Can a regional-scale reduction of atmospheric CO2 during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO2 retrievals

Abstract

Abstract. The COVID-19 pandemic resulted in reduced anthropogenic\ncarbon dioxide (CO 2 ) emissions during 2020 in large parts of the world.\nTo investigate whether a regional-scale reduction of anthropogenic CO 2 \nemissions during the COVID-19 pandemic can be detected using space-based\nobservations of atmospheric CO 2 , we have analysed a small ensemble of\nOCO-2 and GOSAT satellite retrievals of column-averaged dry-air mole\nfractions of CO 2 , i.e. XCO 2 . We focus on East China and use a\nsimple data-driven analysis method. We present estimates of the relative\nchange of East China monthly emissions in 2020 relative to previous periods,\nlimiting the analysis to October-to-May periods to minimize the impact of\nbiogenic CO 2 fluxes. The ensemble mean indicates an emission reduction\nby approximately 10\u2009%\u2009 ± \u200910\u2009% in March and April 2020. However, our\nresults show considerable month-to-month variability and significant\ndifferences across the ensemble of satellite data products analysed. For\nexample, OCO-2 suggests a much smaller reduction ( ∼ \u20091\u2009%–2\u2009%\u2009 ± \u20092\u2009%). This indicates that it is challenging to reliably detect and\nto accurately quantify the emission reduction with current satellite data\nsets. There are several reasons for this, including the sparseness of the\nsatellite data but also the weak signal; the expected regional XCO 2 \nreduction is only on the order of 0.1–0.2\u2009ppm. Inferring COVID-19-related\ninformation on regional-scale CO 2 emissions using current satellite\nXCO 2 retrievals likely requires, if at all possible, a more\nsophisticated analysis method including detailed transport modelling and\nconsidering a priori information on anthropogenic and natural CO 2 surface\nfluxes.