Analysis Of Carbon Emissions And Peak Carbon Prediction In Yichang City Based On STIRPAT And Neural Network

The world is currently facing global challenges such as climate change and environmental pollution,with carbon emissions as one of the major sources of greenhouse gases,which has become an urgent problem to be solved.As an important city in the central and western regions of China,Yichang City has significant implications for achieving low-carbon development and promoting urban sustainability.This paper aims to study the carbon emission scenario forecast in Yichang City in order to provide reasonable and effective suggestions for low-carbon development.To achieve this goal,this paper adopts various methods,including the STIRPAT(Stochastic Impacts by Regression on Population,Affluence,and Technology)model,grey relational analysis,ridge regression,scenario analysis,and BP neural network algorithm,to conduct a detailed analysis of the current situation of Yichang City,the influencing factors of carbon emissions,and the future trends of carbon emissions.Firstly,this paper analyzes the current situation of Yichang City.Through the collation and comparison of historical carbon emission data,it is found that the carbon emissions in Yichang City have shown a gradual increase trend in recent years.This paper finds that in the future,Yichang City will face uncertainties in achieving the peak of carbon emissions as scheduled,due to the adjustment of industry and energy structure,as well as the comprehensive resumption of production and work after the end of the epidemic.Secondly,this paper analyzes the multiple influencing factors of carbon emissions in Yichang City.Through grey correlation analysis,it was found that the urbanization rate and energy structure have particularly prominent explanatory power for carbon emissions.The coefficients of the ridge regression equation show that,in addition to the negative correlation between the industrial structure(coefficient of-0.571)and carbon emissions,population size(coefficient of 8.482),per capita GDP(coefficient of 0.119),energy structure(coefficient of0.896),energy intensity(coefficient of 0.099),carbon emission intensity(coefficient of 0.038),and urbanization rate(coefficient of 0.465)are all positively correlated with carbon emissions.In addition,grey correlation analysis shows that the correlation degree of all evaluation objects exceeds 0.5,among which the correlation degree of urbanization rate is 0.837,energy structure is 0.791,per capita GDP is 0.774,population size is 0.753,industrial structure is 0.75,carbon emission intensity is 0.591,and energy intensity is 0.576.The seven influencing factors are all highly correlated with carbon emissions.These analysis results provide a scientific basis for formulating future low-carbon development policies and measures in Yichang City.Finally,based on the scenario parameter logic of the mother-son inheritance built-in LEAP software,this paper constructs a benchmark scenario and sets seven influencing factor parameters in two scenarios of high and low levels under the benchmark scenario,totaling 14sub-scenarios.Then,according to the positive or negative correlation between each influencing factor and carbon emissions,parameter combinations are made to set two comprehensive scenarios of high carbon and low carbon.Finally,the BP neural network model is used to predict carbon emissions under different scenarios.The research results show that,by adjusting single parameters only,the peak of carbon emissions cannot be achieved in any of the sub-scenarios.However,in the low-carbon and benchmark scenarios,Yichang City is expected to achieve the goal of carbon emission peak as scheduled.Based on the analysis above and the current situation of Yichang City,this paper proposes policy suggestions for carbon emissions reduction.To achieve low-carbon development,Yichang City should promote the development of green industries and reduce emissions from high-carbon industries;strengthen the management of energy intensity and carbon emission intensity,improve energy utilization efficiency and resource utilization rate,and reduce carbon emission levels;promote low-carbon lifestyle,popularize low-carbon transportation and energy-saving and emission-reducing behaviors;strengthen environmental protection and ecological restoration,and increase the carbon sequestration capacity of ecosystems..In conclusion,the research findings of this article are of significant importance for Yichang City to achieve low-carbon and sustainable development.By accurately predicting and analyzing carbon emissions scenarios,it can provide scientific basis for Yichang City to formulate scientifically reasonable low-carbon development goals and policies.At the same time,the policy recommendations proposed in this article can also provide valuable insights and references for other cities in promoting low-carbon development and addressing climate change.