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The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO₂ emission and toxic air pollution (CO and NO₂). We use column-averaged dry-air mole fractions of CO₂ and CO (XCO₂ and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO₂ column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO₂ emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO₂ and XCO, and XNO₂ (ΔXCO₂, ΔXCO, and ΔXNO₂) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO₂ anomalies derived from FTS time series data provide the ΔXCO to ΔXCO₂ ratio (the correlation slope). The ΔXCO to ΔXCO₂ ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO₂ ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO₂ emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO₂ over the same time period was estimated to be 15% in Beijing from the XCO₂ anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO₂ observation provides a 21.6% decline in NO₂. The NO₂ to CO₂ correlation indicates a 38.2% decline in the CO₂ traffic emission sector. Overall, the reduction in anthropogenic CO₂ emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing.