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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 吳章甫(Chang-Fu Wu) | |
dc.contributor.author | Ching-Chun Chen | en |
dc.contributor.author | 陳景純 | zh_TW |
dc.date.accessioned | 2021-06-15T14:07:35Z | - |
dc.date.available | 2020-09-14 | |
dc.date.copyright | 2015-09-14 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-08-20 | |
dc.identifier.citation | Allen, A. G.,Miguel, A. H., 1995. Biomass burning in the Amazon: Characterization of the ionic component of aerosols generated from flaming and smoldering rainforest and savannah. Environmental science & technology, 29(2), 486-493.
Anderson, M. J., Miller, S. L.,Milford, J. B., 2000. Source apportionment of exposure to toxic volatile organic compounds using positive matrix factorization. Journal of exposure analysis and environmental epidemiology, 11(4), 295-307. Andreae, M., Andreae, T., Annegarn, H., Beer, J., Cachier, H., Le Canut, P., Elbert, W., Maenhaut, W., Salma, I.,Wienhold, F., 1998. Airborne studies of aerosol emissions from savanna fires in southern Africa: 2. Aerosol chemical composition. Journal of Geophysical Research: Atmospheres (1984–2012), 103(D24), 32119-32128. Andreae, M. O., Charlson, R. J., Bruynseels, F., Storms, H., Van Grieken, R.,Maenhaut, W., 1986. Internal mixture of sea salt, silicates, and excess sulfate in marine aerosols. Science, 232(4758), 1620-1623. Anttila, P., Paatero, P., Tapper, U.,Järvinen, O., 1995. Source identification of bulk wet deposition in Finland by positive matrix factorization. Atmospheric Environment, 29(14), 1705-1718. Bisht, D., Dumka, U., Kaskaoutis, D., Pipal, A., Srivastava, A., Soni, V., Attri, S., Sateesh, M.,Tiwari, S., 2015. Carbonaceous aerosols and pollutants over Delhi urban environment: Temporal evolution, source apportionment and radiative forcing. Science of The Total Environment, 521, 431-445. Brinkman, G., Vance, G., Hannigan, M. P.,Milford, J. B., 2006. Use of synthetic data to evaluate positive matrix factorization as a source apportionment tool for PM2. 5 exposure data. Environmental science & technology, 40(6), 1892-1901. Brown, S. G., Eberly, S., Paatero, P.,Norris, G. A., 2015. Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results. Science of The Total Environment, 518, 626-635. Brown, S. G., Frankel, A.,Hafner, H. R., 2007a. Source apportionment of VOCs in the Los Angeles area using positive matrix factorization. Atmospheric Environment, 41(2), 227-237. Brown, S. G., Frankel, A., Raffuse, S. M., Roberts, P. T., Hafner, H. R.,Anderson, D. J., 2007b. Source apportionment of fine particulate matter in Phoenix, AZ, using positive matrix factorization. Journal of the air & waste management association, 57(6), 741-752. Buzcu-Guven, B., Brown, S. G., Frankel, A., Hafner, H. R.,Roberts, P. T., 2007. Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the midwestern United States. Journal of the air & waste management association, 57(5), 606-619. Cao, J., Wu, F., Chow, J., Lee, S., Li, Y., Chen, S., An, Z., Fung, K., Watson, J.,Zhu, C., 2005. Characterization and source apportionment of atmospheric organic and elemental carbon during fall and winter of 2003 in Xi'an, China. Atmospheric Chemistry and Physics, 5(11), 3127-3137. Carvalho, A., Pio, C., Santos, C.,Alves, C., 2006. Particulate carbon in the atmosphere of a Finnish forest and a German anthropogenically influenced grassland. Atmospheric Research, 80(2), 133-150. Chan, Y.-C., Hawas, O., Hawker, D., Vowles, P., Cohen, D. D., Stelcer, E., Simpson, R., Golding, G.,Christensen, E., 2011. Using multiple type composition data and wind data in PMF analysis to apportion and locate sources of air pollutants. Atmospheric Environment, 45(2), 439-449. Chan, Y., Simpson, R., Mctainsh, G. H., Vowles, P. D., Cohen, D.,Bailey, G., 1997. Characterisation of chemical species in PM 2.5 and PM 10 aerosols in Brisbane, Australia. Atmospheric Environment, 31(22), 3773-3785. Chen, W.-N., Chen, Y.-C., Kuo, C.-Y., Chou, C.-H., Cheng, C.-H., Huang, C.-C., Chang, S.-Y., Raman, M. R., Shang, W.-L.,Chuang, T.-Y., 2014. The real-time method of assessing the contribution of individual sources on visibility degradation in Taichung. Science of The Total Environment, 497, 219-228. Cheng, M.-T., Horng, C.-L.,Lin, Y.-C., 2007. Characteristics of atmospheric aerosol and acidic gases from urban and forest sites in central Taiwan. Bulletin of environmental contamination and toxicology, 79(6), 674-677. Chow, J. C., Lowenthal, D. H., Chen, L.-W. A., Wang, X.,Watson, J. G., 2015. Mass reconstruction methods for PM2. 5: a review. Air Quality, Atmosphere & Health, 1-21. Chow, J. C., Watson, J. G., Mauderly, J. L., Costa, D. L., Wyzga, R. E., Vedal, S., Hidy, G. M., Altshuler, S. L., Marrack, D.,Heuss, J. M., 2006. Health effects of fine particulate air pollution: lines that connect. Journal of the air & waste management association, 56(10), 1368-1380. Cusack, M., Pérez, N., Pey, J., Alastuey, A.,Querol, X., 2013. Source apportionment of fine PM and sub-micron particle number concentrations at a regional background site in the western Mediterranean: a 2.5 year study. Atmospheric Chemistry and Physics, 13(10), 5173-5187. Dockery, D. W.,Pope, C. A., 1994. Acute respiratory effects of particulate air pollution. Annual review of public health, 15(1), 107-132. Edney, E., Kleindienst, T., Conver, T., Mciver, C., Corse, E.,Weathers, W., 2003. Polar organic oxygenates in PM 2.5 at a southeastern site in the United States. Atmospheric Environment, 37(28), 3947-3965. Engel-Cox, J. A.,Weber, S. A., 2007. Compilation and assessment of recent positive matrix factorization and UNMIX receptor model studies on fine particulate matter source apportionment for the eastern United States. Journal of the air & waste management association, 57(11), 1307-1316. Fang, G.-C., Wu, Y.-S., Chen, J.-C., Rau, J.-Y., Huang, S.-H.,Lin, C.-K., 2006. Concentrations of ambient air particulates (TSP, PM 2.5 and PM 2.5–10) and ionic species at offshore areas near Taiwan Strait. Journal of Hazardous Materials, 132(2), 269-276. Geron, C., 2009. Carbonaceous aerosol over a Pinus taeda forest in Central North Carolina, USA. Atmospheric Environment, 43(4), 959-969. Gras, J.,Ayers, G., 1983. Marine aerosol at southern mid‐latitudes. Journal of Geophysical Research: Oceans (1978–2012), 88(C15), 10661-10666. Green, M. C., Chen, L. A., Dubois, D. W.,Molenar, J. V., 2012. Fine particulate matter and visibility in the Lake Tahoe Basin: Chemical characterization, trends, and source apportionment. Journal of the air & waste management association, 62(8), 953-965. Gu, L., Wang, C., Wang, X., Wang, Y.,Wang, Q., 2013. Variation characteristics of fine particulate matter PM2. 5 concentration in three urban recreational forests in Hui Mountain of Wuxi City, Jiangsu Province of East China. Ying yong sheng tai xue bao= The journal of applied ecology/Zhongguo sheng tai xue xue hui, Zhongguo ke xue yuan Shenyang ying yong sheng tai yan jiu suo zhu ban, 24(9), 2485-2493. Guo, H., Wang, T., Simpson, I., Blake, D., Yu, X., Kwok, Y.,Li, Y., 2004. Source contributions to ambient VOCs and CO at a rural site in eastern China. Atmospheric Environment, 38(27), 4551-4560. Hai, C. D.,Oanh, N. T. K., 2013. Effects of local, regional meteorology and emission sources on mass and compositions of particulate matter in Hanoi. Atmospheric Environment, 78, 105-112. Han, Y.,Zhu, T., 2015. Health effects of fine particles (PM2. 5) in ambient air. Science China Life Sciences, 1-3. Hasheminassab, S., Daher, N., Ostro, B. D.,Sioutas, C., 2014. Long-term source apportionment of ambient fine particulate matter (PM 2.5) in the Los Angeles Basin: A focus on emissions reduction from vehicular sources. Environmental Pollution, 193, 54-64. Heo, J.-B., Hopke, P.,Yi, S.-M., 2009. Source apportionment of PM 2.5 in Seoul, Korea. Atmospheric Chemistry and Physics, 9(14), 4957-4971. Ho, K., Lee, S., Cao, J., Chow, J. C., Watson, J. G.,Chan, C. K., 2006. Seasonal variations and mass closure analysis of particulate matter in Hong Kong. Science of The Total Environment, 355(1), 276-287. Hock, N., Schneider, J., Borrmann, S., Römpp, A., Moortgat, G., Franze, T., Schauer, C., Pöschl, U., Plass-Dülmer, C.,Berresheim, H., 2008. Rural continental aerosol properties and processes observed during the Hohenpeissenberg Aerosol Characterization Experiment (HAZE2002). Atmospheric Chemistry and Physics, 8(3), 603-623. Hopke, P. K., 2003. Recent developments in receptor modeling. Journal of Chemometrics, 17(5), 255-265. Hsu, N. C., Herman, J. R.,Tsay, S. C., 2003. Radiative impacts from biomass burning in the presence of clouds during boreal spring in southeast Asia. Geophysical Research Letters, 30(5). Huang, S., Arimoto, R.,Rahn, K. A., 2001. Sources and source variations for aerosol at Mace Head, Ireland. Atmospheric Environment, 35(8), 1421-1437. Hwang, I.,Hopke, P. K., 2007. Estimation of source apportionment and potential source locations of PM 2.5 at a west coastal IMPROVE site. Atmospheric Environment, 41(3), 506-518. Ion, A., Vermeylen, R., Kourtchev, I., Cafmeyer, J., Chi, X., Gelencsér, A., Maenhaut, W.,Claeys, M., 2005. Polar organic compounds in rural PM 2.5 aerosols from K-puszta, Hungary, during a 2003 summer field campaign: Sources and diel variations. Atmospheric Chemistry and Physics, 5(7), 1805-1814. John, K., Karnae, S., Crist, K., Kim, M.,Kulkarni, A., 2007. Analysis of trace elements and ions in ambient fine particulate matter at three elementary schools in Ohio. Journal of the air & waste management association, 57(4), 394-406. Juntto, S.,Paatero, P., 1994. Analysis of daily precipitation data by positive matrix factorization. Environmetrics, 5(2), 127-144. Karlsson, R.,Ljungström, E., 1995. Nitrogen dioxide and sea salt particles—a laboratory study. Journal of Aerosol Science, 26(1), 39-50. Karlsson, R.,Ljungström, E., 1998. Formation of nitryl chloride from dinitrogen pentoxide in liquid sea salt aerosol. Atmospheric Environment, 32(10), 1711-1717. Keene, W. C., Sander, R., Pszenny, A. A., Vogt, R., Crutzen, P. J.,Galloway, J. N., 1998. Aerosol pH in the marine boundary layer: A review and model evaluation. Journal of Aerosol Science, 29(3), 339-356. Kim, E., Brown, S. G., Hafner, H. R.,Hopke, P. K., 2005a. Characterization of non-methane volatile organic compounds sources in Houston during 2001 using positive matrix factorization. Atmospheric Environment, 39(32), 5934-5946. Kim, E.,Hopke, P. K., 2006. Characterization of fine particle sources in the Great Smoky Mountains area. Science of The Total Environment, 368(2), 781-794. Kim, E.,Hopke, P. K., 2008. Characterization of ambient fine particles in the northwestern area and Anchorage, Alaska. Journal of the air & waste management association, 58(10), 1328-1340. Kim, E., Hopke, P. K.,Edgerton, E. S., 2003. Source identification of Atlanta aerosol by positive matrix factorization. Journal of the air & waste management association, 53(6), 731-739. Kim, E., Hopke, P. K.,Edgerton, E. S., 2004. Improving source identification of Atlanta aerosol using temperature resolved carbon fractions in positive matrix factorization. Atmospheric Environment, 38(20), 3349-3362. Kim, E., Hopke, P. K.,Qin, Y., 2005b. Estimation of organic carbon blank values and error structures of the speciation trends network data for source apportionment. Journal of the air & waste management association, 55(8), 1190-1199. Kloog, I., Zanobetti, A., Nordio, F., Coull, B., Baccarelli, A.,Schwartz, J., 2015. Effects of airborne fine particles (PM2. 5) on deep vein thrombosis admissions in the northeastern United States. Journal of thrombosis and haemostasis: JTH, 13(5), 768-774. Kourtchev, I., Ruuskanen, T., Maenhaut, W., Kulmala, M.,Claeys, M., 2005. Observation of 2-methyltetrols and related photo-oxidation products of isoprene in boreal forest aerosols from Hyytiälä, Finland. Atmospheric Chemistry and Physics, 5(10), 2761-2770. Kourtchev, I., Warnke, J., Maenhaut, W., Hoffmann, T.,Claeys, M., 2008. Polar organic marker compounds in PM2. 5 aerosol from a mixed forest site in western Germany. Chemosphere, 73(8), 1308-1314. Kuo, C.-P., Liao, H.-T., Chou, C. C.-K.,Wu, C.-F., 2014. Source apportionment of particulate matter and selected volatile organic compounds with multiple time resolution data. Science of The Total Environment, 472, 880-887. Lee, E., Chan, C. K.,Paatero, P., 1999. Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong. Atmospheric Environment, 33(19), 3201-3212. Lee, J. H., Yoshida, Y., Turpin, B. J., Hopke, P. K., Poirot, R. L., Lioy, P. J.,Oxley, J. C., 2002. Identification of sources contributing to mid-Atlantic regional aerosol. Journal of the air & waste management association, 52(10), 1186-1205. Lewandowski, M., Jaoui, M., Kleindienst, T. E., Offenberg, J. H.,Edney, E. O., 2007. Composition of PM 2.5 during the summer of 2003 in Research Triangle Park, North Carolina. Atmospheric Environment, 41(19), 4073-4083. Li, L., Wang, W., Feng, J., Zhang, D., Li, H., Gu, Z., Wang, B., Sheng, G.,Fu, J., 2010. Composition, source, mass closure of PM 2.5 aerosols for four forests in eastern China. Journal of Environmental Sciences, 22(3), 405-412. Liao, H.-T., Kuo, C.-P., Hopke, P. K.,Wu, C.-F., 2013. Evaluation of a modified receptor model for solving multiple time resolution equations: a simulation study. Aerosol Air Qual Res, 13, 1253-1262. Liu, W., Hopke, P. K.,Vancuren, R. A., 2003. Origins of fine aerosol mass in the western United States using positive matrix factorization. Journal of Geophysical Research: Atmospheres (1984–2012), 108(D23). Mészáros, A.,Vissy, K., 1974. Concentration, size distribution and chemical nature of atmospheric aerosol particles in remote oceanic areas. Journal of Aerosol Science, 5(1), 101-109. Maenhaut, W., Raes, N., Chi, X., Cafmeyer, J.,Wang, W., 2008. Chemical composition and mass closure for PM2. 5 and PM10 aerosols at K‐puszta, Hungary, in summer 2006. X‐Ray Spectrometry, 37(2), 193-197. Maykut, N. N., Lewtas, J., Kim, E.,Larson, T. V., 2003. Source apportionment of PM2. 5 at an urban IMPROVE site in Seattle, Washington. Environmental science & technology, 37(22), 5135-5142. Miller, S. L., Anderson, M. J., Daly, E. P.,Milford, J. B., 2002. Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data. Atmospheric Environment, 36(22), 3629-3641. Mo, H., Li, L., Lai, W., Zhao, M., Pu, J., Zhou, Y.,Deng, S., 2015. Characterization of summer PM 2.5 aerosols from four forest areas in Sichuan, SW China. Particuology, 20, 94-103. Mueller, P., Mosley, R.,Pierce, L., 1972. Chemical composition of Pasadena aerosol by particle size and time of day. IV. Carbonate and noncarbonate carbon content. Journal of Colloid and Interface Science, 39(1), 235-239. Ni, T., Li, P., Han, B., Bai, Z., Ding, X., Wang, Q., Huo, J.,Lu, B., 2013. Spatial and temporal variation of chemical composition and mass closure of ambient PM10 in Tianjin, China. Aerosol Air Qual. Res, 13, 1832-1846. Paatero, P., Eberly, S., Brown, S.,Norris, G., 2014. Methods for estimating uncertainty in factor analytic solutions. Atmospheric Measurement Techniques, 7(3), 781-797. Paatero, P.,Hopke, P. K., 2003. Discarding or downweighting high-noise variables in factor analytic models. Analytica Chimica Acta, 490(1), 277-289. Paatero, P.,Tapper, U., 1993. Analysis of different modes of factor analysis as least squares fit problems. Chemometrics and Intelligent Laboratory Systems, 18(2), 183-194. Paatero, P.,Tapper, U., 1994. Positive matrix factorization: A non‐negative factor model with optimal utilization of error estimates of data values. Environmetrics, 5(2), 111-126. Paterson, K. G., Sagady, J. L., Hooper, D. L., Bertman, S. B., Carroll, M. A.,Shepson, P. B., 1999. Analysis of air quality data using positive matrix factorization. Environmental science & technology, 33(4), 635-641. Pey, J., Alastuey, A.,Querol, X., 2013. PM 10 and PM 2.5 sources at an insular location in the western Mediterranean by using source apportionment techniques. Science of The Total Environment, 456, 267-277. Pio, C., Legrand, M., Alves, C., Oliveira, T., Afonso, J., Caseiro, A., Puxbaum, H., Sánchez-Ochoa, A.,Gelencsér, A., 2008. Chemical composition of atmospheric aerosols during the 2003 summer intense forest fire period. Atmospheric Environment, 42(32), 7530-7543. Pui, D. Y., Chen, S.-C.,Zuo, Z., 2014. PM 2.5 in China: Measurements, sources, visibility and health effects, and mitigation. Particuology, 13, 1-26. Reche, C., Moreno, T., Amato, F., Viana, M., Van Drooge, B. L., Chuang, H.-C., Bérubé, K., Jones, T., Alastuey, A.,Querol, X., 2012. A multidisciplinary approach to characterise exposure risk and toxicological effects of PM 10 and PM 2.5 samples in urban environments. Ecotoxicology and environmental safety, 78, 327-335. Reff, A., Eberly, S. I.,Bhave, P. V., 2007. Receptor modeling of ambient particulate matter data using positive matrix factorization: review of existing methods. Journal of the air & waste management association, 57(2), 146-154. Saarikoski, S., Sillanpää, M., Sofiev, M., Timonen, H., Saarnio, K., Teinilä, K., Karppinen, A., Kukkonen, J.,Hillamo, R., 2007. Chemical composition of aerosols during a major biomass burning episode over northern Europe in spring 2006: experimental and modelling assessments. Atmospheric Environment, 41(17), 3577-3589. Samet, J.,Krewski, D., 2007. Health effects associated with exposure to ambient air pollution. Journal of Toxicology and Environmental Health, Part A, 70(3-4), 227-242. Schauer, J. J., Kleeman, M. J., Cass, G. R.,Simoneit, B. R., 2002. Measurement of emissions from air pollution sources. 5. C1-C32 organic compounds from gasoline-powered motor vehicles. Environmental science & technology, 36(6), 1169-1180. Shridhar, V., Khillare, P., Agarwal, T.,Ray, S., 2010. Metallic species in ambient particulate matter at rural and urban location of Delhi. Journal of Hazardous Materials, 175(1), 600-607. Simon, H., Bhave, P., Swall, J., Frank, N.,Malm, W., 2011. Determining the spatial and seasonal variability in OM/OC ratios across the US using multiple regression. Atmospheric Chemistry and Physics, 11(6), 2933-2949. Song, Y., Xie, S., Zhang, Y., Zeng, L., Salmon, L. G.,Zheng, M., 2006. Source apportionment of PM2. 5 in Beijing using principal component analysis/absolute principal component scores and UNMIX. Science of The Total Environment, 372(1), 278-286. Standard operating procedure for the X-ray fluorescence analysis of particulate matter deposits on teflon filters. 2009. Swietlicki, E.,Krejci, R., 1996. Source characterisation of the Central European atmospheric aerosol using multivariate statistical methods. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 109, 519-525. Tanner, R. L., Parkhurst, W. J., Valente, M. L.,Phillips, W. D., 2004. Regional composition of PM 2.5 aerosols measured at urban, rural and “background” sites in the Tennessee valley. Atmospheric Environment, 38(20), 3143-3153. Tao, J., Zhang, L., Ho, K., Zhang, R., Lin, Z., Zhang, Z., Lin, M., Cao, J., Liu, S.,Wang, G., 2014. Impact of PM 2.5 chemical compositions on aerosol light scattering in Guangzhou—the largest megacity in South China. Atmospheric Research, 135, 48-58. U.S. Environmental Protection Agency, 1999. EPA Positive Matrix Factorization (PMF) 3.0 Fundamentals & User Guide. 2008. U.S. Environmental Protection Agency, 1999. EPA Positive Matrix Factorization (PMF) 5.0 Fundamentals and User Guide. 2014. U.S. Environmental Protection Agency, 1999. Method IO-3.3 determination of metals in ambient particulate matter using X-ray fluorescence(XRF) spectroscopy. 1999. Ulbrich, I., Canagaratna, M., Zhang, Q., Worsnop, D.,Jimenez, J., 2009. Interpretation of organic components from Positive Matrix Factorization of aerosol mass spectrometric data. Atmospheric Chemistry and Physics, 9(9), 2891-2918. Viana, M., Querol, X., Alastuey, A., Gil, J.,Menéndez, M., 2006. Identification of PM sources by principal component analysis (PCA) coupled with wind direction data. Chemosphere, 65(11), 2411-2418. Ward, T. J.,Smith, G. C., 2005. The 2000/2001 Missoula Valley PM 2.5 chemical mass balance study, including the 2000 wildfire season—seasonal source apportionment. Atmospheric Environment, 39(4), 709-717. Watson, J. G., 1979. Chemical element balance receptor model methodology for assessing the sources of fine and total suspended particulate matter in Portland, Oregon. Watson, J. G., Chow, J. C.,Fujita, E. M., 2001. Review of volatile organic compound source apportionment by chemical mass balance. Atmospheric Environment, 35(9), 1567-1584. Winkler, T., Goschnick, J.,Ache, H., 1991. Reactions of nitrogen oxides with NaCl as model of sea salt aerosol. Journal of Aerosol Science, 22, S605-S608. Wu, C.-F., Larson, T. V., Wu, S.-Y., Williamson, J., Westberg, H. H.,Liu, L.-J. S., 2007. Source apportionment of PM 2.5 and selected hazardous air pollutants in Seattle. Science of The Total Environment, 386(1), 42-52. Xiao, Y.-H., Liu, S.-R., Tong, F.-C., Kuang, Y.-W., Chen, B.-F.,Guo, Y.-D., 2014. Characteristics and Sources of Metals in TSP and PM2. 5 in an Urban Forest Park at Guangzhou. Atmosphere, 5(4), 775-787. Xiao, Y., Xi, D., Tong, F., Kuang, Y., Li, J., Chen, B., Shi, X., Pei, N., Huang, J.,Pan, Y., 2013. [Characteristics of rain season atmospheric PM2. 5 concentration and its water-soluble ions contents in forest parks along an urban-rural gradient in Guangzhou City of South China]. Ying yong sheng tai xue bao= The journal of applied ecology/Zhongguo sheng tai xue xue hui, Zhongguo ke xue yuan Shenyang ying yong sheng tai yan jiu suo zhu ban, 24(10), 2905-2911. Yang, X., Miller, D. R., Xu, X., Yang, L. H., Chen, H.-M.,Nikolaidis, N. P., 1996. Spatial and temporal variations of atmospheric deposition in interior and coastal Connecticut. Atmospheric Environment, 30(22), 3801-3810. Yin, L., Niu, Z., Chen, X., Chen, J., Zhang, F.,Xu, L., 2014. Characteristics of water-soluble inorganic ions in PM2. 5 and PM2. 5–10 in the coastal urban agglomeration along the Western Taiwan Strait Region, China. Environmental Science and Pollution Research, 21(7), 5141-5156. Yu, L., Wang, G., Zhang, R., Zhang, L., Song, Y., Wu, B., Li, X., An, K.,Chu, J., 2013. Characterization and source apportionment of PM2. 5 in an urban environment in Beijing. Aerosol and air quality research, 13(2), 574-583. Zhao, W.,Hopke, P. K., 2004. Source apportionment for ambient particles in the San Gorgonio wilderness. Atmospheric Environment, 38(35), 5901-5910. Zhao, W.,Hopke, P. K., 2006. Source identification for fine aerosols in Mammoth Cave National Park. Atmospheric Research, 80(4), 309-322. doi: 10.1016/j.atmosres.2005.10.002 王富民. 2007. 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. 國立中興大學. 王嘉瑋. 2011. 山谷邊界層之觀測與模擬. 臺灣大學大氣科學研究所學位論文, 1-96. 吳思穎. 2006. 有害空氣污染物之來源分析與風險評估. 國立臺灣大學. 李翊慈. 2015. 利用移動監測資料進行揮發性有機化合物濃度特性分析以及受體模式解析. 臺灣大學. Available from Airiti AiritiLibrary database. (2015年) 張木彬. 2007. 大陸沙塵暴及東亞生質燃燒期間台灣大氣中持久性污染物之傳輸特性研究; Long Range Transport of Dioxin-Like Pollutants via Asian Dust Storm and Biomass Burning. 梁志鋒. 2006. 受體模式CMB 與PMF 之比較與驗證. (碩士論文), 國立中興大學. 郭承彬. 2013. 多時間解析度資料於推估懸浮微粒與揮發性有機氣體來源之效用. 臺灣大學. Available from Airiti AiritiLibrary database. (2013年) 陳佩娟. 2003. 沿海地區大氣中懸浮微粒化學特性分析研究. 勞研所. 1996. 氣膠原理與應用. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52084 | - |
dc.description.abstract | 近年來台灣空氣污染的問題日益嚴重,在過去十幾年來人為排放量越來越高,使得大氣中存在許多污染物質,包括懸浮微粒(Particulate Matter, PM),倘若人體暴露到氣動直徑為2.5微米之細懸浮微粒(PM2.5)可能會影響身體的健康狀態,例如:肺功能減損或呼吸道相關疾病等。
本研究以南投縣溪頭自然教育園區苗圃地所監測之資料為例,監測2013年10月至2014年7月,每22小時收集懸浮微粒PM2.5樣本,共收集106筆資料。採樣PM2.5質量濃度之結果,秋季晝夜平均濃度分別為28.86 ± 7.02 µg/m3以及19.12 ± 5.14 µg/m3、冬季平均為19.16 ± 10.74 µg/m3、春季平均26.33 ± 10.81 µg/m3以及夏季11.52 ± 6.31µg/m3。觀測森林遊樂園區的PM2.5濃度變化進行資料分析,PM2.5組成成分之濃度分析包含16種元素(Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ba, Pb)、有機碳(OC)、元素碳(EC)以及12種離子(Na+, NH4+, K+, Mg2+, Ca2+, Cl−, NO2-, NO3−, PO43-, SO4=)。本研究使用受體模式(receptor model)— 正矩陣因子法(Positive Matrix Factorization, PMF),進行污染物來源推估。 利用PMF 5.0模式計算Q值、IM、IS以及誤差區間估計(Error Estimation)評估最合適之污染源數量,以模式解析之污染源指紋(Source profile)結果,以及污染源貢獻量(Source contribution) 推估出溪頭至少有4種主要污染源,包含交通相關之衍生型氣膠污染源(Diesel/Secondary)、燃油燃燒/交通污染源(Fuel-oil combustion/ Traffic)、海鹽傳輸污染源(Sea salt transported)以及生質燃燒(Biomass burning),其中以交通相關之衍生型氣膠污染源貢獻量佔44%最高。 | zh_TW |
dc.description.abstract | In recent years, problem of air pollution in Taiwan is worsening. Anthropogenic emissions are increasing, resulting in a lot of pollutants present in the atmosphere, including particulate matters. Expoures to the fine particles (PM2.5) with aerodynamic diameter less than 2.5 micron may cause adverse effect on human health, such as lung function impairment or respiratory-related diseases.
In this study, PM2.5 were measured at the nursery in Xitou natural education area from September 2013 to July 2014. PM2.5 samples were collectd for 80 days and each sample covered 22 hours. The analysis results showed that the average PM2.5 concentration during day and night was 28.86 ± 7.02 µg/m3 and 19.12 ± 5.14 µg/m3 in Fall, respectively; the average of PM2.5 concentration is 19.16 ± 10.74 µg/m3 in winter, 26.33 ± 10.81 µg/m3 in spring and 11.52 ± 6.31 µg/m3 in summer. For PM2.5 compositions, sixteen elements (Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ba, Pb), organic carbon (OC), elemental carbon (EC) as well as concentrations of twelve inorganic ions (Na+, NH4+, K+, Mg2+, Ca2+, Cl−, NO2-, NO3−, PO43-, SO4=) were determined. The model of the positive matrix factorization (PMF) was applied to estimate pollution sources in this study. We assessed the best-fitted solution by evaluating the Q value, Maximum Individual Column Mean (IM), Maximum Individual Column Standard Deviation (IS), and Error Estimation (EE). Based on the resolved source profiles and source contribution, four sources were identified: Diesel/Secondary, Fuel-oil combustion/ Traffic, Sea salt transported and Biomass burning, while the largest contributors of PM2.5 were Diesel/Secondary pollution source (44%). | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T14:07:35Z (GMT). No. of bitstreams: 1 ntu-104-R02844010-1.pdf: 2498555 bytes, checksum: 7dc656d291b2fc8b76d085c30e8b3d4a (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 致謝 ii
摘要 iii Abstract v 第一章 前言 1 1.1研究背景 1 1.1.1細懸浮微粒之化學組成特性 2 1.1.2森林環境細懸浮微粒之特性 3 1.2受體模式 7 1.2.1正矩陣因子法 7 1.2.2受體模式應用於森林環境 10 1.3 研究架構 11 第二章 研究方法 18 2.1 溪頭自然教育園區環境介紹 18 2.2 採樣策略與分析 18 2.3 樣本分析 19 2.4 受體模式樣本前處理 20 2.5 樣本品質控管 22 2.6 決定污染源數量 23 2.7 誤差估計 (Error Estimation) 25 2.7.1誤差分析 25 2.7.2 Q值判定污染源數量 26 2.8 污染源指紋圖譜之解釋 27 第三章 結果與討論 29 3.1溪頭PM2.5濃度 29 3.2溪頭氣象資訊 31 3.3 PM2.5成分分析 32 3.3.1 XRF QA/QC 32 3.3.2 溪頭PM2.5組成成分描述性分析 32 3.4 受體模式樣本前處理 36 3.5 選定污染源(factor)之數量 36 3.5.1 Q值判定污染源數量 38 3.5.2 誤差估計分析(Error Estimation analysis) 39 3.6 污染源解析 42 3.6.1 三個污染源模式結果 42 3.6.2 四個污染源模式結果 45 3.7 限縮設定(Constraint) 48 3.8 污染源貢獻分析 50 3.9 研究限制 53 第四章 結論與建議 54 文獻參考 102 附錄 112 | |
dc.language.iso | zh-TW | |
dc.title | 應用正矩陣因子法推估森林環境細懸浮微粒污染來源 | zh_TW |
dc.title | Applying Positive Matrix Factorization to Identify Pollution Sources of Fine Particles in Forest Environments | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蘇大成(Ta-Chen Su),蔡明哲(Ming-Jer Tsai),周崇光 | |
dc.subject.keyword | 森林,細懸浮微粒,來源推估,受體模式,正矩陣因子法,誤差估計, | zh_TW |
dc.subject.keyword | Forest,Fine Particle Matter,Source apportionment,Receptor model,Positive Matrix Factorization,Error Estimation, | en |
dc.relation.page | 118 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-08-20 | |
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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