Abstract. Emissions of methane (CH4) from offshore oil and gas installations are poorly ground-truthed, and quantification relies heavily on the use of emission factors and activity data. As part of the United Nations Climate & Clean Air Coalition (UN CCAC) objective to study and reduce short-lived climate pollutants (SLCPs), a Twin Otter aircraft was used to survey CH4 emissions from UK and Dutch offshore oil and gas installations. The aims of the surveys were to (i) identify installations that are significant CH4 emitters, (ii) separate installation emissions from other emissions using carbon-isotopic fingerprinting and other chemical proxies, (iii) estimate CH4 emission rates, and (iv) improve flux estimation (and sampling) methodologies for rapid quantification of major gas leaks. In this paper, we detail the instrument and aircraft set-up for two campaigns flown in the springs of 2018 and 2019 over the southern North Sea and describe the developments made in both the planning and sampling methodology to maximise the quality and value of the data collected. We present example data collected from both campaigns to demonstrate the challenges encountered during offshore surveys, focussing on the complex meteorology of the marine boundary layer and sampling discrete plumes from an airborne platform. The uncertainties of CH4 flux calculations from measurements under varying boundary layer conditions are considered, as well as recommendations for attribution of sources through either spot sampling for volatile organic compounds (VOCs) ∕ δ13CCH4 or using in situ instrumental data to determine C2H6–CH4 ratios. A series of recommendations for both planning and measurement techniques for future offshore work within marine boundary layers is provided.

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Methane (CH4) is a potent greenhouse gas with a warming potential 84 times that of carbon dioxide (CO2) over a 20‐year period. Atmospheric CH4 concentrations have been rising since the nineteenth century but the cause of large increases post‐2007 is disputed. Tropical wetlands are thought to account for ∼20% of global CH4 emissions, but African tropical wetlands are understudied and their contribution is uncertain. In this work, we use the first airborne measurements of CH4 sampled over three wetland areas in Zambia to derive emission fluxes. Three independent approaches to flux quantification from airborne measurements were used: Airborne mass balance, airborne eddy‐covariance, and an atmospheric inversion. Measured emissions (ranging from 5 to 28 mg m−2 hr−1) were found to be an order of magnitude greater than those simulated by land surface models (ranging from 0.6 to 3.9 mg m−2 hr−1), suggesting much greater emissions from tropical wetlands than currently accounted for. The prevalence of such underestimated CH4 sources may necessitate additional reductions in anthropogenic greenhouse gas emissions to keep global warming below a threshold of 2°C above preindustrial levels.

Abstract. The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian Continental Shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t year−1 (with a mean of 211 t year−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representivity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritizing targeted emission mitigation solutions. Surveys of individual facilities may always require this. However, for field-aggregated emissions, our results show that an accurate estimate of total field-level emissions simply requires a sufficiently large and representative sample of facilities, to yield meaningful comparisons and flux statistics, irrespective of operational status information. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of measurement approaches to validate bottom-up accounting.