| Title |
Eco-Efficiency Analysis of Industrial Systems in the Songhua River Basin: A Decomposition Model Approach |
| ID_Doc |
7918 |
| Authors |
Guo, FY; Lo, K; Tong, LJ |
| Title |
Eco-Efficiency Analysis of Industrial Systems in the Songhua River Basin: A Decomposition Model Approach |
| Year |
2016 |
| Published |
Sustainability, 8, 12 |
| DOI |
10.3390/su8121271 |
| Abstract |
Eco-efficiency is an important sustainable development and circular economy construct that conceptualizes the relationship between industrial output, resource utilization, and environmental impacts. This paper conducts an eco-efficiency analysis for basin industrial systems using the decomposition model approach. Using data on 10 cities in China's Songhua River basin, we illustrate the evolutionary characteristics and influencing factors of industrial systems' eco-efficiency. The results indicate that cities in upstream and midstream areas focus on improving resource efficiency, whereas cities in downstream areas focus on improving terminal control efficiency. The results also show that the government plays an increasingly important role in promoting eco-efficiency and that significant differences in the influencing factors exist among the upstream area, midstream area, and downstream area. Our results offer deeper insights into the eco-efficiency of industrial systems and give further hints on how policy-making can help achieve sustainable development, balancing between economic activities and environmental protection. |
| Author Keywords |
industrial system; environmental impact; spatiotemporal difference; eco-efficiency; Songhua River basin; China |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000389317100062 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
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