关中地区高时空分辨率机动车污染排放清单研究

发布时间：2018-03-21 00:30

本文选题：关中地区　切入点：机动车污染　出处：《长安大学》2015年硕士论文　论文类型：学位论文

【摘要】：近年来,随着经济的快速发展,人民生活水平的提高,关中地区机动车保有量迅速增加,机动车污染排放在关中大气复合型污染中所占的比重越来越大。机动车尾气中的污染物通过呼吸道进入人体,会引起呼吸道疾病,对人体的健康产生极大的危害。因此,开展机动车污染控制研究,探寻关中地区机动车污染排放特征及其时空分布规律,制定有效的污染控制策略,已成为迫在眉睫的问题。机动车污染排放清单是机动车污染源排放各种污染物信息的集合,是政府和环保部门在政策制定和环境管理时重要的参考依据,也是空气质量模型重要的基础输入数据,它对于模拟和了解研究区域的空气质量状况,制定有效的污染减排措施具有重要的作用。本论文建立了一套详细的机动车污染排放清单测算方法,包括排放因子的模拟,排放清单的估算和时空分布的建立等内容。首先,本文利用MOVES模型模拟了关中地区机动车分车型排放因子,并通过排放因子法估算得到机动车污染排放清单。2012年关中机动车PM2.5、PM10、NOX、THC、CO、VOC、NH3和SO2排放量依次为0.41×104吨、0.55×104吨、8.19×104吨、5.24×104吨、45.4×104吨、4.1×104吨、0.1×104吨和0.42×104吨。其中,西安市的污染排放比重最大,PM2.5和PM10排放量分别占到46.53%和48.39%;汽油车(主要是小型客车和摩托车)是CO和VOC的主要机动车排放源,柴油车(主要是中、重型货车)是NOx和PM的主要机动车排放源。其次,以关中现有道路网为基础,通过线源和面源相结合的方式对排放清单进行时空分布,并研究了污染排放时间分布规律和空间分布特征,得出机动车污染排放呈现出明显的区域性特征,在路网较为稠密,人口流动量较大的城市中心地带污染排放较高,以西安市最为明显,城区污染排放最严重,向外延伸,排放也逐渐减少。最后,根据关中实际情况,简要探讨了适合关中地区的污染控制措施。
[Abstract]:In recent years, with the rapid development of economy and the improvement of people's living standard, the number of motor vehicles in Guanzhong area has increased rapidly. Vehicle pollution emissions account for more and more of the air pollution in Guanzhong. The pollutants from motor vehicle exhaust enter the human body through the respiratory tract, which will cause respiratory diseases and cause great harm to human health. To study motor vehicle pollution control, to explore the characteristics of motor vehicle pollution emission and its space-time distribution in Guanzhong area, and to formulate effective pollution control strategies. Motor vehicle pollution emission inventory is a collection of pollutant information from motor vehicle pollution sources. It is an important reference basis for government and environmental protection departments in policy formulation and environmental management. It is also an important input data for air quality models, which can be used to simulate and understand the air quality situation in the study area. It is very important to establish effective emission reduction measures. In this paper, a set of detailed vehicle emission inventory calculation methods are established, including the simulation of emission factors, the estimation of emission inventory and the establishment of space-time distribution. In this paper, MOVES model is used to simulate vehicle emission factors in Guanzhong area. In 2012, the emission of vehicle PM2.5G10NOXTHCTHCTHCTHCTHC-COVOCU NH3 and SO2 were 0.41 脳 104 tons, 0.55 脳 104 tons, 8.19 脳 104 tons, 5.24 脳 104 tons, 45.4 脳 104 tons, 4.1 脳 10 4 tons, 0.1 脳 104 tons and 0.42 脳 104 tons, respectively. Xi'an has the largest proportion of pollution emissions, PM2.5 and PM10, which account for 46.53% and 48.39.The gasoline vehicles (mainly minibuses and motorcycles) are the main sources of motor vehicle emissions of CO and VOC, while diesel vehicles (mainly medium), Heavy truck) is the main vehicle emission source of NOx and PM. Secondly, based on the existing road network in Guanzhong, the emission inventory is distributed in time and space through the combination of line source and non-point source. The characteristics of time and space distribution of pollution emission are studied. It is concluded that vehicle pollution emission shows obvious regional characteristics, and the pollution emission is higher in the urban center where the road network is dense and the population is large. The pollution discharge in Xi'an is the most serious, which extends outward and decreases gradually. Finally, according to the actual situation of Guanzhong, the pollution control measures suitable for Guanzhong are briefly discussed.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X734.2

【共引文献】