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論文名稱 Title |
以空氣品質模式及受體模式解析懸浮微粒排放源之貢獻量 Source contributions of suspended particles using Air Quality Model and Receptor Model |
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系所名稱 Department |
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畢業學年期 Year, semester |
語文別 Language |
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學位類別 Degree |
頁數 Number of pages |
210 |
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研究生 Author |
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指導教授 Advisor |
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召集委員 Convenor |
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口試委員 Advisory Committee |
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口試日期 Date of Exam |
2008-12-09 |
繳交日期 Date of Submission |
2008-12-21 |
關鍵字 Keywords |
空氣品質模式、CMB、TAPM、高屏空品區、受體模式 TAPM, Kao-Ping airshed, CMB, air quality model, receptor model |
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統計 Statistics |
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中文摘要 |
台灣地區依行政區域之劃分,共分七大空品區。其中,以高屏空品區最具惡劣之空氣品質狀況。高屏空品區空品不良率介於6.65 −13.56% (1998−2007年),為次差之雲嘉南空品區(2.58 − 6.98%)之2倍以上。石化、鋼鐵、電力等高污染性工業為高屏地區之主要發展產業,綜以人口、車輛密度、地形及氣象等因素致使污染物擴散不易,令空氣污染問題更為嚴重。於秋末、冬季及春季,受東北季風與中央山脈地形的影響,形成不利空氣污染擴散的環境,伴隨污染物隨季風之跨區域傳送,加上高屏地區工廠及移動車輛廢氣排放,形成全國最糟之空氣品質。 本研究主要應用TAPM (The Air Pollution Model)及CMB (Chemical Mass Balance)解析高屏地區懸浮微粒之物化現象及流佈,期以空氣品質模式及受體模式分析下,解析高屏地區重大污染源對大氣懸浮微粒之貢獻,掌握重要傳輸途徑與重要污染源,並瞭解氣象因素、地形因素及污染源在大氣懸浮污染事件之因果關係。空品模式解析結果可得工業型都市(小港)污染來源主要來自點源排放(49.1%),其次為面源(35.0%)及鄰近地區之傳輸(7.8%)。商業型都市(屏東)與郊區(潮州)之鄰近地區傳輸具極高之比例(屏東:39.1%;潮州:48.7%)。受體模式分析顯示,PM2.5之來源以汽油車及柴油車為主(小港汽油車:43%;柴油車17%。屏東汽油車:45%;柴油車:19%。潮州汽油車:12%;柴油車:29%)。PM2.5-10則以鋪面道路為主(小港:40%,屏東:48%,潮州:50%)。於兩種模式之交互應用下,可先以空品模式得知大區域之主要污染源類型,於特定點再利用受體模式得知當地污染類型,實施有效且較為細緻之空氣污染防治方法。 |
Abstract |
Air quality of the Kao-Ping airshed has been the worst of all airsheds which are divided into seven groups by districts in Taiwan. The percentage of annual bad air quality (Pollution Standard Index, PSI > 100) in the Kao-Ping airshed (6.65−13.56%) was twice than it in the Yun-Chia-Nan airshed (2.58−6.98%) during the past decade (1998−2007). Oil refineries, petrol/plastic industries, power plants, and iron/steel/metal plants are the major industries in the Kaohsiung metropolitan area. Due to intensive industrial and traffic activities, the Kao-Ping area has the poorest air quality in Taiwan − either increased ground-level concentrations of particulate matter (PM) or ozone (O3) associated with unfavorable meteorological conditions − particularly between late fall and mid-spring The temporal and spatial characterization of suspended particles in the Kao-Ping area was analyzed by using TAPM (air quality model) and CMB (receptor model) to understand the contributions of the major emission sources. Estimations using the TAPM model suggest that point-source emissions were the predominant contributors (about 49.1%) to PM10 concentrations at Hsiung-Kong industrial site in Kaohsiung City, followed by area sources (approximately 35.0%) and neighboring transport (7.8%). Because Ping-Tung City (urban) and Chao-Chou town (rural) are located downwind of Kaohsiung City when north or northeasterly winds prevail, the two sites also experience severe pollution events despite the lack of industrial sources; neighboring transport contributed roughly 39.1% to PM10 concentrations at Ping-Tung and 48.7% at Chao-Chou. Results of CMB (chemical mass balance) modeling show that the main contributors to PM2.5 mass are vehicle exhaust (gasoline vehicle emission: 43% and diesel vehicle emission: 17% at Hsiung-Kong; gasoline vehicle emission: 45% and diesel vehicle emission: 19% at Ping-Tung; gasoline vehicle emission: 12% and diesel vehicle emission: 29% at Chao-Chou). And the main contribution to PM2.5-10 mass is the paved road emission (Hsiung-Kong: 40%; Ping-Tung: 48%; Chao-Chou: 50%). It is recommended that air quality model is an appropriate tool to large area and receptor model is more suitable to specific point to identify emission sources by the results in this study. |
目次 Table of Contents |
謝誌I 摘要II ABSTRACT III 目 錄 V 表目錄 VIII 圖目錄 IX 第一章 前言 1-1 1.1 研究緣起 1-1 1.2 研究目的 1-1 1.3 研究架構 1-2 第二章 文獻回顧 2-1 2.1 高屏地區空氣品質趨勢2-1 2.2 指標污染物(PM10 及O3)趨勢變化 2-3 2.3 懸浮微粒特性概述 2-10 2.4 高屏空品區氣象概述 2-15 2.5 空氣品質模式及受體模式之相關研究 2-19 2.5.1 空品模式 2-19 2.5.1.1 箱型模式(Box model) 2-19 2.5.1.2 高斯模式(Gaussian model)2-20 2.5.1.3 計算流體動力模式 (Computational fluid dynamic model) 2-21 2.5.2 受體模式 2-23 2.5.2.1 化學質量平衡法(CMB) 2-23 2.5.2.2 主成分分析/絕對主成分分析(PCA /APCA) 2-24 2.5.2.3 正矩陣因子化法(PMF)2-25 VI 第三章 研究方法 3-1 3.1 TAPM 模式概述 3-1 3.1.1 TAPM 大氣制御方程式 3-1 3.1.2 TAPM 污染物傳輸制御方程式 3-3 3.1.3 TAPM 地表使用分類 3-9 3.1.4 模式評估工具 3-10 3.2 逆軌跡模式 3-11 3.3 CMB 模式概述 3-12 第四章 結果與討論 4-1 4.1 TAPM 模擬結果 4-1 4.1.1 模擬案例概述 4-1 4.1.2 春季案例(2005/3/8−10) 4-3 4.1.2.1 春季天氣條件 4-3 4.1.2.2 春季模擬結果 4-7 4.1.3 夏季案例(2005/7/12−14) 4-10 4.1.3.1 夏季天氣條件 4-10 4.1.3.2 夏季模擬結果 4-14 4.1.4 秋季案例(2005/10/12−14) 4-17 4.1.4.1 秋季天氣條件 4-17 4.1.4.2 秋季模擬結果 4-21 4.1.5 冬季案例(2005/12/16−18) 4-24 4.4.5.1 冬季天氣條件 4-24 4.4.5.2 冬季模擬結果 4-28 4.1.6 工業型、商業型及郊區之氣膠來源分佈 4-31 4.2 軌跡模式分析 4-32 4.3 受體模式分析結果 4-34 VII 4.3.1 受體點大氣物種濃度 4-34 4.3.2 指紋資料敏感性分析 4-37 4.3.3 污染源貢獻量 4-41 第五章 結論與建議 5-1 5-1 結論 5-1 5-2 建議 5-3 參考文獻 參-1 附錄A 模擬案例風場模擬結果 附A-1 附錄B 模擬案例PM10 濃度場模擬結果 附B-1 附錄C 作者簡歷 附C-1 |
參考文獻 References |
Balczo, M., Farago, T., Lajos, T., 2005. Modelling urban pollution dispersion by using MISKAM. In: Proceedings der Konferenz microCAD 2005, Miskolc University. Benson, P.E., 1984. CALINE 4—A Dispersion Model for Predicting Air Pollutant Concentrations near Roadways. FHWA User Guide. U. Trinity Consultants Inc. Chang, M.E. Cardelino, C., 2000. Application of the Urban Airshed Model to Forecasting Next-day Peak Ozone Concentrations in Atlanta, Georgia. J. Air and Waste Manage. Assoc. 50, 2010–2024. Chen, K.S., Lin, C.F., Chou, Y.M., 2001. Determination of source contributions to ambient PM2.5 in Kaohsiung, Taiwan, using a receptor model. J. Air and Waste Manage. Assoc. 51, 489–498. Chen, K.S., Ho, Y.T., Lai, C.H., Chou, Y.M., 2003. Photochemical modeling and analysis of meteorological parameters during ozone episodes in Kaohsiung, Taiwan. Atmos. Environ. 37, 1811–1823. Chen, K.S., Chen, S.J., Lin, J.J., Hwang, K.L., 2006. Studies of Spatial and Temporal Variations of Atmospheric PM2.5− Modeling and Analysis of Source Contributions in Kao-Ping Area, Taiwan. Final Report (NSC 94-EPA-Z-110-001) to EPA/NSC, Taiwan. Chow, J.C., Liu, C.S., Cassmassi, J., Watson, J.G., Lu, Z., Pritchett, L.C., 1992. A neighborhood-scale study of PM10 source contributions in Rubidoux, California. Atmos. Environ. 26, 693–706. Engelbrecht, J.P., Swanepoel, L., Chow, J.C., Watson, J.G., Egami, R.T., 2002. The comparison of source contributions from residential coal and low-smoke fuels, using CMB modeling, in South Africa. Environ. Sci. and Policy 5, 157–167. Espinosa, A.J.F., Rodriguez, M.T., Alvarez, F.F., 2004. Source characterisation of fine urban particles by multivariate analysis of trace metals speciation. Atmos. Environ. 38, 873–886. Friedlander, S.K., 1973. Chemical element balances and identification of air pollution sources. Environ. Sci. Technol. 7, 235–240. Gifford Jr., F.A., 1976. Consequences of effluent releases. Nuclear Safety 17, 68–86. Gordon, G.E., 1980. Receptor models. Environ. Sci. Technol. 14, 792-800. Gordon, G.E., 1988. Receptor models. Environ. Sci. Technol. 22, 1132-1142. Guo, H., Ding, A.J., So, K.L., Ayoko, G., Li, Y.S., Hung, W.T., 2008. Receptor modeling of source apportionment of Hong Kong aerosols and the implication of urban and regional contribution. Atmos. Environ., article in press. Harrison, R.M., Smith, D.J.T., Luhana, L., 1996. Source apportionment of atmospheric polycyclic aromatic hydrocarbons collected from an urban location in Birmingham, U.K. Environ. Sci. Technol. 30, 825-832. Hidy, G.M., Friedlander, S.K., 1971. The nature of the Los Angeles aerosol. Proc. Second Int. Clean Air Congress. Academic Press. Hien, P.D., Bac, V.T., Thinh, N.T.H., 2004. PMF receptor modelling of fine and coarse PM10 in air masses governing monsoon conditions in Hanoi, northern Vietnam. Atmos. Environ. 38, 189–201. Hinds, W.C., 1997. Aerosol Technology: Properties, behavior, and measurement of airborne particles, 2nd ed., John Wiley & Sons, Inc.. Holmes, N.S., Morawska, L., 2006. A review of dispersion modelling and its application to the dispersion of particles: An overview of different dispersion models available. Atmos. Environ. 40, 5902−5928 Hurley, P.J., Blockley, A., Rayner, K., 2001. Verification of a prognostic meteorological and air pollution model for year-long predictions in the Kwinana industrial region of Western Australia. Atmos. Environ. 35, 1871–1880. Hurley, P., Manins, P., Lee, S., Boyle, R., Ng, Y.L. Dewundege, P., 2003. Year-long, high-resolution, urban airshed modelling: Verification of TAPM predictions of smog and particles in Melbourne, Australia. Atmos. Environ. 37, 1899–1910. Hurley, P.J., Physick, W.L., Luhar, A.K., 2005. TAPM: a practical approach to prognostic meteorological and air pollution modeling. Environ. Modelling and Software 20, 737–752. Hurley, P., 2005a. The Air Pollurion Model (TAPM) Version 3. Part 1: Technical Description. CSIRO Atmospheric Research Technical NO. 71. Hurley, P., 2005b. The Air Pollurion Model (TAPM) Version 3. User Manual. CSIRO Atmospheric Research Internal Paper NO.31. Hurley, P., Physick, W.L., Luhar, A.K., Edwards M., 2005c. The Air Pollurion Model (TAPM) Version 3. Part 2: Summary of some verification studies. CSIRO Atmospheric Research Technical NO. 72. Johnson, G.M., 1984. A simple model for predicting the ozone concentration of ambient air, Proceedings of the 8th International Clean Air and Environment Conference, New Zealand, Clean Air Society of Australia and New Zealand. Kneip, T.J., Kleinman, M.T., Eisenbud, M., 1973. Relative contribution of emission sources to the total airborne particulates in New York City. In Third International Clean Air Congress, Dusseldorf, FRG. Luhar, A.K., Patil, R., 1989. A general finite line source model for vehicular pollution dispersion. Atmos. Environ. 23, 555–562. Luhar, A.K., Galbally, I.E., Keywood, M., 2006. Modelling PM10 concentrations and carrying capacity associated with woodheater emissions in Launceston, Tasmania. Atmos. Environ. 40, 5543–5557. Marcazzan, G.M., Ceriani, M., Valli, G., Vecchi, R., 2003. Source apportionment of PM10 and PM2.5 in Milan (Italy) using receptor modeling. Sci. of Total Environ. 317, 137–147. Mensink, C., Colles, A., Janssen, L., Cornelis, J., 2003. Integrated air quality modelling for the assessment of air quality in streets against the council directives. Atmos. Environ. 37, 5177–5184. Miller, F.J., Gardner, D.E., Graham, J.A., Lee, R.E., Wilson, W.E., Bachmann, J.D., 1979. Size considerations for establishing a standard for inhalable particles, JAPCA 29, 610−615. Oettl, D., Sturm, P., Almbauer, R., 2005. Evaluation of GRAL for the pollutant dispersion from a city street tunnel portal at depressed level. Environmental Modelling and Software 20, 499–504. Olson, D.A., Turlington, J., Duvall, R.M., McDow, S.R., Stevens, C.D., Williams, R., 2008. Indoor and outdoor concentrations of organic and inorganic molecular markers: Source apportionment of PM2.5 using low-volume samples. Atmos. Environ. 42, 1742–1751. Owega, S., Khan, B.U.Z., Dsouza, R., Evans, G.J., Fila, M., Jervis, R.E., 2004. Receptor modeling of Toronto PM2.5 characterized by aerosol laser ablation mass spectrometry. Environ. Sci. Technol. 38, 5712–5720. Paatero, P., Tapper, U., 1994. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values. Environmetrics 5, 111–126. Pasquill, F., 1961. The estimation of the dispersion of windborne material. Meteorology Magazine 90, 33–40. Pearson, K., 1901. On line and planes of closest fit to systems of points in space, Philosophy Magazine 2, 559 - 572. Stern, R., Yamartino, R.J., 2001. Development and first evaluation of micro-calgrid: a 3-D, urban-canopy-scale photochemical model. Atmos. Environ. 35, 149–165. Sokhi, R., Fisher, B., Lester, A., McCrae, I., Bualert, S., Sootornstit, N., 1998. Modelling of air quality around roads. Proceedings of the 5th International Conference on Harmonisation with Atmospheric Dispersion Modelling for Regulatory Purposes, Greece. Swietlicki, E., Krejci, R., 1996. Source characterisation of the Central European atmospheric aerosol using multivariate statistical methods. NIMB: Beam Interactions with Materials and Atoms 109/110, 519-525. Thurston, G.D., Spengler, J.D., 1985. A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston. Atmos. Environ. 19, 9-25. Tsai, Y.I., Chen, C.L., 2006. Atmospheric aerosol composition and source apportionments to aerosol in southern Taiwan. Atmos. Environ. 40, 4751–4763. Tsuang, B.J., Chao, C.P., 1999. Application of circuit model for Taipei City PM10 simulation. Atmos. Environ. 33, 1789–1801. USEPA (2002), SPECIATE 3.2. US Environmental Protection Agency, released in November 2002. Vecchi, R., Chiari, M., D’Alessandro, A., Fermo, P., Lucarelli, F., Mazzei, F., Nava, S., Piazzalunga, A., Prati, P., Silvani, F., Valli, G., 2008. A mass closure and PMF source apportionment study on the sub-micron sized aerosol fraction at urban sites in Italy. Atmos. Environ. 42, 2240–2253. Vega, E., Garcia, I., Apam, D., Ruiz, M.E., Baraiaus, M., 1997. Application of a Chemical Mass Balance Receptor Model to Respirable Matter in Mexico City. J. Air and Waste Manage. Assoc. 47, 524–529. Vignati, E., Berkowicz, R., Palmgren, F., Lyck, E., Hummelshøj, P., 1999. Transformation of size distributions of emitted particles in streets. Sci. of Total Environ. 235, 37–49. Watson, J.G., 1979. Chemical element balance receptor model methodology for assessing the sources of fine and total particulate matter in Portland, Oregon. Ph.D. Oregon Graduate Center, Beaverton, OR. Watson, J.G., Robinson, N.F., Lewis, C., Coulter, T., 1997. Chemical Mass Balance Receptor Model-Version 8 (CMB8) User’s Manual. Desert Research Institute Document No. 1808. 1D1. Watson, J.G., Robinson, N.F., Fujita, E.M., Chow, J.C., Pace, T.G., Lewis, C., Coulter, T., 1998. CMB8 applications and validation protocol for PM2.5 and VOCs, Desert Research Institute Document No.1808.2D1. Wark, K., Warner, C.F., Davis, W.T., 1998. Air pollution: its origin and control, 3rd ed., Addison Wesley Longman, Inc.. Willmott, C.J., 1982. Some comments on the evaluation of model performance. Bull. Amer. Meteorol. Soc. 63, 1309-1313. Willmott, C.J., Ackleson, S.G., Davis, R.E., Feddema, J.J., Klink, K.M., Legates, D.R., O’Donnell, J., Rowe, C.M., 1985. Statistics for the Evaluation and Comparisons of Model. J. Geophys. Res. 90,8995-9005. Wilson, J.G., Zawar-Reza, P., 2006. Intraurban-scale dispersion modelling of particulate matter concentrations: Applications for exposure estimates in cohort studies. Atmos. Environ. 40, 1053–1063 Winchester, J.W., Nifong, G.D., 1971. Water Pollution in Lake Michgan by Trace Elements from Pollution Aerosol Fallout. Water, Air, & Soil Pollution 1, 50–64. Zawar-Reza, P., Kingham, S., Pearce, J., 2005. Evaluation of a year-long dispersion modelling of PM10 using the mesoscale model TAPM for Christchurch, New Zealand. Sci. of Total Environ. 349, 249-259. 陳康興、陳瑞仁、林銳敏、黃國林,2007,「高屏地區大氣懸浮微粒(PM10 及PM2.5) 特性及成因分析研究-總計畫暨子計畫一:高屏地區大氣懸浮微粒(PM10 及PM2.5)化學組成特性 時空變化調查分析、來源模擬及成因探討研究」,95 年度「環保署/國科會空污防 制科研合作計畫」成果完整報告,NSC 95-EPA-Z-110-001。 何宜達,2004,「高屏地區臭氧事件日光化學模式解析及氣象條件之探討」,中山大學環工所博士論文。 柳中明及尤思喻,2006,「高屏地區大氣懸浮微粒(PM10 及PM2.5)特性及成因分析研究子計畫二:本土化「空氣品質指標」(AQI)研析與建議」,95 年度「環保署/國科會空污防制科研合作計畫」成果完整報告,NSC 95-EPA-Z-002-005。 廖琇怡,2005,「高雄市臭氧特性與氣象因子之相關性探討」,中山大學環工所碩士論文。 |
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