Satellite-based estimates of decline and rebound in China’s CO ₂ emissions during COVID-19 pandemic

Abstract

Changes in CO2 emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO2 emissions during the pandemic. Unlike activity data, our observation-based analysis deploys independent measurement of pollutant concentrations in the atmosphere to correct misrepresentation in the bottom-up data and can provide more detailed insights into spatially explicit changes. Specifically, we use TROPOMI observations of NO2 to deduce 10-day moving averages of NOx and CO2 emissions over China, differentiating emissions by sector and province. Between January and April 2020, China’s CO2 emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels before the coronavirus outbreak at the beginning of January 2020 owing to the fast economic recovery in provinces where industrial activity is concentrated.

Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals

“…These findings, which are consistent with other recent studies (e.g. Zeng et al, 2020), are not unexpected. Regional XCO 2 enhancements due to fossil fuel emissions are typically only 1 to 2 ppm and even a 10 % emission reduction would therefore only correspond to a reduction of the fossil-fuel-related regional XCO 2 enhancement by 0.1 to 0.2 ppm.…”

“…They concluded that these places have not been well observed by the OCO-2 satellite because of frequent or persistent cloud conditions and they give recommendations for future carbon-monitoring systems. Zeng et al (2020) used modelling, GOSAT XCO 2 and other data sets. They conclude that GOSAT is able to detect a short-term global mean XCO 2 anomaly decrease of 0.2-0.3 ppm after temporal averaging (e.g.…”

Decreased Anthropogenic CO2 Emissions during the COVID-19 Pandemic Estimated from FTS and MAX-DOAS Measurements at Urban Beijing

“…This reduction in XCO 2 growth, as estimated from the target-background difference, reveals that the related atmospheric concentration changes can be detected by column measurement from the satellite; however, the method is too simplified to quantify the reduction in anthropogenic emission. The reduction is a bit higher than the average reduction in China (11.5%) inferred by sector-specific ratio maps of CO 2 to NOx emissions, where the latter was estimated from TROPOMI NO 2 reduction [17]. These estimations are higher than the bottom-up estimation (6.6%) from the traffic data in Beijing [18] or the average reduction in China estimated from all inventories (~10%).…”

Local Anomalies in the Column‐Averaged Dry Air Mole Fractions of Carbon Dioxide Across the Globe During the First Months of the Coronavirus Recession

“…The variations in human CO 2 emissions have been considerable within just a few months, but, depending on both their human origin and the specific local development of the pandemic, have been concentrated in some places that changed over time. In early April, emissions in China rebounded to pre‐pandemic levels (Zheng, Geng, et al, 2020) as several Western countries had only started restrictions on mobility. Within the same country, Covid‐induced emission reductions could coexist with an increase in emissions linked or not to the pandemic: according to the National Bureau of Statistics of China (http://data.stats.gov.cn/english/), thermal power generation in some western provinces of China (Yunnan, Xinjiang, and Guangxi) notably increased in March, while it decreased in the eastern provinces of China.…”