Research On Influencing Factors Of Energy Consumption Intensity And Prediction Of Carbon Emissions

In recent years,with the rapid development of the global economy,energy consumption has also increasing sharply,resulting in a series of problems such as resource shortage and climate change.As an index to measure the comprehensive utilization efficiency of energy,energy consumption intensity reflects the degree of economic dependence on energy and the economic benefits of energy use.It is the key point to solve the contradiction between economic development and energy and environment constraints.Studying the influencing factors of energy consumption intensity and analyzing the relationship between energy intensity change and carbon emission is conducive to improving energy utilization efficiency,thus restraining unreasonable energy consumption and promoting the construction of high-efficiency and low-carbon energy system.However,most of the existing studies used a single regression model or decomposition model to analyze the energy consumption intensity and carbon emissions under the background of the traditional economic development model,which is difficult to adapt to the accelerated development trend of China's economic transformation and upgrading.Based on the review and summarize from the current research at home and abroad,this paper focuses on the influencing factors of energy consumption intensity and carbon emissions prediction under the background of “New Normal”.We conduct multidimensional and multi-level in-depth research,which combines short-term fluctuation analysis with long-term trend analysis,attribution analysis with regression analysis,and decomposition analysis with scenario analysis.This paper systematically analyzed the trend,fluctuation and elasticity characteristics of energy consumption intensity,studied the influencing factors of regional energy consumption intensity,and constructed a scenario model of carbon emissions prediction considering sectoral energy consumption intensity.This work has important theoretical significance and practical value in promoting the transformation of green and efficient energy consumption mode.The research content and innovations of this paper are as follows:(1)Research on the characteristics of energy consumption intensity.Firstly,the historical change trend of energy consumption intensity,coal consumption intensity and electricity consumption intensity are analyzed.Then,the structural vector autoregressive model is constructed to study the fluctuation characteristics of energy consumption intensity.Combined with impulse response function and variance decomposition method,the dynamic impact of coal and electricity consumption proportion on energy consumption intensity fluctuation is revealed.Based on the decoupling theory,the calculation method of electricity decoupling index is proposed,and its relationship with energy consumption intensity elasticity index is established.We comprehensively analyses the influence of power proportion,energy intensity and industrial structure on electricity consumption,and explains the changing trend of decoupling index and the characteristics and causes of the elasticity change of sectoral energy consumption intensity.This chapter lays a foundation for the multi-dimensional and in-depth study of energy consumption intensity.(2)Research on the influencing factors of energy consumption intensity.Firstly,on the basis of dividing China into three regions: eastern,central and western regions,a decomposition and attribution analysis model of energy consumption intensity in multiregions is proposed.The change of energy consumption intensity of manufacturing industry is decomposed into regional intensity effect and regional structure effect,which reveals the contribution of different regions to these two effects.The distribution of energy consumption intensity at the regional level is realized for the first time.Then,considering six key influencing factors: the production efficiency,structure and investment of manufacturing industry and provincial development level,urbanization level and openness level,a quantile regression model based on panel data is established.The mechanism and differences of influencing factors at different levels of energy consumption intensity in different regions are comprehensively investigated.It provides a reference for regional exploration of energy efficiency improvement and energy-saving.(3)Research on prediction of energy consumption intensity and carbon emissions.Firstly,a multi-energy and multi-sectoral decomposition model of carbon emissions is proposed.The effects of energy consumption intensity on carbon emissions are analyzed from two aspects: single-period and multi-period.Furthermore,the value added and energy consumption intensity reduction rate in each sector are predicted,and the scenario model of carbon emissions prediction is established.On this basis,the feasibility of achieving the carbon intensity reduction goal under reference scenario and outlook scenario is verified.Then,an evaluation framework combining decomposition model and scenario model is constructed to explore the potential driving forces for future carbon emissions reduction,and the effectiveness of energy and economic policies is compared.Finally,based on the above research,relevant suggestions are put forward to reduce energy consumption intensity and achieve carbon emissions reduction.A systematic evaluation of energy consumption intensity and its relationship with carbon emissions in the context of economic transformation and upgrading is conductive to the coordinated development of economy,energy and environment.In this paper,the characteristics of energy consumption intensity are discussed from the aspects of its trend,fluctuation and elasticity change.The influencing factors and its mechanism of regional energy consumption intensity are deeply analyzed.A scenario prediction model of energy consumption intensity and carbon emissions is constructed.This paper provides an important reference for the establishment of a green and low-carbon sustainable development system.With the deepening of Internet Services and the application of Cloud Computing Technology,energy data is accumulating continuously.How to mine and analyze the massive energy data and optimize the operation and management of energy system will become an important research direction in the future.