Evaluation and optimization of blanket production from recycled polyethylene terephthalate based on the coordination of environment, economy, and society.

The recycling of waste polyethylene terephthalate (PET) is widely regarded as an eco-friendly and cost-effective technology and has been gradually developed into an important direction for the utilization of solid waste resources. However, the integrated evaluation research on this technology from the environmental, economic, and social aspects are still not in place. Based on the theory of collaborative entropy, this study constructs an integrated evaluation and optimization methodology system for the environmental, economic, and social impacts of blanket production from recycled PET, using environmental life cycle assessment, life cycle cost assessment, social life cycle assessment, and sensitivity analysis. The study assessed the environmental load, economic cost, and social impact of blanket production from recycled PET, and then identified the key processes through sensitivity analysis. In addition, the graphical method and the principle of collaborative entropy model are applied to evaluate two of the environmental load, economic cost, and social impact in the blanket production from recycled PET. The results of the two methods are consistent, which indicates that to carry out multi-objective integrated evaluation with collaborative entropy model have good reliability. Moreover, the quantified results of collaborative entropy showed that the key processes that affected the coordinated development of the environment, economy, and society were organic chemicals usage process, electricity generation process, and direct air emission process. Based on the "Reduce-Reuse-Recycle" theory and the position of key processes in the system, feasible optimization suggestions were proposed. The establishment of this methodology system could provide theoretical and practical references for other waste utilization industry.

Robustness of eco-industrial symbiosis network: a case study of China.

As a complex network, eco-industrial symbiosis network is featured with complexity, openness, and non-linearity. A methodology is proposed to analyze and optimize the eco-industrial symbiosis network from the perspective of complex network theory. Structural robustness index and performance robustness index are established as the analysis model. Consequently, a robust method is developed to optimize the eco-industrial symbiosis network system based on the percolation theory. A conceptual framework is put forward to improve the robustness of eco-industrial symbiosis network system by introducing the "spare core" enterprise which is validated by quantitative analysis. The empirical results show that the robustness of eco-industrial symbiosis network varies under both random failure and intentional disturbance scenarios. However, eco-industrial symbiosis network system has strong self-regulation capability as long as the core enterprise is still in operation. It is recommended that supplementary chain could be added to those enterprises with lower network node connectivity to form "spare core" enterprise. This can not only effectively reduce the dependence of other enterprises on core enterprises, but also further improve the robustness of eco-industrial symbiosis network. This methodology is practically validated by a case analysis of eco-industrial park in China. The findings provide useful inputs to the design and operation of eco-industrial parks.

Investigating vulnerability of ecological industrial symbiosis network based on automatic control theory.

System fluctuations of eco-industrial symbiosis network (EISN) organization due to disturbance are very similar to the controller adjustment in the automatic control theory. Thus, a methodology is proposed in this study to assess the vulnerability of EISN based on the automatic control theory. The results show that the regulator plays a key role to enhance the resilience of the network system to vulnerability. Therefore, it is imperative to strengthen the real-time regulation and control of EISN so that the system stability is improved. In order to further explore the impact of various regulations on the system vulnerability, the influence of system stability is simulated by means of proportional, differential, and integral control. A case study with Guigang eco-industrial park (EIP) was undertaken to test this model. The results showed that when the system was disturbed at different positions, the key nodes which had great influence on system vulnerability could be selected according to the magnitude of simulation curve. By changing the ratio coefficient of proportional, differential, and integral units to adjust the ecological chain network, the system's resilience to vulnerability can be enhanced. Firstly, if basic conditions of EISN organization remain unchanged, the integral control of the policy support and infrastructure sharing should be strengthened. Secondly, the differential regulation should be improved continuously for the technological innovation capability of key node enterprises. Finally, the key chain filling projects should be introduced for proportional control so that the chain network design can be optimized from the source.