# Preliminary Global NO2 Retrieval from EMI-II Onboard GF5B/DQ1 and Comparison to Tropopmi
## 3 Results and Validation
### Total VCD Satellite Intercomparison of GF5B and DQ1  
Although the GF5B EMI-II and DQ1 EMI-II are two independent payloads, their technical statuses are identical. The spatial distribution consistency and temporal variation consistency of their NO\({}_{2}\) products may not reflect the accuracy of the retrieval results, and the intercomparison results of GF-5B and DQ1 include the inevitable variations of the diurnal cycle. However, they can indicate the ability of the payloads to characterize the spatial distribution and temporal variations in NO\({}_{2}\). The consistency comparison between the two sensors can serve as a cross-validation. Notable anomalies in their consistency may suggest a potential issue with one of the payloads. The variation in consistency can be used as a metric of temporal stability. Similar forms of satellite intercomparisons of the TROPOMI, GOME-2B, and OMI can be found in reference [36]. In addition, NO\({}_{2}\) products derived from multiple satellites with different local cross-times were combined to estimate the NO\({}_{2}\) emissions [37], and identifying the differences in input data to interpret the results is important. The difference in the NO\({}_{2}\) measurements between the GF5B and DQ1 is expected to depend on the source strength and factors that contribute to the diurnal variation. The global spatial correlation coefficients (R\({}^{2}\)) between GF5B and DQ1 in June and December 2022 were 0.985 and 0.973, respectively. Specific regions with notable NO\({}_{2}\) emissions were delineated, including eastern China (region 1), most parts of India (region 2), the Arabian Peninsula and Iran (region 3), and southern North America (region 4), as illustrated in Figure 3f. The spatial consistency between the GF5B and DQ1 was compared in these hotspot areas (Table 3). In regions 1, 2, and 3, the spatial consistency (R\({}^{2}\)) between the GF5B and DQ1 exceeded 0.91, 0.84, and 0.8, respectively. However, significant variations were observed in region 4, where the R\({}^{2}\) values were 0.93 in June and 0.74 in December. A possible reason for this is that this region has lower NO\({}_{2}\) emissions in the winter and exhibits diurnal variations, which requires further investigation. Importantly, in June 2022, increased NO\({}_{2}\) values were observed in Central Africa in the spatial distribution maps of the DQ1 EMI-II and TROPOMI, but these high values were not detected in the GF5B EMI-II maps. In Central Africa, NO\({}_{2}\) is primarily emitted from biomass burning activities, such as straw burning and grassland fires, which typically take place during the daytime and require time to accumulate. The overpass time for the GF5B is 10:30 AM, while for the DQ1, it is 13:30 PM. Consequently, it is challenging to detect elevated NO\({}_{2}\) concentrations at 10:30 AM using GF5B data. To compare the temporal consistency, typical city coordinates were selected in the highlighted regions in Figure 3f. The daily mean values within a 5 km radius around these latitudinal and longitudinal points were calculated over time. Figure 4 displays the daily variations in the mean NO\({}_{2}\) VCD and correlation between GF5B and DQ1 in the Beijing area from 1 September to 31 December 2022. The correlation coefficient (R\({}^{2}\)) during this period was 0.84. In general, the NO\({}_{2}\) results of the two EMI-II payloads exhibited a relatively high consistency across different time and spatial scales. However, there are inevitable differences, which may primarily be attributed to uncertainties from the differences in the FWHM and SCD uncertainty. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Region** & **R\({}^{2}\)** & **202206** & \multicolumn{3}{c}{**202212**} \\  & **R\({}^{2}\)** & **RMSE** & **R\({}^{2}\)** & **RMSE** \\ \hline Region 1 & 0.91 & 0.03 & 0.93 & 0.04 \\ Region 2 & 0.92 & 0.03 & 0.86 & 0.03 \\ Region 3 & 0.85 & 0.04 & 0.85 & 0.04 \\ Region 4 & 0.94 & 0.02 & 0.75 & 0.02 \\ \hline \hline \end{tabular}
\end{table}