Search Results (2,823)

With the increasing awareness of energy consumption issues, there has been a growing emphasis on energy-saving retrofits for central air-conditioning systems that constitute a significant proportion of energy consumption in buildings. Efficient energy utilization can be achieved by optimizing the modeling of the equipment within the chiller plants of central air-conditioning systems. Traditional modeling approaches have been static and have focused on modeling within narrow time frames when a certain amount of equipment operating data has accumulated, thus prioritizing the precision of the model itself while overlooking the fact that energy-saving retrofits are a long-term process. This study proposes a modeling scheme for the equipment within chiller plants throughout the energy-saving retrofit process. Based on the differences in the amount of available operating data for the equipment and the progress of retrofit implementation, the retrofit process was divided into three stages, each employing different modeling techniques and ensuring smooth transitions between the stages. The equipment within the chiller plants is categorized into two types based on the clarity of their operating characteristics, and two modeling schemes are proposed accordingly. Based on the proposed modeling scheme, chillers and chilled-water pumps were selected to represent the two types of equipment. Real operating data from actual retrofit projects was used to model the equipment and evaluate the accuracy of the model predictions. The results indicate that the models established by the proposed modeling scheme exhibit good accuracy at each stage of the retrofit, with the coefficients of variation (CV) remaining below 6.88%. Furthermore, the prediction accuracy improved as the retrofitting process progressed. The modeling scheme performs better on equipment with simpler and clearer operating characteristics, with a CV as low as 0.67% during normal operation stages. This underscores the potential application of the proposed modeling scheme throughout the energy-saving retrofit process and provides a model foundation for the subsequent optimization of the refrigeration system. Full article

Accurate estimation of groundwater levels in river basins is essential for effective water resource planning. Innovations in deep learning and artificial intelligence (AI) have been introduced into this field to enhance the accuracy of long-term groundwater level estimation. This study employs the Transformer deep learning model to estimate groundwater levels, with a benchmark comparison against the long short-term memory (LSTM) model. These models were applied to estimate groundwater levels in the Yellow River Basin, where approximately 1100 monitoring wells are located. Monthly average groundwater level data from the period 2018–2023 were collected from these wells. The two models were used to estimate groundwater levels for the period 2003–2017 by incorporating remote sensing information. The Transformer model was enhanced to simultaneously capture features from both historical temporal data and surrounding spatial data, while automatically enhancing key features, effectively improving estimation accuracy and robustness. At the basin-averaged scale, the enhanced Transformer model outperformed the LSTM model: R² increased by approximately 17.5%, while RMSE and MAE decreased by approximately 12.4% and 10.9%, respectively. The proportion of poorly predicted samples decreased by an average of approximately 12.1%. The estimation model established in this study contributes to improving the quantitative analysis capability of long-term groundwater level variations in the Yellow River Basin. This could be helpful for water resource development planning in this densely populated region and likely has broad applicability in other river basins. Full article

As a typical grain base with a dense population and high-level urbanization, the North China Plain (NCP) faces a serious threat to its sustainable development due to water shortage. Surface water area (SWA) is a key indicator for continuously measuring the trends of regional water resources and assessing their current status. Therefore, a deep understanding of its changing patterns and driving forces is essential for achieving the sustainable management of water resources. In this study, we examined the interannual variability and trends of SWA in the NCP from 1990 to 2023 using annual 30 m water body maps generated from all available Landsat imagery, a robust water mapping algorithm, and the cloud computing platform Google Earth Engine (GEE). The results showed that the SWA in the NCP has significantly increased over the past three decades. The continuous emergence of artificial reservoirs and urban lakes, along with the booming aquaculture industry, are the main factors driving the growth of SWA. Consequently, the expansion of artificial water bodies resulted in a significant increase in water evaporation (0.16 km³/yr). Moreover, the proportion of water evaporation to regional evapotranspiration (ET) gradually increased (0–0.7%/yr), indicating that the contribution of water evaporation from artificial water bodies to ET is becoming increasingly prominent. Therefore, it can be concluded that the ever-expanding artificial water bodies have become a new hidden danger affecting the water security of the NCP through evaporative loss and deserve close attention. This study not only provides us with a new perspective for deeply understanding the current status of water resources security in the NCP but also provides a typical case with great reference value for the analysis of water resources changes in other similar regions. Full article

Concrete mix design plays a pivotal role in ensuring the mechanical performance, durability, and sustainability of construction projects. However, the nonlinear interactions among the mix components challenge traditional approaches in predicting compressive strength and optimizing proportions. This study presents a two-stage hybrid framework that integrates deep learning with reinforcement learning to overcome these limitations. First, a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model was developed to capture spatial–temporal patterns from a dataset of 1030 historical concrete samples. The extracted features were enhanced using an eXtreme Gradient Boosting (XGBoost) meta-model to improve generalizability and noise resistance. Then, a Dueling Double Deep Q-Network (Dueling DDQN) agent was used to iteratively identify optimal mix ratios that maximize the predicted compressive strength. The proposed framework outperformed ten benchmark models, achieving an MAE of 2.97, RMSE of 4.08, and R² of 0.94. Feature attribution methods—including SHapley Additive exPlanations (SHAP), Elasticity-Based Feature Importance (EFI), and Permutation Feature Importance (PFI)—highlighted the dominant influence of cement content and curing age, as well as revealing non-intuitive effects such as the compensatory role of superplasticizers in low-water mixtures. These findings demonstrate the potential of the proposed approach to support intelligent concrete mix design and real-time optimization in smart construction environments. Full article

To ensure water source security and sustainability of the national major strategic project “South-to-North Water Diversion”, this study aims to evaluate the spatio-temporal evolution characteristics of the ecosystem service value (ESV) in its water source area from 2002 to 2022. This study reveals its changing trends and main influencing factors, and thereby provides scientific support for the ecological protection and management of the water source area. Quantitative assessment of the ESV of the region was carried out using the Equivalence Factor Method (EFM), aiming to provide scientific support for ecological protection and resource management decision-making. In the past 20 years, the ESV has shown an upward trend year by year, increasing by 96%. The regions with the highest ESV were Garzê Prefecture and Aba Prefecture, which increased by 130.3% and 60.6%, respectively. The ESV of Xinlong county, Danba county, Rangtang county, and Daofu county increased 4.8 times, 1.5 times, 12.5 times, and 8.9 times, respectively. In the last two decades, arable land has decreased by 91%, while the proportions of bare land and water have decreased by 84% and 91%, respectively. Grassland had the largest proportion. Forests and grasslands, vital for climate regulation, water cycle management, and biodiversity conservation, have expanded by 74% and 43%, respectively. It can be seen from Moran’s I index values that the dataset as a whole showed a slight positive spatial autocorrelation, which increased from −0.041396 to 0.046377. This study reveals the changing trends in ESV and the main influencing factors, and thereby provides scientific support for the ecological protection and management of the water source area. Full article

The accumulation of end-of-life tires and the rapid increase in demolition activities pose significant environmental and waste-management challenges. The redevelopment of construction materials incorporating this waste is a potentially promising strategy for minimizing environmental impact while promoting the principles of a circular economy. This study investigates the performance of self-compacting concrete (SCC) incorporating up to 20% rubber aggregates (sand and gravel) and 40% recycled concrete aggregate (RCA) for non-structural applications. A series of tests was conducted to assess fresh and hardened properties, including flowability, compressive strength, tensile strength, flexural strength, water absorption, and density. The results indicated that increasing RCA content reduced density and compressive strength, while tensile and flexural strengths were only moderately affected. Response surface methodology (RSM), utilizing a Box–Behnken design, was employed to optimize compressive, tensile, and flexural strength responses. Statistical analysis was used to identify the optimal mix proportions, which balance the mechanical performance and sustainability of SCC with recycled components. Mixtures incorporating moderate rubber content—specifically, 5–5.5% sand rubber and 0–6% coarse rubber—and 40% recycled-concrete aggregate (RCA) achieved the highest predicted performance, with compressive strength ranging from 20.00 to 28.26 MPa, tensile strength from 2.16 to 2.85 MPa, and flexural strength reaching 5.81 MPa, making them suitable for sidewalks and walkways. Conversely, mixtures containing higher rubber proportions (5.5–20% sand rubber and 20% coarse rubber) combined with the same RCA level (40%) showed the lowest mechanical performance, with compressive strength between 5.2 and 10.08 MPa, tensile strength of 1.05–1.41 MPa, and flexural strength from 2.18 to 3.54 MPa. These findings underscore the broad performance range achievable through targeted optimization. They confirm the viability of recycled materials for producing environmentally friendly SCC in non-structural applications. Full article

This study proposes a new air treatment system that integrates dehumidification, cooling, and water recovery using a Horizontal Air–Ground Heat Exchanger (HAGHE) combined with Peltier cells. The airflow generated by a fan flows through an HAGHE until it meets a septum on which Peltier cells are placed, and then separates into two distinct streams that lap the two surfaces of the Peltier cells: one stream passes through the cold surfaces, undergoing both sensible and latent cooling with dehumidification; the other stream passes through the hot surfaces, increasing its temperature. The two treated air streams may then pass through a mixing chamber, where they are combined in the appropriate proportions to achieve the desired air supply conditions and ensure thermal comfort in the indoor environment. A Computational Fluid Dynamics (CFD) analysis was carried out to simulate the thermal interaction between the HAGHE and the surrounding soil. The simulation focused on a system installed under the subtropical climate conditions of Nairobi, Africa. The simulation results demonstrate that the HAGHE system is capable of reducing the air temperature by several degrees under typical summer conditions, with enhanced performance observed when the soil is moist. Condensation phenomena were triggered when the relative humidity of the inlet air exceeded 60%, contributing additional cooling through latent heat extraction. The proposed HAGHE–Peltier system can be easily powered by renewable energy sources and configured for stand-alone operation, making it particularly suitable for off-grid applications. Full article

The rapid urbanization process has accelerated the degradation of ecosystem services (ESs) in peri-urban rural areas of the Yangtze River Delta (YRD), leading to increasing landscape ecological risks (LERs). Establishing a scientifically grounded landscape ecological risk assessment (LERA) system and corresponding control strategies is therefore imperative. Using rural areas of Jiangning District, Nanjing as a case study, this research proposes an optimized dual-dimensional coupling assessment framework that integrates ecosystem service value (ESV) and ecological risk probability. The spatiotemporal evolution of LER in 2000, 2010, and 2020 and its key driving factors were further studied by using spatial autocorrelation analysis and geodetector methods. The results show the following: (1) From 2000 to 2020, cultivated land remained dominant, but its proportion decreased by 10.87%, while construction land increased by 26.52%, with minimal changes in other land use types. (2) The total ESV increased by CNY 1.67 × 10⁹, with regulating services accounting for over 82%, among which water bodies contributed the most. (3) LER showed an overall increasing trend, with medium- to highest-risk areas expanding by 55.37%, lowest-risk areas increasing by 10.10%, and lower-risk areas decreasing by 65.48%. (4) Key driving factors include landscape vulnerability, vegetation coverage, and ecological land connectivity, with the influence of distance to road becoming increasingly significant. This study reveals the spatiotemporal evolution characteristics of LER in typical peri-urban villages. Based on the LERA results, combined with terrain features and ecological pressure intensity, the study area was divided into three ecological management zones: ecological conservation, ecological restoration, and ecological enhancement. Corresponding zoning strategies were proposed to guide rural ecological governance and support regional sustainable development. Full article

The utilization of recycled concrete aggregate presents an effective solution for construction waste mitigation. However, concrete service in sulfate environments leads to sulfate ion retention in recycled aggregates, substantially impairing their quality and requiring modification approaches. A critical question remains whether traditional recycled aggregate modification techniques can effectively enhance the performance of these sulfate-containing recycled aggregates (SRA). Cement paste wrapping in various proportions was used in this investigation to enhance SRA. The performance of both SRA and modified aggregates was systematically assessed through measurements of apparent density, water absorption, crushing value, and microhardness. Microstructural analysis of the cement wrapping modification mechanism was conducted by scanning electron microscopy coupled with mercury intrusion porosimetry. Results revealed that internal sulfate addition decreased the crushing value and increased the water absorption of recycled aggregates, primarily due to micro-cracks formed by expansion. Additionally, the pores were occupied by erosion products, leading to a slight increase in the apparent density of aggregates. The performance of SRA was effectively enhanced by cement paste wrapping at a 0.6 water–binder ratio, whereas it was negatively impacted by a ratio of 1.0. The modifying effect became even more effective when 15% fly ash was added to the wrapping paste. Scanning electron microscopy observations revealed that the interface of SRA was predominantly composed of gypsum crystals. Cement paste wrapping greatly enhanced the original interface structure, despite a new dense interface formed in the modified aggregates. Full article

Volcanic rock is a natural mineral material which has garnered interest for its potential application in water treatment due to its unique physicochemical properties. In this study, we prepared a polysilicate aluminum chloride (PSAC) coagulant using volcanic rock which exhibited good coagulation–flocculation performance. Further investigation into the influence of synthetic parameters, such as calcination temperature, reaction time, and alkali types, on the structure and performance of a volcanic rock-derived coagulant was conducted. Techniques including Scanning Electron Microscopy, Energy-Dispersive Spectroscopy, Fourier-Transform Infrared Spectroscopy, and X-Ray Diffraction were utilized to characterize it. Also, a ferron-complexation timed spectrophotometric method was used to study the distribution of aluminum species in the coagulant. Results indicated that the volcanic rock that was treated with acidic and alkaline solutions had the potential to form PSAC with Al-OH, Al-O-Si, Fe-OH, and Fe-O-Si bonds, which influenced the coagulation–flocculation efficiency. An acid leaching temperature of 90 °C, 8 mL of 2 mol/L NaOH, a reaction time of 0.5 h, and a reaction temperature of 60 °C were conducive to the preparation. A higher temperature could result in a higher proportion of Alb species, and, at 100 °C, the Ala, Alc, and Alb were 29%, 24%, and 47%, respectively, achieving a residual turbidity lower than 1 NTU at an appropriate dosage, as well as a reduction of over 0.1 to 0.018 in the level of UV₂₅₄. The findings of this study provide a feasible method to prepare a flocculant using volcanic rock. Further application is expected to yield good results in wastewater/water treatment. Full article

Although corn germ meal is a rich source of dietary fiber, it contains a relatively low proportion of soluble dietary fiber (SDF) and is frequently contaminated with high levels of zearalenone (ZEN). Solid-state fermentation has the dual effects of modifying dietary fiber (DF) and degrading mycotoxins. This study optimized the solid-state fermentation process of corn germ meal using Bacillus subtilis K6 through response surface methodology (RSM) to enhance SDF yield while efficiently degrading ZEN. Results indicated that fermentation solid-to-liquid ratio and time had greater impacts on SDF yield and ZEN degradation rate than fermentation temperature. The optimal conditions were determined as temperature 36.5 °C, time 65 h, and solid-to-liquid ratio 1:0.82 (w/v). Under these conditions, the ZEN degradation rate reached 96.27 ± 0.53%, while the SDF yield increased from 9.47 ± 0.68% to 20.11 ± 1.87% (optimizing the SDF/DF ratio from 1:7 to 1:3). Scanning electron microscopy (SEM) and confocal laser scanning microscope (CLSM) revealed the structural transformation of dietary fiber from smooth to loose and porous forms. This structural modification resulted in a significant improvement in the physicochemical properties of dietary fiber, with water-holding capacity (WHC), oil-holding capacity (OHC), and water-swelling capacity (WSC) increasing by 34.8%, 16.4%, and 15.2%, respectively. Additionally, the protein and total phenolic contents increased by 23.0% and 82.61%, respectively. This research has achieved efficient detoxification and dietary fiber modification of corn germ meal, significantly enhancing the resource utilization rate of corn by-products and providing technical and theoretical support for industrial production applications. Full article

Isoflavones are the main phenolic compounds of soybean that affect its biological activity. The quantity of these valuable compounds extracted from plant material can significantly vary, influenced by the chosen extraction method and the specific extractants employed. Moreover, in cosmetics and pharmacy, the application of non-toxic, eco-friendly solvents is very important. This study aimed to develop the best mixture of extractants to maximize the recovery of individual isoflavones from soybean seeds by optimization of the proportion of three components: ethanol, water, and propanediol. The design of experiments (DOE) method was strategically employed. The extracts were obtained through accelerated solvent extraction and meticulously analyzed for isoflavone content using advanced electrospray ionization–time of flight–mass spectrometry (ESI-TOF-MS) profiling. The predominant isoflavones were daidzin, genistin, malonylgenistin, malonyldaidzin, and malonylglycitin. Our experiment demonstrated that employing three extractants in a balanced 1:1:1 v/v/v ratio resulted in the highest isolation of isoflavones compared to all other mixtures tested. Nevertheless, a detailed exploration of approximate values and utility profiles revealed a more effective composition for extraction efficiency. This optimal mixture features 32.8% ethanol, 39.2% water, and 27.8% propanediol, maximizing the yield of isoflavones from soybean seeds. The innovative use of mixture design and triangular response surfaces has proven to be a powerful approach for developing this superior three-component extraction mixture. This innovative approach not only enhances extraction efficiency but also paves the way for improved processing methods in the industry. Full article

This study aims to explore the potential of aerogel to optimise the thermal conductivity of mineralised foam materials. Experiments were conducted with (i) addition methods of aerogel, (ii) proportion of aerogels in cement slurry, and (iii) water/cement ratio as influencing parameters for mineralised foam. Additionally, mixed Ordinary Portland Cement (OPC)/Calcium Sulphoaluminate Cement (CSA) slurries were used to test whether a synergy could be achieved. In this study, the defoaming effect of the aerogel and its mitigation to a certain extent by pre-mixing the aerogel with cement slurry were confirmed. The thermal conductivity of the mineralised foams was reduced from 0.049 to 0.036 W/(m·K) when the aerogel was up to 10 wt.% of the cement. In the specimens prepared from the mixed OPC/CSA slurry, a homogeneous circular pore structure was observed under the microscope along with a reduction in the thermal conductivity. The use of aerogels and CSA cements can effectively reduce the thermal conductivity of ultra-low-density mineralised foams to levels comparable with certain plastic foams that dominate the building insulation market. Full article

This paper presents the Green Watershed Index (GWI) methodology, focusing on the 17 sustainability indicators selected in the Razey watershed, NW Iran. Field surveys and data collection have provided the possibility of field inspection and measurement of the present condition of the watershed and the indicators taken. Based on the degree of compliance with the required process, each indicator was scored from 0 to 10 and classified into three categories: unsustainable, semi-sustainable, and sustainable. Using the Entropy method to assign weight to each indicator and formulating a proportional mathematical relationship, the GWI score for each sub-watershed was derived. Spatial changes regarding the selected indicators and, consequently, the GWI were detected in the study area. Development of water infrastructure, particularly in the upstream sub-watersheds, plays a great role in increasing the GWI score. The highest weight is related to environmental productivity (0.26), and the five indicators of water footprint, knowledge management and information quality system, landscape attractiveness, waste recycling, and corruption control have approximately zero weight due to their monotonous spatial distribution throughout sub-watersheds. Only sub-watershed R1 has the highest score (5.13), indicating a semi-sustainable condition. The rest of the sub-watersheds have unsustainable conditions (score below 5). Concerning the GWI, the watershed is facing a critical situation, necessitating the implementation of management and conservation strategies that align with the sustainability level of each sub-watershed. Full article

Objectives: The major sugarcane-producing regions of Guangxi represent a critical agricultural zone in China. Investigating the mechanisms of land use change and carbon storage dynamics in this area is essential for optimizing regional ecological security and promoting sustainable development. Methods: Employing the land use transfer matrix, the InVEST model and the Geodetector model to analyze carbon storage changes and identify key driving factors and their interactive effects. Results: (1) From 2011 to 2022, Guangxi’s major sugarcane-producing regions experienced significant land use changes: reductions in cultivated land, grassland and water bodies alongside expansions of forest, bare land and construction land. (2) The total carbon storage in Guangxi’s major sugarcane-producing regions has increased from 2011 to 2018 by 0.99%, representing 1627.03 and 1643.10 million tons, while it has decreased by 0.1% in 2022 (1641.47 million tons) compared to 2018. (3) Cultivated land proportion and forest coverage rate were the primary drivers of spatial heterogeneity, followed by average slope and land urbanization rate. (4) Interaction analysis revealed strong synergistic effects among cultivated land proportion, forest coverage rate, NDVI and average slope, confirming multi-factor control over carbon storage changes. Conclusions: Carbon storage in the Guangxi sugarcane-producing regions is shaped by land use patterns and multi-factor interactions. Future strategies should optimize land use structures and balance urbanization with ecological protection to enhance regional carbon sequestration. Full article