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Study On The Spatiotemporal Pattern And Influencing Factors Of Carbon Emissions In Shandong Provinc

Posted on:2024-05-13Degree:MasterType:Thesis
Country:ChinaCandidate:L X WangFull Text:PDF
GTID:2531306923490074Subject:Human Geography
Abstract/Summary:PDF Full Text Request
For a long time,China’s energy structure has been dominated by fossil fuels.Therefore,in the rapid economic development,the consumption of fossil fuels is also rapidly increasing,leading to an increase in carbon emissions.As the world’s largest carbon emitter,China has a long and arduous task to protect its ecological environment.In September 2020,China proposed the goals of carbon peaking and carbon neutrality.To achieve this goal,it is not only necessary to carry out overall deployment at the national level,but also to take specific actions at the regional level.Since 2003,Shandong Province has been the largest provincial-level carbon dioxide emitter in China.Therefore,it is of great significance to study the temporal and spatial pattern of carbon emissions in Shandong Province and its influencing factors for formulating differentiated regional carbon reduction policies and developing a green Low-carbon economy.The thesis analyzed the carbon emissions of 136 counties in Shandong Province from 1998 to 2017 using natural breakpoint method and SLOPE tipping method,based on the carbon emission data of Chinese counties from 1998 to 2017 and statistical yearbook data of each county;Study the temporal trend of carbon emissions in Shandong Province and analyze the rate of increase or decrease in carbon emissions in each county.The thesis studies the spatiotemporal heterogeneity characteristics of carbon emissions in counties and per capita carbon emissions in Shandong Province through global spatial autocorrelation analysis and local spatial autocorrelation analysis.Based on indicators such as economic development level,industrial structure,population size,urbanization level,technology level,and financial investment,and combined with the Geographically and Temporally Weighted Regression(GTWR)model,the influencing factors of carbon emissions in counties in Shandong Province are analyzed for spatiotemporal heterogeneity.The main conclusions obtained are as follows:Firstly,from 1998 to 2017,the total carbon emissions in Shandong Province showed an overall upward trend,with an average annual increase of 33 million tons.Since 2013,the growth rate of total carbon emissions has gradually slowed down,with an average annual growth rate of 1.75%.The growth trend of per capita carbon emissions and total carbon emissions in Shandong Province is similar.There are significant spatial differences in carbon emissions among counties in Shandong Province,with a pattern of high in the northeast and low in the southwest overall.The counties with high carbon emissions are mainly concentrated in areas with developed industries and economies,as well as some coastal areas.The regions with high per capita carbon emissions are mainly concentrated in the northern region of Shandong and gradually expanding towards the southern and eastern regions of Shandong.Second,from 1998 to 2017,there was a positive spatial correlation between regional carbon emissions in Shandong Province and county-level carbon emissions,with a stronger correlation observed at the county level.The regions with significant spatial correlation of county-level carbon emissions were mainly distributed in the northern and northeastern parts of Shandong Province,showing a tendency of concentration in high-value clusters.The regions with significant spatial correlation of per capita carbon emissions were mainly distributed in the northern and southwestern parts of Shandong Province,showing a tendency of concentration in low-value clusters.Thirdly,the study analyzed the influencing factors of carbon emissions in counties in Shandong Province through the Geographically and Temporally Weighted Regression(GTWR)model.The results showed that GDP,industrial structure,population size,and technological level have a promoting effect on carbon emissions.The urbanization level and financial input have both positive and negative effects on carbon emissions.As for the average regression coefficient,the urbanization level has a inhibitory effect on carbon emissions,while financial input has a promoting effect.The correlation between openness and carbon emissions is not significant.Fourthly,under the current social trends and policies,each county in Shandong Province should continuously reduce carbon emissions and strive to build low-carbon cities by transforming economic development approaches,optimizing industrial structures,promoting carbon reduction technologies,and raising public awareness of emissions reduction during the process of urbanization.
Keywords/Search Tags:Carbon emissions, Spatial autocorrelation, Influencing factors, GTWR model, County scale, Shandong Province
PDF Full Text Request
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