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研究生:齊宛儒
研究生(外文):WAN-JU CHI
論文名稱:以訊號分析資料探勘方法探討PM2.5污染傳播時空特徵及相應之天氣條件
論文名稱(外文):Investigation of the main PM2.5 sources and spreading patterns and corresponding meteorological conditions by the wavelet analysis approach
指導教授:林遠見林遠見引用關係
指導教授(外文):Yuan-Chien Lin
學位類別:碩士
校院名稱:國立中央大學
系所名稱:土木工程學系
學門:工程學門
學類:土木工程學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:105
中文關鍵詞:PM2.5污染傳播特徵小波訊號分析天氣條件
外文關鍵詞:PM2.5pollutant spreading patternswavelet transformmeteorological conditions
相關次數:
  • 被引用被引用:1
  • 點閱點閱:179
  • 評分評分:
  • 下載下載:46
  • 收藏至我的研究室書目清單書目收藏:0
由於對人體及環境的危害甚鉅,空氣污染為當今重要的研究議題,尤其是細懸浮微粒(PM2.5)。本研究建立了污染源及傳播特徵萃取流程,以分析台灣中部地區PM2.5複雜的環境系統之物理機制。首先以移動平均結合區域極值建立半自動選取污染事件機制;接著以交叉小波計算延遲時間空間分布(定為傳播情況),透過主成分分析萃取出六個主要傳播特徵;最後,以各傳播特徵之主導事件探討小尺度氣象因子及大尺度天氣系統對於PM2.5傳播特徵之影響。
結果顯示PM2.5濃度日變動呈現雙峰模式—約於上午6:00~9:00及傍晚17:00~20:00左右開始累積,當污染事件發生時,PM2.5累積量約21.35μg/m3,而濃度平均升高時間(開始累積至峰值所需時間)約在8~9小時。第一至六主成分(PC1~6)對中部地區傳播情形解釋力分別為20.43%、14.36%、10.48%、10.10%、9.66%及8.15%,其中PC1為在東北風影響下,污染物由海岸往內陸傳遞的情況,其日均風速(1.6 m/s)與濃度升高百分率(82%)皆為六特徵之首;而污染狀況最嚴重PC5,處在大環境較弱的天氣條件,亦觀察到南風影響,有較高日PM2.5濃度(55.3μg/m3)及較低日風速(1.2m/s),而其他傳播特徵主要受夾雜高壓出海及高壓迴流之天氣場影響,而台中火力發電廠(中火)在PC4~6等較為破碎的傳播特徵發生時,台中市區較高機會出現較差的日空氣品質,有較PC1~3高的PM污染。總結而言,本研究提供創新研究流程用以探討環境相關議題,並替污染排放政策提供科學依據。
Due to its adverse impact on the human body and environment, air pollution has been an important issue of study, particularly for fine particulate matter (PM2.5). We propose a novel sources and patterns detection technique to analyze the complex physical mechanisms of PM2.5 in central Taiwan. The procedure started with the auto-selecting events mechanism composed of moving average and local extrema calculations, followed by spreading pattern extraction, which combined the lag-time spatial distribution calculation results (spreading situation namely) from wavelet coherence with principal component analysis to yield the six main spreading patterns. Finally, representative events were analyzed to discuss the influence of meteorological conditions and weather systems on the PM2.5 spreading patterns.
The results showed that the general daily PM2.5 concentration variation displayed a bimodal pattern. Among the high PM2.5 events, the cumulative amount was ~21.35 μg/m3, and the average rise time was ~8–9 h. Principal Component 1 (PC1) shows the pattern from the coast to inland under the influence of the northeast wind with the highest daily average wind speed (1.6 m/s) and concentration increase percentage (82%); the most serious pollution situation happened in PC5, which is under the influence of weak synoptic, with the highest daily PM2.5 concentration (55.3 μg/m3) and minimum wind speed (1.2 m/s). PM2.5 events with other spreading patterns (PC2––6) were more likely under the influence of the continental high-pressure peripheral circulation and high-pressure reflux. In addition, the Taichung Power Plant had a higher chance of worsening the air quality in the Taichung urban area when PC4––6 occurred. Overall, the study provides a novel procedure to study environmental problems and a scientific basis for emission control strategies.
摘要 i
Abstract ii
誌謝 iii
圖目錄 vi
表目錄 ix
第一章 緒論 1
1.1. 研究背景 1
1.2. 研究動機及目的 2
1.3. 論文架構 3
第二章 文獻回顧 4
2.1. 國內空氣污染標準及相關健康危害 4
2.2. 天氣條件與空氣污染之關聯 5
2.2.1. 天氣及氣象條件對PM2.5之影響 6
2.2.2. 大氣擴散條件 8
2.3. 台灣地區空氣品質時空特徵 11
2.3.1. 空污季節之空氣品質週期 11
2.3.2. PM2.5濃度日變化 14
2.4. 研究區域空氣污染狀況 16
2.5. 訊號分析於空氣污染之應用 17
第三章 研究方法 20
3.1. 研究架構 20
3.2. 資料蒐集及描述 22
3.2.1. 環保署資料(EPA) 24
3.2.2. 氣象局資料(CWB) 27
3.2.3. NCEP再分析資料 32
3.2.4. 資料前處理步驟 34
3.3. 污染源及傳播特徵萃取流程 35
3.3.1. 半自動選取污染事件技術 35
3.3.2. 污染物傳播特徵萃取技術 37
3.4. 天氣因子分析 45
3.4.1. 混合層高度及大氣穩定度 45
3.4.2. 大尺度氣壓場及風場 49
第四章 結果與討論 50
4.1. PM2.5污染事件特性分析 50
4.2. 污染傳播特徵與大尺度天氣場探討 51
4.3. 污染傳播特徵與天氣因子探討 55
4.3.1. 混合層高度對空氣品質之影響 57
4.3.2. 大氣穩定度對空氣品質之影響 63
4.4. 污染傳播特徵分析 65
4.5. 污染傳播特徵之潛在污染源探討 69
第五章 結論與建議 70
5.1. 結論 70
5.2. 建議 71
參考文獻 72
附錄一 76
評審意見回覆表 90
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