Search Results (8,192)

This study examines whether environmental assurance and environmental management certifications are associated with subsequent environmental performance and reputational exposure in European Union listed firms. Using Refinitiv Eikon panel data for 441 firms (1773 firm-year observations) from 2017–2023, we analyze environmental pillar sub-scores (Emissions, Resource Use, and Innovation) and three intensity indicators (energy, pollution, and recycled waste intensity). We estimate firm fixed-effects models for performance outcomes and Firth’s logistic regression models for media-reported environmental controversies, using lagged assurance/certification indicators. Environmental assurance is consistently associated with higher environmental sub-scores and with lower energy and pollution intensity, alongside higher recycled waste intensity. In contrast, certification effects are weaker and more heterogeneous across intensity-based indicators. Regarding reputational exposure, assured firms show a higher likelihood of subsequent media-reported environmental controversies, which is consistent with heightened scrutiny and visibility rather than evidence of intent. These findings inform boards, assurance providers, investors, and policymakers seeking to strengthen the credibility and use of corporate environmental information. Full article

Environmental pesticide exposure has been linked to adverse health effects, and residential proximity to agricultural land is commonly used as a proxy for exposure; however, the contribution of non-agricultural biomes remains insufficiently explored. This study examined whether the proximity and area of different biomes are associated with the detection of selected pesticides in human urine in Latvia. Urine samples were collected from 202 participants (101 adults and 101 children) within the Human Biomonitoring for Europe (HBM4EU) study during the winter and summer seasons of 2020. A suspect screening approach using liquid chromatography–high-resolution mass spectrometry (LC-HRMS) was applied and 23 pesticides were detected (8 insecticides, 12 fungicides, 2 herbicides and triclosan, an antimicrobial ingredient used in cleaning agents). Geospatial data were analysed in Quantum Geographic Information System (QGIS) to derive biome proximity and area within a 1000 m residential buffer; associations were assessed using generalized linear mixed-effects models. Agricultural land was present within 1000 m of 93.1% of residences, yet neither its distance nor area was consistently associated with pesticide detection. Boscalid was detected in 18.4% of samples and was positively associated with wetland area across seasons (p < 0.001), while fludioxonil (14.7%) showed weak and heterogeneous spatial associations and pirimiphos-methyl (10.2%) showed no significant patterns. Overall, pesticide exposure was substance-specific and influenced by landscape characteristics beyond agricultural proximity, highlighting the need to integrate non-agricultural biomes into human biomonitoring in low-intensity pesticide-use settings. Full article

Climate change poses a threat to global rice production by increasing the frequency and intensity of extreme weather events. The widespread cultivation of genetically uniform modern varieties has narrowed the genetic base of rice, increasing its vulnerability to these increased pressures. Rice landraces are traditional rice varieties that have been cultivated by farming communities for centuries and are considered crucial resources of genetic diversity. These landraces are adapted to a wide range of agro-ecological environments and exhibit valuable traits that provide tolerance to various biotic stresses, including drought, salinity, nutrient-deficient soils, and the increasing severity of climate-related temperature extremes. In addition, many landraces possess diverse alleles associated with resistance to biotic stresses, including pests and diseases. In addition, rice landraces exhibit great grain quality characters including high levels of essential amino acids, antioxidants, flavonoids, vitamins, and micronutrients. Hence, their preservation is vital for maintaining agricultural biodiversity and enhancing nutritional security, especially in vulnerable and resource-limited regions. However, rice landraces are increasingly threatened by genetic erosion due to widespread adoption of modern high-yielding varieties, habitat loss, and changing farming practices. This review discusses the roles of rice landraces in developing resilient and climate-smart rice cultivars. Moreover, the Pantiange Heigu landrace, cultivated at one of the highest altitudes globally in Yunnan Province, China, has been used as a case study for integrated conservation by demonstrating the successful combination of in situ and ex situ strategies, community engagement, policy support, and value-added development to sustainably preserve genetic diversity under challenging environmental and socio-economic challenges. Finally, this study explores the importance of employing advanced genomic technologies with supportive policies and economic encouragements to enhance conservation and sustainable development of rice landraces as a strategic imperative for global food security. By preserving and enhancing the utilization of rice landraces, the agricultural community can strengthen the genetic base of rice, improve crop resilience, and contribute substantially to global food security and sustainable agricultural development in the face of environmental and socio-economic challenges. Full article

Communication in mammals constitutes a complex, multimodal system that integrates visual, acoustic, tactile, and chemical signals whose functions extend beyond simple information transfer to include the regulation of social relationships, coordination of behaviour, and expression of emotional states. This article examines the fundamental mechanisms of communication from biological, neuroethological, and behavioural perspectives, with particular emphasis on domesticated and farmed species. Analysis of sensory signals demonstrates that their perception and interpretation are closely linked to the physiology of sensory organs as well as to social experience and environmental context. In companion animals such as dogs and cats, domestication has significantly modified communicative repertoires ranging from the development of specialised facial musculature in dogs to adaptive diversification of vocalisations in cats. The neurobiological foundations of communication, including the activity of the amygdala, limbic structures, and mirror-neuron systems, provide evidence for homologous mechanisms of emotion recognition across species. The article also highlights the role of communication in shaping social structures and the influence of husbandry conditions on the behaviour of farm animals. In intensive production environments, acoustic, visual, and chemical signals are often shaped or distorted by crowding, noise, and chronic stress, with direct consequences for welfare. Furthermore, the growing importance of multimodal technologies such as Precision Livestock Farming (PLF) and Animal–Computer Interaction (ACI) is discussed, particularly their role in enabling objective monitoring of emotional states and behaviour and supporting individualised care. Overall, the analysis underscores that communication forms the foundation of social functioning in mammals, and that understanding this complexity is essential for ethology, animal welfare, training practices, and the design of modern technologies facilitating human–animal interaction. Full article

In response to the growing interest in sustainable and material-efficient architectural solutions, this study focuses on innovative applications of engineered timber in lightweight structural systems. It investigates the material optimization and structural performance of engineered timber thin-shell structures through an integrated parametric design approach. The study compares three prefabricated, panelized building systems, gridshell, segmented full-plate shell, and ribbed shell, to evaluate their efficiency in terms of material intensity, stiffness, and geometric behavior. Using Rhinoceros and Grasshopper environments with Karamba3D, Kiwi3D, and Kangaroo plugins, a comprehensive parametric workflow was developed that integrates geometric modeling, structural analysis, and material evaluation. The results show that segmented ribbed shell and two segmented gridshell variants offer up to 70% reduction in material usage compared with full-plate segmented timber shells, with hybrid timber shells achieving the best balance between stiffness and mass, offering functional advantages (roofing without additional load). These findings highlight the potential of parametric and computational design methods to enhance both the environmental efficiency (LCA) and digital fabrication readiness of timber-based architecture. The study contributes to the ongoing development of computational timber architecture, emphasizing the role of design-to-fabrication strategies in sustainable construction and the digital transformation of architectural practice. Full article

To improve the accuracy and robustness of lithium-ion battery state of charge (SOC) estimation, this paper proposes a generalized mixture maximum correlation-entropy criterion-based adaptive extended Kalman filter (GMMCC-AEKF) algorithm, addressing the performance degradation of the traditional extended Kalman filter (EKF) under non-Gaussian noise and inaccurate initial conditions. Based on the GMMCC theory, the proposed algorithm introduces an adaptive mechanism and employs two generalized Gaussian kernels to construct a mixed kernel function, thereby formulating the generalized mixture correlation-entropy criterion. This enhances the algorithm’s adaptability to complex non-Gaussian noise. Simultaneously, by incorporating adaptive filtering concepts, the state and measurement covariance matrices are dynamically adjusted to improve stability under varying noise intensities and environmental conditions. Furthermore, the use of statistical linearization and fixed-point iteration techniques effectively improves both the convergence behavior and the accuracy of nonlinear system estimation. To investigate the effectiveness of the suggested method, experiments for SOC estimation were implemented using two lithium-ion cells featuring distinct rated capacities. These tests employed both dynamic stress test (DST) and federal test procedure (FTP) profiles under three representative temperature settings: 40 °C, 25 °C, and 10 °C. The experimental findings prove that when exposed to non-Gaussian noise, the GMMCC-AEKF algorithm consistently outperforms both the traditional EKF and the generalized mixture maximum correlation-entropy-based extended Kalman filter (GMMCC-EKF) under various test conditions. Specifically, under the 25 °C DST profile, GMMCC-AEKF improves estimation accuracy by 86.54% and 10.47% over EKF and GMMCC-EKF, respectively, for the No. 1 battery. Under the FTP profile for the No. 2 battery, it achieves improvements of 55.89% and 28.61%, respectively. Even under extreme temperatures (10 °C, 40 °C), GMMCC-AEKF maintains high accuracy and stable convergence, and the algorithm demonstrates rapid convergence to the true SOC value. In summary, the GMMCC-AEKF confirms excellent estimation accuracy under various temperatures and non-Gaussian noise conditions, contributing a practical approach for accurate SOC estimation in power battery systems. Full article

Addressing the growing threat of climate change requires urgent and sustainable solutions for managing carbon dioxide (CO₂) emissions. This review investigates the latest advancements in technologies for capturing and converting CO₂, with a focus on approaches that prioritize energy efficiency, environmental compatibility, and economic viability. Emerging strategies in CO₂ capture are discussed, with attention to low-carbon-intensity materials and scalable designs. In parallel, innovative CO₂ conversion pathways, such as thermocatalytic, electrocatalytic, and photochemical processes, are evaluated for their potential to transform CO₂ into valuable chemicals and fuels. A growing body of research now focuses on integrating capture and conversion into unified systems, eliminating energy-intensive intermediate steps like compression and transportation. These integrated carbon capture and conversion/utilization (ICCC/ICCU) technologies have gained significant attention as promising strategies for sustainable carbon management. By bridging the gap between CO₂ separation and reuse, these sustainable technologies are poised to play a transformative role in the transition to a low-carbon future. Full article

This follow-up study investigates the long-term environmental sustainability and remediation outcomes of the UPPER (‘Urban Productive Parks for Sustainable Urban Regeneration’-UIA04-252) project in Latina, Italy, focusing on Nature-Based Solutions (NbS) applied to urban green infrastructure. By integrating proximal and satellite-based remote sensing methodologies, the research evaluates persistent improvements in vegetation health, soil moisture dynamics, and overall environmental quality over multiple years. Building upon the initial monitoring framework, this case study incorporates updated data and refined techniques to quantify temporal changes and assess the ecological performance of NbS interventions. In more detail, ground-based data from meteo-climatic, air quality stations and remote satellite data from the Sentinel-2 mission are adopted. Ground-based measurements such as temperature, humidity, radiation, rainfall intensity, PM10 and PM2.5 are carried out to monitor the overall environmental quality. Updated satellite imagery from Sentinel-2 is analyzed using advanced band ratio indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI) and the Normalized Difference Moisture Index (NDMI). Comparative temporal analysis revealed consistent enhancements in vegetation health, with NDVI values significantly exceeding baseline levels (NDVI 2022–2024: +0.096, p = 0.024), demonstrating successful vegetation establishment with larger gains in green areas (+27.0%) than parking retrofits (+11.4%, p = 0.041). However, concurrent NDWI decline (−0.066, p = 0.063) indicates increased vegetation water stress despite irrigation infrastructure. NDMI improvements (+0.098, p = 0.016) suggest physiological adaptation through stomatal regulation. Principal Component Analysis (PCA) of meteo-climatic variables reveals temperature as the dominant environmental driver (PC2 loadings > 0.8), with municipality-wide NDVI-temperature correlations of r = −0.87. These multi-scale findings validate sustained NbS effectiveness in enhancing vegetation density and ecosystem services, yet simultaneously expose critical water-limitation trade-offs in Mediterranean semi-arid contexts, necessitating adaptive irrigation management and continued monitoring for long-term urban climate resilience. The integrated monitoring approach underscores the critical role of continuous, multi-scale assessment in ensuring long-term success and adaptive management of NbS-based interventions. Full article

To align with disaster monitoring and sustainable risk assessment, the low-carbon transition of fisheries necessitates comprehensive carbon emission management throughout the supply chain. As China advances supply-side structural reform, transitioning from traditional to low-carbon fisheries is vital for the green development of the industry and its associated sectors. This study employs input–output models and LMDI decomposition to examine the trends and drivers of embodied carbon emissions within China’s fishery production system from 2010 to 2019. By constructing a cross-sectoral full-emission accounting system, the research calculates total direct and indirect emissions, exploring how accounting scopes influence regional responsibility and reduction strategies. Empirical results indicate that while China’s aquatic trade and processing have steadily developed, the sector remains dominated by low-value-added primary products. This structure highlights vast potential for deep processing development amidst shifting global dietary habits. Factor decomposition reveals that economic and technological development are the primary drivers of carbon emissions. Notably, technological progress within fisheries emerges as the most significant factor, playing a pivotal role in both driving and potentially mitigating emissions. Consequently, to effectively lower carbon intensity, the study concludes that restructuring the fishery industry is crucial. Promoting low-carbon development and enhancing the R&D of green technologies are essential strategies to navigate the dual challenges of industrial upgrading and environmental protection. Full article

Respiratory diseases pose a significant threat to intensive pig farming, and cough recognition serves as a key indicator for early intervention. However, its practical application is constrained by the scarcity of labeled samples and the complex acoustic conditions of farm environments. To address these challenges, this study proposes a lightweight pig cough recognition method based on a pre-trained model. By freezing the backbone of a pre-trained audio neural network and fine-tuning only the classifier, our approach achieves effective knowledge transfer and domain adaptation with very limited data. We further enhance the model’s ability to capture temporal–spectral features of coughs through a time–frequency dual-stream module. On a dataset consisting of 107 cough events and 590 environmental noise clips, the proposed method achieved an accuracy of 94.59% and an F1-score of 92.86%, significantly outperforming several traditional machine learning and deep learning baseline models. Ablation studies validated the effectiveness of each component, with the model attaining a mean accuracy of 96.99% in cross-validation and demonstrating good calibration. The results indicate that our framework can achieve high-accuracy and well-generalized pig cough recognition under small-sample conditions. The main contribution of this work lies in proposing a lightweight fine-tuning paradigm for small-sample audio recognition in agricultural settings, offering a reliable technical solution for early warning of respiratory diseases on farms. It also highlights the potential of transfer learning in resource-limited scenarios. Full article

Floods and wildfires are two extreme environmental events with significant yet different impacts on soil health and on two particularly important soil pollutants, heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs), which are directly associated with ishytoxic properties and their ability to enter the food chain. The present study includes a methodological approach that was based on a literature review of published studies conducted worldwide regarding these two phenomena. The main forms of both pollutants, their possible sources and inevitable deposition onto the soil surface, along with their behavior–transport–mobility, and their residence time in soil were investigated. Furthermore, the changes that both HMs and PAHs induce in the physicochemical properties of post-flood and post-fire soils (in soil pH, Cation Exchange Capacity (CEC), organic matter content, porosity, mineralogical alterations, etc.), are investigated after a literature review of various case studies. Wildfires, in contrast to floods, can more easily remove large quantities of heavy metals into the soil ecosystem, most likely due to the intense erosion they cause. At the same time, floods appear to significantly burden soils with PAHs. In wildfires, the largest mean increases were observed for Mn (386%), Zn (300%), and Cu (202%). In floods, Pb showed the highest mean increase (534%), with Cd also rising substantially (236%). Regarding total PAHs, mean post-event concentrations reached 482.3 μg/kg after wildfires, compared to 4384 μg/kg after floods. Changes in the structure and chemical composition of flooded and burned soils may also affect the mobility and bioavailability of the pollutants under study. Overall, these two phenomena significantly alter soil quality, affecting both ecological processes and potential health impacts. Full article

Rapid, sensitive, and environmentally sustainable spectrophotometric methods for the determination of nitrite (${{\mathrm{N}\mathrm{O}}_2}^{-}$) in environmental specimens are proposed. The presented procedures are grounded in the diazotization of sulphathiazole (STZ), followed by coupling with rhodanine (RDN) or 7-hydroxycoumarin (7-HC) in an alkaline medium, and the results were studied. This reaction gave an intense soluble red color at 504 nm and a pale red color at 525 nm for RDN and 7-HC, respectively. The conditions producing the maximum performance and other important analytical criteria in relation to the proposed procedures were investigated to enhance their sensitivity. Beer’s law was abided by for ${{\mathrm{N}\mathrm{O}}_2}^{-}$ over the concentration ranges of 0.08–2.0 µg mL⁻¹ and 0.04–2.4 µg mL⁻¹ using RDN and 7-HC, respectively. The lower limit of detection (LLOD), lower limit of quantification (LLOQ), molar absorptivity (ε), and Sandell’s sensitivity were calculated as follows: 0.0303 µg mL⁻¹, 0.0918 µg mL⁻¹, 4.20 × 10⁴ L mol⁻¹ cm⁻¹, and 1.63 × 10⁻⁶ µg cm⁻² (in the case of RDN); and 0.0387 µg mL⁻¹, 0.1172 µg mL⁻¹, 6.90 × 10⁴ L mol⁻¹ cm⁻¹, and 1.00 × 10⁻⁶ µg cm⁻² (in case of 7-HC). Furthermore, the ecological implications were assessed using three green assessment methodologies: Analytical Eco-Scale (ESA), Analytical GREEnness metric (AGREE), and Green Analytical Procedure Index (GAPI). Thus, our proposed procedures are fully validated and implemented in order to carry out ${{\mathrm{N}\mathrm{O}}_2}^{-}$ quantification in the selected ecological samples (water and soil samples). Full article

Climate change and increasing groundwater demand underscore the urgency of sustainable water resource planning. Managed Aquifer Recharge (MAR) represents a promising strategy, yet its implementation depends on accurately identifying locations suited for specific MAR techniques. This study presents a GIS-based methodology developed under the DEEPWATER-CE project for identifying suitable locations for six MAR techniques in Central Europe. The methodology integrates environmental, hydrological, and land use criteria in a two-stage approach: an initial screening to delineate potentially suitable areas, followed by a detailed classification of those areas into high, moderate, and low suitability categories. The approach was tested in the Polish part of the Dunajec River catchment (4835 km²), revealing that river or lake bank filtration, infiltration ditches, and underground dams are the most viable MAR options, suitable for 12.6%, 13%, and 15.6% of the catchment area, respectively. A focused analysis within the Tarnów agglomeration, identified as highly vulnerable to climate change and with intensive groundwater use, demonstrated that 83–87% of the area is moderately suitable for infiltration ditches and riverbank filtration techniques. This decision-support tool can inform water managers and planners regarding the best locations for implementing MAR to enhance aquifer resilience, ensure water availability, and mitigate the impacts of extreme weather events. The methodology is transferable to other regions facing similar hydroclimatic challenges. Full article

This paper presents an energy-focused analysis of structural materials used in passenger cars, with a particular emphasis on the impact of construction materials on total energy consumption throughout the vehicle’s life cycle. Three production periods (2000, 2010, and 2020) were analysed for B- and C-segment vehicles using inventory data from Life Cycle Assessment databases, the scientific literature, and certified dismantling stations. The embodied energy of key material groups—steel, aluminium, plastics, and other materials—was calculated based on representative mass shares and material-specific energy intensity indicators. The computational model was supplemented with statistical analyses (Kolmogorov–Smirnov test, Levene’s test, ANOVA, and Tukey’s post hoc tests) to verify whether observed temporal trends were statistically significant. The results indicate that total material-related energy inputs increased from approximately 57 GJ to 64 GJ per vehicle, while the specific energy intensity per kilogram decreased from 47.6 MJ/kg to 42.6 MJ/kg. Aluminium exhibited a pronounced reduction in unit energy intensity due to the rising share of secondary materials, whereas plastics and other materials showed substantial increases. Steel remained the largest contributor in absolute terms because of its dominant mass share. This study highlights the growing importance of the production phase in the environmental balance of modern vehicles, particularly in the context of the rising share of lightweight materials and recycling-based components. The results emphasise the importance of energy-efficient material use and underscore the significance of material selection and recycling strategies in reducing energy demand within the automotive sector. Full article

To investigate the impacts of the continuous application of urban sewage sludge on heavy metal pollution risks in wine grape orchards, this study conducted a five-year field plot experiment using wine grapes as the test crop. The experimental design included three sludge application rates and a control without sludge application. Soil physicochemical properties, the single-factor and integrated pollution indices (PI and NIPI) of heavy metals, potential ecological risk indices (EI and RI), and the safe application duration of sludge were analyzed. The results suggest that sludge application significantly increased soil organic matter, total nitrogen, total phosphorus, and available phosphorus by 39.99–46.56%, 59.37–73.69%, 83.57–143.19%, and 88.79%, respectively, while reducing soil bulk density by 8.70–27.92%. The PI and EI of Cd exhibited significant linear increases with the duration of sludge application, with annual increments of 0.010 and 0.31, respectively. Hg was influenced by both the application rates and duration, with annual increments of 0.013 and 0.52 for the PI and EI, respectively. These two elements collectively drove overall increases of 7.31–24.96% in NIPI and 32.51–59.90% in RI, with mean annual increases of 0.0064 and 0.84, respectively. In contrast, Cr, Pb, and As showed no significant changes. Based on the calculated environmental capacities of Cd and Hg, the safe application durations were estimated to be 46.99–126.93 and 48.58–131.21 years, respectively. These results demonstrate that under the current application intensity, sludge can improve soil fertility in the short term with controllable ecological risks. However, considering their potential environmental risks, the continuous accumulation of Cd and Hg necessitates vigilance. Full article