Evidence map›Paper›PMID 30032373›Full record

ArticleEnvironmental science and pollution research international2018

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

Qingsong Wang, Hongrui Tang, Xueliang Yuan, Jian Zuo, Jian Zhang, Zhenlei Gao, Jinglan Hong

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Article in Environmental science and pollution research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Qingsong WangSchool of Energy and Power Engineering, Shandong University, 17923 Jingshi Road, Jinan, 250061, China.
Hongrui TangSchool of Energy and Power Engineering, Shandong University, 17923 Jingshi Road, Jinan, 250061, China.
Xueliang YuanSchool of Energy and Power Engineering, Shandong University, 17923 Jingshi Road, Jinan, 250061, China. yuanxl@sdu.edu.cn.ORCID http://orcid.org/0000-0002-7331-1059
Jian ZuoSchool of Architecture and Built Environment, Entrepreneurship, Commercialisation and Innovation Centre (ECIC), The University of Adelaide, Adelaide, SA, 5005, Australia.
Jian ZhangSchool of Environmental Science and Engineering, Shandong University, 27 Shanda Road, Jinan, 250100, China.
Zhenlei GaoSchool of Energy and Power Engineering, Shandong University, 17923 Jingshi Road, Jinan, 250061, China.
Jinglan HongSchool of Environmental Science and Engineering, Shandong University, 27 Shanda Road, Jinan, 250100, China.

Funding

Fundamental Research Funds of Shandong University 2015JC056Innovation Fund of Shandong University IFYT1401, IFYT14010Key R&D Plan of Shandong Province 2018GSF121005National Key R&D Plan 2017YFC0703100National Natural Science Foundation of China (CN) 41471461
6 · The paper itself

Abstract

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.

Indexed as

EcologyIndustryModels, TheoreticalSystems TheoryAutomatic controlRegulation effectSymbiosis networkVulnerability

Identifiers

PMID30032373

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.