When comparing the column NO2 from the Baseline and "Optimized NOx" simulations to the GCAS measurements, we found better agreement and an improvement in bias, albeit a smaller improvement than we had expected (Figure ). The column NO2 low bias improved from -30.6% to -25.2% with a small increase in correlation from r 2 =0.78 to r 2 =0.80. When we further add an artificial 0. When comparing the column NO2 from the Baseline and "Optimized NOx" simulations to the Pandora measurements, we found better agreement and an improvement in bias, albeit a smaller improvement than we had expected (Figure ). The column NO2 low bias improved from -20.2% to -17.8% with a small increase in correlation from r 2 =0.39 to r 2 =0.41. However, much of the apparent low bias appears to be driven by the large Pandora measured values. When then exclude values exceeding 10e15 molec/cm 2which approximate fine-scale NO2 plumes that we cannot expect CAMx to recreate in space due to the need to match wind speed and direction. For moderately polluted scenes (values <10e15), the NO2 low bias is only -6.8%. When evaluating the new model simulation improved from -6.8% to -3.4%; the correlation is notably poor in both scenarios due to the smaller range of values. When comparing the MLR results between the Baseline and Optimized NOx simulations, we see substantial improvement in the coefficients attributed to on-road and shipping emissions (Figure ), while all other coefficients remain largely steady. This indicates both the robustness of the method as well as a strong indication that the adjustments made to the NOx emissions were appropriate. The on-road NOx emissions may have been slightly overcorrected, and the "other" NOx emissions still need an adjustment up. As expected, the coefficient attributed to the background NO2 did not change, and this would be more difficult to control without modifying the boundary conditions or the NO2 lifetime. A longer discussion on the influence of NO2 long-range transport on the MLR can be found in the supporting information. This study expands upon previous work by applying additional measures to identify and quantify the magnitude of NOx emissions. The FD method was able to distinguish the linear shape of major highways, many of the large point sources, and the Galveston Bay ship track. The NO2 FD comparison between CAMx and GCAS shows underestimates at highway locations. Through a multiple linear regression model, we were able to isolate on-road, railyard, and "other" NOx emissions as the likeliest cause of this low bias, while simultaneously finding that shipping NOx emissions may be overestimated. A new "Optimized NOx" simulation was performed with on-road NOx emissions increased by a factor of 1.68 and shipping NOx emissions decreased by a factor of 0.77, and confirmed that these NOx adjustments made to the inventory were reasonable and yielded better agreement with NO2 measurements acquired during the TRACER-AQ campaign.