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Study On The Evolution Of Carbon Footprint And The Potential Of Emission Reduction In Qingdao City

Posted on:2017-01-05Degree:MasterType:Thesis
Country:ChinaCandidate:P SongFull Text:PDF
GTID:2271330503459970Subject:Business Administration
Abstract/Summary:PDF Full Text Request
Due to the rapid development of economy and the improvement of human living standard, energy demand is increasing in countries around the world, lead to the world’s carbon footprint is growing, the impact on the environment is also increased. The problem of carbon footprint has been widely concerned by countries all over the world. China’s rapid economic development and population increase, resulting in China’s energy demand is gradually increasing, China is already the world’s second largest carbon footprint.With the global warming, the impact of global warming has been gradually strengthened, and the carbon footprint has attracted wide attention from domestic and international academic circles.With the development of economy and the increase of energy consumption in Shandong Province, Shandong province has become one of the provinces in China. Qingdao’s economic development in Shandong province has a pivotal position, its energy consumption is very big, also produced a huge amount of carbon emissions. From the current domestic and foreign scholars study, the study of carbon emissions in Qingdao is a lot, but there is very little literature research on the comprehensive carbon emission and emission reduction potential in Qingdao. he purpose of this paper is to establish a comprehensive system for the study of carbon footprint in Qingdao City, The system includes the check of carbon footprint in Qingdao City, and the impact factor analysis of carbon footprint, carbon footprint prediction, as well as the potential of carbon footprint in Qingdao and emission reduction measures, It provides a comprehensive scientific research idea for the carbon footprint of Qingdao city.Many methods are involved in the study of the carbon footprint of Qingdao city. Using IPCC calculation method to calculate the carbon footprint of Qingdao city and analysis of the evolution trend of the carbon footprint of Qingdao city; The influence factors of carbon footprint in Qingdao city by using KAYA factor analysis method; Using the modified IPAT model and scenario analysis method to predict the carbon footprint of Qingdao city in 2020, Based on the above methods and the relevant data of Qingdao City, the following conclusions are obtained:(1)The carbon footprint of Qingdao has been increasing, but the energy intensity is decreasing year by year from 2004 to 2013 year. he factors that drive the carbon footprint of Qingdao city are the growth of population and per capita GDP, The energy intensity of carbon footprint is inhibited, the energy structure of carbon footprint is positive and negative effects;(2) Based on scenario analysis, if the Qingdao city does not take measures to reduce the section, carbon footprint will reache 11816.7 million tons in 2020 year; If energy saving measures were taken, the carbon footprint of Qingdao city will reache 1093.14 million tons in 2020 year.(3) The reduction of carbon footprint in Qingdao, can take the main measures are to focus on the industrial sector to reduce emissions and improve energy efficiency of each industry, and adjust the industrial structure, reduce the proportion of the second industry.In this paper, the evolution trend of the carbon footprint of Qingdao city is studied, and the future carbon footprint is predicted, and the potential of emission reduction and countermeasures are analyzed. The carbon footprint accounting, influencing factor analysis, forecasting model fitting, scenario analysis prediction and emission reduction potential research integration into a whole system of Qingdao carbon footprint study. Finally, the purpose of this paper is to achieve the desired research, and also made some innovation.
Keywords/Search Tags:carbon footprint, emission reduction potential, influencing factors, scenario prediction
PDF Full Text Request
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