隨著全球氣候變化，溫室氣體排放已成為了一個不容忽視的問題。本研究採用熵值法(Entropy method)設計碳排放指標，並採用Dynamic Directional Distance Function Data Envelopment Analysis Model（動態方向性距離函數資料包絡分析模型）測量歐盟29個國家2015年至2019年的勞動力效率、固定資產效率、可再生能源消耗效率、不可再生能源消耗效率、碳排放效率和GDP效率。本研究結果如下：(1) CH4的熵權大於CO2的熵權，由此可知， CH4對總碳排放的影響大於CO2。(2)丹麥、希臘、愛爾蘭、盧森堡、馬爾他、瑞典和英國這7個國家的勞動力效率、可再生能源消耗效率、不可再生能源消耗效率、碳排放指標效率、GDP效率和固定資產效率在研究期間是29個國家中位列第一的，亦即他們的投入和產出分配最優。(3)大多數國家的不可再生能源消耗效率比可再生能源消耗效率更高。(4)碳排放效率差的國家在不可再生能源消耗或可再生能源消耗方面的效率也較低。

With global climate change, greenhouse gas emissions are an issue that cannot be overlooked. The entropy method is used in this work to design carbon emission indicators and the Dynamic Directional Distance Function Data Envelopment Analysis Model is used to evaluate the overall efficiency, labor efficiency, fixed capital efficiency, renewable energy consumption efficiency, non-renewable energy consumption efficiency, carbon emissions efficiency and GDP efficiency in 29 EU countries for the period from 2015 to 2019. The results of this research are as follows: (1) CH4 had a greater impact on total carbon emissions than CO2. (2)The overall efficiency value, labor efficiency value, renewable energy consumption efficiency value, non-renewable energy consumption efficiency value, carbon efficiency value, GDP efficiency value and fixed capital efficiency value for Denmark, Greece, Ireland, Luxembourg, Malta, Sweden and United Kingdom were the highest among the 29 countries during the study period. These 7 countries have the optimal input and output allocations. (3) Non-renewable energy consumption in most countries is more efficient than renewable energy consumption. (4) Countries with poor carbon emission efficiency are also inefficient in terms of non-renewable energy consumption or renewable energy consumption.

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