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华北地区气溶胶光学厚度时空分布特征研究

Research on spatial and temporal distribution characteristics of aerosol optical depth in North China
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摘要 华北地区一直是我国颗粒物污染最严重的地区之一,深入研究该地区近年来气溶胶光学厚度(AOD)空间分布和时间变化特征,能够为其环境治理提供决策支持。文章基于2014—2019年VIIRS IP 550 nm的AOD数据,系统分析了华北地区AOD的时空演化与空间分异特征。结果表明:2014—2019年,华北地区AOD月均差异较大,6~8月其值最大,1、12月其值最小;“十三五”期间,天津、济南、郑州、石家庄的AOD均值会出现明显下降,其中石家庄的下降幅度最大为18.5%,天津的下降幅度最小为3.4%,北京的AOD年均值增长率为0.2%,但始终保持较低水平;华北地区AOD空间分布受人为影响明显,呈南高北低的格局,高值区分布在河北南部、山东西部和河南北部,低值区则主要在河北北部和山西。 North China has always been one of the most serious areas of particulate matter pollution in China.By studying the spatial and temporal distribution characteristics of aerosol optical depth(AOD),the decision support for environmental governance can be provided Based on the AOD data of 550 nm of VIIRS IP from January 2014 to December 2019,the spatio-temporal evolution characteristics of AOD in the study area were systematically analyzed using North China as the study area.The results show that the monthly average of AOD in North China from 2014 to 2019 varies greatly,with the largest AOD value from June to August,the smallest AOD value in January and December.And then,during the 13th Five-Year Plan period,the average AOD of Tianjin,Jinan,Zhengzhou and Shijiazhuang dropped significantly,with the largest drop of 18.5%in Shijiazhuang and the smallest drop of 3.4%in Tianjin.the average annual growth rate of AOD in Beijing was 0.2%,but remained relatively low.Finally,the spatial distribution of AOD in North China is obviously influenced by anthropogenic influences,with a pattern of high-south and low-north,high-value areas in southern Hebei,western Shandong and northern Henan,while low-value areas are mainly found in northern Hebei and Shanxi provinces.
作者 孟飞 郭霖 MENG Fei;GUO Lin(School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China)
出处 《山东建筑大学学报》 2021年第2期9-15,共7页 Journal of Shandong Jianzhu University
基金 国家自然科学基金项目(41271413) 山东省自然科学基金项目(ZR2018MD008)。
关键词 VIIRS IP 气溶胶光学厚度 华北地区 时空变化 VIIRS IP aerosol optical depth North China spatial-temporal variation
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