On the Detection of COVID-Driven Changes in Atmospheric Carbon Dioxide.

ABSTRACT: We assess the detectability of COVID-like emissions reductions in global atmospheric CO₂ concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO₂ sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions (2 or 4 times the observed reductions). Internal variability and carbon-concentration feedbacks obscure the detectability of short-term emission reductions in atmospheric CO₂. COVID-driven changes in the simulated,

SUBMITTER: Lovenduski NS 

PROVIDER: S-EPMC8667626 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature