Chia Nan University of Pharmacy & Science Institutional Repository:Item 310902800/33889
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    Title: 以固體廢棄物之物理組成推估灰分含量之研究
    SWIFT MODEL FOR A BOTTOM ASH PREDICTION BASED ON WET-BASED PHYSICAL COMPONENTS OF MUNICIPAL SOLID WASTE
    由於焚化一直是都會固體廢棄物(Municipal solid waste;MSW)處理的最重要技術之一,而在其管理經營時亟需相關數據作為後續運作之用,而在本研究中,透過多元回歸分析法分析MSW之物理組成與灰渣之關聯並提出焚化底渣之推估模式,本研究計收集2018-2019年期間臺灣不同都會地區之焚化廠126個MSW樣本,研究首先對MSW進行物理組成分析;其成分分別為:紙、木材、廚餘、塑料、其他可燃垃圾、鐵金屬、有色金屬、玻璃與其他成分。根據其結果顯示我國MSW主要來自於紙板、塑料與廚餘,其佔比超過80%。由於底渣之來源主要來自都會固體廢棄物中之不可燃成分(例如鐵金屬與玻璃),底渣之推估模式則以以此為主要成分,本研究並使用平均絕對百分比誤差(Mean absolute percentage error; MAPE)來評估值之準確度,經本研究多元回歸分析所得之快速推估模式之MAPE值為22.26 %,屬可接受水平,此結果即說明所提出模式之底渣預測值屬可接受值。另由統計檢驗顯示測量值與預測值之間亦未有顯著差異,由此可知本研究所建議之基於濕基物理成分之底渣預測模式可應於臺灣城市固體廢棄物焚化管理實務,提升整體效能。
    Since the incineration has been one of the most important technology of municipal solid waste (MSW) treatment. In this study, a bottom ash prediction model from the physical compositions was proposed by using multiple regression analysis. There were 126 samples gathered from the incineration plants in different cities during 2018-2019 in Taiwan. The physical compositions included paper, wood, food waste, plastics, other combustible wastes, iron metal, non-ferrous metal, glass, and miscellaneous components. According to the obtained results, more than 80% of MSW came from paper and cardboard, plastics, and food waste. However, the main sources of bottom ash mainly come from the non-combustible components of MSW (e.g. iron metal and glass). The mean absolute percentage error (MAPE) value was used to evaluate the model and MAPE value of the obtained swift model was 22.26% (acceptable level). It implied that the bottom ash prediction of the proposed model was acceptable and there was also no significant difference between the measured values and predicted values by statistical analysis. It concluded that the prediction model of bottom ash by the physical composition (wet basis) was an acceptable tool in MSW management in Taiwan.
    Authors: Klomkaew, Chatchai
    Contributors: 環境資源管理系
    林建榮
    Keywords: 底渣預測
    底渣
    都會固體廢棄物
    預測模式
    Ash prediction
    Bottom ash
    Municipal solid waste
    Prediction equation
    Date: 2020
    Issue Date: 2022-10-21 10:27:11 (UTC+8)
    Relation: 學年度:108, 66頁
    Appears in Collections:[Dept. of Environmental Resources Management] Dissertations and Theses

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