斗六地區高PM2.5事件期間之 天氣特徵與大氣垂直結構;Weather regimes and atmospheric stability associated with high PM2.5 days in Douliu city, Taiwan

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題名:	斗六地區高PM2.5事件期間之天氣特徵與大氣垂直結構;Weather regimes and atmospheric stability associated with high PM2.5 days in Douliu city, Taiwan
作者:	黃文琪;Huang, Wen-Chi
貢獻者:	大氣科學學系
關鍵詞:	高PM2.5事件;天氣分類;大氣穩定度;high PM2.5 event;weather classification;atmospheric stability
日期:	2024-11-28
上傳時間:	2025-04-09 16:01:04 (UTC+8)
出版者:	國立中央大學
摘要:	斗六地區位於台灣中部並鄰近山區，雖非主要污染排放源，但PM2.5濃度卻在中部地區中居首。本研究的核心目標與重要貢獻在於建立天氣型態分類方法與估算歷史大氣穩定度，以深入探討斗六地區高PM2.5事件的成因。透過分析2019-2023年歷史資料，篩選高PM2.5事件，並根據地面天氣圖的大陸高壓與鋒面位置建立21種天氣型態，分析高PM2.5污染事件所伴隨的天氣系統與環流條件，定量統計天氣型態和污染事件發生的比例。同時，利用不同海拔測站的溫度數據估算垂直大氣穩定度，並以一組高污染事件個案之光達與無人機資料，驗證該穩定度指標之適用性。結果顯示，斗六及周邊地區PM2.5濃度逐年下降，其中，1-3月為空污事件高發時期，統計5年期間的天氣型態顯示，高壓迴流天氣型態(C3)共發生81天，其中41天為污染事件日，比例高達51%；高壓出海型態共發生102天，其中44天為污染事件日；東北季風型態(C1)則有147天，其中23天為污染事件日。進一步解析不同天氣型態的高污染特徵，發現東北季風型態的PM2.5濃度峰值出現在午夜後至中午前；高壓迴流型態則呈現雙峰結構，濃度峰值分別出現在晚上至午夜前及日出後至中午前。C1的風速較C3強0.3 m s⁻¹，並有更多北風分量；而C3於入夜後出現來自山區的東南風分量，可能導致午夜後至清晨PM2.5濃度較低。大氣穩定度分析結果指出，高污染事件期間，C1的穩定時數比例為77%，高於C3的66%。穩定度的差異可能與逆溫層結構有關，無人機資料顯示C3期間逆溫層結構相對淺薄（約400公尺），而C1期間逆溫層結構較深厚（約900公尺），此結果意味著，藉由不同測站高度的溫度差所定義的穩定度指標並無法有效地解析出斗六地區夜間輻射冷卻引發的淺薄逆溫結構，因此，對於歷史大氣穩定度和長期污染趨勢之討論應該較保守。整體而言，本研究提供了斗六地區高污染事件與大氣條件的系統性分析，結果可以確認斗六PM2.5高污染事件成因與天氣型態和其伴隨的水平環流和垂直大氣穩定度有密不可分的關係，而地形效應更是在其間扮演重要的角色，上述三者皆非人為可控制因素，值得未來空氣品質管理與污染控制措施規畫參考。 ;Douliu City is situated in a near-mountainous region of central Taiwan, which has the highest concentration of PM2.5. However, Douliu is not a significant pollutants emissions source. To investigate the causes, this study defines high PM2.5 events using historical air quality data and establishes a weather classification method based on the position of continental high-pressure and frontal systems to analyze the weather patterns associated with high pollution events. The atmospheric stability is defined using temperature data from weather stations at different altitudes, and atmospheric stability data are validated by analyzing high temporal resolution micro-pulse lidar (MPL) and unmanned aerial vehicle (UAV) data on high PM2.5 events. The results indicate a year-on-year decline in PM2.5 concentrations in Douliu. January to March remains the peak period for air pollution events. During this time, High-pressure peripheral circulation type (C3) occurred on 81 days, with 41 days (51%) being pollution events; high-pressure moving offshore type appeared on 102 days, with 44 pollution events; and northeast monsoon type on 147 days, with 23 pollution events. A detailed analysis of high-pollution characteristics across these types revealed that the PM2.5 concentration peaks for the northeast monsoon pattern (C1) occurred from midnight to noon. In contrast, the high-pressure return pattern (C3) exhibited a double PM2.5 peaks structure, with peaks occurring from evening to midnight and from dawn to noon. C1 had stronger winds (by 0.3 m s⁻¹) and more northerly wind components, whereas C3 showed southeasterly wind components from the mountainous regions at night, leading to lower PM2.5 concentrations from midnight to early morning. Atmospheric stability analysis revealed that during high-pollution events, stable conditions accounted for 77% of the time in C1, higher than 66% in C3. This difference in stability is likely related to the inversion layer structure, as drone data indicated a shallower inversion layer (about 400 meters) during C3 events, compared to a deeper inversion layer (about 900 meters) during C1 events. The stability index is suitable for extended periods of inversion structures but may show uncertainty for shallow inversion layers induced by radiative cooling. This study systematically analyzes high-pollution events and atmospheric conditions in the Douliu area. The findings enhance understanding of the causes of local PM2.5 pollution and serve as a reference for future air quality management and pollution control strategies.
顯示於類別:	[大氣物理研究所 ] 博碩士論文

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