5.1 結論
1. 本研究以貝氏蒙地卡羅法，應用於生命週期評估之不確定性研 究，可以解決生命週期評估不充分數據之困難。而增加不確定 性分析，並提供決策者完整之資訊，改善生命週期評估之可信 度。
2. 貝氏不確定性分析結果顯示，事前主觀機率分布結合統計或場 址數據，可更新參數及模式不確定性，及減低生命週期評估不 確定性。
3. 貝氏方法可混合已知數據以尋求代表性之事後分布，且可說明 不同事前分布相對於已知數據之影響，因此，貝氏蒙地卡羅法 可用於協助設計數據收集計畫，如增加實驗研究或收集品質較 佳之數據。
4. 雖然貝氏蒙地卡羅法可減低不確定性，但方法上之限制，包括 事前分布之來源及決定適合概似函數。前者當不同分析者之主 觀判斷選取之事前分布不同時，缺乏推論之一致性；後者則需 增加經費進行數據收集或實驗研究。
5.2 後續研究方向
1. 現階段生命週期評估之衝擊類別，僅選擇溫暖化潛勢單一指 標，後續將再選擇其他衝擊類別進行研究。
2. 持續探討貝氏蒙地卡羅法理論基礎，以進一步深入了解貝氏方 法之應用與限制，期能用於設計數據收集計畫，作為決定事後 分布要收斂到相同基準所需之數據之量及品質，以改善生命週 期評估數據，降低評估結果之不確定性。
3. 探討不同系統邊界對生命週期評估產生之不確定性影響。
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