Spatial-Temporal Pattern Evolution And Influencing Factors Of Carbon Emissions From Industrial Processes In China

As the largest CO2 emitter,China’s response to climate change is both an inherent need to promote its sustainable development and a responsibility to build a community of human destiny.2020 will see China pledge to increase its independent national contribution,adopt stronger policies and measures,and strive to peak CO2 emissions by 2030 and achieve carbon neutrality by 2060.The key to achieving the "double carbon" goal lies in the accounting and analysis of carbon emissions.At present,among the sources of greenhouse gas emissions in China,carbon emissions from industrial processes rank second,after carbon emissions from energy activities,and is a key area of carbon emissions that requires attention.Therefore,accounting for industrial process carbon emissions and exploring the total and structural characteristics of industrial process carbon emissions,the evolution of spatial patterns and their influencing factors at the provincial level in China can provide a reference for understanding the basic situation of industrial process carbon emissions at the provincial level,formulating regionally differentiated policies and measures for carbon control and emission reduction in industrial production processes,and implementing carbon reduction actions in industrial production processes.In this paper,firstly,according to the classification of economic sectors in the IPCC Guidelines for National Greenhouse Gas Inventories,the carbon emissions of industrial processes in 31 provinces of China(excluding Hong Kong,Macao and Taiwan)from 2010 to 2019 are accounted for according to the carbon emission accounting method for industrial processes published by the IPCC,using the carbon dioxide emission factor data from the latest research results at home and abroad,and analyzing the carbon The spatial pattern of carbon emissions from industrial processes in China is explored by using global spatial autocorrelation,local spatial autocorrelation and standard deviation ellipse analysis,and the spatial and temporal patterns of carbon emissions from extractive industries,metal industries and chemical industries are analyzed;finally,the factors affecting carbon emissions from industrial processes in China and each province are analyzed by using geographically weighted regression analysis.Finally,a geographically weighted regression analysis was used to analyze the factors affecting the carbon emissions of industrial processes in China and each province.The main findings of this study are summarized as follows:(1)Between 2010 and 2019,the total industrial process carbon emissions in China showed two stages of rapid increase followed by a slow increase,in which the growth rate was 5.03% until 2014 and 0.67% afterward.The proportion of each industry in the total carbon emissions of industrial processes from high to low is the extractive industry,metal industry,and chemical industry,in which the proportion of the extractive industry is stable at 49%,the proportion of metal industry increases from 35.15% to 38.31%,and the proportion of chemical industry decreases from 15.17% to 13.04%.The industrial process carbon emissions of three major industries,namely,the extractive industry,metal industry,and chemical industry,also show the characteristics of rapid increase and then slowdown in 2014,with negative growth of carbon emissions of the chemical industry after 2014.(2)Spatial heterogeneity exists in the total carbon emissions of industrial processes and industrial process emissions of key industries in China and shows the general characteristics of local clustering.The spatial differences of total carbon emissions are generally stable,and the high value areas are mainly concentrated in central China and its surrounding provinces,and show a pattern of clustering in the northeast-southwest direction,with the degree of clustering gradually increasing and showing more aggregation around central China;the spatial differences of carbon emissions from extractive industries have decreased,and the high value areas are mainly concentrated in central China and its surrounding provinces,and show a pattern of clustering in the northeast-southwest direction,and the degree of clustering is as follows The spatial differences in carbon emissions from the metal industry are generally stable,with the high value areas mainly concentrated in North and Central China and showing a Northeast-Southwest clustering pattern,with the degree of clustering gradually weakening and then increasing in the direction of the Southwest region;the spatial differences in carbon emissions from the metal industry are generally stable,with the high value areas mainly concentrated in North and Central China,and showing a Northeast-Southwest clustering pattern,with the degree of clustering gradually The spatial differences of carbon emissions from the chemical industry have expanded significantly,and the high-value areas are mainly concentrated in East,Central,North and Northwest China,showing a pattern of clustering in the NortheastSouthwest direction first and then in the Northwest-Southeast direction,with the degree of clustering gradually weakening and clustering in the Northwest direction.(3)The change in China’s industrial process carbon emissions is mainly influenced by population size,innovation level,and industrial structure,and the influence of each influencing factor on the total industrial process carbon emissions has obvious spatial dependence and spatial heterogeneity characteristics,which is manifested as the degree of influence of each factor on the total industrial process carbon emissions from high to low in each category,with provinces within each category showing spatial clustering and provinces between each category showing obvious spatial differences.The increase in population size and industrial structure will promote the growth of industrial process carbon emissions,and the increase in innovation level will suppress the growth of industrial process carbon emissions,and the degree of influence of each influencing factor on the whole country has increased,and the degree of influence of innovation level has increased the most.