长三角地区大气NO<sub>2</sub>和CO<sub>2</sub>浓度的时空变化及驱动因子分析

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摘要以长三角城市群为研究对象，利用卫星遥感观测数据协同分析长三角地区大气NO₂和CO₂浓度的时空变化特征和驱动因子，揭示了长三角地区污染物和CO₂高浓度地区空间格局.结果表明长三角城市群地区大气NO₂和CO₂浓度的时空分布及变化特征呈现了受化石燃料燃烧和机动车排放等人为活动以及区域地形、地表覆盖、气候等自然条件的综合影响结果.大气NO₂和CO₂高浓度值围绕太湖明显呈口对西南向的U字形分布，一致于围绕太湖分布的杭州、上海、苏州、无锡、常州和南京等大型城市区域，以及安徽铜陵地区的工业排放区.大气NO₂浓度值呈现秋冬时期较高，夏季最低的季节分布特征.大气CO₂浓度受植被CO₂吸收和CO₂的积累影响，8~9月最低，4~5月最高.此外，随着人为排放活动的急剧减少，2020年1~3月的大气NO₂浓度比2019年同时期降低了50%以上，其中分布了以钢铁厂、燃煤厂为主的大型工业热源的城市NO₂浓度下降最多，如镇江、南京、马鞍山.

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	何月
	绳梦雅
	雷莉萍
	郭开元
	贺忠华
	蔡菊珍
	方贺
	张小伟
	刘樱
	张育慧

关键词 ：大气污染, 人为排放, NO₂, CO₂, 协同分析, 长三角地区, 空间分布

Abstract：In this paper, with the Yangtze River Delta urban agglomerations as the study area, the satellite remote sensing data were used to carry out collaborative analysis on the temporal and spatial variations of atmospheric NO₂ and CO₂ concentrations and the driving factors, which revealed the areas with high concentrations of air pollution and CO₂. The results indicated that the spatio-temporal distributions of NO₂ and CO₂ and its changing characteristics in the Yangtze River Delta urban agglomeration areas were subjected to the combined effects of human activities such as fossil fuel combustion and vehicle emissions, as well as natural conditions such as regional topography, regional topography, surface coverage and climate. The areas with high concentrations of atmospheric NO₂ and CO₂ were in an U-shaped distribution towards the southwest direction around Taihu Lake, which was consistent with the distribution of the surrounding large urban areas and the industrial emission areas. Featured with seasonal distribution characteristics, the atmospheric NO₂ concentrations were higher in autumn and winter, and the lowest in summer. Affected by vegetation CO₂ uptake and CO₂ emission accumulation, atmospheric CO₂ concentrations were the lowest in August-September and the highest in April-May. In addition, with the sharp reduction in anthropogenic emission activities from January to March 2020, NO₂ concentrations were reduced by more than 50% compared with the same period in 2019 and dropped the most in cities with large-scale ferrous-metal and coal-processing industrial heat sources.

Key words： air pollution anthropogenic emission NO₂ CO₂ collaborative analysis the Yangtze River Delta spatial distribution

收稿日期: 2021-12-27

PACS:

X511

基金资助:中国气象局创新发展专项（CCSF202036）；浙江省自然科学基金（LQ21D050001，2017C33072，LDF18D050001）；中国气象局卫星专项（FY-3（03）-AS-12.13）；浙江省气象局重点项目（2019ZD08）

通讯作者: 雷莉萍,研究员,leilp@radi.ac.cn E-mail: leilp@radi.ac.cn

作者简介: 何月(1981-),女,浙江湖州人,高级工程师,主要从事生态环境及遥感应用研究.发表论文10余篇.

引用本文:

何月, 绳梦雅, 雷莉萍, 郭开元, 贺忠华, 蔡菊珍, 方贺, 张小伟, 刘樱, 张育慧. 长三角地区大气NO₂和CO₂浓度的时空变化及驱动因子分析[J]. 中国环境科学, 2022, 42(8): 3544-3553. HE Yue, SHENG Meng-ya, LEI Li-ping, GUO Kai-yuan, HE Zhong-hua, CAI Ju-zhen, FANG He, ZHANG Xiao-wei, LIU Ying, ZHANG Yu-hui. Driving factors and spatio-temporal distribution on NO₂ and CO₂ in the Yangtze River Delta. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(8): 3544-3553.

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