Spatiotemporal Analysis of Carbon Emissions and Carbon Storage Using National Geography Census Data in Wuhan, China

Mapping changes in carbon emissions and carbon storage (CECS) with high precision at a small scale (urban street-block level) can improve governmental policy decisions with respect to the construction of low-carbon cities. In this study, a methodological framework for assessing the carbon budget and its spatiotemporal changes from 2015 to 2017 in Wuhan is proposed, which is able to monitor a large area. To estimate the carbon storage, a comprehensive coefficient model was adopted with carbon density factors and corresponding land cover types. Details regarding land cover were extracted from the Geographic National Census Data (GNCD), including forests, grasslands, croplands, and gardens. For the carbon emissions, an emission-factor model was first used and a spatialization operation was subsequently performed using the geographic location that was obtained from the GNCD. The carbon emissions that were identified in the study are from fossil-fuel consumption, industrial production processes, disposal of urban domestic refuse, and transportation. The final dynamic changes in the CECS, in addition to the net carbon emissions, were monitored and analyzed, yielding temporal and spatial maps with a high-precision at a small scale. The results showed that the carbon storage in Wuhan declined by 2.70% over the three years, whereas the carbon emissions initially increased by 0.2%, and subsequently decreased by 3.1% over this period. The trend in the net carbon emission changes was similar to that of the carbon emissions, demonstrating that the efficiency of carbon reduction was improved during this period. Precise spatiotemporal results at the street-block level can offer insights to governments that are engaged in urban carbon cycle decision making processes, improving their capacities to more effectively manage the spatial distribution of CECS