環保專案成果報告查詢系統

專案計畫編號
經費年度	112
計畫經費	6,730 千元
預算科目	空氣品質監測
專案開始日期	2022/12/28
專案結束日期	2024/04/30
專案主持人	王聖翔
主辦單位	環境部監測資訊司
承辦人	鐘偉瑜
執行單位	社團法人台灣氣膠研究學會
專案分類	大氣空氣、環境監測及檢測
中文關鍵字	微脈衝光達監測網、氣膠自動監測網、國際合作
英文關鍵字	Micro-pulse lidar (MPL) Network, Aerosol automatically observation network, International collaboration
協同主持人
共同主持人
計畫聯絡人	吳莆馨
計畫聯絡電話	03-4227151#65519
計畫聯絡信箱	b95605041@g.ncu.edu.tw

中文摘要	臺灣空氣污染來源，除境外傳送，本土境內排放日益受到重視，由以中部至雲嘉南空品區經常性出現高PM2.5污染事件，類似之污染事件除了受排放源直接影響，大氣擴散條件不佳亦為元凶之一，而氣象條件從中小尺度環流至邊界層氣象的掌握，皆影響空氣污染預報與分析的成效，因此探討邊界層內的熱動力結構特性，有助釐清污染成因。地面空氣品質監測網雖然能夠提供地面以及區域性的特性，但卻無法解釋垂直方向上氣膠分布的特性，過去研究使用光達觀測探討低層大氣結構，結果顯示混合層的發展與地表加熱、對流作用增強、混合層之上的逆溫結構被抬升有關，顯示藉由氣膠的垂直結構可以反映出大氣的熱力穩定度，而熱力結構能再進一步影響地面空氣品質的變化，或為高污染事件之肇因。因此利用光學遙測技術於長時間持續監測垂直方向氣膠光學特性，提供污染物在垂直剖面上隨時間演變的資料，便顯得重要。本計畫之目標與工作內容為(1)持續與NASA MPLNET與AERONET進行國際合作交流，及技術諮詢與資料交換；(2)建置AERONET亞太檢校訓練中心檢校實驗室(APAC)相關場域，並建立APAC相關維護與校正流程；(3)協助辦理APAC開幕典禮相關事宜；(4)強化設備技術支援檢修量能與辦理教育訓練等工作以提升微脈衝光達系統觀測準確度；(5)建構觀測資料庫並定期完成資料品質保證與品質管制作業；(6)整合微脈衝光達系統與環境部空氣品質測站資料，提供高污染事件之可能成因分析報告，輔助空氣品質預報作業；(7)研析邊界層高度估算，並探討垂結構與地面空品關聯性；(8)利用環境部斗六站資料、光達PBLH等，研擬AI技術預報地面測站PM2.5濃度；(9)評估結合環境物聯網微感測器觀測、地面空品監測、無人機資料，優化光達垂直觀測資料判讀技術。執行之重要成果如下： • 為提高資料品質並加強國際交流，本計畫持續與NASA MPLNET及AERONET進行合作交流，逐步建立與維護AERONET亞太檢校訓練中心(APAC)相關流程與設施，逐步完成建置APAC室內校正空間與室外校正平台，並協助辦理APAC開幕典禮。 • 為持續強化微脈衝光達觀測量能，持續與NASA MPLNET進行合作，包含技術諮詢與資料交換、調整與校準校正設備、儀器寄送檢修等，於計畫執行期間使WFR設備之調整與校準有顯著進展，增進亞洲指標站之重要性，更提升近地表資料可信度。 • 建立資料品質管控程序，持續更新與維護環境部微脈衝光達測站網頁及資料庫，提供計畫及環境部相關人員查詢，亦提供專業諮詢及相關儀器評估、監測站運轉之環境與安全等資訊。 • 為維持站體與儀器運作穩定，本計畫持續中大站、西屯站、斗六站與左營站站體定期維護，每月AP/DC校正程序及現地維護員訓練等工作。並提供光達資料可用率月報，對各站儀器與資料品質掌握度良好。 • 以客觀統計方法定義出高污染並建立事件資料庫，整合微脈衝光達系統、太陽光度計資料、空氣品質測站、氣象資料等，觀察污染物垂直及水平方向分布情形，釐清區域性污染傳送特徵，有效應用於部內針對高污染事件探討。 • 完成計畫期間提供北中南大氣邊界層結構季節性特徵與空氣品質關係。並利用環境部斗六站資料、光達PBLH等，研擬AI技術預報地面測站PM2.5濃度並完成階段性測試。結合環境物聯網微感測器觀測、地面空品監測、無人機資料，評估優化光達垂直觀測資料判讀技術。
中文關鍵字	微脈衝光達監測網、氣膠自動監測網、國際合作

中文摘要

臺灣空氣污染來源，除境外傳送，本土境內排放日益受到重視，由以中部至雲嘉南空品區經常性出現高PM2.5污染事件，類似之污染事件除了受排放源直接影響，大氣擴散條件不佳亦為元凶之一，而氣象條件從中小尺度環流至邊界層氣象的掌握，皆影響空氣污染預報與分析的成效，因此探討邊界層內的熱動力結構特性，有助釐清污染成因。地面空氣品質監測網雖然能夠提供地面以及區域性的特性，但卻無法解釋垂直方向上氣膠分布的特性，過去研究使用光達觀測探討低層大氣結構，結果顯示混合層的發展與地表加熱、對流作用增強、混合層之上的逆溫結構被抬升有關，顯示藉由氣膠的垂直結構可以反映出大氣的熱力穩定度，而熱力結構能再進一步影響地面空氣品質的變化，或為高污染事件之肇因。因此利用光學遙測技術於長時間持續監測垂直方向氣膠光學特性，提供污染物在垂直剖面上隨時間演變的資料，便顯得重要。本計畫之目標與工作內容為(1)持續與NASA MPLNET與AERONET進行國際合作交流，及技術諮詢與資料交換；(2)建置AERONET亞太檢校訓練中心檢校實驗室(APAC)相關場域，並建立APAC相關維護與校正流程；(3)協助辦理APAC開幕典禮相關事宜；(4)強化設備技術支援檢修量能與辦理教育訓練等工作以提升微脈衝光達系統觀測準確度；(5)建構觀測資料庫並定期完成資料品質保證與品質管制作業；(6)整合微脈衝光達系統與環境部空氣品質測站資料，提供高污染事件之可能成因分析報告，輔助空氣品質預報作業；(7)研析邊界層高度估算，並探討垂結構與地面空品關聯性；(8)利用環境部斗六站資料、光達PBLH等，研擬AI技術預報地面測站PM2.5濃度；(9)評估結合環境物聯網微感測器觀測、地面空品監測、無人機資料，優化光達垂直觀測資料判讀技術。執行之重要成果如下： • 為提高資料品質並加強國際交流，本計畫持續與NASA MPLNET及AERONET進行合作交流，逐步建立與維護AERONET亞太檢校訓練中心(APAC)相關流程與設施，逐步完成建置APAC室內校正空間與室外校正平台，並協助辦理APAC開幕典禮。 • 為持續強化微脈衝光達觀測量能，持續與NASA MPLNET進行合作，包含技術諮詢與資料交換、調整與校準校正設備、儀器寄送檢修等，於計畫執行期間使WFR設備之調整與校準有顯著進展，增進亞洲指標站之重要性，更提升近地表資料可信度。 • 建立資料品質管控程序，持續更新與維護環境部微脈衝光達測站網頁及資料庫，提供計畫及環境部相關人員查詢，亦提供專業諮詢及相關儀器評估、監測站運轉之環境與安全等資訊。 • 為維持站體與儀器運作穩定，本計畫持續中大站、西屯站、斗六站與左營站站體定期維護，每月AP/DC校正程序及現地維護員訓練等工作。並提供光達資料可用率月報，對各站儀器與資料品質掌握度良好。 • 以客觀統計方法定義出高污染並建立事件資料庫，整合微脈衝光達系統、太陽光度計資料、空氣品質測站、氣象資料等，觀察污染物垂直及水平方向分布情形，釐清區域性污染傳送特徵，有效應用於部內針對高污染事件探討。 • 完成計畫期間提供北中南大氣邊界層結構季節性特徵與空氣品質關係。並利用環境部斗六站資料、光達PBLH等，研擬AI技術預報地面測站PM2.5濃度並完成階段性測試。結合環境物聯網微感測器觀測、地面空品監測、無人機資料，評估優化光達垂直觀測資料判讀技術。

中文關鍵字

微脈衝光達監測網、氣膠自動監測網、國際合作

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	2023_成果報告_定稿(含附錄).pdf	39MB	112-113年光達監測網與氣膠自動監測網操作維護及資料解析計畫成果報告	2024/6/5 上午 12:00:00

摘要	Besides the transboundary transport of pollutants, the local accumulation is the source of air pollution in Taiwan. Especially the central to southern areas, high concentrations of PM2.5 occur more frequent than other areas. The emission from factories and anthropogenic activities are important causes of the pollution events. In addition, the weak dispersion ability of atmospherics is the key reason leads to the poor air quality. To understand the meso scale or microscale and planetary boundary meteorology can help us to explain or study the air quality deeply. The monitoring near surface provides the horizontal distribution of pollutants but lack of the vertical information. Thus, use MPL and sun-photometers observation can enhance the vertical characteristics of aerosol and pollutants, complete the 4D information of high polluted events. The objectives and task of this project are: (1) to continue the conduct of international collaborations cooperation with NASA MPLNET and AERONET, and technical consultation and data exchange; (2) to build the environment and equipment of Asia Pacific AERONET Calibration and Training Center (APAC), establish the standard operating procedure (SOP) of calibration and maintenance; (3) to assist the Opening ceremony of APAC; (4) to offer professional consultation on micro-pulse lidar systems and sun photometers, evaluation of related equipment, and environmental safety information about the stations; (5) to build the lidar and sun photometer observation database and accomplish the operations of data QA/QC; (6) to integrate the observational data based on MOENV MPL systems and air quality monitoring station, and further analyze the possible causes of high pollution events, also export its potential on air quality forecast; (7) to estimate the PBLH and discuss the relationship between vertical structure with air quality at near surface; (8) to evaluate the technique of AI on predicting concentrations of PM2.5 by using MOENV Douliu air quality monitoring data and the PBLH which retrieved from MPL; (9) to evaluate the optimization of MPL data analysis by combining MOENV IoT data, MOENV air quality monitoring stations data, and UAV measurements. The important achievements from this project are listed as follows: • We continued to cooperate with NASA MPLNET and AERONET. We used online meeting and physical meeting in Taiwan with the PI of AERONET, and researchers for discussing AERONET Asia Pacific Calibration Training Center (APAC) established, including the indoor and outdoor calibration environment and equipment. We assisted with the Opening ceremony of APAC. • We used emailing, online meeting, and physical meeting in Taiwan with the chair of MPLNET, and the main engineering staff for discussing data retrieval techniques, calibrating the WFR equipment, and educating the techniques and webtools on calibrating, and replacing components. • We had executed the AP/DC calibration and both MPL and sun-photometers data QA/QC procedure on schedule to ensure the availability and stability of data. The MPL data has been posted to webpages and database real time and update to MOENV server simultaneously. • We applied a statistical method to define the high pollution events in this year and set up a database for case studies. We systematically analyze those pollution events with observational data obtained from EPA MPL system and air quality monitoring stations in Taiwan. We explained the causes of high pollution events based on multiscale analysis including vertical and horizontal distribution of particulate matters and meteorological conditions. The results from those case studies significantly improve our understanding on the air quality deterioration. • We provided the preliminary research of analyzing boundary layer height seasonal characteristics from north to south over Taiwan. We evaluated the technique of AI on predicting concentrations of PM2.5 at Douliu, and the optimization of MPL data analysis by combining MOENV IoT data with MOENV air quality monitoring stations data, UAV measurements.
英文關鍵字	Micro-pulse lidar (MPL) Network, Aerosol automatically observation network, International collaboration

摘要

Besides the transboundary transport of pollutants, the local accumulation is the source of air pollution in Taiwan. Especially the central to southern areas, high concentrations of PM2.5 occur more frequent than other areas. The emission from factories and anthropogenic activities are important causes of the pollution events. In addition, the weak dispersion ability of atmospherics is the key reason leads to the poor air quality. To understand the meso scale or microscale and planetary boundary meteorology can help us to explain or study the air quality deeply. The monitoring near surface provides the horizontal distribution of pollutants but lack of the vertical information. Thus, use MPL and sun-photometers observation can enhance the vertical characteristics of aerosol and pollutants, complete the 4D information of high polluted events. The objectives and task of this project are: (1) to continue the conduct of international collaborations cooperation with NASA MPLNET and AERONET, and technical consultation and data exchange; (2) to build the environment and equipment of Asia Pacific AERONET Calibration and Training Center (APAC), establish the standard operating procedure (SOP) of calibration and maintenance; (3) to assist the Opening ceremony of APAC; (4) to offer professional consultation on micro-pulse lidar systems and sun photometers, evaluation of related equipment, and environmental safety information about the stations; (5) to build the lidar and sun photometer observation database and accomplish the operations of data QA/QC; (6) to integrate the observational data based on MOENV MPL systems and air quality monitoring station, and further analyze the possible causes of high pollution events, also export its potential on air quality forecast; (7) to estimate the PBLH and discuss the relationship between vertical structure with air quality at near surface; (8) to evaluate the technique of AI on predicting concentrations of PM2.5 by using MOENV Douliu air quality monitoring data and the PBLH which retrieved from MPL; (9) to evaluate the optimization of MPL data analysis by combining MOENV IoT data, MOENV air quality monitoring stations data, and UAV measurements. The important achievements from this project are listed as follows: • We continued to cooperate with NASA MPLNET and AERONET. We used online meeting and physical meeting in Taiwan with the PI of AERONET, and researchers for discussing AERONET Asia Pacific Calibration Training Center (APAC) established, including the indoor and outdoor calibration environment and equipment. We assisted with the Opening ceremony of APAC. • We used emailing, online meeting, and physical meeting in Taiwan with the chair of MPLNET, and the main engineering staff for discussing data retrieval techniques, calibrating the WFR equipment, and educating the techniques and webtools on calibrating, and replacing components. • We had executed the AP/DC calibration and both MPL and sun-photometers data QA/QC procedure on schedule to ensure the availability and stability of data. The MPL data has been posted to webpages and database real time and update to MOENV server simultaneously. • We applied a statistical method to define the high pollution events in this year and set up a database for case studies. We systematically analyze those pollution events with observational data obtained from EPA MPL system and air quality monitoring stations in Taiwan. We explained the causes of high pollution events based on multiscale analysis including vertical and horizontal distribution of particulate matters and meteorological conditions. The results from those case studies significantly improve our understanding on the air quality deterioration. • We provided the preliminary research of analyzing boundary layer height seasonal characteristics from north to south over Taiwan. We evaluated the technique of AI on predicting concentrations of PM2.5 at Douliu, and the optimization of MPL data analysis by combining MOENV IoT data with MOENV air quality monitoring stations data, UAV measurements.

英文關鍵字

Micro-pulse lidar (MPL) Network, Aerosol automatically observation network, International collaboration