Search Results (704)

Calorific value and moisture content are the key indices to evaluate Caragana pellet fuel’s quality and combustion characteristics. Calorific value is the key index to measure the energy released by energy plants during combustion, which determines energy utilization efficiency. But at present, the determination of solid fuel is still carried out in the laboratory by oxygen bomb calorimetry. This has seriously hindered the ability of large-scale, rapid detection of fuel particles in industrial production lines. In response to this technical challenge, this study proposes using hyperspectral imaging technology combined with various chemometric methods to establish quantitative models for determining moisture content and calorific value in Caragana korshinskii fuel. A hyperspectral imaging system was used to capture the spectral data in the 935–1720 nm range of 152 samples from multiple regions in Inner Mongolia Autonomous Region. For water content and calorific value, three quantitative detection models, partial least squares regression (PLSR), random forest regression (RFR), and extreme learning machine (ELM), respectively, were established, and Monte Carlo cross-validation (MCCV) was chosen to remove outliers from the raw spectral data to improve the model accuracy. Four preprocessing methods were used to preprocess the spectral data, with standard normal variate (SNV) preprocessing performing best on the quantitative moisture content detection model and Savitzky–Golay (SG) preprocessing performing best on the calorific value detection method. Meanwhile, to improve the prediction accuracy of the model to reduce the redundant wavelength data, we chose four feature extraction methods, competitive adaptive reweighted sampling (CARS), successive pojections algorithm (SPA), genetic algorithm (GA), iteratively retains informative variables (IRIV), and combined the three models to build a quantitative detection model for the characteristic wavelengths of moisture content and calorific value of Caragana korshinskii fuel. Finally, a comprehensive comparison of the modeling effectiveness of all methods was carried out, and the SNV-IRIV-PLSR modeling combination was the best for water content prediction, with its prediction set determination coefficient $\left(R_P^2\right)$, root mean square error of prediction (RMSEP), and relative percentage deviation (RPD) of 0.9693, 0.2358, and 5.6792, respectively. At the same time, the moisture content distribution map of Caragana fuel particles is established by using this model. The SG-CARS-RFR modeling combination was the best for calorific value prediction, with its $R_P^2$, RMSEP, and RPD of 0.8037, 0.3219, and 2.2864, respectively. This study provides an innovative technical solution for Caragana fuel particles’ value and quality assessment. Full article

Salinity intrusion is a growing threat to freshwater resources, particularly in low-lying coastal and estuarine regions, necessitating the development of effective early warning systems (EWS) to support timely mitigation. Although various water quality monitoring technologies exist, many face challenges related to long-term sustainability, ongoing maintenance, and accessibility for local users. This study introduces a novel hybrid real-time salinity intrusion early warning system that uniquely integrates fixed and portable monitoring technologies with strong community participation—an approach not yet widely applied in comparable urban-adjacent delta regions. Unlike traditional systems, this model emphasizes local ownership, flexible data collection, and system scalability in resource-constrained environments. This study presents a real-time salinity intrusion early warning system for Bang Kachao, Thailand, combining eight fixed monitoring stations and 20 portable salinity measurement devices. The system was developed in response to community needs, with local input guiding both station placement and the design of mobile measurement tools. By integrating fixed stations for continuous, high-resolution data collection with portable devices for flexible, on-demand monitoring, the system achieves comprehensive spatial coverage and adaptability. A core innovation lies in its emphasis on community participation, enabling villagers to actively engage in monitoring and decision-making. The use of IoT-based sensors, Remote Telemetry Units (RTUs), and cloud-based data platforms further enhances system reliability, efficiency, and accessibility. Automated alerts are issued when salinity thresholds are exceeded, supporting timely interventions. Field deployment and testing over a seven-month period confirmed the system’s effectiveness, with fixed stations achieving 90.5% accuracy and portable devices 88.7% accuracy in detecting salinity intrusions. These results underscore the feasibility and value of a hybrid, community-driven monitoring approach for protecting freshwater resources and building local resilience in vulnerable regions. Full article

It is well established that effective management and restoration of freshwater ecosystems is often limited by the availability of reusable data. Although numerous public, private, and nonprofit organizations collect data from freshwater ecosystems, much of what is collected remains inaccessible or unusable by Rights holders and end users (including researchers, practitioners, community members, and decision-makers). In Canada, the federal government plans to improve freshwater data sharing practices through the newly formed Canada Water Agency, which is currently drafting a National Freshwater Data Strategy. Our study aimed to support these efforts by synthesizing insights from the technology sector, where data management and sharing practices are more mature. We interviewed 12 experts from the technology sector, asking them for advice on how to improve data sharing practices in the freshwater science sector. Using a Reflexive Thematic Analysis of participants’ responses to semi-structured interview questions, we identified nine broad recommendations. Recommendations centred on motivating open data sharing, promoting data reuse through data licences, training and skill building, and developing standards and digital solutions that enable data discovery, accessibility, interoperability, and reuse. These recommendations can support the numerous initiatives that are working to improve access to high-quality freshwater data and help address the pressing crisis of global freshwater ecosystem degradation. Full article

During the operation of structures, the components and materials from which they are made are exposed to various environmental, technological, and operational impacts. In this context, the use of a modified water-dispersion composition containing finely dispersed fillers with enhanced protective and performance characteristics proves to be effective. This article examines the development of a paint-and-coating composition using hollow glass microspheres and modified diatomite as finely dispersed fillers. The influence of technological factors on the properties of coating materials based on a synthesized acrylic dispersion and fillers—such as modified diatomite and hollow glass microspheres ranging from 20 to 100 μm in size with a bulk density of 0.107–0.252 g/cm³—is analyzed. The optimal formulation of the coating materials was determined to ensure the required coating quality. Experimental results demonstrate the improved strength and hardness of the coating due to the use of acrylic dispersion obtained through an emulsifier-free method and modifiers in the form of finely dispersed fillers. It has been established that the resulting samples also exhibit high adhesion to mineral and metallic substrates, along with excellent corrosion resistance. Moreover, the incorporation of acrylic dispersion contributes to increased elasticity of the coating, resulting in improved resistance to washing and abrasion. The developed protective material can be applied to a variety of surfaces, including walls, ceilings, and roofs of buildings and structures, pipelines, and many other applications. Thus, modified water-dispersion compositions based on synthesized acrylic dispersion showed the following results: resistance to sticking—5, which is the best; chemical resistance and gloss level with standard single-phase acrylic dispersion—no destruction or change in gloss. The adhesion of coatings cured under natural conditions and under the influence of UV radiation was 1 point. The developed formulations for obtaining water-dispersion paint and varnish compositions based on synthesized polymer dispersions, activated diatomite, and hollow glass microspheres, meet all the regulatory requirements for paint and varnish materials in terms of performance, and in terms of economic indicators, the cost of 1 kg of paint is 30% lower than the standard. Full article

Indoor radon constitutes a public health issue in various regions across the United States as the second leading cause of lung cancer following tobacco smoke. The U.S. Environmental Protection Agency advises radon mitigation interventions for residential buildings with indoor radon concentrations exceeding the threshold level of 4 pCi/L. Despite considerable research assessing the technical effectiveness of radon mitigation systems, there remains a gap in understanding their broader influence on occupant behavior and preferences in residential design. This study aims to investigate the impact of residing in radon-mitigated homes within the Commonwealth of Kentucky—an area known for elevated radon concentrations—on occupants’ preferences regarding healthy home design attributes. The objectives of this research are twofold: firstly to determine if living in radon-mitigated homes enhances occupant awareness and consequently influences their preferences toward health-related home attributes and secondly to quantitatively evaluate and compare the relative significance homeowners assign to health-related attributes such as indoor air quality, thermal comfort, and water quality relative to conventional attributes including home size, architectural style, and neighborhood quality. The overarching purpose is to explore the potential role radon mitigation initiatives may play in motivating occupants towards healthier home construction and renovation practices. Using choice-based conjoint (CBC) analysis, this paper compares preferences reported by homeowners from radon-mitigated homes against those from non-mitigated homes. While the findings suggest a relationship between radon mitigation and increased preference for indoor air quality, the cross-sectional design limits causal interpretation, and the possibility of reverse causation—where health-conscious individuals are more likely to seek mitigation—must be considered. The results provide novel insights into how radon mitigation efforts might effectively influence occupant priorities towards integrating healthier design elements in residential environments. Full article

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

This research focuses on improving the characteristics of recycled concrete and utilizing solid waste resources through the combination of industrial waste pre-impregnation and the carbonation process. A novel pre-impregnation–carbonation aggregate method is proposed to increase the content of carbonatable components in the surface-bonded mortar of recycled coarse aggregate by pre-impregnating it with carbide slag slurry (CSS). This approach enhances the subsequent carbonation effect and thus the properties of recycled aggregates. The experimental results showed that the method significantly improved the water absorption, crushing value, and apparent density of the recycled aggregate. Additionally, it enhanced the compressive strength, split tensile strength, and flexural strength of the recycled concrete produced using the aggregate improved by this method. Microanalysis revealed that CO₂ reacts with calcium hydroxide and hydrated calcium silicate (C-S-H) to produce calcite-type calcium carbonate and amorphous silica gel. These reaction products fill microcracks and pores on the aggregate and densify the aggregate–paste interfacial transition zone (ITZ), thereby improving the properties of recycled concrete. This study presents a practical approach for the high-value utilization of construction waste and the production of low-carbon building materials by enhancing the quality of recycled concrete. Additionally, carbon sequestration demonstrates broad promise for engineering applications. Full article

Ecological security patterns (ESPs) are fundamental to safeguarding regional ecological integrity and enhancing human well-being. Consequently, research on conservation and restoration in critical regions is vital for ensuring ecological security and optimizing territorial ecological spatial configurations. Focusing on the Henan section of the Yellow River Basin, this study established the regional ESP and conservation–restoration framework through an integrated approach: (1) assessing four key ecosystem services—soil conservation, water retention, carbon sequestration, and habitat quality; (2) identifying ecological sources based on ecosystem service importance classification; (3) calculating a comprehensive resistance surface using the entropy weight method, incorporating key factors (land cover type, NDVI, topographic relief, and slope); (4) delineating ecological corridors and nodes using Linkage Mapper and the minimum cumulative resistance (MCR) theory; and (5) integrating ecological functional zoning to synthesize the final spatial conservation and restoration strategy. Key findings reveal: (1) 20 ecological sources, totaling 8947 km² (20.9% of the study area), and 43 ecological corridors, spanning 778.24 km, were delineated within the basin. Nineteen ecological barriers (predominantly located in farmland, bare land, construction land, and low-coverage grassland) and twenty-one ecological pinch points (primarily clustered in forestland, grassland, water bodies, and wetlands) were identified. Collectively, these elements form the Henan section’s Ecological Security Pattern (ESP), integrating source areas, a corridor network, and key regional nodes for ecological conservation and restoration. (2) Building upon the ESP and the ecological baseline, and informed by ecological functional zoning, we identified a spatial framework for conservation and restoration characterized by “one axis, two cores, and multiple zones”. Tailored conservation and restoration strategies were subsequently proposed. This study provides critical data support for reconciling ecological security and economic development in the Henan Yellow River Basin, offering a scientific foundation and practical guidance for regional territorial spatial ecological restoration planning and implementation. Full article

The efficient and precise identification of urban slums is a significant challenge for urban planning and sustainable development, as their morphological diversity and complex spatial distribution make it difficult to use traditional remote sensing inversion methods. Current deep learning (DL) methods mainly face challenges such as limited receptive fields and insufficient sensitivity to spatial locations when integrating multi-source remote sensing data, and high-quality datasets that integrate multi-spectral and geoscientific indicators to support them are scarce. In response to these issues, this study proposes a DL model (coordinate-attentive U²-DeepLab network [CAU²DNet]) that integrates multi-source remote sensing data. The model integrates the multi-scale feature extraction capability of U²-Net with the global receptive field advantage of DeepLabV3+ through a dual-branch architecture. Thereafter, the spatial semantic perception capability is enhanced by introducing the CoordAttention mechanism, and ConvNextV2 is adopted to optimize the backbone network of the DeepLabV3+ branch, thereby improving the modeling capability of low-resolution geoscientific features. The two branches adopt a decision-level fusion mechanism for feature fusion, which means that the results of each are weighted and summed using learnable weights to obtain the final output feature map. Furthermore, this study constructs the São Paulo slums dataset for model training due to the lack of a multi-spectral slum dataset. This dataset covers 7978 samples of 512 × 512 pixels, integrating high-resolution RGB images, Normalized Difference Vegetation Index (NDVI)/Modified Normalized Difference Water Index (MNDWI) geoscientific indicators, and POI infrastructure data, which can significantly enrich multi-source slum remote sensing data. Experiments have shown that CAU²DNet achieves an intersection over union (IoU) of 0.6372 and an F1 score of 77.97% on the São Paulo slums dataset, indicating a significant improvement in accuracy over the baseline model. The ablation experiments verify that the improvements made in this study have resulted in a 16.12% increase in precision. Moreover, CAU²DNet also achieved the best results in all metrics during the cross-domain testing on the WHU building dataset, further confirming the model’s generalizability. Full article

Research on the supply–demand relationships of ecosystem services (ESs) in alpine pastoral regions remains relatively scarce, yet it is crucial for regional ecological management and sustainable development. This study focuses on the Sanjiangyuan Region, a typical alpine pastoral area and significant ecological barrier, to quantitatively assess the supply–demand dynamics of key ESs and their spatial heterogeneity from 2000 to 2020. It further aims to elucidate the underlying driving mechanisms, thereby providing a scientific basis for optimizing regional ecological management. Four key ES indicators were selected: water yield (WY), grass yield (GY), soil conservation (SC), and habitat quality (HQ). ES supply and demand were quantified using an integrated approach incorporating the InVEST model, the Revised Universal Soil Loss Equation (RUSLE), and spatial analysis techniques. Building on this, the spatial patterns and temporal evolution characteristics of ES supply–demand relationships were analyzed. Subsequently, the Geographic Detector Model (GDM) and Geographically and Temporally Weighted Regression (GTWR) model were employed to identify key drivers influencing changes in the comprehensive ES supply–demand ratio. The results revealed the following: (1) Spatial Patterns: Overall ES supply capacity exhibited a spatial differentiation characterized by “higher values in the southeast and lower values in the northwest.” Areas of high ES demand were primarily concentrated in the densely populated eastern region. WY, SC, and HQ generally exhibited a surplus state, whereas GY showed supply falling short of demand in the densely populated eastern areas. (2) Temporal Dynamics: Between 2000 and 2020, the supply–demand ratios of WY and SC displayed a fluctuating downward trend. The HQ ratio remained relatively stable, while the GY ratio showed a significant and continuous upward trend, indicating positive outcomes from regional grass–livestock balance policies. (3) Driving Mechanisms: Climate and natural factors were the dominant drivers of changes in the ES supply–demand ratio. Analysis using the Geographical Detector’s q-statistic identified fractional vegetation cover (FVC, q = 0.72), annual precipitation (PR, q = 0.63), and human disturbance intensity (HD, q = 0.38) as the top three most influential factors. This study systematically reveals the spatial heterogeneity characteristics, dynamic evolution patterns, and core driving mechanisms of ES supply and demand in an alpine pastoral region, addressing a significant research gap. The findings not only provide a reference for ES supply–demand assessment in similar regions regarding indicator selection and methodology but also offer direct scientific support for precisely identifying priority areas for ecological conservation and restoration, optimizing grass–livestock balance management, and enhancing ecosystem sustainability within the Sanjiangyuan Region. Full article

This study aimed to investigate phytoplankton dynamics and water quality at three drinking water intakes (Duchang, Hukou, and Xingzi) in Poyang Lake through monthly monitoring from May 2023 to April 2024. The results showed that a total of 168 species of phytoplankton were identified in nine phyla, and there were significant spatial and temporal differences in the abundance of phytoplankton at the three waterworks intakes, with a spatial trend of annual mean values of Duchang > Xingzi > Hukou and a seasonal trend of summer and autumn > spring and winter. The dominant species of phytoplankton in the waterworks intakes of the three waterworks also showed obvious spatial and temporal differences. Cyanobacteria (particularly Pseudanabaena sp. and Microcystis sp.) dominated the phytoplankton communities during summer and autumn, demonstrating significant water degradation potential. In contrast, Cyclotella sp. prevailed in winter and spring assemblages. Based on water quality assessments at the three intake sites, the Duchang County intake exhibited year-round mild eutrophication with persistent mild cyanobacterial blooms (June–October), while the other two sites maintained no obvious bloom conditions. Further analyzing the toxic/odor-producing algal strains, the numbers of dominant species of Pseudanabaena sp. and Microcystis sp. in June–October in Duchang County both exceeded 1.0 × 10⁷ cells·L⁻¹. It is necessary to focus on their release of ATX-a (ichthyotoxin-a), 2MIB (2-Methylisoborneol), MCs (microcystins), etc., to ensure the safety of the water supply at the intake. Building upon these findings, we propose a generalized algal monitoring framework, encompassing three operational pillars: (1) key monitoring area identification, (2) high-risk period determination, and (3) harmful algal warnings. Each of these is substantiated by our empirical observations in Poyang Lake. Full article

The “Green Riyadh” project in Saudi Arabia represents a major initiative to enhance urban sustainability by expanding green spaces throughout Riyadh City. The initiative aims to improve air and water quality, increase tree and plant coverage, and promote environmental well-being for city residents. However, accurately assessing the extent and quality of green spaces remains a significant challenge. Current methods for evaluating green areas and measuring tree density are limited in precision and reliability, preventing effective monitoring and planning. This paper proposes an innovative solution that leverages live satellite imagery and advanced deep learning techniques to address these challenges. We collect extensive satellite data from two sources and then build two separate analytical pipelines. These pipelines process high-resolution satellite imagery to identify trees and measure green density in vegetated areas. The experimental results show significant improvements in accuracy and efficiency, with the YOLOv11 model achieving a mAP@50 of 95.4%, precision of 94.6%, and recall of 90.2%. These findings offer a scalable and reliable alternative to traditional methods, enabling comprehensive progress evaluation and facilitating informed decision-making for urban planning. The proposed methodology not only supports the objectives of the “Green Riyadh” project but also sets a benchmark for green space evaluation that can be adopted by cities worldwide. Full article

To enhance fire safety in converter stations, this study focuses on detecting abnormal data and potential faults in fire protection Internet of Things (IoT) devices, which are networked sensors monitoring parameters such as temperature, smoke, and water tank levels. A data quality evaluation model is proposed, covering both validity and timeliness. For validity assessment, a transformer-based time series reconstruction method is used, and anomaly thresholds are determined using the peaks over threshold (POT) approach from extreme value theory. The experimental results show that this method identifies anomalies in fire telemetry data more accurately than traditional models. Based on the objective evaluation method and clustering, an interpretable health assessment model is developed. Compared with conventional distance-based approaches, the proposed method better captures differences between features and more effectively evaluates the reliability of fire protection systems. This work contributes to improving early fire risk detection and building more reliable fire monitoring and emergency response systems. Full article

Drinking Water Safety Plans (DWSP) in buildings serve to identify health hazards associated with the drinking water system. Sanitation Safety Plans (SSP) fulfill the same purpose for the sewage system. Water Safety Plans (WSP) include DWSPs, SSPs, and water systems like gray water and firefighting water. WSPs are based on a high-quality description of the water systems. This paper presents a new methodology for describing water systems. In contrast to previous approaches, the system description begins at the point where the water is consumed. These points of use are described using ecomaps, which are then supplemented with information about the pipe network. This approach makes it possible to fulfill four relevant premises: (1) the system description includes all essential parts of the drinking water installation, (2) the system description is possible with usual equipment, (3) the system description can be carried out with the least possible additional personnel costs, and (4) the system description is controllable, versionable, changeable, and forgery-proof. The ecomaps created in this way are suitable for the next step within the WSP framework, namely hazard and risk assessment. In addition, the ecomaps can be integrated into a quality, occupational safety, or environmental management system. Aspects of water security can be added to enable the ecomaps to be used as the basis for a total integrated water management system. Full article

Achieving both indoor environmental quality (IEQ) and energy efficiency in school buildings remains a challenge, particularly in older structures where renovation strategies often lack site-specific validation. This study evaluates the impact of energy retrofits on a 1970s primary school in France by integrating in situ measurements with a validated numerical model for forecasting energy demand and IEQ. Temperature, humidity, and CO₂ levels were recorded before and after renovations, which included insulation upgrades and an air handling unit replacement. Results indicate significant improvements in winter thermal comfort (PPD < 20%) with a reduced heating water temperature (65 °C to 55 °C) and stable indoor air quality (CO₂ < 800 ppm), without the need for window ventilation. Night-flushing ventilation proved effective in mitigating overheating by shifting peak temperatures outside school hours, contributing to enhanced thermal regulation. Long-term energy consumption analysis (2019–2022) revealed substantial reductions in gas and electricity use, 15% and 29% of energy saving for electricity and gas, supporting the effectiveness of the applied renovation strategies. However, summer overheating (up to 30 °C) persisted, particularly in south-facing upper floors with extensive glazing, underscoring the need for additional optimization in solar gain management and heating control. By providing empirical validation of renovation outcomes, this study bridges the gap between theoretical predictions and real-world effectiveness, offering a data-driven framework for enhancing IEQ and energy performance in aging school infrastructure. Full article