| Global warming has become a major challenge for human development.Reducing carbon dioxide emissions is not a practical need for countries to address climate change but also an inherent requirement for sustainable development.National-level CO2 reduction targets need to be implemented at the regional level.Transportation infrstructure is an important support for the regional economic development and links economic activities of different regions.Its construction and expansion directly increase carbon emissions because of transport activities’ energy consumption and indirectly impact the regional emissions because of the social and economic agglomeration effect.Existing research has proved that deep structural reforms in transportation infrastructure can affect 80% of regional CO 2 reductions through direct and indirect ways.Therefore,it is an important reference and urgent need to clarify the impact of transportation infrastructure on regional carbon emissions and its potential.Based on the literature review and the theory analysis including complex systems,sustainable development,environmental economic geography and externality theory,this study analyzes the impact connotation,mechanism,degree and path of transportation infrastructure on the regional carbon emission using methods including bibliometrics,spatial econometrics,dynamics simulation,nonparametric prediction and scenario analysis.The main research contents are as follows:This dissertation defines the connotation of the impact of transport infrastructure on regional carbon emissions.It is clarified the importance of spatial elements and this impact is generated by the coupling of multiple factors.In details,this study identifies all impact factors of regional carbon emission including the transport factor and analyzes the driving force,direct impact and indirect impact.Then the conceptual model of research problem and expanded STIRPAT theoretical model are constructed to reveal the impact mechanism.Because of the spatial characteristics of regional carbon emissions,the exploratory spatial data analysis method(ESDA)is used to calculate the spatial correlation of the elements based on the STIRPAT model.This dissertation constructs several spatial econometric models to calculation the impact of transprotation infrastruture on the emission using the panel data of 30 provincial regions between 1997 and 2015 in China.It is proved that the STIRPAT-SDM model has strong explanatory ability.Then the spatial relationship of factors and impact degrees of various driving factors on regional carbon emissions are analyzed.The driving factors of the theoretical model STIRPAT are further extended to different system modules with different elements.According to the causal relationship between specific elements,the system dynamics(SD)method is applied to visually express the causal connection,mutual influence and feedback loop s.And the path simuulation model STIRPAT-SD is constructed.This model is tested for its intuitiveness,validity and sensitivity to ensure the interpretation ability of the simulation model.Based on the above content,scenario simulation and emission reduction path identification are carried out from two perspectives.First,these factors including the transport infrastructure that significantly affect regional carbon emission levels are used as predictors,and a nonparametric machine learning prediction model STIRPATPSO-SVM is constructed to predict China’s regional carbon emission in 2015-2030.Then,according to the path simulation model STIRPAT-SD,the transport carbon emission is forecasted and scenario simulated.Based on these two kinds of scenario results,comprehensive carbon reduction scenarios and paths,as well as corresponding policy recommendations are proposed.This study measures the impact of transportation infrastructure on regional carbon emissions from a spatial perspective and proves that transport infrastructure is important driving factor affecting regional carbon emissions.This further expand the STIRPAT theoretical model.In addition,the joint scenario simulation integrating non-parametric prediction and parameter prediction methods is used to find the decarbonization paths.The combination of qualitative and quantitative approaches improves the accuracy of scenario simulation and enriches the method of low-carbon scenario simulation and path identification.Besides,This study identifies regional carbon reduction threshold scenarios,pathways,and plans under the influence of transport infrastructure which provide a policy reference for regional low carbon development.In general,these results are helpful for understanding the mechanism of the impact of transportation infrastructure on regional carbon emissions,and provide practical reference for regional low-carbon development related to transport infrastructure. |
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