上海市机动车污染物排放的测算与协同控制效应研究

发布时间：2018-05-25 06:01

本文选题：机动车 + 排放因子　；参考：《合肥工业大学》2015年硕士论文

【摘要】：近年来,随着社会经济的高速发展和居民生活水平的提高,城市机动车保有量快速增长,机动车污染物排放已成为众多城市大气污染的主要来源。针对地区机动车污染物排放特征开展控制研究,合理制定地区机动车污染控制措施已迫在眉睫。本文以上海市机动车污染物排放量研究为目标,借鉴国内外机动车污染相关研究经验,通过详细调查上海市机动车道路交通等基础资料,利用机动车排放因子与机动车活动水平数据的乘积得到上海市机动车各污染物排放量,同时对上海市未来几年的机动车污染物排放量进行了预测。计算结果表明：(1)2007-2012年间,上海市机动车污染物年排放量呈递减趋势,从2007年的56.47万t下降到2012年的50.79万t,说明近几年该地区机动车污染物排放情况得到一定的缓解,但污染仍然很严峻；同时由机动车污染物排放的车型分担率结果可知MC、LDGV、 HDDT和HDDV是机动车污染物主要的排放源,其排放量总和占到机动车污染物总量的90%以上。(2)采用一元线性回归模型的构造与检验原理,通过对2007-2012年上海市机动车保有量、机动车污染物排放总量以及各污染物排放量数据的分析,建立起上海市机动车保有量与机动车污染物排放总量之间的一元线性回归预测模型Yi=71.703-0.06X,,相关系数R=0.958。而后,利用该预测模型分析得到2013-2018年上海市机动车污染物排放总量以及6种污染物排放量的预测值。其次通过现有资料与数据,以2007-2012年为一个时间序列,采用灰色关联法对上海市大气环境影响因素进行分析知,大气中各污染物浓度受众多因素的影响,其中机动车排放是造成空气污染物浓度升高的主要原因。同时选取七个经济指标作为上海市代表性经济变量,通过主成分分析法提取出的主成分作为经济代表性因素,再通过多元线性回归方法建立多元线性回归方程：Y=102.81+0.408X1+7.107X2,根据该方程的系数可知：经济因素对汽车保有量的影响最大,其次是汽车产量对汽车保有量的影响。由此我们得出经济因素是影响汽车保有量变化的最重要因素。最后根据国内外实施机动车污染控制手段结合上海市实际情况,运用协同控制坐标系评价方法,设计了三类机动车污染减排的控制情景：“单个措施控制方案、结构性调整控制方案、综合控制方案”,分析在不同的机动车控制措施情景下各污染物与温室气体的之间协同效应,为上海市今后开展机动车污染减排提供理论依据。
[Abstract]:In recent years, with the rapid development of social economy and the improvement of residents' living standard, the number of urban motor vehicles has increased rapidly, and the emission of motor vehicle pollutants has become the main source of air pollution in many cities. It is urgent to study the emission characteristics of regional motor vehicle pollutants and make reasonable measures to control regional vehicle pollution. This paper aims at the study of the emission of motor vehicle pollutants in Shanghai, draws on the relevant research experience of motor vehicle pollution at home and abroad, and through the detailed investigation of the basic data of motor vehicle road traffic in Shanghai, By using the product of motor vehicle emission factor and motor vehicle activity level data, the emission of motor vehicle pollutants in Shanghai is obtained, and the emission of motor vehicle pollutants in Shanghai in the next few years is forecasted. The calculated results show that the annual emission of motor vehicle pollutants in Shanghai decreased from 564700 tons in 2007 to 507900 tons in 2012 from 2007 to 2012, indicating that the emission of motor vehicle pollutants in this area has been alleviated in recent years. However, the pollution is still very serious. At the same time, the results of the vehicle model share rate of vehicle pollutant emission show that MCG, HDDT and HDDV are the main emission sources of motor vehicle pollutants. The total amount of its emissions accounts for more than 90% of the total amount of motor vehicle pollutants.) based on the principle of the construction and inspection of a linear regression model for the construction and inspection of motor vehicle ownership in Shanghai from 2007 to 2012, Based on the analysis of the total emission of motor vehicle pollutants and the emission data of various pollutants, a linear regression prediction model was established for predicting the relationship between vehicle ownership and total emission of motor vehicle pollutants in Shanghai, with a correlation coefficient of 0.958 and 71.703-0.06Xn. Then, the forecast values of total motor vehicle pollutant emission and six kinds of pollutants emissions from 2013 to 2018 in Shanghai were obtained by using the forecasting model. Secondly, based on the existing data and data, taking 2007-2012 as a time series and using the grey correlation method to analyze the influence factors of atmospheric environment in Shanghai, we know that the concentration of pollutants in the atmosphere is affected by many factors. Motor vehicle emission is the main cause of the increase of air pollutant concentration. At the same time, seven economic indicators are selected as the representative economic variables of Shanghai, and the principal components extracted by principal component analysis are taken as representative economic factors. The multivariate linear regression equation is established by the method of multivariate linear regression. According to the coefficient of the equation, the economic factors have the greatest influence on the vehicle ownership, and the next is the effect of the automobile output on the automobile ownership. From this, we draw the conclusion that economic factors are the most important factors affecting the change of vehicle ownership. Finally, according to the implementation of motor vehicle pollution control methods at home and abroad combined with the actual situation in Shanghai, using the evaluation method of coordinated control coordinate system, three control scenarios of vehicle pollution reduction are designed: "single measure control scheme," Structural Adjustment Control Scheme, Comprehensive Control Scheme, this paper analyzes the synergistic effect between pollutants and greenhouse gases under different vehicle control measures, and provides a theoretical basis for the future development of motor vehicle pollution emission reduction in Shanghai.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X734.2

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