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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/66042


    Title: 竹苗空品區2008~2012年空氣品質趨勢探討;Investigation of Air Quality in Chu-Miao Area during 2008~2012
    Authors: 范振清;FAN,JHEN-CING
    Contributors: 環境工程研究所
    Keywords: 竹苗空品區;空氣污染;排放清單;氣象因子;PM2.5;臭氧;Chu-Miao air quality area;air pollution;emission inventory;meteorological factor;PM2.5;ozone
    Date: 2014-07-22
    Issue Date: 2014-10-15 17:25:52 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究利用環保署設置於新竹市、新竹縣及苗栗縣的六個空氣品質監測站2008至2012年的監測數據,並配合全國排放清冊[TEDS]竹苗地區污染物排放清單,以評估同時段之空氣品質及趨勢,瞭解空氣污染管制在竹苗空品區的成效,釐清氣象因子的影響,探討各個監測站的污染形成,並在此基礎上提出未來污染管控的重點。
    就空氣污染物的排放方式而言,2008至2012年竹苗空品區的固定源污染物排放以工業源貢獻最大,其次為營建源,工業源尤其是印刷電路版製造業,營建源為車輛行駛揚塵最為重要。移動源的排放主要集中在公路運輸排放,尤其是自用小客車和大貨車的排放,這應該是未來污染防制的重點。從主要空氣污染物濃度監測結果來看,各個監測站在不同時間尺度上呈現不同特點。如就年平均濃度來看,各站之污染指標並未出現顯著的下降或上升趨勢;就季平均濃度而言,夏季各站污染普遍較輕,而冬春二季則顯著高於其它各季節;就月平均而言則更加複雜,SO2沒有明顯規律的波動,而O3濃度全年在4~5月和9~10月期間呈現雙高峰分布期,PM濃度在3~4月份有明顯抬高,這可能與大陸沙塵的長程傳輸有關。就影響空氣污染物形成及擴散的氣象因子而言,各監測站各污染物對各氣象因子的敏感性存在顯著差別。另外本論文也透過對PM2.5與CO、O3、NOx、SO2的相關性分析,探討各監測站空氣污染物濃度與移動源和固定源的相關性。
    ;This study combines monitoring data obtained from six automated air-quality monitoring stations operated by Environmental Protection Administration (EPA), as well as emission inventory data derived from Taiwan Emission Data System (TEDS) in Hsinchu City, Hsinchu County and Miaoli County. The objectives of this study are to use these data to assess the performance of air quality control during the last 5 years (2008-2012) and to investigate how the meteorological conditions influence the air quality and pollution episodes. Finally, several suggestions regarding the keys of air pollution control in the future are proposed based on the results, which could expect to serve as guidelines for related organizations to the consolidation of local monitoring stations and the improvement of air quality in Chu-Miao area.
    The results can be divided into three different parts. Firstly, the result of emission inventory shows that from 2008 to 2012, industry sector dominates the emission of stationary sources (in which the printed circuit board manufacturing is the highest profile contributor), followed by infrastructure sector, which is also the most important source of road fugitive dust. The pollutants emitted from mobile sources stem mainly from on-road traffic, especially the passenger cars and freight trucks, which should be the focus of emission control in the future. Additionally, the monitoring results demonstrate that the pollution level of all sites varied differently among different time scales. Specifically, there is no obvious trend of declining or rising year by year. Seasonally, air quality in summer is generally fine, but the situation is much worse in winter and spring. The variation of different pollutants becomes quite complex from the standpoint of monthly average. For instance, no distinct fluctuation is observed for SO2, while the concentration of O3 is distributed as double-peaks in April-May and September-October, respectively. Besides, the concentration level of PM appears an abrupt increase between March and April, which can be explained by the influence of long-range transported dust storms originated from mainland China. Moreover, the results obtained also confirm that the sensitivity of a variety of meteorological factors to various pollutants is presented in different patterns. Furthermore, the correlation analysis of PM2.5 against CO、O3、NOx、SO2 is conducted in order to explore the potential link between air quality and mobile/ stationary sources.
    Appears in Collections:[環境工程研究所 ] 博碩士論文

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