Short-term reduction of regional enhancement of atmospheric CO₂ in China during the first COVID-19 pandemic period

Abstract

Recent studies have reported a 9% decrease in global carbon emissions during the COVID-19 lockdown period; however, its impact on the variation of atmospheric CO2 level remains under question. Using atmospheric CO2 observed at Anmyeondo station (AMY) in South Korea, downstream of China, this study examines whether the decrease in China’s emissions due to COVID-19 can be detected from the enhancement of CO2 mole fraction (ΔCO2) relative to the background value. The Weather Research and Forecasting–Stochastic Time-Inverted Lagrangian Transport model was applied to determine when the observed mole fractions at AMY were affected by air parcels from China. Atmospheric observations at AMY showed up to a −20% (−1.92 ppm) decrease in ΔCO2 between February and March 2020 compared to the same period in 2018 and 2019, particularly with a −34% (−3.61 ppm) decrease in March. ΔCO, which was analyzed to explore the short-term effect of emission reductions, had a decrease of −43% (−80.66 ppb) during the lockdown in China. Particularly in East China, where emissions are more concentrated than in Northeast China, ΔCO2 and ΔCO decreased by −44% and −65%, respectively. The ΔCO/ΔCO2 ratio (24.8 ppb ppm−1), which is the indicator of emission characteristics, did not show a significant difference before and after the COVID-19 lockdown period (α = 0.05), suggesting that this decrease in ΔCO2 and ΔCO was associated with emission reductions rather than changes in emission sources or combustion efficiency in China. Reduced carbon emissions due to limited human activity resulted in a decrease in the short-term regional contribution to the observed atmospheric CO2.

Satellite reveals a steep decline in China’s CO 2 emissions in early 2022

“…The long lifetime of CO 2 makes it hard to directly investigate the effect of its emission variation on CO 2 concentration ( 36 ). On the basis of a well-established method ( 37 ), we calculate CO 2 concentrations above the background levels (ΔCO 2 ) using the CO 2 concentrations from four surface stations (fig. S5), including Anmyeondo (AMY), Jeju Gosan (JGS), Ryori (RYO), and Yonagunijima (YON), all of which are located downwind of China (World Data Centre for Greenhouse Gases, https://gaw.kishou.go.jp/).…”

Assessing the “negative effect” and “positive effect” of COVID-19 in China

“…It can be seen that indicators used to measure CO 2 emission are usually based on production perspective ( Sim et al, 2022 ), while some conventional indicators are used to assess the performance of the national economy such as domestic production, gross national income, and economic growth rate. These indicators can well measure the amount of direct economy loss and CO 2 emission reduction from COVID-19, but the indirect economy loss and CO 2 emission reduction under the COVID-19 will trigger the economy of the total chain reaction, which will continuously intensify, amplify and expand their influence through circulation and causality accumulation.…”

Near-real-time estimation of fossil fuel CO2 emissions from China based on atmospheric observations on Hateruma and Yonaguni Islands, Japan

“…Since the estimated change of 0.5–0.7 PgC corresponds to the globally averaged atmospheric CO 2 mole fraction of 0.2–0.3 ppm, it is rather difficult to detect such subtle signals in the atmospheric CO 2 trends after the emitted CO 2 is mixed globally (Lovenduski et al 2021 ). Nevertheless, several studies succeeded in detecting signals related to the FFCO 2 reductions in China caused by the COVID-19 lockdown in both local-scale observations (Zeng et al 2022 ; Liu et al 2021 ; Wu et al 2021 ) and regional-scale observations (Tojima et al 2020 ; Buchwitz et al 2021 ; Weir et al 2021 ; Sim et al 2022 ) of atmospheric CO 2 .…”