為研究生質物相關效能提升之方式，於本研究第一部分使用焙燒強度因子(TSF)來預測焙燒後的性質如重量損失、熱值、能量產率等，並可透過焙燒強度因子找出最佳的焙燒條件，以達到省時、省成本的效果。第二部分利用工業廢棄物高粱酒粕渣(SDR)及鋸木削(sawdust)透過添加沸石觸媒(ZSM-5)，透過熱重分析(TGA)、熱裂解氣象層析質譜（Py-GC/MS）、並創造觸媒效應指標如觸媒效果面積(CEA)、觸媒指標(CI)、芳香烴提升指數(AEI)來探討觸媒對於生質物的影響。
第一部分是將焙燒程度的指標如重量損失（WL）、焙燒強弱性指數（TSI）和強弱程度因子（SF）進行修正，於強弱程度因子（SF）加入時間指數並找出新的指標稱為焙燒強度因子（TSF）用以預測焙燒性能。在本篇中使用了四種不同生質物，如: Chinese medicine residue, Arthrospira platensis residue, C. sp. JSC4, 和 spent coffee grounds，通過時間指數的優化之後，TSF可以準確地連結WL，並可以精確地表示焙燒強弱性，與SF相比最高可將預測準確度提升至13％。結果表明，TSF亦能夠預測enhancement factor of HHV 和 energy yield，而其決定係數（R2）皆超過0.83。總體而言，TSF成功地結合了操作條件（焙燒溫度、實驗時間）和生質物的性質，可應用於預測焙燒後的性質。應用於焙燒實驗的設計與反應時間，TSF提供了一種簡單快速的方法，可以達到節省實驗時間、成本與得到有效之預測。
在第二部分中，通過熱重分析儀（TG）和熱裂解氣相層析質譜（Py-GC / MS）研究了ZSM-5催化生物質的催化熱解現象和機制，本研究著重於催化效應、芳香烴的分析及芳香烴碳氫化合物（AHs）的形成。本實驗中使用兩種生質物分別為木屑(sawdust)及高粱酒粕渣（SDR），並同時考慮了四種不同生物質與觸媒（B：C）的比例，分別為1：0、1：1、1：5及1:10。生質物的熱解過程可分為三個區域，從傳熱主導區（區域）到催化主導區（區域2和3）。分別使用四個指標分別為差異強度（IOD），催化有效面積（CEA），催化指數（CI）和芳香烴增強指數（AEI），以測量ZSM-5對生質物熱解和AHs形成的催化作用。最大的IOD發生在區域2中，這表示最高的催化作用強度。此兩種生物量的CI值隨B / C比的增加而提升。但是，當鋸末熱解效應存在極限值，這表示鋸末的催化作用將會受到限制。當催化劑添加量越高，裂解氣流中的AHs比例越高。當B / C比為1/10時，鋸末和SDR的AEI值為27.33和10.33。這表明AHs的形成顯著增強，尤其是對於木屑。總體而言，在本研究中進行的指標可以提供有用的措施，以識別催化熱解動力學及產物。

With the depletion of fossil fuels and increasing attention to environmental protection. Bioenergy is one of the most promising renewable energy sources. Therefore, in recent years, the development of biomass conversion technology and many ways to improve the fuel characteristics of biomass, such as torrefaction, catalytic pyrolysis, etc. are popular. Hence, in the first part of this study, the torrefaction severity index (TSF) was used to predict the properties of terrified biomass such as weight loss (WL), high heating value (HHV), and energy yield. The suitable experimental conditions can be found through TSF, to save both time and cost. The second part of this study uses industrial waste i.e., sorghum distillery residue (SDR) and sawdust with different ratios of zeolite catalyst (ZSM-5), and through TGA, Py-GC/MS. Several indices are used to explore the effect of catalysts on biomass such as catalyst effect indicators such as catalytic effect area (CEA), catalytic index (CI), aromatics enhancement index (AEI).
The first part of the discussion is about torrefaction. Many indicators have been used to describe the torrefaction severity, such as; weight loss (WL), torrefaction severity index (TSI), and, severity factor (SF). In this study, the term torrefaction severity factor (TSF) is proposed by introducing a time exponent in SF. Four different biomass materials of Chinese medicine residue, Arthrospira platensis residue, C. sp. JSC4 and spent coffee grounds are examined. After the optimization of the time exponent, TSF can accurately correlate with WL and thereby torrefaction severity, and improve the prediction by up to 13% when compared to SF. Also, the results suggest that TSF can appropriately predict the enhancement factor of HHV and energy yield where the coefficient of determination (R2) is beyond 0.83. Overall, TSF has successfully combined the operating conditions (temperature and duration) and biomass species, which can be utilized for predicting torrefaction performance. This gives a simple and fast way for torrefaction operation and reactor design, thereby saving time and carrying out efficient predictions.
In the second part, catalytic pyrolysis phenomena and mechanisms of biomass with ZSM-5 are investigated via a thermogravimetric analyzer (TG) and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), with particular emphasis on catalytic level identification and aromatic hydrocarbons (AHs) formation. Two biomass materials of sawdust and sorghum distillery residue (SDR) are investigated, while four biomass-to-catalyst (B:C) ratios of 1: 0, 1: 1, 1: 5, and 1:10 are considered. The pyrolysis processes of the biomasses can be divided into three zones, proceeding from a heat-transfer dominant zone (zone) to catalysis dominant zones (zones 2 and 3). Four indexes of the intensity of difference (IOD), catalytic effective area (CEA), catalytic index (CI), and aromatic enhancement index (AEI) are conducted to measure the catalytic effect of ZSM-5 on biomass pyrolysis and AHs formation. The maximum IOD occurs in zone 2, showing the highest intensity of the catalytic effect. The CI values of the two biomasses increase with increasing the B/C ratio. However, there exists a threshold for sawdust pyrolysis, indicating a limit for the catalytic effect on sawdust. The higher the catalyst addition, the higher the AHs proportion in the vapor stream. When the B/C ratio is 1/10, the AEI values of sawdust and SDR are 27.33 and 10.33. This reveals that AHs formation is intensified significantly, especially for sawdust. Overall, the indexes conducted in the present study can provide useful measures to identify the catalytic pyrolysis dynamics and levels.

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