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玻璃纖維廠區周圍大氣氣狀及氣膠氟化物與化學組成研究

為了解決Glacier filter的問題，作者Kridtikar Narongin 這樣論述：

Fluorides (F-) were released into the environment may be present in the gas or particulate phase, natural emissions from volcanoes, marine aerosols, and anthropogenic industrial activity sources. The fluoride concentrations in the particulate matter (PM) and gaseous fluoride (primarily in hydrogen

fluoride, HF) sampled in the specific fiberglass company (SFGC), located in the Douliu industrial park, Yunlin County, and the general vicinity directly affected. Personal Environment Monitor collected PM2.5 and PM10 while Honeycomb Denuder System collected HF, then Ion Chromatography System (Dionex

ICS-5000) analyzed for fluoride concentrations. However, this study identified the mean of total fluoride concentration (Total F-, F- in PM10 included with HF), in the background year study (2019) accounted for 780.42 ng/m3 and in the range of 565.68 to 732.74 ng/m3 for the SFGC and the vicinity sa

mpling sites, respectively. During late of February and late of April sampling periods of 2020, the mean of Total F- was 661.85 ng/m3 and 658.58 to 827.57 ng/m3 for the SFGC and the vicinity sampling sites. Fluoride was mainly distributed in the gas phase, which was more than 89% and 90% in the 2019

and 2020 study periods. Fluoride in the ambient air recommended by the World Health Organization (WHO) should not over 1.0 μg/m3, preventing effects on livestock, plants and protecting human health. Moreover, the International Programme on Chemical Safety (IPCS) reported levels might be slightly hi

gher in urban than in rural locations; however, even in the vicinity of emission sources, airborne fluoride levels usually do not exceed 2 to 3 µg/m3. While the secondary inorganic aerosol (sulfate, nitrate, and ammonium) during the sampling periods were most abundant in PM2.5 and PM10, which accoun

ted for 64-85% of total water-soluble inorganic ions mass. Moreover, the average percentage of total carboxylates in particulate matter was lower than 5% and 10% during late Feb and late April in 2020, respectively. Then, total saccharides during the sampling periods was lower than 2% in particulate

matter.

精進UAV影像細緻化山坡地調查監測及分析

為了解決Glacier filter的問題，作者林迪詒 這樣論述：

台灣的山坡地常因豪雨、颱風、地震等引起邊坡滑動，滑動的山坡區域上建築、道路等設施會隨著滑動的持續發生，而導致開裂或傾斜等問題。由於引起滑動可能是受到地質、外部作用力之影響，所產生的變動範圍和變動量對於環境引起的災害程度不同，因此調查和監測邊坡變動，以及分析變動行為具有其必要性。近年來遙測技術發展迅速，可提供多樣的感測器選擇，並可以由衛載、空載、地面的形式進行測量地表變化，因此本研究為了能掌握週期性和細緻性的邊坡變動，採取不同空間與時間尺度之遙測方法。週期性的調查上以衛載的SAR影像為主，藉由雷達干涉技術獲得大範圍地表的時間序列位移資訊，另外細緻化地表監測採用高解析度的UAV影像觀察地表細微的

變化。儘管UAV影像本身具有高解析度的優點，在收集和處理的程序仍有其可精進的部分，因此本研究基於等高線概念設計航線，提升山坡區拍攝距離的一致性且維持高重疊率，並改善SFM演算法中相機自率定的準確性，提升建立影像幾何位置與三維模型的精度，以及將三維模型利用深度學習剔除植被區，提升計算多期變動量的可靠度，以上述基礎作為精進UAV影像的拍攝和處理的程序，提供更準確的地表變動資訊。另外針對有高風險性的區域，架設多台監視器即時監測位移速率。因此本研究整合上述三種影像建立一套分層監測流程，應用於監測山坡範圍廣的國立高雄科技大學燕巢校區。高雄市柴山西南側地區長期發生地滑，該區域建物與道路常發生開裂等問題，由

於區域的地質多樣且地面建立多面擋土牆，使得該區域具有許因素影響著滑動行為，因此藉由SAR影像透過雷達干涉技術獲得時間序列的變動資訊，以及藉由本研究提出的精進UAV影像拍攝和處理方法監測地表細節的變化。從監測成果發現降雨為主要的觸發該地滑的外部因素，但邊坡滑動過程受到擋土牆限縮位移的空間，使得擋土牆與淺層土層形成互制行為，讓該區產生不規則區塊的隆起和沉陷，根據實驗成果證實本研究提出的監測方法，可有效掌握現地的變化，並且可細緻化掌握各區域細微的變動行為。