Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion

Abstract

Abstract. Concentrations of atmospheric methane (CH4), the second most important greenhouse gas, continue to grow. In recent years this growth rate has increased further (2020: +14.7 ppb), the cause of which remains largely unknown. Here, we demonstrate a high-resolution (~80 km), short-window (24-hour) 4D-Var global inversion system based on the ECMWF Integrated Forecasting System (IFS) and newly available satellite observations. The largest national disagreement found between prior (63.1 Tg yr−1) and posterior (59.8 Tg yr−1) CH4 emissions is from China, mainly attributed to the energy sector. Emissions estimated form our global system agree well with previous basin-wide regional studies and point source specific studies. Emission events (leaks/blowouts) >10 t hr−1 were detected, but without accurate prior uncertainty information, were not well quantified. Our results suggest that global anthropogenic CH4 emissions for 2020 were 5.7 Tg yr−1 (+1.6 %) higher than for 2019, mainly attributed to the energy and agricultural sectors. Regionally, the largest 2020 increases were seen from China (+2.6 Tg yr−1, 4.3 %), with smaller increases from India (+0.8 Tg yr−1, 2.2 %) and Indonesia (+0.3 Tg yr−1, 2.6 %). Results show the rise in emissions, and subsequent atmospheric growth, would have occurred with or without the COVID-19 slowdown. During the onset of the global slowdown (March–April, 2020) energy sector CH4 emissions from China increased; however, during later months (May–June, 2020) emissions decreased below expected pre-slowdown levels. The accumulated impact of the slowdown on CH4 emissions from March–June 2020 is found to be small. Changes in atmospheric chemistry, not investigated here, may have contributed to the observed growth in 2020. Future work aims to develop the global IFS inversion system and to extend the 4D-Var window-length using a hybrid ensemble-variational method.

COVID-19 impact on the oil and gas industry emissions: a case study of methane and nitrogen dioxide in the Permian basin

“…During the COVID-19 lockdown period (April to June 2020) CH4 concentrations did not decrease in comparison to the same period of 2019 and even appeared to increase, which is the opposite of what it is observed with NO2. This positive trend has been observed by Mcnorton et al, 2022 finding an increase of 150 kt yr -1 in the overall background and a global trend of 05 -0.8 % per year. Deriving the local changes in the CH4 emissions from the total column satellite observations is challenging because of the large and increasing background concentration, in combination with a poor temporal sampling.…”

Assimilation of S5P/TROPOMI carbon monoxide data with the global CAMS near-real-time system

“…Factors such as the distribution of the hydroxyl radical OH, secondary CO sources from the oxidation of methane and NMVOCs, and deposition processes might also be important. CAMS is in the process of developing an inversion prototype using ECMWF's 4D-Var system (McNorton et al, 2022), which should help to address shortcomings in emission inventories, but work on modelling aspects is also needed.…”

Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020

“…The CAMS GHG reanalysis has been produced using the IFS model. The same model is used to produce operational numerical weather predictions (NWP) at ECMWF and the CAMS global forecast and analyses for reactive gas, aerosols and greenhouse gases at ECMWF (Fleming et al 2015, Agustí-Panareda et al, 2017, Agustí-Panareda et al, 2022. The IFS model version used is IFS CY42R1, the same as in the CAMS reanalysis for reactive gases and aerosols (Inness et al, 2019).…”

“…Doumia et al, 2021) and atmospheric inversion systems to estimate the changes (e.g. McNorton et al, 2022).…”

“…At the model surface the greenhouse gases are forced by a set of surface fluxes and emissions. Such modelling configuration allows to produce a realistic representation of the spatio-temporal variability of greenhouse gases in the atmosphere over a wide range of scales from hours to seasons and from local to global (Agustí-Panareda et al, 2022).…”