Detectability of COVID-19 global emissions reductions in local CO2 concentration measurements

Abstract

It is estimated that global anthropogenic carbon dioxide (CO _2 ) emissions reduced by up to 12% at the start of 2020 compared to recent years due to the COVID-19 related downturn in economic activity. Despite the large decrease in CO _2 emissions, no reduction in the trend in background atmospheric CO _2 concentrations has been detected. So, how long would it take for sustained COVID-19 CO _2 emission reductions to be detected in daily and monthly averaged local CO _2 concentration measurements? CO _2 concentration measurements for five measurement sites in the UK and Ireland are combined with meteorological numerical weather prediction data to build statistical models that can predict future CO _2 concentrations. It is found that $75\%$ of the observed daily variability can be explained by these simple models. Emission reduction scenario experiments using these simple models illustrate that large daily and seasonal variability in local CO _2 concentrations precludes the rapid emergence of a detectable signal. COVID-19 magnitude emissions reductions would only be detectable in the daily CO _2 concentrations after at least 38 months and in monthly CO _2 concentrations after 11 months of sustained reductions. For monthly CO _2 concentrations the time of emergence is similar for all sites since the seasonal variability is largely driven by non-local fluxes of CO _2 between the terrestrial biosphere and the atmosphere. The COVID-19 CO _2 anthropogenic emissions reductions are similar in magnitude to those that are required to meet the Paris Agreement target of keeping global temperatures below $2\,^{\circ}$ C. This study demonstrates that, using measurements alone, there will be a considerable lag between changes in global anthropogenic emissions and a detected signal in local CO _2 concentration trends. Thus, there is likely to be a delay of several years between changes in policy designed to meet CO _2 anthropogenic emissions targets and our ability to detect the impact of these policies on CO _2 concentrations using atmospheric measurements alone.

Keywords

• CO2 emissions policy
• climate change
• multiple linear regression