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影響大台北地區懸浮微粒濃度變化之氣象分析

Meteorological Influences on the Changes of Suspended Particulate Concentration in the Great Taipei Area

摘要


本文從邊界層氣象參數和綜觀天氣型態兩方面,探討其與大台北地區懸浮微粒(PM10)日平均濃度變化之關係,重點則在討論導致大台北地區空氣品質劣化之氣象條件。結果顯示,近地面逆溫之存在和微弱的低層風速為導致大台北地區空氣品質劣化的兩個基本氣象條件,然而近地面逆溫層對日平均PM10濃度變化之影響較為定性,逆溫層底高度與PM10濃度之負相關係數常在0.5以下,且因季節而變。至於降水對日平均PM10濃度之影響,因降水型態和季節而不同,但一般降水時數越長,沖刷作用越強。大台北地區PM10濃度之季節變化,主要受季風環流(和地形)影響,基本上夏季西南季風時PM10濃度值較高,而冬天東北季風時,則值較低。然而逐日PM10濃度值之變化則受移動系統所控制;當天氣系統移行較緩,台灣地區等壓線較疏且偏南風時,大台北地區空氣品質一般較差;若有高壓脊經過(而出現近地面逆溫)時,則污染情形更嚴重。在分析中,我們將此等劣化之天氣型態歸納為冬、夏各四類型,並統計、討論各天氣類型伴隨之PM10濃度分佈;而此八種天氣類型在反應空氣品質劣化技術得分(Threat Score)達到80%(冬季為70%),而前估、後符值亦皆在90%左右。此結果顯示,若能利用數值天氣預報圖以掌握劣化天氣型態之出現時間,對空氣品質潛勢預報將大有助益。

並列摘要


This paper discusses the influences of boundary layer parameters and synoptic patterns on the air quality of the Great Taipei area or the daily average concentration of PM10 (suspended particulate matter with diameter less than 10 micrometers). Focus is placed on the analysis of the meteorological conditions associated with the air pollution episode. Results show that near surface inversion and light wind are two most important factors leading to the local air pollution event. However, the influences of the inversion height on the air quality is more on the qualitative sense. The value of negative correlation coefficient between the inversion height and the daily average PM10 concentration is generally less than 0.5 and varies with season. The influence of rainfall on the daily average PM10 concentration also varies with season and precipitation type. But, the washout effect of rainfall generally increases as the daily rainfall period becomes longer.The seasonal variations of PM10 concentration in the Great Taipei area are controlled primarily by the monsoon circulation (and Taiwan topography). The PM10 concentration is higher during the summer southwest monsoon season and lower during the winter northeast monsoon season. However, the changes in the daily average PM10 concentration are controlled by the moving synoptic systems. The air quality is generally poor when the synoptic systems are moving slowly with weak pressure gradient and southerly over Taiwan area. The air pollution condition will become more severe if the ridge is across Taiwan area and causes the inversion to occur. In our analysis, we classify all synoptic conditions, which are associated with the air pollution episodes in the Great Taipei area, into four synoptic patterns in winter and summer, individually. The PM10 concentration associated with these eight synoptic patterns are also summarized and discussed. Results show that the threat score of these eight synoptic patterns in predicting the air pollution event reaches 0.8 (0.7 in winter). These results suggest that the prediction of the pollution synoptic patterns using numerical weather prediction charts is helpful to the daily operation of air quality potential forecasts.

被引用紀錄


王光宇(2007)。利用主動性構件疏導都市氣膠微粒分佈之改善效果研究〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841%2fNTUT.2007.00453
魏名材(2007)。建立氣候變遷對空氣品質及涵容能力衝擊評估與預警機制〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841%2fNTUT.2007.00003
蔡豐懋(2005)。都市街廓量體型態改變對於都市風場與懸浮微粒PM10分佈之影響〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841%2fNTUT.2005.00158
邱瑞仙(2008)。桃園地區空氣污染物濃度相關性及地理分布〔碩士論文,國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-0207200917352113

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