海区域在内的12个站点连续5年的 NO2、SO2、HCHO及气溶胶的长期立体分布数据库，填补了我国痕量气体立体分布监测数据的空白。我国东部地区NO2、SO2、HCHO及气溶胶时空分布总体呈现内陆地区高于沿海地区的区域特征；污染气体和气溶胶呈现出随高度指数下降的分布特征（污染气体主要分布在1km以内、气溶胶主要分布在1.5km以内）；针对重点区域重污染过程，通过MAX-DOAS、卫星观测结合模型对东部地区大气重污染过程成因进行模拟，分析了区域污染形成与局地、输送、气象条件间的关系。.京津冀及周边地区是长三角大气污染的重要外围因素，气溶胶污染输送贡献为20%，输送集中在1km-2km内；NO2和HCHO分别源于局地排放和前体物生成；静稳及高湿（>80%）是重污染形成的天气条件，加剧了空气质量恶化。本项目为我国对流层化学、污染模型、卫星遥感校验等研究提供了立体监测数据，为环保部门制定京津冀及长三角区域污染联防联控政策提供了科学支撑。