New Energy Development and Pollution Emissions in China
Bibliographic Data
| ID | 15480254 |
|---|---|
| Authors | Ying Li (0000-0003-0678-9535, Sichuan University), Yung-Ho Chiu (0000-0002-9702-2892, Soochow University, corresponding author), Liang Chun Lu (0000-0001-7079-2443, Soochow University) |
| Year | 2019 |
| Volume | 16 |
| Issue | 10 |
| Pages | 1764-1764 |
| Publication date | 2019-05-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph16101764 |
| PMID | 31109040 |
| OpenAlex | W2945750580 |
| Language | EN |
| Citations received | 2 |
| References cited | 49 |
China's rapid economic growth is accompanied by increasing energy consumption and severe environmental problems. As sustainable development can only be achieved by reducing energy intensity, new energy and renewable energy investment, as well as improving traditional energy efficiency, is becoming increasingly important. However, past energy efficiency assessments using data envelopment analysis (DEA) models mostly focused on radial and non-radial DEA model analyses. However, traditional radial DEA models ignore non-radial slacks when evaluating efficiency values, and non-radial DEA models ignore the same proportionality as radial DEA when evaluating efficiency value slacks. To balance the radial and non-radial model characteristics and consider undesirable output, this study combines a modified Epsilou-based measure (EBM) DEA and undesirable output and proposes a modified undesirable EBM DEA model to analyze the efficiency of China's new and traditional energy sources. The empirical results found that (1) most new energy investment in most municipalities/provinces rapidly grew from 2013 to 2016; (2) as the annual efficiency score was only 1 in Beijing, Inner Mongolia, Shanghai, and Tianjin, the other 26 municipalities/provinces need significant improvements; (3) traditional energy efficiency scores were higher than new energy efficiency; and (4) NO 2 efficiencies are slightly better than CO 2 and SO 2 efficiencies
Beijing · China · Data envelopment analysis · Econometrics · Economics · Efficient energy use · Energy consumption · Environmental economics · Greenhouse gas · Investment (military · Renewable energy · Statistics · Efficiency Analysis Using DEA · Energy, Environment, Economic Growth · Engineering · Environmental Impact and Sustainability · Environmental Science · Mathematics
Dynamic DEA
The dynamic impact of renewable energy consumption on CO 2 emissions
Total-factor energy efficiency of regions in China
Renewable energy consumption and economic growth
Measuring the efficiency of decision making units
The Measurement of Productive Efficiency
A slacks-based measure of efficiency in data envelopment analysis
Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
An integration model of DEA and RST for measuring transport sustainability
Measuring and decomposing sustainable efficiency in agricultural production
Efficiency in Brazil's industrial sectors in terms of energy and sustainable development
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,29 |
| Citation span | 2019 - 2019 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |