本文選題：城市大氣質量 + 網格化��； 參考：《西安科技大學》2017年碩士論文

【摘要】：隨著我國經濟水平的快速提高,城市化進程和各種產業(yè)發(fā)展日益增快,對環(huán)境的破壞也日益加重。大氣質量作為可持續(xù)發(fā)展的重要組成部分也越來越受到人們的關注。大氣中的污染物濃度在不斷增加,影響范圍也越來越大,以顆粒污染物、二氧化硫、氮氧化物等為主的城市大氣污染問題日趨嚴重。因此,研究和分析城市大氣質量綜合水平是解決城市環(huán)境問題,改善城市大氣質量,建設城市大氣污染對策,實現環(huán)境與經濟的可持續(xù)發(fā)展的首要任務。本研究主要以西安市大氣質量分布狀況為例,分析了西安市大氣污染物的時空分布特征,建立了西安市大氣質量綜合評價模型,同時還對影響西安市大氣質量的因素進行了分析。結果顯示,2013～2016年西安市大氣質量污染較為嚴重,處于四級重度污染水平;采暖期污染比非采暖期污染嚴重,主城區(qū)污染比郊區(qū)污染嚴重;顆粒物污染特別是細顆粒物污染相當嚴重。影響西安市大氣質量的主要因素為工業(yè)企業(yè)廢氣排放、供暖廢氣排放、風速、機動車尾氣排放、人口密度分布等。20世紀中期以來,國內外逐漸開始實施大氣質量監(jiān)測工作,并將監(jiān)測數據對外公布,還在全國范圍內進行綜合排名,以便人們更方便具體的了解自己的居住環(huán)境和全國的大氣質量分布狀況。因此,監(jiān)測點位的代表性,監(jiān)測結果的真實性、可靠性便成了亟待解決的問題。本研究以西安市為例,采用多目標優(yōu)化方法,對西安市大氣質量監(jiān)測點位進行優(yōu)化,并使用約束法和層次序列化方法分別對模型求解,并將結果使用ArcGis軟件在地圖上顯示。結果顯示,該模型較為科學合理地實現了西安市大氣質量監(jiān)測點位的優(yōu)化,兩種求解方法的結果都能很好地滿足西安市實際狀況和模型要求,新增的4個監(jiān)測點位均分別位于周至縣、戶縣、藍田縣和高陵區(qū)內。但是采用層次序列化方法求解的結果分布相對比約束法的結果更為均勻,空間覆蓋率較高,代表性較好,監(jiān)測結果能很好地反映出整個西安市的大氣分布狀況。
[Abstract]:With the rapid improvement of our country's economic level, the process of urbanization and the development of various industries are increasing day by day, and the damage to the environment is becoming more and more serious. As an important part of sustainable development, atmospheric quality has attracted more and more attention. The concentration of pollutants in the atmosphere is increasing, and the influence range is becoming larger and larger. The urban air pollution problems, such as particulate pollutants, sulfur dioxide, nitrogen oxides and so on, are becoming more and more serious. Therefore, to study and analyze the comprehensive level of urban atmospheric quality is the first task to solve urban environmental problems, improve urban air quality, build urban air pollution countermeasures and realize the sustainable development of environment and economy. Taking the distribution of air quality in Xi'an as an example, the characteristics of spatial and temporal distribution of air pollutants in Xi'an are analyzed, and a comprehensive evaluation model of air quality in Xi'an is established. At the same time, the factors influencing the air quality in Xi'an are analyzed. The results show that the air quality pollution in Xi'an city is more serious from 2013 to 2016, and the pollution in heating period is more serious than that in non-heating period, and the pollution in main urban area is more serious than that in suburban area, and the pollution in heating period is more serious than that in non-heating period. The pollution of particulates, especially fine particles, is quite serious. Since the middle of the 20th century, the main factors affecting the air quality of Xi'an are exhaust gas emissions from industrial enterprises, exhaust gas emissions from heating, wind speed, vehicle exhaust emissions, population density distribution, and so on. Since the middle of the 20th century, the monitoring of air quality has gradually begun to be carried out at home and abroad. And the monitoring data will be released to the public, but also in the national comprehensive ranking, so that people more convenient to understand their living environment and the distribution of national atmospheric quality. Therefore, the representativeness of monitoring points, the authenticity and reliability of monitoring results are urgent problems to be solved. Taking Xi'an city as an example, the multi-objective optimization method is used to optimize the monitoring points of air quality in Xi'an city. The model is solved by constraint method and hierarchical serialization method, and the results are displayed on the map by ArcGis software. The results show that the model can realize the optimization of air quality monitoring points in Xi'an City scientifically and reasonably, and the results of the two methods can well meet the actual situation and model requirements of Xi'an City. Four new monitoring points are located in Zhouzhi County, Huxian County, Lantian County and Gaoling area. However, the results obtained by the hierarchical serialization method are more uniform, higher spatial coverage and better representativeness than the constraint method. The monitoring results can well reflect the atmospheric distribution situation of the whole Xi'an city.
【學位授予單位】：西安科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：X823;X831

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