The production of crude oil and natural gas is associated with emissions of air pollutants, such as nitrogen oxides (NOx = NO + NO2) and volatile organic compounds, which are precursors for the formation of ground-level ozone. Knowledge of these emissions is critical to the understanding and mitigation of local air quality. NOx emissions from oil and gas production activities are not well described in commonly used emission inventories, and discrepancies of several factors have been found in the past. Here we present an easy and computationally efficient method to quantify NOx emissions from satellite NO2 observations that can be applied to evaluate common emission inventories and provide timely input for chemistry transport models. Using NO2 columns from the TROPOspheric Monitoring Instrument (TROPOMI), we calculated annually averaged NOx emissions from the divergence of NO2 column fluxes for six oil and gas production regions in the United States. Derived NOx emissions for the years 2018 to 2020 range between 4.8 and 81.1 t/day, and observed trends over time are consistent with changes in industrial activity. To evaluate the method, we compared our results with the fuel-based oil and gas NOx inventory (FOG) and performed sensitivity studies using model output from the Weather Research Forecasting model with Chemistry (WRF-Chem). We found that annually averaged NOx emissions from oil and gas production activities can in most cases be calculated within an uncertainty of 50%, while simultaneously derived emission maps show the spatial distribution of NOx emissions with a high level of detail. For future use, this method can easily be applied globally.

Nitrogen oxides (NO_x) 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, WRF-Chem 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.

U.S. oil and natural gas production volumes have grown by up to 100% in key production areas between January 2017 and August 2019. Here we show that recent trends are visible from space and can be attributed to drilling, production, and gas flaring activities. By using oil and gas activity data as predictors in a multivariate regression to satellite measurements of tropospheric NO₂ columns, observed changes in NO₂ over time could be attributed to NO_x emissions associated with drilling, production and gas flaring for three select regions: the Permian, Bakken, and Eagle Ford basins. We find that drilling had been the dominant NO_x source contributing around 80% before the downturn in drilling activity in 2015. Thereafter, NO_x contributions from drilling activities and combined production and flaring activities are similar. Comparison of our top-down source attribution with a bottom-up fuel-based oil and gas NO_x emission inventory shows agreement within error margins.