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The vision of a sustainable and safe use of chemicals to protect human health, preserve the environment and maintain the ecosystem requires innovative and more holistic approaches to risk assessment (RA) in order to better inform decision making. Integrated risk assessment (IRA) has been proposed as a solution to current scientific, societal and policy needs. It is defined as the mutual exploitation of environmental risk assessment (ERA) for human health risk assessment (HHRA) and vice versa in order to coherently and more efficiently characterize an overall risk to humans and the environment for better informing the risk analysis process. Extrapolating between species which are relevant for HHRA and ERA requires a detailed understanding of pathways of toxicity/modes of action (MoA) for the various toxicological endpoints. Significant scientific advances, changes in chemical legislation, and increasing environmental consciousness have created a favourable scientific and regulatory environment to develop and promote the concept and vision of IRA. An initial proof of concept is needed to foster the incorporation of IRA approaches into different chemical sectorial regulations and demonstrate their reliability for regulatory purposes. More familiarity and confidence with IRA will ultimately contribute to an overall reduction in in vivo toxicity testing requirements. However, significant progress will only be made if long-term support for MoA-related research is secured. In the short term, further exchange and harmonization of RA terminology, models and methodologies across chemical categories and regulatory agencies will support these efforts. Since societal values, public perceptions and cultural factors are of increasing importance for the acceptance of risk analysis and successful implementation of risk mitigation measures, the integration of socio-economic analysis and socio-behavioural considerations into the risk analysis process may help to produce a more effective risk evaluation and consideration of the risks and benefits associated with the use of chemicals. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract Biobased chemistry has gained interest and has the potential to tackle some of the sustainability challenges the chemical industry must endure. Sustainability impacts need to be evaluated and monitored to highlight the advantages and pitfalls of different biobased routes over the entire product life cycle. This study aims for expert consensus concerning indicators needed and preferred for sustainability analysis of biobased chemicals in Europe. Experts are consulted by means of a Delphi method with stakeholders selected from three core groups: the private, public and academic sector. Best-Worst Scaling (BWS) is performed to gather data on the prioritization of the sustainability indicators per respondent. Afterwards, Multi-Criteria Decision Analysis (MCDA) is used to develop a consensus ranking among the experts. The results show that GHG emissions , market potential and acceptance of biobased materials are deemed the most crucial indicators for respectively environmental, economic and social sustainability. Expert consensus is positive in all three sustainability domains, with the strongest consensus measured for environmental sustainability showing a median Kendall's τ of 0.63 (τ ranging from -1 to 1) and the weakest consensus found within social sustainability showing a median Kendall's τ of 0.50. Further research can apply the ranked indicators on specific case studies to evaluate the practicability of the defined indicator set. [ABSTRACT FROM AUTHOR]

This paper aims to perform a literature review on the use of multi-criteria methods for assessing agricultural sustainability, focusing on the distribution of papers according to year, journal, and countries, the most productive authors, the most frequently used multi-criteria methods and their characteristics, the type of system and the type of agriculture in which these methods are being performed, the methodological approaches and assessment types, and the sustainability dimensions considered. The data collection has been carried out through the Web of Science™ platform on September 3rd, 2021. After a refinement process, 41 papers were selected. The descriptive analysis was carried out through Bibliometrix tool, while content analysis was performed using Nvivo. The descriptive analysis shows that from 2016 to 2021 the scientific production addressing multi-criteria methods to assess agricultural sustainability started to grow markedly in a very rapid matter, reaching an average of 6 papers per year. France and China are the most scientifically productive countries. The content analysis points out that the most used multi-criteria method is the AHP that was used 11 times. The outranking methods, instead, were used only 3 times. In 68% of the papers the Triple Bottom Line was used as dimensions, and in 41% of the papers the spatial applicability was the farming system. The results highlight that doesn't exist many MCDM/A methods for assessing agricultural sustainability, and most of them are compensatory. These results point out that the use of multi-criteria methods in assessing agricultural sustainability is still underexplored and can be improved. [Display omitted] • Multicriteria methods are powerful tools for assessing agricultural sustainability. • A literature review on agricultural sustainability evaluation was performed. • The number of studies has been increasing in the last five years. • Most of the approaches are based on compensatory multicriteria methods. [ABSTRACT FROM AUTHOR]

• Propose an end-of-use condition estimation method based on reliability and warranty policy. • Present a two-stage optimization model for the Re -X decision-making problem. • Develop a condition-based end-of-use processing policy under demand uncertainty. • Reduce lifecycle cost and environmental impact for product family. • Demonstrate the methodology with case study and result analysis. The concept of circular economy has been diffused in recent decades to promote economic growth that does not add to the burden on natural resource extraction. Re -X options (e.g., reuse, repair, refurbish, remanufacture, recycle) have been gradually adopted in the product development process and optimized to reduce or eliminate waste and pollution. Although manufacturing incorporating Re -X options can be more environmentally friendly, it involves more sources of uncertainty than traditional manufacturing since the end-of-use products can be collected from multiple origins with various quantities and qualities, and the market demand for both new and remanufactured products cannot be forecasted perfectly. Thus, there is a need to optimize the Re -X policy to alleviate the negative impacts of the higher uncertainty. One option is using the reliability information of new products to estimate the end-of-use conditions and applying multi-stage stochastic optimization to capture multiple demand scenarios. This paper develops a two-stage stochastic optimization model to optimize the quality thresholds for reuse, recycling, and remanufacturing options. Our objective is to minimize the total cost, energy consumption, and environmental impact of producing and providing warranty service for a product family. The model employs reliability information of product components to estimate the warranty service cost and the end-of-use conditions of the returned resources. A case study on a general product family is implemented to illustrate the efficacy of the optimization model. Results show that the two-stage optimization can achieve cost and environmental impact reduction for a hybrid manufacturing and remanufacturing process. [ABSTRACT FROM AUTHOR]

Biologicalisation as the convergence of biology, engineering and information technology offers the prospect of dramatic step change scenarios for future innovative development. A large number of highly stimulating and potentially very valuable solutions, created over millions of years of evolution, are available in nature's solution space and waiting for application in technology. Transfer methods linking the biosphere and the technosphere are classified as functionalities which assume: bio-inspiration from nature, bio-integration combining biological and technological solutions, and bio-intelligence. The latter aims at achieving developments towards living systems based on the (reasonably) high level of appreciation of the environment, the system's capability and the specific task to be undertaken using decision making or self-reasoning. The use of large numbers of different sensors is involved together with sensor fusion strategies, self-healing and self-organising properties, along with functional integration. Moreover, to derive maximum benefit, the key enabling technologies will play a crucial role going forward. The impact on industry of unique and outstanding solutions will radically change the way manufacturing is performed today by building on new levels of latency, interconnectivity and communication. This paper aims at supporting the comprehension of these developments and revealing future trends, research needs and educational requirements in manufacturing science and technology as the biosphere and the technosphere converge to create the new levels of global sustainability. [ABSTRACT FROM AUTHOR]

Recently, Indian manufacturing industries have undergone a significant transformation emphasising customer-centric objectives to meet the dynamic market's demands. To achieve this, existing industries must upgrade their existing infrastructure to a smart environment driven by automatic data exchange, transparency, and interconnected digital systems. These are the key enabling elements of Industry 4.0. As a result, many Indian industries are developing various sophisticated implementation strategies for adopting it. However, few research works and strategies contribute to its effective and successful implementation. This paper proposes two types of implementation strategies for implementing Industry 4.0 enabling technologies based on the requirements and adaptability of India's commercial vehicle manufacturing industry. The first strategy identifies various aspects of implementing Industry 4.0 enabling framework elements and categorizes it for developing implementation strategies based on India's commercial vehicle manufacturing industry. The significance of each was determined using fuzzy-AHP analysis and ranked accordingly based on the linguistic responses of the industry experts. The most significant framework element is found to be 'Decision Making and Management Skills'. The second strategy emphasizes long-term sustainable implementation objectives. The framework elements are reconstructed and developed into a novel, customized sustainable framework based on six dimensions of sustainability. Using the Fuzzy-DEMATEL method, the causal relationships among these elements are investigated to determine a sustainable implementation strategy. 'Central Database Server' is determined to be the most significant sustainable framework element, while the maximum number of casual relationships is obtained from the group, 'Skill upgradation of the workforce'. This paper proposes a novel research direction for implementing Industry 4.0 technologies into the existing industry. The findings provide several insights and strategies for technological upgradation in other industries in this geographical region. The findings of the work enhance the implementation process of I4.0 technologies, transitioning it from a conventional approach to a futuristic sustainable implementation that is economical and effective. • Industry 4.0 enabling framework elements for Indian manufacturing industry were identified and categorised. • Significance of each framework element are determined using Fuzzy AHP. • A customised sustainable framework of I4.0 enabling elements is presented. • Fuzzy DEMATEL approach used to examine their causal relationships and significance based on long-term sustainability. • Sustainable implementation strategies and implications are discussed. [ABSTRACT FROM AUTHOR]

This work makes the case for the integration of the circular economy (CE) and large-scale data (LD), also known as big data. The paper is one of the first to integrate conceptual and practical trends regarding: (a) the ReSOLVE based models of the circular economy; (b) key stakeholders roles in pursuing a more sustainable society; and (c) the volume, velocity, variety, and veracity (4V's) of large-scale data (LD) management. This study's contributions include: (1) introducing a new integrative framework to enhance the understanding of the CE-LD nexus; (2) a relational matrix which illustrates the complexity of large-scale data and stakeholders management; and (3) a research agenda, with clear research propositions and future research direction. The proposed CE-LD integrative framework provides socio-technical insights for academics, practitioners, managers, and policy decision-makers. • This paper integrates the disparate fields of the circular economy (CE) and large-scale data (LD). • Discusses how large-data can support the circular economy's business models. • An integrative framework for CE-LD is proposed. • A research agenda for the circular economy and large-data integration is proposed. • Implications for challenges and opportunities of sustainable production in a digital world. [ABSTRACT FROM AUTHOR]

Environmental degradation is currently one of the biggest challenges for policy makers designing public policies. In particular, the emission of greenhouse gases as side effect of human activity is a significant problem. One of the methods and instruments used in the public sector to limit the progressing environmental degradation are environmental taxes. It is an element of fiscal policy used by countries around the world, including in the European Union, although it has no compulsory nature. So far, studies on the effectiveness of environmental taxes are not explicit. The effects of environmental taxes differ in EU countries, also environmental taxes systems are of different construction, and tax policies in this scope vary as well. This paper uses the taxonomic measure based on the Weber median to analyse the link between environmental taxes and environmental degradation. 23 EU countries belonging to OECD were analysed for 2016, on the basis of the Eurostat dataset. The study attempts to answer the question whether environmental taxes are an effective instrument for shaping environmental policy and whether they can become an important tool in the decision-making process at the government level. The paper assumes that the role of environmental taxes and their impact is different in developed and converging economies. The results prove a positive relationship between environmental taxes and environmental performance in the case of one indicator (Share of renewable energy in gross final energy consumption) for others a negative link is reported. [ABSTRACT FROM AUTHOR]

This paper develops connections between design thinking and social practice theories, presenting a toolkit intended to support the development of sustainability interventions and policies capable of encouraging sustainable practices. Key developments in design thinking and social practice theories are critically examined, and a toolkit is presented that sensitively combines their conceptual and methodological insights. The toolkit is one of the first resources that enables practitioners to operationalise social practice theories without substantial prior engagement or training. It thereby offers an accessible resource to support the design of initiatives that could disrupt resource intensive practices and support the emergence and normalisation of less resource intensive alternatives. This paper specifically addresses the contribution the toolkit makes to advancing discussions regarding practice-oriented design. • Connections between social practice theories and design thinking are developed. • Social Practice Theories extend focus towards a socio-technical system focus. • Design Thinking provides immersive participatory methods for intervention planning. • We present a toolkit to aid creation of practice-based sustainability interventions. • A co-productive approach is outlined to enable others to develop practicable outputs. [ABSTRACT FROM AUTHOR]

Assessment of the sustainability of countries for afordable and clean Energy requires a framework with relevant criteria, simultaneous inclusion of multiple criteria in the evaluation, and consideration of the dynamics of changes in performance over time. A wide variety of multi-criteria decision analysis (MCDA) approaches using different algorithms for multi-criteria aggregation are currently available. These methods are suitable for sustainability assessment because they allow the consideration of multiple criteria, the construction of a hierarchical structure of criteria, and the assignment of significance to criteria weights. However, MCDA methods have the limitation of being able to evaluate a data set for a single moment in time, which is insufficient for the sustainability paradigm. The mentioned limitation of MCDA motivates researchers to develop approaches that adapt MCDA methods to temporal assessment. The purpose of this paper is to present the application of a method called Data vARIability Assessment Technique for Order of Preference by Similarity to Ideal Solution (the DARIA-TOPSIS method) for multi-criteria temporal assessment of European countries for affordable and clean energy. This aspect of sustainability is included in Sustainable Development Goal 7 proposed by United Nations in the 2030 Agenda for Sustainable Development. The DARIA-TOPSIS method combines the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for multi-criteria evaluation with a Gini coefficient-based measure of result variability. The method has identified the best-scored countries in terms of implementing sustainable energy policies focused on affordable and clean energy, including Norway, Iceland, and Sweden. [ABSTRACT FROM AUTHOR]

Abstract The ocean is the next frontier for many conservation and development activities. Growth in marine protected areas, fisheries management, the blue economy, and marine spatial planning initiatives are occurring both within and beyond national jurisdictions. This mounting activity has coincided with increasing concerns about sustainability and international attention to ocean governance. Yet, despite growing concerns about exclusionary decision-making processes and social injustices, there remains inadequate attention to issues of social justice and inclusion in ocean science, management, governance and funding. In a rapidly changing and progressively busier ocean, we need to learn from past mistakes and identify ways to navigate a just and inclusive path towards sustainability. Proactive attention to inclusive decision-making and social justice is needed across key ocean policy realms including marine conservation, fisheries management, marine spatial planning, the blue economy, climate adaptation and global ocean governance for both ethical and instrumental reasons. This discussion paper aims to stimulate greater engagement with these critical topics. It is a call to action for ocean-focused researchers, policy-makers, managers, practitioners, and funders. Highlights • There has been inadequate attention to social justice and inclusion in ocean science, management, governance and funding. • This paper reviews injustices and exclusions across key ocean policy domains and argues for greater attention to these issues. • The social sciences can increase understanding and help develop robust and evidence-based solutions. • We need to learn from past mistakes and identify ways to navigate a just and inclusive path towards sustainable oceans. • This is a call to action for ocean researchers, policy-makers, managers, practitioners, and funders. [ABSTRACT FROM AUTHOR]

Poly-centrality is an essential feature of megaregions and is generally considered an important source of megaregional vitality and competitiveness. Numerous studies have highlighted the growing trends of poly-centrality across different megaregions worldwide. However, with accelerated urbanization, some observations suggest that the existing polycentric urban theories must be improved and that decision-makers require more knowledge on the potential trends, spatial characteristics and influencing factors of polycentric development to implement sustainable regional governance under this context. This paper proposes a series of hypotheses on spatiotemporal dynamics of polycentric megaregion evolution and verifies them in an empirical study on the Megaregion around Hangzhou Bay (MAHB). A new algorithm, which is applicable for long time series data, is proposed to evaluate and monitor the status of polycentric development in MAHB. In particular, landscape metrics and average nearest neighbor analysis are employed in the first stage of our algorithm which is designed to implement data compression. Then, the gravity model, minimum spanning tree (MST) and weighed betweenness centrality indicator form the second stage which aims to construct and explore the polycentric megaregional network. Results show that: (1) the speed and patterns of built-up land expansion significantly affect the number and distribution of megaregion centers; (2) the value of poly-centrality reaches a maximum in approximately 2013 and then declines, which can be well fitted by a Gaussian curve; and (3) the variation of poly-centrality is successively dominated by an increase and decrease in the number of centers with urbanization. This paper renews the assumptions in current polycentric evolution models and provides evidences for single-peaked change of megaregion center number instead of “wave-like”, “scaling-up” or monotonous change proposed in existing urban theories. The proposed algorithm and assumed mechanisms can also be applied to model and explore poly-centrality dynamics of other megaregions around the world. The results are believed to provide critical implications for polycentric policies. [ABSTRACT FROM AUTHOR]

Smart agriculture offers the potential to analyse agricultural data at a scale not previously possible. Researchers argue that the combination of rich data and intelligent decision support has the potential to improve productivity and profitability in agriculture, whilst also improving sustainability. We argue that achieving this potential requires not just on technological advancement, it also requires a detailed understanding of factors that impact technology acceptance in smart agriculture. Acceptance is necessary if technical advances are to translate into real-world impact. However, technology acceptance is complex and often poorly understood. This systematic review focuses on technology acceptance in prediction and decision support systems in crop production. Major databases were searched to identify papers that formally address technology acceptance and include detailed data. 16 papers met the inclusion criteria and were included in the final analysis. Common facilitators and barriers are identified, and papers are mapping against the Theoretical Framework of Acceptability. This analysis showed that constructs including perceived effectiveness are addressed frequently, but others such as opportunity costs and burden have received less attention. The findings suggest the necessity for greater application of formal methods and the need for standardized, domain-specific methods to support this assessment. • Presents a systematic review of technology acceptance in smart agriculture, focusing on decision support in crop farming. • Increased productivity, access to information, and support for training are amongst the most common facilitators of acceptance. • Complexity, infrastructure requirements, increased burden, and not directly addressing farming needs are common burdens. • While effectiveness has been widely addressed, issues such as burden, opportunity costs and ethicality have received limited attention. • The development of a validated models of technology acceptance, and associated instruments, should be prioritised. [ABSTRACT FROM AUTHOR]

During the past two centuries, the world has undergone deep societal, political, and economical changes that heavily affected human life. The above changes contributed to an increased awareness about the deep impact that policy decisions have at the local and the global level. Therefore, there is a strong need that policy-making and decision-making processes for a sustainable development be based on the best available knowledge about Earth system and environment. The recent advance of information technologies enables running complex models that use the large amount of Earth Observation datasets available. However, data and model interoperability are still limited to the syntactic level allowing to access and process datasets independently of their structural characteristics (data format, coordinate reference systems, service interface, ...) but with no clear reference to their content (the semantic level) and context of use (the pragmatic level). This poses heavy limitations to the reusability of scientific processes and related workflows. The paper presents a general framework to address this issue through the design of a Knowledge Base supporting data and model semantic (and pragmatic) interoperability. In this framework, a general ontology represents the knowledge generation process for policy relevant decision-making, while multiple vocabularies formalize the semantics of data and models, identifying different types of observables, process variables, and indicators/indices. To evaluate the proposed approach to semantic interoperability of data and models, the Knowledge Base has been integrated with an advanced model-sharing framework, and a proof-of-concept has been developed for the assessment of one of the indicators of the Sustainable Development Goals defined by the United Nations. • Earth Observation and Earth Science are essential for environmental decision-making. • Essential Variables play a key role in building environmental scientific processes. • Digital transformations support interoperability of environmental data and models. • Environmental knowledge generation requires addressing semantic and pragmatic aspects. • Knowledge formalization enable transparency and reusability of scientific workflows. [ABSTRACT FROM AUTHOR]

Abstract Within a repowering context, this paper opens a new field of application for visibility and Visual Impact Assessment (VIA) procedures in the decision-making process typical of the design stage of Wind Farms (WF). The proposed methodology presents a test capable of reporting on the visual sustainability of different layouts. It is called Equivalent Visual Impact (EVI). To work with EVI, visibility data have to be numerically available at a level of each pixel and each Wind Turbine (WT). This is called High Resolution Data (HRD). The paper shows how these ideas, EVI and HRD, were applied to a real repowering experience; the result was that the WF could sustain an increment in its power by 37.25% with no additional visual effects. Other associated consequences are discussed. Highlights • Wind farm repowering addressed by visibility and visual impact assessment criteria. • Decision making based on a new sustainability criterium: Comparison of Equivalent Visual Impact (EVI). • EVI involves supporting decisions with High Resolution Data (HRD). [ABSTRACT FROM AUTHOR]

Highlights • The electrical vehicle charging station (EVCS) is studied in this paper. • A Bayesian network model is developed to assess the locations of EVCS. • Sensitivity analysisis is performed to determine the robustness of decisions. • Propagation analysis is conducted to evaluate the criticality of decision variables. Abstract Fast charging sites play a crucial role for public acceptance of electric vehicle (EV). Selection of the most sustainable site positively contributes to the life cycle of electric vehicle charging station (EVCS), which requires considering some conflicting criteria. Previous researches mainly focused on utilizing optimization models to deal with EVCS site selection that only accounts for quantitative factors, while this paper proposes a Bayesian Network (BN) model that considers not only quantitative factors but also qualitative (subjective) ones. Based on academic literature and expert judgments, the assessment index for EVCS site selection was mainly made from sustainability point of view, which contains of economic, environmental, and social criteria with a total of eleven sub-criteria. BNs are powerful tools for handling risk assessment and decision making under uncertainty. The developed BN model is validated through sensitivity analysis approach. Finally, different propagation analyses have been performed to make special types of reasoning. This paper provides a new research perspective by considering uncertainty, qualitative and quantitative factors into the site selection assessment, and presents the mainstream penetration of BN as a powerful decision making tool in the context of electrical energy management. [ABSTRACT FROM AUTHOR]

The long term impact posed by climate change risk remains unclear and is subject to diverse interpretations from different maritime stakeholders. The inter-dynamics between climate change and ports can also significantly diversify in different geographical regions. Consequently, risk and cost data used to support climate adaptation is of high uncertainty and in many occasions, real data is often unavailable and incomplete. This paper presents a risk and cost evaluation methodology that can be applied to the analysis of port climate change adaptation measures in situations where data uncertainty is high. Risk and cost criteria are used in a decision-making model for the selection of climate adaptation measures. Information produced using a fuzzy-Bayesian risk analysis approach is utilized to evaluate risk reduction outcomes from the use of adaptation measures in ports. An evidential reasoning approach is then employed to synthesize the risk reduction data as inputs to the decision-making model. The results can assist policymakers in developing efficient adaptation measures that take into account the reduction in the likelihood of risks, their possible consequences, their timeframe, and costs incurred. A technical study across 14 major container ports in Greater China is presented to demonstrate the interaction between cost and risk analysis, and to highlight the applicability of the stated methodology in practice. The paper offers a useful analytical tool for assessing climate change risks to ports and selecting the most cost-effective adaptation measures in uncertain conditions. It can also be used to compare the practitioners’ perceptions of climate risks across different geographical regions, and to evaluate improvements after implementation of the selected adaptation measures with potential budgetary constraints. The methodology, together with the illustrative cases, provides important insights on how to develop efficient climate change adaptation measures in a supply chain context to improve the sustainability of development and enhance adaptation measures for ports, port cities, intermodal transport, supply chains, and urban and regional planning in general. [ABSTRACT FROM AUTHOR]

Global warming, as many other threats, requires more activity from the government, and people inquire about this, rightfully so. However, the public and private sectors nowadays have a joint responsibility with society. Global warming has come out of the scientific community and shows that climate change is an important social, economic, and political issue. Currently the carbon dioxide (CO 2 ) emissions by transportation sector are the main polluter of the planet. For this reason, in this paper we propose a reflection on transport, which is an important sector of the economy, responsible for the generation of many jobs and wealth but, at the same time, it has negative impacts on people, companies, and the environment. Recent investigations demonstrate that mobility problems affects the life quality of the people, business productivity and gross domestic product (GDP) performance. In the face of the changes that we are experiencing, it is important to find alternatives that assistance governments in the decision-making to solve the problem of traffic in large and medium-size cities and bring well-being to the population. The goal is to provide accurate tool to help take the best decisions in situations that most of the time has a lack of economic resources and transparency. Another motivation is to increase the productivity of companies and achieve sustainable development by reducing mobility problems and CO 2 emissions. As outcomes of the paper, an in-depth study is presented on the subject that indicates a gap in the literature with fuzzy logic applied to sustainability. We indicate a sustainable option for the transport sector using algorithms for decision-making, and broaden the discussion on climate change and solutions to reduce the impacts caused by humanity. When the models were applied through a conceptual study, it was possible to provide an instrument generated on the use of algorithms that can aid decision-making by getting qualitative data from a discussion with stakeholders on a topic. Finally, the document identifies the importance of the participation of stakeholder, reinforces legitimacy and transparency in decision-making processes and above all present a tool that can help governments to solve this problem. In short, this work proposes an original and valuable tool to be applied in the decision-making process for the sustainable transport sector based on the stakeholder engagement. [ABSTRACT FROM AUTHOR]

What is sustainability? Sustainability is a concept that can be defined in many ways depending upon a society's perception of current material needs and the actual material needs of future generations. Much of our ability to achieve sustainability entails developing indicators and measurements that will guide us to this goal. This paper suggests that we can strengthen the prediction of sustainability indicators by adopting a “multiple equilibria” approach for a more effective decision-making process in various sectors of the economy, in ecosystem protection, or in political arenas. There is an emerging need for further development of predictive mathematical models of system sustainability over economic growth models for sustainable resource measurement and management. The objective of this paper is to use computer modeling and differential equations to simulate the “multiple equilibria” of a 3 variable real world system. In our study, we tested the theoretical validity of “multiple equilibria” sustainability modeling through simulated measurements of precipitation and nitrogen runoff into a hypothetical lake. As a quantitative tool to model, the “multiple equilibria” techniques can have tremendous predictive power for business leaders, political decision makers, and environmental scientists, and assist in better management of ecological, economic, and material resources in short-term and long-term end-use scenarios. [ABSTRACT FROM AUTHOR]

This paper explores the existing social life cycle assessment (SLCA) literature (theoretical and case studies) from decision making perspective. In order to tackle this, a critical review of 90 published work, including journal papers, conference proceedings and book chapters was undertaken. The selected articles were analyzed with a focus on methodological framework, boundary scoping, data inventories and practices. The analysis highlighted the inadequacies in the existing frameworks in terms of flexibility, conflicts in choosing and defining Area of Protection (AoP). Lack of consideration of social conditions of stakeholders in no-work and no-use phase, lack of inclusion of positive impacts, less attention to suppliers and consumers and choice of subjective indicators are highlighted as some weak portions within the boundary scoping. Less coverage of contextual and indirect indicators, and absence of documentation of a link between data collected (subjective indicators) and product activities are highlighted as a limitation within inventories, and finally within practices, lack of benchmarks is highlighted. This analysis highlighted an important differentiating factor between the actual definition of sustainability (maintenance of stocks for future generation) and the most common interpretation in literature as a summation of the three (social, environmental and economic) indices. [ABSTRACT FROM AUTHOR]

The paper draws from the general literature on energy efficiency and historic buildings to explain the importance and potential of user-driven energy efficiency in historic buildings. It is the first review that places the user as a central object of study in the research field of historic buildings and energy efficiency. Relevant interdisciplinary topics and research results that make up the core of the field are presented and discussed in relation to user behaviour and its impact on energy consumption. The paper also investigates how user behaviour aspects can be integrated in a procedural approach to energy refurbishment in historic buildings. Research and experience from the building stock in general clearly shows how a user's awareness and behaviour, such as choice of temperature, zone heating and controlled airing, can have a significant effect on energy demand yet have no physical impact on the building. However, this has not received enough attention with regards to the historic building stock, where many physical energy efficiency measures can have negative impacts on the historic qualities of the building. Modification of user behaviour can therefore be a way not only to reduce energy demand but also to minimise the physical impact of increasing energy efficiency on historic buildings. The paper concludes that the current research agenda on historic buildings and energy efficiency has broken much ground but remains focused more on technical solutions than bottom-up user perspectives. Two main topics are identified as key barriers and future research fields: First, energy performance modelling is identified as a general barrier to developing sustainable strategies that promote user impact in historic buildings. Accurate energy modelling of historic buildings is a complex field reliant on the thermal interplay between user-building and building-district. Improved knowledge and intensified research is necessary to avoid distorted energy modelling results and unwanted rebound effects. Practical tools also require that the modelling can be used for trade-off scenarios where other sustainability aspects such as cultural heritage and economy are weighed in. Second, awareness raising in order to foster a deeper understanding and knowledge about the construction, system and cultural heritage values of a building is proposed as a key ingredient and driver for improved and sustainable energy behaviour. The paper argues that while user-driven energy efficiency represents an important resource for fostering less energy-demanding and less intrusive interventions in historic buildings, there are no guarantees for achieving the planned level of energy efficiency without taking into account user behaviour and the actual operation and energy performance of the historic building. To do this without risking negative consequences, improved decision-making processes are needed on policy, building and user level. An interdisciplinary bottom-up approach to energy refurbishment is presented. The essence of the model is that users and residents should always play a central role in the decision-making process because the well-being of the historic building will always depend on its day-to-day users, and vice versa. [ABSTRACT FROM AUTHOR]

Over the last four decades, Environmental Accounting tools have been developed to conceptualise and quantify the direct and indirect effects of human activity on the environment, to enable decision-makers to track and measure progress towards sustainability outcomes and goals. These environmental accounting methods range from ecological footprinting, carbon footprinting, energy analysis, emergy analysis, ecological pricing and life cycle assessment to environmental input-output analysis. Regrettably, the contemporaneous development of these tools has frequently occurred in isolation from each other, even though they often seek to serve common analytical and evaluative purposes, as well as serving similar communities of interest. It is the central argument of this paper that, in spite of this isolation, the environmental accounting methods have a number of common features − that is, they can be mathematically reduced to similar analytics, and they often confront the same methodological issues − e.g., joint production (co-products) problem, weighting, commensuration, double counting and boundary setting. In this regard the paper reviews how the various environmental accounting tools can ‘learn’ from each other − e.g., how the mathematics of ecological pricing can address the joint production problem in a number of the other environmental accounting methods; and how the insights from input-output analysis can be used in system boundary setting. The paper concludes by agreeing with previous authors, that a better understanding of any given environmental issue is likely to be achieved by using a mix of these environmental accounting tools, rather than relying on just one tool, one perspective or one criterion. [ABSTRACT FROM AUTHOR]

The procurement of high-quality aggregates is a global problem. In Chile, mining companies are in the process of developing massive underground projects that require the extensive use of Portland cement concrete (PCC), approximately 60%–75% of which is aggregate. Currently, mining projects transport all the required aggregate to the site from stockpiles that can be more than 100 km away, while mining excavations produce millions of cubic meters of waste rock (WR) that are disposed of in landfills. The use of WR in PCC seems to be a sustainable solution for the production of PCC, but decision-makers lack the tools to support a sustainable decision based on CO 2 emissions and operation costs. This paper proposes a methodology that uses stochastic simulation tools to evaluate CO 2 emissions and operation costs to decide when it is sustainable to use WR in PCC for underground mining projects. The main objective of this paper is to provide a methodology to quantify CO 2 emissions and the cost of transporting natural aggregate versus recycling WR for PCC production in tunneling operations. A sensitivity analysis is also presented, which considers scenarios that include natural aggregate transportation distances of 50, 60, 70, 80, 90, and 100 km, and 0%, 25%, 50%, 75%, and 100% replacement of natural aggregate with recycled WR in PCC. The results indicate that the use of WR leads to reductions in CO 2 emissions only for natural aggregate transportation distances of greater than 70 km owing to the emissions produced when recycling WR. In addition, 100% replacement of natural aggregate with recycled WR leads to a greater reduction in CO 2 emissions than that obtained in scenarios in which a percentage of the required natural aggregate is obtained from WR. In terms of costs, 100% replacement of natural aggregate with recycled WR is the most economical alternative for most scenarios; however, the cost reduction varies with the required transportation distance of natural aggregate. It is concluded that using 100% recycled WR in PCC leads to lower CO 2 emissions and costs as compared to the traditional approach in which the natural aggregate is procured from a site located at a distance of 70 km or more from the construction site, under model assumptions. [ABSTRACT FROM AUTHOR]

Provision of adequate and affordable housing is a major challenge in both emerging and industrialised countries. With increasing urgency for addressing climate change and other environmental issues these habitats will need to be environmentally sustainable too. Conventional construction, especially in dense urban centres and in rural or remote areas, is putting great pressures on cost and resource efficiency and is compelling the industry and governments globally to question the approach of business-as-usual. Prefabrication or off-site construction can offer great opportunities for both environmental and economic performance and hence is emerging as an attractive alternative to on-site construction. Although in the established markets the share of prefabrication in overall construction output remains strong, in many countries including Australia it still remains in its infancy. In order to enhance the profile of prefab housing and effectively develop high performance sustainable and affordable housing it is vital that first the needs and perceptions of the industry on these issues are adequately studied. This paper relates to the first of a two part research project aimed at exploring the makeup of the prefab housing industry and identifying various challenges and opportunities. The study was conducted as an international industry survey in which barriers, opportunities, performance and perceptions of sustainability and affordability were explored. The paper presents the results of this survey. Based on a cross-sectional analysis the responses are compared and categorised. Among other things the findings highlight the gaps in our understanding of the relationship between sustainability and affordability. This research contributes to the discourse on the need to better understand the role of design and design decision making for developing high performance prefab housing. [ABSTRACT FROM AUTHOR]

Waste management has a crucial role for human health and well-being. The novel waste collection technologies, information and communications technologies (ICTs) and Internet of Things (IoT) play important roles in the field of municipal waste management considering sustainability aspects such as economic, social and environmental. Considering future development and the sustainability of the environment, selecting the most appropriate smart technology to manage waste collection may have long-term impacts. This paper aims to evaluate the smart waste collection systems based on IoT with respect to uncertain parameters by applying modified Entropy measure and Multi-Criteria Decision Making (MCDM) method for the local municipal in Istanbul. To deal with uncertainty and vagueness associated with the decision-making process Interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) is employed in the process. As a result, the waste collection system developed using RFID, GIS and GPRS is selected as the most appropriate smart waste collection system based on IoT for municipal. To validate results and prove robustness of the proposed method in the decision making, Sensitivity and Comparative analysis are conducted at the end of the study. • This paper aims to evaluate the smart waste collection systems based on IoTs. • Modified Entropy based MCDM method is applied for the local municipal in Istanbul. • To deal with uncertainty during decision-making process IVq-ROFSs is employed. • To validate results of the proposed approach, Sensitivity analysis is conducted. • To prove robustness, Comparative analysis is applied at the end of the study. [ABSTRACT FROM AUTHOR]

Increasing attention was given to building information modeling (BIM) and multi-criteria decision-making (MCDM) globally due to their advantages for various stages of the life cycle of a building. The aim of this paper is to improve practitioners' understanding of the process for BIM and MCDM adoption towards sustainable construction through energy efficiency. A questionnaire survey is being conducted for construction professionals and building industry experts in Malaysia. With expert survey data, a multi-criteria decision model using analytical network process (ANP) was built to identify key factors affecting sustainable building by reducing both embodied and operational energy and carbon emissions. Data from the survey was analysed using descriptive statistics. Model developed consisted of three clusters with a total of six nodes, and the level of importance was compared pairwise with one another. Results shows that design optimisation, reduced material requirements are important factors for sustainable construction considered in the BIM application. [ABSTRACT FROM AUTHOR]

In the present paper, the suitability of the selected oilseeds, their corresponding vegetable oils, and few other raw materials to produce bio-based plastics was evaluated by constructing a novel criteria-based framework for Multi-Criteria Decision-Making (MCDM) analysis with a focus on the criteria of chemical functionality, sustainability, production quantity, cost, and market availability. Qualitative, semi-quantitative, and quantitative data was utilized as a base for the criteria, for which a 1–5–9 scaling technique was developed to convert the hybrid starting data into the quantitative form, when required. Additionally, two varying sets of starting data, four scenarios with differing weights of importance, as well as two different MCDM techniques, namely Technique for Order Preference and Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW), were used as a form of sensitivity analysis. The MCDM results were influenced by the dissimilar algorithm of TOPSIS and SAW techniques, resulting in different level of accuracy and a phenomenon of rank reversal, together with the developed MCDM framework in terms of the utilized data types, scaling technique, assumptions to treat data uncertainty as well as the selected criteria and scenarios. Regardless of the different starting data sets, scenarios, and MCDM techniques utilized for the MCDM analysis, tall, linseed, soybean, and palm oil were identified as the most suitable and palm kernel, coconut, and sunflower oil as the least suitable raw materials with their feature trade-offs to produce bio-based plastics. The MCDM results of the present paper can be treated as a guidepost targeted for diverse actors in the early stage of the bio-based plastics' value chain with varying point-of-views. Further, in the future, the novel MCDM framework can be of relevant significance in analysing the features of various raw materials to produce bio-based plastics. [Display omitted] • The suitability of plant-based oils to produce bio-based plastics was evaluated. (82). • Framework for Multi-Criteria Decision-Making (MCDM) analysis was constructed. (72). • MCDM techniques of TOPSIS and SAW were utilized to rank the plant-based oils. (79). • Framework and the type of MCDM techniques influenced on the results. (70). • Tall, linseed, soybean, and palm oil showed the most suitable performance. (76). [ABSTRACT FROM AUTHOR]

Energy management problems associated with rapid institutional, political, technical, ecological, social and economic development have been of critical concern to both national and local governments worldwide for many decades; thus, addressing such issues is a global priority. The main of objective of this study is to provide a review on the application and use of decision making approaches in regard to energy management problems. This paper selected and reviewed 196 published papers, from 1995 to 2015 in 72 important journals related to energy management, which chosen from the “Web of Science” database and in this regard, the systematic and meta-analysis method which called “PRISMA” has been proposed. All published papers were categorized into 13 different fields: environmental impact assessment, waste management, sustainability assessment, renewable energy, energy sustainability, land management, green management topics, water resources management, climate change, strategic environmental assessment, construction and environmental management and other energy management areas. Furthermore, papers were categorized based on the authors, publication year, nationality of authors, region, technique and application, number of criteria, research purpose, gap and contribution, solution and modeling, results and findings. Hybrid MCDM and fuzzy MCDM in the integrated methods were ranked as the first methods in use. The Journal of Renewable and Sustainable Energy Review was the important journal in this paper, with 32 published papers. Finally, environmental impact assessment was ranked as the first area that applied decision making approaches. Results of this study acknowledge that decision making approaches can help decision makers and stakeholders in solving some problems under uncertainties situations in environmental decision making and these approaches have seen increasing interest among previous researchers to use these approaches in various steps of environmental decision making process. [ABSTRACT FROM AUTHOR]

This paper describes an integrated decision analysis method to support the managing board to define a restructuring plan for a small oil refinery in south Brazil. The refinery is facing an extreme crisis situation due to the obsolescence of its production plant. The decision approach proposed in this paper consists of four phases. Initially, potentially performing restructuring alternatives were identified, as well a set of criteria covering the dimensions of corporate sustainability. Based on the relative importance evaluation of each criteria given by a group of decision-makers, and on the performance of the alternatives in each of the criteria, a fuzzy decision-making method, called FETOPIS, was applied for ranking the alternatives. The information resulting from this analysis, along with economic data, was used in a portfolio optimization model to identify restructuring investment projects (RIPs), a combination of feasible restructuring alternatives. FETOPSIS was used again to generate overall performance scores of each RIP, aggregating the individual performances of the constituent alternatives. The application of the method in the refinery demonstrated the efficiency and efficacy of the proposed approach to facilitate the understanding and exploitation of the problem, considering simultaneously several distinct and conflicting dimensions. [ABSTRACT FROM AUTHOR]

• Co-production regularly falls short of its transformation ambitions. • Co-production is being stretched beyond the local into global research and technology spaces. • The meaning of co-production is extended in transformative ways in global gene drive. • Transformative ambitions in gene drive'slip' towards reductive framings of collaboration. • Slippage in co-production can be linked to established and new knowledge hierarchies. Co-production is an increasingly popular framework for knowledge generation, evaluation and decision making. Despite its potential to open up decisions and practices to the input of others, co-production regularly falls short of its transformative ambitions. Through documentary analysis, we investigate the meaning and dynamics of co-production as it stretches beyond the local into global research and technology spaces. We find that in the case of global gene drive, the meaning of co-production is extended in novel ways and underpinned by new possibilities for meaningful transformation. At the same time, we also identify a simultaneous resurfacing of reductive framings of collaboration. In the paper we present 'slippage' as a useful heuristic in helping to understand why co-production fails. We argue that if co-production in these new spaces is to achieve its transformative ambitions, there is a need to engage with new and entrenched knowledge hierarchies that contribute to this slippage. [ABSTRACT FROM AUTHOR]

Local level decision-making can provide a vital and practicable means through which to deliver carbon reductions at individual, household and community levels. This paper explores the opportunities and challenges associated with the role of local government action in delivering a resilient, low carbon future. Drawing on qualitative data gathered through interviews with six case study local authorities in the UK, the paper examines in particular the ways in which they have tried to address energy and environmental goals in their areas of jurisdiction. The principles of Multi-Level Perspective (MLP) are employed to provide fresh insights on the potential for local government to encourage ‘niche’ level influences on economic, technological and social/behavioural innovation. In doing so, we identify the enabling factors and drivers that have given rise to success in linking microlevel goals with existing macro-level objectives, as well as highlighting some of the persistent obstacles that continue to hamper progress. [ABSTRACT FROM AUTHOR]

The aim of this paper is to prefigure the future of urban sustainability governance by implementing crowdsourcing-based solutions for governance processes. We explore the convergence between recent research in urban sustainability governance and crowdsourcing. This is done by reviewing the literature in order to acquire important evidence to support the inductive process of theory building, and to highlight the upcoming trends in participatory research and policy-making that exploit ICT and Web 2.0 social software. Our analysis indicates that a transformative relationship between data and people creates new forms of distant search for solutions and decision making. We argue that interest in crowdsourcing has expanded from computing researches to social and environmental applications. This new practical dimension unlocks the futures of integration of crowdsourcing into best practices in the governance of sustainability in an urban context. Building on evidence that implementing crowdsourcing into the forthcoming governance of urban sustainability is increasingly recognised as a common priority, the paper suggests policy makers to devote more resources to ensure openness, transparency, interoperability and adaptability of crowdsourcing platforms. [ABSTRACT FROM AUTHOR]

Power Plants (PPs) is considered as critical facilities in each region because of essential role through energy generation processes. These facilities are also depended to water availability especially in water stress areas. Due to the critical water shortage in many areas around the world, it is necessary to make an optimal condition among water consumption and the increasing demand for electricity to prevent any further conflict of interests between industry, householders and the environmental goals. There are different techniques for controlling Water Consumption (WC) in these industries. This paper develops a smart Decision Support System (DSS) for monitoring, prediction and control sections based on Artificial Intelligent (AI) and integration of the PESTEL matrix and Multi Criteria Decision Making (MCDM) methods. Monitoring section comprises Fuel Consumption (FC), Atmospheric Temperature (AT), Power Plant Temperature (PPT) and Power Plant Efficiency (PPE), in which FC has the most influence on WC based on ANOVA evaluations in both cold and warm seasons. The prediction results have illustrated that Adaptive Neuro Fuzzy Inference System model is more efficient for the WC estimation with a correlation coefficient over 0.99. Ordered Weighted Averaging (OWA) also demonstrated that in the optimistic and pessimistic states, the most priority is linked to E3 (Establishment of evaporation control systems by contractor companies and concluding a guaranteed purchase contract with a power plant worth one and a half times the current amount of water price). In the last step of technical approaches, the smart controlling system is added for execution of water-energy nexus in the PP based on proportional–integral–derivative controller system. Finally, the performance of the DSS is approved with more than 80% agreement of experts and more than 90% precision in prediction procedure through this investigation. Application of this DSS can also be helpful for developing countries to achieve the UN Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

Sustainability assessment provides essential information to facilitate informed decision-making, enabling the selecting of the best option among various projects. This research paper considers the decision-making problem in the context of marginalised and isolated communities, introducing a groupal model for evaluating the sustainability of small-scale power supply projects. The proposed model incorporates a comprehensive set of five indicators and 25 criteria. The analysis presented in this study prioritises these indicators and criteria, introducing new criteria based on several stakeholders' participation and offering guidance on measuring the identified criteria. Furthermore, the proposal provides fundamental thresholds for evaluating the projects' sustainability and proposes a model based on aggregated indicators to assess the available alternatives. It encompasses all stages of the decision-making process, employing multiple indicators to evaluate the sustainability of power supply projects. The effectiveness of the proposed model was validated in a real case study conducted in a marginalised community facing isolation challenges in La Guajira, Colombia. The evaluation showcased the model's contribution to decision-making processes regarding power supply projects in isolated communities. Finally, the results demonstrated the suitability of this strategy for immediate application, highlighting its potential impact on decision-making for sustainable development within marginalised areas. • The multi-criteria-based decision-making model maximises projects' sustainability. • The model evaluates the projects' sustainability, incorporating innovative criteria. • The model implementation in a study case confirms its efficacy for decision-making. • The study case findings suggest adopting cooperative or community-based governance. [ABSTRACT FROM AUTHOR]

The major objective of this paper is to introduce a novel multi-criteria decision making method (MCDM) called Root Assessment Method (RAM) which is easy to understand, straightforward to use and comparable with other well-known MCDM methods. RAM is motivated by the shortcomings of existing MCDM methods to obtain a reliable result in a decision problem and also the fact that decision maker (DM) should understand the whole decision making process to be able to avoid possible computational pitfalls. To do so, we define an aggregating function to rank the alternatives based on a radical expression which its radicand and index are the sums of benefit and cost criteria of each alternative, respectively. Accordingly, RAM allows a different compensation degree between beneficial and non-beneficial criteria which is rare in existing MCDM methods. As the advantages of RAM, the ranking result is not influenced by additional parameter, beneficial and non-beneficial criteria can be simultaneously considered without any transformation and pairwise comparisons are not used. On the other hand, it is observed that RAM can provide the advantage of preventing rank reversal in two case studies, whereas TOPSIS and VIKOR are subject to this problem in the same cases. As another contribution, a new heuristic procedure is suggested to compare the ranking results obtained by RAM with other methods. Ten numerical examples demonstrate that RAM results are consistent with its presumed function and are easily interpretable for a DM who may not be well acquainted with theoretical aspects of MCDM methods. Examples are positioned in the field of sustainability research as the area with wide application of MCDM methods. The results provided by RAM are encouraging and we hope this method contributes to enrich decision theory. [ABSTRACT FROM AUTHOR]

Water, which is predicted to be one of the most critical resources for the near future, also plays a vital role in society's sustainable development. Wastewater treatment is a critical part of the circular water management system and offers various technological alternatives. Taking appropriate decision for the technology selection is, therefore, essential for a long-term perspective. A complex yet imperative process is the sustainable selection of the wastewater treatment process. This paper presents the use of multi-criteria decision-making (MCDM) in the sustainability assessment of wastewater treatment technologies that may be very relevant to the growing sector with many emerging options. A comparison of six wastewater treatment technologies based on four sustainability parameters using three MCDM techniques, namely FSWARA, FMOORA and FTOPSIS is presented in detail. FSWARA is used for weighting criteria and the other two for technology ranking. The detailed step-by-step comparison study is presented and the results were somewhat predictable for the study, and this confirms the reliability of the methodology. This paper's primary objective is to propose a well-defined increscent practice for making sustainable wastewater treatment decisions among state-of-the-art technologies. • Sustainability ranking of wastewater treatment technologies using multi-criteria decision making methods. • Combined Fuzzy SWARA-MOORA and fuzzy SWARA-TOPSIS methods. • While weighing the criteria, most significance is given to environmental factors. • Inclusion of both conventional and non-conventional technologies. [ABSTRACT FROM AUTHOR]

One of the problems facing researchers in the application of renewable energy systems is that the evaluation of the sustainability is extremely perplex. Decision making in energy projects requires consideration of technical, economic, environmental and social impacts and is often complicated. This paper presents a review of the current state of the art in decision support methods applied to renewable and sustainable energy throughout the literature in the field of energy planning. The selected papers were classified by their year of publication, decision making technique, energy type, the criteria used, geographic distribution and the application areas. [ABSTRACT FROM AUTHOR]

Performance indicators (PIs) are essential in the benchmarking process used to rate and rank water companies. However, a set of individual PIs does not provide a holistic assessment of company performance from multiple perspectives. A multidimensional evaluation of the performance of water companies can be achieved by aggregating the PIs into a synthetic indicator. Although the concept of sustainability involves economic, environmental and social criteria, most of the previous studies have not considered these three dimensions simultaneously. This paper discusses a process of indicator aggregation using two approaches based on multi-criteria decision analysis to evaluate and compare the sustainability of water companies from a holistic perspective. A synthetic indicator embracing economic, environmental and social PIs was computed for a sample of 154 Portuguese water companies. Both methods yielded similar rankings of water company sustainability. The techniques and results presented in this paper may be utilized as a means of improving the benchmarking process in regulated water industries, as well as providing valuable contributions to decision-makers on the most efficient steps for improving the sustainability of urban water services. [ABSTRACT FROM AUTHOR]

Customers’ individual preferences are calling for more variety of the firms offerings. Faced with this situation, firms endeavor to meet customer requirements while reducing their costs and impact on environment in order to remain competitive. Further on, achieving such a goal entails various issues that need to be tackled such as the multiple performance drivers and criteria relating to sustainability and variety. Accordingly, tradeoffs need to be defined and balanced between such heterogeneous criteria in order to facilitate the decision making process on variety levels with regards to sustainability impact. These tradeoffs should involve decision makers so as to reflect firm priorities and takes into account its realm. This paper proposes an approach supporting the decision making process on variety delivered to the market while taking into account sustainability criteria. More specifically, the approach uses performance indicators which are calculated by LCA based tools, then applies weightings, and finally computes the expected variety levels for a given demand data. The paper highlights the impact of variety steering on environmental and economic sustainability indicators. [ABSTRACT FROM AUTHOR]

In the context of sustainable densification of post-industrial European cities, regeneration of disused urban areas offer an important potential of surfaces to recapture. Indeed, these projects can contribute concurrently to densify and revitalize existing built fabrics. Although numerous initiatives of this type can be observed, the integration of sustainability issues is in most cases partial or superficial. As a matter of fact, achieving the goals of sustainable development is not a spontaneous process. It depends upon a proactive search of global quality, integrated into the project dynamics, and a continuous assessment of the environmental, social and economic dimensions of sustainability adapted to the specificities of such projects. Based on these considerations, this paper introduces the indicator system entitled SIPRIUS, designed for the assessment of sustainability integrated into the project dynamics of regeneration of disused urban areas. First, the methodology that stands behind the development of SIPRIUS is exposed. Then, the paper presents the potential of SIPRIUS and its adequacy with concrete situations through a test application performed on a project underway in Neuchâtel (Switzerland). It reveals that an adapted and structured assessment approach truly contributes to integrating sustainability into regeneration of disused urban areas. Furthermore, future work will include the adaptation of SIPRIUS into a digital monitoring tool in order to make it accessible to key stakeholders involved in this type of operations. [ABSTRACT FROM AUTHOR]

Could the theory of Strategic Environmental Assessment (SEA) be ahead of its time and decoupled from its practice? This paper evolved in search for this leading research question. Over the years the discourse on SEA experienced a gradual shift from the technocratic and rationalist thinking that supported its origin to more strategic approaches and integrated concepts, suggested since the mid 1990's. In this paper we share the results of our analysis of international thinking and practical experience with SEA. Results reveal that SEA practice changes very slowly when compared to advanced thinking supporting the noted shift. Current SEA practice shows to be still predominantly rooted in the logic of projects' environmental impact assessment (EIA). It is strongly bound to legal and regulatory requirements, and the motivation for its application persists being the delivery of environmental (or final) reports to meet legal obligations. Even though advanced SEA theoretical thinking claim its potential to help decisions to look forward, change mind-sets and the rationale of decision-making to meet sustainability challenges and enhance societal values, we note a weak relationship between the theoretical development of SEA and its practice. Why is this happening? Which factors explain this apparent inertia, resistance to change, in the SEA practice? Results appear to demonstrate the influence of assumptions, understandings, concepts, and beliefs in the use of SEA, which in turn suggest the political sensitivity of the instrument. [ABSTRACT FROM AUTHOR]

In a context of Small and Medium Enterprises (SMEs), the concept of sustainability has become increasingly important within the decision making strategies. The competitiveness and uncertain environment has also a key role for decision makers to find best practices to achieve sustainability which is concerned with integrating environmental, social and economic goals across a supply chain process. This paper proposes an intelligent dynamic system driven by agents that integrates Fuzzy Logic (FL) and Multi-criteria/multi-objective decision making (MC/MODM) methods to highlight the assessment process of the triple bottom line performance from a small scale (SMEs) to a large scale supply chain under uncertainty. [ABSTRACT FROM AUTHOR]

This paper proposes MULTIMOORA-IFN2 technique for multi-criteria decision making MCDM). The proposed approach involves information fusion which allows considering information expressed in both crisp and fuzzy variables. What is more, we introduce the aggregation of the different parts of MULTIMOORA which makes the technique more operational, especially in case of large-scale applications. The empirical example considers the case of energy storage technology selection. The sensitivity of the results obtained by applying MUTIMOORA-IFN2 is checked in two ways. The weighting is adjusted to ascertain whether the changes in the importance of the criteria impact the ranks of the energy storage technologies. Further on, the results obtained by applying MULTIMOORA-IFN2 are compared to those obtained by employing TOPSIS and VIKOR methods. • The MULTIMOORA approach for intuitionistic fuzzy sets is revised. • Intuitionistic fuzzy sets are applied for information fusion. • Energy storage technologies are assessed. • Technical, economic, and environmental criteria are considered. • Different scenarios are assumed for robustness analysis. [ABSTRACT FROM AUTHOR]

Assessments and sustainable management of ecosystem services (ES) require an understanding of both ES supply and demand qualities, quantities, spatial scales and dynamics. Mismatches, i.e., differences in quality or quantity between the supply and demand of ES, can occur in many different forms. Being able to identify these mismatches and their nature is of prime importance for informing governance and management decisions. This manuscript explores which mismatches can be detected by current ES supply and demand assessments and which mismatches currently remain unidentified. An analytic framework was developed comprised of five interlinked components of ES supply and demand linking nature and society (i.e., potential supply, managed supply, match, demand, and interests). This framework was used to examine 11 recent papers, which applied ES assessments to both ES supply and demand, to determine which mismatches were or could be identified and which mismatches remained unidentified. The selected papers typically used multiple methods in their assessments to capture supply and demand components. The found diversity in methods and the inclusion of temporal and spatial dimensions, and the existence of multiple stakeholder groups allowed for the assessments to identify several mismatches, but also lead to differences in the discriminative capacity of the assessments between the selected papers. The mismatch that was most often included in the assessments was Unsatisfied demand , whereas the least included mismatch was Unsustainable uptake. The mismatches caused by differing spatial patterns were most often identified, whereas the existence of mismatches among different stakeholder groups was least often detected in the assessment methods. Three options emerged that could further strengthen the discriminative capacity of ES supply and demand assessments to inform sustainable ES governance and management decisions: (i) include multiple stakeholders groups and the diversification of their roles and demands; (ii) acknowledge that ES supply is not only determined by the bio-geophysical conditions, but also determined by the ES demand by society, in terms of their quantity, quality and location, as well as by the applied management; (iii) include temporal and spatial scale sensitivity into the discriminative capacity of assessment methods to allow for a better identification which institutional structures could most effectively act upon them. [ABSTRACT FROM AUTHOR]

This paper applies an Analytic Network Process (ANP) to supplier selection at a Taiwanese Electronics Company. The selection process is based on the Triple Bottom Line (TBL). It shows that the use of ANP helps to capture the imprecision in human judgment while TBL enables the consideration of social development, environmental protection, and economic development issues. With TBL, a holistic view of the company is taken in the decision making process. A framework is developed to enable general application of ANP. A case study using ten company executives from an anonymous Taiwanese company is used to illustrate the framework, and also to identify the key factors in supplier selection. Our results, which are consistent with other research findings, show that product design for sustainability and green supply chain management are the most important factors in supplier selection. This is also consistent with our earlier results in the paper which showed environmental protection has the highest priority index among the three components of TBL, namely social development, environmental protection, and economic development. [ABSTRACT FROM AUTHOR]

Catastrophic incidents can generate a large number of samples of analytically diverse types, including forensic, clinical, environmental, food, and others. Environmental samples include water, wastewater, soil, air, urban building and infrastructure materials, and surface residue. Such samples may arise not only from contamination from the incident but also from the multitude of activities surrounding the response to the incident, including decontamination. This document summarizes a range of activities to help build laboratory capability in preparation for sample analysis following a catastrophic incident, including selection and development of fit-for-purpose analytical methods for chemical, biological, and radiological contaminants. Fit-for-purpose methods are those which have been selected to meet project specific data quality objectives. For example, methods could be fit for screening contamination in the early phases of investigation of contamination incidents because they are rapid and easily implemented, but those same methods may not be fit for the purpose of remediating the environment to acceptable levels when a more sensitive method is required. While the exact data quality objectives defining fitness-for-purpose can vary with each incident, a governing principle of the method selection and development process for environmental remediation and recovery is based on achieving high throughput while maintaining high quality analytical results. This paper illustrates the result of applying this principle, in the form of a compendium of analytical methods for contaminants of interest. The compendium is based on experience with actual incidents, where appropriate and available. This paper also discusses efforts aimed at adaptation of existing methods to increase fitness-for-purpose and development of innovative methods when necessary. The contaminants of interest are primarily those potentially released through catastrophes resulting from malicious activity. However, the same techniques discussed could also have application to catastrophes resulting from other incidents, such as natural disasters or industrial accidents. Further, the high sample throughput enabled by the techniques discussed could be employed for conventional environmental studies and compliance monitoring, potentially decreasing costs and/or increasing the quantity of data available to decision-makers. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the strategic environmental assessment (SEA)–sustainability relationship over the past decade, from 2000 to 2010, focusing in particular on the incorporation of sustainability in SEA. A total of 86 papers from the academic literature containing the terms ‘sustainability’ or ‘sustainable development’ and ‘strategic environmental assessment’ were identified and reviewed. Several common themes emerged by which SEA can support sustainability, including providing a framework to support decision making for sustainability; setting sustainability objectives, ensuring the consideration of ‘more sustainable’ alternatives, and integrating sustainability criteria in PPP development; and promoting sustainability outcomes through tiering and institutional learning. At the same time, our review identified many underlying barriers that challenge SEA for sustainability, including the variable interpretations of the scope of sustainability in SEA; the limited use of assessment criteria directly linked to sustainability objectives; and challenges for decision-makers in operationalizing sustainability in SEA and adapting PPP development decision-making processes to include sustainability issues. To advance SEA for sustainability there is a need to better define the scope of sustainability in SEA; clarify how to operationalize the different approaches to sustainability in SEA, as opposed to simply describing those approaches; provide guidance on how to operationalize broad sustainability goals through assessment criteria in SEA; and understand better how to facilitate institutional learning regarding sustainability through SEA application. [Copyright &y& Elsevier]

• An integrated decision model is presented for resilience and sustainability assessment. • The framework includes three modules, four sets of criteria, and three decision models. • Damage to non-structural components increases expected number of injuries markedly. • In MCDM, benefits of sustainable design can outweigh other performance shortcomings. • Proposed diagrid form achieved better scores than original one in decision analysis. Resilience and sustainability are both key criteria in risk-informed decision analysis of structural systems. However, a comprehensive framework which incorporates both in a multi-criteria decision-making (MCDM) process is yet to be developed particularly for more recent structural systems such as diagrids. This paper introduces a coupled resilience- and sustainability-based decision-making framework for seismic design and rehabilitation of building structures. FEMA method for intensity-based and time-based loss, downtime, and casualty estimation are used to evaluate seismic asset, time, and life losses. Economic input-output life-cycle assessment method is adapted to evaluate the environmental loss due to earthquakes, as well. Aiming to study the trade-off between various economic, social, and environmental impacts of earthquakes, an MCDM framework is proposed based on analytic hierarchy process, multi-attribute utility theory, and technique for order preference by similarity to ideal solution (TOPSIS). The framework is used to study the resiliency and sustainability of archetype steel diagrid buildings in a high seismic region. Six scenarios with different objectives including minimum asset, time, life, or environmental loss and maximum resilience are studied. A survey is conducted to find the weight factors for each criterion for each scenario. Results show that in an MCDM framework, the benefits of sustainable design techniques can outweigh possible shortcomings due to structural configuration and performance. [ABSTRACT FROM AUTHOR]

The growing role of sustainability in the construction industry must be considered in the entire lifecycle of a building. This way BIM (Building Information Modeling) figures as an important factor in the management of this lifecycle, from design and construction, through the operation and maintenance until the demolition. An efficient interoperability along the lifecycle supported by BIM allows an overall better management and help users to improve sustainability of projects. This interoperability must consider not only data, but also should be concerned with broader aspects, such as processes and guidelines, avoiding information loss, facilitating analysis, and therefore, improving sustainability. In the light of this scenario, a systematic literature review was performed considering sustainability factors, interoperability concerns and lifecycle stages. This review was based on existing methods complemented by a multicriteria decision analysis method to aid the selection of relevant papers. Also, a qualitative data analysis was performed to identify the relations of the fields studied. Results showed that even though some fields receive much attention in the literature, few studies are performed considering interoperability in the entire lifecycle of sustainable buildings. Also, results showed the relevant connections among lifecycle stages and sustainability fields, providing an influence matrix of these two areas. This review can be used as a tool to organize knowledge and data and systematize processes and even to structure interoperability frameworks. [ABSTRACT FROM AUTHOR]

For the last decades, Sustainable Development has been encouraged to be integrated into the operations of business organisations. Businesses are being blamed to cause environmental degradation and social problems because of their unsustainable activities. However, to know whether businesses are implementing sustainable strategies in their operations, a Business Sustainability Performance Assessment (BSPA) is required. As a result, many approaches, tools, and techniques have been devised to assess sustainability performance at the business level. Therefore, this study aims at identifying the various sustainability assessment approaches, tools, and techniques at the business level. A systematic literature review was conducted whereby 38 related articles from 2000 to 2021 were obtained and analyzed. Following the review, 5 different approaches were identified namely: application of established guidelines; normative framework; management system; index system; and rating/ranking system. Under each approach, there are different tools. In all, 88 tools were obtained. Furthermore, 9 techniques were identified and classified into 4 functional categories. Techniques such as Fuzzy Logic, Multi-Criteria Decision Analysis, and Principle Component Analysis were predominantly favoured by researchers. However, there was no consensus on which method or tool is best for BSPA. A bibliometric analysis found that 60% of studies used the environmental, social, and economic dimensions for performance assessment. Results demonstrated that the application of BSPA approaches, tools, and techniques had been receiving attention across various industries and the application was more toward industry-generic context rather than industry-specific. Finally, the paper presents key research issues on BSPA and proposes future studies based on reported data. [ABSTRACT FROM AUTHOR]