English  |  正體中文  |  简体中文  |  Items with full text/Total items : 21921/27947 (78%)
Visitors : 4243107      Online Users : 717
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://140.128.103.80:8080/handle/310901/1377


    Title: 大氣中微粒污染與重金屬成分之模擬與分析
    Other Titles: Simulation and analysis of the particle and heavy metal pollution in tmosphere
    Authors: 盧彥勳
    Lu, Yen-Hsun
    Contributors: 張鎮南
    Chang, Cheng-Nan
    東海大學環境科學與工程學系
    Keywords: 主成分分析法(PCA);工業污染源複合模式(ISCST3);空氣污染擴散模式(AERMOD);風險評估;PM10, PM2.5
    PCA;ISCST3;AERMOD;Risk Characterization;PM10, PM2.5
    Date: 2009
    Issue Date: 2011-02-25T01:22:30Z (UTC)
    Abstract: 擴建科學工業園區是全球開發中國家提升出口產品價值的必經流程,而台灣正是個典型的例子,靠著其強大的產能為台灣賺進許多外匯,也讓台灣成為全球的科技重鎮,而同時,由於過度開發卻也無形中可能排放出大量的有害污染物進入週邊空氣及水體中。砷、鎘、鉛正是典型的精密機械及光電半導體產業排放污染物。本研究自2007年12月到2009年3月於台灣中部科學園區進行空氣中總懸浮微粒的採樣,並且檢測其內含的重金屬濃度,且利用此探討工業區在運作中對於週邊空氣品質所造成的衝擊。中部科學園區是由玻璃基板、液晶面板生產、精密機械、半導體、光電、研發機構…等產業組成。本研究依據此工業區的風向來設置採樣地點,而採樣器為PM10高流量採樣器(流量為1,132 L min-1),使用石英濾紙,採樣時間為一天。而樣品經過消化後以火焰式原子吸收光譜儀或石墨式原子吸收光譜儀來進行分析,分析元素為︰As、Fe、Mn、Cu、Cd、Ca、Zn、Pb、Mg、Ni、及Cr等11項重金屬。 本研究首先針對大氣中微粒濃度分佈及重金屬含量進行分析,再利用主成分分析法(PCA)指出此科學園區週邊有數個潛在污染源;以最適於模擬小尺度範圍之模式ISCST3與AERMOD模式模擬分析,並比較探討兩模式差異。此外,本研究亦針對風險評估進行估算,以了解此重金屬汙染對人體危害之程度。 微粒濃度方面,與過去所做之文獻比較,近年來微粒細粒化趨勢愈加明顯,可能對人體造成更大危害;而重金屬濃度分析方面,致癌性較高之重金屬已有下降趨勢。PCA方面,以優勢風向南風及北風兩季節分別探討,分為上下風關係。上風處其污染源多為工業發散及地殼元素;反觀下風處,則多為高科技產業、工業污染及交通來源。模式推估方面,ISCST3在模擬上趨於保守,對濃度值有略為高估的現象;而AERMOD可能因為本身機制及設定上的不同,在模擬複雜地形上誤差較小。在風險評估方面,本研究利用暴露方程式來做計算,所求得之危害指數及致癌率皆在標準限制值之內。
    The expansion of high-tech industry is the way to upgrade the product value in many developing countries. In Taiwan, there are several science-based industrial parks, which generate tremendous high value-added export products, meanwhile they also may emit toxic substances into both air and water bodies. Some heavy metals are commonly found in the ambient air near industrial parks like arsenic, cadmium and lead, etc. This study conductes a survey program since Dec. 2007 to Mar. 2009, at the Central Taiwan Science Park (CTSP) in Taiwan. The types of CTSP industry include flat glass, aerospace, precision machinery, optoelectronics, semiconductor and other strategic research and development laboratories. This project allocates the sampling sites which cover the upstream and downstream of the emission sources according to the wind directions. The atmospheric particulate is collected through a PM10 high volume air sampler with quartz filter under the initial air flow rate of 1,132 L min-1 for 24 hours. The digested filter samples were analyzed by either flame or graphite type furnace of atomic absorption spectrophotometer. First, this study is aiming at the distribution of ambient particulates (PM2.5 and PM10) and heavy metal component from the science-based park. Then use Principal Component Analysis (PCA) to find out the possible source. The ISCST3 (Industrial Source Complex Short Term 3 Model ) and AERMOD (AMS/EPA REGULATORY MODEL) models were adapted to simulate the heavy metal dispersion phenomena. Besides, this study also use the risk characterization to evaluate the risk level to the human beings.The observed particle concentration, compared with reference, which indicates the particle becomes more and more small. It will be harmful to human bodies while the heavy metal concentration, which tends to be less than previous years due to the heavy economic recession since 2008. The study adapts PCA to category the possible pollution sources and based upon either the north and south wind seasons. The pollution sources on upward mostly were crustal elements and industrial processes, while the pollution sources at downward are mostly found from high-tech industry, industrials and vehicular emission. The simulation by ISCST3 model is too conservative to estimate and it is over-predicted than the measured. On the other hand, the AERMOD model obtains more close data to the measurement concentrations due to its inside framework. The risk characterization finds the hazard index and carcinogenic ratio is still far below limitation.
    Appears in Collections:[環境科學與工程學系所] 碩博士論文

    Files in This Item:

    File SizeFormat
    097THU00518008-001.pdf3291KbAdobe PDF2423View/Open


    All items in THUIR are protected by copyright, with all rights reserved.


    本網站之東海大學機構典藏數位內容,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback