利用高分辨率卫星数据改进华北地区近地面臭氧数值模拟的研究

Uncertain emission inventories may impair the accuracy of ground-level ozone modeling and mislead the control policy development. Using satellite-measured data via inverse modeling to constrain emissions can identify biases and reduce uncertainties in the current emission inventory. Studies on inverse modeling of nitrogen oxides (NOx) or volatile organic compounds (VOCs) using space-based observations, at global or continental-scale, have become prevalent in recent years. However, applications of satellite NO2 and HCHO data-based inversions to regulatory air quality modeling at regional scales, especially to the heavily polluted northern region of China have rarely been explored. In this study, a discrete Kalman filter approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-Decoupled Direct Method (DDM) model to adjust both NOx and VOCs emissions in north China using Ozone Monitoring Instrument (OMI)-measured NO2 and HCHO data. The influence of satellite-derived NOx and VOCs emissions on simulating ozone formation, transport and trend, and on developing optimized control measures will be further analyzed, in order to provide more reliable abatement strategies for ground-level ozone pollution in North China.

污染源排放清单中的不确定性会影响近地面臭氧模拟结果的准确性，并对相关控制措施的制定产生误导。以卫星遥感观测数据为基准通过反演方法得到的排放清单能够很好的反映出现有源清单中的偏差，从而降低源清单中的不确定性。应用卫星数据反演NOx或VOCs排放清单的相关研究近些年来已在一定程度上开展，但多集中在全球或大区域尺度。基于中区域尺度针对我国华北地区NOx和VOCs排放清单的协同反演,及其对臭氧模拟影响的研究工作仍然较少。本课题将应用OMI卫星观测的高分辨率NO2和HCHO数据，通过卡尔曼滤波与区域空气质量模型CAMx-DDM相结合的方法，对我国华北地区NOx和VOCs的排放清单进行协同反演，并研究反演前后的排放清单对模拟近地面臭氧的成因、传输和演变态势，以及通过敏感因子建立的源汇定量关系优化NOx和VOCs协同控制情景的影响，为华北地区臭氧污染研究和治理提供更可靠的科学依据。

污染源排放清单中的不确定性会影响近地面臭氧模拟结果的准确性，并对相关控制措施的制定产生误导。以卫星遥感观测数据为基准通过反演方法得到的排放清单能够很好的反映出现有源清单中的偏差，从而降低源清单中的不确定性。应用卫星数据反演NOx或VOCs排放清单的相关研究近些年来已在一定程度上开展，但多集中在全球或大区域尺度。基于中区域尺度针对我国华北地区NOx和VOCs排放清单的协同反演,及其对臭氧模拟影响的研究工作仍然较少。本课题应用OMI卫星观测的高分辨率NO2和HCHO数据，通过卡尔曼滤波与区域空气质量模型CAMx-DDM相结合的方法，对我国华北地区NOx和VOCs的排放清单进行协同反演，结果表明基准NOx源清单高估了排放大概30-70%左右，VOCs源清单高估了排放大概10-20%左右。反演后清单同时提高了NO2和O3的模拟精度。