Recently, in accordance with global environmental conservation awareness, undesirable outputs of production and social activities (e.g.. air pollutants) have harmful social and environmental dimensions especially in developing countries. Therefore, this study discusses how to apply Data Environment Analysis (DEA) for environmental assessment. However, previous DEA research has documented a limited use of DEA on envirommental assessment. A unique feature of DEA-based environmental assessment is that it needs to classify outputs into desirable and undesirable outputs. On the other hand. there is a lack of literatures in field of measuring on economic and environmental energy efficiency between ISIC codes. Therefore, this paper measured the energy efficiency of Iran's main ISIC sub sectors using non linear.DEA approach. Results indicated that between studied ISIC codes. the codes 15 and 24 have most economic (0.97 and 1.00) and environmental (1.00 and 0.82) efficiency. respectively. Also. in comparison with the other studied ISIC codes, the code 23 is economically and environmentally inefficient (0.28 and 0.32)

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