Comparing GOSAT observations of localized CO2 enhancements by large emitters with inventory‐based estimates. Issue 7 (2nd April 2016)

• Record Type: Journal Article
• Authors: Janardanan, Rajesh; Maksyutov, Shamil; Oda, Tomohiro; Saito, Makoto; Kaiser, Johannes W.; Ganshin, Alexander; Stohl, Andreas; Matsunaga, Tsuneo; Yoshida, Yukio; Yokota, Tatsuya
• Is Part Of: Geophysical research letters. Volume 43:Issue 7(2016)
• Page Start: 3486
• Page End: 3493
• Publication Date: 2016-04-02
• Subjects: anthropogenic CO2 emission -- emission inventory -- megacities -- GOSAT; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2016GL067843
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: We employed an atmospheric transport model to attribute column‐averaged CO2 mixing ratios ( X CO2 ) observed by Greenhouse gases Observing SATellite (GOSAT) to emissions due to large sources such as megacities and power plants. X CO2 enhancements estimated from observations were compared to model simulations implemented at the spatial resolution of the satellite observation footprint (0.1° × 0.1°). We found that the simulated X CO2 enhancements agree with the observed over several continental regions across the globe, for example, for North America with an observation to simulation ratio of 1.05 ± 0.38 ( p < 0.1), but with a larger ratio over East Asia (1.22 ± 0.32; p < 0.05). The obtained observation‐model discrepancy (22%) for East Asia is comparable to the uncertainties in Chinese emission inventories (~15%) suggested by recent reports. Our results suggest that by increasing the number of observations around emission sources, satellite instruments like GOSAT can provide a tool for detecting biases in reported emission inventories. Key Points: GOSAT estimated CO2 abundance due to large emitters compared to inventory‐based estimate Observed and inventory‐based CO2 abundance agree well over global and subcontinental scales Observation‐model discrepancy (22%) over East Asia is close to uncertainty in emission inventory