Search Results (418)

Background: this research presents an integrated approach to enhancing the sustainability of plastic bag supply chains in Indonesia by addressing critical issues related to ineffective post-consumer waste management and low recycling rates. The objective of this study is to develop a combined framework of material flow analysis (MFA) and sustainable supply chain planning to improve demand forecasting and inflow management across the plastic bag lifecycle. Method: the research adopts a quantitative method using the XGBoost algorithm for forecasting and is supported by a polymer-based MFA framework that maps material flows from production to end-of-life stages. Result: the findings indicate that while production processes achieve high efficiency with a yield of 89%, more than 60% of plastic bag waste remains unmanaged after use. Moreover, scenario analysis demonstrates that single interventions are insufficient to achieve circularity targets, whereas integrated strategies (e.g., reducing export volumes, enhancing waste collection, and improving recycling performance) are more effective in increasing recycling rates beyond 35%. Additionally, the study reveals that increasing domestic recycling capacity and minimizing dependency on exports can significantly reduce environmental leakage and strengthen local waste management systems. Conclusions: the study’s novelty lies in demonstrating how machine learning and material flow data can be synergized to inform circular supply chain decisions and regulatory planning. Full article

The maritime sector is undergoing rapid transformation, driven by increasingly stringent international regulations targeting air pollution. While newly built vessels integrate advanced technologies for compliance, the global fleet averages 21.8 years of age and must meet emission requirements through retrofitting or operational changes. This study evaluates, at environmental and economic levels, two key sulphur abatement strategies for a 1998-built cruise vessel nearing the end of its service life: (i) the installation of open-loop scrubbers with fuel enhancement devices, and (ii) a switch to marine diesel oil as main fuel. The analysis was based on real operational data from a cruise vessel. For the environmental assessment, a Tier III hybrid emissions model was used. The results show that scrubbers reduce SO_x emissions by approximately 97% but increase fuel consumption by 3.6%, raising both CO₂ and NO_x emissions, while particulate matter decreases by only 6.7%. In contrast, switching to MDO achieves over 99% SO_x reduction, an 89% drop in particulate matter, and a nearly 5% reduction in CO₂ emissions. At an economic level, it was found that, despite a CAPEX of nearly USD 1.9 million, scrubber installation provides an average annual net saving exceeding USD 8.2 million. From the deterministic and probabilistic analyses performed, including Monte Carlo simulations under various fuel price correlation scenarios, scrubber installation consistently shows high profitability, with NPVs surpassing USD 70 million and payback periods under four months. Full article

Background: Intermediate care units face growing complexity due to aging populations and chronic illnesses. Non-technical skills such as empathy and communication are crucial for quality care. We aimed to examine the relationship between communication skills, self-efficacy, and sense of coherence among intermediate care nurses. Methods: We conducted an observational, cross-sectional study with 60 intermediate care nurses from three units in a Catalan hospital, Spain. Participants engaged in high-fidelity simulation using geriatric end-of-life scenarios with an ultra-realistic manikin representing a geriatric patient at the end of life. NTSs were measured using validated tools: the Health Professionals Communication Skills Scale (HP-CSS), the General Self-Efficacy Scale, and the Sense of Coherence Questionnaire (OLQ-13). Sessions followed INACSL standards, including prebriefing, simulation, and debriefing phases. Results: Post-simulation outcomes revealed significant gains in interpersonal competencies, with men reporting higher assertiveness (p = 0.015) and greater satisfaction with both the simulation experience (p = 0.003) and the instructor (p = 0.008), underscoring gender-related perceptions in immersive training. Conclusions: Ultra-realistic clinical simulation is effective in enhancing NTS among intermediate care nurses, contributing to improved care quality and clearer professional profiles in geriatric nursing. Full article

This study analyses the greenhouse gas reduction potential of different end-of-life (EoL) strategies based on a case study of light electric vehicles (LEVs). Using a shared electric moped scooter as a reference, four EoL scenarios are evaluated in a comparative life cycle assessment (LCA). The modelling of the scenarios combines different R-strategies (e.g., recycling, reusing, and repurposing) regarding both the vehicle itself and the battery. German and EU regulations for vehicle and battery disposal are incorporated, as well as EU directives such as the Battery Product Pass. The global warming potential (GWP₁₀₀) of the production and EoL life cycle stages ranges from 644 to 1025 kg CO₂ eq among the four analysed scenarios. Landfill treatment led to the highest GWP₁₀₀, with 1.47 times higher emissions than those of the base scenario (status quo treatment following EU directives), while increasing component reuse and repurposing the battery cells achieved GWP₁₀₀ reductions of 2.8% and 7.8%, respectively. Overall, the importance of implementing sustainable EoL strategies for LEVs is apparent. To achieve this, a product design that facilitates EoL material and component separation is essential as well as the development of political and economic frameworks. This paper promotes enhancing the circularity of LEVs by combining the LCA of EoL strategies with eco-design considerations. Full article

Background and Objectives: Acute respiratory failure (ARF) represents an increasingly relevant clinical challenge in older subjects due to population aging and the high prevalence of cardiopulmonary comorbidities. Non-invasive ventilation (NIV), developed as continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP), has become a first-line treatment in various forms of ARF, including acute cardiogenic pulmonary oedema (ACPE) and acute exacerbations of COPD (AECOPD), offering several clinical advantages. In this context, the limited evidence on the efficacy of NIV in older patients leaves considerable uncertainty as to whether it constitutes a valid therapeutic option or represents medical futility in these patients. Materials and Methods: This narrative review explores the use of NIV and its outcomes in four key clinical scenarios in the elderly: ARF due to ACPE, AECOPD, community-acquired pneumonia (CAP), and palliative/end-of-life care. Results: Strong evidence supports NIV use with improved outcomes in ACPE and AECOPD, even in older populations. Conversely, data on its use in pneumonia are inconclusive, with potential harm if applied inappropriately. In palliative care, NIV can help relieve symptoms, but if not used appropriately, it may extend suffering. Conclusions: Age alone does not appear to be a sufficient factor to determine whether or not to use NIV; it becomes relevant only when considered in conjunction with the purpose of its use and the patient’s clinical history and condition. Data remain limited and often conflicting, particularly when investigating the elderly population and patients with a “do not intubate” (DNI) order. There is a need for additional research on these patients, focusing on long-term outcomes and quality of life. Full article

Despite the well-documented health risks of noise pollution, its impact remains overlooked mainly in life cycle assessment (LCA). This study introduces a methodological innovation by integrating both traffic and construction noise into the LCA framework for concrete construction, providing a more holistic and realistic evaluation of environmental and health impacts. By combining building information modeling (BIM) with LCA, the method automates material quantification and assesses both environmental and noise-related health burdens. A key advancement is the inclusion of health-based indicators, such as annoyance and sleep disturbance, quantified through disability-adjusted life years (DALYs). Two scenarios are examined: (1) a comparative analysis of concrete versus timber flooring and (2) end-of-life options (reuse vs. landfill). The results reveal that concrete has up to 7.4 times greater environmental impact than timber, except in land use. When noise is included, its contribution ranges from 7–33% in low-density regions (Darwin) and 62–92% in high-density areas (NSW), underscoring the critical role of local context. Traffic noise emerged as the dominant source, while equipment-related noise was minimal (0.3–1.5% of total DALYs). Timber slightly reduced annoyance but showed similar sleep disturbance levels. Material reuse reduced midpoint environmental impacts by 67–99.78%. Sensitivity analysis confirmed that mitigation measures like double glazing can cut noise-related impacts by 2–10% in low-density settings and 31–45% in high-density settings, validating the robustness of this framework. Overall, this study establishes a foundation for integrating noise into LCA, supporting sustainable material choices, environmentally responsible construction, and health-centered policymaking, particularly in noise-sensitive urban development. Full article

Italy strives to meet its renewable energy targets for 2030 and 2050, with photovoltaic (PV) technology playing a central role. However, the push for increased solar adoption, spurred by past incentive schemes such as “Conto Energia” and “Superbonus 110%”, raises long-term challenges related to PV waste management. In this study, we present a multi-scale approach to forecast End-of-Life (EoL) PV waste across Italy’s 20 regions, aiming to support national circular economy strategies. Historical installation data (2008–2024) were collected and combined with socio-economic and energy-related indicators to train a Backpropagation Neural Network (BPNN) for regional PV capacity forecasting up to 2050. Each model was optimised and validated using R² and RMSE metrics. The projections indicate that current trends fall short of meeting Italy’s decarbonisation targets. Subsequently, by applying a Weibull reliability function under two distinct scenarios (Early-loss and Regular-loss), we estimated the annual and regional distribution of PV panels reaching their EoL. This analysis provides spatially explicit insights into future PV waste flows, essential for planning regional recycling infrastructures and ensuring sustainable energy transitions. Full article

Amidst the global strategic transition towards low-carbon energy systems, electric vehicles (EVs) are pivotal for achieving deep decarbonization within the transportation sector. Consequently, enhancing the scientific rigor and precision of their life-cycle carbon footprint assessments is of paramount importance. Addressing the limitations of existing research, notably ambiguous assessment boundaries and the omission of dynamic coupling characteristics, this study develops a dynamic regional-level life-cycle carbon footprint assessment model for EVs that incorporates time-variant carbon emission factors. The methodology first delineates system boundaries based on established life-cycle assessment (LCA) principles, establishing a comprehensive analytical framework encompassing power battery production, vehicle manufacturing, operational use, and end-of-life recycling. Subsequently, inventory analysis is employed to model carbon emissions during the production and recycling phases. Crucially, for the operational phase, we introduce a novel source–load synergistic optimization approach integrating dynamic carbon intensity tracking. This is achieved by formulating a low-carbon dispatch model that accounts for power grid security constraints and the spatiotemporal distribution of EVs, thereby enabling the calculation of dynamic nodal carbon intensities and consequential EV emissions. Finally, data from these distinct stages are integrated to construct a holistic life-cycle carbon accounting system. Our results, based on a typical regional grid scenario, reveal that indirect carbon emissions during the operational phase contribute 75.1% of the total life-cycle emissions, substantially outweighing contributions from production (23.4%) and recycling (1.5%). This underscores the significant carbon mitigation leverage of the use phase and validates the efficacy of our dynamic carbon intensity model in improving the accuracy of regional-level EV carbon accounting. Full article

The timely detection of delamination is essential for preventing catastrophic failures and extending the service life of carbon fiber-reinforced polymers (CFRP). Full wavefields in CFRP encapsulate extensive information on the interaction between guided waves and structural damage, making them a widely utilized tool for damage mapping. However, due to the multimodal and dispersive nature of guided waves, interpreting full wavefields remains a significant challenge. This study proposes an end-to-end delamination imaging approach based on UNet++ using 2D frequency domain spectra (FDS) derived from full wavefield data. The proposed method is validated through a self-constructed simulation dataset, experimental data collected using Scanning Laser Doppler Vibrometry, and a publicly available dataset created by Kudela and Ijjeh. The results on the simulated data show that UNet++, trained with multi-frequency FDS, can accurately predict the location, shape, and size of delamination while effectively handling frequency offsets and noise interference in the input FDS. Experimental results further indicate that the model, trained exclusively on simulated data, can be directly applied to real-world scenarios, delivering artifact-free delamination imaging. Full article

EU accession countries, including the Republic of Serbia, are under growing pressure to align their plastic waste management systems with EU environmental directives. Despite this, significant challenges remain, including inadequate infrastructure, a limited recycling capacity, and weak enforcement mechanisms. This study employs life cycle assessment (LCA) to evaluate the environmental impacts of polyethylene terephthalate (PET) packaging waste in Serbia, focusing on three end-of-life scenarios (EoL): landfilling, recycling, and incineration. Using GaBi Professional v6.0 software and the ReCiPe 2016 methodology, the results indicate that mismanaged PET waste contributes notably to terrestrial ecotoxicity (3.69 kg 1.4-DB eq.) and human toxicity (non-cancer) (2.36 kg 1.4-DB eq.). In 2023, 14,967.8 tons of PET were collected by authorized operators; however, unreported quantities likely end up in landfills or the natural environment. Beyond the quantified LCA results, this study highlights microplastic pollution as an emerging environmental concern. It advocates for the development of Serbia-specific characterization factors (CFs) for PET microplastics, incorporating localized fate, exposure, and effect data. Tailored CFs would enhance the precision of impact assessments for Serbian terrestrial ecosystems, contributing to more effective, evidence-based environmental policies. These insights are crucial for supporting Serbia’s transition to sustainable waste management and for meeting EU environmental standards. Full article

In this study, we selected the production processes and main products of three typical chemical enterprises in Shanghai, namely SH Petrochemical (part of the oil-refining sector), SK Ethylene, and HS Chlor-Alkali, to quantitatively assess the synergistic effects across technology, policy, and emission mechanisms. The localized air pollutant levels and greenhouse gas emissions of the three enterprises were calculated. The synergistic effects between the end-of-pipe emission reductions for air pollutants and greenhouse gas emissions were analyzed using the pollutant reduction synergistic and cross-elasticity coefficients, including technology comparisons (e.g., acrylonitrile gas incineration (AOGI) technology vs. traditional flare). Based on these data, we used the SimaPro software and the CML-IA model to conduct a life cycle environmental impact assessment regarding the production and upstream processes of their unit products. By combining the life cycle method and the scenario simulation method, we predicted the trends in the environmental impacts of the three chemical enterprises after the implementation of low-carbon development policies in the chemical industry in 2030. We also quantified the synergistic effects of localized air pollutant and greenhouse gas (GHG) emission reductions within the low-carbon development scenario by using cross-elasticity coefficients based on life cycle environmental impacts. The research results show that, for every ton of air pollutant reduced through end-of-pipe treatment measures, the HS Chlor-Alkali enterprise would increase its maximum CO₂ emissions, amounting to about 80 tons. For SK Ethylene, the synergistic coefficient for VOC reduction and CO₂ emissions when using AOGI thermal incineration technology is superior to that for traditional flare thermal incineration. The activities of the three enterprises had an impact on several environmental indicators, particularly the fossil fuel resource depletion potential, accounting for 69.48%, 53.94%, and 34.23% of their total environmental impact loads, respectively. The scenario simulations indicate that, in a low-carbon development scenario, the overall environmental impact loads of SH Petrochemical (refining sector), SK Ethylene, and HS Chlor-Alkali would decrease by 3~5%. This result suggests that optimizing the upstream power structure, using “green hydrogen” instead of “grey hydrogen” in hydrogenation units within refining enterprises, and reducing the consumption of electricity and steam in the production processes of ethylene and chlor-alkali are effective measures in reducing carbon emissions in the chemical industry. The quantification of the synergies based on life cycle environmental impacts revealed that there are relatively strong synergies for air pollutant and GHG emission reductions in the oil-refining industry, while the chlor-alkali industry has the weakest synergies. Full article

This study investigates the enhancement of condition and the extension of service life in architectural structures of shopping malls through the application of a hybrid methodological framework that integrates Life Cycle Assessment (LCA) and Service Life Planning (SLP). Thisresearch identifies key parameters related to physical performance, sustainability indicators, and functional characteristics of architectural systems that are subject to deterioration and shifting market conditions during the operational phase. The methodology encompasses a theoretical synthesis of LCA/SLP principles and advances in modeling for both the integrated design of new facilities and the monitoring and renewal of existing ones—from data collection and early-stage planning, through construction, use, and maintenance, to end-of-life phases. A second component of the model focuses on quantitative assessment and condition forecasting, based on Markov chain modeling, applied to the case study of the “Deva 1” shopping mall in Serbia. The results demonstrate the model’s ability to correlate physical condition indices with predictive service life scenarios.This study further contributes by integrating time-dependent impact categories, usage profiles, and planning parameters into a unified evaluation matrix, which can be applied to the development and improvement of systems aimed at enhancing the structural, functional, esthetic, and indirectly economic value of shopping mall buildings throughout their entire life cycle—from an architectural perspective. Full article

Purely electric and hybrid vehicles are emerging as the transport sector’s response to meet climate goals, aiming to mitigate global warming. As the adoption of transport electrification increases, the importance of recycling components of the electric propulsion system at the end of their life grows, particularly the battery pack, which significantly contributes to the vehicle’s final cost and generates environmental impacts and CO₂ during production. This work presents an overview of the recycling processes for lithium-ion automotive batteries, emphasizing the developing Brazilian scenario and more established international scenarios. In Brazil, companies and research centers are investing in recycling and using reused cathode material to manufacture new batteries through the hydrometallurgical process. On the international front, pyrometallurgy and physical recycling are being applied, and other methods, such as direct processes and biohydrometallurgy, are also under study. Regardless of the recycling method, the main challenge is scaling prototype processes to meet current and future battery demand, driven by the growth of electric and hybrid vehicles, pursuing both environmental gains through reduced mining and CO₂ emissions and economic viability to make recycling profitable and support global electrification. Full article

This paper demonstrates the application of cognitive modeling methods to study problems relating to the functioning and advancement of a strategy for the development of rural areas. Rural areas play a vital role in human life; they have enormous economic, natural, demographic, historical, and cultural potential, and their revival ensures the achievement of the United Nations Sustainable Development Goals in the field of SDG 2: “End hunger, achieve food security and improve nutrition and promote sustainable agriculture”. The relevance of the study lies in the need to develop approaches in order to improve the efficiency of agriculture and to ensure the sustainable development of rural areas. The goal was to use cognitive modeling tools to understand the cause-and-effect mechanism of ensuring sustainable development of rural areas and analyze their possible development under the influence of internal and external factors to select the best strategy for sustainable development. Based on 24 selected quantitative and qualitative indicators, a cognitive map “Sustainable Development of Rural Areas” was constructed, and an analysis of 351 cycles of the cognitive model was carried out, among which 286 positive and 65 negative cycles were observed, indicating the structural stability of the model. Computational experiments were carried out using pulse and scenario modeling; the results are presented and visualized in the form of five scenarios for complex systems development. The results of this study can be used as decision support tools for substantiating strategies and developing policies for the balanced development of rural areas. Full article

The Fourth Industrial Revolution and artificial intelligence (AI) technology are driving the transformation of the meat industry from mechanization and automation to intelligence and digitization. This paper provides a systematic review of key technological innovations in this field, including physical technologies (such as smart cutting precision improved to the millimeter level, pulse electric field sterilization efficiency exceeding 90%, ultrasonic-assisted marinating time reduced by 12 h, and ultra-high-pressure processing extending shelf life) and digital technologies (IoT real-time monitoring, blockchain-enhanced traceability transparency, and AI-optimized production decision-making). Additionally, it explores the potential of alternative meat production technologies (cell-cultured meat and 3D bioprinting) to disrupt traditional models. In application scenarios such as central kitchen efficiency improvements (e.g., food companies leveraging the “S2B2C” model to apply AI agents, supply chain management, and intelligent control systems, resulting in a 26.98% increase in overall profits), end-to-end temperature control in cold chain logistics (e.g., using multi-array sensors for real-time monitoring of meat spoilage), intelligent freshness recognition of products (based on deep learning or sensors), and personalized customization (e.g., 3D-printed customized nutritional meat products), these technologies have significantly improved production efficiency, product quality, and safety. However, large-scale application still faces key challenges, including high costs (such as the high investment in cell-cultured meat bioreactors), lack of standardization (such as the absence of unified standards for non-thermal technology parameters), and consumer acceptance (surveys indicate that approximately 41% of consumers are concerned about contracting illnesses from consuming cultured meat, and only 25% are willing to try it). These challenges constrain the economic viability and market promotion of the aforementioned technologies. Future efforts should focus on collaborative innovation to establish a truly intelligent and sustainable meat production system. Full article