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  • 學位論文

多變量統計分析應用於空氣品質總量管制區自動監測資料之探討

Application of Multivariate Statistical Analysis to Investigate the Automatic Monitoring Data in an Air Quality Total Quantity Control District

指導教授 : 吳明洋

摘要


台灣地區目前對於空氣品質優劣的評斷係根據空氣污染指標(pollution standard index, PSI),其適用於任何可能產生嚴重空氣污染及進行空氣污染總量管制之地區,而目前國內外針對利用空氣污染指標來探討一地區之空氣污染特性及等級劃分的方式並不多見。本文利用台灣中部空氣品質總量管制區8個自動空氣品質監測站之空氣品質資料,利用統計分析方法探討各空氣品質變量間的相互關係,期能真正反應各空氣品質監測站之間空氣品質的差異,進而建立能夠適用於台灣中部,乃至台灣地區空氣品質等級劃分之程度。經由自動監測站監測資料中初步選擇7種空氣污染物為重要的,再經由「因子分析」後可簡化為三個主要因子,分別為有機性污染因子、光化學污染因子及燃料因子,這三個因子為主要影響台灣中部地區空氣品質優劣的主要因素。經由「群集分析」將本地區空氣品質狀況劃分為五種不同的類群,每個群集可代表不同特性的空氣品質狀況與污染程度。最後利用「判別分析」來判別確定待判別樣本的所屬類別,以確認先前的群集分析方法是否適當,經由判別分結果,判識正確百分比高達96.57%,顯示先前群集分析結果是可以接受的。本研究結果不僅可提供空氣品質管理成效檢討及管制策略之研擬,對於空氣污染管理應用工具上亦為一良好之方式。

並列摘要


The air quality in Taiwan, at present, is determined by a pollution standard index (PSI) that is applied to areas of possible serious air pollution and Air Quality Total Quantity Control Districts. Few studies in both Taiwan and other countries have examined the characteristics and levels of air pollution with PSI. This study uses air quality data collected from eight automatic air quality monitoring stations in an Air Quality Total Quantity Control District in central Taiwan and discusses the correlation between air quality variables with statistical analysis in an attempt to accurately reflect the difference of air quality observed by each monitoring station as well as to establish an air quality classification system suitable for the whole Taiwan. After using factor analysis(FA), seven air pollutants are grouped into three factors: organic, photochemical, and fuel. These three factors are the dominant ones in regards to the air quality of central Taiwan. Cluster analysis is used to classify air quality in central Taiwan into five clusters to present different characteristics and pollution degrees of air quality. Lastly, discriminant analyses (DA) is adopted to determine the classification of samples in order to test the adequateness of the cluster analysis. The discriminant results indicate an accuracy of 94.75% and the acceptance of the previous cluster analysis. This research results should serve as a reference for those involved in the review of air quality management effectiveness and/or the enactment of management control strategies. It is also a good method to use in an air quality management program.

參考文獻


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