Technological innovation plays a crucial role for improving energy efficiency. But the excessive energy consumption has presented a significant challenge at the same time, which indicates that the direct energy rebound effect exists in China. Cobb-Douglas production function and Logarithmic Mean Divisia Index decomposition model are employed to analyze the rebound effect of energy consumption of all three main industries sector in China. The results show that total technological effect curve and total substitution effect curve fluctuated more significantly than total structure effect curve from 1991 to 2014.The first two curves were the most critical factors for the energy consumption intensity. Stabilizing energy prices, developing new and renewable energy and implementing policies related to energy conservation and emission reduction are effective measures to reduce energy consumption intensity. More attention should be paid to the growing demand for living energy consumption derived from the rapid development of the tertiary industry. The direct rebound effect of energy consumption in China showed an overall descending trend. This shows that technological effect has well prevented the growth of energy consumption. Direct energy rebound effect can be controlled effectively by means of formulating and implementing the corresponding energy related policies.

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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.

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