The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. To investigate whether a regional-scale reduction of anthropogenic CO2 emissions during the COVID-19 pandemic can be detected using space-based observations of atmospheric CO2, we have analysed a small ensemble of OCO-2 and GOSAT satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2. We focus on East China and use a simple data-driven analysis method. We present estimates of the relative change of East China monthly emissions in 2020 relative to previous periods, limiting the analysis to October-to-May periods to minimize the impact of biogenic CO2 fluxes. The ensemble mean indicates an emission reduction by approximately 10 % ± 10 % in March and April 2020. However, our results show considerable month-to-month variability and significant differences across the ensemble of satellite data products analysed. For example, OCO-2 suggests a much smaller reduction (∼ 1 %-2 % ± 2 %). This indicates that it is challenging to reliably detect and to accurately quantify the emission reduction with current satellite data sets. There are several reasons for this, including the sparseness of the satellite data but also the weak signal; the expected regional XCO2 reduction is only on the order of 0.1-0.2 ppm. Inferring COVID-19-related information on regional-scale CO2 emissions using current satellite XCO2 retrievals likely requires, if at all possible, a more sophisticated analysis method including detailed transport modelling and considering a priori information on anthropogenic and natural CO2 surface fluxes.
