Search Results (96)

The growing environmental crisis, particularly water pollution from detergents, necessitates a shift from reactive compliance to proactive eco-innovation, as current methods often fail to systematically resolve trade-offs between performance, safety, and ecology. This study develops and illustrates the application of the Evolutionary-Driven Design Framework (EDDF), an integrated methodology that combines PESTEL analysis, historical evolutionary pattern analysis, Quality Function Deployment (QFD) with a novel contradiction index, Theory of Inventive Problem Solving (TRIZ), and environmental assessment. The framework was applied to redesign a conventional laundry detergent with the objectives of zero phosphates, superior biodegradability (>85%), maintained efficacy, and controlled cost. The quantitative contradiction index matrix prioritized critical unsustainable parameters (e.g., EDTA, Cocamide DEA) for substitution over mere optimization. Through an iterative feedback loop, the process evolved from a biobased concentrate to an “enzymatic power tablet” (Concept B). This waterless, solid formulation uses sodium citrate as a biodegradable builder and an encapsulated multi-enzyme system, achieving an estimated >90% biodegradability and zero phosphates while meeting technical and economic targets. The EDDF provides a structured, anticipatory roadmap that transforms regulatory and market pressures into drivers of innovation, offering companies a promising method for designing sustainable products by proactively resolving contradictions and avoiding historical mistakes. Full article

We investigate the coevolutionary dynamics in a predator–prey system with Holling-III functional response. By using the theory of adaptive dynamics, we first classify coevolutionary singular coalitions and then prove the existence of cyclic coevolution. Coupling this cyclic trait evolution with oscillatory population dynamics generates multi-timescale oscillations in population size. These oscillations arise from the interplay of fast ecological and slow evolutionary processes, producing distinct patterns such as frequency-modulated and bursting oscillations. Our results demonstrate that complex oscillations in population size emerge intrinsically from eco-evolutionary feedback loops. Full article

The Educational Competition Optimizer (ECO) shows promise on simple tasks but struggles with high-dimensional and complex landscapes due to rigid stage division and limited search operators. This paper proposes a Hybrid Strategy Enhanced ECO (HSECO) featuring: (i) a self-adaptive parameter evolution mechanism for individual-level flexibility, (ii) a multi-operator adaptive selection scheme switching between learning and differential evolution strategies based on real-time feedback, and (iii) an archive-assisted diversity preservation module to mitigate premature convergence. HSECO is validated on CEC2017, CEC2020 and CEC2022, and a continuous engineering benchmark. Statistical tests confirm its superiority over nine State-of-the-Art and parameter-free algorithms in accuracy, convergence speed, and robustness. Ablation and diversity analyses verify its balanced exploration–exploitation dynamics. Finally, HSECO is applied to a three-dimensional UAV path-planning problem, where path length, altitude variation, and turning smoothness are integrated into a single fitness function using a weighted-sum formulation. Therefore, from a metaheuristic optimization perspective, the UAV case is treated as a single-objective constrained optimization problem rather than a Pareto-based multi-objective problem. Experimental results show that HSECO obtains shorter, safer, and smoother trajectories with lower overall weighted fitness. Full article

Artificial Intelligence systems increasingly shape environmental decision making, infrastructure planning, and resource use across public and urban domains. However, prevailing AI trust and governance mechanisms, including labels, certifications, and assurance schemes, remain primarily focused on ethical and legal accountability, with limited operational attention to environmental sustainability. This paper reconceptualises AI trust mechanisms as socio-technical governance infrastructures that can support both ethical assurance and environmental accountability. Drawing on a comparative qualitative analysis of nine AI trust initiatives, the study develops a three-dimensional analytical framework embedding Environmental Performance Indicators across three governance dimensions: trust-building effectiveness, governance readiness, and sustainable adoption. Applying a systems governance lens, the framework examines how governance instruments structure information flows, institutional practices, and lifecycle feedback relevant to environmental performance. It is analytically illustrated through two urban mobility cases, Helsinki’s Whim application and Barcelona’s smart mobility system, to examine how governance conditions enable or constrain the integration of Environmental Performance Indicators in practice. Findings show that current trust mechanisms lack measurable and publicly visible environmental criteria, indicating a gap between AI assurance and environmental governance. The study contributes a systems-oriented framework for evaluating AI trust mechanisms as governance instruments capable of supporting environmental accountability. While exploratory and based on secondary data, the results indicate that future AI trust mechanisms must incorporate measurable sustainability indicators to support eco-efficient and accountable digital transformation. Full article

Edible insects are recognised as a sustainable, high-protein food source, yet consumption in Western diets remains limited due to cultural barriers and concerns about taste, appearance, and safety. This study explored the factors affecting the acceptance of familiar products where insects have been added as ingredients, and how purchase intent is influenced by label information. During sensory evaluation, 59 participants tested pasta-only and pasta-with-sauce samples that were presented with and without insects (controls). Results showed no significant differences in preference between insect and control samples (pasta only: p = 0.150; pasta with sauce: p = 0.193). Open-ended feedback highlighted flavour, texture, and familiarity as key drivers. Label design strongly shaped purchase intent, with participants preferring labels that combined clear allergen and ingredient information with credible nutrition and eco-certification logos. Benefit-focused price framing (protein and sustainability) significantly increased willingness to pay (p < 0.001), while prior insect consumption, age and gender had no effect. Overall, the findings show that adding insects into a well-known ready-meal format, supported by transparent labelling and benefit-based communication, has the potential to improve acceptance. This approach highlights a practical way to bring insect proteins into mainstream food systems while contributing to nutrition and sustainability goals. Full article

Agrivoltaics (AV) has emerged as an integrated land-use innovation capable of simultaneously addressing food, energy, and water challenges, yet its systemic implications for farming system sustainability remain insufficiently synthesized. This review adopts a farming system dynamics perspective to examine how AV systems reorganize biophysical, ecological, and socio-economic interactions across agroecosystems. Drawing upon agroecological principles, pathways of sustainable intensification and ecological intensification, and resource-loop strategies in circular economy, we identify the key elements and cause-and-effect relationships that shape AV system performance. Evidence indicates that the co-location of photovoltaics (PV) structures and crop cultivation generates new system properties, altered light distribution, moderated microclimates, redistributed soil moisture, and diversified production functions that influence productivity, resource-use efficiency, ecological services, and farm resilience. Using causal loop analysis, we conceptualize four central feedback dynamics: (i) PV–crop trade-offs and spatial-sharing relationships; (ii) microclimate modifications and crop physiological responses; (iii) ecological performance and landscape-level interactions; and (iv) circularity loops connecting resource conservation, renewable-energy substitution, soil processes, and material flows. This feedback collectively determines eco-efficiency outcomes, including enhanced land-equivalent productivity, improved water-use efficiency, strengthened regulating services, and reductions in external energy dependence. At the farming-system scale, AV diversifies income streams and stabilizes yields under climatic variability, whereas at the landscape scale, it fosters multifunctionality by supporting regenerative resource flows and ecological resilience. Building on these insights, we propose an integrated framework that links agroecological elements with dynamic feedback structures to guide context-specific AV design, management, and governance. This system-oriented synthesis provides a foundation for future research and policy efforts aimed at optimizing AV as a circular, resilient, and sustainable farming system innovation. Full article

This study develops an integrated decision-support framework to advance green supply chain management (GSCM) by systematically linking Environmental, Social, and Governance (ESG) practices, environmental product innovation, corporate performance, and strategic alternatives. Employing the Analytic Network Process (ANP), the proposed model captures complex interdependencies and feedback relationships across life-cycle value chain stages, enabling a holistic evaluation of sustainability-oriented strategies. A Delphi panel comprising 15 experts from academia, industry, and government is used to validate the evaluation criteria and network structure. The empirical results indicate that eco-friendly design, energy and resource efficiency, and carbon–climate management are the most influential drivers shaping green supply chain performance. Moreover, operational and sustainability performance are found to exert greater strategic importance than short-term financial performance, highlighting GSCM as a long-term capability-building approach rather than a cost-centered initiative. To enhance analytical adaptability, this study proposes a conceptual extension integrating neural feature extraction (NFE) signals with ANP-based expert weights. The NFE module is not empirically trained or validated; rather, it illustrates a theoretically consistent mechanism for incorporating data-driven feature signals into structured multi-criteria decision frameworks. Empirical validation of the NFE component is proposed as a future research direction. Full article

Decoupling between CO₂ emissions and economic growth is critical to reversing climate change. The OECD plays a crucial role in this regard, given its considerable share of global CO₂ emissions and GDP. This study examines the decoupling performance and the roles of renewable energy transition, as well as specific eco-innovations on climate change mitigation and environmental technology development across the OECD economies. The preliminary tests on a large panel of OECD countries identify cross-sectional dependence, structural breaks and heterogeneity. For robustness, the study proposes Fourier-CS-ARDL, Fourier-AMG, and Fourier–Dumitrescu–Hurlin methods as generalizations of their linear counterparts. After identifying cointegration and its singularity with Fourier-bootstrapping bounds and Fourier–Johansen tests, the modeling stage suggested a positive, but significantly inelastic long- and short-run elasticity of emissions to economic growth. Most of these effects are reversed by renewable energy transition in the long run and partially reversed in the short run. These CO₂ mitigation effects are also evident across different eco-innovations with varying temporal impacts. Novel Fourier causality tests identify feedback loops between CO₂ and CO₂-mitigating factors, as well as unidirectional causality from growth to all mitigating factors, confirming the indirect effect of growth on CO₂ mitigation. Overall, these results clearly suggest “relative” decoupling in OECD accompanied by CO₂e mitigation effects from eco-innovations and energy transition, and highlight the potential for green growth following the successful adaptation of energy transition and eco-innovations. Policymakers in OECD are encouraged to leverage the identified feedback mechanisms and establish international technology transfer policies to homogenously curb CO₂ emissions. Full article

Enhancing the flame retardancy of polymeric materials by adding only eco-friendly ammonium polyphosphate (APP) while simultaneously maintaining high-temperature resistance has become a challenge. Talcum has been introduced as a cooperative agent into the silicone rubber/APP system to investigate the effect of talcum on flame retardancy, thermal stability, and high-temperature resistance. The machining process induces the orientation of talcum in the system. The ceramifiable silicone rubber blends containing oriented talcum (e.g., sample SA₆T₄) exhibited superb flame retardancy, including an LOI of 29.4%, a UL-94 rating of V-0, and a peak heat release rate (PHRR) of 250.2 kW·m⁻². More importantly, the blends present excellent thermal stability and high-temperature resistance, characterized by outstanding self-supporting properties and dimensional stability. Based on the structural analysis of the blends and their residues, the made of action for the improved flame retardancy may be attributed to the formation of a compact barrier layer. This layer is formed by oriented talcum platelets combined with phosphoric acid, from the thermal decomposition of APP, promoting crosslinking, thereby achieving a good inhibition barrier to inhibit heat feedback from the condensation zone. The excellent thermal stability and high-temperature resistance of the ceramifiable silicone rubber blends may be ascribed to a cooperative effect between APP and talcum at high temperatures, which facilitates the formation of ceramic structures. The novel ceramifiable silicone rubber composite has potential applications as flame-retardant sealing components for rail transit equipment and encapsulation materials for new energy battery modules. Full article

Food systems operate as socio-ecological systems (SES) in which governance, markets, and biophysical constraints interact through feedback. However, how resilience capacities accumulate across sequential shocks, particularly in hyper-arid, import-dependent rentier states, remains under-traced. We analyze Qatar’s food-system SES across three distinct stress tests: the 2017–2021 blockade, the COVID-19 pandemic (multi-node logistics and labor shock), and the post-2022 Russia–Ukraine war (global price and agricultural input-cost shock). Using a qualitative longitudinal case-study design, we combine documentary review with process tracing and a two-layer coding scheme that maps interventions to SES components (actors, governance system, resource systems/units, interactions, outcomes/feedback) and to predominant resilience capacities (absorptive, adaptive, transformative). The results indicate path-dependent capability building: the blockade activated rapid buffering and rerouting alongside early adaptive investments; COVID-19 accelerated adaptive reconfiguration via digitized logistics, e-commerce scaling, and targeted controlled-environment agriculture; and the Russia–Ukraine shock validated an institutionalized portfolio (fiscal buffering, reserves, procurement diversification, and upstream linkages). Across episodes, supply continuity was maintained, but resilience gains also generated water–energy–food tradeoffs, shifting pressures toward energy-intensive cooling/desalination and upstream water demands linked to domestic buffers. We conclude that durable resilience in eco-constrained, import-dependent systems requires explicit governance of these tradeoffs through measurable performance criteria, rather than crisis-driven expansion alone. Full article

Smart thermostats are a key technology for reducing residential energy consumption in smart cities, but their real-world effectiveness depends on the interaction between automation, occupant behavior, and the design of behavioral interventions. This study presents a physics-informed assessment of thermostat strategies across Luxembourg’s single-family home stock, using an aggregate thermal model calibrated to eight years of hourly national heating demand and meteorological data. We simulate five categories of behavioral scenarios: dynamic thermostat adjustments, heat-wasting window-opening behavior, flexible comfort models, occupancy-based automation, and a portfolio of four probabilistic nudges (social comparison, real-time feedback, pre-commitment, and gamification). Results show that occupancy-based automation delivers the largest energy savings at 12.9%, by aligning heating with presence. In contrast, behavioral savings are highly fragile, as a stochastic window-opening behavior significantly erodes the 9.8% savings from eco-nudges, reducing the net gain to 7.6%. Among nudges, only social comparison yields significant savings, with a mean reduction of 7.6% (90% confidence interval: 5.3% to 9.8%), by durably lowering the thermal baseline. Real-time feedback and pre-commitment fail, achieving less than 0.5% savings, because they are misaligned with high-consumption periods. Thermal comfort, the psychological state of satisfaction with the thermal environment drives a large share of residential energy use. These findings demonstrate that effective smart thermostat design must prioritize robust, presence-responsive automation and interventions that reset default comfort norms, offering scalable, policy-ready pathways for residential energy reduction in urban energy systems. Full article

The intricate connections between plants and the microbial populations that surround them are crucial for plant development and resilience, but little is known about the evolutionary processes influencing these partnerships. Less is known about how pathogenic and beneficial microbes coevolve with their plant hosts over ecological and evolutionary timeframes, despite the fact that several studies identify rhizosphere and endophytic microbes that support nutrient acquisition, disease resistance, and stress tolerance. Using molecular, ecological, and evolutionary investigations from soil, rhizosphere, and endosphere habitats, this review summarizes current findings on microbial coevolution in plant–microbe systems. We look at the endosymbiotic processes that underlie the development of organelles, the mechanisms of mutualism and antagonism, and the eco-evolutionary feedbacks that affect plant health and agricultural output. The inadequate comprehension of intraspecific microbial diversity, the application of laboratory coevolution experiments to field settings, and the long-term effects of climate change on the evolutionary dynamics of plants and microbiomes are some of the major knowledge gaps. When pathogenic and beneficial microbes apply selective pressures to one another and their common host, coevolution takes place. This results in mutual genetic and physiological adaptations, such as modifications to host immunity, microbial virulence, or competitive tactics, which influence the way the two types interact over time. We conclude that understanding plants as holobiont-integrated units of hosts and their microbiomes offers fresh chances to develop microbiome-based approaches to sustainable agriculture, such as coevolutionary breeding programs, precision biofertilizers, and resilient cropping systems. Full article

We study the global dynamics and bifurcation structure of an evolutionary Beverton–Holt model with Allee effects, a framework that couples ecological constraints with adaptive trait evolution. The model accounts for density dependence, mate limitation, and predator saturation, while traits evolve according to selection gradients that influence reproduction and competition. From an ecological perspective, we show that weak Allee effects create bistability between extinction and survival, while strong Allee effects generate a critical threshold below which populations collapse and above which they persist at carrying capacity. Evolutionary feedback further reshapes these outcomes by shifting thresholds, modifying stability regions, and producing multiple long-term attractors. Biologically, this reveals how demographic pressures such as scarce mates or high predation interact with trait evolution to determine persistence or extinction, and how adaptive responses may rescue populations facing critical density barriers. Our rigorous analysis and simulations demonstrate that eco–evolutionary processes not only alter classical Beverton–Holt outcomes but also provide insight into mechanisms underlying species persistence, extinction risk, and invasion success under Allee constraints. Full article

This review investigates and analyzes the state of the art on scientific evidence related to educational interventions to improve air quality indoors and outdoors through a mapping review. The review followed proposed guidelines for mapping reviews in environmental sciences and the steps described in the Template for a Mapping Study Protocol. The search was conducted in PubMed, Web of Science, Embase, Cinahl, and Google Scholar with no language restrictions, and was completed in January 2025. Three filters were applied: search, selection with inclusion and exclusion criteria (PECOS strategy), and data extraction. Two independent reviewers assessed article eligibility, and disagreements were resolved by a third researcher. Twenty-four studies that met the eligibility criteria were included. Five research questions were answered. Studies published between 1977 and 2024 were included, totaling 7289 participants aged 12 to 85. The geographic distribution was concentrated in China (five studies) and the United States (four studies), followed by South Korea, India, Australia, and other countries, with fewer publications. The methodological predominance was experimental studies; observational studies were also analyzed, although less frequently. The period with the greatest increase in the number of publications was between 2020 and 2024. The educational methods most commonly used in the studies were lectures and the delivery of information leaflets. Particulate matter with diameters of 2.5 μm and 10 μm (PM_2.5 and PM₁₀) were the most widely investigated pollutants in the studies. From our analyses, it was observed that the educational interventions to improve air quality, adopted in the selected studies, resulted in the acquisition of knowledge about the environmental effects and the importance of individual actions. The changes in behavior included the adoption of more sustainable practices and an improvement in air quality in the environment, with a significant reduction in pollutant emissions. We conclude that interventions through environmental education demonstrate great potential to improve air quality. Based on the mapped evidence, governments and global policymakers can use this information to develop new strategies or improve existing ones to reduce air pollution in affected environments and regions. Full article

N-Acetylneuraminic acid (Neu5Ac), the predominant form of sialic acids (Sias), is extensively utilized in the food, pharmaceutical, and cosmetic industries. Microbial fermentation serves as a critical production method for its economical, eco-friendly, and scalable production. Escherichia coli and Bacillus subtilis, as primary industrial workhorses for Neu5Ac production, have been extensively investigated owing to their well-characterized genetic frameworks and mature molecular toolkits. Nevertheless, the intricate regulatory networks inherent to microbial systems present formidable obstacles to the high-efficiency biosynthesis of Neu5Ac. This review delineates the genetic and molecular mechanisms underlying Neu5Ac biosynthesis in both E. coli and B. subtilis. Furthermore, the rational and irrational strategies for constructing Neu5Ac microbial cell factories are systematically summarized, including the application of rational metabolic engineering to relieve feedback regulation, reconfigure metabolic networks, implement dynamic regulation, and optimize carbon sources; as well as the use of irrational strategies including directed evolution of key enzymes and high-throughput screening based on biosensors. Finally, this review addresses current challenges in Neu5Ac bioproduction and proposes integrative solutions combining machine learning with systems metabolic engineering to advance the construction of high-titer Neu5Ac microbial cell factory and the refinement of advanced fermentation technologies. Full article