Sustainable Management Research Articles

Life Cycle Patterns of Epigeic Earthworm Species (Eisenia fetida, Eisenia andrei, and Dendrobaena veneta) in a Blend of Brewery Sludge and Cow Dung

Comprehending the growth and reproductive capabilities of vermicomposting worm species across diverse wastes from various sources is crucial for the effective utilization of earthworms in sustainable waste management systems. This study evaluated the growth and reproductive potential of three epigeic earthworm species in a substrate comprising brewery sludge mixed with cow dung. Following the introduction of sexually matured earthworm species into the experimental substrate, E. fetida released 165 ± 0.88 cocoons at a reproduction rate of 32.8 ± 0.67 cocoons/worm, E. andrei released 164 ± 1.48 cocoons at a cocoon production rate of 32.19 ± 1.38 cocoons/worm, and D. veneta released 110.25 ± 1.2 cocoons at a cocoon production rate of 22.7 ± 1.5 cocoons/worm. The incubation period for E. fetida and E. andrei ranged between 3 and 4 weeks, while D. veneta required a relatively longer period of 5 to 7 weeks. After the introduction of newly hatched hatchlings into the test substrate, a similar pattern of biomass increment was observed between E. fetida and E. andrei, with both species exhibiting progressive growth up to the 5th week. In D. veneta, successive biomass increments were recorded up to the 7th week, after which the biomass of each experimental species gradually declined. The current study demonstrated that all experimental earthworm species exhibited robust growth and reproductive performance in brewery waste mixed with cow dung.

Sensitivity of daily reference evapotranspiration to weather variables in tropical savanna: a modelling framework based on neural network

Accurate prediction of reference evapotranspiration (ETo) is crucial for many water-related fields, including crop modelling, hydrologic simulations, irrigation scheduling and sustainable water management. This study compares the performance of different soft computing models such as artificial neural network (ANN), wavelet-coupled ANN (WANN), adaptive neuro-fuzzy inference systems (ANFIS) and multiple nonlinear regression (MNLR) for predicting ETo. The Gamma test technique was adopted to select the suitable input combination of meteorological variables. The performance of the models was quantitatively and qualitatively evaluated using several statistical criteria. The study showed that the ANN-10 model performed superior to the ANFIS-06, WANN-11 and MNLR models. The proposed ANN-10 model was more appropriate and efficient than the ANFIS-06, WANN-11 and MNLR models for predicting daily ETo. Solar radiation was found to be the most sensitive input variable. In contrast, actual vapour pressure was the least sensitive parameter based on sensitivity analysis.

Bridging operations research and machine learning for service cost prediction in logistics and service industries

AbstractOptimizing shared resources across multiple clients is a complex challenge in the production, logistics, and service sectors. This study addresses the underexplored area of forecasting service costs for non-cooperative clients, which is essential for sustainable business management. We propose a framework that merges Operations Research (OR) and Machine Learning (ML) to fill this gap. It begins by applying the OR model to historical instances, optimizing resource allocation, and determining equitable service cost allocations for each client. These allocations serve as training targets for ML models, which are trained using a combination of original and augmented client data, aiming to reliably project service costs and support competitive, sustainable pricing strategies. The framework’s efficacy is demonstrated in a reverse logistics case study, benchmarked against two traditional cost estimation methods for new clients. Comparative analysis shows that our framework outperforms these methods in terms of predictive accuracy, highlighting its superior effectiveness. The integration of OR and ML offers a significant decision-support mechanism, improving sustainable business strategies across sectors. Our framework provides a scalable solution for cost forecasting and resource optimization, marking progress toward a circular, sustainable economy by accurately estimating costs and promoting efficient operations.

Can multi-stakeholder platforms and dialogues facilitate the meaningful and effective participation of Indigenous Peoples in managing natural resource conflicts?

Indigenous Peoples have important roles and contributions in the systematic and sustainable management of natural resources; however, their full and effective participation in the related processes, mechanisms including related multi-stakeholder platforms, and dialogues (MSPDs) are not always ensured at the national and global levels. This article focuses on the review and analysis of the published and online papers, reports on Indigenous Peoples, and their contributions and conflicts related to natural resources, especially concerning power, politics, and policies with specific examples in the Asian context. The interest-based “power sharing” and “power with governance” model is appropriate for the effective engagement of Indigenous Peoples in multi-stakeholder dialogue on natural resources.

Predictive Models for Optimal Irrigation Scheduling and Water Management: A Review of AI and ML Approaches

Purpose: Maintaining agricultural output, protecting water supplies, and lessening environmental effects all depend on effective water management. Through a comprehensive review of the literature and an in-depth analysis of various AI and ML techniques, this paper aims to put light on the cutting-edge approaches used in irrigation scheduling predictive modeling. The goal of the research is to determine the advantages, disadvantages, and future directions of AI and ML-based irrigation management systems by means of a methodical analysis of various algorithms, data sources, and applications. Additionally, the study seeks to demonstrate how data-driven methods can enhance irrigation systems' sustainability, accuracy, and precision. Stakeholders in agriculture, water resource management, and environmental conservation can make well-informed decisions to maximize irrigation scheduling techniques by having a thorough understanding of the theoretical underpinnings and practical applications of predictive models. The study also attempts to tackle issues like scalability, model interpretability, and lack of data when implementing AI and ML solutions for practical irrigation management. In final form, this review's conclusions advance our understanding of how to use AI and ML to improve agricultural systems' resilience and water use efficiency, supporting adaptive and sustainable water management strategies in the face of rising water scarcity concerns and climate change. Design/Methodology/Approach: In order to gather information for this review study, several research articles from reliable sources were analyzed and compared. Objective: To provide the current research gaps in prediction models for the best irrigation scheduling and water management, and suggest using AI and ML techniques to fill in these gaps. Results/ Findings: In response to the growing challenges of water scarcity and climate change, the paper's findings highlight the transformative potential of AI and ML techniques in optimizing irrigation scheduling, enhancing agricultural resilience, increasing water use efficiency, and supporting adaptive and sustainable water management strategies. Originality/Value: This paper's uniqueness and significance come from its thorough analysis of AI and ML approaches in predictive modeling for ideal water management and irrigation scheduling. It also provides insights into new methods and their possible effects on resource optimization and agricultural sustainability. Type of Paper: Literature Review.

Environmental Management Framework for Road Network Demolition Wastes for Construction Industry of Pakistan

Demolition waste from construction industry, especially from road networks, is one of the most voluminous and harmful categories of waste worldwide; therefore, its proper handling is essential for sustainable waste management for environmental, social, and economic benefits. Prolific and unregulated construction activities, conflicts, and defective works are major reasons. The current work aims to address the issue by presenting a framework for an enhanced understanding of sustainable demolition waste management (DWM). A critical analysis of the literature aided to identify major concerns related to different causes, their impacts, and challenges being faced by the construction industry in such management endeavors. The study adopted questionnaire-based methodology to understand the critical relation among the three variables. The Delphi technique supported by industry professionals and pilot study helped to formulate a realistic questionnaire tool. Using the concept of multivariate statistical analysis, structure equation modeling (SEM) helped to assess the structural relationships between the three variables. The research instrument met the reliability, validity and internal consistency criteria required. Each variable achieved a high effect size, f2, with a value of co-efficient of determination of more than the threshold value of 70%. Thus, this supported the fitness criterion of the SEM-based measurement model. Path coefficients yielded the acceptance of all alternate hypotheses, resulting in a strong positive relationship among the three constructs. Therefore, demolition waste impacts are deemed as an effective mediator when explaining the impact between the other two variables. The developed framework presents a coherent and systematic approach and identifies strategies that could be used to address these issues and lead to DWM, including options available for capacity building and implementation and evaluation for supporting sustainability.

Global perspectives and transdisciplinary opportunities for locust and grasshopper pest management and research

Locusts and other migratory grasshoppers are transboundary pests. Monitoring and control, therefore, involve a complex system made up of social, ecological, and technological factors. Researchers and those involved in active management are calling for more integration between these siloed but often interrelated sectors. In this paper, we bring together 38 coauthors from six continents and 34 unique organizations, representing much of the social-ecological-technological system (SETS) related to grasshopper and locust management and research around the globe, to introduce current topics of interest and review recent advancements. Together, the paper explores the relationships, strengths, and weaknesses of the organizations responsible for the management of major locust-affected regions. The authors cover topics spanning humanities, social science, and the history of locust biological research and offer insights and approaches for the future of collaborative sustainable locust management. These perspectives will help support sustainable locust management, which still faces immense challenges such as fluctuations in funding, focus, isolated agendas, trust, communication, transparency, pesticide use, and environmental and human health standards. Arizona State University launched the Global Locust Initiative (GLI) in 2018 as a response to some of these challenges. The GLI welcomes individuals with interests in locusts and grasshoppers, transboundary pests, integrated pest management, landscape-level processes, food security, and/or cross-sectoral initiatives.

Forest Management Type Identification Based on Stacking Ensemble Learning

Forest management is the fundamental approach to continuously improve forest quality and achieve the quadruple functions of forests. The identification of forest management types is the basis of forest management and a key technical link in the formulation of forest management plans. However, due to insufficient application of forestry informatization and digitization, there are problems in the organization and application of management types, such as inaccurate identification, diversified standards, long organizational cycles, and low decision-making efficiency. Typical technical models are difficult to widely promote and apply. To address these challenges, this study proposes the Stacking Ensemble Forest Management Type Identification (SEFMTI) method based on Stacking ensemble learning. Initially, four typical forest management types from the sustainable forest management pilot of the Yichun Forestry Group were selected as research subjects, and 19 stand parameters were chosen to form the research data, training various recognition models. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression and random forest (RF) methods were used to analyze key decision-making indicators for forest management type recognition and compare the performance of different models. The results show that (1) the SEFMTI model achieved an accuracy rate of 97.14%, effectively improving the accuracy of forest management type recognition while ensuring stability; (2) average age (AG), age group (AGG), crown density (CD), and stand origin (SO) are key decision-making indicators for recognizing forest management types; and (3) after feature selection, the SEFMTI model significantly enhanced the efficiency of model training while maintaining a high accuracy rate. The results validate the feasibility of the SEFMTI identification method, providing a basis for the gradual implementation of sustainable forest management pilots and aiding in the precise improvement of forest quality.

Potential of Cold-Water Agriculture (ColdAg) in Mexico: Challenges and Opportunities for Sustainable Food Production

To guarantee sustainable development at a global level, humanity currently faces serious challenges related to a greater demand and better distribution of food to meet the needs of the growing population in environments affected by global climate change (GCC), and in limiting conditions with respect to natural, genetic, financial, and technological resources. Therefore, there is a dire need to implement technologies that can guarantee food security and sovereignty around the world, enabling sustainable development for all nations. Cold-Water Agriculture (ColdAg) is an available technology that offers an alternative to conventional food production in coastal areas and islands of the tropical and subtropical belts worldwide, making use of cold deep ocean water. Mexico has places with the optimal environmental conditions to adapt this technology, mainly in coastal areas and islands, which can contribute to ensuring access to food and drinking water. Initial tests have shown its viability, while production costs need to be adjusted to make this technology accessible to the poorest populations, so that it can contribute to their sustainable development and wealth. In this review article, we aimed to critically analyze some of the most salient literature on the ColdAg technology and outline the feasibility of this technology to be implemented and exploited in Mexico to contribute to alternative food production in a sustainable manner.

Investigating the Role of Municipal Waste Treatment within the European Union through a Novel Created Common Sustainability Point System

Over the last several decades, the European Union (EU) has championed recycling and sustainable waste management through Directives 2008/98/EC and 2018/851, shaping practices across its member states. Currently, 30% of the EU’s municipal waste is recycled, 19% composted, 23% incinerated, and 23% landfilled. However, regional variations exist within the EU, with Greece and other Mediterranean/Balkan nations favoring landfilling, while Germany and other Western/Central EU nations prioritize recycling and composting, and Nordic countries lean toward incineration. To address these differences, a new sustainability point system was created in order to evaluate and compare all different municipal waste management strategies of EU members. Notably, countries like Germany, the Netherlands, and Sweden score the highest due to low municipal waste generation, high recycling rates (>35%), minimal landfilling (<1%), and significant incineration. In contrast, Cyprus, Malta, and Greece score lower due to landfill reliance and lower recycling rates. Therefore, this study introduces a novel sustainability point system to mitigate disparities, highlighting the need for targeted interventions and policy initiatives at the national and EU levels. By leveraging these insights, policymakers can allocate resources effectively, foster collaboration, and motivate citizens to achieve common environmental goals as well as the Sustainable Development Goals (SDGs).

Low-Cost Grey Water Treatment System Design And Treatability Studies In Relation To Recycling And Reuse In Rural Area of Angul District of Odisha

As global water scarcity intensifies, there is a growing need for sustainable water management solutions, particularly in rural areas where access to clean water is often limited. This study focuses on the development of a low-cost greywater treatment system tailored for rural settings, emphasizing the recycling and reuse of greywater. The research encompasses the design, implementation, and treatability studies of the proposed system, aiming to provide an affordable and effective solution for improving water sustainability in resource-constrained communities. The designed greywater treatment system incorporates cost-effective technologies and locally available materials to ensure its feasibility in rural contexts. The treatability studies explore the system's efficiency in removing contaminants commonly found in greywater, evaluating its potential to meet water quality standards suitable for various non-potable applications. Emphasis is placed on the system's adaptability to local conditions, promoting community engagement and ownership for long-term sustainability. By addressing the unique challenges faced by rural areas, this research contributes to the broader goal of achieving water security through decentralized, affordable, and environmentally conscious greywater treatment solutions. The findings from this study can inform policymakers, engineers, and local communities on practical approaches to enhance water quality, reduce environmental impact, and promote water recycling and reuse in rural settings.

Navigating Supply Chain Resilience: A Hybrid Approach to Agri-Food Supplier Selection

Globalization and multinational commerce have increased the dynamism and complexity of supply networks, thereby increasing their susceptibility to disruptions along interconnected supply chains. This study aims to tackle the significant concern of supplier selection disruptions in the Thai agri-food industry as a response to the aforementioned challenges. A novel supplier evaluation system, PROMETHEE II, is suggested; it combines the Fuzzy Analytical Hierarchy Process (FAHP) with inferential statistical techniques. This investigation commences with the identification of critical indicators of risk in the sustainable supply chain via three phases of analysis and 315 surveys of management teams. Exploratory factor analysis (EFA) is utilized to ascertain six supply risk criteria and twenty-three sub-criteria. Following this, the parameters are prioritized by FAHP, whereas four prospective suppliers for an agricultural firm are assessed by PROMETHEE II. By integrating optimization techniques into sensitivity analysis, this hybrid approach improves supplier selection criteria by identifying dependable solutions that are customized to risk scenarios and business objectives. The iterative strategy enhances the resilience of the agri-food supply chain by enabling well-informed decision-making amidst evolving market dynamics and chain risks. In addition, this research helps agricultural and other sectors by providing a systematic approach to selecting low-risk suppliers and delineating critical supply chain risk factors. By bridging complexity and facilitating informed decision-making in supplier selection processes, the results of this study fill a significant void in the academic literature concerning sustainable supply chain risk management.

Design and management considerations towards productively sustainable work places in Saudi Arabia

Purpose This paper aims to review and assess the sustainable design and management considerations affecting workplaces’ productivity in Saudi Arabia. Design/methodology/approach The study uses a mixed approach, commencing with literature review, development and pilot-testing of a structured questionnaire instrument to assess design and management considerations towards productively sustainable workplaces (PSWs). In total, 31 considerations affecting sustainable workplaces’ productivity were identified and clustered under five main directions. A collective group of stakeholders, including architects/engineers (A/E), workplace users and facilities managers, were approached to correlate and compare their individual assessment of the identified PSWs. The relative importance index (RII) for each of the PSW considerations is correlated and discussed. Findings A high level of agreement is recognized among the three stakeholder groups for PSWs considerations’ assessed rankings. The provision of sufficient ventilation and illumination levels, availability of occupational health, security and safety, availability of ergonomically oriented technological infrastructure, availability of formal and informal meeting spaces, efficient space utilization and ergonomic workstations are all ranked highest in importance as design considerations towards PSWs. Originality/value The study stems from the need to understand how the PSWs’ design and management considerations are perceived by all streams of stakeholders. The findings identify the considerations’ importance for prioritization on PSWs’ investments.

Exploring sustainable and cost-effective wastewater management solutions for urban India through life cycle cost analysis: a case study approach

Exploring sustainable and cost-effective wastewater management solutions for urban India through life cycle cost analysis: a case study approach

Optimizing scope 3 emissions in the automotive manufacturing industry: a multidisciplinary approach

The acceleration of global climate change poses enormous challenges to the automotive manufacturing industry, a key sector in reducing greenhouse gas (GHG) emissions. Particularly, Scope 3 emissions, encompassing indirect emissions, often constitute the largest carbon footprint component in this sector, yet their quantification and management remain challenging. This paper proposes an interdisciplinary approach that integrates cloud computing, text analysis, and machine learning, and systematically details its implementation, key benefits, and potential applications. Through this methodology, the paper seeks to provide the automotive industry with innovative and actionable insights to tackle the complexities of Scope 3 emissions. It focuses on enhancing the accuracy of emission quantification and optimizing supply chains, aiming to reduce the overall carbon footprint. Moreover, this paper outlines the future challenges and directions for these technologies and methodologies in sustainable development and environmental management. This work underlines the critical role of interdisciplinary approaches in resolving environmental challenges, setting the stage for the automotive industry to forge paths towards a greener future.Graphical

Known and potential benefits of applying herbicides with glutathione S-transferase inhibitors and inducers – a review

Abstract Weed resistance to herbicides has increased exponentially during the past 30 to 40 years, consequently reducing the number of effective products available to control certain species and populations. Future efforts should target not only the discovery of new protein binding sites and the development of new molecules, but also the revival of old molecules with reduced efficacy due to widespread herbicide resistance. The addition of herbicide synergists that inhibit metabolic pathways or enhance intrinsic plant stress is a possible solution to ameliorate the negative effects caused by the lack of new herbicide chemistries. Glutathione S-transferase (GST) enzymes are involved with numerous herbicide detoxification reactions and plant stress responses. This review approaches the potential use of natural and synthetic GST-inhibitors to enhance herbicidal activity or induce crop safety to provide effective, sustainable weed management strategies in the future.

Environmental Control and Management Continuation Through the Ruling of the State Administrative Court

Changes in environmental law provisions that have the potential to cause inconsistencies in these decisions must be harmonized with the legal system. Without consistency in decisions regarding environmental public administration disputes, it will be difficult for the government to make decisions and guideline for determining policies related to environmental protection and management. The aim of this research is to determine the consistency of environmental administration dispute decisions in state administrative courts. The writing method uses a normative juridical approach with statutory regulations, the legal sources used are primary and secondary legal sources relating to state administrative law and those relating to environmental regulations, apart from that the author uses a case study approach. The results of the research show that the implementation of regulations related to state administrative decisions in the environmental sector is still inconsistent, with the government placing more emphasis on remedial (retroactive) efforts in environmental problems which are manifested in the form of government intervention to restore environmental conditions after pollution and/or damage occurs. environment. Considering that the majority of environmental law enforcement is in the field of government administration, inconsistencies in environmental state administration decisions must be resolved immediately to realize good environmental protection and management. In fact, the decision of the state administrative court judge is not only intended to resolve a dispute but will also serve as a guideline for government agencies/officials in realizing sustainable environmental protection and management.

Determinants of spatial distribution of trees outside forests along urban-rural gradients: A review

Urbanization can create uncertainty for biodiversity. Understanding the spatial distribution of trees along urban-rural gradients is crucial for sustainable land management and the conservation of biological diversity. However, limited information is available on the factors influencing the distribution of trees outside forests along urban-rural transition gradients. This paper uses the Preferred Reporting items for Systematic Reviews and Meta-Analyses (PRISMA) to review how distance from urban centers, land use types, socio-economic disparities, and community attitudes and perceptions impact the spatial distribution of trees outside forests along urban-rural gradients. The review indicates that the species composition, diversity, density, and spatial arrangement of trees outside forests vary along the urban-rural gradient. The most commonly cited factors influencing this distribution are respondents' attitudes and perceptions of trees, socio-economic factors, and land use variations. Distance from the urban center was the least cited factor. However, there is significant variation in how different factors impact this distribution from study to study. Therefore, further research is needed to better understand the factors driving changes in the diversity of trees outside forests in various urban-rural contexts and to determine whether variations exist across different settings.

Taking charge of change: building community ownership for educational change with Indigenous communities

Education is often posed as the harbinger of progress in discourses related to the development of marginalised Indigenous communities. However, since they entered the mainstream schools in the 1960s, the four Indigenous communities of Gudalur, India have experienced various forms of injustice in seeking formal education. This article draws from the work of the Vishwa Bharati Vidyodaya Trust, a community-driven organisation that has been working on matters related to the education of these four communities since 1996, and two research initiatives that captures the community’s voices on their experiences and aspirations related to education, to put forth recommendations for practice that is geared towards greater equality and justice for the children of Indigenous communities. Rooted in the belief that the active participation of the community is crucial to devising solutions that truly address in a sustainable manner the historical injustices faced by them, the article outlines various interventions at different sites of learning that builds community ownership and nurtures a meaningful continuum between the home and school environment of the children.

Unlocking the potential of second cheese whey: a comprehensive review on valorisation strategies

AbstractThe second cheese whey (SCW) is the liquid fraction that remains after the production of whey-cheeses. SCW appears as a white to yellow/green opalescent liquid with suspended solids and contains up to 6% lactose and variable amounts of proteins, fats, and mineral salts. Due to its organic load, SCW is characterized by levels of Biochemical Oxygen Demand and Chemical Oxygen Demand that are significantly higher than urban wastewater. Therefore, it poses an environmental challenge and represents a significant cost and a problem for cheese production facilities when it comes to disposal. On the flip side, SCW contains valuable nutrients that make it a cost-effective substrate for bio-based productions including lactose extraction, and the production of lactic acid, bioethanol, eco-friendly bioplastics, biofuels, beverages, bioactive peptides, and microbial starters. A search in Scopus database indicates that despite the numerous potential applications, interest in SCW exploitation is surprisingly limited and, accordingly, sustainable management of SCW disposal remains an unresolved issue. In this review, which marks the first exclusive focus on SCW, with the aim of contributing to increase the interest of both the scientific community and the stakeholders in the exploitation of this by-product, the processes aimed at SCW valorisation will be described, with particular attention to its use in the production of beverages, food and feed, single cell proteins and as a source of biodegradable bioplastics, organic acids and renewable energy. Moreover, to provide valuable insights into its applications and innovations, an overview on patents regarding the exploitation of SCW will be presented. Graphical Abstract