Industrial Symbiosis Networks Research Articles

Filtering ‘3-2’ Industrial Symbiosis Networks at a Carbon-Intensive Cluster in a Small Island Developing State to Reuse CO2 and Water

Small island developing states (SIDS) face internal and external pressures for more sustainable manufacturing e.g., economic and ecological water provision, and anti-carbon leakage tariffs. As SIDS have special developmental challenges, locally appropriate strategies are needed. In one of these SIDS, Trinidad and Tobago, is a carbon-intensive industrial cluster of global standing, the Point Lisas Industrial Estate (PLIE). So, to investigate ‘3-2’ industrial symbiosis (IS) on the PLIE, a simple enterprise input-output MILP model of a representative IS network was developed. Different quality wastewater streams and high-purity process CO2 from ammonia processes were selected as materials to be reused in: existing petrochemical plants, a mineral carbonate factory and a propylene carbonate plant. To filter the IS relations, economic and environmental objectives were set for each material. Combining economic objectives left a tri-objective problem, which was resolved with ε-constraint optimization and multi-criteria decision-making methods. Kleinberg's hub and authority scores were found to give beneficial insight into the solved IS networks. Potential revenue-generating opportunities were uncovered for sharing and reusing water and process CO2. The results suggest adding two proposed carbonate factories could increase the mass of CO2 reused in the cluster by 10.4% and mitigate releasing 5 Tg/y of rejected desalination brine.

Facilitator roles for knowledge sharing in industrial symbiosis networks during emergence

Facilitator roles for knowledge sharing in industrial symbiosis networks during emergence

A blockchain architecture with smart contracts for an additive symbiotic network - a case study

AbstractAdopting innovative technologies such as blockchain and additive manufacturing can help organisations promote the development of additive symbiotic networks, thus pursuing higher sustainable goals and implementing circular economy strategies. These symbiotic networks correspond to industrial symbiosis networks in which wastes and by-products from other industries are incorporated into additive manufacturing processes. The adoption of blockchain technology in such a context is still in a nascent stage. Using the case study method, this research demonstrates the adoption of blockchain technology in an additive symbiotic network of a real-life context. The requirements to use a blockchain network are identified, and an architecture based on smart contracts is proposed as an enabler of the additive symbiotic network under study. The proposed solution uses the Hyperledger Fabric Attribute-Based Access Control as the distributed ledger technology. Even though this solution is still in the proof-of-concept stage, the results show that adopting it would allow the elimination of intermediary entities, keep available tracking records of the resources exchanged, and improve trust among the symbiotic stakeholders (that do not have any trust or cooperation mechanisms established before the symbiotic relationship). This study highlights that the complexity associated with introducing a novel technology and the technology’s immaturity compared to other data storage technologies are some of the main challenges related to using blockchain technology in additive symbiotic networks.

Investigating the use of network analysis metrics to benchmark Industrial Symbiosis development

Circular economy (CE) aims to reduce natural resource consumption, waste generation, and related detrimental environmental, social, and economic impacts by keeping valuable materials circulating in the economy. Industrial Symbiosis (IS) contributes to CE through byproduct-exchange partnerships between firms, reducing raw material use, emissions, and waste generation, while promoting the economic growth of partner firms. However, most IS projects fail in the early stages and do not reap the full sustainability benefits of IS. A significant reason for the failure of early-stage IS projects is the lack of knowledge regarding the strategic organization of IS networks. Quantifying IS network organization and operational characteristics and benchmarking IS development can address this challenge, and enable knowledge transfer regarding IS network organization from mature IS networks to guide the advancement of new IS projects. This investigation tests multiple Ecological Network Analysis (ENA) and Social Network Analysis (SNA) metrics using three real-world IS case studies, as potential IS benchmarking tools. The results of the investigation show that ENA and SNA metrics can be used to compare IS networks and identify differences in the following characteristics: Partnership prevalence, producer–consumer relationships, linkage distribution, resource utilization, effect of indirect firm relationships, network cohesion, and network centralization. The values of the multiple network analysis metrics are found to be aligned with the development time of the IS networks and the qualitative markers of IS development stages as identified in the literature. For example, the analysis of producer–consumer relationships indicated that more than 50% of the consumer firms in the early stage IS networks had only one supplier partnership compared to less than 30% of the firms in the most mature IS network. Similarly, the analysis of network cohesion showed that the early-stage IS networks had (on average) five different isolated groups of firms compared to one cohesive group of firms in the more mature IS networks. This investigation demonstrates that network analysis of IS projects only requires anonymized and non-proprietary data, and identifies data-collection and modeling standards needed to develop an IS benchmarking framework using network analysis. The promising results of this investigation motivate future work into these standardization needs and the development of IS benchmarks using network analysis.

Blockchain-based concept for total site heat integration: A pinch-based smart contract energy management in industrial symbiosis

Industrial symbiosis has gained prominence in pursuing sustainable industrial practices, aiming to optimise resource utilisation and reduce environmental impacts. A critical aspect of this endeavour is the efficient management of energy resources within an industrial ecosystem. This paper presents a novel approach to enhance Total Site Heat Integration (TSHI) implementations by employing Blockchain as a facilitator for decentralised energy management. TSHI is an efficient and widely applied method for industrial symbiosis concerning energy flows, which employs the steam mains in site utility systems as the platform for exchanging heat between industrial processes at various temperature levels. It is shown that the synergy of Pinch Analysis and Smart Contract technologies is capable of facilitating energy integration of processes belonging to independent market actors, compared with the currently dominant integration inside a single company. The proposed framework leverages Blockchain as a distributed ledger to enable secure, transparent, and automated energy management across multiple industrial entities in an industrial symbiotic network. The integration of Pinch Analysis principles ensures that the Heat Integration process is optimised to improve the overall energy efficiency. Smart contracts enable automatic negotiation and execution of energy transactions based on predefined rules, minimising the time lag for concluding deals on energy resource exchange and conservation. This paper examines several scenarios to illustrate the implementation of the proposed Blockchain-based TSHI concept within an industrial symbiosis network. It is demonstrated that up to 16 % cost savings are possible by simply enabling transparency via Blockchain. The results could drive innovative development to revolutionise decentralised energy management in a complex industrial ecosystem, especially by synchronising energy exchanges in time.

Distribution of benefits and adverse effects and their role in industrial symbiosis decision-making – A Swedish case study

Industrial symbiosis (IS) has been recognized as an important approach to succeed in the transition towards increased circularity in industry and society. IS involves collaboration between different actors sharing resources, aiming to minimize waste, improve resource and/or energy efficiency, resulting in reduced emissions and environmental impact. This study conducts an embedded single case study at an IS network in Sotenäs, Sweden, where both private and public actors collaborate by exchanging resources. The study identifies benefits and adverse effects of the IS network and explores how these are considered in the actors' decision-making regarding participation. The results indicate that different actors perceive different types and degrees of benefits and adverse effects. To add further value, this study develops an analytical framework for mapping benefits and adverse effects in the form of an impact assessment matrix. The framework maps at what level in society effects accrue and at what point in time they are expected to occur. The results of this study can help understand the role of specific benefits and adverse effects in actors’ decision-making, and show the distribution of effects across societal levels. This knowledge can help understand the complexity of IS networks and thereby facilitate the implementation of IS.

A Review of the Information Technology and Operational Technology Convergence Using Internet of Things within the Circular Economy

Abstract The historical separation of Information Technology and Operational Technology in organizations, particularly in the industrial sector, is being challenged by the digital transformation. This shift towards a converged platform is driven by technological advancements, market pressures, and environmental and regulatory considerations. This paper explores the convergence of Information Technology and Operational Technology through the Internet of Things within the Circular Economy. A comprehensive overview of the current scientific literature is provided using a systematic review method. Initially, the evolving landscape of the Information Technology and Operational Technology integration is reviewed, then Internet of Things and Circular Economy are presented. The findings of this study include the challenges of the converged solution implementation, such as the technical integration complexities, cybersecurity risks, organizational and cultural barriers, and workforce skills gap. Furthermore, the role of the Internet of Things is demonstrated using novel smart circular loops, products, and applications showcasing innovative ideas such as product-as-a-service models, digital circular practices, products with embedded sensors, energy harvesting, and modular and upgrade capabilities as well as novel digital factory use cases such as smart manufacturing and industrial symbiosis networks. The key findings also outline the best practices and recommendations for a successful implementation of this converged infrastructure, highlighting the importance of a strategic implementation and cross-domain collaboration to achieve operational efficiency and environmental sustainability. The insights provided in this paper are valuable for academics, practitioners, and policymakers aimed to understand and harness the digital technologies for advancing sustainable practices towards a smart circular economy.

Selection of waste receiving companies for sustainable industrial symbiosis network: an application a case in Ankara for foundry industry waste

In the past twenty years, besides the technological and innovative efforts for production processes, there have been activities for the recovery and quality improvement of waste based on the development of sustainable solutions. These activities bring us closer to zero waste by protecting natural resources and reducing the environmental impact of production facilities. One of the essential approaches in this process is the industrial symbiosis (IS) approach. Efforts to implement the industrial symbiosis approach in an industrial park constitute the motivation of the study. The study aims to identify alternative enterprises that can evaluate the wastes generated in the main production process of the foundry industry with industrial symbiosis and rank them to establish a symbiotic relationship. First, the Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) model has been developed to evaluate organizational factors, waste-specific factors, and economic and environmental sustainability criteria for establishing an IS network among alternative businesses. Then, alternative businesses were ranked to establish a symbiosis network with the PF-TOPSIS method. The proposed method contributes to the solution of a real-life problem that may arise when there are multiple alternatives to cooperate in the field of industrial symbiosis. By contributing this framework to the literature, the robustness of the results has been demonstrated through sensitivity analysis and comparative analysis. According to the results obtained, it was seen that the importance levels of economic factors came to the fore. Furthermore, among the alternatives, enterprises with high waste exchange potential, such as cement, took first place in the ranking.

The impact of environmental taxation on the structure and performance of industrial symbiosis networks: An agent-based simulation study

How to use appropriate policy measures to intervene industrial symbiosis is valuable in theory but still lacks exploration. This paper discusses the effect of environmental taxation on industrial symbiosis networks. Firstly, the formation mechanism of industrial symbiotic network is analysed with the idea of agent-based modelling. Then, a simulation model was built to simulate the emergence process of industrial symbiosis networks. On this basis, the influence of environmental taxation on the structure and performance of the industrial symbiosis networks is explored. The results show that when the intensity of environmental tax is low, the industrial symbiotic network has the structural characteristics of random network. With the increase of environmental tax intensity, the cyclic ordering of network structure is gradually enhanced. The collection of environmental tax will not only reduce pollution, but also reduce the economic output of the network and reduce enterprise income to a greater extent. Finally, some relevant suggestions for the government to formulate environmental tax policy are provided based on the results.

Agent-based simulation for technology implementation in an energy-based industrial symbiosis network

Agent-based modeling is a promising approach in industrial symbiosis (IS) simulation due to its bottom-up approach. However, the role of implementing feasible technologies in agent-based modeling of IS has been underexplored. In this paper, an agent-based model was developed to optimize the economic benefits of IS stakeholders in a case study region. Feasible technologies were integrated into the proposed model to generate additional economic profit and enhance circularity. The model was implemented on a case study involving a chicken farm, cow farm, dairy, edible oil plant, and a Combined Heat and Power (CHP) plant. Technologies including anaerobic digestion, organic Rankine cycle, heat pump, and membrane separation were employed to produce biogas, recover waste heat, and purify wastewater. While the fossil-based energy consumed by industries reduced, all the waste streams could be recovered. The techno-economic specifications of these technologies had a significant impact on the symbiotic relationships.

A stakeholder decision and road-network-based deterministic model to simulate material flows in regional scale industrial symbioses

Industrial Symbiosis (IS) projects are today well known for their contribution to sustainable development. Designing IS projects implies modelling the quantity of material flows between economic components (ECs), in particular to evaluate the environmental and economic gains obtained through more material circularity and use efficiency. The Industrial Symbiosis concept is now being applied to activities distributed over territories much wider than industrial parks. For such setups, existing modelling methods are becoming strained by the number of economic components involved, their dissemination within heterogeneous landscapes and the resulting complexity of the exchanges. In this paper, we propose a generic, spatially explicit simulation model based on stakeholder decision rules to study regional scale flows quantification between ECs in n-n IS networks. Our approach introduces the use of the Gale-Shapley stable matching algorithm for addressing the many-to-many supply-demand matching problem. The method is deterministic and provides stable solutions that optimise the individual objectives of the ECs. A second introduction considers using transport cost along the road network among the decision rules when ECs preferences are ordered. This solves the issue of correctly estimating travel distance in heterogeneous landscapes where it can be significantly different to the distance as the crow flies. We tested the model with the implementation of two real and concrete case studies related to the bioeconomy of a tropical island: (i) collective storage of fodder and (ii) co-composting platforms. The outputs of the model make it possible to compare scenarios based on EC satisfaction relative to supply and demand as well as the total distance travelled along the road network. Finally, we discuss the limitations and genericity of the model to explore diverse industrial symbiosis projects.

Impact of Transportation Costs on the Establishment of an Industrial Symbiosis Network

The challenges related to natural resource depletion and environmental issues stimulate businesses to look for solutions to overcome them. One of the leading strategies that have emerged from the practical implementation of the circular economy concept is industrial symbiosis, which aims to reduce material extraction and consumption by using the waste (co-product) of one company as input for production processes of another company. This study aims to provide a more profound insight into industrial symbiosis (IS) modeling by considering the transport system impact. To this end, a hybrid approach based on agent-based modeling and system dynamics is presented to comprehensively capture the complexity of interactions between companies and their related impacts on transportation. A case study and numerical example are discussed to validate the proposed approach and related model. The results demonstrate that the development of IS, as expected, is significantly influenced by the transport system.

A two-stage stochastic model for an industrial symbiosis network under uncertain demand

Industrial Symbiosis (IS) networks are structures built by volunteer companies with the aim of exchanging unused or residual resources, benefiting all participating companies. The profitability of these volunteer companies is critical as it affects the sustainability of these networks. Fluctuations in a participating company's production level can potentially disrupt its network by altering the quantity and availability of wastes and by-products. In light of these considerations, we analyse the impact of fluctuations in demand for final products of the companies on company profitability, and waste and by-product usage. For this purpose, we formulated a two-stage stochastic programming model and solved it using the Sample Average Approximation (SAA) method. We tested our model on a theoretical IS network comprising companies in the forest products industry. The results demonstrate that companies in the network keep exchanging by-products and remain profitable despite uncertainties in demand. Consequently, we conclude that the established network exhibits resilience to demand fluctuations, which is an important aspect of its sustainability.

Measuring the symbiotic performance of single entities within networks using an LCA approach

This paper introduces the Symbiotic Performance Indicator, a novel indicator aiming to quantify the environmental benefits generated by by-product exchanges in an industrial symbiosis network. Despite the significant advancements in assessing industrial symbiosis, the lack of indicators for individual entities involved in by-product exchanges hinders a comprehensive understanding of its environmental benefits. This indicator accounts for resource use and greenhouse gas emissions using a life cycle perspective. The resource use is measured using the Cumulative Exergy Extraction from the Natural Environment method, while greenhouse gas emissions are evaluated using the IPCC 2013 Global Warming Potential (100a) method. The use of this indicator is illustrated in a real case study where plastic waste is exchanged among three entities in Mendoza (Argentina). The overall results show that resource use and greenhouse gas emissions can be reduced by 19% and 15%, respectively. Full and partial allocation methods are proposed within the formulation of the Symbiotic Performance Indicator. The indicator results show that the exchange of materials may seem less attractive when using full allocation methods, as one entity gets 100% of the benefits from the by-product exchange compared to the other. Partial allocations make the by-product exchange convenient for both entities which may encourage collaboration. In conclusion, the proposed indicator helps account more precisely for individual environmental benefits behind by-product exchanges, and thus enables better decision-making to set up an industrial symbiosis network.

Connecting organizational context to environmental sustainability initiatives and industrial symbiosis: Empirical results and case analysis

Industrial symbiosis can move us closer to a circular economy and enable efficient and sustainable use of resources. Its potential has however been far from realized, and to increase our understanding of why that is, we investigate drivers, barriers, and outcomes associated with both broadly defined environmental sustainability initiatives and industrial symbiosis from an organizational context perspective. A mixed-methods approach is used, combining statistical analysis of survey material with an embedded case study at an industrial symbiosis network in Sotenäs, Sweden. The position of the customer order decoupling point (CODP), a critical aspect of supply chains that separates forecast-based operations from those tied to specific orders, enables comparisons between organizations with primarily forecast-driven operations from those with primarily order-driven operations. We find that the CODP plays an important role in organizations' commitments to sustainability initiatives in general, as organizations with different CODP positions experience different levels of benefits from such initiatives. We did not find that the CODP position had the same impact for industrial symbiosis initiatives. Our results indicate that both industrial symbiosis, a very specific type of sustainability initiative and collaboration, and environmental sustainability initiatives in a broad sense, are associated with multiple, positive business outcomes. However, case study participants also described that their industrial symbiosis participation was time consuming and associated with an added administrative burden. This could be a reason why such collaborations are not more prevalent, despite the potential of bringing about several positive business outcomes. Finally, our findings indicate that industrial symbiosis may bring business-related benefits to firms regardless of their CODP position, but then in order to understand why such networks are not more prevalent, we recommend that future research investigates ways of quantifying and distributing burdens and rewards associated with industrial symbiosis collaboration.

Prioritizing of sectors for establishing a sustainable industrial symbiosis network with Pythagorean fuzzy AHP- Pythagorean fuzzy TOPSIS method: a case of industrial park in Ankara.

Difficulty in accessing resources and increasing environmental concerns encourage industrial manufacturing enterprises to establish a symbiosis network. The identification of symbiotic relationships contributes to the more sustainable development of industrial activities. However, businesses operating in industrial parks are diversified by sector. In order to establish a sustainable symbiosis network in industrial parks, the symbiotic relations of each sector in industrial parks should be evaluated separately. Thus, the installation process of the symbiosis network will be easier and more sustainable. In this context, this study aims to prioritize the sector in which a symbiosis network will be established by presenting an innovative approach for the evaluation of symbiosis potentials. For this purpose, criteria for the implementation process affecting the establishment of the symbiosis network were determined. Multi-criteria decision-making methods were used to solve the problem. Considering the uncertainties in the process, fuzzy multi-criteria decision-making methods were used. As a result, a decision-making model has been proposed to determine the priority sector in order to establish a symbiosis network in industrial parks. According to the results obtained with the multi-criteria decision-making methods, the number of enterprises that will evaluate the waste, that is, the number of customers with waste, has been determined as the criterion with the highest level of importance. While evaluating the alternatives, the casting sector was chosen as a priority. This sector is followed by the petro and chemical sector as the second alternative.

Conceptualising a Model to Assess the Optimum Water Flow of Industrial Symbiosis (IS)

Industrial Symbiosis (IS) has obtained worldwide concern as a new initiative for achieving collaborative benefits through the exchange of resources including water among industries. Even though these initiatives became prominent as successful projects in the early stages, many of them have resulted in failures in the long term due to the absence of the prior evaluation and optimisation of identified water synergies in IS planning. Further, the main attention has been given to achieving cost reductions in individual plants rather than analysing the environmental benefits of IS networks that can be achieved through the maximum recovery of wastewater. The existing evaluation emphasises the need to have a standardised way to assess the optimum water flow of IS. Thus, the purpose is to conceptualise a model to assess the optimum water flow of IS based on secondary data analysis. A desk study and a detailed literature review were selected as suitable methods for reviewing the existing literature relating to water exchange in IS networks, water input and output flow, and optimisation methodologies. As the key findings derived through analysis, water inputs and outputs, a boundary for the selection of industrial entities, typical water synergies, and optimisation formulas were established. Finally, a conceptual model was developed to assess the optimum water flow of IS, which was evaluated through expert interviews to identify further improvements. The developed model forms a unique foundation for assessing the optimum water flow of IS, applying in any context subject to context-specific enhancements. Most importantly, the novelty can be highlighted as the consideration given to maximum wastewater recovery in achieving the reduction in the freshwater utilisation of industrial entities within the IS network. Nevertheless, this conceptual model is still at its early development stage, and it is subjected to more empirical testing and research for its practicality and further refinement as a way forward for the research.

Credibility-based cascading approach to achieve net-zero emissions in energy symbiosis networks using an Organic Rankine Cycle

Industrial symbiosis (IS) integrates multiple industries to share resources (e.g., energy, water, by-materials) for economic and environmental reasons. Energy demand is dynamic, imposing financial and logistical barriers to achieving Circular Energy (CEn). This paper addresses this by proposing a new framework that integrates central heating networks of an Organic Rankine Cycle (ORC) system to recover unused low-temperature energy. The framework is formulated as a stochastic programming problem to capture the uncertainty of some parameters to reduce the costs arising from fluctuations in energy supply and demand and, subsequently, wasted energy. Disruption management is also applied to handle the risk of suppliers becoming unavailable due to unforeseen events. The proposed multi-objective mixed-integer linear programming model optimizes the conflicting sustainability value preferences in the IS-based CEn network. The paper presents a novel robust possibilistic programming technique to control the epistemic uncertainty of the developed mode and develops a robust variant of the augmented ε-constraint algorithm (AUGMECON-R) to obtain the Pareto optimal solutions. The results provide a new platform for reducing the undesirable effects of worst-case energy symbiosis scenarios. The results show that using ORCs in an IS network increases the economic benefits of such a system by about 20% and reduces customer dissatisfaction from energy supply disruptions by about 27%.

Uncovering and Filtering Industrial Symbiosis Networks for Carbon Dioxide Utilization in Trinidad and Tobago

The emission source profile of the small island developing State of Trinidad and Tobago (T&T) is unique amongst high national CO2 emitters per unit of GDP. To consider appropriate options for sustainably reusing CO2 in an industrial symbiosis network (ISN), a simple enterprise input-output model of CO2 exchanges between representative plants in a petrochemical cluster at the Point Lisas Industrial Estate in T&T was created. Then multi-objective optimization (MOO) was performed, so that both CO2 emissions and levelized transportation costs would be enhanced. Initial benchmarking uncovered the potential to reuse 17% of the process CO2 emissions in chemical manufacturing on the representative petrochemical network. Next, the effect of adding a CO2-reusing propylene carbonate plant to the ISN was examined. To determine how to add the propylene carbonate plant, MOO was reapplied to an updated network model, to filter all the possible ISNs. These MOO results suggest the addition of a CO2-reusing plant would increase the mass of CO2 reused in the ISN by 6.3%. Thus, eco-connectance, which is a measure of the level of IS, would be increased by 35%. The proposed changes could improve multiple Sustainable Development Goal (SDG) indicators concomitant with SDGs 8, 9, 12 and questionably 13.

A Smart Contract Architecture Framework for Successful Industrial Symbiosis Applications Using Blockchain Technology

Industrial Symbiosis (IS) involves a network of organizations that exchange energy, materials, and by-products to lower production costs, reduce environmental impact, and conserve natural resources. Despite over two decades of extensive research into IS, its benefits are well known, but implementation remains challenging. This paper proposes utilizing blockchain technology (BCT) to digitize IS, making it more secure and transparent. First, drivers and barriers of BCT implementation in IS are identified. A smart contract architecture framework using Hyperledger Fabric is then proposed using the constructed theoretical background and abductive method. Finally, the paper discusses how this framework supports the implementation of BCT in IS by addressing its drivers and attempting to overcome its barriers. It is a resource for those seeking a comprehensive grasp of the foundational elements necessary for constructing a successful IS blockchain design, which is adaptable to all types of IS network configurations.