Analysis Of Influence Factors And Prediction Of Carbon Emissions During The Process Of Urbanization In Shanxi Province

China’s urbanization is pushing at full steam, a large number of rural peoplemerge to the city, so the increase of per capita energy expenditure is unavoidable. Inaddition, the growth of urban population will contribute to more energy consumptionin sectors such as traffic, housing, infrastructure and so on, which not only results inmore fossil fuel consumption in cities, but also deteriorates the situation of globalwarming. In the rapid development path of urbanization, China is facing with greatburden of reducing carbon emission.In order to realize the commitment of reducing carbon emission intensity in2005by40%-45%up to2020, Chinese government makes a decomposition of the energy-saving target at provincial level. Thus, each province should consider its economicdevelopment and find out the main driving factors behind carbon emission toformulate its own mitigation policy, which may help it to achieve decomposition goaland to contribute to the realization of the whole country’s carbon emission target.Based on the points above, this paper chooses Shanxi as the study object, and theninvestigates the carbon emission drivers of Shanxi under the process urbanization.Moreover, this paper also makes a prediction of the carbon emission of Shanxiprovince in the period of2012-2020. The main contents in this study are as follows:(1)With the PATH-STIRPAT model, the driving effect on carbon emissionsfrom independent variables such as population, wealth, urbanization, industrialstructure, and energy efficiency is analyzed. The interactions among the explainingvariables are studied. The results indicate that: in terms of direct path coefficient, theenergy efficiency wealth’s is the largest, followed by population, wealth, urbanization,industrial structure. In terms of indirect coefficient, energy structure and urbanizationhave smaller impacts on other variables. As to the value of total path coefficient, thevariable ranks in this order: wealth, urbanization, population, energy efficiency andindustrial structure. With1%increase in population, wealth, industrial structure,energy efficiency and urbanization, the growth of carbon emission will reach1.121%,0.434%,1.576%、-0.998%and1.021%, respectively.(2) The SVAR model is to investigate the dynamic effect among the influencingfactors. This paper conducts a stationary test of three variables: industrial structure,urbanization and carbon emission, due to the requirements of building this model.After getting through these tests, the SVAR model is to develop Granger causality analysis, SVAR model recognition, impulse-response analysis and variancedecomposition. Moreover, the results show that the rise in the proportion of thesecond industry and the advance of urbanization will lead to more carbon emission,and the fluctuation in the rate of urbanization is easy to pass to other variables while itis insusceptible to others.(3) With time series data, the future energy consumption in Shanxi is predictedwith co-integration analysis, selecting population, price, GDP, economic structure,urbanization as variables based on three scenarios: low-speed economic growth,benchmark, and high-speed economic growth. The energy structure is predicted basedon grey model combining spherical data transformation, then with the predictedenergy consumption and energy structure data, the carbon emissions are predicted inperiod of2012-2020in Shanxi Province. In addition, the analysis shows that carbonemissions will increase in all the scenarios, but the growth rate is differences. Theaverage annual growth rate of carbon emissions in2011-2020is lower than theaverage annual growth rate in1990-2011. The task of reducing carbon emission is noteasy for Shanxi to accomplish in a short term, but the adoption of strict and rationalpolicies benefits to control the growth rate of carbon emission.