Novel quantification of regional fossil fuel CO<sub>2</sub> reductions during COVID-19 lockdowns using atmospheric oxygen measurements.
Where this comes from
- Record sourced from PubMed, PMID 35452281.
- Also identified by DOI 10.1126/sciadv.abl9250 and PMC identifier 9032948.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
It is not currently possible to quantify regional-scale fossil fuel carbon dioxide (ffCO<sub>2</sub>) emissions with high accuracy in near real time. Existing atmospheric methods for separating ffCO<sub>2</sub> from large natural carbon dioxide variations are constrained by sampling limitations, so that estimates of regional changes in ffCO<sub>2</sub> 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 ffCO<sub>2</sub> based on continuous atmospheric measurements of oxygen and carbon dioxide combined into the tracer "atmospheric potential oxygen" (APO). We detect and quantify ffCO<sub>2</sub> 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 ffCO<sub>2</sub> emissions reductions from three independent lower-frequency U.K. estimates.