| 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） |
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| Spatial and Temporal Characteristics of Carbon Dioxide in Shanghai Based on OCO-3 Satellite Observations |
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LI Yinsong1， JIA Mengwei1*，JIANG Fei1,2,3
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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
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| 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 |
