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Study On Dynamic Characteristics Of Carbon Emissions’ Driving Factors In Jiangsu Province

Posted on:2016-01-14Degree:MasterType:Thesis
Country:ChinaCandidate:M WuFull Text:PDF
GTID:2191330470469810Subject:Climate change and public change
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As one of the biggest economic provinces in china, the annual energy consumption in Jiangsu province is large. Energy consumption is the most direct and important source of carbon emissions in Jiangsu province. Jiangsu has a huge potential to reduce emissions due to its energy, industrial structure and production conditions. It has guiding significance to scientifically forecast and evaluate the factors and changing trend of future carbon emissions and find the focus and direction of the future emissions reduction work.Firstly, we evaluated the energy consumption and economic development datas of Jiangsu province. Then we carried on the empirical analysis as follows:(1) By using the GM (1,1) forecasting model and polynomial prediction model, we predicted the energy consumption data for each industry during 2013 to 2020, GDP data for each industry and population size data during 2014 to 2020 in order to further decompositing and calculating the amount of emissions increasing by different factors during 1997 to 2012 and 2013 to 2020. (2)According to the extended Kaya identical equation and LMDI model, we decomposited and calculated the amount of carbon emissions brought by population, per capita GDP, industrial structure, energy intensity, structure of energy consumption during 1997 to 2012 and 2013 to 2020. (3) According to the results, we analyzed the dynamic characteristics of carbon emissions’driving factors in Jiangsu province from 1997 to 2012 and the changing trend of carbon emissions’driving factors in Jiangsu province from 2013 to 2020.The results showed that:(1) According to the calculation of LMDI model, carbon emissions in Jiangsu province were growing rapidly except in the year of 1997 and 1999. According to the forecast data, carbon emissions will continue to increase in Jiangsu province during 2013 to 2020.(2) The change of population, industrial structure and energy intensity will cause carbon emissions growth. Economic growth is the main driving factor.(3) Economic growth is still the main driving factor of future carbon emissions’ increase, while energy efficiency will largely reduce the trend of future emissions growth. The adverse effect of industrial structure on future emissions growth will be enhanced gradually, while the adverse effect of energy consumption structure on future carbon emissions growth will be weakened gradually or even disappeared.(4) The potential of emissions reduction is bigger of the second industry. Carbon emissions caused by the third industry will grow, but the amount of carbon emissions caused by the third industry is smaller compared to the second industry.Finally, we provided some advices according to the conclutions we’ve got. From the perspective of we should pay attention to both the speed and quality of economic growth. From the perspective of energy, we should control raw coal consumption and improve energy efficiency. From the perspective of industrial structure, we should develop carbon emissions’ reduction potential of the second industry and pay attention to the carbon emissions of the third industry.
Keywords/Search Tags:Carbon emissions, Forecast model GM(1,1), LMDI decomposition model, Dynamic characteristics
PDF Full Text Request
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