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Study On Peak Prediction Of Regions Carbon Emission And Control Strategies

Posted on:2018-09-12Degree:MasterType:Thesis
Country:ChinaCandidate:T Y YuFull Text:PDF
GTID:2321330518976597Subject:Public Management
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Global warming is one of the factors that threat seriously to human survival and development,with the rapid development of economic globalization and the increasing of people's living standard,regions have a growing reliance on energy,carbon emissions are growing,so controlling carbon emissions?curbing global warming have become the important strategy of sustainable development in the future.China is the biggest developing country in the world today,but after decades of rapid economic growth,China has become the global power which has a lot of energy consumption and carbon emissions,so the problem of carbon emissions causes wide attention from all walks of life.From the public pressure for international climate negotiations,social responsibility of a big country and the needs to reduce energy consumption?protect resources and environment,China has announced a binding emissions target: the carbon emissions to peak in 2030,and give the commitment to international community that the responsibilities of emission reduction in our country,specific tasks are put forward.Zhejiang province as an eastern coastal developed area in China,after reform and opening up 30 years of rapid development,especially the "11th five-year plan","twelfth five-year" period of large-scale economic construction,the level of social development has been located in the top.But in the process of development,energy consumption has also appeared in big and rapid growth?energy structure and industrial structure are not reasonable?carbon emissions rise rapidly and so on,which threat people's economic production and social life.To realize the change of development mode,and promote the social economy develop in low carbon and coordinately is the next phase's key tasks.Predicting regional carbon emissions peak,through the management make carbon emissions into the downward trend in Zhejiang province is an important goal of this study.Paper is based on the theory of low-carbon economy?sustainable development?ecological footprint and energy alternative,in order to analysis social and economic development in Zhejiang province with the correlation of carbon emissions,and discusses the key influence factors of carbon emissions in Zhejiang province with LMDI model,then to make sure carbon increased effect factors and carbon reduction effect factors.Combinedwith the national and Zhejiang province policy planning which related to carbon emissions control,then uses scenario analysis to set three kinds of economic and social development model that named low mode,medium mode and high mode,using the optimized STIRPAT model to set of six factors affecting carbon emissions: population size?GDP per capita?carbon intensity?urbanization rate?energy consumption structure and the proportion of second industry,then to estimate the amount of carbon emissions and the peak year under each scenario in Zhejiang province from 2016 to 2040.Put forward the corresponding policies and measures to reduce emissions according to the results.The thesis research results show that:(1)The main influence factors of carbon emissions in Zhejiang province are: population size?GDP per capita?the industrial structure?energy intensity and energy consumption structure,population size and economic development have a positive role on carbon emissions,industrial structure?energy intensity and energy consumption structure play a negative role on carbon emissions overall.(2)In the low mode scenarios,carbon emissions peak year will be in 2020,the peak volume will be 424 million tones;in the medium mode scenarios,carbon emissions peak year will be in 2025,the peak volume will be 473 million tons;in the high mode scenarios,Zhejiang province cannot achieve carbon emissions peak until 2040.
Keywords/Search Tags:Zhejiang province, Carbon emissions, LMDI model, STIRPAT model, Scenario analysis
PDF Full Text Request
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