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Disaggregation Method of Carbon Emission: A Case Study in Wuhan, China
Urban areas contribute significant carbon emissions. Evaluating and analysing the spatial distribution of carbon emissions are the foundations of low-carbon city development and carbon emissions reduction. In this study, carbon emission inventory was first constructed and carbon emissions in Wuhan were estimated on the basis of energy consumption. Second, the spatial distribution models of carbon emissions in different sectors were developed on the basis of the census of the Wuhan geographical conditions data and other thematic data. Third, the carbon emission distribution in Wuhan was analyzed at the central urban, functional, new urban, built-up, and metropolitan development area scale. Results show that the industry sector emits most of the carbon emissions in Wuhan, followed by the residential population. Carbon emissions in the metropolitan development area can stand for the true carbon emissions in Wuhan. Thus, a geographically weighted (GW) model was adopted to analyze the correlation coefficients between economical-social factors (gross domestic product, population density, road density, industrial land and residential land) and carbon emissions in the metropolitan development area. Comparisons with other studies show that the disaggregation method we proposed in this work, especially the adoption of geographical condition census data, can reflect the spatial distribution of carbon emissions of different sectors at the city scale.
Disaggregation Method of Carbon Emission: A Case Study in Wuhan, China
Urban areas contribute significant carbon emissions. Evaluating and analysing the spatial distribution of carbon emissions are the foundations of low-carbon city development and carbon emissions reduction. In this study, carbon emission inventory was first constructed and carbon emissions in Wuhan were estimated on the basis of energy consumption. Second, the spatial distribution models of carbon emissions in different sectors were developed on the basis of the census of the Wuhan geographical conditions data and other thematic data. Third, the carbon emission distribution in Wuhan was analyzed at the central urban, functional, new urban, built-up, and metropolitan development area scale. Results show that the industry sector emits most of the carbon emissions in Wuhan, followed by the residential population. Carbon emissions in the metropolitan development area can stand for the true carbon emissions in Wuhan. Thus, a geographically weighted (GW) model was adopted to analyze the correlation coefficients between economical-social factors (gross domestic product, population density, road density, industrial land and residential land) and carbon emissions in the metropolitan development area. Comparisons with other studies show that the disaggregation method we proposed in this work, especially the adoption of geographical condition census data, can reflect the spatial distribution of carbon emissions of different sectors at the city scale.
Disaggregation Method of Carbon Emission: A Case Study in Wuhan, China
Minghai Luo (author) / Sixian Qin (author) / Haoxue Chang (author) / Anqi Zhang (author)
2019
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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