請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/5225
標題: 回顧近七年來南投地區臭氧變化
A Review on Ozone Variation in Nantou Area Study period 1997~2003
作者: 林翊逵
Lin, Yi-kuai
關鍵字: Ozone
Data Mining
Decision Tree
Cluster Analysis
Neural Networks
Discrimination analysis
出版社: 環境工程學系所
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Darnall,and James N.Pitts,Jr.,1979,Smog chamber studies of temperature effects in photochemical smog,Environmental Science & Technology, Vol.13,pp.1094-1100. 29.葉家麟 (2002). "以資料採礦方法探討台灣地區機車污染排放特性-各因子間的關聯法則." 碩士論文(中興大學環境工程研究所). 30.潘慧芳 (2004). "中部空氣品質區空氣品質之時空分佈特性分析." 碩士論文(中興大學環工系研究所). 31.吳文雄,1993,台中臭氧污染潛勢之研究,碩士論文,國立中興大學環境工程研究所。 32.李俊毅,1995,台灣南部地區臭氧污染分析,碩士論文,國立台灣大學環境工程研究所。 33.張能復,1997,都會區臭氧污染趨勢分析及防治研究,期中報告,行政院環保署。 34.柳中明,蔡育文,左台利,羅俊光,劉紹臣,1994,”碳氫化合物組合與近地面臭氧生成”,大氣科學,第二十二期,第三號,pp.431-452 35.環保署網頁. http://www.epa.gov.tw 36.南投縣環保局,1997,南投地區臭氧之污染成因探討計畫,期末報告定稿,中興大學環境工程系。
摘要: 本研究資料來源為台中與南投地區境內的空氣品質監測站和中央氣象局設立的氣象站,七年(1997~2003年)的資料做處理分析,了解各項污染物對於南投縣境內臭氧的變化有無影響。採用的分析方法為資料採礦(Data Mining),各方法所得到的結果為:(1)決策樹法(Decision Tree):早上11點到下午5點的這段時間內,NO濃度 < 2.95ppb時,PM10 > 56.85μg/m3,且NO < 0.95ppb,SO2也 < 2.15ppb的情況下,監測站的大氣溫度高達25.95度以上,臭氧濃度的平均值會高達80.2ppb。(2)回歸模式(Regression Model):在11~17點,月份為3、5、9和10月、降雨量稀少、降雨時間短、日照長、此時臭氧值較高;NOx、NO、NO2、THC、NMHC濃度增高時,臭氧值會下降。(3)叢集分析(Cluster Analysis):相對溼度低、風速偏低、降雨量少、能見度佳、雲高度較低、日射量較強、露點溫度、大氣溫度較高、NO、NO2、NOx偏低、竹山測站及南投測站、八月、九月、十一月、中午十二點、下午兩點、三點、六點、臭氧值有偏高的情況發生。(4)類神經網路法(Neural NetWork):用七年的資料經由訓練與測試,產生類神經方程式,代入2005年的資料,對照觀測值與模擬值,與迴歸方程式產生的結果作比較趨勢的變化有何不同。(5)判別分析(Discrimination):得知影響南投地區臭氧良與不良的重要因子為NO、NO2、NOx和CO。
My research data source is supplied from air quality monitoring station and weather station that Central Weather Bureau set up within the border between Taichung and Nantou area, analyze and process this data in seven years from 1997 to 2003. In order to understand wheather every pollutant have influenced the change of ozone in Nantou County, the analysis method I use is Data Mining.The result of Data Mining that every method gets is: (1)Decision Tree : When between eleven o'clock in the morning and five o'clock in the afternoon ,NO concentration is less than 2.95ppb, PM10 concentration is more than 56.85ug/m3 , NO concentration is less than 0.95ppb, SO2 concentration is under 2.15ppb, and the atmospheric temperature of the monitoring station is up to more than 25.95 degrees, then the average of the ozone concentration will be up to 80.2ppb. (2) Regression Model :In March,May,September and October between eleven o'clock in the morning and five o''clock in the afternoon,rainfall rareness, rainfall time are short, the sunshine is long, in this situation,ozone value is relatively high at this moment; When NOx, NO, NO2, THC, NMHC concentration increase, ozone value will drop.(5) Cluster Analysis: The relative humidity is low, the wind speed is on the low side, there is little rainfall, visibility is good, the cloud is relatively low in height, the insolation amount is relatively strong, dew point temperature and atmospheric temperature is relatively high, NO, NO2, NOx is on the low side, in Bamboo Mountain and Nantou Monitoring station, happened in August, September, November,at noon, two o'clock ,three o'clock and six o'clock in the afternoon, ozone value situation will be on the high side. (4) Neural NetWork: Use the data for seven years via training and testing, then produce neural equation, take the place of the pollutant concentration which enter 2005 and contrast observation value and simulation value,compare the change of the trending with the results produced from regression equation.(5) Discrimination:The most important factors that affect ozene concentration better or worse are NO, NO2, NOx and CO.
URI: http://hdl.handle.net/11455/5225
其他識別: U0005-2808200613203500
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2808200613203500


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