空气质量模型的研究与应用

发布时间：2018-07-15 12:49

【摘要】：近年来,因为经济的快速增长所引起的大气环境污染状况日益严重。面对这样的难题,使用高效系统的空气质量模型成为研究空气质量的主要方法。目前,美国环保局研制的基于“一个大气”理念的第三代空气质量模型Models-3/CMAQ是最具代表性的空气质量模型。对于CMAQ的应用不仅是最高级的,同时也是国内研究最多的。CMAQ模式的输入数据包含WRF模式的气象场数据和SMOKE模式的污染物源排放清单数据。所以,把WRF/SMOKE/CMAQ组成空气质量模型系统进行研究。由于使用了Python程序模拟SMOKE模式的功能,所以原来的模型系统变成了WRF/Psmoke/CMAQ模型系统。如果想要应用模型系统研究我国的空气质量问题,就要对它进行本地化。本文以某市的24个区县为例,通过WRF/Psmoke/CMAQ模型系统的本地化过程来研究某市的大气污染问题。模型系统在环境搭建、安装运行方面具有一定的复杂性,所以本文研究了基于Ubuntu操作系统的Py Qt5的模型系统开发平台。开发平台能够使得研究者更快更好的进入到模型系统的学习和使用当中去。基于此,本文的主要内容如下:搭建CMAQ模式、WRF模式、Psmoke模式安装和运行的环境。对三个模式分别进行介绍,同时介绍各个模式的模块化结构和应用流程。安装CMAQ模式和WRF模式。Psmoke模式利用python程序模拟SMOKE模式的功能。进行WRF/Psmoke/CMAQ模型系统的本地化应用过程。首先进行WRF模式的气象场模拟。设置模拟区域和模拟时间。然后,整理收集到的10种污染物的数据,放入Psmoke模式中制作污染物源排放清单。最后,将WRF模式、Psmoke模式的输出数据作为CMAQ模式的输入数据,进行模拟大气化学反应过程。最后的输出结果使用VERDI得到可视化分析。搭建基于Python语言的Py Qt5开发环境。设计模型的可视化框架,将模型系统的本地化应用过程设计到界面里面。其中,功能的实现利用了shell程序和pyth on程序。同时,把手工整理污染物数据的过程进行了自动化整理的设计。这个设计进行了代表性的尝试,得到的结果有一定程度的指导作用。
[Abstract]:In recent years, the atmospheric environment pollution caused by the rapid economic growth is becoming more and more serious. In the face of this problem, the use of efficient air quality models has become the main method of air quality research. At present, Models-3 / CMAQ, the third generation air quality model based on "one atmosphere", developed by EPA, is the most representative model of air quality. The application of CMAQ is not only the most advanced, but also the input data of the CMAQ model, which is the most studied in China, including the meteorological field data of WRF model and the pollutant source emission inventory data of SMOKE model. Therefore, WRF / SMOKE / CMAQ is used to form an air quality model system. Because of the use of Python program to simulate SMOKE mode, the original model system became WRF / Psmoke-CMAQ model system. If we want to apply the model system to study the air quality problem in our country, we must localize it. This paper takes 24 districts and counties of a city as an example to study the problem of air pollution in a certain city through the localization process of WRF / Psmoke-CMAQ model system. The model system has some complexity in environment construction and installation, so this paper studies the model system development platform of Py Qt5 based on Ubuntu operating system. Development platform enables researchers to quickly and better enter the learning and use of model systems. Based on this, the main contents of this paper are as follows: setting up the installation and running environment of CMAQ mode / WRF mode / Psmoke mode. The three models are introduced respectively, and the modularization structure and application flow of each model are introduced at the same time. Install CMAQ mode and WRF mode. Psmoke mode using python program to simulate SMOKE mode. The localization process of WRF / Psmoke-CMAQ model system is carried out. First, the weather field simulation of WRF model is carried out. Set the simulation area and the simulation time. Then, the collected data of 10 pollutants are compiled and put into Psmoke mode to make pollutant source emission inventory. Finally, the output data of WRF mode and Psmoke mode are used as the input data of CMAQ model to simulate the atmospheric chemical reaction process. The final output is visualized by Verdi. Build Py Qt5 development environment based on Python language. The visualization framework of the model is designed to design the local application process of the model system into the interface. Among them, the realization of the function uses shell program and pyth on program. At the same time, the process of manual collation of pollutant data is designed automatically. This design has carried on the representative attempt, the result has the certain degree guidance function.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X51;TP311.52

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