A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space

Yilong Wang, Philippe Ciais, Grégoire Broquet, François Marie Bréon, Tomohiro Oda, Franck Lespinas, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, Haoran Xu, Shu Tao, Kevin Gurney, Geoffrey Roest, Diego Santaren, Yongxian Su

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A large fraction of fossil fuel CO 2 emissions emanate from "hotspots", such as cities (where direct CO 2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO 2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO 2 has the potential to provide independent estimates of CO 2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO 2 accuracy and precision of < 1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO 2 (XCO 2 ). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO 2 emitting sources which generate coherent XCO 2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as "emission clumps" hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO 2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72% of the global fossil fuel CO 2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO 2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO 2 . The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

Original languageEnglish (US)
Pages (from-to)687-703
Number of pages17
JournalEarth System Science Data
Volume11
Issue number2
DOIs
StatePublished - May 17 2019

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space'. Together they form a unique fingerprint.

Cite this