本文選題：水泥　切入點(diǎn)：顆粒物　出處：《昆明理工大學(xué)》2015年碩士論文

【摘要】：隨著社會(huì)生產(chǎn)力的發(fā)展,工業(yè)項(xiàng)目對(duì)環(huán)境質(zhì)量的影響日趨嚴(yán)重,其中,工業(yè)大氣顆粒物排放已成為對(duì)我國(guó)城市空氣質(zhì)量影響最大的污染行為之一。水泥的生產(chǎn)特點(diǎn)決定了其對(duì)大氣環(huán)境的主要污染物為顆粒物,經(jīng)粗略統(tǒng)計(jì),我國(guó)水泥工業(yè)每年約向大氣排放數(shù)十萬(wàn)噸的粉塵,水泥生產(chǎn)已成為我國(guó)大氣顆粒物污染的主要來(lái)源之一。目前,我國(guó)針對(duì)工業(yè)項(xiàng)目的大氣環(huán)境污染預(yù)測(cè)主要是通過(guò)導(dǎo)則推薦模型來(lái)模擬預(yù)測(cè)的,但導(dǎo)則推薦模型對(duì)氣象數(shù)據(jù)的要求頗為嚴(yán)格,部分地區(qū)特別是對(duì)于我國(guó)的偏遠(yuǎn)地區(qū)來(lái)說(shuō),其當(dāng)?shù)貧庀笳镜臍庀筚Y料不足以滿足導(dǎo)則的參數(shù)和距離要求,同時(shí)我國(guó)提供的網(wǎng)上氣象資料又存在諸多權(quán)限,因此,針對(duì)替代氣象資料的氣象數(shù)據(jù)研究就顯得頗為重要;另一方面,水泥生產(chǎn)的特點(diǎn)決定其顆粒物的無(wú)組織排放節(jié)點(diǎn)多,且受環(huán)境因素影響大，，其排放過(guò)程的復(fù)雜性導(dǎo)致對(duì)其評(píng)價(jià)和控制都較困難�；谝陨蟽牲c(diǎn),本文首先通過(guò)運(yùn)用AERMOD模式模擬不同氣象情景下的PM10地面濃度值并進(jìn)行誤差分析、符合度分析、回歸分析和模糊評(píng)價(jià),判斷NOAA(美國(guó)國(guó)家海洋和大氣管理局)提供的在線氣象數(shù)據(jù)的替代可行性；其次,利用方差分析法探究無(wú)組織排放源強(qiáng)的最優(yōu)核算方法和預(yù)測(cè)模式系統(tǒng)并進(jìn)行驗(yàn)證。結(jié)果如下：(1)使用NOAA氣象數(shù)據(jù)替代常規(guī)地面氣象數(shù)據(jù)輸入AERMOD模型進(jìn)行預(yù)測(cè)模擬時(shí),與常規(guī)氣象情景模擬值比較分析可知：PM10的關(guān)心點(diǎn)地面濃度模擬效果優(yōu)于高值點(diǎn)和網(wǎng)格點(diǎn)的濃度模擬；針對(duì)期間濃度來(lái)說(shuō),關(guān)心點(diǎn)的長(zhǎng)期濃度模擬符合度大于短期濃度的模擬符合度,但高值點(diǎn)和網(wǎng)格點(diǎn)的短期濃度模擬效果則優(yōu)于長(zhǎng)期濃度的模擬。因此,根據(jù)項(xiàng)目預(yù)測(cè)需求的不同,在一定程度上是可以使用NOAA提供的地面氣象資料替代導(dǎo)則規(guī)定的常規(guī)地面氣象數(shù)據(jù)來(lái)進(jìn)行AERMOD預(yù)測(cè)的。(2)在本文設(shè)計(jì)的四種針對(duì)水泥廠顆粒物無(wú)組織排放的模擬方案中,AERMOD-類(lèi)比經(jīng)驗(yàn)公式法經(jīng)監(jiān)測(cè)數(shù)據(jù)驗(yàn)證確定為最優(yōu)預(yù)測(cè)方案,采用類(lèi)比經(jīng)驗(yàn)公式法計(jì)算出的顆粒物無(wú)組織排放源強(qiáng)最為可靠,其模擬值與監(jiān)測(cè)值的符合度d為0.7090.6,均方誤差MSE為0.0088,符合度良好。但在對(duì)該方案進(jìn)行進(jìn)一步應(yīng)用驗(yàn)證時(shí)發(fā)現(xiàn),由于模擬使用的氣象數(shù)據(jù)不能與監(jiān)測(cè)期間氣象狀況完全吻合以及近場(chǎng)復(fù)雜地形的因素,該方案在預(yù)測(cè)顆粒物無(wú)組織排放時(shí)可能會(huì)出現(xiàn)不同風(fēng)向模擬效果差異較大的結(jié)果。因此,在使用本研究的核算方法時(shí),結(jié)合項(xiàng)目的實(shí)際生產(chǎn)情況來(lái)進(jìn)行源強(qiáng)核算,并準(zhǔn)確設(shè)置各參數(shù)才能保證模擬結(jié)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.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：X781.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 姚增權(quán);國(guó)外空氣質(zhì)量模式研究現(xiàn)狀及展望[J];電力環(huán)境保護(hù);1999年03期

2 黃創(chuàng)綿;蔡汝山;;單因素方差分析方法在環(huán)境試驗(yàn)中的應(yīng)用[J];電子產(chǎn)品可靠性與環(huán)境試驗(yàn);2010年06期

3 肖楊;毛顯強(qiáng);馬根慧;李卓;;基于ADMS和線性規(guī)劃的區(qū)域大氣環(huán)境容量測(cè)算[J];環(huán)境科學(xué)研究;2008年03期

4 孫璐;蔡娟;;AERMOD與EIAA大氣預(yù)測(cè)模型在環(huán)境影響評(píng)價(jià)中的應(yīng)用比較[J];環(huán)境污染與防治;2008年10期

5 聶邦勝;;國(guó)內(nèi)外常用的空氣質(zhì)量模式介紹[J];海洋技術(shù);2008年01期

6 王菊;李娜;房春生;;以長(zhǎng)春為例研究環(huán)境空氣中TSP、PM_(10)和PM_(2.5)的相關(guān)性[J];中國(guó)環(huán)境監(jiān)測(cè);2009年02期

7 李冰晶;馬衛(wèi)東;潘峰;仝紀(jì)龍;魏穎;;基于AERMOD2.2的蘭州大學(xué)交通尾氣污染模擬分析[J];安全與環(huán)境工程;2013年03期

8 牛文勝,孫振海;大氣擴(kuò)散模式的簡(jiǎn)要回顧[J];氣象科技;2000年02期

9 樵獻(xiàn)蘭;;5000t/d水泥生產(chǎn)線收塵系統(tǒng)的工藝設(shè)計(jì)[J];水泥工程;2014年03期

相關(guān)博士學(xué)位論文 前1條

1 昝軍;新型干法水泥旋窯窯頭煙塵控制技術(shù)研究[D];中國(guó)地質(zhì)大學(xué);2010年

相關(guān)碩士學(xué)位論文 前2條

1 胡瑩;基于AERMOD模型的復(fù)雜地形下大氣工業(yè)源污染模擬與評(píng)估[D];吉林大學(xué);2014年

2 國(guó)世友;基于AERMOD模式不同氣象情景下SO_2地面濃度的預(yù)測(cè)研究[D];哈爾濱工業(yè)大學(xué);2011年

本文編號(hào)：1685347