GEMS逐小时对流层NO_(2)产品数据质量评价与提升:以华东地区为例  

Quality Evaluation and Improvement of Hourly Tropospheric NO_(2) Data from GEMS:A Case Study in East China

作　　者：高鸿睿 秦凯[1] 何秦[1] 康俊亭 Gao Hongrui;Qin Kai;He Qin;Kang Junting(School of Environment and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,Jiangsu,China)

机构地区：[1]中国矿业大学环境与测绘学院,江苏徐州221116

出　　处：《光学学报》2024年第24期78-88,共11页Acta Optica Sinica

基　　金：国家自然科学基金(42375125)。

摘　　要：分别使用对流层监测仪(TROPOMI)和地基多轴差分吸收光谱仪(MAXDOAS)对地球静止环境监测光谱仪(GEMS)对流层二氧化氮(NO_(2))柱浓度进行对比验证。结果表明,GEMS对流层NO_(2)柱浓度产品与TROPOMI及地面观测结果均表现出较好的相关性,且其逐小时的观测优势能够更好地揭示空气污染过程的动态演变。进一步,针对GEMS产品数据在质量控制后空间覆盖度大幅降低的问题,采用基于经验正交函数的数据插值(DINEOF)方法进行缺失数据重构,从而提升该产品的应用价值。Objective Nitrogen dioxide(NO_(2)),the main component of nitrogen oxides(NOx),is an important air pollutant that can adversely affect human health and the environment.Satellite remote sensing monitoring offers nearrealtime,continuous,and largescale monitoring of atmospheric NO_(2).The geostationary environmental monitoring spectrometer(GEMS)aboard GK2B,launched in February 2020,is the world’s first satellite payload capable of monitoring atmospheric trace gases on an hourly scale.It provides tropospheric NO_(2) column densities in Asia and the Pacific during the daytime.In this study,we validate GEMS tropospheric NO_(2) column density products using observations from the TROPOspheric Monitoring Instrument(TROPOMI)and groundbased multiaxis differential optical absorption spectroscopy(MAXDOAS)to obtain more comprehensive results.These steps are essential prerequisites for applying quantitative remote sensing products.Furthermore,since satellite data coverage can be influenced by various factors,including cloud cover,which can drastically reduce the spatial coverage of the GEMS dataset after quality control,applying the data interpolating empirical orthogonal functions(DINEOF)method to the qualitycontrolled GEMS dataset significantly improves spatial coverage.This enables a more comprehensive assessment of tropospheric NO_(2) concentrations across the study area.Methods The datasets we used are satellitebased data from GEMS and TROPOMI and groundbased data from MAXDOAS(Xuzhou).In the data preprocessing phase,the satellite data are first screened by parameters such as cloud fraction to ensure the state and quality of the inversion results.Then,the bilinear interpolation method is applied to resample both GEMS and TROPOMI observation data into a 0.05°×0.05°grid.In the comparison with TROPOMI,the TROPOMI data are first averaged on a daily basis.Subsequently,the data from GEMS at 12:45 and 13:45(Beijing time)are selected for averaging,and the integrated dataset is used for correlation analysis.For the comparison wi

关 键 词：GEMS 地球静止卫星 NO_(2) 质量评价 对比验证 数据重构 

分 类 号：P237[天文地球—摄影测量与遥感]