Search Results (253)

With the advance of digital transformation, the assessment of the environmental impact of digital tools and technologies grows more relevant. Considering the inflated expectations of environmental responsibility in higher education, this study analyses how websites of Polish universities conform to sustainable web design criteria. The sustainability audit employed a methodology encompassing carbon emissions measurement, technical website analysis, and SEO evaluation. The author analysed 63 websites of public universities in Poland using seven independent audit tools, including an original AI Custom GPT agent preconfigured in the ChatGPT ecosystem. The results revealed a substantial differentiation in CO₂ emissions and website optimisation, with an average EcoImpact Score of 66.41/100. Nearly every fourth website exhibited a significant carbon footprint and excessive component sizes, which indicates poor asset optimisation and energy-intensive design techniques. The measurements exposed considerable variability in emission intensities and resource intensity among the university websites, suggesting the need for standardised digital sustainability practices. Regulations on the carbon footprint of public institutions’ websites and mobile applications could become vital strategic components for digital climate neutrality. Promoting green hosting, “Green SEO” practices, and sustainability audits could help mitigate the environmental impact of digital technologies and advance sustainable design standards for the public sector. The proposed auditing methodology can effectively support the institutional transition towards sustainable management of digital infrastructure by integrating technical, sustainability, and organisational aspects. Full article

Based on a comprehensive review of the current research status of ecological compensation both domestically and internationally, combined with field survey data, this study delves into the issue of multi-stakeholder participation in the ecological compensation mechanisms of the Xin’an River Basin. This research reveals that the joint participation of multiple stakeholders is crucial to achieving the goals of ecological compensation in river basins. The government plays a significant role in macro-guidance, financial support, policy guarantees, supervision, and management. It promotes the comprehensive implementation of ecological environmental protection by formulating relevant laws and regulations, guiding the public to participate in ecological conservation, and supervising and punishing pollution behaviors. The public, serving as the main force, forms strong awareness and behavioral habits of ecological protection through active participation in environmental protection, monitoring, and feedback. As participants, enterprises contribute to industrial transformation and green development by improving resource utilization efficiency, reducing pollution emissions, promoting green industries, and participating in ecological restoration projects. Scientific research institutions, as technology enablers, have effectively enhanced governance efficiency through technological research and innovation, ecosystem value accounting to provide decision-making support, and public education. Social organizations, as facilitators, have injected vitality and innovation into watershed governance by extensively mobilizing social forces and building multi-party collaboration platforms. Communities, as supporters, have transformed ecological value into economic benefits by developing characteristic industries such as eco-agriculture and eco-tourism. Based on the above findings, further recommendations are proposed to mobilize the enthusiasm of upstream communities and encourage their participation in ecological compensation, promote the market-oriented operation of ecological compensation mechanisms, strengthen cross-regional cooperation to establish joint mechanisms, enhance supervision and evaluation, and establish a sound benefit-sharing mechanism. These recommendations provide theoretical support and practical references for ecological compensation worldwide. Full article

Zwitterionic hydrogels have emerged as eco-friendly anti-fouling materials owing to their superior hydration-mediated resistance to biofouling. Nevertheless, their practical utility remains constrained by intrinsically poor mechanical robustness. Herein, this study proposes a novel strategy to develop novel tough zwitterionic hydrogels by freezing the gels’ polymer network. As a proof of concept, a zwitterionic hydrogel was synthesized via copolymerization of hydrophobic monomer phenyl methacrylate (PMA) and hydrophilic cationic monomer N-(3-dimethylaminopropyl) methacrylamide (DMAPMA), followed by post-oxidation to yield a zwitterionic structure. At service temperature, the rigid and hydrophobic PMA segments remain frozen, while the hydrophilic zwitterionic units maintain substantial water content by osmotic pressure. Synergistically, the zwitterionic hydrogel achieves robust toughness and adhesiveness, with high rigidity (66 MPa), strength (4.78 MPa), and toughness (2.53 MJ/m³). Moreover, the hydrogel exhibits a distinct temperature-dependent behavior by manifesting softer and more stretchable behavior after heating, since the thawing of the gel network at high temperatures increases segmental mobility. Therefore, it achieved satisfactory adhesiveness to substrates (80 kPa). Additionally, the hydrogel demonstrated remarkable anti-fouling performance, effectively suppressing biofilm formation and larval attachment. In summary, this work opens up promising prospects for the development of zwitterionic hydrogels with high application potential. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

This article explores the integration of artificial intelligence (AI) in digital marketing through social and mobile networks and its role in fostering sustainable consumer behavior. AI enhances personalization, sentiment analysis, and campaign automation, reshaping marketing dynamics and enabling brands to engage interactively with users. A quantitative study conducted on 501 social media users evaluates how perceived benefits, risks, trust, transparency, satisfaction, and social norms influence the acceptance of AI-driven marketing tools. Using structural equation modeling (SEM), the findings show that social norms and perceived transparency significantly enhance trust in AI, while perceived benefits and satisfaction drive user acceptance; conversely, perceived risks and negative emotions undermine trust. From a sustainability perspective, AI supports the efficient targeting and personalization of eco-conscious content, aligning marketing with environmentally responsible practices. This study contributes to ethical AI and sustainable digital strategies by offering empirical evidence and practical insights for responsible AI integration in marketing. Full article

Per- and polyfluoroalkyl substances (PFASs) are synthetic chemicals widely used in industrial applications and have become persistent environmental contaminants due to their chemical stability. Water-soluble PFASs with fewer than ten carbon atoms, such as perfluorooctanoic acid (PFOA), are particularly concerning because of their high solubility in water, environmental mobility, and resistance to degradation. In this work, we present an eco-friendly Fe₃O₄ magnetic nanoparticle (MNP)-based platform for the detection and removal of PFOA from water. The synthesized iron oxide MNPs exhibit rapid and strong magnetic responsiveness, enabling efficient magnetic separation for both PFOA detection and removal. To optimize surface affinity for PFOA, we functionalized the MNPs with distinctive ligands, including polyethylene glycol (PEG), β-cyclodextrin (βCD), and dopamine (DA). Among these, PEG and DA showed notable binding affinity toward PFOA, as confirmed by infrared spectroscopy and colorimetric assays. After incubation with the functionalized MNPs followed by magnetic retrieval, we achieved over 90% PFOA removal efficiencies, demonstrating the potential for future research in PFAS remediation technologies. Importantly, the system was validated using deionized, tap, and lake water, all of which yielded comparable and promising results. This study provides a promising, eco-friendly, and recyclable nanomaterial platform for investigating the crucial role of surface chemistry in nanoparticle–PFAS interactions through ligand-mediated magnetic separation. Full article

Background: Sustainability is a critical concern in transportation, notably in light of governmental initiatives such as cap-and-trade systems and eco-label regulations aimed at reducing emissions. In this context, collaborative approaches among carriers, which involve the exchange of shipment requests, are increasingly recognized as effective strategies to enhance efficiency and reduce environmental impact. Methods: This research proposes a novel collaborative planning model for multimodal transport designed to minimize the total costs associated with freight movements, including both transportation and $C{O}_2$ emissions costs. Transshipments of freight between vehicles are modeled in the proposed formulation, promoting carrier coalitions. This study incorporated eco-labels, representing different emission ranges, to capture shipper sustainability preferences and integrated authority-imposed low-emission zones as constraints. A bi-objective approach was adopted, combining transportation and emission costs through a weighted sum method. Results: A case study on the Naples Bypass network (Italy) is presented, highlighting the model’s applicability in a real-world setting and demonstrating the effectiveness of collaborative transport planning. In addition, the model quantified the benefits of collaboration under low-emission zone (LEZ) constraints, showing notable reductions in both total costs and emissions. Conclusions: Overall, the proposed approach offers a valuable decision support tool for both carriers and policymakers, enabling sustainable freight transportation planning. Full article

Sustainable traffic management relies on accurate traffic flow prediction to reduce congestion, fuel consumption, and emissions and minimise the external environmental impacts of traffic operations. This study contributes to this objective by developing and evaluating advanced machine learning models that leverage multisource data to predict traffic patterns more effectively, allowing for the deployment of proactive measures to prevent or reduce traffic congestion and idling times, leading to enhanced eco-friendly mobility. Specifically, this paper evaluates the impact of multisource sensor inputs and spatial detector interactions on machine learning-based traffic flow prediction. Using a dataset of 839,377 observations from 14 detector stations along Melbourne’s Eastern Freeway, Bidirectional Long Short-Term Memory (BiLSTM) models were developed to assess predictive accuracy under different input configurations. The results demonstrated that incorporating speed and occupancy inputs alongside traffic flow improves prediction accuracy by up to 16% across all detector stations. This study also investigated the role of spatial flow input interactions from upstream and downstream detectors in enhancing prediction performance. The findings confirm that including neighbouring detectors improves prediction accuracy, increasing performance from 96% to 98% for eastbound and westbound directions. These findings highlight the benefits of optimised sensor deployment, data integration, and advanced machine-learning techniques for smart and eco-friendly traffic systems. Additionally, this study provides a foundation for data-driven, adaptive traffic management strategies that contribute to sustainable road network planning, reducing vehicle idling, fuel consumption, and emissions while enhancing urban mobility and supporting sustainability goals. Furthermore, the proposed framework aligns with key United Nations Sustainable Development Goals (SDGs), particularly those promoting sustainable cities, resilient infrastructure, and climate-responsive planning. Full article

The increasing environmental concerns and regulatory restrictions on toxic conventional solvents have driven the search for sustainable alternatives. Dimethyl isosorbide (DMI), a bio-renewable solvent, has shown potential as a replacement for short-chain glycol ethers, although its use as solvent in liquid chromatography (LC) is underexplored. This study presents a physicochemical characterization of DMI with a particular focus on its application as an innovative solvent in LC analyses. The partition coefficient (log P = −0.44) was determined using the OECD 107 method, and viscosity measurements for DMI and its mixtures with water and ethanol were conducted at 25 °C, 40 °C, and 60 °C. Viscosity ranged from 1.28 mPa·s at 60 °C to 2.62 mPa·s at 40 °C. The Central Composite Face 2³ experimental design for studying the chromatographic behavior of DMI confirmed that 50% (v/v) DMI can be effectively utilized in the mobile phases, at a column temperature of 40 °C, with backpressures ranging from 160 to 300 bar and a UV cut-off at 240 nm. Its effectiveness as an eluent in LC was demonstrated for the quantification of methylparaben and propylparaben in pharmaceutical formulations. This study highlights DMI’s promise as a sustainable bio-renewable alternative to conventional organic solvents used as eluents in LC, supporting eco-friendly practices in pharmaceutical analysis. Full article

Integrating Electric Vehicle (EV) charging stations into buildings is becoming increasingly important due to the rapid growth of private EV ownership and prolonged parking durations in residential areas. This paper proposes robust, building-integrated charging solutions that combine mobile energy storage systems (ESSs), station linkage data, and traffic volume data. The proposed system promotes eco-friendly EV usage, flexible energy management, and carbon neutrality through a polyfunctional Vehicle-to-Grid (V2G) architecture that integrates decentralized energy networks. Two core strategies are implemented: (1) configuring Virtual Power Plant (VPP)-based charging packages tailored to station types, and (2) utilizing EV batteries as distributed ESS units. K-means clustering based on spatial proximity and energy demand is followed by heuristic algorithms to improve the efficiency of mobile ESS operation. A three-layer framework is used to assess improvements in energy demand distribution, with demand-oriented VPPs deployed in high-demand zones to maximize ESS utilization. This approach enhances station stability, increases the load factor to 132.7%, and reduces emissions by 271.5 kgCO₂. Economically, the system yields an annual benefit of USD 47,860, a Benefit–Cost Ratio (BCR) of 6.67, and a Levelized Cost of Energy (LCOE) of USD 37.78 per MWh. These results demonstrate the system’s economic viability and resilience, contributing to the development of a flexible and sustainable energy infrastructure for cities. Full article

This study explores the potential of biopolymers as sustainable alternatives to synthetic polymers in enhanced oil recovery (EOR), aiming to reduce reliance on partially hydrolyzed polyacrylamides (HPAM). Mucilage extracted from Opuntia ficus-indica cladodes was investigated individually and in combination with HPAM in an 80/20 blend. The objective was to evaluate the physicochemical and rheological properties of these formulations, and their efficiency in improving oil recovery under realistic reservoir conditions. The materials were characterized using thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier-transform infrared spectroscopy (FTIR). Rheological tests showed that both Opuntia mucilage and the HPAM–mucilage blend displayed favorable viscoelastic behavior in saline environments (2% NaCl) at high concentrations (10,000 ppm). The mucilage also exhibited thermal stability above 200 °C, making it suitable for harsh reservoir conditions. Core flooding experiments conducted at 120 °C using core plugs from Algerian reservoirs revealed enhanced oil recovery performance. The recovery factors were 63.3% for HPAM, 84.35% for Opuntia mucilage, and 94.28% for the HPAM–mucilage blend. These results highlight not only the synergistic effect of the blend but also the standalone efficiency of the natural biopolymer in improving oil mobility and pore permeability. This study confirms the viability of using locally sourced biopolymers in EOR strategies. Opuntia ficus-indica mucilage offers a cost-effective, eco-friendly, and thermally stable alternative to conventional polymers for enhanced oil recovery, particularly in saline and high-temperature reservoirs such as Hassi Messaoud in Algeria. Full article

The total cost of ownership (TCO) of electric vehicles (EVs) is significantly influenced by several economic factors which play a critical role in shaping their cost competitiveness, including tax policies. The primary objective of this analysis is to evaluate whether (EVs) can be competitive with internal combustion engine vehicles (ICEVs) for everyday use over a multi-year period. Therefore, the TCO of passenger EVs was compared with that of ICEVs across three categories: affordable, mid-range, and luxury. This allowed us to show how tax laws affect EVs’ TCO and adoption rates. The analysis of the Jordanian regulatory structure showed that specific incentives, like lower sale taxes and customs duty applicable to EVs, successfully offset the higher initial costs of EVs, making them cost-competitive, especially in the affordable and mid-range categories. These results not only demonstrate the effectiveness of such policies in Jordan but also support national sustainability objectives by encouraging eco-friendly modes of transportation. The results provide a valuable framework for other developing countries, particularly in the Middle East, to accelerate EV adoption and transition toward cleaner mobility solutions. Full article

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article

This research focuses on current photojournalism practices in the media representation of the climate crisis, exploring how images published by Spain’s leading digital newspapers contribute to shaping public perception of the phenomenon. Through a mixed-methods approach, this study examines eco-visual reporting in 2023—a year characterized by unprecedented global temperatures—alongside an examination of the initial month of coverage of the 2024 DANA floods. The main objective of this study is to evaluate whether the visual depiction of climate change in mainstream media aligns with or deviates from the established visual patterns associated with stereotyped iconography and alarmist narratives. This research provides a taxonomy of the predominant thematic elements and their frequency, addressing key issues such as the persistence of worn-out visual tropes, the reliance on stock images, and the episodic nature of its news treatment. The inclusion of the most catastrophic climate disaster of the 21st century in Spain allows for an exploration of how the media pressure inherent to crisis situations intensifies the risk of errors in image attribution and contextualization. Finally, we offer practical recommendations to guide visual coverage toward comprehensive, accurate, and human-centered approaches, aiming to foster public trust and maximize the potential of photojournalism as a key tool in collective mobilization against the climate emergency. Full article

The rapid advancement of sustainable materials has driven the need for high-performance polymer nanocomposites with superior mechanical, thermal, and structural properties. In this study, a novel RPET/PA-11/Joncryl^® nanocomposite reinforced with halloysite nanotubes (HNTs) is developed for the first time, marking a significant breakthrough in polymer engineering. Six different proportions of HNT (0, 1, 2, 3, 4, and 5 phr) are introduced to the blend of rPET/PA-11/Joncryl^® through a twin-screw extruder and injection moulding machine. The incorporation of HNTs into the RPET/PA-11 matrix, coupled with Joncryl^® as a compatibilizer, results in a synergistic enhancement of material properties through improved interfacial adhesion, load transfer efficiency, and nanoscale reinforcement. Comprehensive characterization reveals that the optimal formulation with 2 phr HNT (NCS-H2) achieves remarkable improvements in tensile strength (56.14 MPa), flexural strength (68.34 MPa), and Young’s modulus (895 MPa), far exceeding conventional polymer blends. Impact resistance reaches 243.46 J/m, demonstrating exceptional energy absorption and fracture toughness. Thermal analysis confirms enhanced stability, with an onset degradation temperature of 370 °C, attributing the improvement to effective matrix–filler interactions and restricted chain mobility. Morphological analysis through FESEM validates uniform HNT dispersion at optimal loading, eliminating agglomeration-induced stress concentrators and reinforcing the polymer network. The pioneering integration of HNT into RPET/PA-11/Joncryl^® nanocomposites not only bridges a critical gap in sustainable polymers but also establishes a new benchmark for polymer nanocomposites. This work presents an eco-friendly solution for engineering applications, offering mechanical robustness, thermal stability, and recyclability. The results form the basis for next-generation high-performance materials for industrial use in automotive, aerospace, and high-strength structural applications. Full article