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基于Sentinel-5P卫星的中国NO_(2)浓度遥感监测 被引量:3

Monitoring atmospheric NO_(2)concentrations in China based on Sentinel-5P satellite products
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摘要 NO_(2)是重要的痕量气体,对其监测有助于大气污染治理.本文基于Sentinel-5P大气污染监测卫星提供的对流层NO_(2)浓度数据和总NO_(2)浓度数据,借助谷歌地球引擎(google earth engine,GEE)分析了2018~2021年间中国大气NO_(2)浓度时空变化特征,使用OLS模型揭示了中国地区NO_(2)浓度的主要影响因子.结果表明:我国对流层NO_(2)浓度空间分布呈现东高西低的总体格局,东中部城市群对流层NO_(2)柱浓度水平明显呈现冬高夏低、春秋过渡的季节特征,西部大部分城市的四季变化不明显.北京、深圳、上海3所城市NO_(2)柱浓度分布呈现出较为显著的圈层结构.OLS模型结果表明,中国地区NO_(2)浓度变化受到社会经济和自然因素的共同影响,其中城市化程度是影响NO_(2)排放的重要因子. NO_(2)is an important trace gas and its monitoring contributes to air pollution control.Based on the tropospheric vertical column and total vertical column of NO_(2)provided by the Sentinel-5P air pollution monitoring satellite,we analyzed spatial-temporal characteristics of NO_(2)in China during 2018~2021 by Google Earth Engine(GEE)and revealed the main drivers of NO_(2)concentration using OLS model.Results showed that there were a spatial pattern with high in the east and low in the west regarding the tropospheric vertical column of NO_(2)in China.A seasonal pattern with high in winter,low in summer and excessive in spring and autumn,was presented in the eastern and central city clusters and Urumqi city.The western cities,however,had less significant changes within seasons.The concentration distribution of tro NO_(2)in Beijing,Shanghai and Shenzhen showed a significant circle structure.The OLS model results showed that the atmospheric NO_(2)concentration in China was influenced collectively by socio-economic and natural factors,with the degree of urbanization being the critical factor driving NO_(2)emissions.
作者 刘怡阳 颉耀文 郭泽呈 LIU Yi-yang;XIE Yao-wen;GUO Ze-cheng(College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China)
出处 《中国环境科学》 EI CAS CSCD 北大核心 2022年第11期4983-4990,共8页 China Environmental Science
基金 中国科学院战略性先导科技专项A类(XD2009000003)。
关键词 NO_(2) 对流层柱浓度 总大气柱浓度 Sentinel-5P NO_(2) tropospheric vertical column total vertical column Sentinel-5P
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