引用本文:楼振纲,蔡哲,夏峥,唐志伟,贺亚南,江飞.基于OCO-2卫星观测的浙江省典型城市CO2柱浓度变化特征及碳排放重点源识别应用[J].环境监控与预警,2023,15(5):90-95
LOU Zhengang,CAI Zhe,XIA Zheng,TANG Zhiwei,HE Yanan,JIANG Fei.Characteristics of CO2 Column Concentration of Typical Cities in Zhejiang Province and Application Examples of Key Carbon Emission Sources Based On OCO2 Satellite Observation[J].Environmental Monitoring and Forewarning,2023,15(5):90-95
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基于OCO-2卫星观测的浙江省典型城市CO2柱浓度变化特征及碳排放重点源识别应用
楼振纲1,蔡哲2*,夏峥1,唐志伟2,贺亚南2,江飞3
1.浙江省生态环境监测中心,浙江 杭州 310012;2.南京创蓝科技有限公司,江苏 南京 211135;3.南京大学,国际地球系统科学研究所,江苏 南京 210046
摘要:
为有效制定城市层面的低碳发展政策,实现碳达峰的发展目标,利用碳卫星2号(OCO-2)监测的高分辨率大气CO2柱浓度数据(XCO2),分析浙江省杭州、宁波和嘉兴3个典型城市的XCO2变化特征,以及人类活动和XCO2变化的关系;识别城市碳排放热点区域,评估碳排放热点源对XCO2的影响,并利用拉格朗日粒子扩散模型(LPDM)进行验证。结果表明:(1)2016—2021年3个城市的XCO2年增长量分别为3.1×10-6,2.3×10-6和2.2×10-6,杭州的增长量最为明显;杭州和宁波在2019—2021年XCO2增量明显,分别为8.0×10-6和5.7×10-6。杭州XCO2的变化趋势与临安大气本底站CO2观测数据的变化趋势一致。(2)与2017年相比,3个城市的建筑用地面积都略有增加,分别增加了0.9%,2.2%和4.8%;从人口和GDP数据来看,2016—2021年3个城市也均呈持续增加的变化趋势。表明CO2浓度升高与人类活动密切相关。(3)XCO2正距平高值区域基本都对应了碳排放热点源(电力企业)的下风向地区,电力企业CO2的排放会导致下风向地区的XCO2出现局地性增长,增量为7×10-6~9×10-6
关键词:  碳卫星2号  二氧化碳  拉格朗日粒子扩散模型  碳排放热点  浙江省
DOI:10.3969/j.issn.1674-6732.2023.05.013
分类号:X87
基金项目:国家重点研发计划项目(2020YFA0607504);浙江省生态环境科研和成果推广项目(2022XM0055)
Characteristics of CO2 Column Concentration of Typical Cities in Zhejiang Province and Application Examples of Key Carbon Emission Sources Based On OCO2 Satellite Observation
LOU Zhengang1, CAI Zhe2*, XIA Zheng1, TANG Zhiwei2, HE Yanan2, JIANG Fei3
1.Zhejiang Ecological and Environmental Monitor Center, Hangzhou,Zhejiang 310012,China; 2.Nanjing Climblue Technology Co.,Ltd.,Nanjing,Jiangsu 211135,China; 3.International Institute for Earth System Science, Nanjing University,Nanjing,Jiangsu 210046,China
Abstract:
In this paper, to effectively formulate city level low carbon development policies and provide scientific basis for achieving carbon peak,the high resolution XCO2 column concentration data monitored by OCO2 satellite were used to analyze the XCO2 column concentration variation characteristics of Hangzhou, Ningbo and Jiaxing, which are the typical cities in Zhejiang Province. The relationship between the changes of human activities and XCO2 column concentration was analyzed. The Lagrange Particle Diffusion Model(LPDM) was adopted to evaluate the influence of carbon emission hotspots on XCO2 column concentrations, and to identify the urban carbon emission hotspots. The results showed that:(1) The annual increases of XCO2 concentration in the three cities from 2016 to 2021 were 3.1×10-6, 2.3×10-6 and 2.2×10-6, respectively. Hangzhou had the most pronounced increase. XCO2 concentration increased significantly in Hangzhou and Ningbo from 2019 to 2021, with an increment of 8.0×10-6 and 5.7×10-6 ,respectively. The change trend of Hangzhou XCO2 is consistent with the change trend of Lin an atmospheric CO2 observation data. (2) Compared with 2017, the construction land area of Hangzhou, Ningbo and Jiaxing in 2021, increased slightly, increasing by 0.9%, 2.2% and 4.8% respectively. For the perspective of population and GDP data, Hangzhou, Ningbo and Jiaxing also showed a continuous increase trend from 2016 to 2021, indicating that elevated CO2 concentrations were closely related to human activities. (3) The XCO2 column concentration is basically corresponding to the downwind area of the carbon emission hotspot source(power enterprise), and the greenhouse gas emissions of the power enterprise will lead to a local increase in the concentration of XCO2 column in the downwind area, with increase between 7×10-6 ~ 9×10-6.
Key words:  OCO-2 Satellite  CO2  Lagrange Particle Diffusion Model(LPDM)  Carbon emission hotspot  Zhejiang Province