全球暖化是當前最迫切的環境議題之一，為降低溫室氣體排放，各國紛紛推動能源轉型，朝向碳中和目標邁進。台灣政府亦配合國際趨勢，預定於2025年使再生能源佔總發電量20%，並逐步降低對煤炭與核能的依賴。在此背景下，天然氣因碳排較低，被視為過渡階段的重要能源。為穩定供應天然氣，台灣中油公司規劃於桃園大潭藻礁區新建第三座液化天然氣接收站（以下稱三接），引發社會對環境保育的高度關注。雖中油提出多項緩解措施，如低衝擊施工、強化環境監測與生態補償等，但相關生態監測數據在評估報告中尚缺乏系統性分析與探討。 本研究以三接開發前與開發中的環境監測資料為基礎，運用趨勢線與多元迴歸分析，探討環境因子對殼狀珊瑚藻(Crustose Coralline Algae，CCA)覆蓋率的潛在影響。結果顯示，多數環境因子開發中變動相較於開發前趨於穩定，反映開發行為改變原有自然模式；而多元迴歸中的多元判定係數（R²）由開發前的97.2%驟降至開發期間的9.1%，顯示開發過程中可能有更多未考慮的影響因子在開發中產生。本研究結果可為未來類似工程之環境影響評估與生態管理策略提供科學依據與參考。;Global warming is one of the most pressing environmental issues today. In response to the need for reducing greenhouse gas emissions, many countries have promoted energy transition policies to achieve carbon neutrality. Taiwan, aligning with this global trend, aims to increase the share of renewable energy to 20% of total electricity generation by 2025 while gradually reducing its reliance on coal and nuclear power. As a transitional energy source, natural gas is favored for its relatively low carbon emissions. To ensure stable gas supply, CPC Corporation Taiwan has planned the construction of a third liquefied natural gas (LNG) receiving terminal in the Datan Algal Reef area of Taoyuan. This development has sparked considerable public concern regarding its potential ecological impact. Although CPC has proposed several mitigation measures, including low-impact construction methods, strengthened environmental monitoring, and ecological compensation, the monitoring data has not been systematically analyzed in related environmental assessments. This study utilizes environmental monitoring data from both before and during the construction phase of the Third LNG Terminal to assess the potential impact of environmental factors on the coverage of crustose coralline algae (CCA) using trend line and multiple regression analysis. Results indicate that most environmental factors became more stable during construction, suggesting that the development altered the original natural variability. Moreover, the coefficient of determination (R²) in the regression model dropped significantly from 97.2% before construction to 9.1% during construction, indicating the emergence of unaccounted variables during development. The findings provide a scientific reference for future environmental impact assessments and ecological management strategies in similar infrastructure projects.
