Nitrogen oxides (NOx) are air pollutants critical to ozone and fine particle production in the troposphere. Here, we present fuel-based emission inventories updated to 2018, including for mobile source engines using the Fuel-based Inventory of Vehicle Emissions (FIVEs) and oil and gas production using the Fuel-based Oil and Gas (FOG) inventory. The updated FIVE emissions are now consistent with the NEI17 estimates differing within 2% across the contiguous US (CONUS). Tropospheric NO2 columns modeled by the Weather Research and Forecasting with Chemistry model (WRF-Chem) are compared with those observed by TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) during the summer of 2018. Modeled NO2 columns show strong temporal and spatial correlations with TROPOMI (OMI), identified with biases of −3% (−21%) over CONUS, and +8% (−6%) over point sources plus urban regions. Taking account of the negative bias (∼20%) in early version of TROPOMI over polluted regions, WRFChem shows good performance with updated FIVE and FOG emissions. Our model tends to under-predict the tropospheric NO2 columns over background and rural regions (bias of −21% to −3%). Through model sensitivity analyses, we demonstrate the important roles of emissions from soils (11.7% average over CONUS), oil and gas production (4.1%), wildfires (10.6%), and lightning (2.3%) with greater contributions at regional scales. This work provides a roadmap for satellite-based evaluations for emission updates from various sources. Plain Language Summary Satellite observations of tropospheric NO2 columns provide important constraints on air pollutants from space, which have been widely used to validate the performance of atmospheric models. To gain better knowledge of the accuracy of the recently updated fuel-based emissions inventory, we conducted NO2 assessments between a regional chemical transport model (Weather Research and Forecasting with Chemistry model, WRF-Chem), with the TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) over the contiguous United States. We find that model simulation results show strong spatial and temporal correlations with satellite observations across point sources, urban, oil and gas production, and rural regions. With updated emissions, our regional atmospheric model can reconcile with satellite retrievals differing from −3% (TROPOMI) to −21% (OMI) overall. Soils, oil and gas production, wildfires and lightning emissions can play key roles in regional air quality. This work provides an important baseline of a pre-COVID year by which sharp changes in anthropogenic NOx emissions due to the pandemic can be assessed.