# Preliminary Global NO2 Retrieval from EMI-II Onboard GF5B/DQ1 and Comparison to Tropopmi
## 3 Results and Validation
### Total VCD Compared with Tropoomi  
The TROPOMI has been in operation for six years. Its NO\({}_{2}\) products have undergone multiple iterations and optimizations, as validated by numerous ground-based MAX-DOAS measurements [38; 39; 40; 41]. Cross-validation via TROPOMI products can indirectly reflect the accuracy of the trends in the EMI-II's retrieval results. Due to the differences in the pixel spatial resolution between the EMI and TROPOMI, as well as the variations in the central latitude and longitude of the pixels, this study divides the research area into multiple 0.25\({}^{\circ}\) grids for comparative analysis. The NO\({}_{2}\) value for each grid is calculated by determining the mean of the pixels whose central coordinates fall within the grid. Subsequently, the grid values from the EMI are compared with those from the TROPOMI.  
In both summer and winter, the global hotspot regions identified by the EMI-II on single days are entirely consistent with those captured by the TROPOMI. The global correlation coefficient (R\({}^{2}\)) between the GF5B and TROPOMI was 0.93 on 5 July 2022 and 0.88 on 20 December 2022. For the DQ1, the corresponding values were 0.92 and 0.89 on the same dates. Compared with the TROPOMI (Figure 5), the GF5B and DQ1 EMI-II clearly exhibited entirely consistent global hotspot regions on a monthly timescale. In June 2022, the global correlation coefficient between the GF5B (DQ1) EMI-II and TROPOMI was 0.99 (0.98). In December 2022, the correlations between the GF5B and DQ1 EMI-II were 0.98 and 0.97, respectively, compared to those of the TROPOMI. The total VCD of the EMI-II  
Figure 4: Intercomparison of the daily mean NO\({}_{2}\) VCD within 5 km of Beijing from GF5B and DQ1. (a) Daily variations in the mean NO\({}_{2}\) VCD (b) Correlation between GF5B and DQ1.  
was 12% higher than that of the TROPOMI. The main reason for this may be the different correction methods used in the de-stripe correction process.  
In the highlighted regions in Figure 3f, the EMI-II observational results were compared with the TROPOMI results on a seasonal scale. Figure 6 depicts the seasonal averages of the GF5B and DQ1 EMI-II in regions 1 (first row), 2 (second row), 3 (third row), and 4 (fourth row), which correspond to the TROPOMI data in the spring (first column), summer (second column), autumn (third column), and winter (fourth column). In all the regions during the different seasons, the seasonal mean correlation (R\({}^{2}\)) between the EMI-II and TROPOMI exceeds 0.9 except for in spring in region 4 (0.82). The primary reason for this is that region 4 has the lowest average NO\({}_{2}\) concentration among the four regions, and the spring season results in the lowest NO\({}_{2}\) concentration throughout the year in this region.  
The uncertainty in the NO\({}_{2}\) total VCD comprises two main components: (a) uncertainty from the SCD retrieval and (b) uncertainty introduced by strip correction. The uncertainty associated with the SCD retrieval is primarily influenced by the DOAS fitting process, with the contributing factors ranked as follows: the instrument signal-to-noise ratio, accuracy of data radiative correction and wavelength calibration, cloud effects, and precision of the least squares algorithm. Nonetheless, the predominant source of uncertainty in the NO\({}_{2}\) total VCD is attributed to strip correction, which cannot be quantitatively assessed. As noted in R10, the strip phenomenon in the SCD retrieval results is so significant that subsequent retrievals cannot proceed without strip correction. Consequently, this study attributes the primarily uncertainty in the NO\({}_{2}\) total VCD to de-stripe correction.  
Figure 5: Global NO2 VCD correlation between GF5B and DQ1 EMI-II with TROPOMI in June (**a**) and December (**b**) 2022.