Multi-Time Scale Analysis of Regional Aerosol Optical Depth Changes in National-Level Urban Agglomerations in China Using Modis Collection 6.1 Datasets from 2001 to 2017

Abstract

With the rapid development of China’s economy and industry, characterizing the spatial and temporal changes of aerosols in China has attracted widespread attention from researchers. The national-level urban agglomerations are the most concentrated areas of China’s economic, population and resource. Studying the spatial and temporal changes of aerosol optical depth (AOD) in these regions has practical guiding significance for effective monitoring of atmospheric particulate pollution. This paper analyzed the spatial and temporal variations of AOD in China’s urban agglomerations during 2001–2017 by using Terra Moderate resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) Level 2 aerosol products (MOD04_L2). Five national-level urban agglomerations were chosen: Yangtze River Delta (YRD), Pearl River Delta (PRD), Beijing-Tianjin-Hebei (BTH), Yangtze River Middle-Reach (YRMR) and Cheng-Yu (CY). We analyzed the change patterns of AOD in different urban agglomerations at multi-time scales and built a time series decomposition model to mine the long-term trend, seasonal variation and abnormal change information of AOD time series. The result indicated that averaged AOD values in the five urban agglomerations were basically increased first and then decreased at the annual time scale during 2001–2017. The averaged AOD showed strong seasonal differences and AOD values in spring and summer were typically higher than those in autumn and winter. At the monthly time scale, the AOD typically varied from low in cold months to high in warm months and then decreased during the rainy periods. Time series decompositions revealed that a notable transition around 2007–2008 dominated the long-term overall trend over the five selected urban agglomerations and an initial upward tendency followed by a downward tendency was observed during 2001–2017. This study can be utilized to provide decision-making basis for atmospheric environmental governance and future development of urban agglomerations.

Evidence of air quality data misreporting in China: An impulse indicator saturation model comparison of local government-reported and U.S. embassy-reported PM2.5 concentrations (2015–2017)

“…Nonetheless, the persistence of local data misreporting does not invalidate results which that suggest urban air quality in China has improved in recent years [12][13][14][15][16]. Even measurements from U.S. embassies and consulates show that annual concentrations of PM 2.5 fell by more than 25% between 2013 and 2017.…”

“…For example, government data indicate that urban air quality improved significantly over the past several years [12][13][14]. While independent data sources confirm this positive trend [15,16], the magnitude of improvements could be exaggerated if the Chinese government misreports the data.…”

Urban Features Identification from Dual-Pol SAR Images with Filter Properties

“…In the field of remote sensing, the main instrument which is used for the capture of images in worst atmospheric situations is synthetic aperture radar. Which gives high-resolution images (Blaschke et al, 2019;Ji & Wu, 2015;Werner et al, 2014). While capturing the data due to different backscattered values from the target the speckle noise error occurs and for the better-quality interpretation, we need to extract useful information to reduce the speckle noise or enhance the image quality (Li et al, 2020;Yang et al, 2016).…”

Statistical Study of Modis Algorithms in Estimating Aerosol Optical Depth Over the Czech Republic

“…Aerosol Optical Depth (AOD) is a measure of the columnar atmospheric aerosol content, these particles could absorb or scatter the sunlight and prevent it reaching the ground [1]. These small solid or liquid particles are suspended in the atmosphere and they differ in the size, shape, and chemical adaption [2].…”