AUTHOR=Liu Yu , Wu Binwei , Yue Tianxiang 

TITLE=Spatiotemporal analysis of global atmospheric XCO2 concentrations before and after COVID-19 using HASM data fusion method

JOURNAL=Frontiers in Environmental Science

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.1079480

DOI=10.3389/fenvs.2022.1079480

ISSN=2296-665X

ABSTRACT=<p>The COVID-19 outbreak that began in 2020 has changed human activities and thus reduced anthropogenic carbon emissions in most parts of the world. To accurately study the impact of the COVID-19 pandemic on changes in atmospheric XCO<sub>2</sub> concentrations, a data fusion method called High Accuracy Surface Modeling (HASM) is applied using the CO<sub>2</sub> simulation from GEOS-Chem as the driving field and GOSAT XCO<sub>2</sub> observations as the accuracy control conditions to obtain continuous spatiotemporal global XCO<sub>2</sub> concentrations. Cross-validation shows that using High Accuracy Surface Modeling greatly improves the mean absolute error and root mean square error of the XCO<sub>2</sub> data compared with those for GEOS-Chem simulation data before fusion, and the <italic>R</italic><sup>2</sup> is also increased from 0.54 to 0.79 after fusion. Moreover, OCO-2/OCO-3 XCO<sub>2</sub> observational data verify that the fused XCO<sub>2</sub> data achieve a lower MAE and RMSE. Spatiotemporal analysis shows that the global XCO<sub>2</sub> concentration exhibited no obvious trend before or after the COVID-19 outbreak, but the growth of global and terrestrial atmospheric XCO<sub>2</sub> in 2020 can reflect the impact of the COVID-19 pandemic; that is, the rapid growth in terrestrial atmospheric XCO<sub>2</sub> observed before 2019 slowed, and high-speed growth resumed in 2021. Finally, obvious differences in the pattern of XCO<sub>2</sub> growth are found on different continents.</p>