Unified network analysis on the organization of an industrial metabolic system

Fan, Yupeng; Qiao, Qi; Chen, Weiping

doi:10.1016/j.resconrec.2017.05.009

Cited by 19 publications

(6 citation statements)

References 43 publications

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“…ENA provides an analytical tool for various applications to study metabolism in cities from different perspectives i.e. ecological hierarchy relationship, spatial variation, energy flows in previous scholarly researches (Chen and Chen, 2014;Fan et al, 2017;Fath and Borrett, 2006;Fath et al 2010;Zhang et al, 2010Zhang et al, , 2016. The technique of ENA is not limited to intra-system flows scaled on a single level such as city, region or country but also applied to study interregional energy flows between connected cities at combined levels, as demonstrated in the case study of Beijing-Tianjin-Hebei in China (Zheng et al, in press).…”

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confidence: 99%

Ecological network analysis on intra-city metabolism of functional urban areas in England and Wales

Tan

Arbabi

et al. 2018

Resources, Conservation and Recycling

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The UK has one of the world's most urbanised societies where nearly 83% of the total population lives 13 in cities. The continuing population growth could lead to increases in environmental pollutions and congestion within cities. The framework of urban metabolism uses an analogy between cities and ecosystems to study the 15 metabolic processes within complex urban systems akin to natural biological systems. It remains as a challenge 16 to fully understand the complicated distribution of resource flows within an urban network. In this paper, 17 Ecological Network Analysis was applied to study the intra-city flows between economic sectors in 35 functional 18 urban areas in order to investigate their respective metabolic relationships. The intra-city flows network of each area was also supplemented with the geographical distance between the workplace zones to study the impacts of spatial distribution on the density of resource flows. The metabolic systems were dominated by 64% of exploitative relationships with an average mutualism index of 0.93 and synergism index of 3.56 across all 35 areas. The consumption-control and production-dependency relationships revealed the hierarchical orders among the sectors resembling the pyramidal structure of an urban ecosystem. Network community classification emphasized the importance of interrelationship within the organisation of each community class. The producertype and consumer-type communities showed the tendencies of those sectors to cluster based on their respective hierarchical roles in the ecosystem. This work provides an insight into the wide range of intra-city ecological metabolic characteristics which can potentially expand to a multi-scale assessment of urban metabolism across the country.

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confidence: 99%

Ecological network analysis on intra-city metabolism of functional urban areas in England and Wales

Tan

Arbabi

et al. 2018

Resources, Conservation and Recycling

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“…SNA explores the spatial association of a region as a whole, breaking away from the limitation of “adjacency” of traditional spatial measurement methods [ 82 ]. It provides algebraic analysis and visual expression of social relations [ 83 ], and has become a popular interdisciplinary academic method [ 84 ]. At present, the social network analysis method has been widely used in many fields such as tourism flow [ 85 , 86 ], energy consumption [ 87 , 88 ], environmental protection [ 89 , 90 ].…”

Section: Methodsmentioning

confidence: 99%

Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration

Sun

Hou

2021

IJERPH

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Based on the panel data of 41 cities in the Yangtze River Delta from 2008 to 2017, this paper constructs an evaluation indicators system for urban tourism eco-efficiency. By measuring the tourism eco-efficiency in the Yangtze River Delta urban agglomeration, we analyze its spatial-temporal evolution characteristics. Furthermore, the modified gravity model and social network analysis are introduced to explore the spatial network structure of tourism eco-efficiency and its evolution trend.The results show that:(1) The overall eco-efficiency of tourism in the Yangtze River Delta region presents a fluctuating downward trend, among which Jiangsu and Zhejiang have high eco-efficiency, Shanghai and Anhui are relatively low. The gap within the region first increased and then decreased. (2) During this decade, the spatial network structure of tourism eco-efficiency in the Yangtze River Delta has become increasingly loose. The weakening of the network connection strength has led to a decrease in the regional tourism eco-efficiency to a great extent. (3) The network centrality of cities such as Zhoushan, Huzhou, and Huangshan has always maintained a high level, and these cities have firmly occupied the core position of network. (4) The spatial association network of tourism eco-efficiency can be divided into four blocks: “two-way spillover”, “net spillover”, “net benefit” and “agent”. The synergy and spillover effect between various blocks are significant, and there is a spatial polarization trend centered on a few cities. Based on this, this paper puts forward optimization suggestions for the spatial network structure of the Yangtze River Delta urban agglomeration, in anticipation of promoting the improvement of regional tourism eco-efficiency.

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“…As shown in Equations ( 15) and ( 16), in addition to the directly associated nodes, there was also a dependency relationship between the nodes and the remaining nodes (Fan et al, 2017), and minor change occurred in the trend between the dependency degree of the nodes of both scenarios. Through the direct and indirect flow of substances between nodes, the complete dependence of FP on SA was the greatest in both scenarios.…”

Section: Direct and Complete Consumption Coefficientsmentioning

confidence: 99%

“…Presently, IMA is primarily used to investigate waste treatment aspects (Tazi et al., 2019) or in combination with material flow analysis (MFA) to track and analyze chemical processing of copper, sulfur, and chlorine in industrial parks (Han et al., 2016; Ma et al., 2016). IMA can provide suggestions for improving urban wastewater metabolism (Guan et al., 2019), by developing ecological networks in industrial parks, and implementing a circular economy in ecological industrial parks (Fan et al., 2017; Gómez et al., 2018). IMA models are mainly used for the analysis of economic and material flows (Hawkins et al., 2007), and waste input–output (Nakamura et al., 2007).…”

Section: Introductionmentioning

confidence: 99%

Industrial metabolism analysis of a Chinese wine industry chain based on material flow and input–output analyses

Liu

Jia

et al. 2021

J of Industrial Ecology

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Recently, Chinese wine industry has developed rapidly and its sustainability has attracted increasing attention. However, the existing wine industry chain is short and its metabolic pathway and metabolic efficiency remain unknown. Therefore, we selected a representative wine company in China to conduct industrial metabolism analysis (IMA) research based on material flow analysis (MFA) and input–output analysis. MFA model and input–output matrix for the traditional industry chain (TIC) and ecological industry chain (EIC) of the investigated company were established to explore the material flow relationship between the industrial structure and the nodes. A new IMA evaluation index system was developed to evaluate the industrial metabolic efficiency and development trends of two scenarios considered in the study. The results showed that the addition of nodes in EIC promoted the reuse of byproducts and wastes, and reduced the waste of resources. The industrial metabolic efficiency of EIC was also higher than that of TIC. For example, the node material cycle coefficient (Ri) during the preliminary treatment and pressing and fermentation of EIC was increased by 0.041 and 0.127, respectively, compared with TIC. A correlation analysis showed that EIC nodes had stronger pull and push effects on upstream and downstream than those of TIC, and the influence coefficient (Uj) of viticulture and pressing and fermentation increased by 0.168 and 0.112, respectively. This study provides a scientific basis for optimizing the wine industrial layout, improving the overall environmental performance of the industry chain, and promoting sustainable development.

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Unified network analysis on the organization of an industrial metabolic system

Cited by 19 publications

References 43 publications

Ecological network analysis on intra-city metabolism of functional urban areas in England and Wales

Ecological network analysis on intra-city metabolism of functional urban areas in England and Wales

Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration

Industrial metabolism analysis of a Chinese wine industry chain based on material flow and input–output analyses

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