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京津冀气溶胶光学厚度时空演变及气象解释
引用本文:文韶鑫,刘海新,高叶鹏,钱以临.京津冀气溶胶光学厚度时空演变及气象解释[J].科学技术与工程,2022,22(30):13569-13577.
作者姓名:文韶鑫  刘海新  高叶鹏  钱以临
作者单位:河北工程大学 矿业与测绘工程学院
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:针对京津冀地区日益严重的大气污染问题,采用逐像元法对2001-2019年MCD19A2与MOD04气溶胶数据进行融合,并基于AERONET地面站点数据对其在京津冀地区的适用性进行验证后,采用EOF、ISODATA以及回归分析等方法,分析了京津冀地区气溶胶光学厚度(AOD)时间序列的时空演变过程,同时采用地理探测器对其演变过程进行气象解释,对京津冀地区大气污染的防治工作具有重要意义。具体结论如下:(1)从年际演变来看,AOD在2001-2013年绕平均值上下波动,2013-2019年迅速下降。空间分布模式以全局一致型为主,南北分异型为辅,且空间分布与高程呈明显的负相关性。(2)从季节演变来看,夏季AOD较其他季节高,春季和夏季的变化幅度较大。研究期内AOD整体呈减少不显著趋势,其中春季和夏季主要趋势是减少不显著,而秋季和冬季减少不显著和增加不显著比例大致相等。(3)在选取的五个气象因子中,气温对AOD变化的解释力最强。多个气象因子之间会相互影响,对AOD变化具有更强的影响力。气温和湿度对AOD的解释力最强,是主导交互因子。

关 键 词:融合数据    EOF分析  地理探测器  气象解释
收稿时间:2022/1/18 0:00:00
修稿时间:2022/8/7 0:00:00

Temporal and Spatial Evolution of AOD in Beijing-Tianjin-Hebei Region and its Meteorological Interpretation
Wen Shaoxin,Liu Haixin,Gao Yepeng,Qian Yilin.Temporal and Spatial Evolution of AOD in Beijing-Tianjin-Hebei Region and its Meteorological Interpretation[J].Science Technology and Engineering,2022,22(30):13569-13577.
Authors:Wen Shaoxin  Liu Haixin  Gao Yepeng  Qian Yilin
Institution:School of Mining and Surveying Engineering, Hebei University of Engineering
Abstract:In response to the deteriorating air pollution problem, the reliability of fusion data constituted by MCD19A2 and MOD04 is verified in the Beijing-Tianjin-Hebei (BTH) region based on aeronet data. And then spatiotemporal evolution of the AOD time series are analyzed in the BTH region using EOF, ISODATA and regression analysis methods. At the same time, evolution process is interpreted by analyzing explanatory power between AOD and meteorological factors based on geo-detector. The results showed that: (1) From the perspective of inter-annual evolution, AOD fluctuate around the average value from 2001 to 2013, and drop rapidly from 2013 to 2019. The spatiotemporal distribution pattern is mainly the global consistent type, supplemented by the northern-southern different pattern. The spatial distribution is obviously negatively correlated. (2) From the perspective of seasonal evolution, summer AOD is higher than other seasons, and the range of changes in spring and summer is large. AOD show a decreasing trend as a whole. The main trend in spring and summer is that the decrease was insignificant, while the proportions of insignificant decrease and insignificant increase in autumn and winter were roughly equal. (3) Among the five selected meteorological factors, temperature have the strongest explanatory power for AOD changes. Multiple meteorological factors influenced each other and have a stronger influence on AOD changes. Temperature and humidity have the strongest explanatory power for AOD and are the dominant interaction factors.
Keywords:Fusion data  EOF analysis  Geodetector  Meteorological interpretation
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