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Wang et al. Carbon Footprints 2024;3:14 https://dx.doi.org/10.20517/cf.2024.19 Page 9 of 19

For point source emissions, the proxy data uncertainty could be set to 0 because of the manual geographic
identification of high-emission point source emissions one by one in this study. The proxy data uncertainty
of non-point source emissions was mainly concentrated in residential emissions and transportation
emissions. The proxy data uncertainty of transportation emissions was determined by the drift value of
traffic volume, which was set to ±5% of road traffic volume. For the latter, we estimated by the grid drift
[51]
method . The target grid was moved by 10% of the grid length in the direction of south, north, east, and
west, resulting in four drifted grids. Subsequently, we calculated the weighted sum by applying a ratio of
90% of the target grid’s population and 10% of the adjacent grid’s population in each drifted grid. This
process yielded the weighted population data for the four drifted girds, from which the standard deviation
of population data was computed as the proxy data uncertainty for the target grid.

After separately calculating the proxy data uncertainties of point and non-point sources, the uncertainties of
the above emissions were aggregated by using the error transfer algorithm, resulting in the proxy data
uncertainty of inventory.

RESULTS
Gridded CO emission inventory and results analysis
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The spatial allocation results of the CO emission inventory for 2020 in Chengdu, namely the high-
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resolution emission inventory of Chengdu (HEI-CD), are shown in Figure 5A. This figure illustrates the
spatial distribution of emission intensity within the study area. Different colored grids represent varying
levels of emission intensity, measured in tons per square kilometer per year (t·km ·yr ). Red areas indicate
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the highest emission intensity, while blue areas indicate the lowest.
In the study area, three high-emission areas are identified [Figure 5B]: the city center, the northwest
industrial zone, and the eastern power plant region. The combined emissions from these three high-
emission areas total 20,228 kt, accounting for 52.9% of the total emissions of Chengdu. Region 1, which
represents emission intensity in the city center, includes five districts: Qingyang District, Wuhou District,
Jinniu District, Chenghua District, and Jinjiang District. Emissions in this area total 8,238 kt, with an
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emission intensity of 5.51 kt·km ·yr . This region has a dense population, a well-developed road network,
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and numerous service facilities, with emissions primarily from transportation and residents. Region 2,
located in the northwest industrial zone, mainly includes Dujiangyan City and Pengzhou. City. The
emissions for this region amount to 8,164 kt, with an emission intensity of 9.21 kt·km ·yr , accounting for
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approximately 21.3% of the total emissions. This area contains a large number of chemical enterprises and
several building materials enterprises, with cement manufacturing plants being the primary source of CO
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emissions. The cement manufacturing process requires the combustion of large amounts of coal to calcine
limestone. Coal combustion produces significant amounts of CO , and the thermal decomposition of
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limestone also generates substantial CO emissions. The cement industry has become a major global source
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of CO emissions, with fuel combustion accounting for 35% and the calcination process for approximately
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52% . Region 3 is situated on the eastern side of the city center, within the territory of Jintang County. The
[52]
total emissions for this region amount to 3,827 kt, accounting for 10%. The primary source of these
emissions is fossil fuel combustion at a major power plant.
Chengdu currently comprises 20 district- and county-level administrative units, along with 371 township-
and subdistrict-level administrative units. The emission intensity and quantity for each district, county,
county-level city, township, town, and subdistrict are shown in Figure 5C, with the emission quantity of
town-level administrative units represented by a color bar and the emission intensity of district-level units
depicted by histograms. The top five districts with the highest emission intensities are located in the city