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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 譚義績(Yih-Chi Tan) | |
dc.contributor.author | An-Tzu Chang | en |
dc.contributor.author | 張恩慈 | zh_TW |
dc.date.accessioned | 2021-06-15T04:07:54Z | - |
dc.date.available | 2015-02-11 | |
dc.date.copyright | 2010-02-11 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-02-05 | |
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Atmospheric Environment, 42:4047–4062, 2008a. 33. Yu, H-L, A. Kolovos, G. Christakos, J-C Chen, S. Warmerdam and B. Dev, 2007. “Interactive Spatiotemporal Modelling of Health Systems: The SEKS-GUI Framework”, Stochastic Environmental Research & Risk Assessment Special Volume on Medical Geography as a Science of Interdisciplinary Knowledge Synthesis under Conditions of Uncertainty, 21(5), 555-572. 34. 林尚德,2003,以反應空間不穩定性為基礎之土地估價模型之建立,台南:國立成功大學都市計畫研究所碩士論文。 35. 王誌鑫、林翊婷、余化龍,2008,「不同時間尺度下降水量推估精確性探討」,《農業工程學報》。 36. 林炎欣、林漢良,2008,房價特徵價格模型之空間自我相關問題分析,台南:國立成功大學都市計畫研究所碩士論文。 37. 張齡方、古建廷、林俊男,2006,「以地理加權迴歸分析建立灌溉率與各影響因子之關係」,農業工程學報,第五十二卷,第二期,73-82。 38. 陳佩伶、徐慈鴻、李貽華。2001。「粒狀污染物與農作物」。藥毒所專題報導 62期。 39. 溫在弘、謝欣怡、潘麒帆、蘇明道,(2005),「應用地理加權迴歸分析區域製造業用水之地理空間差異」,2004年台灣地理資訊學會年會暨學術研討會論文集。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/45184 | - |
dc.description.abstract | 火災為嚴重迫害生態環境與人體健康的主要原因,近年來由於全球暖化的因素,森林大火發生頻率不斷增加,在美國西岸加州又有聖安納焚風的助燃下,導致每年都會有森林大火的發生,本研究目的為使用PM2.5與PM10比值關係及氣象變數與PM2.5迴歸關係推估火災前後時PM2.5濃度變化情形,比較火災造成空氣污染之嚴重性。
本研究採用貝氏最大熵法及地理加權迴歸分析。貝氏最大熵法不僅可考慮確定性資料(實際觀測值),同時還可以加入不確定資料(比值關係或迴歸關係下產生之資料)增加推估的準確性,而地理加權迴歸分析改善了一般線性迴歸所忽略的空間變化,於模型建置時納入空間的概念,並解決自相關的問題。 火災時的驗證中,可發現同時加入比值關係與氣象關係下產生之不確定性資料驗證誤差為8.35μg/m3,無火災時誤差更降低至4.81μg/m3。於火災下 =0.27,無火災時 提升到0.71。 在PM2.5時空推估圖中,可以發現濃度較高的發生區域為San Diego及Los Angles區域,小時濃度最高超過300μg/m3。於無火災時濃度大部分區域都下降,不過部份區域PM2.5尚未消散,因此濃度還是高於一般標準,約為60~80μg/m3間。 貝氏最大熵法利用加入不確定性資料的概念確實改善了推估的準確性。但由於本研究事件並非常態性,若此概念應用於常態性研究或是任何其他領域的研究,並能使得推估更加完整且精確。 | zh_TW |
dc.description.abstract | A wildfire is one of issues to seriously damage the ecological environment and human health. Due to the impact of global warming and the foehn at Santa Ana, the frequency of wildfire occurrences is increasing in recent years. This study used PM2.5/PM10 ratios and meteorological variables to estimate the PM2.5 spatiotemporal distribution before and after the fire, in order to compare the quality caused by the wildfire at south California during Oct.21 ~Oct.29,2007.
In this study, Bayesian maximum entropy method and geographical weighted regression are used. Bayesian maximum entropy method can account for both certain and uncertain information to improve the accuracy of estimation. The Geographically Weighted Regression model is applied to modify the traditional regression model, which cannot capture spatial variations, and to solve the spatial non-stationary. The results show that the relative error and the r-square during the period of the wildfire are 8.35μg/m3 and 0.27, respectively. The low r-square can result from the extreme events of PM2.5 during the period. The spatial distribution maps show that the higher concentration of PM2.5 occurred in San Diego and Los Angles, which is accord with the smoke shown in the satellite images. The study applied BME method to assimilate the empirical relationship of PM2.5 derived by GWR and uncertain information. More information is required to account for the extreme events caused by the fires. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T04:07:54Z (GMT). No. of bitstreams: 1 ntu-99-R95622036-1.pdf: 3458429 bytes, checksum: d31335eb254c2aa361851b5e6cbe5bf9 (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | 口試委員會審定書
誌謝 I 摘要 II Abstract III 目錄 IV 圖目錄 VI 表目錄 IV 第一章 緒論 1 1.1 研究緣起 1 1.2 研究目的 2 1.3 研究步驟 3 1.4 本文架構 5 第二章 文獻回顧 6 2.1 PM2.5之危害 6 2.2 火災中空氣品質之變化與影響 8 2.3 地理加權迴歸相關研究 9 2.4 相關變數的選擇 10 第三章 研究方法與材料 12 3.1 研究區域概述 23 3.2 資料收集 13 3.2.1 PM資料 14 3.2.2 氣象資料 18 3.2.3 遙測衛星資料 19 3.3 資料轉換處理 20 3.4 貝氏最大熵法 22 3.5 地理加權迴歸分析 28 第四章 結果與討論 32 4.1 火災時推估結果 32 4.1.1 交叉驗證結果 32 4.1.2 地理加權迴歸分析結果 36 4.1.3 共變異圖 39 4.1.4 PM2.5時空推估圖 40 4.2 無火災時推估結果 50 4.2.1 交叉驗證結果 50 4.2.2 地理加權迴歸分析結果 53 4.2.3 共變異圖 56 4.2.4 PM2.5時空推估圖 56 4.3 討論 62 第五章 結論與建議 64 5.1 結論 64 5.2 建議 65 參考文獻 66 附錄 72 | |
dc.language.iso | zh-TW | |
dc.title | 細懸浮微粒於2007年南加州森林大火之時空變異分析 | zh_TW |
dc.title | Spatiotemporal Analysis of PM2.5 from Wildfires in South California,2007 | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-1 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 余化龍(Hwa-Lung Yu) | |
dc.contributor.oralexamcommittee | 陳主惠(Chu-Hui Chen),熊光華 | |
dc.subject.keyword | 細懸浮微粒,火災,貝氏最大熵法,地理加權迴歸分析, | zh_TW |
dc.subject.keyword | PM2.5,wildfire,BME,GWR, | en |
dc.relation.page | 74 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-02-05 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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