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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 張尊國 | |
dc.contributor.author | Li-Chi Chiang | en |
dc.contributor.author | 江莉琦 | zh_TW |
dc.date.accessioned | 2021-06-13T08:04:05Z | - |
dc.date.available | 2005-07-28 | |
dc.date.copyright | 2005-07-28 | |
dc.date.issued | 2005 | |
dc.date.submitted | 2005-07-21 | |
dc.identifier.citation | 第六章 參考文獻
1. 台大農化系,「台灣農地土壤環境重金屬背景調查分析」,行政院環保署,1998。 2. 行政院環境保護署,「污染農地灌溉渠道底泥及水質重金屬污染調查計劃成果報告」,2002。 3. 阮建豐,「利用混合模型估計風險值的探討」,政治大學統計學系碩士論文,2000。 4. 李達源、莊愷瑋,「地理統計應用於土壤污染調查與污染區之界定」,第五屆土壤污染防治研討會,第169頁至第198頁,1997。 5. 李唯榮,「WCDMA系統中以EM演算法實現的SIR估測法」,交通大學電信工程學系碩士班論文,2003。 6. 林裕彬、張尊國,「條件模擬小樣區土壤鋅重金屬污染」,中國農業工程學報,第四十五卷,第一期,第24頁至第37頁,1999。 7. 徐貴新,「台灣地區土壤重金屬含量空間特性分析」,台灣大學生物環境系統工程學研究所博士論文,1999。 8. 馬秀雯,「使用音訊與視訊資料融合方法於生物驗證」,成功大學資訊工程學系研究所碩士論文,2004。 9. 張尊國、王允義、林裕彬,「利用地理統計方法鑑識土壤重金屬污染之空間分佈」,第九屆環境規畫與管理研討會,第388頁至第395頁,1996。 10. 張尊國、黃國珍、徐貴新,「土壤重金屬污染特性探討-因子分析」,中國農業工程學報,第四十三卷,第二期,第11頁至第19頁,1997。 11. 莊愷瑋、李達源、陳尊賢,「地理統計預測污染土壤中重金屬的空間分佈 Ι.極端值與變異圖模式的影響」,中國農業化學會誌,第三十四卷,第五期,第560頁至第574頁,1996。 12. 陳尊賢,「台灣地區土壤環境重金屬背景值調查分析」,行政院環保署,EPA-87H104-03-03,1998。 13. 陳冠博,「受污染農地重金屬存在型態與環境因子之相關性研究」,逢甲大學環境工程與科學學研究所碩士論文,2004。 14. 鄭智馨、廖淑華、李達源、謝長富、陳尊賢,「南仁山區土壤性質之空間分佈」,中國農業化學會誌,第三十四卷,第五期,第547頁至第559頁,1996。 15. 鄭森源、萬鑫森,「地理統計學在土壤污染方面之應用」,中國農業化學會誌,第三十二卷,第四期,第406頁至第429頁,1992。 16. 闕蓓德、駱尚廉,「土壤污染評估決策支援系統之敏感度分析」,第九屆環境規畫與管理研討會,第169頁至第176頁,1996。 17. Alloway, W. H., 1968, Advances in agronomy. Vol.20.p.240-243. 18. Arnt, J., Rudnitski, K., Schmidt, B., Speelman, L. and Noboupha-savanh, S., 1997, “Environmental Risk Assessment of Spraying Landfill Leachate on the Guelph Turfgrass Institute (GTI) Site: Focus on Lead and Arsenics,” Earth and Atmosphere Field Camp, pp. 87-411. 19. Bishop, C. M., 1995, Neural Networks for Pattern Recognition, Oxford: Oxford University Press. 20. Breckenridge, R. P. and Crockett, A. B., 1995, “Determination of Background Concentrations of Inorganic in Soils and Sediments at Hazardous Waste Sites,” EPA/540/S-96/500. Washington, DC. 21. Burgess, T.M. and R. Webster, 1980, “Optimal interpolation and isarithmic mapping of soil properties,” Journal of Soil Science, 31, pp.315-331. 22. Burmaster, D. E., and Hull, D. A., 1996, “Using Lognormal Distributions and Lognormal Probability Plots in Probabilistic Risk Assessments,” Human and Ecological Risk Assessment, Vol. 3, pp.235-255. 23. Burmaster, D. E., and Thompson, K. M., 1997, “Fitting Second-Order Parametric Distributions to Data Using Maximum Likelihood Estimation,” Human and Ecological Risk Assessment, Vol. 4, pp.319-339. 24. Cameron, S. and J. Heckman, 1998, “Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males,” Journal of Political Economy, Vol. 106, pp. 262-333. 25. Cameron, S. and J. Heckman, 2001, “The Dynamics of Educational Attainment for Black, Hispanic, and White Males,” Journal of Political Economy, Vol.109, pp. 455-499. 26. Davies, B.E., 1992, “Trace Metals in the Environment: Retrospect and Prospect,” Biogeochemistry of Trace Metals, pp. 1-18. (Adriano, D.C., Ed.). Boca Raton, FL, CRC Press. 27. Davies, B.E., 1997, “Heavy Metal Contaminated Soil in an Old Industrial Area of Walse, Great Britain: Source Identification through statistical Data Interpretation”. Soil. Sci. Am. J.61. 28. DeBusk, W.F.﹐K.R. Reddy﹐M.S. Koch and Y. Wang﹐1994, “Spatial Distribution of Soil Nutrients in a Northern Everglades Marsh Water Conservation Area 2A”. Soil Sci. Soc. Am. J. 58, pp.543-552. 29. Eckstein, Z. and K. Wolpin, 1999, “Why Youth Drop Out of High School: The Impact of Preferences, Opportunities and Abilities,” Econometrica, Vol. 67, pp. 1295-1339. 30. Everitt, B. S., and Hand, D. J., 1981, “Finite Mixture Distributions,” Chapman & Hall. 31. Folkes, D. J., and Kuehster, T. E., 2001, “Contributions of Pesticide use to Urban Background Concentrations of Arsenic in Denver, Colorado, U.S.A.” Environmental Forensics 2, pp. 127-139. 32. Fowlkes, E. B., 1979, “Some Methods for Studying the Mixture of Two Normal (Lognormal) Distributions,” Journal of the American Statistical Association, Vol. 74, No. 367, pp. 561-575. 33. Gotway, C.A., R.B. Ferguson, G.W. Herget and T.A. Petetson, 1996, “Comparison of Kriging and Inverse-Distance Methods for Mapping of Soil Parameters”. Soil Sci. Soc. Am. J., 60, pp.1237-1247. 34. Gotway, C.A. and G.W. Herget, 1997, “Incorporating Spatial Trends and Anistotropy in Geostatistical Mapping of Soil Properties,” Soil Sci. Soc. Am. J., 61, pp.298-309. 35. Hamilton, J. D., 1989, “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle,” Econometrica, Vol. 57, pp. 357-385. 36. Heckman, J. and B. Singer, 1984, “A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data,” Econometrica, Vol. 52, pp. 271-320. 37. Hunt, A., D.L. Johnson, I. Thornton and J.M. Watt, 1993, “Apportioning the sources of lead in housedusts in the London Borough of Richmond, England,” The Science of the Total Environment, Vol. 138, pp.183-206. 38. Jeffrey L. Smith et al., 1993, “Using Multiple-Variable Indicator Kriging for Evaluating Soil Quality”. Soil Sci. Soc. Am. J. 57, pp.43-749. 39. Journel, A.G., 1988, “Nonparametric geostatistics for risk and additional sampling assessment”, In L. Keith (ed.) Principles of environmental sampling, American Chemical Society, pp.45-72. 40. Juang, K.W. and D.Y. Lee, 1998a, “Simple Indicator Kriging for Estimating the Probability of Incorrectly Delineating Hazardous Areas in a Contaminated Site,” Environmental Science & Technology, Vol. 32, NO. 17, pp.2487-2493. 41. Juang, K.W. and D.Y. Lee, 1998b, “A Comparison of Three Kriging Methods Using Auxiliary Variables in Heavy-Metal Contaminated Soils,” Journal of Environmental Quality, Vol. 27, NO. 2, pp.355-363. 42. Keane, M. and K. Wolpin, 1997, “The Career Decisions of Young Men,” Journal of Political Economy, Vol. 105, pp. 473-522. 43. Laird, N., 1978, “Nonparametric Maximum Likelihood Estimation of a Mixing Distribution,” Journal of the American Statistical Association, Vol. 73, pp. 805-811. 44. Lena, Q., Ma, C. G., Hoogeweg, and Harris, W. G., 2001, “Arsenic Background Concentrations in Florida, U.S.A. Surface Soils: Determination and Interpretation,” Environmental Forensics 2, pp.117-126. 45. Lindsey. B., 1983, “The Geometry of Mixture Likelihoods: A General Theory,” Annals of Statistics, Vol. 11, pp. 86-94. 46. Mcdonald, P., 1998, “Fitting Mixture Distributions, Software and Applications,” Hamilton, Ontario, Canada, http://icarus.math.mcmaster.ca/peter/mix/mix.html. 47. McLachlan, G. J., and Peel, D., 2000, Finite Mixture Models. Wiley, New York. 48. Moen, J. E. T., J. P. Cornet, and C. W. A. Evers, 1986, “Soil Protection and Remedial Actions: Criteria for Decision Making and Standardisation of Requirements,” Contaminated Soils, Vol.90, pp. 441-448. 49. Mroz, T. A., 1999, “Discrete Factor Approximations in Simultaneous Equation Models: Estimating the Impact of a Dummy Endogenous Variable on a Continuous Outcome,” Journal of Econometrics, Vol. 92, pp. 233-274. 50. NJDEP (New Jersey Department of Environmental Protection), 1998, “Revised Guidance Document for the Remediation of Contaminated Soils,” Trenton, NJ. 51. O'Neill, P., 1990, “Arsenic,” Heavy Metals in Soils, pp. 83-99. (Alloway, B.J., Ed.) New York, John Wiley & Sons. 52. Pearson, K., 1894, “Contributions to the mathematical theory of evolution,” Phil. Trans. Royal. Soc., 185A, pp. 71-110. 53. Pierzynski, G. M., Sims, J. T., and Vance, G. F., 2000, Soils and Environmental Quality. 54. Portier, K. M., 2001, “Statistical Issues in Assessing Anthropogenic Background for Arsenic,” Environmental Forensics 2, pp.155-160. 55. Priebe, C.1994, 'Adaptive Mixtures,' Journal of the American Statistical Association, Vol.89, pp.796–806. 56. Redner, R. A., and Walker, H. F., 1984, “Mixture Densities, Maximum Likelihood and the EM Algorithm,” Society for Industrial and Applied Mathematics, Vol.26, No.2, pp.195-239. 57. Robertson. C. A. and J. G. Fryer, 1970, “The Bias and Accuracy of Moment Estimators,” Biometrika, Vol. 57, Part 1, pp. 57-65. 58. Roeder, K., 1994, “A Graphical Technique for Determining the Number of Components in a Mixture of Normals,” Journal of the American Statistical Association, Vol. 89, No. 426, pp. 487-495. 59. Sansom, J., and Thomson, P. J., 1998, “Detecting Components in Censored and Truncated Meteorological Data,” Environmetrics, Vol. 9, pp.673-688. 60. Tait C., Ma, L. Q., and Hornsby, A. G., 2001, “Protocol Development for Assessing Arsenic Background Concentrations in Florida Urban Soils,” Environmental Forensics 2, pp.141-153. 61. Tan, W. Y. and Chang, W.C., 1972, “Convolution approach to genetic analysis of quantitative characters of self-fertilized population,” Biometrics, Vol. 28, pp. 1073-1090. 62. Titterington, D.M., Smith, A.F.M., and Makov, U.E., 1985, “Statistical Analysis of Finite Mixture Distributions,” John Wiley & Sons, New York. 63. Tonner-Navarro, L., Halmes, N.C. and Roberts, S.M., 1998, Development of Soil Cleanup Target Levels (SCTLs) for Chapter 62-785, Gainesville, FL, F.A.C. 64. USEPA, 1992, “Supplemental Guidance to RAGS: Calculating the Concentration Term,” Publication 9285.7-08I, Office of Solid Waste and Emergency Response, Washington, DC. 65. USEPA, 1997, “Data Quality Evaluation Statistical Toolbox (DataQUEST) User’s Guide and Software,” EPA QA/G-9D. EPA-600-R-96-085. December. Available at http//www.epa.gov/QUALITY/dqa.html. 66. USEPA, 1998, “Integratedrisk Information System (IRIS): Arsenic, Inorganic,” CASRN 7440-38-2. Cincinnati, OH. 67. USEPA, 2000, “Guidance for Data Quality Assessment: Practical Methods for Data Analysis,” EPA QA/G-9, QA00 Version. Quality Assurance Management Staff, Washington, DC, EPA 600-R-96-084. July. Available at http//www.epa.gov/QUALITY/dqa.html. 68. USEPA, 2002, “Guidance for Comparing Background and Chemical Concentrations in Soil for CERCLA Sites,” EPA 540-R-01-003, OSWER 9285.7-41. September. 69. Warrick, A.W., D.E. Myers and D.R. Nielsen, 1986, “Geostatistical Methods Applied to Soil Science”, in A. Klute(ed.) Methods of Soil analysis, part1, pp.53-80. 70. Whyoming Department of Environmental Quality (DEQ), 2000, “Establishing Site-Specific Background Metals Concentrations in Soil,” Fact Sheet #24. 71. Yang, S. Y., and Chang, W. L., 2005, 'Use of Finite Mixture Distribution Theory to Determine the criteria of Cadmium Concentrations in Taiwan Farmland Soils,' Soil Science, Vol. 170(1), pp.55-62. 72. Yost, R.S., G. Uehara and R.L. Fox, 1982,“Geostatistics analysis of soil chemical properties or large land area. II. Kriging”. Soil Sci. Am. J. 46, pp.1033-1037. 73. Zhang, X. P., Deng, W., and Yang, X. M., 2002, “The background concentrations of 13 soils trace elements and their relationships to parent materials and vegetation in Xizang (Tibet), China,” Journal of Asian Earth Sciences 21, pp.167-174. 74. Zillioux, E. J., 2001, “Arsenic Background Definition: Introduction and Objectives,” Environmental Forensics 2, pp.115-116. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/36523 | - |
dc.description.abstract | 有限混合分佈理論模式(finite mixture model)在各種土壤重金屬調查結果之分類上,可達到許多目的,本研究探討五個方向之應用:
一、 以全省大樣區砷、銅金屬資料,比較Graphical Method、有母數統計 評估方法與有限混合分佈理論所得到的背景濃度值,並與環保機關 所訂定之標準進行比較,結果顯示後兩者方法較適合用來界定台灣 地區土壤重金屬背景濃度範圍。 二、 結合一般克利金法,將彰化和美地區受重金屬鉻、銅、鎳、鋅污染 的農地之調查結果,以有限混合分佈理論,依據最小誤判機率,將 推估監測區客觀劃分為兩區,其中的「高度重點監測區」代表具有 與管制區相同的污染特性,需特別加強監測。 三、 以有限混合分佈理論得到的區分值與法定管制標準作為門檻值,並結合指標克利金法,可劃分出與「污染區」具有相同特性的「可能污染潛勢區」,結果顯示Cr金屬之「可能污染潛勢區」面積為原污染區之2.24倍,Cu金屬為1.85倍,必須加強監控,較為完備。 四、 探討彰化地區受污染農地與溝渠底泥的關係,測量農地進水口與農地採樣點的距離,建立重金屬濃度與進水口距離的關係式,並以有限混合分佈理論,區分污染農地受到底泥和廢水影響的可能比例,可有效提高管理效率。 五、 以有限混合理論模式可分析彰化地區由不同實驗室所做出的樣本,有著明顯的系統性誤差存在,可提供作為數據檢核之工具。 關鍵詞:有限混合分佈理論、重金屬、土壤污染。 | zh_TW |
dc.description.abstract | By using the Finite Mixture Model to analyze the soil heavy metal survey data, many useful conclusions can be draw. In this study, five application cases were discussed:
1. When using the Taiwan’s large-scale As and Cu survey data, as compare the background concentrations defined by the Graphical Method, the Parametric Estimating Techniques and the Finite Mixture Model, it shows that the later two methods can properly define the range of soil heavy metal background concentration of Taiwan. 2. Combined with Ordinary Kriging and based on the investigation data of Chang-Hua polluted area, use the Finite Mixture Model to separate the estimated monitoring area. One of the parts is called the “High Monitoring Area”, which has the same characteristics of “Control Area” and needs to be monitored continuously. 3. By combined with Indicator Kringing, and using the cut-off point determined by the Finite Mixture Method and the Control Standard as the thresholds, we can separate the “Potential Pollution Area” which has the same characteristics of the “Control Area”. It shows that the “Potential Pollution Area” of Cr is 2.24 times as large as original control area, and Cu is 1.85 times. 4. To decide the pollution sources from sediments or wastewater drainages, by measuring the distances between the water inlet of the farmland and the soil concentration in the farmland, we can establish the relation formula of heavy metal concentrations and distances to the water inlet. These results can be used as reference to manage the farmland in the future. 5. By using the Finite Mixture Model, we can check the systemic error between the two data analyses by different laboratories in Chang-Hua area. It can be a useful tool for data quality control. Keywords: Finite Mixture Model, heavy metal, soil pollution. | en |
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dc.description.tableofcontents | 目錄 頁次
謝誌 中文摘要 英文摘要 目錄 表目錄...............................................................................................................Ⅰ 圖目錄...............................................................................................................Ⅳ 第一章 緒論........................................................................................................1 1-1 研究動機..............................................................................................1 1-2 研究目的..............................................................................................2 1-3 研究流程..............................................................................................3 第二章 文獻回顧................................................................................................5 2-1 重金屬在土壤中之行為與存在型態..................................................5 2-2 農地土壤重金屬調查概述..................................................................7 2-3 國內外重金屬整治標準比較............................................................11 2-4 地理統計............................................................................................16 2-5 有限混合分佈理論............................................................................19 第三章 研究方法..............................................................................................23 3-1 地理統計法........................................................................................23 3-1-1 一般克利金法.............................................................................23 3-1-2 指標克利金法.............................................................................24 3-2 有限混合分佈理論............................................................................27 3-2-1 有限混合分佈的分群意義.........................................................29 3-2-2 最大概似法與EM演算法.........................................................32 3-2-3 卡方適合度檢定.........................................................................37 3-2-4 誤判機率與區分值.....................................................................40 第四章 實例研究…………………………………………………………….44 4-1以有限混合分佈理論探討土壤重金屬背景值.................................44 4-1-1 研究方法與材料.........................................................................48 4-1-2 結果與討論.................................................................................54 4-1-3 結論.............................................................................................58 4-2運用有限混合分佈理論評估土壤污染監測策略.............................60 4-2-1 研究步驟與材料.........................................................................60 4-2-2 結果與討論.................................................................................62 4-2-3 結論.............................................................................................77 4-3 運用有限混合分佈理論於土壤污染潛勢分析................................78 4-3-1 研究步驟與材料.........................................................................78 4-3-2 結果與討論.................................................................................80 4-3-3 結論.............................................................................................91 4-4 灌溉渠道底泥與受污染農地間關係之探討....................................92 4-4-1 研究步驟與材料.........................................................................98 4-4-2 結果與討論...............................................................................100 4-4-3 結論...........................................................................................127 4-5 以有限混合分佈理論判別彰化地區農地鉛金屬調查空間 分佈之系統性誤差………………………………………………...128 4-5-1 研究步驟與材料.......................................................................129 4-5-2 結果與討論...............................................................................130 4-5-3 結論...........................................................................................141 第五章 結論與建議.......................................................................................142 第六章 參考文獻...........................................................................................144 | |
dc.language.iso | zh-TW | |
dc.title | 有限混合分佈理論運用於台灣農地重金屬污染特性之分群 | zh_TW |
dc.title | Use of Finite Mixture Model to Classify Farmland Heavy Metal Pollution Characteristics in Taiwan | en |
dc.type | Thesis | |
dc.date.schoolyear | 93-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 張文亮,陳尊賢,李達源,林裕彬 | |
dc.subject.keyword | 有限混合分佈理論,重金屬,土壤污染, | zh_TW |
dc.subject.keyword | Finite Mixture Model,heavy metal,soil pollution, | en |
dc.relation.page | 152 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2005-07-21 | |
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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