Global Accuracy Comparison from Multi-Source NO2 Products Based on Pandora Observations

Effective evaluation of the accuracy of multi-source NO2 products from different satellites and reanalysis is of great significance for data fusion and application. Based on NO2 observation data from Pandora stations worldwide, we verify and compare the accuracy of the total column density of NO2 (TOTNO2) from OMI, TROPOMI, GOME-2 satellites and CAMS reanalysis. The mean biases of the four TOTNO2 datasets relative to the Pandora station observation data are all negative, indicating that all four TOTNO2 products show systematic underestimation with respect to Pandora. Overall, TROPOMI has the highest correlation (R = 0.88) and the smallest root mean square error (RMSE = 4.83 Pmolec·cm−2), suggesting that among the four TOTNO2 products, the accuracy of TROPOMI TOTNO2 is higher compared with the other TOTNO2 products. The accuracies of OMI and GOME-2 are in the middle, while the performance of CAMS is the poorest. The TOTNO2 values and accuracies from the four TOTNO2 products both show a seasonal characteristic. Among the four TOTNO2 products, the accuracy is higher in summer, and the error increases in autumn and winter. After performing linear fitting correction on the four NO2 products, the mean biases of each data are reduced by more than 79%, and the RMSE decreases by 4–28%. The consistency of the four TOTNO2 products with the ground-based observation data is significantly improved.