Research On The Effect And Path Simulation Optimization Of Scientific And Technological Innovation Promoting Provincial Carbon Emission Reduction In China

Human production and living activities have an increasing demand for natural resources,causing a large amount of carbon dioxide-based（CO₂）greenhouse gas emissions and ultimately harming the earth’s ecological environment.The increase in atmospheric CO₂ concentration has led to a severe greenhouse effect,which has caused tremendous damage to global agriculture and animal husbandry,ecosystems,water resources,coastal zones,and social economy.In 1992,the United Nations Framework Convention on Climate Change（UNFCCC）was established;in 1997,the Kyoto Protocol was signed;in 2016,the Paris Agreement entered into force,which has laid the political foundation and legal framework for countries around the world to work together and address climate change.The international community reached a consensus on carbon peaking and carbon neutrality.Many countries have emphasized the role of technological innovation in their core strategies to deal with climate change.However,previous literature has found that technological innovation can both increase and inhibit carbon emissions.The research on the relationship between scientific and technological innovation and carbon emission reduction is not systematic,and the view that scientific and technological innovation promotes is the core of carbon emission reduction lacks empirical research and testing.Limited research has explored the optimization and simulation of carbon emission reduction path.At present,China is the largest carbon emitter.It is necessary to explore the spatial characteristics of carbon emissions in China’s provinces in-depth and systematically and study the effects and paths that technological innovation can promote carbon emission reduction,so as to help achieve the"dual carbon"goal.Based on spatial autocorrelation,system dynamics,game theory,innovation theory,sustainable development,and circular economy theory,this research used literature induction,statistical analysis,computer simulation,and scenario analysis to study the effect and path of scientific and technological innovation in promoting provincial carbon abatement in China.（1）The IPCC method was used to calculate the provincial carbon emissions,Moran’s I,and the Moran scatter plots were used to explore the spatial characteristics and spatial agglomeration of the provincial carbon emissions.The spatialβconvergence model and spatial Durbin model（SDM）were established to investigate provincial carbon emission’s conditional and absolute convergence trends.（2）The Moran’s I and Moran scatter plots were used to identify the spatial autocorrelation of technological innovation.SDM and quantile regression were used to explore the spatial effect of technological innovation on provincial carbon emissions.The moderation effect of environmental regulation was tested at the national and province levels.Hansen’s threshold model was used to identify the threshold value and threshold effect of environmental regulation on the relationship between technological innovation and provincial carbon emissions.（3）A multiple mediation model was established using industrial structure upgrade and energy consumption structure change as the mediation variables to identify mechanisms through which technological innovation influences carbon emission reduction.The moderating effect of the environmental regulation on the mediating variable was tested using Bootstrap methods.（4）The system dynamics method was used to identify the boundary conditions of technological innovation in promoting provincial carbon abatement.The Vensim simulation platform was used to test the correctness and effectiveness of the basic system dynamics model.To acquire the quantitative feedback loop of the system dynamics model,the evolutional game theory models were established.The optimal carbon reduction paths were identified for both inland and coastal regions based on sensitivity analysis of technology investment structure.The effect of environmental regulation on promoting carbon peaks was tested through the sensitivity analysis.The optimization paths under different scenarios were simulated,the results of the static and dynamic simulation were compared,and parameter configurations under different scenarios were obtained.Main contribution and conclusion:（1）Combining scientific and technological innovation,sustainable development,and circular economy theory,this research provides strong support for the practical path of carbon emission control.This research constructed a system dynamics model and obtained the optimal configuration of variables in the system through dynamic simulation and established optimal paths for carbon emission reduction under different scenarios.This research provides a new perspective and points out the strategic direction for the coordinated and unified development of society,economy,and ecological environment.The results can effectively help with the urgent challenges brought by global climate change.（2）China’s provincial carbon emissions show a significant spatial agglomeration effect and conditional and absoluteβ-convergence.From 2008 to 2019,provincial carbon emissions in China continued to increase.The increasing trend of carbon emissions in coastal provinces slowed down,and the carbon emissions in inland provinces showed a nonlinear trend.Regional carbon emissions showed spatial dependence.The spatial absoluteβconvergence coefficient is-0.161 on the national level,and that in inland and coastal provinces are-0.141 and-0.235,respectively,indicating absolute spatialβconvergence,and the degree of convergence in coastal regions is more significant than that in the inland areas.The spatial conditionalβconvergence coefficient is-0.353 on the national level,and that in inland and coastal provinces are-0.372 and-0.473,respectively,indicating conditional spatialβconvergence,and the degree of convergence in coastal regions is more significant than that in the inland areas.Technological innovation is one of the main factors that affect the amount of provincial carbon emission and increases the convergence speed.（3）Scientific and technological innovation has a significant promoting effect on carbon reduction and shows spatial-temporal heterogeneity.For every 1%increase in scientific and technological innovation,provincial carbon emissions decrease by0.086%.The promoting effect of scientific and technological innovation on carbon reduction in inland regions is greater than that of coastal areas（the coefficients are-0.145 and-0.114）,and the inhibiting effect further strengthened after 2013（coefficient is-0.197 in 2013 and after,-0.060 before 2013）.Environmental regulation boosts the promoting impact of technological innovation on carbon reduction in the inland regions.When environmental regulation is above the threshold value of 11.964,the coefficient of technological innovation on provincial carbon emissions changes from-0.102 to-0.099,showing a decrease in the inhibiting effect.（4）Industrial structure change and energy consumption structure change moderate the relationship between technological innovation and provincial carbon emissions.Three mediating paths are identified:path 1 is technological innovation→industrial structure upgrades→carbon emissions（effect value-0.072）,path 2 is technological innovation→energy consumption structure change→carbon emissions（effect value-0.059）,and path 3 is technological innovation→industrial structure upgrades→energy consumption structure change→carbon emission（effect value 0.024）.Environmental regulation has a moderating effect on the mediating effects.In path 1,only when the environmental regulation is greater than-0.725,the negative impact of technological innovation on carbon emissions is significant.In Path 3,when the environmental regulation is within（-1.33,-0.12）,technological innovation promotes provincial carbon emissions,and when environmental regulation is greater than 0.55,the promoting effect of technological innovation on provincial carbon emissions reduction is stronger.（5）The optimal path for inland provinces should address short-term dynamic adjustments,and the technological investment in optimization of the energy consumption structure is the key to carbon reduction;the optimal path for coastal provinces should address long-term static stability,and the technological investment in the upgrade of industrial structure is the key to carbon reduction.Based on the system dynamics model,this research used sensitivity analysis of the technology investment structure（i.e.,the proportion of technology innovation investment in energy structure optimization,industrial structure upgrade,and green technology innovation）and high-level environmental regulation to find the dynamic and static optimization path of carbon control through technological innovation.The optimization path in the inland regions is sensitive to the structure of science and technology investment,and the proportion of technology investment in clean energy structure optimization is the key to carbon emissions control.The simulation of dynamic and static optimization paths in the coastal regions shows similar results,emphasizing long-term technology investments in industrial structure upgrades and green technology innovation.This research could provide methods and references for policymakers when governing carbon emissions using scientific and technological innovation policies.