請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/5704
標題: 受體模式PMF解析中部地區揚塵來源之共線性
Using PMF as a Receptor Model to Resolve Dust Sources in Central Taiwan
作者: 蔡宏杰
Tsai, Hung-Chieh
關鍵字: 受體模式
PMF
揚塵
Dust
出版社: 環境工程學系所
引用: Alastuey A., Sánchez-de-la-Campa A., Querol X., Rosa J. d. l., Plana F., and Mantilla E. et al., “Identification and chemical characterization of industrial PM sources in SW Spain.,” Journal of the Air and Waste Management Association, Vol. 56, pp. 993–1006 (2006). Amato F., Pandolfi M., Escrig A., Querol X., Alastuey A., Pey J., Perez N., and Hopke P.K., “Quantifying road dust resuspension in urban environment by Multilinear Engine : A comparison with PMF2.,” Atmospheric Environment, Vol. 43, No. 17, pp. 2770-2780 (2009). Andersen Z. J., Wåhlin P., Raaschou-Nielsen O., Scheike T., and Loft S., “Ambient particle source apportionment and daily hospital admissions among children and elderly in Copenhagen.,” Journal of Exposure Science and Environmental Epidemiology, pp. 1–12 (2007). Anttila P., Paatero P., Tapper U., and Jarvinen O., “Source Identification of Bulk Wet Deposition in Finland by Positive Matrix Factorization.,” Atmospheric Environment, Vol. 29, pp. 1705-1718 (1995). Chan Y.C., Simpson R.W., Mctainsh G.H., Vowles P.D., Cohen D.D., Bailey G.M., “Source apportionment of PM2.5 and PM10 aerosols in Brisbane (Australia) by receptor modeling.,” Atmospheric Environment, Vol. 33, pp. 3251-3268 (1999). Chow J.C., Liu C.S., Cassmassi J., Watson J.G., Lu Z., and Prichett L.C., “A Neighborhood-Scale Study of PM10 Source Contirbutions in Rubidoux, California.,” Atmospheric Environment, Vol. 26, pp. 693-706 (1992). Chueinta W., Hopke P.K., and Paatero P., “Investigation of Sources of Atmospheric Aerosol at Urban and Suburban Residential Areas of Thailand by Positive Matrix Factorization.,” Atmospheric Environment, Vol. 34, pp. 3319-3329 (2000). Currie L.A., Gerlach R.W., Lewis C.W., Balfour W.D., Cooper J.A., Dattner S.L., Cesar R.T.D., Gordon G.E., Heisler S.L., Hopke P.K., Shah J.J., Thurston G.D., and Williamson H.J., “Interlaboratory comparison of source apportionment procedures: Results for Simulated Data Sets.,” Atmospheric Environment, Vol. 18, pp. 1517-1537 (1984). Dzubay T.G., and Mamane Y., “Use of electron Microscopy Data in receptor Models For PM10.,” Atmospheric Environment, Vol. 23, pp. 467-476 (1989). Fung Y.S., and Wong L.W.Y., “Apportionment of air pollution sources by receptor models in Hong Kong.,” Atmospheric Environment, Vol. 29, pp. 2041-2048 (1995). Ghan S.J., MacCracben M.C., and Walton J.J., “Climatic response to large atmospheric “smoke” injections : Sensitivity studies with a tropospheric general circulation model.,” J.Geophys. Res., 93:8315-8337(1988). Groblicki P.J., Wolff G.T., and Countess R.J., “Visibility-reducing species in the Denver “brown cloud” —I. Relationship between extinction and chemical composition.,” Atmospheric Environment, Vol. 15, pp. 2473-2484 (1981). Harrison R.M., Smith D.J.T., and Luhana L., “Source apportionment of atmospheric polycyclic aromatic hydrocarbons collected from an urban location in Birmingham.,” U.K. Environmental Science and Technology, Vol. 30, pp. 825-832 (1996). Harrison R.M., Tilling R., Callen Romero M.S., Harrad S., and Jarvis K., “A study of trace metals and polycyclic aromatic hydrocarbons in the roadside environment.,” Atmospheric Environment Vol. 37, pp. 2391-2402 (2003). Hedberg E., Gidhagen L., and Johansson C., “Source contribution to PM10 and arsenic concentrations in Central Chile using positive matrix factorization.,” Atmospheric Environment, Vol. 39, pp. 549-561 (2005). Hien P.D., Bac V.T., and Thinh N.T.H., “Investigation of sulfate and nitrate formation on mineral dust particles by receptor modeling.,” Atmospheric Environment, Vol. 39, pp. 7231-7239 (2005). Hinds W.C., Aerosol Technology: Properties, behavior, and measurement of airborne particles, 2nd ed., John Wiley & Sons, Inc...(1997) Hosiokangas J., Ruuskanen J. and Pekkanen J., “Effects of soil dust episodes and mixed fuel sources on source apportionment of PM10 particles in Kuopio, Finland.,” Atmospheric Environment, Vol. 33, pp. 3821-3830 (1999). Ito K., Xue N., and Thurston G., “Spatial Variation of PM2.5 Chemical Species and Source-Apportioned Mass Concentrations in New York City.,” Atmospheric Environment, Vol. 38, pp. 5269-5282 (2004). Karanasiou A.A., Siskos P.A., and Eleftheriadis K., “Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions.,” Atmospheric Environment, Vol. 43, pp.3385-3395 (2009). Kim E., Hopke P.K., and Edgerton E.S. , “Improving Source Identification of Atlanta Aerosol Using Temperature Resolved Carbon Fractions in Positive Matrix Factorization.,” Atmospheric Environment, Vol. 38, pp. 3349-3362. (2004). Kim E., Hopke P.K., and Qin Y., “Estimation of organic carbon blank values and error structures of the speciation trends network data for source apportionment.,” Journal of Air and Waste Management Association, Vol. 55, pp. 1190-1199 (2005). Koistinen K., Edwards R., Mathys P., Ruuskanen J., Künzli N., and Jantunen M., “Sources of fine particulate matter in personal exposures and residential indoor residential outdoor and workplace microenvironments in the Helsinki phase of the EXPOLIS study.,” Vol. 30, pp. 36-46 (2005). Kuo C.Y., Lin C.Y., Chiang W.F., Ko L.C., Wu C.W., and Shang W.L., “Variations of Chemical Compositions in Coarse Aerosols and Fine Aerosols in Two Successive Episodes.,” Environmental Toxicology and Chemistry, Vol. 25 pp. 2059-2066(2006). Kuo C.Y., Wang J.Y., Chang S.H., and Chen M.C., “Study of Metal Concentrations in the Environment Near Diesel Transport Routes.,” Atmospheric Environment, Vol. 43, pp. 3070-3076(2009). Larson C.L., and Hanson R.J., Solving Least-squares Problems, Prentitce-Hall, Englewood Cliffs, NJ (1974). Lee E., Chan C. K., and Paatero P., “Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong.,” Atmospheric Environment, Vol. 33, pp. 3201-3212 (1999). Li Z., Hopke P.K., Husain L., Qureshi S., Dutkiewicz V.A., Schwab J.J., Drewnick F., and Demerjian K.L., “Sources of fine particle composition in New York city.,” Atmospheric Environment, Vol. 38, pp. 6521-6529 (2004). Liu W., Wang Y., Russell A., and Edgerton E. S., “Atmospheric aerosol over two urban-rural pairs in the southeastern United States: Chemical composition and possible sources.,” Atmospheric Environment, Vol. 39, pp. 4453-4470 (2005). Liang J., and Fairley D., “Validation of an efficient non-negative matrix factorization method and its preliminary application in Central California.,” Atmospheric Environment, Vol. 40, pp. 1991-2001 (2005). Loh M.M., Levy J.I., Spengler J.D., Andres Houseman E., and Bennett D.H., “Ranking Cancer Risks of Organic Hazardous Air Pollutants in the United States, ” Environmental Health Perspectives, Vol. 115, pp.1160-1168 (2007) Maenhaut W., Cornille P., Pacyna J.M. and Vitols V., “Trace element composition and origin of the atmospheric aerosol in the Norwegian arctic.,” Atmospheric Environment Vol. 23, pp. 2551-2569 (1989) Malinowski E.R., Factor Analysis in Chemistry , Wiley, New York, 2nd Ed (1991). Metzger K.B., Tolbert P.E., Klein M., Peel J.L., Flanders W.D., Todd K., Mulholland J.A., Ryan P.B., and Frumkin H., “Ambient air pollution and cardiovascular emergency department visits.,” Epedemiology, Vol. 15, pp. 46-56(2004) Miller M.S., Friedlander S.K., and Hidy G.M., “A chemical element balance for the Pasadena Aerosol.,” J. Colloid Interface Sci., Vol. 39, pp. 165-176 (1972). Minguillón M. C., Querol X., Alastuey A., Monfort E., and Miró J. V., “PM sources in a highly industrialised area in the process of implementing PM abatement technology. Quantification and evolution.,” Journal of Environmental Monitoring, Vol. 9, pp.1071–1081 (2007). Morishit M., Keeler G.J., Wagner J.G., and Harkema J.R., “Source identification of ambient PM2.5 during summer inhalation exposure studies in Detroit, MI,.” Atmospheric Environment, Vol. 40, pp. 3823-3834 (2006). Nicolas J., Chiari M., Crespo J., Orellana I.G., Lucarelli F., Nava S., Pastor C., and Yubero E., “Quantification of Saharan and local dust impact in an arid Mediterranean area by the positive matrix factorization (PMF) technique.,” Atmospheric Environment, Vol. 42, pp. 8872-8882 (2008). Paatero P., and Tapper U., “Analysis of Different Models of Factor Analysis as Least Squares Fit Problems.,” Chemometrics Inteligent Laboratory Systems, Vol. 18, pp. 183-194 (1993). Paatero P., and Tapper U., “Positive matrix factorization : a non-negative factor model with optimal utilization of error estimates of data values.,” Environmetrics , Vol. 5, pp. 111-126 (1994). Paatero P., “Least squares formulation of robust nonnegative factor analysis.,” Chemometrics Intelligent Laboratory Systems, Vol. 38, pp. 223-242 (1997). Paatero P., “The multilinear engine –a table –driven least squares program for solving multilinear program, including the n-way parallel factor analysis model.,” Journal of Computational and Graphical Statistics, Vol. 8, pp. 854-888 (1999). Per´e-Trepat E., Kim E., Paatero P., and Hopke P.K., “Source apportionment of time and size resolved ambient particulate matter measured with a rotating DRUM impactor.,” Atmospheric Environment, vol. 41, pp. 5921–5933 (2007). Pio C. A., Nunes T. V., Borrego C. A., and Martins J., “Assessment of air pollution sources in a industrial atmosphere using principalcomponent multilinear regression analysis.,” Science of the Total Environment, Vol. 80, pp. 279–292. (1989) Querol X., Minguillón M. C., Alastuey A., Monfort E., Mantilla E., and Sanz M. J. et al., “Impact of the implementation of PM abatement technology on the ambient air levels of metals in a highly industrialised area.,” Atmospheric Environment, Vol. 41, pp. 1026–1040 (2007). Querol X., Viana M., Alastuey A., Amato F., Moreno T., and Castillo S. et al., “Source origin of trace elements in PM from regional background, urban and industrial sites of Spain.,” Atmospheric Environment, Vol. 41, pp. 7219–7231 (2007). Ramadan Z., Song X-H., and Hopke P. K., “Identification of sources of Phoenix aerosol by positive matrix factorization.,” Atmospheric Environment, Vol. 34, pp. 3319-3329 (2000). Ramadan Z., Song X-H., and Hopke P.K., “Identification of Sources of Phoenix Aerosol by Positive Matrix Factorization.,” J. Air & Waste Man-age. Assoc Vol. 50, pp. 1308-1320 (2000). Reff A., Eberly S.I., and Bhave P.V., “Receptor modeling of ambient particulate matter data using positive matrix factorization: review of existing methods.,” Journal of the Air & Waste Management Association Vol. 57, pp. 146–154 (2007) Rodríguez S., “Sources and processes affecting levels and composition of atmospheric particulate matter in theWesternMediterranean.,” Ph.D. thesis, Universitat Politècnica de Catalunya (2002). Song X-H., Polissar A.V., Hopke P.K., “Source of fine particle composition in the northeastern US.,” Atmospheric Environment, Vol. 35, pp. 5277-5286 (2001). Salvador P., Artinano B., Alonso D.G., Querol X., and Alastuey A., “Identification and Characterisation of Sources of PM10 in Madrid(Spain) by Statistical Methods,” Atmospheric Environment, Vol. 38, pp. 435-447 (2004). Song Y., Zhang Y., Xie S., Zeng L., Zeng M., Salmon L.G., Shao M., and Slanina S., “Source apportionment of PM2.5 in Beijing by positive matrix factorization.,” Atmospheric Environment, Vol. 40, pp. 1526-1537 (2006). U.S.EPA, “Receptor Model Source Composition Library,” Environmental Protection Agency Research Triangle Park, NC., EPA-450/4-85-002 (1984). U.S.EPA, Code of Federal Regulations. Part 50. National primary and secondary ambient air quality standards. Available on the Internet at http://earth1.epa.gov /epacfr40/chap_1.info/subch_C/40P0050.pdf (1998). U.S.EPA, Impact of April 2001 Asian Dust Event on Particulate Matter Concentrations in the United States. National Air Quality And Emissions Tredns Report, Special Studies, http://www.epa.gov /air/ airtrends/ asian-dust4.pdf (2003). U.S.EPA, EPA PMF 1.1 User’s Guide. National Exposure Research Laboratory, Research Triangle Park, NC 27711 (2005). U.S.EPA, EPA PMF 3.0 User’s Guide. National Exposure Research Laboratory, Research Triangle Park, NC 27711 (2008). Vecchi R., Chiari M., D’Alessandro A., Fermo P., Lucarelli F., Mazzei F., Nava S., Piazzalunga A., Prati P., Silvani F., and Valli G., “A mass closure and PMF source apportionment study on the sub-micron sized aerosol fraction at urban site in Italy.,” Atmospheric Environment, Vol. 42, pp. 2240-2253 (2008). Viana M., Kuhlbusch T.A.J., Querol X., et al., “Source apportionment of particulate matter in Europe: a review of methods and results.,” Journal of Aerosol Science, Vol. 39, pp.827–849 (2008) Viana M., Querol X., and Alastuey A., “Chemical characterisation of PM episodes in NE Spain.,” Chemosphere, Vol. 62, pp.947–956 (2006). Viana M., Zabalza J., Querol X., Alastuey A., Santamaría J. M., Gil J. I., et al., “Comparative analysis of PMF and PCA-MLRA results for PM2.5 at an industrial site in Northern Spain.,” In Summit on environmental modelling and software, July 9–12, 2006, Burlington, Vermont,USA (2006). Watson J.G., “Chemical Elemental Balance Receptor Model Methodology for Assessing the Sources of Fine and Total Suspended Particule Matter in Portland, Oregon.,” Doctor of Philosophy Dissertation, Oregon Graduate Center, Beaverton, Oregon (1979). Wang S., and Larson T., “Partial Least Squares Regression—A New Receptor Model.,” The 8th Annual Conference on Air Pollution Control Technology, pp. 145-154 (1991). Wang S., “Generation and Interpretation of Source Apportionment Models of Airborne Particles with Application to Both a Simple and a Moderately Complex Urban Airshed.,” Doctor of Philosophy, University of Washington (1991). Wang C.F., Chiang P.C., Cheng M.T., and Chiang H.L., “Improvement of receptor model use in analytical aspect.,” Atmospheric Environment, Vol. 41, pp. 9146-9185 (2007) Xie Y.L., Hopke P.K.,Paatero P., Barrie L.A., and Li S.M., “Identification of source nature and seasonal variations of Arctic aerosol by the multilinear engine.,” Atmospheric Environment, Vol. 33, pp. 2549-2562 (1999). Yang C.Y., Cheng M.F., Chiu J.F., and Tsai S.S., “Female lung cancer and petrochemical air pollution in Taiwan.,” Archives of Environmental Health, Vol. 54, pp. 180-185 (1999). Zabalza J., Ogulei D., Hopke P. K., Lee J. H., Hwang I., and Querol X. et al., “Concentration and sources of PM10 and its constituents in Alsasua, Spain.,” Water, Air and Soil Pollution, Vol. 174, pp. 385–404 (2006). Zheng M., Salmon L.G., Schauer J.J., Zeng L., Kiang C.S., Zhang Y., and Cass G.R., “Seasonal trends in PM2.5 source contribution in Beijing, China.,” Atmospheric Environment, Vol. 39, pp. 3967-3976 (2005). 邱嘉斌,「台灣中部都會與沿海區域PM2.5及PM2.5 - 10氣膠化學組成及污染源貢獻量之研究」,博士論文,國立中興大學環境工程研究所,台中(2005)。 阮俊凱,「硫酸鹽與硝酸鹽之轉換比率在受體模式中之探討-以大甲和后里作為研究測站」,碩士論文,國立中興大學環境工程研究所,台中 (2005)。 梁志峰,「受體模式CMB與PMF之比較與驗證」,碩士論文,國立中興大學環境工程研究所,台中 (2006)。 王富民,「利用CMB與PMF模式針對不同共線性程度之污染源的分析與比較」,碩士論文,國立中興大學環境工程研究所,台中 (2007)。 孫孟祺,「利用受體模式推估中部空品區受到河川揚塵之影響」,碩士論文,國立中興大學環境工程研究所,台中 (2008)。 林啟文、吳秋芬、高滄志,「濁水溪鄰近地區季風揚塵來源分析」,中華民國環境工程學會第二十三屆空氣污染控制技術研討會,台中市 (2006)。 張時獻、翁瑞宏、郭崇義,「94年度南投縣懸浮污染物暴露與居民健康之調查」,南投縣環境保護局報告 (2006)。 郭崇義、林傳堯、林昭遠、黃隆明、望熙榮,「中部地區河川揚塵對空氣品質影響之調查評估專案工作計畫」,行政院環境保護署報告,EPA-95-FA14-03-A216 (2007)。 郭崇義、林傳堯、林昭遠、黃隆明、望熙榮,「河川揚塵對大氣懸浮微粒影響程度之評估專案工作計畫」,行政院環境保護署報告,EPA-97-FA14-03-A042 (2009)
摘要: 受體模式是以受體點為導向透過周界採樣資料與污染源組成來追溯污染源,常見的受體模式有1.化學質量平衡法CMB (Chemical Mass Balance);2.絕對主成分分析APCA (Absolute Principal Component Analysis); 3.正矩陣因子法PMF (Positive Matrix Factorization)。本研究主要是以受體模式PMF針對共線性的污染源來做探討,此模式是多變量分析中的一種,它利用樣本濃度和其不確定性,藉由加權最小平方法推估污染源。此方法有幾項優點:(1)免去搜集污染源指紋那樣龐大的資料而怕資料不完全無法有效分析。(2)PMF並不會跟傳統CMB模式在解析相似污染源時,發生共線性的問題,導致CMB無法有效判定污染源的特徵。(3)其他多變量分析會有負值產生,PMF加入非負值的限制條件進行求解,能夠較好去判斷分析結果。 本研究主要目的是探討在已知污染源且至少兩個以上相似污染源情況下的結果,利用自製樣本進行模擬並比較污染源指紋及貢獻量的推估。因應實際採樣中人為因素所增添的誤差,故將四條河川樣本的量測誤差項納入考慮,但是要先驗算物種的量測誤差是否會大過於物種的濃度值,驗算過後有發生此情形者,此物種不放到受體模式PMF中運算。
Receptor models use numerical techniques to simulate the physical and chemical processes that affect air pollutants in the atmosphere. There are several receptor models include CMB (Chemical Mass Balance), APCA (Absolute Principal Component Analysis) and PMF (Positive Matrix Factorization). If sources have collinearity, factor analysis is generally applied by PMF (Positive Matrix Factorization). PMF combines concentration and uncertainty to estimate sources. PMF has some advantages: (1) not require so much source profiles. (2) will not have problems caused by high collinear sources. (3) contributions from sources are always positive unlike other multivariate analysis methods. Using PMF resolve at least two or more similar sources. The samples are simulated and compared the sources of contribute and the amount of fingerprints. The additional erro which increase four rivers of measurement error into account. If measurement error is larger than concentration of species that will not be on the PMF model to resolve.
URI: http://hdl.handle.net/11455/5704
其他識別: U0005-2008200916022500
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