| 研究生: |
施昱廷 Yu-Ting Shi |
|---|---|
| 論文名稱: |
以氣相層析搭載電子捕捉偵測技術驗證自製前濃縮儀穩定性 |
| 指導教授: |
王家麟
Jia-Lin Wang 王介亨 Chieh-Heng Wang |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
理學院 - 化學學系 Department of Chemistry |
| 論文出版年: | 2023 |
| 畢業學年度: | 112 |
| 語文別: | 中文 |
| 論文頁數: | 149 |
| 中文關鍵詞: | 分析化學 、電子捕捉偵測器 、自製前濃縮儀 、氣相層析儀 |
| 外文關鍵詞: | analytical chemistry, electron capture detector, thermo desorption, gas chromatography |
| 相關次數: | 點閱:17 下載:0 |
| 分享至: |
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面對空氣中複雜的成分,本研究室研發了前濃縮儀(Thermo Desorption Unit, TD)進行痕量揮發性有機化合物(Volatile Organic Compounds, VOCs)的捕捉與濃縮。由於台灣潮濕的環境,在TD前加裝了除水儀(Dewater Unit, DW)以除去大氣樣品的水分,並能夠同時保留極性與非極性物種,不造成樣品的流失。這些珍貴的研究成果,在過去實驗室的分析中,成功的在DW-TD接上氣相層析儀(Gas Chromatography, GC)並搭載火焰離子偵測器(Flame Ionization Detector, FID)與質譜儀(Mass Spectrometry, MS),雖然GC-FID的數據品質十分的穩定且完整,相較之下,GC-MS本身的漂移與不穩定性卻是顯而易見的。本研究利用了維護保養容易、靈敏度高且相當穩定的電子捕捉偵測器(Electron Capture Detector, ECD)以測試本DW-TD的性能表現。ECD的另一項優勢為只使用氮氣(Nitrogen, N2)作為載流氣體及尾吹氣,使得利用GC-ECD進行實場監測,會比使用GC-FID還更加地方便與直接。我們利用了ECD對於大氣中的痕量級氟氯碳化合物(Chlorofluorocarbons, CFCs)十分靈敏且具有高度的選擇性,驗證自製DW-TD的性能,由於CFCs高生命期、大氣混和均勻與早已因蒙特簍議定書(Montreal Protocol)而被世界禁止大部分生產的緣故,其在以周或月為單位的短時間連續分析時,其變異性會小於大部分的GC分析精度,而會有一定的背景值,我們利用這些特點分析CFCs以評估自製儀器的穩定性。
在新竹科學園區持續一個月的DW-TD/GC-ECD線上連續分析中,被禁用的CFC-12濃度為489.70±0.38 ppt,CFC-113為68.17±0.12 ppt,其RSD分別為0.08%及0.18%;CFC-11及CCl4雖早已被禁用,但仍能在這次的連續採樣中偵測到許多的高值事件,因此懷疑在科學園區中可能有排放,選定濃度相對平穩的三天進行RSD的計算,分別為1.21%及0.96%。這些結果會與AGAGE線上連續分析的Medusa/GC-MS及NOAA離線式採樣GC-MS進行RSD的比較,並在後續的研究探討中討論誤差的來源,推論出可能與熱脫附的再現性與流量計的流量穩定度有很大的關聯。在連續分析時出現的高值事件,可以透過當時的風速風向資料,使用實驗室開發之風瑰圖及逆軌跡推移追溯排放源為何。
本研究的第二部份聚焦在GC-MS線上連續分析中,參考標準方法NIEA A715.16B,在連續分析數天後,每日中濃度查核超出允收範圍及連續分析的濃度失真,是由於原本的檢量線建立,會利用四支內標準品進行二次的校正,但離子源的感度持續衰退,每個物種對於離子源感度皆不相同,造成檢量線的偏移不可用。透過每次分析皆會施打固定濃度的內標準品與建構每日的中濃度檢量線標準品查核,可以得到4個內標準品感度的衰退趨勢線與標準品中的86個目標物種衰退趨勢線,透過這兩條趨勢線可以預測當離子源感度衰退時,每個物種在每一筆分析的衰退程度。利用數據後處理的方式,將這些偏離允收範圍的物種校正回更加精準的值,避免系統誤差造成數據報告的失準。此外,透過CFC-12在大氣中濃度固定,不會有劇烈的變化或高值事件發生的特點,將每日連續數據拉回到相對的準確值,避免後續數據報告時的爭議。
In the face of the complex composition of atmospheric pollutants, our laboratory has developed a Thermo Desorption Unit (TD) for capturing and concentrating trace-level volatile organic compounds (VOCs) in air samples. Because of the humid climate, we further added a Dewater Unit (DW) before the TD to remove excess moisture from air samples, while retaining both polar and non-polar species to keep sample integrity. These achievements have been successfully utilized over the past few years by connecting the DW-TD units with gas chromatography (GC) equipped with flame ionization detection (FID) and mass spectrometry (MS). While the data quality from GC-FID was extremely stable and robust, the drift and thus instability in MS is significant by comparison. In this research, we attempted to use electron capture detection (ECD) to test the stability of the DW-TD units by exploiting ECD’s high sensitivity, stability, and the ease of operation. Another prominent advantage of ECD is that it only needs high-purity nitrogen gas as both the carrier and make-up gas. The deployment of GC-ECD in the field becomes much more straightforward than that of GC-FID. We exploited the highly sensitive and selective properties of ECD to measure trace-level atmospheric chlorofluorocarbons (CFCs) to demonstrate the performance of the self-built DW-TD apparatuses. Since CFCs have extremely long atmospheric lifetimes, and are well-mixed in the atmosphere due to the Montreal Protocol to ban them from most applications, they exhibit certain background mixing levels during a relatively short period of time, e.g., weeks or months, with variability smaller than most GC’s analytical precisions. We then utilized this property to assess the stability of our homemade instrument.
During the one-month continuous online analysis of DW-TD/GC-ECD at the Hsinchu Science Park, the concentration of the already banned CFC-12 was found to be 490±0.38 ppt (parts per trillion), and CFC-113 = 68±0.12 ppt, with RSD (Relative Standard Deviations) = 0.08% and 0.18%, respectively. Although CFC-11 and CCl4 have also been banned, they were still detectable in the continuous measurements, showing high-value events, suggesting emissions may still existed in this industrial park. By filtering out three consecutive days of data with relatively stable concentrations, the RSD for CFC-11 and CCl4 were found to be 1.21% and 0.96%, respectively. These results will be compared with the RSD from AGAGE's online data using Medusa/GC-MS and the off-line data of NOAA by GC-MS. Furthermore, in subsequent discussions, we also explored the sources of errors in measurements and inferred that the largest sources of error may be related to the stability of the heating coils and mass flow meters during continuous analysis. The occurrence of the high-value events during the month-long measurements can be traced back to emission sources by utilizing wind speed and direction data at the time, along with the laboratory-developed concentration wind roses and backward trajectory analysis.
The second part of research focuses on GC-MS online continuous analysis, following the standard method NIEA A715.16B. After several days of continuous analysis, deviations beyond the acceptance range of recovery in daily checks were observed. This is due to the original calibration curve establishment, which involved secondary calibration using four compounds as the internal standards. However, due to the rapid decline in ion source sensitivity, each species exhibits different responses, making calibration unreliable. By injecting an aliquot of internal standard for each analysis and conducting daily calibration check, we can determine the decreasing trends for both the four internal standards and the 86 target compounds in the standard mixture. By utilizing these two trend lines, we can predict the extent of degradation for each target species when the ion source sensitivity declines. Through post data processing, we can then correct these compounds deviating from the acceptance range to more accurate values, avoiding systematic errors in subsequent data reporting. Additionally, by using the fixed concentration of CFC-12 in the atmosphere, which does not experience significant variations, we can align the daily continuous data with the relatively accurate values to ensure the data robustness.
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