Spatio-Temporal Changes in Air Quality of the Urban Area of Chongqing from 2015 to 2021 Based on a Missing-Data-Filled Dataset

Air pollution is one of the severe environmental issues in Chongqing. Many measures made by government for improving air quality have been put into use these past few years, while influence remains unknown. This study analyzed changes urban area Chongqing between 2015 and 2021 using a complete situ observation dataset that all missing data were filled interpolation low-rank tensor completion model with truncate nuclear norm minimization (LRTC-TNN). The results include: (1) LRTC-TNN robustly performs to reconstruct pollutant concentrations an R2 0.93 RMSE 7.78; (2) index (AQI) decreases 15.96%, total polluted days decrease 21.05% from 2021, showing obvious promotion quality; (3) changing attributed decreasing PM2.5 (34.10%), PM10 (25.03%), NO2 (5.53%) whereas increasing concentration O3 (10.49%) observed. processing method data, intact AQI datasets, analysis are beneficial policy-making improvement fill gap field datasets mountainous areas.