Simulation Study On Agricultural Carbon Emissions And Its Influencing Factors Based On System Dynamics

In recent years,countries around the world have paid more and more attention to the issue of carbon dioxide emissions.In order to cope with extreme weather changes,it is necessary to achieve a profound change of carbon peaking and carbon neutrality as soon as possible.The Chinese government has announced that it will strive to reach the peak of domestic carbon emissions by 2030 and reach the goal of carbon neutrality by 2060.As a major agricultural country,it is particularly important for China to explore the influencing factors related to agricultural carbon emissions and achieve carbon reduction in the agricultural sector.The 14 th Five Year Plan period is the beginning period of exploration for China’s agriculture to move towards green and high-quality development,and also a key window period for carbon peak in2030.Based on this,this article uses system dynamics to study China’s agricultural carbon emissions,agricultural energy consumption,agricultural economic growth,and related influencing factors.Based on this research,a grey correlation evaluation is conducted on the effectiveness of China’s agricultural carbon emission reduction,and corresponding emission reduction paths are designed and policy recommendations are proposedThis article provides an overview of the current situation of agricultural carbon emissions,agricultural energy consumption,and agricultural economic growth in China.From multiple perspectives such as population,policy issuance,government regulation,society,economy,energy,and environment,and with the help of system dynamics theory,a dynamic correlation analysis is conducted on the influencing factors of agricultural carbon emissions.The feedback loop of the system is analyzed from the perspective of causal logic,Obtain a causal loop diagram of agricultural carbon emissions and their related influencing factors.Based on this,conduct quantitative research on the entire system,construct a flow stock diagram,clarify variables and related parameter values,and set dynamic equations.By using the system dynamics VENSIM simulation platform and combining with historical real data from 2016 to 2021 in China,the stability and historicity of the model were tested to verify its effectiveness.The agricultural carbon emissions,agricultural energy consumption,and total agricultural output value of China from2023 to 2030 were predicted.Finally,policy simulations were conducted by changing the parameter values of four variables: government financial investment,agricultural machinery power,national control efforts,and per capita disposable income of rural residents.Subsequently,a system of evaluation indicators for China’s agricultural carbon reduction effectiveness was constructed,and a comprehensive evaluation of China’s agricultural carbon reduction effectiveness from 2016 to 2021 was conducted using entropy weight method and grey correlation model.The results showed that China’s overall agricultural carbon reduction effectiveness showed a stable trend,with the lowest correlation between agricultural carbon emissions and the optimal sequence in 2020.Considering social factors,the large-scale outbreak of the epidemic in 2020 led to large-scale production and business stoppages,The total global carbon emissions have significantly decreased,and China’s agricultural carbon emissions have also significantly decreased,which is significantly different from the optimal sequence.The highest correlation between the development effect of agricultural carbon emissions in China and the optimal sequence in 2021 proves that China’s agricultural carbon reduction effect in 2021 is high,with strong and significant reduction efforts.By calculating the weight values of each indicator in the indicator system,it was found that factors such as crop planting area,grain yield,and agricultural machinery power are the main reasons for the differences in agricultural carbon emissions.The development of carbon reduction paths in agriculture should be directed towards areas with high weight values such as crop planting area,total agricultural output value,urban population,and grain yield.At the end of the article,by studying the main greenhouse emission sources and emission reduction measures of agriculture in China at present,the path for carbon reduction in agriculture in China is designed,and a path map for carbon sequestration and emission reduction in agriculture is drawn.Policy recommendations for carbon reduction in agriculture are also proposed.The innovation of this study lies in the integration of system dynamics into the systematic study of China’s agricultural carbon emissions,agricultural energy consumption,agricultural economic growth,and related influencing factors.Based on this research,a grey correlation evaluation is conducted on the effectiveness of China’s agricultural carbon emission reduction,corresponding emission reduction paths are designed,and policy recommendations are proposed.The article forms a systematic whole for the study of China’s agricultural carbon emissions.