Life cycle assessment (LCA) is a reference methodology to evaluate environmental impacts along supply chains of products. Planetary boundaries (PBs) were developed to define the safe operating space (SOS) for humanity. So far, no study has investigated whether wine production and consumption result in crossing the planetary boundary of climate change and no SOS has been calculated for wine production in Greece. Our study applies an LCA according to the European Product footprint environmental category rules to calculate the climate change score of a bottle of 0.75 L of Greek red organic wine in 2021 and 2026, and also applies planetary boundaries to investigate whether the climate change boundary is exceeded. The latter employed the calculation of a SOS based on four partitioning methods: grandfathering principle, economic value, agricultural land area use, and calorific content. The LCA results showed that wine is a carbon emitter. The 2021, 2026-Low yield, and 2026-High yield systems resulted in positive climate change scores between 0.69–1.14 kg CO₂ eq.bottle wine⁻¹. The PBs revealed that carbon emissions of wine production in 2021 exceeded all four SOSs, while carbon emissions of expected wine production in 2026 remained within the SOS of grandfathering, economic value and agricultural land area use partitionings, but exceeded the SOS of the caloric content partitioning. The PB method can be complementary to LCA results in terms of providing context to decision-makers in business and public policy on whether red organic wine production and consumption remain within ecological constraints on human development.

Industrial revolution 4.0 takes our world forward in recognizing that since the industrial revolution, which was powered by wood and cheap coal-fired energy in the 1760s, the world has externalized the environmental costs of our industrial production, which has resulted in significant levels of environmental destruction and climate change. Industrial ecology and circular economy are approaches that have considered the combination of environmental impact reduction and industrial development for many years. In this chapter it will be shown how the two aforementioned approaches, together with the idea of industrial revolution 4.0, will see the increasing automation and dematerialization of industry and manufacturing with an increased focus on sustainability performance and circular economy thinking.

These issues present the context in which individually and collectively, sustainability education must be considered and developed. They are invariably interlinked and together present some of the most critical resource issues that the 21st century will face, including the scale of environmental impacts that are associated with our increasing production and consumption decisions and the need to consider new paradigms in our economic business models and governance frameworks.

Reducing packaging waste requires organizations to look beyond their own products, services, and business models. Collaboration in circular ecosystems may offer a promising approach. Material flows in circular ecosystems are affected by social, economic, and technical variables, including decision-making behaviour, material prices, and available technologies. The complexity of these interactions makes it challenging to assess the impact of strategic choices on circular ecosystems' effectiveness in reducing waste. Agent-based modelling (ABM) is a useful methodology for analysing dynamics within such complex systems. This study develops an ABM for a Dutch food packaging ecosystem and integrates organizational decision-making theory to account for actor behaviour, considering different decision-styles and rules. The ABM includes three types of agents representing beverage producers, packaging producers, and waste treaters, who can form circular ecosystems for closed-loop recycling. Experimentation indicates that with just 10 % of organizations prioritizing circularity over maximizing individual profit, significant waste reduction is achievable, although the decision-style of the beverage producer is crucial in profit-driven ecosystems. Furthermore, centralized waste management could stabilize recycled material supply and mitigate fluctuations in recycled content. While the model is limited by deterministic agent behaviour and simplified decision-making processes, our findings demonstrate the value of ABM in understanding dynamics in circular ecosystems and provide insights for policymakers and industry stakeholders. Future research could explore alternative circular strategies with ABM, such as packaging reuse and material substitution, and the impact of modelling more nuanced decision-making behaviour on the model's scientific and practical value.

Purpose: Life cycle assessment (LCA) studies have overlooked the potential range of biochar’s effects on agricultural soils. Only several of the numerous soil effects reported in empirical studies have been included in LCA models. This study aims to establish a consistent lifecycle inventory (LCI) approach to include biochar’s soil effects in LCA and assess the conceptual applicability of LCA to model soil effects. Methods: To exemplify this approach, a case study was conducted, which also provides insight into the environmental implications of biochar’s soil effects and whether LCA results can help guide biochar optimization for greater environmental benefits. For soil effects that met all inclusion criteria, empirical data was selected based on controlling factors and translated into inventory data. The LCI approach was applied to a case study in Aguascalientes, a semi-arid state in central Mexico that suffers from droughts. Results: The combined soil effects have a substantial overall impact across all impact categories, mostly dwarfing upstream biochar production and treatment impacts. This is driven by the persistent soil effects; the transient soil effects contribute far less. Biochar primarily leads to a net environmental benefit in an impact category, strongly depending on the soil effect literature data that is selected. While some soil effects have been researched sufficiently to produce sensible meta-analyses (e.g. crop yield increase), others have only been quantified a handful of times or solely qualitatively assessed (e.g. fire hazard increase). Most soil effects have a non-intermediate impact and can be modelled as intervention or economic flow in some form, with some missing appropriate characterization models. Biochar’s soil effects have a substantial environmental effect and cannot be ignored. A highly accurate inclusion of soil effects in LCA is hindered by several conceptual (non-linearity of soil effect expression, missing characterization models, focus on environmental impact) but mostly data-related (availability of long-term empirical field data) constraints. Conclusion: Although the results varied across scenarios due to differences in model assumptions and uncertainties, they provided in order of magnitude trends that still allowed for informed conclusions on how to tailor biochar in Aguascalientes to maximize environmental benefits while minimizing associated risks (e.g. increasing pyrolysis temperature to reduce PAH content).

This paper evaluates the potential impacts of introducing low-carbon intensity hydrogen technologies in two oil refineries with different complexity levels, emphasizing the role of hydrogen production in reducing CO₂ emissions. The novelty of this work lies in three key aspects: Comprehensive system analysis of refinery complexity using real site data, integration of low-carbon Hydrogen technologies, long-term and short-term strategies. Two Colombian refineries serve as case studies, with technological solutions adapted to their complexity levels. The methodology involves evaluating different options for hydrogen production, accounting for improvement in technological efficiency over time. The refinery systems were evaluated in a cost-optimization model built in Linny-r. Three different scenarios were considered, Business-As-Usual (BAU), high, and low-ambitions decarbonization scenarios, focusing on the time horizons of 2030 and 2050. When comparing the two case studies, the preferred decarbonization strategy for both facilities involves the substitution of SMR technology with water electrolyzers powered by renewable electricity. Post-2030, biomass-based hydrogen technology is still a costly alternative; however, to achieve CO₂ neutrality, negative emissions storage of biogenic CO₂ emerges as an achievable alternative. Our results indicate the achievability of CO₂ reduction objectives in both refineries. Our results show that achieving long-term CO₂ neutrality requires both refineries to increase renewable electricity production by 5 to 6 times for powering water electrolyzers, steam production by 2 to 2.5 times for CO₂ capture, and supply of dry biomass by 2.6 to 4.5 kt/d. The two most significant factors influencing the refining net margin in the decarbonization scenarios are primarily the CO₂ and the renewable electricity prices. The short-term horizon emerges as the pivotal period, particularly within the high-ambition decarbonization scenarios. In this context, the medium complexity refinery demonstrates economic viability until a CO₂ price of 140 €/t CO₂, while the high complexity refinery endures up to 205 €/t CO₂. The high complexity refinery is better prepared to face the challenges of decarbonization and the impacts generated on the refining margin. Compared to the BAU scenario, the high complexity refinery shows a negative impact on the net margin that corresponds to a 40 % and 5 % reduction in the short and long term, respectively. Meanwhile, for the medium complexity refinery, the impact on net margin amounts to a 52 % reduction in the short term and a 27 % improvement in the long term. Furthermore, our research highlights the significant potential for reducing CO₂ emissions by fully eliminating the use of refinery gas as fuel, providing alternative applications for it beyond combustion.

This research uses system optimization to assess short, medium, and long-term scenarios to achieve the committed CO₂-emission goals of Ecopetrol while minimizing potential adverse impacts such as incremental operational costs and utility demand. Two Colombian refineries are used as a case study: a medium-complexity and a high-complexity refinery. The study explores whether the level of complexity plays a significant role in the results. Potential technologies were ranked using a multi-criteria decision analysis. The system analysis and optimization were done in Linny-R, a mixed integer linear programming software package developed by TU Delft. In the short-term (2030) scenario, the selected technologies include low-carbon H₂ produced from Steam Methane Reformer units with carbon capture and storage and H₂ produced from renewable electricity sources. The medium and long-term (2050) scenario also included biomass gasification, naphtha reforming, and the cracking unit, all with carbon capture and storage. The refineries were modelled using on-site company data. The results indicate that using low-carbon H₂ and carbon capture and storage to flue gases would allow to reach the net zero target. Furthermore, the results show that the level of complexity in a refinery significantly impacts the decarbonization deployment pathways. The high-complexity refineries benefited from using low-carbon H₂ as feedstock while the medium-complexity refinery relied on a combination of carbon capture and low-carbon H₂ as an alternative fuel. This research highlights the potential to achieve substantial CO₂ emissions reductions with less impact on the total operational cost by using the amount of excess refinery gas generated when H₂ is used as fuel in boilers and process furnaces. A significant challenge remains in identifying suitable applications for surplus refinery fuel gas beyond its conventional use in combustion within boilers and furnaces.

Self-organized industrial symbiosis (IS) starts with one actor's decision to invest in a waste recovery plant and the other actors' decision to buy the recovered flow. Technical and institutional conditions of the cluster influence actors' decisions. This paper explores the emergence of IS collaborations in industrial clusters under different techno-economic conditions in the long term. We propose a mixed-integer linear programming model that incorporates costs and constraints associated with waste recovery and exchange to study actors' investment decisions and investigate shaped symbiotic exchanges under rising energy prices and limited electricity supply. The approach is implemented in Iran's Persian Gulf Mining and Metals Special Economic Zone as a case study. The results revealed that changes in internal or external condition simultaneously influence the industrial and waste recovery plants. For instance, increasing energy prices without raising product prices significantly decreased the production level of industrial plants and, consequently, heat recovery potential. Furthermore, the waste heat recovery plants' contribution to improving the cluster's economic and environmental performance was not the same. Electricity recovery from a power plant's waste heat can result in 55 PJ grid electricity intake reduction and 720 M€ cluster cash flow increase. Recovered cooling or electricity from the steelmaking plant waste heat was consumed internally rather than shaping IS. These model outcomes show its capability to study IS within the socio-technical structure of the cluster, not a standalone phenomenon. Implemented conceptualization offers a novel system-level approach, which could be adjusted to assess other industrial development strategies.

In view of the energy transition, it is important that engineering students are familiar with the concept of exergy and the added value of exergy analysis compared to energy analysis. Exergy analysis tells the truth about energy efficiency and exergy is directly related to sustainable development. This paper focuses on teaching exergy to students at the Delft University of Technology (TU Delft), but the contents are valuable to other engineering students as well. To encourage the teaching of exergy, the basics of exergy and exergy analysis are presented, as well as examples and ideas for teaching exergy to BSc students that are related to the topics of their BSc programme. It is recommended that the contents of this paper be discussed with many teachers of BSc programmes, especially teachers of BSc programmes that do not yet seem to include the teaching of exergy, and that attention be paid to teaching exergy to MSc students as well.

Natural gas for heating is widespread in the built environment of The Netherlands, where the government aims at limiting heat demand and reducing natural gas consumption over the coming decades. In the owner-occupied residential sector, this transition is complex and requires cooperation and coordination of individuals and groups that make investment decisions. We use agent-based modelling to explore the effect that various financial policies could have in an illustrative neighbourhood, given that households make multi-criteria and group decisions. In the scientific literature, this type of energy model seldom focuses on the adoption of competing technologies by households as individual and collective agents grouped in homeowner associations in multi-family buildings. To address the problem and knowledge gaps, we model individual preferences with a multi-criteria perceived lifetime utility submodel, and decisions as outcomes of individual preferences and a threshold voting system. We explore energy taxes (natural gas and electricity), regulated price of heat from networks, and subsidies (insulation and heat pumps). Under our assumptions, we found that combinations of fiscal policies, regulated heat prices, and subsidies can sometimes create incentives for households to disconnect from natural gas, but that steering the transition mainly with financial policies could prove ineffective. We also found that, in terms of collective CO2 reduction, some transitions in which only some households phase out natural gas could have results similar to some scenarios in which households only improve their dwellings’ insulation levels.

Safe-and-sustainable-by-design (SSbD) is a concept that takes a systems approach by integrating safety, sustainability, and functionality throughout a product’s the life cycle. This paper proposes a framework based on a prospective life cycle assessment for early safety and sustainability assessment. The framework’s purpose is to identify environmental sustainability and toxicity hotspots early in the innovation process for future SSbD applicability. If this is impossible, key performance indicators are assessed. Environmental sustainability aspects, such as global warming potential (GWP) and cumulative energy demand (CED), and toxicity aspects, such as human toxicity potential and freshwater ecotoxicity potential, were assessed upon applying the framework on a case study. The case study regarded using nano-titanium dioxide (P25-TiO2) or a modified nano-coated version (Cu2O-coated/P25-TiO2) as photocatalysts to produce hydrogen from water using sunlight. Although there was a decrease in environmental impact (GWP and CED), the modified nano-coated version had a relatively higher level of human toxicity and freshwater eco-toxicity. For the presented case study, SSbD alternatives need to be considered that improve the photocatalytic activity but are not toxic to the environment. This case study illustrates the importance of performing an early safety and environmental sustainability assessment to avoid the development of toxic alternatives.

Life Cycle Assessment (LCA) is a powerful tool for achieving sustainability. Traditional LCAs analyze well defined and developed industrial systems, but recent developments of LCA focus on analyzing emerging technologies which are not yet optimized with respect to energy and materials. Therefore, LCA results of ex-ante applications can be very different from ex-post applications for the same system. The purpose of this study is to show the different effects of data scales on LCA results regarding global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication potentials. For this purpose torrefaction technology was selected as the case study and assessed based on bench scale data, lab scale data, data derived from process simulations, pilot scale data and commercial scale data. Considered environmental impacts were global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication. Results showed that process efficiencies improved significantly between the bench scale system and systems with higher technology readiness levels (TRLs), such as pilot, process simulations and commercial scale systems. Furthermore, process simulations result in scores closer to commercial scale regarding all considered environmental impacts. However, if LCA practitioners focus only on global warming impact, then pilot scale is also a good alternative. Finally, due to torrefaction technology being relatively simple in terms of raw materials input, we suggest more complex chemical systems to be assessed with LCA in various TRLs.

Coal-mine effluent treatment has the potential to both reduce the environmental impact of the effluent and provide economic opportunities by recovering valuable minerals and clean water. In this study, we modeled a novel treatment process, which includes nanofiltration (NF), two-step crystallization, reverse osmosis (RO), electrodialysis (ED), multi-effect distillation (MED), and a NaCl crystallizer, and performed a techno-economic analysis of its full-scale implementation, using a circular economy approach. We estimated the thermal and electrical energy consumption to be 745.5 kWhth/tonNaCland 565.1 kWhel/tonNaCl(or 13.6 kWhthand 10.3 kWhelper m3of feed effluent), respectively. The levelized cost of the NaCl salt that accounts for the revenue from the plant's co-products (Mg(OH)2, CaSO4and, pure water) was estimated to be 203 USD/tonNaCl. The economic viability of the treatment chain can be improved by using renewable electricity sources, reducing the total expenditure on NF and RO, and integrating alternate technologies into the treatment plant

This study furthers game-based learning for circular business model innovation (CBMI), the complex, dynamic process of designing business models according to the circular economy principles. The study explores how game-play in an educational setting affects learning progress on the level of business model elements and from the perspective of six learning categories. We experimented with two student groups using our game education package Re-Organise. All students first studied a reader and a game role description and then filled out a circular business model canvas and a learning reflection. The first group, i.e., the game group, updated the canvas and the reflection in an interactive tutorial after gameplay. The control group submitted their updated canvas and reflection directly after the interactive tutorial without playing the game. The results were analyzed using text-mining and qualitative methods such as word co-occurrence and sentiment polarity. The game group created richer business models (using more waste processing technologies) and reflections with stronger sentiments toward the learning experience. Our detailed study results (i.e., per business model element and learning category) enhance understanding of game-based learning for circular business model innovation while providing directions for improving serious games and accompanying educational packages.

Sustainability is high on the agendas of public and private organizations. Governments are setting targets for reducing the use of virgin raw materials in products and to eliminate waste. To accelerate the transition towards a Circular Economy (CE) policymakers are launching instruments. However, policy instruments, such as financial incentives or new regulatory guidelines, are prone to manipulations when the stakes for the involved stakeholders are high. Therefore, policymakers and government authorities need a solid system to monitor and control the implementation and effectiveness of their CE measures. To this end, digital technologies are key to enabling visibility and monitoring of materials flows. They allow governments and other stakeholders to use data to steer the transition towards a CE. However, data from different materials supply chains reside in a diversity of digital platforms used by a diversity of stakeholders involved. Blockchain-based platforms can support the required visibility by combining data from different stakeholders across different materials supply chains. But connecting all data for CE visibility throughout the entire materials flows into one singular platform is unlikely. With the growing number of blockchain-based platforms that each covers parts of data on CE flows, there is a need to assess the level of visibility they offer and to determine which data is lacking to monitor full CE flows. In this article, the development of a framework to evaluate blockchain-enabled information systems on their ability to act as monitoring systems for CE purposes is presented. The design science research approach was followed to develop the framework. Insights provided by academic literature as well as empirical data from three extant blockchain-enabled platforms were used (i.e., TradeLens, FoodTrust, and Vinturas). The evaluation framework can be deployed by public and private actors (e.g., governments and banks) for monitoring purposes, but also by IT providers to offer CE visibility solutions.

The Netherlands aims at reducing natural gas consumption for heating in the housing sector. Although homeowners are responsible for replacing their heating systems and improving dwelling insulation, they are not always able to make individual decisions. Some projects require group decisions within and between buildings. We use an agent-based modelling and simulation approach to explore how these individual and group decisions would influence natural gas consumption and heating costs in an illustrative neighbourhood, under a set of assumptions. We model individual household preferences over combinations of insulation and heating systems as a lifetime cost calculation with implicit discount rates, and we use quorum constraints to represent group decisions. We model three fiscal policies and a policy to disconnect all dwellings from the natural gas network. Results show that the disconnection policy was the only necessary and sufficient condition to incentivize households to replace their heating systems and that group decisions influenced the alternatives that were chosen. Since results were influenced by group decisions within buildings and by the market discount rate, we recommend further research regarding policies around these topics. Future work can apply our approach to case studies, incorporate new empirical knowledge, and explore group decisions in other contexts.

MSocial Life Cycle Assessment (S-LCA) uses a life cycle perspective to assess social impacts of products, and the S-LCA guidelines describe developing the system boundaries based on a factory-level perspective. However, such a perspective may exclude stakeholders with a negative social performance which are cooperating with a factory but are not directly involved with the product under study, and it can result in a step back on corporate social responsibility (CSR). Our study aimed to align S-LCA with the CSR concept. Therefore, we designed a case study for the manufacturing sector in which we practiced expanding the system boundaries of S-LCA. Our results showed larger social risks after expanding the system boundaries due to subsidiary and supplier companies located in countries with less strict regulations than the Netherlands, which is where the main organizations and parent company existed. We conclude that system boundaries expansion can result in more complete picture of the involved organizations, and lead practitioners to approach S-LCA with the goal of improving social conditions and identify companies which deserve excellent or poor social scores. Its usefulness is mostly expected when S-LCA practitioners aim to identify social hotspots in supply chains in socially sensitive markets.

The viability of novel network-level circular business models (CBMs) is debated heavily. Many companies are hesitant to implement CBMs in their daily practice, because of the various roles, stakes and opinions and the resulting uncertainties. Testing novel CBMs prior to implementation is needed. Some scholars have used digital simulation models to test elements of business models, but this this has not yet been done systematically for CBMs. To address this knowledge gap, this paper presents a systematic iterative method to explore and improve CBMs prior to actual implementation by means of agent-based modelling and simulation. An agent-based model (ABM) was co-created with case study participants in three Industrial Symbiosis networks. The ABM was used to simulate and explore the viability effects of two CBMs in different scenarios. The simulation results show which CBM in combination with which scenario led to the highest network survival rate and highest value captured. In addition, we were able to explore the influence of design options and establish a design that is correlated to the highest CBM viability. Based on these findings, concrete proposals were made to further improve the CBM design, from company level to network level. This study thus contributes to the development of systematic CBM experimentation methods. The novel approach provided in this work shows that agent-based modelling and simulation is a powerful method to study and improve circular business models prior to implementation.

Industrial Symbiosis Networks (ISNs) consist of firms that exchange residual materials and energy locally, in order to gain economic, environmental and/or social advantages. In practice, ISNs regularly fail when partners leave and the recovery of residual streams ends. Regarding the current societal need for a shift towards sustainability, it is undesirable that ISNs should fail. Failures of ISNs may be caused by actor behaviour that leads to unanticipated economic losses. In this paper, we explore the effect of these behaviours on ISN robustness by using an agent-based model (ABM). The constructed model is based on insights from both literature and participatory modelling in three real-world cases. It simulates the implementation of synergies for local waste exchange and compost production. The Theory of Planned Behaviour (TPB) was used to model agent behaviour in time-dependent bilateral negotiations and synergy evaluation processes. We explored model behaviour with and without TPB logic across a range of possible TPB input variables. The simulation results show how the modelled planned behaviour affects the cash flow outcomes of the social agents and the robustness of the network. The study contributes to the theoretical development of industrial symbiosis research by providing a quantitative model of all ISN implementation stages, in which various behavioural patterns of entrepreneurs are included. It also contributes to practice by offering insights on how network dynamics and robustness outcomes are not only related to context and ISN design, but also to actor behaviour.

Industrial Symbiosis (IS) is a collaboration between nearby industrial plants to exchange waste material and energy and achieve economic and environmental benefits that cannot be obtained individually. IS emergence in a cluster requires both technical potentials for material and energy exchange and social readiness for collaboration. In this paper, to gain insight into IS dynamics in emerging industrial clusters; we investigate shared concepts governing actors' behavior in the form of rules and regulations, and social norms and practices. We implemented the IS dynamics framework to reveal which dynamics are supported either by the legislation or actors' preferences. The Persian Gulf Mining and Metal Industries Special Economic Zone in Iran is used as a case study. The case study revealed that previous successful collaborations in the cluster were often self-organized, but stakeholders preferred to initiate new IS collaborations if financial incentives and infrastructure are provided. Meanwhile, the institutional analysis showed that institutional arrangements (e.g., pricing and penalties) are not in favor of IS emergence. Even though stakeholders might engage in self-organized IS because of inherent problems such as resource scarcity, the lack of clear and effective institutions could hinder IS. This understanding can help both the government and stakeholders in their strategies for future collaborations under different economic and environmental policies.

Environmental pollution, resource scarcity, and freshwater shortage are critical world challenges facing humanity. Process industry produces large amounts of brine, a waste water with a high salinity level and often critical raw materials. This study applies the social life cycle assessment (S-LCA) to quantify societal benefits and risks in developing brine treatment systems. S-LCA is implemented for hotspot and site-specific levels on four case studies of the Zero Brine project. Hotspot analysis focused on the major commodities. Social Hotspot Database was used as source for data and endpoint indicators. In addition, site-specific analysis regarded the social performance of the case studies companies; interviews and questionnaires were performed with representatives of the four case studies. The collected data were converted to scores with subcategory assessment method and performance reference points. The results show that for all case studies “Labor rights and decent work” and “Health and safety” indicators result in the largest impacts due to imports of commodities from developing countries. Site-specific results show that the overall social sustainability performance of the case study companies is at a good level. The only potential areas for improvement are the “Occupational accidents” and “Contribution to the local community”. The former are minimally higher for silica plant and higher for coal mine in relation to these sectors average accidents rates. Furthermore, the coal mine company can contribute more to the local community and reduce conflicts concerning environmental impacts at the city level. Common identified hotspots among the case studies are: China, India and Congo. Reducing imports from these countries will significantly improve the societal performance of the brine systems.