Global to local impacts on atmospheric COfrom the COVID-19 lockdown, biosphere and weather variabilities
Environmental Research Letters, ISSN: 1748-9326, Vol: 17, Issue: 1
2022
- 15Citations
- 20Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The worldwide lockdown in response to the COVID-19 pandemic in year 2020 led to an economic slowdown and a large reduction in fossil fuel CO2 emissions (Le Quéré 2020 Nat. Clim. Change 10 647-53, Liu 2020 Nat. Commun. 11); however, it is unclear how much it would slow the increasing trend of atmospheric CO2 concentration, the main driver of climate change, and whether this impact can be observed considering the large biosphere and weather variabilities. We used a state-of-the-art atmospheric transport model to simulate CO2, and the model was driven by a new daily fossil fuel emissions dataset and hourly biospheric fluxes from a carbon cycle model forced with observed climate variability. Our results show a 0.21 ppm decrease in the atmospheric column CO2 anomaly in the Northern Hemisphere latitude band 0-45 N in March 2020, and an average of 0.14 ppm for the period of February-April 2020, which is the largest decrease in the last 10 years. A similar decrease was observed by the carbon observing satellite GOSAT (Yokota et al 2009 Sola 5 160-3). Using model sensitivity experiments, we further found that the COVID and weather variability are the major contributors to this CO2 drawdown, and the biosphere showed a small positive anomaly. Measurements at marine boundary layer stations, such as Hawaii, exhibit 1-2 ppm anomalies, mostly due to weather and the biosphere. At the city scale, the on-road CO2 enhancement measured in Beijing shows a reduction by 20-30 ppm, which is consistent with the drastically reduced traffic during the COVID lockdown. A stepwise drop of 20 ppm during the city-wide lockdown was observed in the city of Chengdu. The ability of our current carbon monitoring systems in detecting the small and short-lasting COVID signals at different policy relevant scales (country and city) against the background of fossil fuel CO2 accumulated over the last two centuries is encouraging. The COVID-19 pandemic is an unintended experiment. Its impact suggests that to keep atmospheric CO2 at a climate-safe level will require sustained effort of similar magnitude and improved accuracy, as well as expanded spatiotemporal coverage of our monitoring systems.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85123759686&origin=inward; http://dx.doi.org/10.1088/1748-9326/ac3f62; https://iopscience.iop.org/article/10.1088/1748-9326/ac3f62; https://dx.doi.org/10.1088/1748-9326/ac3f62; https://validate.perfdrive.com/fb803c746e9148689b3984a31fccd902/?ssa=136f13c7-f273-4bbb-97c4-ffb7f7141571&ssb=20440214526&ssc=https%3A%2F%2Fiopscience.iop.org%2Farticle%2F10.1088%2F1748-9326%2Fac3f62&ssi=80a9f2a7-8427-4585-ba8d-157557f170e8&ssk=support@shieldsquare.com&ssm=61447033118036567839175773647091167&ssn=a77f856051f2fe336b35a570196d4117532017f9ea44-4e1f-4e35-b32330&sso=31f3c15e-f9d9f87a371fcaee7b37e1a23a9ba93a5adb8ffad7604c17&ssp=07282521611719399284171966681121822&ssq=74300948709405427150105699921792057740751&ssr=NTIuMy4yMTcuMjU0&sst=com.plumanalytics&ssu=&ssv=&ssw=&ssx=eyJ1em14IjoiN2Y5MDAwMWUxYTVkMGQtYjRlNi00ZTQ0LWFmYTgtNzUxMTFmZjg0ZDlmNS0xNzE5MzA1Njk5NDA1MzgxMzk1MjYxLWQ3YTJiOTRkMmUxZGExZmY4MzkwOCIsIl9fdXptZiI6IjdmNjAwMGMwYjYzMzU0LTQ4ZGQtNGM1NS04NWZlLTQ3NmYyODFjMTlkODE3MTkzMDU2OTk0MDUzODEzOTUyNjEtMWM0NTk1NGVhOGIwYWVmNjgzOTA4IiwicmQiOiJpb3Aub3JnIn0=
IOP Publishing
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know