隨著全球人口不斷增加，加上工業生產的需求與能源的依賴，造成了環境的進一步破壞與全球暖化的嚴重問題。對於環境汙染所帶來的負面影響，不僅影響到人們的健康與生活，更直接影響到了國家的經濟發展。此外，經濟發展與能源排放密切相關，隨著國家經濟水平的提高，能源消耗量也相應增加，進而導致對環境造成嚴重的污染和氣候變遷。
本研究採用Modified Undesirable Dynamic SBM(Slacks-based Measure) DEA Model分析歐洲19國2016－2019年的經濟效率、能源消費效率和溫室氣體排放效率。此模型將非意欲產出納入分析之同時也使用Entropy Weight Method將五種歐盟特別注重的溫室氣體CO2（二氧化碳），CH4（甲烷）， N2O（一氧化二氮），HFC（三氟甲烷），SF6（六氟化硫）設計為溫室氣體排放指標。
而本研究第一階段主要研究經濟效率，而第二階段則研究氣候變遷效率。本研究第一階段重於非再生能源及各種再生能源消費效率，第二階段則為本研究的重點部分，包含溫室氣體排放效率、氣候異常次數效率。
第一階段效率結果顯示出19個歐洲國家當中有17個國家處於最有效率的境界，且平均效率值0.893高於氣候變遷階段的平均效率，顯現89.4%的歐洲國家在經濟階段是具有效率的，僅有保加利亞及羅馬尼亞2個國家的效率值小於0.5明顯缺乏效率，表示此兩國家在經濟發展效率上具有很大的進步空間，而就非再生能源效率來看，歐洲國家可以致力於減少非再生能源的消費、多使用再生能源來促進能源效率的提高。
第二階段的結果得出，氣候變遷階段效率平均值為0.75831，且所有國家的效率值皆在0.5以上，顯現出歐洲這19個國家在氣候變遷階段上皆具有效率，尤其是葡萄牙，效率表現更是達到最有效率的境界，此外，單就個別效率而言，歐州國家溫室氣體排放效率普遍接近最有效率的境界而氣候異常次數效率方面，各國皆尚有進步空間。

As the global population and industrial production increase, the negative impacts of environmental pollution and climate change are becoming more severe. This not only affects people's health and daily lives but also has a direct impact on a country's economic development. In this study, the Modified Undesirable Dynamic SBM (Slacks-based Measure) DEA Model was used to analyze the economic efficiency, energy consumption efficiency, and greenhouse gas emission efficiency of 19 European countries from 2016 to 2019. The results show that during the economic stage, 17 out of 19 European countries had efficient economic performance, while Bulgaria and Romania have significant room for improvement. During the climate change stage, all 19 European countries were efficient, with Portugal having the most efficient performance. It is worth noting that there is still room for improvement in abnormal temperature frequency efficiency. The study suggests that countries can further reduce their consumption of non-renewable energy, promote renewable energy, and thereby reduce the frequency of abnormal climate events. Overall, this study highlights the importance of addressing climate change, improving renewable energy efficiency, and reducing non-renewable energy consumption.

1. Begum, R. A., Sohag, K., Abdullah, S. M. S., & Jaafar, M. (2015). CO2 emissions, energy consumption, economic and population growth in Malaysia. Renewable and Sustainable Energy Reviews, 41, 594-601.

2. Brown, C., Meeks, R., Ghile, Y., & Hunu, K. (2010). An empirical analysis of the effects of climate variables on national level economic growth. World Bank Policy Research Working Paper, (5357).

3. Chien, T., & Hu, J. L. (2007). Renewable energy and macroeconomic efficiency of OECD and non-OECD economies. Energy Policy, 35(7), 3606-3615.

4. Farajzadeh, Z., Ghorbanian, E., & Tarazkar, M. H. (2022). The shocks of climate change on economic growth in developing economies: Evidence from Iran. Journal of Cleaner Production, 372, 133687.

5. Gökgöz, F., & Güvercin, M. T. (2018). Energy security and renewable energy efficiency in EU. Renewable and Sustainable Energy Reviews, 96, 226-239.

6. Hamit-Haggar, M. (2012). Greenhouse gas emissions, energy consumption and economic growth: A panel cointegration analysis from Canadian industrial sector perspective. Energy Economics, 34(1), 358-364.

7. Hu, J. L., & Wang, S. C. (2006). Total-factor energy efficiency of regions in China. Energy policy, 34(17), 3206-3217.

8. Jebli, M. B., & Youssef, S. B. (2015). Output, renewable and non-renewable energy consumption and international trade: Evidence from a panel of 69 countries. Renewable energy, 83, 799-808.

9. Karimi, M. S., Ahmad, S., Karamelikli, H., Dinç, D. T., Khan, Y. A., Sabzehei, M. T., & Abbas, S. Z. (2021). Dynamic linkages between renewable energy, carbon emissions and economic growth through nonlinear ARDL approach: Evidence from Iran. Plos one, 16(7), e0253464.
10. Kuang, Y., & Lin, B. (2022). Natural gas resource utilization, environmental policy and green economic development: Empirical evidence from China. Resources Policy, 79, 102992.

11. Li, B., Han, Y., Wang, C., & Sun, W. (2022). Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China. Energy Policy, 167, 113081.

12. Meyghani, S., Khodaparast Mashhadi, M., & Salehnia, N. (2022). Long-term effects of temperature and precipitation on economic growth of selected MENA region countries. Environment, Development and Sustainability, 1-19.

13. Niu, S., Ding, Y., Niu, Y., Li, Y., & Luo, G. (2011). Economic growth, energy conservation and emissions reduction: A comparative analysis based on panel data for 8 Asian-Pacific countries. Energy policy, 39(4), 2121-2131.

14. Saidi, K., & Hammami, S. (2015). The impact of energy consumption and CO2 emissions on economic growth: Fresh evidence from dynamic simultaneous-equations models. Sustainable Cities and Society, 14, 178-186.

15. Xie, X., & Li, K. (2022). Measuring total‐factor energy environment efficiency, energy‐saving and carbon emission‐reduction potential in China's food industry: Based on a meta‐frontier slacks‐based measure model. Food and Energy Security, 11(1), e324.

16. Yang, T., Chen, W., Zhou, K., & Ren, M. (2018). Regional energy efficiency evaluation in China: A super efficiency slack-based measure model with undesirable outputs. Journal of cleaner production, 198, 859-866.

17. Zhou, P., & Ang, B. W. (2008). Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy, 36(8), 2911-2916.

18. Zhou, P., Ang, B. W., & Han, J. Y. (2010). Total factor carbon emission performance: a Malmquist index analysis. Energy Economics, 32(1), 194-201.