大气污染物排放源处理系统EMIPS的开发与应用

发布时间：2018-05-03 17:11

本文选题：排放源清单 + SMOKE模型　；参考：《西安建筑科技大学》2015年硕士论文

【摘要】：随着社会经济的高速发展,工业水平的不断提高,能源的消耗量也越来越多,而由此造成的大气污染物的排放量也急剧增加,严重影响了人们的日常生活和社会的发展。空气质量预报模式可以对未来的空气质量进行预报,为相关政策的制定和空气污染的治理提供依据。而大气污染物排放源清单作为空气质量预报模式的重要输入数据,对预报结果的准确性起着重要的作用,所以更高效、更准确的对排放源清单进行处理是非常必要的。本文参考排放因子的排放源计算方法以及目前普遍使用的排放源处理模式SMOKE模型,开发了大气污染物排放源处理系统EMIPS。系统基于MeteoInfo Java库,由Java程序设计语言进行开发,并用MySQL数据库对排放源数据进行管理。MeteoInfo Java库可以提供一定的GIS功能,用来进行数据的格点化等处理。EMIPS还可以根据对数据格式的不同需要,自行编写Jython脚本对数据进行批量处理。EMIPS主要功能包括排放源清单的计算、模式可用的排放源的处理以及一些NetCDF数据文件的处理等功能。排放源清单的计算根据排放因子法来进行计算,主要是将基础的统计数据以及排放因子等导入MySQL数据库中,然后从数据库中读取相应的数据计算出相应排放源的排放量,并把计算出的结果导回到数据库中,以便进行后续的排放源处理操作。排放源的处理主要包括对面源的处理、对点源的处理以及对外部已经格点化的排放源数据进行处理。对点源的处理过程主要包括格点的转化以及集合、化学组份分配、时间分配;对面源的处理过程主要包括空间分配、化学组份分配、时间分配;对外部格点化数据的处理过程主要包括格点大小的转化、投影类型的转化、时间分配、化学组份分配。对排放源的最终处理结果将存入创建好的NetCDF文件中,方便数据的分析。本文利用曹国良老师收集的2010年的排放源基础数据及排放因子对EMIPS系统的排放源计算功能进行了调试,最终处理成空气质量模式CUACE可用的排放源格式,并成功运用在CUACE模式中。计算出的清单通过分析表明,EMIPS对排放源的计算及内部数据处理结果比较合理。系统使用HTAP的2010年格点化排放源数据对外部排放源的处理以及格点大小、投影类型的转化等功能进行调试,调试结果通过分析表明对外部数据的处理以及格点大小、投影类型转化等处理都比较合理。通过对CUACE模式预报结果进行评估得到模式的预报效果良好。
[Abstract]:With the rapid development of social economy and the continuous improvement of industrial level, the consumption of energy is increasing, and the emissions of atmospheric pollutants are also increasing rapidly, which seriously affects the daily life of people and the development of society. The air quality prediction model can forecast the air quality in the future and provide the basis for the formulation of relevant policies and the control of air pollution. As the important input data of the air quality prediction model, the air pollutant emission source inventory plays an important role in the accuracy of the forecast results, so it is necessary to process the emission source inventory more efficiently and accurately. Referring to the emission source calculation method of emission factor and the SMOKE model of emission source treatment model widely used at present, the emission source treatment system of atmospheric pollutants (EMIPs) is developed in this paper. The system is based on MeteoInfo Java library, developed by Java programming language, and managed by MySQL database. MeteoInfo Java library can provide certain GIS function. EMIPS can also write Jython script for batch processing of data according to different data format. EMIPS main functions include the calculation of emission source inventory. Mode available emission source processing and some NetCDF data file processing and other functions. The calculation of the emission source inventory is based on the emission factor method, which mainly introduces the basic statistical data and emission factors into the MySQL database, and then reads the corresponding data from the database to calculate the emissions of the corresponding source. The calculated results are brought back to the database for subsequent emission source processing. The treatment of emission source mainly includes the treatment of point source, the processing of point source and the processing of external already punctured emission source data. The processing process of point source mainly includes lattice transformation, collection, chemical component distribution and time distribution, while the processing process of non-point source mainly includes space distribution, chemical component distribution and time distribution. The processing process of external lattice data mainly includes the transformation of lattice size, projection type, time distribution and chemical component distribution. The final processing result of the emission source will be stored in the created NetCDF file to facilitate the analysis of the data. Based on the basic data and emission factors collected by Cao Guoliang in 2010, this paper debugs the function of emission source calculation in EMIPS system, and finally processes the emission source format available for CUACE in air quality mode, and successfully applies it to CUACE mode. The calculated inventory shows that EMIPS is reasonable for the calculation of emission sources and internal data processing. The system uses HTAP's 2010 lattice emission source data to deal with the external emission source, as well as the lattice size, projection type transformation and other functions to debug. The debugging results show that the external data processing and lattice size, Projection type transformation and other processing are more reasonable. By evaluating the prediction results of the CUACE model, it is shown that the model has a good prediction effect.
【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X51

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