上海市碳排放特征及预测研究

发布时间：2018-07-04 17:01

本文选题：碳排放特征 + 能源　；参考：《上海师范大学》2015年硕士论文

【摘要】：为应对气候变化,世界各国在过去的几十年中做出了一系列的努力,未来的全球活动和制度交流也会持续的推进。一个城市在未来几十年里能否走在世界的前列,很大程度取决于其在低碳时代来临时的适应力。节能减排的前提需要科学的核算区域的碳排放源并进行定量计算。本文以上海市为研究对象,基于该市最近十年(2003-2012年)的统计年鉴数据,在基本理论概述和文献回顾的基础上,选取和改进适合本文的碳排放测算模型,从碳源和碳汇的角度对上海市碳排放情况进行全面统计和估算,选择特征指标来对上海市碳排放随时间序列变化的特征进行分析和评价;横向上以长江三角洲两省一市为比较对象,并从碳排放效率指标进行地区间碳排放效果比较分析,说明上海市的碳排放特点;采用岭回归函数,并运用MATLAB计算工具对STIRPAT模型进行回归拟合,探讨研究人口因素、富裕因素、能源结构和技术因素对能源活动的碳排放影响因素。通过KAYA恒等式对上海市未来碳排放趋势变化进行情景预测。并根据研究结果及综合评价,对上海市的低碳发展提出对策和建议。主要结论如下:(1)上海市碳排放现状和特征:2003年上海市净碳排放量为18200.34万吨,2012年增至23762.96万吨,年均增长率约为3.2%。总排放量随时间序列呈阶段式变化,2009年出现负增长。碳源贡献上来看,上海市碳排放基本来自化石能源的消耗比重达98%,工业生产过程为1.8%。人均碳排放虽然呈现着一定的上升的趋势,上海市碳排放强度基本呈直线下降。与长三角地区其他两省相比,上海市碳排放总量最少,但人均碳排放量位列第一,随时间变化,差距逐渐拉近。上海市碳排放强度与江浙两省相比先高后低,同时十年来的下降幅度较大。从碳排放效率来评价,上海市2003年至2012年的碳排放效率均值为1.005,高于浙江(0.957)和江苏省(0.9),但稳定度较差,呈起伏式变化。(2)上海市碳排放驱动因素:根据扩展的STIRPAT模型对2003-2012年上海碳排放影响因素驱动分析。发现对我市碳排放总量驱动最快的为能源结构,驱动指数为0.215;其次为人口,驱动指数为0.162,产业结构影响作用最弱,为0.125;技术的提升会抑制碳排放在增长。系数均小于1说明,各个驱动因子带来的环境效应变化速率小于该因子的变化速率。(3)上海市未来碳排放预测:采用KAYA恒等式对未来十五年碳排放分为基准情景和参照情景进行预测。基准情景的发展模式下,也就是以目前的发展状况,基于历史的发展特征和规律。2015年,预计我市的碳排放总量达到26171.4万吨,而到2030年预计高达49031.37万吨。在参照情景的发展模式下,仍保持相同的经济发展速度,但加强能源结构优化,以及节能减排,主要是降低能源强度和人口控制,预测2015年碳排放量为24560.54万吨,而2030年可控制在29644.38万吨,相对于基准模式,碳排放减少幅度分别为6%和39%。
[Abstract]:In response to climate change, countries around the world have made a series of efforts in the past decades, the future of global activities and institutional exchanges will continue to advance. Whether a city can be in the forefront of the world in the coming decades depends in large part on its resilience to the advent of a low-carbon era. The premise of energy saving and emission reduction is to calculate the sources of carbon emission in the region scientifically and calculate quantitatively. Taking Shanghai as the research object, based on the statistical yearbook data of the last ten years (2003-2012), based on the overview of basic theory and literature review, this paper selects and improves the carbon emission measurement model suitable for this paper. From the point of view of carbon source and carbon sink, the carbon emission in Shanghai is calculated and estimated, and the characteristic index is selected to analyze and evaluate the change of carbon emission with time series in Shanghai. Horizontally, taking two provinces and one city in the Yangtze River Delta as the comparative object, and analyzing the effect of carbon emission among regions according to the efficiency index of carbon emissions, the characteristics of carbon emissions in Shanghai are explained, and the ridge regression function is used. In order to study the influence factors of population factors, affluence factors, energy structure and technology factors on carbon emissions of energy activities, the STIRPAT model was fitted with MATLAB calculation tools. The future carbon emission trends in Shanghai are predicted by KAYA identity. According to the research results and comprehensive evaluation, the countermeasures and suggestions for the development of low carbon in Shanghai are put forward. The main conclusions are as follows: (1) the current situation and characteristics of carbon emissions in Shanghai: in 2003, the net carbon emissions in Shanghai were 182.0034 million tons, increasing to 237.6296 million tons in 2012, with an average annual growth rate of 3.2 tons. Total emissions varied in stages with time series, with negative growth in 2009. In terms of the contribution of carbon sources, the proportion of carbon emissions from fossil energy consumption in Shanghai is 98%, and the industrial production process is 1.8%. Although the per capita carbon emissions show a certain upward trend, Shanghai's carbon emission intensity basically decreased linearly. Compared with the other two provinces in the Yangtze River Delta, Shanghai has the lowest total carbon emissions, but the per capita carbon emissions are the first, the gap gradually narrowed with the change of time. Compared with Jiangsu and Zhejiang provinces, the carbon emission intensity of Shanghai is higher than that of Zhejiang province, and the decrease of carbon emission in Shanghai is larger than that in Jiangsu and Zhejiang provinces in the past ten years. Judging from the efficiency of carbon emissions, the average value of carbon emission efficiency in Shanghai from 2003 to 2012 is 1.005, which is higher than that in Zhejiang (0.957) and Jiangsu Province (0.9), but the stability is poor. (2) the driving factors of carbon emissions in Shanghai: according to the extended STIRPAT model, the driving factors of carbon emissions in Shanghai from 2003 to 2012 are analyzed. It is found that the energy structure is the fastest driving factor for the total carbon emission in our city, and the driving index is 0.215, followed by the population, the driving index is 0.162, and the effect of industrial structure is the weakest (0.125). The improvement of technology will restrain the increase of carbon emissions. The coefficients are all less than 1. The change rate of environmental effect brought by each driving factor is smaller than that of this factor. (3) the prediction of future carbon emissions in Shanghai: using KAYA identity formula to predict the carbon emissions in the next 15 years as the benchmark scenario and reference scenario. Based on the development characteristics and laws of history, the total carbon emission of our city is expected to reach 261.714 million tons in 2015 and 490.3137 million tons by 2030. In the development model of reference scenario, the same economic development rate is maintained, but to strengthen the optimization of energy structure, and to save energy and reduce emissions, mainly by reducing energy intensity and population control, the carbon emissions in 2015 are projected to be 245.6054 million tons. By 2030, it could be controlled at 296.4438 million tons, with carbon reductions of 6% and 39%, respectively, relative to the benchmark model.
【学位授予单位】：上海师范大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X321

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