| Literature DB >> 31839293 |
Qingyuan Zhu1, Xingchen Li2, Feng Li3, Dequn Zhou4.
Abstract
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.Entities:
Keywords: Big data; Carbon emission reduction; Data envelopment analysis; Energy saving
Year: 2019 PMID: 31839293 DOI: 10.1016/j.scitotenv.2019.135009
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963