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Research On Temporal And Spatial Evolution Of The Carbon Intensity And Its Influencing Factors In China’s Coastal Provinces And Cities

Posted on:2019-12-14Degree:MasterType:Thesis
Country:ChinaCandidate:J LiuFull Text:PDF
GTID:2371330548951111Subject:Human Geography
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Today,the emission of carbon dioxide has become one of the issues of great concern to all countries in the world.It has not only caused a vicious cycle of the natural environment,but also caused a huge loss to the countries due to its negative impact on the society and economy.Therefore,when developing environmental policies and economic policies in various countries of the world,the first thing that should be considered is how to reduce greenhouse gas emissions,the cause of global warming,and carbon dioxide is the most important component of greenhouse gases.Since fossil fuels are used in large amounts in human daily life and production,the control of carbon dioxide emissions is the control of greenhouse gas emissions.Since the reform and opening up in 1978,the development of China’s economy can be described with each passing day.However,it corresponds to the inestimable destruction of carbon dioxide caused by the burning of large amounts of fossil fuels,as well as energy consumption that is in short supply.“We must not only ask Jinshan Yinshan but also green mountains”.We cannot pay for a prosperous economy at the expense of a beautiful environment,and we should actively shift the extensive economic growth model to an intensive economic growth model.In the face of global warming and energy crisis,we should work hard to study ways and measures to reduce greenhouse gas emissions.As the largest developing country,the contradiction between the development of the economy and energy-saving emission reduction is particularly evident,and the amount of carbon dioxide emissions is already ranked first in the world.Because of its geographical location,resource endowments,preferential policies and technological conditions,China’s coastal provinces and cities have been in a more unique regional level in our country.For this reason,the energy consumption in coastal provinces and cities is also the main source of China’s carbon emissions.Its carbon Emissions account for a large proportion of the country’s carbon emissions.Therefore,under the background of energy saving and emission reduction in China,we use certain technical methods to study the spatial and temporal evolution and influencing factors of carbon emission intensity in coastal provinces and cities can provide reference for local governments in coastal provinces and cities to establish a fair and efficient carbon emission reduction differentiated policy Basis,but also for other provinces and cities in China to provide reference for energy-saving emission reduction work.The article takes the carbon emission intensity of coastal provinces and cities in China as the research object.First,after collecting relevant data,the distribution of total carbon emissions and carbon emission intensity in coastal provinces and cities is calculated and analyzed according to the calculation formula,Then,based on the data of carbon emission intensity of coastal provinces and cities in 2007,2011 and 2015,using the spatial autocorrelation analysis method,we found that there is a significant correlation between carbon emission intensity of coastal provinces and cities.Finally,a LMDI factor decomposition model is further established to analyze the factors affecting carbon emission intensity and determine the influencing factors of carbon.The main conclusions of the dissertation are as follows:(1)From the time sequence point of view,the total amount of carbon emissions in coastal provinces and cities is on the rise,and the intensity of carbon emissions shows a downward trend.According to the data of 2003,2007,2011 and 2015,we find that Shandong Province is the area with the highest total carbon emissions in 2007,while the remaining years are the areas with the highest total carbon emissions in Hebei Province.However,The areas with the lowest emissions are all Hainan Provinces,and the total carbon emissions are much lower than those of other provinces and cities.Calculated carbon emission intensity results show that in 2003,2007,2011,2015 these four years,Hebei Province has always been the highest carbon intensity of the region,while the lowest carbon intensity of the region there are some changes in 2003,In 2011,Zhejiang Province became the lowest carbon emission intensity in all the coastal provinces and cities.In 2007 and 2015,Guangdong became the region with the lowest carbon emission intensity.(2)The global spatial autocorrelation of carbon emission intensity in coastal provinces and cities generally shows the development trend of "falling-rising-rising" :(1)From 2003 to 2007,the global spatial autocorrelation index decreased from-0.0787 to-0.1146;(2)In 2007 By 2011,the global spatial autocorrelation index rose from-0.1146 to-0.0922;(3)From 2007 to 2011,the global spatial autocorrelation index rose from-0.0922 to-0.0699.According to the results of spatial autocorrelation,the low-low concentration area is basically located in the southeast coastal area,while the high-high concentration area is mainly concentrated in the northern coastal area.In the "high-high" agglomeration type,there were no significant areas in 2003,while in 2007 there were three significant agglomeration areas in Liaoning,Hebei and Shandong;the "low-low" agglomeration provinces were generally increasing,From 2 in 2003 to 4 in 2015,indicating that spatial agglomeration has a certain diffusion effect on the positive role of coastal provinces in reducing their carbon intensity.(3)The influencing factors of carbon emission intensity in coastal provinces and cities can be roughly divided into the following several factors: energy intensity,energy efficiency,energy structure and industrial structure.Among the above four factors,energy efficiency factor and energy structure factor are the main reasons for the decrease of carbon emission intensity.However,the change of industrial structure factor is the effective carbon emission reduction way.
Keywords/Search Tags:carbon emission intensity, spatial autocorrelation, LMDI decomposition model
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