Abstract
Abstract. A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 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 CO2 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 CO2 has the potential to provide independent estimates of CO2 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 XCO2 accuracy and precision of <1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). 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 CO2 emitting sources which generate coherent XCO2 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 XCO2 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 CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.
Highlights
Monitoring the effectiveness of emission reductions after the Paris Agreement on Climate (UNFCCC, 2015) requires frequently updated estimates of fossil fuel CO2 emissions and a global synthesis of these estimates
We focus on planned low earth-orbiting (LEO) imagers on Sentinel missions, assuming an equator crossing time around 11:30 local time (Buchwitz et al, 2013; Broquet et al, 2018), so that XCO2 plumes sampled by these imagers are from morning emissions
We have identified a set of emission clumps with large emission rates from a high-resolution emission inventory
Summary
Monitoring the effectiveness of emission reductions after the Paris Agreement on Climate (UNFCCC, 2015) requires frequently updated estimates of fossil fuel CO2 emissions and a global synthesis of these estimates. The Greenhouse Gases Observing Satellite 2 (GOSAT-2) aims to measure XCO2 at 0.5 ppm precision (https://directory.eoportal.org/ web/eoportal/satellite-missions/g/gosat-2, last access: 7 August 2018). XCO2 measurements from selected 10 km wide OCO-2 tracks downwind of large power plants were used to quantify their emissions by fitting observed XCO2 plumes with Gaussian dispersion models (Nassar et al, 2017). The primary scientific goal of the OCO-2 mission was to estimate natural land and ocean carbon fluxes, and tracks overpassing power plants are very sporadic, given the narrow swath width and frequent clouds. The list includes the Geostationary Carbon Observatory (GeoCARB) mission (Polonsky et al, 2014), the OCO-3 instrument on board the International Space Station capable of pointing to chosen emitting areas (https://www.nasa.gov/mission_pages/ station/research/experiments/2047.html, last access: 7 August 2018) and a constellation of low earth-orbiting (LEO) imagers with a swath of a few hundred kilometers planned as future operational missions within the European Copernicus Program (Ciais et al, 2015)
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