Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/5021
標題: 地理資訊系統在空氣品質監測上之應用
The Application of Geographic Information Systems to The Routine Work of Air Quality Monitoring
作者: 林界宏
Lin, Jieh-Horng
關鍵字: GIS;地理資訊系統;Backward trajectory model;Kriging interpolation method;Arcview;Avenue;air quality monitoring;反軌跡模式;克力金插值法;空氣品質監測;空氣品質資料庫;監測站選址
出版社: 環境工程學系
摘要: 
本研究主要目的是藉由地理資訊系統空間整合分析的能力,將反軌跡模式
與克力金插值法經由Avenue程式語言設計整合於地理資訊系統ArcView當
中,使之成為適合空氣品質分析的模組化工具,以輔助空氣污染問題之解
析與相關行政管理決策之形成。本研究主要利用環保署位於台灣中部地區
現有的十處一般空氣品質監測站之監測資料進行研究,並針對1997年高臭
氧事件日的濃度趨勢分佈之成因與臭氧前驅污染物之軌跡傳輸路徑進行個
案調查,亦應用克力金標準偏差探討現行空氣品質監測站之站址規畫,配
合中彰投地區各鄉鎮之人口密度統計及選址模擬程式運算,選擇出適合增
設新站之地點。經由案例選址模擬後之結果,彰化縣田中鎮附近為日後考
慮於中部地區新增測站時之最佳設站位置。研究結果發現,運用地理資訊
系統的確能有效管理具空間分佈特性的空氣品質監測資料,亦能迅速地進
行整合分析與模擬,而透過分析模擬結果的展示,使得對於空氣污染物的
傳輸、擴散及濃度分佈更可清楚的掌握,因此使得空氣污染問題的成因得
以澄清。

The focus of this research is placed on the application of
geographic information systems (GIS) to the routine work of air
quality monitoring. Avenue, the built-in programming language
of ArcView, is used to integrate GIS with the backward
trajectory model and the Kriging interpolation method in order
to make GIS a modular tool that supports analysis of the air
pollution problems and decision making of the decision makers.
This research utilizes the air quality monitoring data of EPA in
1997 to study the air quality situation of the midland of
Taiwan, especially the trend of ozone concentration distribution
and the reasons resulting in ozone episode days. The transport
path of precursors of ozone in ozone episode day is also
studied. Furthermore, Kriging standard deviation associated
with population density are applied as indexes for the planning
of air quality monitoring network in the midland of Taiwan.The
results of Kriging analysis for several specific cases indicate
that Tienchung town of Changhua county is considered the optimum
place for EPA to build a new air quality monitoring station if
necessary.This study shows that GIS is a powerful tool which is
able to efficiently manage spatially distributed air quality
monitoring data. The visualization of the simulated results
make the transportation, diffusion and distribution pattern of
air pollutant more clear and understandable which is useful for
researchers and decision makers to figure out the reasons and
solutions of air pollution problems.
URI: http://hdl.handle.net/11455/5021
Appears in Collections:環境工程學系所

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