College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China; Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Avenue, Nanjing 211106, China.
School of Accounting, Nanjing Audit University, Nanjing, Jiangsu 211815, China.
Sci Total Environ. 2020 May 10;716:135009. doi: 10.1016/j.scitotenv.2019.135009. Epub 2019 Nov 16.
Rapid economic growth of China's industry has brought many problems. Among them, the problems of energy shortage and environmental pollution have become increasingly serious. The quick development of the big data has brought new challenges and opportunities for environmental management. In this paper, we propose a new data envelopment analysis (DEA) model to analyze the energy and environmental efficiency of industrial sectors from China's 30 provincial-level regions in order to determine the potential and route for energy saving (ES) and carbon emission reduction (CER). The new DEA model not only considers the dynamic data, but also involves the technology heterogeneity and closest targets, which could achieve the potential or provide the route for ES and CER step by step with least effort. The new approach is illustrated by using the regional industrial dataset of China and some implications for ES and CER are proposed.
中国工业的快速经济增长带来了许多问题。其中，能源短缺和环境污染问题变得越来越严重。大数据的快速发展为环境管理带来了新的挑战和机遇。在本文中，我们提出了一种新的数据包络分析（DEA）模型，以分析中国 30 个省级地区工业部门的能源和环境效率，以确定节能（ES）和碳减排（CER）的潜力和途径。新的 DEA 模型不仅考虑了动态数据，还涉及技术异质性和最接近的目标，可以逐步以最小的努力实现 ES 和 CER 的潜力或提供途径。该新方法通过使用中国的区域工业数据集进行了说明，并提出了一些关于 ES 和 CER 的启示。
