Spatio-Temporal Evolution Of Carbon Emissions And Spatial Spillover Effects In The County Area Of The Ha-Chang Urban Group

Carbon emissions and urbanization are two important topics in the relationship between socio-economic development and the environment in recent years.Under the party's policy and guidelines,China's urbanization has undergone rapid development over the past four decades since reform and opening up,and urban agglomerations are an inevitable product of the development of urbanization to an advanced stage.The Hachang urban agglomeration is an urban agglomeration with rapid development and high level of urbanization in Northeast China.Explore the relationship between county urban development and carbon emissions in urban agglomerations,study the spatiotemporal evolution characteristics of urban carbon emissions in urban agglomerations,and reveal the influencing factors and spatial spillover effects of county carbon emissions.It is of great significance for low carbon development in urban agglomerations The results can provide a reference for the low-carbon development strategy of the national “14th FiveYear Plan” period.This paper studies the spatiotemporal evolution of urban energy carbon emissions,the degree of discreteness of order,influencing factors,and spatial spillover effects in the county-level cities of the Ha-chang urban agglomeration.Based on energy statistics and NPP / VIIRS night light data,this study calculated the carbon emissions data of counties and cities from 2012 to 2016,and verified the fitting accuracy.On this basis,the current status of urban carbon emissions,carbon intensity and per capita carbon emissions were first described,GIS technology was used to visualize carbon emissions in the study area,and Moran's I index was used to test the spatial correlation of urban carbon emissions.The order-scale rule is introduced to analyze the degree of dispersion of urban carbon emissions.Then,from the scale of cities in counties and counties,a variety of econometric models are used to analyze the influencing factors of urban carbon emissions.Finally,spatial Markov model and Durbin model are used to analyze the spatial spillover effects of carbon emissions in counties of the Harbin-Changzhou urban agglomeration.Research indicates:Firstly,from 2012 to 2016,the overall carbon emissions in the study area showed a downward trend,with an average annual decrease rate of 17.9%.The emissions decreased from 90.637 million tons in 2012 to 74.376 million tons in 2016.The carbon emissionintensity showed a trend of first decline and then stability.In the period 2012~2015,urban carbon emission intensity decreased from 0.041 to 0.030,and it fell by 36% in four years.At the same time,carbon emissions per capita also decreased from 1.948 tons in 2012 to 1.587 tons in 2016.Secondly,the global and local Moran's I test results are highly significant.The carbon emissions from Haran urban agglomeration in 2012~2016 show an upward trend,and the spatial agglomeration is stable.The carbon emissions in the study area are subordinate.The main contributors to the intensity of carbon emissions come from the municipal districts centered on Harbin and Changchun.The carbon emission rank-scale characteristics of the top ten cities are reduced first and then increased,and the trend has also shifted from decentralized to concentrated.Thirdly,a variety of panel models analyze the influencing factors and compare the empirical results of various classification models of fixed effects,random effects,spatial lags,and spatial errors.It is concluded that the urban economic level factors and population density factors in the regression model produce carbon emissions in cities Significant positive impact;fixed investment and foreign investment factors have significant effects only in the time-fixed model of the spatial lag and spatial error models;technological progress and road network density factors in the model have a reverse driving effect on urban carbon emissions.Fourthly,the spatial Markov chain transfer model shows that the maximum probability of shifting from a high-emission area to a low-emission area is 75%,and the maximum probability of shifting to a medium and high-level emission area is 66.7%.The regions and high-level regions show relatively stable states,respectively.The results of the spatial Durbin model show that the urban economic factors,the direct and indirect effects of the industrial structure are all positive,they have a positive impact on local carbon emissions and neighboring areas.The network density factor has a negative effect locally,and has a positive effect on the spatial spillover of adjacent areas.Finally,according to the conclusions of the study,the corresponding policy recommendations are proposed,as well as the shortcomings of the thesis.