本研究結果顯示垃圾發熱量高低與濕基物理組成中皮革含量多寡關係最為密切，其次為塑膠、纖維布、紙類、廚餘類、木竹類及其他類，模式之判定係數R2等於0.994，顯示本研究所推導之以濕基物理組成或乾基物理組成推估垃圾發熱量之經驗公式為合宜的統計推估模式。另將本研究所推估之結果相較現行之三成分或物理組成模型或元素分析推估模式比較，顯示本研究推導之經驗公式適用性與精確度為模式中最為精準者，在台灣地區極具實用價值，其成果有益於台灣地區都市焚化廠以簡單之濕基物理組成分類或乾基組成，即可預判進入焚化廠垃圾發熱量品質之優劣，據以調整焚化爐之操作條件。此外，本結果亦顯示都市垃圾估計塑膠類乾基組成降低1%，每公斤垃圾將損失62 kcal左右之熱值，此一結果可提供目前環保署所推動之塑膠限用政策，研擬對焚化爐進場垃圾低位發熱量變化之政策參考。 This study employed the multiple regression model to construct a set of local empirical equations of lower heating value (LHV) for municipal solid waste (MSW) in Taiwan. Solid waste samples were gathered from different cities and counties during the period of 2001-2002 in Taiwan. First, the LHV and physical combustible component contents of each sample are examined for the establishment of the regression model. Contents of combustible physical component were then used to match the equation of lower heating value, and the multiple regression analysis was applied to establish the empirical equations for LHV. Finally, another sets of data obtained from another research were used to evaluate the feasibility of the LHV prediction model in this work.
Two equations, the dry-basis and wet-basis equations which were obtained based on the dry-basis and wet-basis, are presented in this study. The correlation coefficients of multiple determination for the dry-basis equation and the wet-basis equation are 0.994 and 0.986, respectively. Both equations are fitted well by the statistical. Furthermore, if we compare these two empirical equations with other equations presented in the literatures, the Mean Absolute Percentage Error (MAPE) of these two equations is lower obviously than those of other equations. These results reveal that these empirical equations obtained in the present paper are applicable for the determination of LHV of MSW economically by physical component, in place of bomb calorimeter.