Tianhao Zhang

TL;DR: In this paper, the daily PM2.5 concentrations were estimated using the new AOD data with a 160m spatial resolution retrieved by the Gaofen-1 (GF) wide field of view (WFV) along with the nested linear mixed effects model and ancillary variables from the Weather Research & Forecasting (WRF) meteorological simulation data.

TL;DR: Wang et al. as mentioned in this paper analyzed the characteristics of PM and their relation to black carbon using statistical methods and found that variations in the monthly average mass concentrations of PM have similar concave parabolic shapes, with the highest values occurring in January and the lowest values appearing in August or September.

TL;DR: A newly developed GWR model combined with a fused Aerosol Optical Depth product and meteorological parameters could explain approximately 87% of the variability in the corresponding PM2.5 mass concentrations by introducing NO2 and Enhanced Vegetation Index into the Geographically Weighted Regression (GWR) model.

TL;DR: It is found that random errors of less than 0.3% can be expected for most regions of the study area, which will allow the provision of valuable data that will help researchers gain a deeper insight into carbon cycle processes and accurately estimate carbon uptake and emissions.

TL;DR: An improved AOD retrieval algorithm for Gaofen-1 (GF-1) wide-field-of-view (WFV) camera data is proposed that has a spatial resolution of 160 m and covers all land surface types and was found to overestimate AOD in some cases.