The production of crude oil and natural gas is associated with emissions of air pollutants, such as nitrogen oxides (NO x = NO + NO 2 ) 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. NO x 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 NO x emissions from satellite NO 2 observations that can be applied to evaluate common emission inventories and provide timely input for chemistry transport models. Using NO 2 columns from the TROPOspheric Monitoring Instrument (TROPOMI), we calculated annually averaged NO x emissions from the divergence of NO 2 column fluxes for six oil and gas production regions in the United States. Derived NO x 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 NO x inventory (FOG) and performed sensitivity studies using model output from the Weather Research Forecasting model with Chemistry (WRF-Chem). We found that annually averaged NO x 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 NO x emissions with a high level of detail. For future use, this method can easily be applied globally.

Methane (CH 4 ) is the second most important anthropogenic greenhouse gas after carbon dioxide (CO 2 ). As the atmospheric lifetime of CH 4 is relatively short at 9.1 ± 0.9 years (Masson-Delmotte et al., 2021) and the global warming potential large, a reduction in CH 4 emissions would lower the combined radiative forcing from greenhouse gases on a timescale of years making it a relatively efficient option to mitigate climate change. For this reason, the Global Methane Pledge was initiated at the UN Climate Change Conference (COP26) in November 2021 (European Commission, United States of America, 2021), which aims at reducing CH 4 emissions by 30% by 2030.A significant fraction of global methane emissions comes from the oil and gas (O&G) industry (IEA, 2021). CH 4 is emitted during the construction of new wells, when operating, during storage and transportation of oil and gas, and when wells are abandoned. Some of the emissions are intended releases, for example, from venting, while others are unintentional and caused by malfunctioning equipment or by accidents. The CH 4 emissions of the oil and gas supply chain are estimated as 13 ± 2 Tg yr −1 (Alvarez et al., 2018) in the USA in

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Emissions of methane (CH 4 ) in the Permian basin (U.S.A.) have been derived for 2019 and 2020 from satellite observations of the Tropospheric Monitoring Instrument (TROPOMI) using the divergence method, in combination with a data driven method to estimate the background concentrations. The resulting CH 4 emission data, which have been verified using model with known emissions, have a spatial resolution of approximately 10 km. The spatial patterns of the emissions are in a good agreement with the locations of oil and gas production and drilling activities in the Permian basin, as well as with emissions of nitrogen oxides (NOx). Analysis of time-series of locations with large CH 4 emissions indicated that there are significant continuous emissions in this region. The CH 4 emissions can be characterized as a continuous area source, rather than as dominated by a few large unplanned releases. This is important considering possible CH 4 emission mitigation strategies. In addition to providing spatially resolved emissions, the divergence method also provides the total emissions of the Permian basin and its main sub-basins. The total CH 4 emission of the Permian is estimated as 3.0 ± 0.7 Tg yr -1 for 2019, which agrees with other independent estimates based on TROPOMI data. For the Delaware sub-basin, it is estimated as 1.4 ± 0.3 Tg yr -1 for 2019, and for the Midland sub-basin 1.2 ± 0.3 Tg yr -1 . In 2020 the emissions are 8% lower compared to 2019, which could be a result of strong decreases in drilling activities due to the COVID-19 crisis.

Remote sensing holds great potential for detecting stress in vegetation caused by hydrocarbons, but we need to better understand the effects of hydrocarbons on plant growth and specific spectral expression. Willow (Salix viminalis var. Tora) cuttings and maize (Zea mays var. Lapriora) seedlings were grown in pots of loam soil containing a hydrocarbon-contaminated layer at the base of the pot (crude or refined oil) at concentrations of 0.5, 5, or 50 g·kg−1. Chlorophyll concentration, biomass, and growth of plants were determined through destructive and nondestructive sampling, whilst reflectance measurements were made using portable hyperspectral spectrometers. All biophysical (chlorophyll concentration and growth) variables decreased in the presence of high concentrations of hydrocarbons, but at lower concentrations an increase in growth and chlorophyll were often observed with respect to nonpolluted plants, suggesting a biphasic response to hydrocarbon presence. Absorption features were identified that related strongly to pigment concentration and biomass. Variations in absorption feature characteristics (band depth, band area, and band width) were dependent upon the hydrocarbon concentration and type, and showed the same biphasic pattern noted in the biophysical measurements. This study demonstrates that the response of plants to hydrocarbon pollution varies according to hydrocarbon concentration and that remote sensing has the potential to both detect and monitor the variable impacts of pollution in the landscape.