Research On China's CO2 Emission Reduction Path Based On ARDL And Multi-objective Programming Mode

Under the background of green and low-carbon development,it is of great significance to clarify the influencing factors of carbon dioxide（CO₂）emissions,analyze the corresponding transmission mechanism,and then explore the path of CO₂emission reduction.Based on the theory of environmental Kuznets curve（EKC）,this paper constructed an auto-regressive distributed lag（ARDL）model and a multi-objective programming model,and designed monte Carlo simulation,linear weighting and genetic algorithm for model solving and scenario analysis,in order to provide ideas and path selection for CO₂emission reduction in China.Firstly,the deficiencies in the research field of EKC are improved,and the"scale effect","structure effect"and"technique effect"of CO₂emissions are comprehensively investigated.Economic growth and its square term,industrial development level and energy intensity are selected as independent variables,and CO₂emissions are taken as dependent variables to construct ARDL model.The results show that:（1）There is an inverted U-shaped relationship between economic growth and CO₂emissions in both the long and short run.（2）Industrial development level has a significant positive impact on CO₂emissions in the long and short term.（3）Energy intensity has a significant positive impact on CO₂emissions in the long run,but fluctuates in the short run.（4）Scenario analysis based on Monte Carlo simulation shows that during the 14th Five-Year Plan period（2021-2025）,China is most likely to have an average annual growth rate of 6.26%to 6.71%of CO₂emissions.Furthermore,based on clarifying the influencing factors of China’s CO₂emissions,the objective functions of minimizing CO₂emissions,minimizing energy consumption,and maximizing GDP are selected respectively,and the output value of each industry is one decision variable.On the premise of meet the conditions such as CO₂emission reduction,a multi-objective programming model is constructed,and a linear weighting method and a genetic algorithm for solving the model are designed.The output results show that:（1）If CO₂emission minimization is selected as the core decision objective,the output value of construction industry should be reduced,and the output value of wholesale and retail,accommodation and catering industry should be increased.（2）If energy consumption minimization is selected as the core decision objective,the output value of construction industry needs to be reduced and the output value of agriculture,forestry,animal husbandry and fishery needs to be increased.（3）If GDP maximization is selected as the core decision objective,it needs to focus on promoting the development of wholesale and retail,accommodation and catering industries.（4）The key to reducing CO₂emissions and energy intensity in China lies in the following industrial sectors:transportation,storage and postal services;electricity,heat,gas and water production and supply;and mining.