Structural complexity analysis for industrial ecosystems: A case study on LuBei industrial ecosystem in China

Chen, Liang; Wang, Rusong; Yang, Jianxin; Shi, Yongliang

doi:10.1016/j.ecocom.2009.10.007

Cited by 16 publications

(7 citation statements)

References 34 publications

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“…According to the key literature reviewed related to the IS planning and development, several research attempts were recognized in which the emergence and the development of IS solutions have been promoted. Among those, Chen et al (2010) proposed the structural analysis method for industrial ecosystems (SAMIE) to apply in analyzing the structural complexity and the efficiency.…”

Section: Extent Of Strategies To Overcome the Identified Issuesmentioning

confidence: 99%

Optimizing the Efficiency of Resource Exchange in Industrial Symbiosis (IS)

Mallawarachchi¹,

Karunasena²,

Sandanayake³

2020

Encyclopedia of the UN Sustainable Development Goals

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Section: Extent Of Strategies To Overcome the Identified Issuesmentioning

confidence: 99%

Optimizing the Efficiency of Resource Exchange in Industrial Symbiosis (IS)

Mallawarachchi¹,

Karunasena²,

Sandanayake³

2020

Encyclopedia of the UN Sustainable Development Goals

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“…In this system, the quantitative relationship between input and output, supply and demand of different industries, appears as the static aspect of the industrial system, while the interaction and restriction between industries in intermediate production processes appears as the dynamic aspect [9]. In the process of continuous development and evolution of the industrial ecosystem, it is affected by a continuous interweaving and integration of various internal and external factors in both spatial and temporal dimensions [10][11][12]. e change of one (or a group of ) element(s) in the system may cause a spatial and temporal change in other elements and even in the entire system [13].…”

Section: Introductionmentioning

confidence: 99%

Synergistic Evaluation and Constraint Factor Analysis on Urban Industrial Ecosystems of Traditional Industrial Area in China

Liu

et al. 2020

Complexity

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Industrial ecology is an advanced form and ideal model of modern industrial development, in which the industrial ecosystem is the core. Based on the PSR model, this paper builds a comprehensive evaluation index system for urban industrial ecosystem development and selects 14 prefecture-level cities in Liaoning Province of the traditional industrial area in Northeastern China as cases to calculate the development level of its industrial ecosystem during 2000–2018 using an improved Topsis method and then to conduct a spatial visualization analysis. Finally, based on the “stress-state-response” subsystem, this paper diagnoses the constraints for industrial ecosystem development, which can provide a reference basis for decision-making in industrial ecology of traditional industrial area represented by those in Northeast China. The results show the following: (1) From 2000 to 2018, the industrial ecology of the 14 cities in Liaoning Province was at a medium level. Except for Shenyang and Dalian with the rapid development, the difference of industrial ecosystem development for other cities was relatively small. (2) From 2000 to 2018, the industrial ecosystem development of each city was in a status of “either increasing, or decreasing, or fluctuating,” which generally raised first and then decreased. Regarding spatial difference, the development exhibited a “center-periphery” pattern, with Shenyang and Dalian as the “dual-core” that were increasingly strengthened with significantly high-level industrial ecology. (3) At system level, PSR constraint grades for the industrial ecosystem development in the 14 cities of Liaoning Province were different. Constraint grades in the pressure subsystem, the state subsystem, and the response subsystem for the industrial ecosystem of Liaoning were 45.73%, 20.01%, and 34.34%, respectively, indicating that the lack of human response to the ecological environment and the pressure of human activities on the ecological environment during the industrial economy development were the main constraints affecting the process of industrial ecology in these cities. (4) Due to the differences in geographical environments, economic bases, industrial structures, and local development contexts, the major constraint factors of industrial ecosystem development in different cities are significantly different and complicated; however, there are five factors that are generally considered as major constraint factors in all cities, i.e., regional GDP, number of labor force employed in the secondary industrial sector, gross investment in fixed assets, amount of industrial sulfur dioxide removal, and production value from “three-wastes” comprehensive utilization. At last, this paper puts forward some recommendations and suggestions for providing scientific support for industrial ecosystem construction in the traditional industrial area of Northeastern China.

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“…Hence the concept of industrial metabolism is first established by Ayres, which is defined as “ the whole integrated collection of physical processes that convert raw materials and energy, plus labor, into finished products and wastes ” [18, 19]. The summary of industrial metabolism is analyzing the whole material flows, extracting all possible emission sources, and assessing the influences within these flows [20]. After that, Graedel shows a good example in using statistical indexes of food web from natural ecosystems for reference in his evaluations of EIPs [21].…”

Section: Introductionmentioning

confidence: 99%

“…One of them is generally based on the inventorying of life-cycle ecological and economic input-output flows, including material flow analysis [3, 22], input-output analysis [23], life-cycle assessment [24], and structure and network analysis based on industrial metabolism [20, 25, 26]. The other method is concerned with the idea of the available solar energy.…”

Section: Introductionmentioning

confidence: 99%

Ecological Network Analysis for a Low-Carbon and High-Tech Industrial Park

Liu

et al. 2012

The Scientific World Journal

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Industrial sector is one of the indispensable contributors in global warming. Even if the occurrence of ecoindustrial parks (EIPs) seems to be a good improvement in saving ecological crises, there is still a lack of definitional clarity and in-depth researches on low-carbon industrial parks. In order to reveal the processes of carbon metabolism in a low-carbon high-tech industrial park, we selected Beijing Development Area (BDA) International Business Park in Beijing, China as case study, establishing a seven-compartment- model low-carbon metabolic network based on the methodology of Ecological Network Analysis (ENA). Integrating the Network Utility Analysis (NUA), Network Control Analysis (NCA), and system-wide indicators, we compartmentalized system sectors into ecological structure and analyzed dependence and control degree based on carbon metabolism. The results suggest that indirect flows reveal more mutuality and exploitation relation between system compartments and they are prone to positive sides for the stability of the whole system. The ecological structure develops well as an approximate pyramidal structure, and the carbon metabolism of BDA proves self-mutualistic and sustainable. Construction and waste management were found to be two active sectors impacting carbon metabolism, which was mainly regulated by internal and external environment.

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Structural complexity analysis for industrial ecosystems: A case study on LuBei industrial ecosystem in China

Cited by 16 publications

References 34 publications

Optimizing the Efficiency of Resource Exchange in Industrial Symbiosis (IS)

Optimizing the Efficiency of Resource Exchange in Industrial Symbiosis (IS)

Synergistic Evaluation and Constraint Factor Analysis on Urban Industrial Ecosystems of Traditional Industrial Area in China

Ecological Network Analysis for a Low-Carbon and High-Tech Industrial Park

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