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Novel quantification of regional fossil fuel CO₂ reductions during COVID-19 lockdowns using atmospheric oxygen measurements.

ABSTRACT: It is not currently possible to quantify regional-scale fossil fuel carbon dioxide (ffCO₂) emissions with high accuracy in near real time. Existing atmospheric methods for separating ffCO₂ from large natural carbon dioxide variations are constrained by sampling limitations, so that estimates of regional changes in ffCO₂ emissions, such as those occurring in response to coronavirus disease 2019 (COVID-19) lockdowns, rely on indirect activity data. We present a method for quantifying regional signals of ffCO₂ based on continuous atmospheric measurements of oxygen and carbon dioxide combined into the tracer "atmospheric potential oxygen" (APO). We detect and quantify ffCO₂ reductions during 2020-2021 caused by the two U.K. COVID-19 lockdowns individually using APO data from Weybourne Atmospheric Observatory in the United Kingdom and a machine learning algorithm. Our APO-based assessment has near-real-time potential and provides high-frequency information that is in good agreement with the spread of ffCO₂ emissions reductions from three independent lower-frequency U.K. estimates.

SUBMITTER: Pickers PA

PROVIDER: S-EPMC9032948 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Novel quantification of regional fossil fuel CO2 reductions during COVID-19 lockdowns using atmospheric oxygen measurements.

Pickers Penelope A PA Manning Andrew C AC Le Quéré Corinne C Forster Grant L GL Luijkx Ingrid T IT Gerbig Christoph C Fleming Leigh S LS Sturges William T WT

Science advances 20220422 16

It is not currently possible to quantify regional-scale fossil fuel carbon dioxide (ffCO2) emissions with high accuracy in near real time. Existing atmospheric methods for separating ffCO2 from large natural carbon dioxide variations are constrained by sampling limitations, so that estimates of regional changes in ffCO2 emissions, such as those occurring in response to coronavirus disease 2019 (COVID-19) lockdowns, rely on indirect activity data. We present a met ...[more]

PMID: 35452281

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Project description:We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020-2022 were calculated relative to those for the preceding 9-year period (2011-2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, - 36 ± 7%, and - 12 ± 8%, respectively, (- 10 ± 9% for JFM overall) relative to 2011-2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, - 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, - 3 ± 10%, and - 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai.Supplementary informationThe online version contains supplementary material available at 10.1186/s40645-023-00542-6.

Dataset Information

Novel quantification of regional fossil fuel CO₂ reductions during COVID-19 lockdowns using atmospheric oxygen measurements.

Publications

Novel quantification of regional fossil fuel CO<sub>2</sub> reductions during COVID-19 lockdowns using atmospheric oxygen measurements.

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