Emergy-based comparative analysis on industrial clusters: economic and technological development zone of Shenyang area, China.
In China, local governments of many areas prefer to give priority to the development of heavy industrial clusters in pursuit of high value of gross domestic production (GDP) growth to get political achievements, which usually results in higher costs from ecological degradation and environmental pollution. Therefore, effective methods and reasonable evaluation system are urgently needed to evaluate the overall efficiency of industrial clusters. Emergy methods links economic and ecological systems together, which can evaluate the contribution of ecological products and services as well as the load placed on environmental systems. This method has been successfully applied in many case studies of ecosystem but seldom in industrial clusters. This study applied the methodology of emergy analysis to perform the efficiency of industrial clusters through a series of emergy-based indices as well as the proposed indicators. A case study of Shenyang Economic Technological Development Area (SETDA) was investigated to show the emergy method's practical potential to evaluate industrial clusters to inform environmental policy making. The results of our study showed that the industrial cluster of electric equipment and electronic manufacturing produced the most economic value and had the highest efficiency of energy utilization among the four industrial clusters. However, the sustainability index of the industrial cluster of food and beverage processing was better than the other industrial clusters.
Institute of Applied Ecology, Chinese Academy of Science, Shenyang, Liaoning Province, 110016, People's Republic of China, liuzhe@iae.ac.cn.
Zhe
Z
Liu
Yong
Y
Geng
Pan
P
Zhang
Huijuan
H
Dong
Zuoxi
Z
Liu
D002681:China; D003246:Conservation of Energy Resources; D003247:Conservation of Natural Resources / Q000379:methods; D004463:Ecology; D017753:Ecosystem; D004777:Environment; D004787:Environmental Pollution; D007221:Industry / Q000191:economics / Q000706:statistics & numerical data*