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2006-2017年四川盆地MODIS气溶胶光学厚度时空变化特征
引用本文:王晨莹,何沐全,陈军辉,刘志红. 2006-2017年四川盆地MODIS气溶胶光学厚度时空变化特征[J]. 环境科学研究, 2020, 33(1): 54-62. DOI: 10.13198/j.issn.1001-6929.2019.07.24
作者姓名:王晨莹  何沐全  陈军辉  刘志红
作者单位:1.成都信息工程大学资源环境学院, 四川 成都 610225
基金项目:国家自然科学基金项目(No.41771535);四川省科技厅重大项目(No.2017SZ0169)
摘    要:四川盆地地形复杂、气候特殊,是我国颗粒物污染高发地.为探究四川盆地气溶胶分布和周期变化特征,深入认识气溶胶污染特性及其气候效应,结合卫星遥感探测方法,利用2006-2017年MODIS C006 3 km AOD(气溶胶光学厚度)产品,分析了四川盆地AOD的时空特征.结果表明:①MODIS AOD(MODIS数据反演的气溶胶光学厚度)与太阳光度计CE318观测的AOD、ρ(PM2.5)、ρ(PM10)线性相关系数分别为0.78、0.77、0.75,表明MODIS C006 3 km AOD产品适用于四川盆地颗粒物污染研究.②四川盆地AOD平均值范围为0.1~1.3,其中,成都平原和四川盆地东南部地区是AOD高值(AOD值>1.0)中心,四川盆地周边高海拔区AOD均小于0.3.③2006-2017年AOD年均值范围为0~2.5,整体呈"倒N型"曲线下降,其峰值和谷值分别出现在2013年和2017年;2013年AOD大于1.0的区域占四川盆地的34.1%,是12 a中颗粒物污染最重的一年;2017年AOD小于0.3的面积占57.1%.④AOD季节性变化呈春季最大、夏季次之、秋季最小的特征.⑤AOD月变化呈"双峰型"波动特征,AOD月均值范围为0~2.5,其中,2-5月AOD月均值均大于0.7,8月AOD月均值为0.6,11-12月AOD月均值均小于0.5.研究显示,四川盆地颗粒物污染防治应以成都平原城市群和四川省南部城市群为主,应重点控制细颗粒物排放,合理安排工业企业的周期性生产强度. 

关 键 词:MODIS   AOD   气溶胶   四川盆地   时空分布
收稿时间:2018-09-29
修稿时间:2019-07-03

Temporal and Spatial Variation Characteristics of MODIS Aerosol Optical Depth in Sichuan Basin from 2006 to 2017
WANG Chenying,HE Muquan,CHEN Junhui,LIU Zhihong. Temporal and Spatial Variation Characteristics of MODIS Aerosol Optical Depth in Sichuan Basin from 2006 to 2017[J]. Research of Environmental Sciences, 2020, 33(1): 54-62. DOI: 10.13198/j.issn.1001-6929.2019.07.24
Authors:WANG Chenying  HE Muquan  CHEN Junhui  LIU Zhihong
Affiliation:1.College of Resource and Environment, Chengdu University of Information Technology, Chengdu 610225, China2.Guangzhou Meteorological Satellite Ground Station, Guangzhou 510640, China3.Sichuan Academy of Eco-Environmental Sciences, Chengdu 610041, China
Abstract:The Sichuan Basin has complex terrain and special climate, which is a high-risk area for particulate pollution in China. In order to explore the aerosol distribution and periodic variation characteristics of the Sichuan Basin, and to better understand the aerosol pollution characteristics and its climatic effects, combined with the satellite remote sensing data, the 2006-2017 MODIS C006 3 km aerosol optical depth (AOD) product was used to analyze the temporal and spatial characteristics of aerosols in the Sichuan Basin. The linear correlation coefficients of MODIS AOD and AOD, ρ(PM2.5), and ρ(PM10) observed by the solar photometer CE318 were 0.78, 0.77, and 0.75, respectively, indicating that MODIS AOD products were suitable for studying the particulate matter pollution in Sichuan Basin. The cumulative average of AOD in the Sichuan Basin in the past 12 years was between 0.1 and 1.3. The Chengdu Plain and the southeastern Sichuan Basin were the AOD high-value centers. The values of the AOD high-value centers were greater than 1.0, and the AOD values of the high-altitude areas around the Sichuan Basin were less than 0.3. The average annual AOD fluctuated in the range of 0 to 2.5, showing a downward trend of 'inverted N type', in which peaks and valleys appeared in 2013 and 2017. In 2013, the area with AOD value greater than 1.0 accounted for 34.1% of the Sichuan Basin, which was the year with the heaviest particulate pollution in the past 12 years, while the area with AOD value less than 0.3 in 2017 accounted for 57.1%. The seasonal variation of AOD was the largest in spring, the second in summer, and the smallest in autumn. The monthly variation of AOD was 'double-peak' fluctuation, and the monthly AOD value varied from 0 to 2.5. The overall average values of AOD from February to May were greater than 0.7, followed by the average value of 0.64 AOD in August, and the average values of AOD from November to December were less than 0.5. The research showed that the prevention and control of particulate matter pollution in the Sichuan Basin should be focused on the Chengdu Plain urban agglomeration and the southern Sichuan urban agglomeration. It is important to control the emission of fine particulate matter and rationally arrange the cyclical production intensity of industrial enterprises. 
Keywords:MODIS  AOD  aerosol  Sichuan Basin  temporal and spatial distribution
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