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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳章甫 | |
| dc.contributor.author | Yu-Chen Yau | en |
| dc.contributor.author | 姚羽真 | zh_TW |
| dc.date.accessioned | 2021-06-15T11:20:57Z | - |
| dc.date.available | 2021-08-26 | |
| dc.date.copyright | 2016-08-26 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-08-19 | |
| dc.identifier.citation | Amato, F., and Hopke, P. K. (2012). Source apportionment of the ambient PM2.5 across St. Louis using constrained positive matrix factorization. Atmospheric Environment, 46, 329-337. doi: 10.1016/j.atmosenv.2011.09.062
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49253 | - |
| dc.description.abstract | 近年來，與空氣污染相關的議題備受大家關注，暴露到揮發性有機物 (volatile organic compounds, VOCs) 及細懸浮微粒 (fine particulate matter, PM2.5) 所造成的人體負面健康效應也被許多研究證實。為了能夠更精確地瞭解空氣污染物之來源，本研究採用正矩陣因子模式結合多重時間解析度受體模式及限縮受體模式在萬華測站進行全年度的實地探討研究。
本研究收集了四季的資料，在研究期間內收集了92份每日一筆的鐵氟龍濾紙及2208份每小時一筆的揮發性有機物資料。由於採樣設備的問題 (例如:幫浦的損壞)，只收集到68份每日一筆的石英濾紙，損失的24筆的石英資料嘗試以含碳推估值代入。揮發性有機物資料由台灣環保署光化學監測站所下載，鐵氟龍濾紙以能量分散式螢光光譜儀 (Energy Dispersive X-Ray Fluorescence spectrometry, ED-XRF) 分析元素成分及以離子層析儀 (Ion Chromatography, IC) 分析離子成分，石英濾紙則以有機碳/元素碳分析儀分析有機碳及元素碳。 本研究掌握了部分環境意義資料，利用不同的限縮方法將解出的其中兩種污染源調整成與真實環境相符合的情形。另外，也獨立拉出原本存在各個指紋圖譜中的污染源，以了解其干擾程度。經過限縮步驟後，最後所得到的污染源指紋圖譜顯示萬華測站於整年度可能受到的污染源有8種，分別為天然氣洩漏 ( natural gas leakages)、溶劑的使用/工業製程 (solvent use/ industrial process)、受污染的海洋氣膠 (contaminated marine aerosol)、衍生性氣膠/長程傳輸 (secondary aerosol/ long-range transport)、油類燃燒 （oil combiustion）、交通排放源 (vehicular emission)、揮發性汽油排放源 (evaporative gasoline emission) 及土壤塵土逸散源 (soil dust)。 其中，揮發性有機化合物之主要貢獻來源為溶劑的使用/工業製程 (21%)，而細懸浮微粒中最主要的貢獻來源為衍生性氣膠/長程傳輸 (48%)。 本研究掌握了全年度的揮發性有機物及細懸浮微粒資訊，更深入地探討四季間污染源的變化。由解出的八個污染源可以清楚地看到季節間變異，揮發性有機物及細懸浮微粒的整體季節趨勢由高到低依序為: 2014年的冬天、2015年的春天、2014年的秋天及2015年的夏天。我們可以利用這些資訊，瞭解各污染源的好發時期，並提供政府作為污染源管制之成效評估及日後擬定防範措施的參考依據。 | zh_TW |
| dc.description.abstract | Exposure to air pollutants such as volatile organic compounds (VOCs) and fine particulate matter (PM2.5), were found to be associated with acute and chronic adverse health effects, including allergy, respiratory and cardiovascular diseases. The feasibility of combining the multiple time resolution data of VOCs and PM2.5 had been mentioned in published paper for increasing the accuracy of source identification. This was a field study applying multiple time resolution data of hourly VOCs and 24-h PM2.5 with the Positive Matrix Factorization (PMF) model for source apportionment.
The data were collected in four seasons. During the study periods, 92 daily Teflon PM2.5 samples and 2208 hourly VOC measurements were collectd. Due to the issues of equipments (e.g. pump falure), only 68 quartz filter samples were obtained. Others 24 were estimated based on measured species on Teflon filtes. VOCs data were monitored by the Wanhua Photochemical Assessment Monitoring Station (PAMS). Teflon filters were analyzed by Energy Dispersive X-Ray Fluorescence spectrometry (ED-XRF) and Ion Chromatography (IC). Quartz filters were analyzed by Thermal Optical Carbon Analyzer for OC and EC. With some prior information, we used different procedures to constrain two sources toward realistic environment, and add an exsisted source for recognizing the impacts. Finally,eight factors were identified as: natural gas leakage, solvent use/ industrial process, contaminated marine aerosol, secondary aerosol/ long-range transport, oil combustion, vehicular emission, evaporative gasoline emission, and soil dust. The results showed that solvent use/ industrial process was the largest contributor (21%) to VOCs mass concentration, while the largest contributor to PM2.5 mass concentration was secondary aerosol/ long-range transport (48%). The seasonal variations of souce contributions were analyzed in this study. The total concentration of VOCs and PM2.5 from the highest to lowest were: winter 2014, spring 2015, autumn 2014, and summer 2015. The serious emission season of each source was recognized in this study and can be used as references for evaluating control efficiencies and developing prevention strategies. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T11:20:57Z (GMT). No. of bitstreams: 1 ntu-105-R03844010-1.pdf: 5852704 bytes, checksum: f3567a3f940412cbbbd4c5c8b52aa7dd (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | Chapter 1 Introduction 1
Chapter 2 Methods 6 2.1 Introduction of Sampling Site 6 2.2 Data Collection and Chemical Analysis 7 2.3 Mass Closure 10 2.4 Evaluating the Effects of Adding OC and EC Data 11 Chapter 3 Model Descriptions 13 3.1 Receptor Modeling 13 3.2 Quality Assurance and Control of Data 16 3.3 Missing Mass 16 3.4 Determination of Sources Numbers 17 3.5 Profile Interpretation 18 3.6 Model Constraints 19 3.7 Conditional Probability Function 21 Chapter 4 Results and Discussion 22 4.1 Descriptive Analysis 22 4.1.1 Double Counting 22 4.1.2 Collinearity 23 4.2 Base Model Runs 23 4.2.1 Determination of Sources Numbers 24 4.2.2 Source Identification 24 4.2.3 Effects of OC/EC Measurements 28 4.3 Constraint Model Runs 31 4.3.1 Soil Dust 31 4.3.2 Vehicular Emission 33 4.3.3 Natural gas leakage 33 4.4 Evaluations of Constraints 34 4.5 Source Contribution and Seasonal Variation 34 4.6 Effects of Using Multiple Time Resolution Data with VOCs and PM2.5 38 4.7 Study Limitations 40 Chapter 5 Conclusions and Recommendations 41 References 63 Appendix 72 Appendix A: Detailed information of VOCs included in this study 72 Appendix B: Frequency distributions of scaled residuals obtained from ME-2. 73 Appendix C: The 72-h back trajectory of extreme episodes in Factor 4 at Wanhua monitoring site by NOAA HYDPLIT model. 76 Appendix D: Hourly variation of total VOCs (mean±std) in each source at Wanhua monitoring site (Scenario A). 80 Appendix E: Source profiles of Scenario B plotted as mass concentration (gray bar) and explained variation (black circle) of: a) VOCs and b) PM2.5 species at Wanhua monitoring site. 81 Appendix F Deduction of estimating OC and EC 82 Appendix F-1 Results of multiple regressions using Equation (21) for data of Wanhua monitoring site… 84 Appendix F-2 Scatter plots of: a) measured OC and measured EC, b) measured OC and estimated OC, and c) measured EC and estimated EC. 85 Appendix G: Source profiles of Scenario C plotted as mass concentration (gray bar) and explained variation (black circle) of: a) VOCs and b) PM2.5 species at Wanhua monitoring site. 86 Appendix H: Time series plot for normalized concentration of each factor presented by seasons at Wanhua monitoring site. 87 Appendix I: Source profiles of Scenario C_S plotted as mass concentration (gray bar) and explained variation (black circle) of: a) VOCs and b) PM2.5 species at Wanhua monitoring site. 91 Appendix J: Source profiles of Scenario C_SV plotted as mass concentration (gray bar) and explained variation (black circle) of: a) VOCs and b) PM2.5 species at Wanhua monitoring site. 92 Appendix K: Source profiles of Scenario D plotted as mass concentration (gray bar) and explained variation (black circle) of VOCs species at Wanhua monitoring site. 93 | |
| dc.language.iso | en | |
| dc.subject | 空氣污染 | zh_TW |
| dc.subject | 正矩陣因子解析 | zh_TW |
| dc.subject | 污染源解析 | zh_TW |
| dc.subject | 限縮模式 | zh_TW |
| dc.subject | 受體模式 | zh_TW |
| dc.subject | constrain | en |
| dc.subject | PMF | en |
| dc.subject | air pollution | en |
| dc.subject | receptor modeling | en |
| dc.subject | source apportionment | en |
| dc.title | 應用限縮正矩陣因子模式結合多重時間解析度數據推估細懸浮微粒及揮發性有機物之污染來源:實地研究探討 | zh_TW |
| dc.title | Applying a Constrained Positive Matrix Factorization Model with Multiple Time Resolution Data in a Field Study for Source Apportionment of PM2.5 and VOCs | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡詩偉,邱嘉斌(justandine@gmail.com),周崇光 | |
| dc.subject.keyword | 污染源解析,受體模式,正矩陣因子解析,限縮模式,空氣污染, | zh_TW |
| dc.subject.keyword | source apportionment,receptor modeling,PMF,constrain,air pollution, | en |
| dc.relation.page | 93 | |
| dc.identifier.doi | 10.6342/NTU201603341 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2016-08-19 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 環境衛生研究所 | zh_TW |
| 顯示於系所單位： | 環境衛生研究所 | |
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