Ecosystem health pattern analysis of urban clusters based on emergy synthesis: Results and implication for management

Su, M., Fath, B.D. ORCID: https://orcid.org/0000-0001-9440-6842, Yang, Z., Chen, B., & Liu, G. (2013). Ecosystem health pattern analysis of urban clusters based on emergy synthesis: Results and implication for management. Energy Policy 59 600-613. 10.1016/j.enpol.2013.04.015.

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Abstract

The evaluation of ecosystem health in urban clusters will help establish effective management that promotes sustainable regional development. To standardize the application of emergy synthesis and set pair analysis (EM-SPA) in ecosystem health assessment, a procedure for using EM-SPA models was established in this paper by combining the ability of emergy synthesis to reflect health status from a biophysical perspective with the ability of set pair analysis to describe extensive relationships among different variables. Based on the EM-SA model, the relative health levels of selected urban clusters and their related ecosystem health patterns were characterized. The health states of three typical Chinese urban clusters - Jing-Jin-Tang, Yangtze River Delta, and Pearl River Delta - were investigated using the model. The results showed that the health status of the Pearl River Delta was relatively good; the health for the Yangtze River Delta was poor. As for the specific health characteristics, the Pearl River Delta and Yangtze River Delta urban clusters were relatively strong in Vigor, Resilience, and Urban ecosystem service function maintenance, while the Jing-Jin-Tang was relatively strong in organizational structure and environmental impact. Guidelines for managing these different urban clusters were put forward based on the analysis of the results of this study.

Item Type: Article
Uncontrolled Keywords: Ecosystem health pattern; Chinese urban cluster; Emergy
Research Programs: Advanced Systems Analysis (ASA)
Bibliographic Reference: Energy Policy; 59:600-613 (August 2013) (Published online 29 April 2013)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 08:48
Last Modified: 27 Aug 2021 17:23
URI: https://pure.iiasa.ac.at/10417

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