Observing carbon dioxide emissions over China's cities and industrial areas with the Orbiting Carbon Observatory-2

Abstract

Abstract. In order to track progress towards the global climate targets, the parties that signed the Paris Climate Agreement will regularly report their anthropogenic carbon dioxide (CO2) emissions based on energy statistics and CO2 emission factors. Independent evaluation of this self-reporting system is a fast-growing research topic. Here, we study the value of satellite observations of the column CO2 concentrations to estimate CO2 anthropogenic emissions with 5 years of the Orbiting Carbon Observatory-2 (OCO-2) retrievals over and around China. With the detailed information of emission source locations and the local wind, we successfully observe CO2 plumes from 46 cities and industrial regions over China and quantify their CO2 emissions from the OCO-2 observations, which add up to a total of 1.3 Gt CO2 yr−1 that accounts for approximately 13 % of mainland China's annual emissions. The number of cities whose emissions are constrained by OCO-2 here is 3 to 10 times larger than in previous studies that only focused on large cities and power plants in different locations around the world. Our satellite-based emission estimates are broadly consistent with the independent values from China's detailed emission inventory MEIC but are more different from those of two widely used global gridded emission datasets (i.e., EDGAR and ODIAC), especially for the emission estimates for the individual cities. These results demonstrate some skill in the satellite-based emission quantification for isolated source clusters with the OCO-2, despite the sparse sampling of this instrument not designed for this purpose. This skill can be improved by future satellite missions that will have a denser spatial sampling of surface emitting areas, which will come soon in the early 2020s.

Carbon Dioxide Emissions During the 2018 Kilauea Volcano Eruption Estimated Using OCO‐2 Satellite Retrievals

“…The volcanic plume was determined to display some non‐Gaussian features (see the supporting information for details); however, we include the Gaussian fits, and corresponding coefficients of determination ( R 2 ), in Figure 2 to help illustrate the cross‐sectional distribution of trace gases and aerosol in the volcanic plume. The distribution of SO 2 and AOD were well fitted by the Gaussian functions, while the XCO 2 retrieval fit was moderate ( R 2 of 0.62) with similar correlation values presented in recent studies using OCO‐2 to derive localized CO 2 fluxes (e.g., Zheng et al, 2020).…”

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

“…After the first work of Nassar et al (2017) and Reuter et al (2019), Zheng, Chevallier, et al (2020) developed a method to estimate the emissions that are associated with atmospheric plumes from isolated clusters of anthropogenic CO 2 emissions (cities and industrial areas) that are visible in OCO‐2 retrievals over China. We have adapted the initial algorithm to the whole world in order to fully automate the procedure and remove the specificities for China.…”

“…A third step limits the cases to the vicinity of the fossil fuel emission zones. Zheng, Chevallier, et al (2020) used a detailed inventory of China for this. We have replaced this with a simple threshold on NO 2 TCVD retrieved from OMI: cases are kept if the maximum gridded TCVD between the day before and the next day (3 values, in order to compensate for the incomplete global coverage of the instrument each day) at the peak of the Gaussian curve is greater than 10 15 molecules per cm 2 .…”

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

“…We focus on China because regional-scale COVID-19related CO 2 emission reductions are expected to be largest there early in the pandemic (Le Quéré et al, 2020;Liu et al, 2020). Satellite data have been used to estimate China's CO 2 emissions during the COVID-19 pandemic as shown in Zheng et al (2020b), but that study inferred CO 2 reductions from retrievals of nitrogen dioxide (NO 2 ) not using XCO 2 . Estimates of emission reductions have also been derived from bottom-up statistical assessments of fossil fuel use and other economic indicators.…”