The COVID-19 pandemic resulted in reduced carbon dioxide (CO2) emissions in 2020 in large parts of the world. We have analysed an ensemble of satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2, to find out if the COVID-19 related regional-scale reduction of anthropogenic CO2 emissions can be detected from space. We focus on East China and analysed a set of latest version XCO2 data products from the satellites Orbiting Carbon Observatory-2 (OCO-2) and Greenhouse gases Observing SATellite (GOSAT). We use a data-driven approach, which is based on the computation of XCO2 anomalies using a method called DAM. Via DAM, trends and seasonal variations are largely filtered out and resulting positive values of the XCO2 anomalies correlate with the location of major CO2 source regions such as East China after spatio-temporal averaging. We analysed satellite data between January 2015 to May 2020 and compared monthly XCO2 anomalies in the time period January to May 2020 with corresponding monthly XCO2 anomalies from previous years. In order to link the satellite-derived XCO2 anomalies to East China fossil fuel (FF) emissions, we used target region XCO2 and corresponding FF emissions from a model.