歐盟碳邊境調整機制(CBAM)自2023年起要求進口商申報產品碳排放，並將於2026年正式課徵碳關稅，對出口導向的臺灣電子製造業形成直接壓力。產品碳足跡(Product Carbon Footprint, PCF)揭露已成為供應鏈競爭力的重要指標，惟中小企業電子製造商在資料取得、盤查技術與制度理解方面仍面臨挑戰。
本研究採個案研究法，以臺灣電子零組件製造商 B 公司之筆記型電腦電源座為個案產品，功能單位為「1個」，每個電源座由插座、電源線及末端端子組成，插座規格為30mm W x 24mm H x 28mm D，電源線長度90mm共有三條，電線尾端接有端子，合計重量36.6公克。彙整與分析其執行產品碳足跡盤查之流程，並依據收集的活動數據計算原料取得與生產製造階段之碳足跡。最後依據碳足跡熱點分析，提出產品減碳可行的做法。
計算結果顯示，每個電源座碳足跡為0.518 kgCO₂e，其中原料階段佔75.9 %，生產製造階段佔24.1%。前七大排放源合計佔比達81.0%，內架、製程用電分別為原料取得、生產製造階段之最大碳排放熱點。整體數據品質評估結果為基本品質(DQR=2.07)，原料階段受限於資料庫估算與供應商標稱值推估，品質偏低(DQR=2.2)，製造階段則達高品質(DQR=1.7)。
研究結果指出，碳排放集中於少數材料與製程能資源，產品減碳策略需優先聚焦於高排放項目，同時提升供應鏈數據透明度，以確保盤查結果的可信度。

The European Union’s Carbon Border Adjustment Mechanism (CBAM) has required importers to report product carbon emissions since 2023 and will formally impose carbon tariffs in 2026, exerting direct pressure on Taiwan’s export-oriented electronics manufacturing sector. Product Carbon Footprint (PCF) disclosure has become a critical indicator of supply chain competitiveness; however, small and medium-sized electronics manufacturers continue to face challenges in data acquisition, assessment techniques, and regulatory compliance.
This study adopts a case study approach—a 36.6g laptop power set manufactured by Company B in Taiwan—the procedures for conducting a product carbon footprint assessment, and the calculation of the carbon footprint of the raw material acquisition and manufacturing stages based on the collected activity data. Finally, feasible product carbon reduction measures are proposed based on carbon footprint hotspot analysis..
Results indicate that the product’s carbon footprint is 0.518 kgCO₂e, with raw materials contributing 75.9% and manufacturing 24.1%. The top seven emission sources account for 81.0% of total emissions, with electricity use representing the dominant hotspot in the manufacturing stage. Overall data quality was rated at a basic level (DQR = 2.07), with raw material data constrained by reliance on database estimates and supplier-declared values (DQR = 2.2), while manufacturing data achieved higher quality (DQR = 1.7).

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