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RSS FeedsSensors, Vol. 18, Pages 3950: Spatial-Temporal Variations in NO2 and PM2.5 over the Chengdu-Chongqing Economic Zone in China during 2005-2015 Based on Satellite Remote Sensing (Sensors)

 
 

15 november 2018 19:00:10

 
Sensors, Vol. 18, Pages 3950: Spatial-Temporal Variations in NO2 and PM2.5 over the Chengdu-Chongqing Economic Zone in China during 2005-2015 Based on Satellite Remote Sensing (Sensors)
 




The Chengdu–Chongqing Economic Zone (CCEZ), which is located in southwestern China, is the fourth largest economic zone in China. The rapid economic development of this area has resulted in many environmental problems, including extremely high concentrations of nitrogen dioxide (NO2) and fine particulate matter (PM2.5). However, current ground observations lack spatial and temporal coverage. In this study, satellite remote sensing techniques were used to analyze the variation in NO2 and PM2.5 from 2005 to 2015 in the CCEZ. The Ozone Monitoring Instrument (OMI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product were used to retrieve tropospheric NO2 vertical columns and estimate ground-level PM2.5 concentrations, respectively. Geographically, high NO2 concentrations were mainly located in the northwest of Chengdu and southeast of Chongqing. However, high PM2.5 concentrations were mainly located in the center areas of the basin. The seasonal average NO2 and PM2.5 concentrations were both highest in winter and lowest in summer. The seasonal average NO2 and PM2.5 were as high as 749.33 × 1013 molecules·cm−2 and 132.39 µg·m−3 in winter 2010, respectively. Over 11 years, the annual average NO2 and PM2.5 values in the CCEZ increased initially and then decreased, with 2011 as the inflection point. In 2007, the concentration of NO2 reached its lowest value since 2005, which was 230.15 × 1013 molecules·cm−2, and in 2015, the concentration of PM2.5 reached its lowest value since 2005, which was 26.43 µg·m−3. Our study demonstrates the potential use of satellite remote sensing to compensate for the lack of ground-observed data when quantitatively analyzing the spatial–temporal variations in regional air quality.


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26 viewsCategory: Chemistry, Physics
 
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Sensors, Vol. 18, Pages 3949: Simultaneous Robot-World and Hand-Eye Calibration without a Calibration Object (Sensors)
 
 
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