Evaluation and calculation of urban carbon emission reduction potential based on spatiotemporal geographic model

Abstract

With the growth of urban carbon emissions, found that the current urban carbon emission reduction potential assessment and calculation in carbon emissions data source, research index selection and cost are some problems, to promote the realization of low carbon emission reduction target, it is necessary to use space and space and geographical weighted regression model to obtain the spatial and temporal distribution of urban carbon reduction. This article combined geographic information system (GIS) technology to construct a spatial database. Based on the geographic weighted regression (GWR) model, a time dimension was introduced to construct a spatiotemporal GWR model, which was used to obtain the spatiotemporal distribution information of urban CEs and draw a spatial distribution (SD) map of urban CE reduction potential (RP). This article also conducted experimental tests on the carbon reduction potential (CRP) of Chinese cities by combining different carbon reduction (CR) measures. This paper uses three CR methods to test P of these cities respectively measure A adjust industrial structure, measure B to promote low carbon technology innovation and measure C is to optimize the urban space structure, the experimental results show that the average carbon emission intensity of measure A cities is 0.72 tons / yuan, 0.02 tons / 0,0.04 tons / yuan less than measures B and C; the average CE efficiency of measures A cities is 0.85,0.02 and 0.05 compared with measures B and C respectively. From the above data, adjusting the industrial structure can effectively improve the CE efficiency of various cities, reduce the CE, reduce the CE intensity, and promote the realization of CE reduction in cities.