Search Results (192)

This study assesses the environmental performance of three wastewater treatment setups through an attributional, gate-to-gate life cycle assessment (functional unit: 1 m³ of treated wastewater): (Sc1) a traditional municipal wastewater treatment plant, (Sc2) an aquaculture recirculation system using microalgae, and (Sc3) a domestic system combining UASB pretreatment with microalgae polishing. Inventory data were analyzed in SimaPro with ReCiPe 2016 Midpoint (Hierarchist) across seven effect categories. Robustness was tested through sensitivity analyses (±20%) of power consumption and influent characteristics, as well as an additional scenario exploring the offset of methane-recovery electricity. The global warming impact remained consistent across scenarios, ranging from 60.5 to 65.1 kg CO₂-eq·m⁻³, indicating no significant difference within the operational parameters. In most categories, power consumption and influent-related burdens were the main contributors, while the impacts from flocculants and microalgae inoculum were minimal. Sc3 showed a lower freshwater eutrophication potential compared to Sc1 and Sc2 (0.028 vs. approximately 0.049 kg P-eq·m⁻³). Normalization highlighted human carcinogenic toxicity and aquatic ecotoxicity as key impact categories. The methane-offset scenario caused only slight changes at low CH₄ outputs, suggesting that energy recovery depends on context. Full article

Life cycle assessment (LCA) studies show that electricity supply and consumption are often a dominant contributor to environmental impacts, yet these results are highly sensitive to the choice of inventory database and its embedded assumptions. This study examines how database structure and scenario flexibility shape electricity-related impacts by comparing three approaches for the 2022 Northeast Power Coordinating Council (NPCC) region in the USA: the Ecoinvent “market for electricity” dataset, the modular U.S. electricity model from the Sphera database, and a customized NPCC model built from Ecoinvent unit processes. Impacts were assessed with both ReCiPe 2016 and TRACI 2.1. While climate change and fossil resource depletion results were consistent across databases and impact assessment methods, toxicity-related categories diverged substantially, with substantially higher values from Ecoinvent inventories. These high toxicity values were directly linked to assumptions about the use of copper in grid infrastructure (66%), including incineration at its end of life (18%), a disposal technique that is not relevant to the NPCC area. A case study of residential heating electrification further highlighted that while heat pumps with a decarbonized grid consistently reduced climate impacts, conclusions for other categories varied depending on the database used. These findings underscore the importance of transparent electricity models and cross-database sensitivity analysis in prospective LCAs when evaluating the overall environmental and health benefits of a sustainable energy future (UN SDG 7, 13). Without such practices, non-climate results, particularly toxicity outcomes, risk reflecting database assumptions and artifacts rather than real technological and environmental differences. Full article

Background/Objectives: Multiple sclerosis (MS) is a chronic, demyelinating, inflammatory, and degenerative disease of the nervous system that may present in childhood or adolescence, defined as Pediatric-Onset Multiple Sclerosis (POMS). Among its diverse clinical manifestations, neurogenic bowel dysfunction (NBD), including chronic constipation and fecal incontinence, represents a distressing condition with a substantial impact on quality of life (QoL). Despite its clinical relevance, the evidence on bowel dysfunction in pediatric MS remains limited. The objective of this case series was to evaluate bowel dysfunction and its management in a pediatric MS cohort, and to assess whether it is associated with QoL. Methods: We reported the data on the urological and bowel conditions and on the quality of life of our pediatric patients affected by MS and urological dysfunction. We considered MS patients with urinary symptoms who were referred to our department between January 2019 and January 2024, only including individuals with symptoms onset before 18 years of age. In our series, the demographic and clinical data were reviewed, and patients were re-evaluated via telephone interview at least one year after initiation of treatment. The International Consultation on International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF), Pediatric Bowel Management Scoring Tool (PBMST), and Pediatric Quality of Life Inventory (PedsQL, young adults’ version) were used to assess urinary and bowel function and related QoL outcomes. Results: Six patients (four females, two males; median age 14.5 years) were included. Bowel symptoms were reported in four cases (66.6%), predominantly constipation. The PBMST scores indicated overall fair bowel management, while the mean PedsQL score was 62.8/100, with poorer scores observed for the non-adherent patients. Conclusions: Bowel dysfunction constitutes an underrecognized but clinically significant manifestation in pediatric MS. Its early identification and adherence to a structured bowel management program seems to be crucial for optimizing symptom control and preserving quality of life. Standardized questionnaires represent effective, non-invasive tools for assessment and longitudinal monitoring. Full article

Based on field inventory data collected from 117 temporary plots in Sichuan Province, 19 bamboo culm height–diameter at breast height (DBH) base models for Cizhu (Bambusa emeiensis) were constructed and assessed to evaluate the effectiveness and applicability of multiple model structures and re-parameterization strategy for model performance improvement. Under a unified evaluation framework (taking the R², RMSE, and AIC as criteria), the impact of model structure on fitting and predictive performance was analyzed. Based on partial correlation analysis and field operability, the branch-free culm node number was selected as an explanatory variable and used to re-parameterize each base model at each parameter position. The performance improvement achieved through re-parameterization for different model structures was systematically assessed. The results showed that at the base model level, the overall performances of most models were roughly similar, with the growth model performing relatively better according to comprehensive evaluation indicators (R²: 0.5764, RMSE: 2.376 m, AIC: 1109.19). As for re-parameterized models, they generally exhibited varying degrees of performance improvement compared to their corresponding base models, among which the growth model re-parameterized at the position of parameter b showed the best performance according to comprehensive evaluation indicators (R²: 0.6445, RMSE: 2.195 m, AIC: 1071.87). Re-parameterization based on growth structure variables can substantially enhance the fitting and prediction performance of bamboo height–DBH models for B. emeiensis. It is concise and easy to implement, which may provide reference for bamboo height–DBH modeling and other related research on B. emeiensis. Full article

Tropical Andean forests are biodiversity hotspots that have been transformed by anthropogenic activities, making ecosystem regeneration and restoration essential for their recovery. This study evaluated floristic composition, forest structure, and diversity in three land cover types within tropical Andean ecosystems: riparian forest (RF), natural regeneration (NR), and ecological restoration areas (RE). Vegetation was inventoried using standardized plots, recording species composition, diameter, and height. Basal area, size class distribution, and vertical structure were estimated. The Shannon Wiener and Simpson indices were evaluated. RF showed the highest structural complexity and basal area among the evaluated cover types, followed by ER, whereas NR showed the lowest values. NR showed the highest diversity values and a predominance of individuals in lower diameter and height classes, reflecting active recruitment and intermediate successional stages. Segment ER exhibited lower diversity and intermediate structural development, consistent with shorter recovery periods and limitations in restoration design. Overall, the integration of floristic, structural, and diversity attributes indicates distinct successional trajectories, conditioned by land-use history, disturbance intensity, and environmental heterogeneity. These findings highlight the great potential for natural regeneration under reduced anthropogenic pressure and emphasize the need to integrate passive and active restoration strategies to enhance biodiversity and resilience in Andean tropical forests. Full article

The territorial development of the city of Brno during the 19th–21st centuries meant not only the growth of built-up areas (residential, industrial, commercial), but also the absorbing of segments of the ancient rural agricultural landscape. Within the current borders of the city of Brno, a number of green areas have been preserved, which have spontaneously developed from the original agricultural landscape, without being the result of urban planning. In half of the cases (17 out of a total of 34), they have still preserved the traditional small-scale division of land. Among the 10 medium-sized Moravian cities (between 30,000 and 400,000 inhabitants) in the historical region of Moravia in the east of the Czech Republic, the presence of 34 remnants of the ancient rural landscape in the city of Brno is quite exceptional (in Ostrava only 1; in other cities 0). The subject of the research is the inventory of such segments within the city borders and an attempt to explain their location in the city, state, focusing on the role of natural factors, land ownership and personal and recreational interests of residents. Segments of the ancient rural cultural landscape were identified by comparing the current landscape on aerial photographs with the landscape image on cadastral maps from the 1820s–1830s. Additional data on their natural and cultural properties were obtained through archival and field research. The segments were classified according to their degree of preservation and forms of threat. The results show that the remains of the ancient rural cultural landscape in the city of Brno have generally been preserved in locations that, due to the slope of the slopes, unsuitable building subsoil and poor soil, but locally on warm southern slopes, were not suitable for construction for the time being. Urban gardening contributes to their preservation and these areas are part of the city’s greenery. However, urban gardening also contributes to the destruction of these remnants. In 17 cases, the land was completely re-divided, built up with recreational facilities and overgrown with trees due to poor care. Another 17 locations are threatened by this process due to ignorance of their historical value, although this is essentially a positive development in terms of benefits for the city’s residents—land users. Although the Master Plan of the city of Brno foresees the existence of garden colonies in the future, it does not address the importance of the best-preserved segments as historical heritage. Community agriculture can play a positive role in maintaining segments of rural heritage within the city. Full article

Temperature Swing Absorption (TSA) is the primary candidate for the Isotope Rebalancing and Protium Removal (IRPR) system within the envisioned EU-DEMO fusion reactor fuel cycle. TSA separates a mixed hydrogen isotope stream into two product streams using a semi-continuous process. One stream, enriched in heavy isotopes, is used to re-establish the required deuterium-to-tritium fuel ratio. The second, enriched in protium, is stripped off from the fuel cycle to counteract the protium build-up. Separation is achieved by cycling an isotope mixture between two columns filled with metallic absorption materials that have opposite isotope effects of metal hydride formation. The selection of these materials, the operation parameters and the column geometry allow for adjusting the resulting enrichments. To identify suitable operation parameters, a TSA process model is developed which depicts the process dynamics and interactions between the columns. A modified process operation mode is introduced, which enables higher system throughputs and non-cryogenic operation, i.e., operational temperatures between 0 to 130 °C, while reducing the tritium inventory due to shorter cycling times by reduced amplitudes of the temperature swings. Finally, simulations of a TSA system at relevant scale confirm the suitability of TSA technology for the separation task of the EU-DEMO IRPR system. Full article

Currently, the manual delineation of landslide anomalies from Interferometric Synthetic Aperture Radar(InSAR )deformation data is labor-intensive and time-consuming, creating a major bottleneck for operational large-scale landslide mapping. This study proposes an automated approach for large-scale landslide identification by integrating InSAR technology with an improved Faster Regional Convolutional Neural Network (Faster R-CNN). First, surface deformation over the study area was obtained using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique. An enhanced CRF-Faster R-CNN model was then developed by incorporating a Residual Network with 50 layers (ResNet-50)-based backbone, strengthened with a Convolutional Block Attention Module (CBAM), within a Feature Pyramid Network (FPN) framework. This model was applied to deformation velocity maps for the automated detection of landslide-prone areas. Preliminary results were subsequently validated and refined using optical images to produce a final landslide inventory. The proposed method was evaluated in the Ahai Reservoir area of the Jinsha River Basin using 248 ascending and descending Sentinel-1A images acquired between January 2019 and December 2021. Its performance was compared with that of the standard Faster R-CNN model. The results indicate that the CRF-Faster R-CNN model outperforms the conventional approach in terms of landslide anomaly detection, convergence speed, and overall accuracy. A total of 38 potential landslide hazards were identified in the Ahai Reservoir area, with an 84% validation accuracy confirmed through field investigations. This study provides crucial technical support for the rapid identification and operational application of large-scale potential landslide hazards. Full article

Microplastic quantification in marine vegetated ecosystems remains analytically demanding, yet little is known about the environmental footprint of the laboratory procedures required to isolate and measure these particles. This study applies Life Cycle Assessment (LCA) to laboratory analytical workflows for microplastics quantification, focusing exclusively on sample preparation and analytical procedures rather than natural environmental absorption or fate processes, in two ecologically relevant matrices: (i) pelagic algae (Sargassum) and (ii) seagrass biomass. Using the openLCA 2.5 and the ReCiPe Midpoint (H) v1.13 methods, the analysis integrates foreground inventories of digestion, filtration, drying, and spectroscopic identification, combined with background datasets from OzLCI2019, ELCD 3.2 and USDA. Results show substantially higher impacts for the algae scenario, particularly for climate change, human toxicity, ionising radiation and particulate matter formation, largely driven by longer digestion times, increased reagent use and higher energy demand during sample pre-treatment. Conversely, the seagrass scenario exhibited lower burdens per functional unit due to reduced organic complexity and shorter laboratory processing requirements. These findings highlight the importance of matrix-specific methodological choices and the influence of background datasets on impact profiles. This study provides the first benchmark for the environmental performance of microplastic analytical workflows and underscores the need for harmonised, low-impact laboratory protocols to support sustainable monitoring of microplastic pollution in marine ecosystems. Full article

Industrial air emissions are major contributors to human exposure to toxic pollutants, posing significant health risks. Life cycle assessment (LCA) is increasingly used to quantify human toxicity impacts from industrial processes. Conventional LCA often overlooks spatial and temporal variability, limiting its ability to capture actual inhaled doses and exposure-driven impacts. To address this, we developed a site-dependent dynamic LCA (SdDLCA) framework that integrates conventional LCA with Enhanced Structural Path Analysis (ESPA) and atmospheric dispersion modeling. Applied to the production of double-glazed PVC windows for a residential project, the framework generates high-resolution, site-specific emission inventories for three key pollutants: nitrogen oxides (NO_x), sulfur dioxide (SO₂), and fine particulate matter (PM_2.5). Local concentration fields are compared with World Health Organization (WHO) air quality thresholds to identify hotspots and periods of elevated exposure. By coupling these fields with the ReCiPe 2016 endpoint methodology and localized demographic and meteorological data, SdDLCA quantifies human health impacts in Disability-Adjusted Life Years (DALYs), providing a direct measure of inhalation toxicity. This approach enhances LCA’s ability to capture exposure-driven effects, identifies populations at greatest risk, and offers a robust, evidence-based tool to guide industrial planning and operations that minimize health hazards from air emissions. Full article

Thyroid cancer survivors often experience worse quality of life than other cancer survivors, with fatigue and sleep disturbance being common contributors. In this prospective cohort from the ICaRe2 cancer registry, survivors completed the Brief Fatigue Inventory (BFI) and Pittsburgh Sleep Quality Index (PSQI) at enrollment and follow-up, with univariate and multivariable analyses identifying factors associated with fatigue and sleep quality. Among 249 survivors (83% female, median age 42), 205 completed the BFI and 224 the PSQI. Most were low (57%) or intermediate (34%) risk or recurrence at diagnosis, and 74% had no structural recurrence. Poor sleep and greater fatigue were significantly associated with female sex (p = 0.0003 and 0.001), younger age at diagnosis (p = 0.02 and 0.0006), and vocal cord paralysis (p = 0.01 and 0.046). Fatigue was also higher in those with hypoparathyroidism (p = 0.04). No associations were found with recurrence risk, therapy response, thyroid hormone type, or TSH levels. Younger female survivors, particularly those with vocal cord paralysis or hypoparathyroidism, are more prone to fatigue and poor sleep, highlighting potential targets for interventions to improve quality of life. Full article

The paper investigates the role of digitalization in strengthening the sustainability of supply chains in the Romanian restaurant sector. The starting point is the intersection between the pressures for digital transformation and the integration of sustainability principles. Digitalization, through advanced digital solutions, can strengthen traceability, reduce waste, and optimize resources, strengthening responsibility for economic efficiency and the environment. However, the implementation of these solutions in HoReCa remains disproportionate and faces barriers such as lack of digital skills, high costs, and resistance to change. The authors conducted a quantitative research study among restaurant managers in Romania. The research was complemented with two Principal Component Analyses (PCA) and a TwoStep Cluster Analysis. The role of the TwoStep Cluster Analysis was to identify a typology of restaurants according to managerial behaviors related to digitalization from a sustainable perspective. The results showed that digitalization is applied predominantly in inventory management, but less in the relationship with consumers and supply chain, where it would bring considerable benefits for sustainability. The study provides theoretical and practical contributions, highlighting the role digitalization has as a facilitator of sustainability and indicating recommendations for managers and decision-makers regarding professional training and financial support policies dedicated to sustainable digitalization. Full article

Engineered wood products have become key sustainable alternatives to conventional building materials, offering strong potential for reducing climate impacts in the construction sector. This review systematically assesses recent life cycle assessment studies on engineered wood products to compare their environmental performance and support low-carbon building practices. The peer-reviewed literature published over the past decade was analyzed for publication trends, geographic focus, and methodological approaches, including goal and scope definition, life cycle inventory, and life cycle impact assessment. Comparative analyses examined climate change impact and key parameters influencing environmental outcomes. Results indicate a steady growth of research in this field, led by China, the United States, and Europe. Volume-based functional units (e.g., 1 m³) are predominant in structural wood studies, while mass-based units are more common for composites. Cradle-to-gate boundaries are most frequently used, and data are primarily drawn from Ecoinvent, Environmental Product Declarations, and regional databases such as GaBi and CLCD. Common impact assessment methods include CML-IA, ReCiPe, and TRACI, with climate change identified as the core impact category. Cross-laminated timber and glue-laminated timber consistently show lower and more stable climate change impacts, while fiberboards exhibit higher and more variable results due to adhesive content and energy-intensive manufacturing. Key factors influencing environmental outcomes include service life, wood species, and material sourcing. The review highlights the need for standardized methodologies and further exploration of emerging products, such as nail-laminated and dowel-laminated timber and laminated bamboo, to improve comparability and inform sustainable design practices. Full article

This study addresses the challenge of aligning inventory forecasting with sustainability and service level goals in re-order point systems. It introduces a semiparametric forecasting method based on exponential smoothing and M-estimation, designed to directly model reorder levels under fill rate (P2) constraints. The proposed approach is benchmarked against state-of-the-art techniques, including Generalized Autoregressive Score (GAS) models, volatility-adjusted smoothing, and DeepAR—a deep learning model for probabilistic time series forecasting. Using monthly demand data from the M3 competition, empirical evaluation demonstrates that the semiparametric method achieves high service level accuracy with low inventory and logistics costs, particularly under short lead times. DeepAR shows strong performance in minimizing inventory levels but tends to underestimate stock requirements under high service level targets. A hybrid strategy combining forecasts from multiple models proves robust across scenarios, reducing forecast risk. The findings highlight the potential of integrating traditional statistical methods with AI-based approaches to support resource-efficient inventory management. By minimizing excess stock and backorders, the proposed methods contribute to reducing environmental impact, offering practical solutions for organizations seeking to balance operational efficiency with sustainability. Full article

Background: An effective healthcare system relies on sufficient and competent human resources. However, many countries face staff shortages, burnout, and turnover, which threaten the quality and safety of care. To address the absence of validated tools assessing healthcare professionals’ perceptions of staff resource adequacy in Latvia, the Staff Resource Adequacy Questionnaire for Healthcare Professionals (SRAQ-HP) was developed. Methods: This study examined its construct validity through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) using a nationwide sample of 1369 healthcare professionals. EFA supported a three-factor structure comprising (1) adequacy of workload and staff resources, (2) quality of care, and (3) working conditions and support. Results: The instrument demonstrated high internal reliability (Cronbach’s α > 0.94) and moderate model fit indices (CFI/TLI > 0.90; RMSEA = 0.145; SRMR = 0.100). Although RMSEA values (0.145) were above conventional cutoffs, this was expected given the large sample and model complexity. Convergent validity was supported by correlations with established measures—the Measure of Moral Distress for Healthcare Professionals (MMD-HP), the Copenhagen Burnout Inventory (CBI), and the Anticipated Turnover Scale (ACT)—while criterion validity showed significant predictive value only for moral distress. Conclusions: Overall, the SRAQ-HP demonstrates promising psychometric properties and practical applicability for assessing staff resource adequacy in healthcare settings, although further refinement and re-validation (particularly of one reverse-worded item) are recommended before broader implementation. Full article