Analysis Of Driving Factors Of Carbon Emission Intensity And Scenario Prediction Of Energy Consumption In China’s Service Industry

With the diminishing marginal effect of carbon emission reduction in agriculture and industry,and the introduction of the "3060" dual carbon target,the full potential of energy saving and emission reduction in the service industry has become an important part of academic research.This paper scientifically calculates the carbon emission intensity of the service industry from 2000 to 2020,and analyzes the spatial and temporal evolution of carbon emission intensity at the national,four regional and industry levels.The spatial and temporal heterogeneity of carbon emission intensity of service industry by different driving factors is analyzed by GTWR model.A service sector carbon emission prediction model is constructed to explore the evolution of carbon emissions in the service sector under high carbon development,benchmark and green energy saving scenarios from 2021 to 2050,analyze the achievement of carbon peak targets and peak paths in 2030,and propose emission reduction strategies on this basis.Through the above study,the following conclusions are mainly drawn:(1)During 2000-2020,the carbon emission intensity of energy consumption in China,the four major regions,and the sub-sectors of service industries shows a gradual decreasing trend,and the transportation,storage and postal industries are the key industries that need to carry out energy conservation and emission reduction reforms;spatially the carbon emission intensity of service industries gradually increases from the eastern coast to the western inland,showing The spatial distribution pattern of "high in the north and low in the south,high in the west and low in the east".The overall carbon emission intensity of China’s service industry shows significant spatial clustering characteristics,and the spatial clustering effect gradually increases;locally,the spatial dependence of service industry carbon emission intensity is significant,showing H-L and L-L clustering.(2)Population density,economic development level,technology level,industrial structure and energy structure exhibit obvious spatial and temporal heterogeneity on carbon emission intensity of service industry.Population density,technology level and industrial structure have both positive driving and negative inhibiting effects on carbon emission intensity in each province,while economic development level shows a negative driving effect in general and energy structure a positive driving effect.(3)From the prediction results,the carbon emissions from the service industry in the high-carbon development,benchmark and green energy-saving scenarios peak in 2040,2035 and 2030,respectively,with decreasing carbon emission peaks of 3.485 billion tons,3.141 billion tons and 2.759 billion tons,and the carbon peak target in 2030 can be achieved only in the green energy-saving scenario.Finally,suggestions related to carbon emission reduction in the service industry are proposed based on the research results.