Characterizing the long‐term dynamics of aerosol optical depth in the Yangtze River Middle‐Reach urban agglomeration, China. (2nd December 2020)

• Record Type: Journal Article
• Authors: Zhang, Ming; Zhang, Lei; He, Qingqing; Yuan, Yanbin
• Is Part Of: International journal of climatology. Volume 41:Number 3(2021)
• Page Start: 2029
• Page End: 2044
• Publication Date: 2020-12-02
• Subjects: aerosol optical depth -- spatio‐temporal filling -- time series decomposition -- Yangtze River Middle‐Reach; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.6945
• Languages: English
• ISSNs: 0899-8418

Abstract

Abstract: Along with the rapid urbanization and economic development, the Yangtze River Middle‐Reach urban agglomeration (YRMR) has suffered from increasingly serious environmental problems. Characterizing the long‐term dynamics of aerosol optical depth (AOD) in YRMR is of important significance for scientific control of aerosol pollutants over this region. Previously, numerous researches have analysed the temporal and spatial characteristics of AOD in different regions through statistical values of AOD time series or using trend analysis methods based on linear regression models. It is challenging to approximate nonlinear trends and identify change points of AOD time series. This paper proposed a new methodology for investigating the dynamics of AOD over the YRMR region on a monthly basis by using the Terra MODIS Collection 6.1 Level 2 aerosol products (MOD04_L2) during 2001–2017. A three‐dimensional spatio‐temporal interpolation method was used to generate gap‐filled monthly AOD maps, and then a generic Bayesian time series decomposition algorithm was applied to analyse the trends and change points of monthly AOD time series. The results showed that the areas with high AOD values were mainly located in the core cities and the connecting belts. Strong positive AOD anomalies had been observed during 2006–2011, whereas the positive anomalies were typically intermingled with negative anomalies and it indicated that the evolution patterns of AOD for different regions were different and influenced by fluctuations. Trend analysis of the monthly mean AOD values indicated that AOD in YRMR increased first, then fluctuated, and finally decreased. Although it was difficult to separate the increasing and fluctuating periods from each other due to the fluctuation, the decreasing trend after 2011 was significant, and a significant drop of AOD had been observed since 2014. Long‐term AOD variations were closely related to national policies, and the results could provide useful references for regional environmental assessment and decision‐making. Abstract : This study proposed a new methodology for characterizing the long‐term dynamics of aerosol optical depth (AOD). The spatio‐temporal interpolation method was introduced to fill gaps of monthly AOD, and then a trend analysis method based on Bayesian regression model was applied to analyse the trends and change points of AOD time series.