A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space
Authors: Wang Yilong , Ciais Philippe , Broquet Grégoire , Bréon François-Marie , Oda Tomohiro , Lespinas Franck , Meijer Yasjka , Loescher Armin , Janssens-Maenhout Greet , Zheng Bo , Xu Haoran , Tao Shu , Gurney Kevin R. , Roest Geoffrey , Santaren Diego , Su Yongxian 
Published: May 2019

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.