| 研究生: |
鄭光利 Cheng, Kuang-Li |
|---|---|
| 論文名稱: |
回收物質再利用之碳足跡評估方法及不確定性分析研究─以台灣鋼鐵業廢鋼為例 Carbon Footprint Calculation Method and Uncertainty Analysis of Recycling: Cases Study of the Steel Industry in Taiwan |
| 指導教授: |
林素貞
Lin, Su-Jhen |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 環境工程學系 Department of Environmental Engineering |
| 論文出版年: | 2012 |
| 畢業學年度: | 100 |
| 語文別: | 中文 |
| 論文頁數: | 150 |
| 中文關鍵詞: | 回收 、碳足跡 、不確定性 、環境額度 、環境負荷 |
| 外文關鍵詞: | Recycle, carbon footprint of a product (CFP), uncertainty, environmental credit, environmental burden |
| 相關次數: | 點閱:86 下載:8 |
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近年來因永續發展觀念興起,目前社會趨向於將物質盡可能的回收再利用延長其效用時間,減少資源消耗,降低對環境的衝擊。生命週期評估(Life cycle assessment, LCA)是國際間常用於評估環境衝擊的方法,至今延伸許多相關應用,碳足跡(Carbon footprint of a product, CFP)便是其中之一。CFP承襲LCA的概念,評估者需由產品之原料開採、製造、使用、棄置或回收各個階段評估其碳足跡。生命週期評估在產品原料開採、製造、使用棄置階段之計算方法大已確立,但於回收階段之評估方法仍尚未一致,隨著溫室氣體管理和資源永續回收再利用的風潮興起,建構一個合理的回收階段碳足跡估方法,使其更確實反應產品對GWP的影響,已成為刻不容緩的研究目標。
本研究以三間電弧爐廠家(A、B、C廠)之盤查資料,進行電弧爐鋼胚之碳足跡評估,爾後對碳足跡以及應用不同回收方法之結果進行不確定性評估,瞭解各參數不確定性對碳足跡評估結果之影響及應用不同回收方法之不確定性,進而應用三種評估方法,包括Cut-off approach(CF)、waste valuation method(WV)、pool method(PL),以探討較合理、完整回收階段碳足跡之評估結果。本研究平均1kg電弧爐製程所產鋼胚之碳足跡為0.56 kgCO2e,碳足跡貢獻最大者為電力(56%),其次依序為廢鋼國外運輸進口(18%)、生石灰(7%)、焦炭(7%)及碳粉占(5%)。三廠家之不確定性排序為A廠>C廠>B廠,造成不確定性主要來源為電力、碳粉、焦炭及生石灰。應用三種不同方法之不確定性分析結果為CF不確定性最高,WV及PL兩者相近;綜合三種不同回收方法之評估及相關不確定性分析之結果,本研究認為同時考慮回收物credit和burden的WV方法為較佳的回收評估方法,因其參數不確定性較低且可獲得較完整之碳足跡資訊,亦可間接帶動整體供應鏈生命週期盤查。
This research is about the carbon footprint of a product (CFP) calculation method for recycled products. In recent years, many CFP reports have been published, but most of this research deals with the general life cycle assessment. The general life cycle includes mining, manufacturing, use, and disposal. For a friendly environment, there are many enterprises now using renewable resources as raw materials. However, the calculation method for the recycling part of this process is not definite. Therefore, this research chooses three steel plants in Taiwan as case studies case to compare the CFP with three different calculation methods. By comparing the differences and by emplying uncertainty analysis, we try to find which method is most appropriate for the recycled product.
Results of this study show that average carbon footprint is 0.56 kgCO2e per kg of crude steel by EAF. The major contribution of CFP comes from electricity (56%). The other includes scrap imports (18%), quicklime (7%), coke (7%) and graphite powder (5%). The total uncertainty are ranked from highest to lowest as plant A> plant C> plant B, and the reasons for uncertainty are related to electricity, graphite powder, coke and quicklime. The results of uncertainty analysis for three different methods─Cut-off approach (CF), waste valuation method (WV), and pool method (PL), shows CF has the most uncertainty while WV and PL are close. Some conclusion of this study is that the WV method, which considers the credit and burden at same time, is a better method to calculate the CFP at the recycling stage, because it has lower uncertainty, more complete information of the CFP, and it can promote the supply chain for the life cycle inventory.
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