Analysis And Forecast Of Factors Affecting Carbon Emissions From Energy Consumption In Various Urbanitys Of Shanxi Province

Facing the increasingly severe global warming issue,China,as a practitioner of ecological civilization,has committed to the world to achieve carbon neutrality by2060.In order to better accomplish the task of carbon emission reduction,the government has issued a series of related policies,set various mandatory targets,and received active responses from various regions.Shanxi Province,rich in natural resources and boasting the highest coal reserves in China,has an industrial structure dominated by secondary industries in each city due to its unique resource advantages.Economic development mainly relies on coal consumption,leading to high carbon emissions.Detailed data on energy consumption is only available at the provincial level,and statistics at the city level are lacking.This has led to greater pressure and difficulties for urbanitys to reduce emissions.Therefore,studying the current carbon emission status and local differences in carbon emission factors among the 11 urbanitys in Shanxi Province is of great significance for formulating local carbon emission reduction policies.At present,China’s research on carbon emissions is mainly concentrated at the national level,provincial level or economically developed regions such as the Yangtze River Delta and the Pearl River Delta,which is mainly due to the lack of official statistics and data tables on energy consumption at the municipal level and at a smaller scale,resulting in less research on municipal energy consumption.Therefore,this paper uses the relationship between the provincial and municipal levels,introduces the allocation coefficient,calculates the municipal energy consumption based on the provincial energy balance sheet,and calculates the municipal carbon emissions.LMDI decomposition method was used to study the influencing factors of carbon emissions;Finally,using the scenario analysis method,the GA-BP neural network model was used to predict the carbon emission trend of each city in Shanxi Province in the next five years under three scenarios.The results of the study showed that:(1)Regional differences in economy,industry,energy consumption and carbon emissions of each city are more obvious.From the perspective of economic development level,from 2011 to 2020,Taiyuan City had the highest level of economic development,increasing from 208.01 billion yuan in 2011 to 415.33 billion yuan in 2020;Xinzhou City and Yangquan City had relatively backward economic development levels,with a total GDP of 74.22 billion yuan and 103.46 billion yuan respectively in 2011.From the perspective of energy consumption and carbon emissions,the cumulative energy consumption of Taiyuan City reached 489 million tons of standard coal,with an average annual carbon emission of 52.5241 million tons of carbon dioxide,ranking first;the average annual growth rate of carbon emissions in Xinzhou City was 4.02%,Taiyuan City was 2.83%,and the average annual growth rate of carbon emissions in Yangquan,Shuozhou,Yuncheng and Linfen was negative.From the perspective of spatial distribution,it shows that the carbon emissions in central Jinzhong are the highest,followed by southern Jin,and the lowest spatial distribution law in northern Jin.(2)The carbon emissions of cities in Shanxi Province are the result of a variety of influencing factors,including energy structure,energy efficiency,industrial structure,economic development level and population size.The level of economic development is the most important factor driving the growth of carbon emissions,energy structure,energy efficiency and industrial structure are all factors inhibiting the growth of carbon emissions,and the role of population size is related to local population changes.Among them,the main influencing factors of carbon emissions in Taiyuan City are economic development level and population size,accounting for0.4535 and 0.2249 respectively,followed by energy efficiency factors,accounting for0.1780;except for Taiyuan City,the main influencing factors of carbon emissions in the other 10 cities in Shanxi Province are economic development level and energy efficiency,and the sum of the proportions of the two factors is above 0.8.(3)In conclusion,based on national and regional policies,future parameter values for carbon emission impact factors are established and divided into three scenarios: high carbon,baseline,and low carbon.The GA-BP neural network prediction model is employed to forecast the carbon emissions of the 11 urbanitys in Shanxi Province from 2021 to 2025 under these three scenarios.The results indicate that the carbon emissions in Taiyuan,Datong,Changzhi,Jincheng,Jinzhong,Yuncheng,Xinzhou,and Lvliang will continue to grow,with Xinzhou experiencing the most pronounced increase.Conversely,the carbon emissions in Yangquan,Shuozhou,and Linfen are expected to decline.The carbon emission situation in the majority of Shanxi Province remains highly concerning,with significant pressure to reduce emissions.