Literature DB >> 31839293

The potential for energy saving and carbon emission reduction in China's regional industrial sectors.

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.
Copyright © 2019 Elsevier B.V. All rights reserved.

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


  1 in total

1.  A Novel Optimization Model and Application of Optimal Formula Design for CuxCo1-xFe2O4 Spinel-Based Coating Slurry in Relation to Near and Middle Infrared Radiation Strengthening.

Authors:  Haiqing Du; Haifei An; Jian Zhang; Yuhao Ding; Chao Lian; Hao Bai
Journal:  Materials (Basel)       Date:  2020-05-19       Impact factor: 3.623

  1 in total

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