水泥工业大气颗粒物的污染模拟应用研究

发布时间：2018-03-30 09:34

本文选题：水泥　切入点：颗粒物　出处：《昆明理工大学》2015年硕士论文

【摘要】：随着社会生产力的发展,工业项目对环境质量的影响日趋严重,其中,工业大气颗粒物排放已成为对我国城市空气质量影响最大的污染行为之一。水泥的生产特点决定了其对大气环境的主要污染物为颗粒物,经粗略统计,我国水泥工业每年约向大气排放数十万吨的粉尘,水泥生产已成为我国大气颗粒物污染的主要来源之一。目前,我国针对工业项目的大气环境污染预测主要是通过导则推荐模型来模拟预测的,但导则推荐模型对气象数据的要求颇为严格,部分地区特别是对于我国的偏远地区来说,其当地气象站的气象资料不足以满足导则的参数和距离要求,同时我国提供的网上气象资料又存在诸多权限,因此,针对替代气象资料的气象数据研究就显得颇为重要;另一方面,水泥生产的特点决定其颗粒物的无组织排放节点多,且受环境因素影响大，，其排放过程的复杂性导致对其评价和控制都较困难。基于以上两点,本文首先通过运用AERMOD模式模拟不同气象情景下的PM10地面浓度值并进行误差分析、符合度分析、回归分析和模糊评价,判断NOAA(美国国家海洋和大气管理局)提供的在线气象数据的替代可行性；其次,利用方差分析法探究无组织排放源强的最优核算方法和预测模式系统并进行验证。结果如下：(1)使用NOAA气象数据替代常规地面气象数据输入AERMOD模型进行预测模拟时,与常规气象情景模拟值比较分析可知：PM10的关心点地面浓度模拟效果优于高值点和网格点的浓度模拟；针对期间浓度来说,关心点的长期浓度模拟符合度大于短期浓度的模拟符合度,但高值点和网格点的短期浓度模拟效果则优于长期浓度的模拟。因此,根据项目预测需求的不同,在一定程度上是可以使用NOAA提供的地面气象资料替代导则规定的常规地面气象数据来进行AERMOD预测的。(2)在本文设计的四种针对水泥厂颗粒物无组织排放的模拟方案中,AERMOD-类比经验公式法经监测数据验证确定为最优预测方案,采用类比经验公式法计算出的颗粒物无组织排放源强最为可靠,其模拟值与监测值的符合度d为0.7090.6,均方误差MSE为0.0088,符合度良好。但在对该方案进行进一步应用验证时发现,由于模拟使用的气象数据不能与监测期间气象状况完全吻合以及近场复杂地形的因素,该方案在预测颗粒物无组织排放时可能会出现不同风向模拟效果差异较大的结果。因此,在使用本研究的核算方法时,结合项目的实际生产情况来进行源强核算,并准确设置各参数才能保证模拟结果的可信度。
[Abstract]:With the development of social productivity, the impact of industrial projects on environmental quality is becoming more and more serious, among which, The emission of industrial atmospheric particulates has become one of the most serious pollution behaviors affecting the air quality of cities in China. The characteristics of cement production determine that the main pollutants to the atmospheric environment are particulate matter. China's cement industry releases hundreds of thousands of tons of dust into the atmosphere every year. Cement production has become one of the main sources of atmospheric particulate pollution in China. The air pollution prediction for industrial projects in China is mainly simulated by the guide recommendation model. However, the guidance recommendation model requires strict meteorological data. Some areas, especially for the remote areas of our country, are very strict. The meteorological data of the local meteorological station is not enough to meet the requirements of the parameters and distance of the guidelines. At the same time, the online meteorological data provided by our country also has many rights. Therefore, it is very important to study the meteorological data to replace the meteorological data. On the other hand, the characteristics of cement production determine that its particulates have many unorganized discharge nodes and are greatly affected by environmental factors. The complexity of the discharge process makes it difficult to evaluate and control them. In this paper, AERMOD model is used to simulate the ground concentration of PM10 in different meteorological scenarios, and error analysis, coincidence analysis, regression analysis and fuzzy evaluation are carried out. To determine the alternative feasibility of the online meteorological data provided by NOAA (National Oceanic and Atmospheric Administration). Secondly, The method of variance analysis is used to study and verify the optimal accounting method and forecasting model system of unorganized emission source strength. The results are as follows: 1) when NOAA meteorological data are used instead of conventional ground meteorological data to be input into AERMOD model for forecasting simulation, Comparing with the conventional meteorological scenario simulation results show that the ground concentration simulation effect of the concerned point of concern is better than that of the high value point and the grid point, and for the concentration of the period, the effect of the simulation is better than that of the high value point and the grid point. The consistency degree of long-term concentration simulation is greater than that of short-term concentration simulation, but the short-term consistency simulation effect of high value point and grid point is better than that of long-term concentration simulation. To a certain extent, it is possible to use the surface meteorological data provided by NOAA to replace the conventional surface meteorological data provided by the guidelines for AERMOD prediction.) in this paper, four simulation schemes for unorganized discharge of particulates from cement plants are designed. The AERMOD- analogical empirical formula method has been verified by monitoring data as the optimal prediction scheme. The empiric formula method is used to calculate the unorganized emission source strength of particulate matter. The coincidence between the simulated value and the monitoring value is 0.7090.6, and the mean square error (MSE) is 0.0088, which is good. Because the meteorological data used in the simulation can not be completely consistent with the meteorological conditions during the monitoring period and the factors of complex terrain in the near field, the simulation results of different wind directions may be quite different in predicting the unorganized discharge of particulate matter. In order to ensure the reliability of the simulation results, the source strength calculation is carried out by combining the actual production situation of the project with the accounting method of this study, and the accurate setting of each parameter can ensure the credibility of the simulation results.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X781.5

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