基于OCO-3卫星观测的上海CO<sub>2</sub>柱浓度特征分析

李英松; 贾梦唯; 江飞

引用本文:	李英松,贾梦唯,江飞.基于OCO-3卫星观测的上海CO₂柱浓度特征分析[J].环境监控与预警,2023,15(5):84-89
	LI Yinsong,JIA Mengwei,JIANG Fei.Spatial and Temporal Characteristics of Carbon Dioxide in Shanghai Based on OCO-3 Satellite Observations[J].Environmental Monitoring and Forewarning,2023,15(5):84-89

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基于OCO-3卫星观测的上海CO₂柱浓度特征分析
李英松¹，贾梦唯^1*，江飞^1,2,3
1.南京大学，国际地球系统科学研究所，江苏南京 210023；2.江苏省地理信息资源开发与应用协同创新中心，江苏南京 210023；3.南京大学，关键地球物质循环前沿科学中心，江苏南京 210023

摘要:

随着卫星遥感技术的发展，城市内部的二氧化碳柱浓度（XCO₂）时空特征逐渐能够被识别。本研究基于轨道碳观测卫星（OCO-3）快拍（SAM）模式XCO₂观测数据，探讨了上海市2020—2022年XCO₂的时空分布特征以及该数据对于火电厂CO₂烟羽信号来源识别的能力。结果表明，上海市XCO₂呈现春季＞冬季＞夏季的特征，上海市XCO₂年均值为418.3×10^-6，高于华东地区的年平均值。从XCO₂空间分布差异来看，中部和东北部是上海冬季XCO₂的高值区域，这主要是由于城市中部人口密集，北部沿江区域大型电厂较为集中，在冬季盛行风西北风的作用下，CO₂被传输至东部沿江多个行政区域。此外，结合近地面风场、CO₂人为排放清单、电厂点源信息、对流层监测仪器（TROPOMI）卫星观测数据等，证实了OCO-3快拍模式具有探测到重点点源信号的能力。

关键词: 轨道碳观测卫星3 快拍模式上海市二氧化碳柱浓度点源识别

DOI：10.3969/j.issn.1674-6732.2023.05.012

分类号:X831

基金项目:国家重点研发项目（2021YFB3901001）

Spatial and Temporal Characteristics of Carbon Dioxide in Shanghai Based on OCO-3 Satellite Observations

LI Yinsong¹， JIA Mengwei^1*，JIANG Fei^1,2,3

1.Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology， International Institute for Earth System Science， Nanjing University， Nanjing， Jiangsu 210023， China； 2.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application， Nanjing， Jiangsu 210023， China；3.Frontiers Science Center for Critical Earth Material Cycling， Nanjing University， Nanjing， Jiangsu 210023， China

Abstract:

With the development of satellite remote sensing technology， the spatial and temporal characteristics of CO₂column concentration（XCO₂）within the city can be recognized gradually. Based on the Orbiting Carbon Observing Satellite（OCO-3）Snapshot Area Map（SAM） mode， this study investigated the spatial and temporal distribution characteristics of XCO₂ in Shanghai from 2020 to 2022 and the potential of the data to identify the source of CO₂ plume signals from power plants. The results showed that the volume fraction of XCO₂ in Shanghai was characterized by spring＞winter＞summer， with an annual average of 418.3×10^-6， which is higher than in developed East China. From the spatial distribution differences of XCO₂， the central and northeastern regions are the high value areas of winter XCO₂ in Shanghai，mainly due to the dense population in the central part of the city， and large power plants are concentrated along the river in the northern of the city， so the CO₂ was transported to several administrative districts in the east by the prevailing northwesterly winds in winter. In addition， combining the near-surface wind field， CO₂ anthropogenic emission inventory， power plant information， and Tropospheric Monitoring Instrument（TROPOMI） satellite observation data， this study confirmed that the OCO-3 SAM mode is capable of detecting key source signals.

Key words: OCO-3 SAM mode Shanghai XCO₂ Point source identification