Search Results (483)

The present research features an experimental comparative design and the objective of this work was to determine the susceptibility to microbiological contamination in fatty acid methyl esters (FAMEs) and the FAME–water interface of residual and refined lard, large volume simulating storage conditions as fuel supply chain, and to identify the microorganisms developed. The plates were seeded according to ASTM E-1259 and the instructions provided by the manufacturer of the Bushnell Haas agar. Microbiological growth was observed at the FAME–water interface of FAME obtained from residual lard. Using the MALDI-TOF mass spectrometry technique, Pseudomonas aeruginosa and Streptomyces violaceoruber bacteria were identified in the residual lard FAMEs, with the latter being previously reported in FAMEs. The implications of microorganism development on the physicochemical quality of FAMEs are significant, as it leads to an increase in the acid index, which may negatively impact metals by inducing corrosion. The refined lard FAMEs did not show any development of microorganisms. The present research concluded that residual lard tends to be more prone to microbiological attack if the conditions of water and temperature affect microbial growth. The findings will contribute to the knowledge base for a safer introduction of FAMEs into the biofuel matrix. Full article

The excellent moisture transport properties of yarns play a crucial role in improving the liquid moisture transfer behavior within textiles and maintaining their thermal-wet comfort. However, the current research on the moisture management performance of fabrics made from yarns with excellent liquid transport properties primarily compares the wicking results, without considering the varying requirements of testing conditions due to differences in human sweating rates during daily activities. Moreover, the understanding of moisture transport mechanisms in yarns within fabrics under different testing conditions remains insufficient. In this study, two types of twisted combination yarns, composed of hydrophobic profiled polyester filaments and hydrophilic spun yarns to form a hydrophobic-hydrophilic gradient along the axial direction of the yarn, were developed and compared with profiled polyester filaments to understand the liquid migration behaviors in the knitted fabrics formed by these yarns. Results showed that hydrophobic profiled polyester filament yarn demonstrated superior liquid transport performance with infinite saturated liquid supply (vertical wicking test). In contrast, the twisted combination yarns exhibited better moisture diffusion properties under limited liquid droplet supply conditions (droplet diffusion test and moisture management test). These contradictory findings indicated that the amount of liquid moisture supply in testing conditions significantly affected the moisture transport performance of yarns within fabrics. It was revealed that the liquid moisture in the twisted combination yarns migrated through capillary wicking for moisture transfer. Under an infinite saturated liquid supply condition, the higher the content of hydrophilic fibers in the spun yarns, the greater the amount of moisture transferred, demonstrating an excellent liquid transport performance. Under the limited liquid droplet supply conditions, both the volume of liquid water and the moisture absorption capacity of the yarn jointly influence internal moisture migration within the yarn. It provided a theoretical reference for testing the internal moisture wicking performance of fabrics under different states of human sweating. Full article

In the global energy sector, water-bearing reservoir-typed gas storage accounts for about 30% of underground gas storage (UGS) reservoirs and is vital for natural gas storage, balancing gas consumption, and ensuring energy supply stability. However, when constructing the UGS in the M gas reservoir, selecting suitable areas poses a challenge due to the complicated gas–water distribution in the multi-layered water-bearing gas reservoir with a long production history. To address this issue and enhance energy storage efficiency, this study presents an integrated geomechanical-hydraulic assessment framework for choosing optimal UGS construction horizons in multi-layered water-bearing gas reservoirs. The horizons and sub-layers of the gas reservoir have been quantitatively assessed to filter out the favorable areas, considering both aspects of geological characteristics and production dynamics. Geologically, caprock-sealing capacity was assessed via rock properties, Shale Gouge Ratio (SGR), and transect breakthrough pressure. Dynamically, water invasion characteristics and the water–gas distribution pattern were analyzed. Based on both geological and dynamic assessment results, the favorable layers for UGS construction were selected. Then, a compositional numerical model was established to digitally simulate and validate the feasibility of constructing and operating the M UGS in the target layers. The results indicated the following: (1) The selected area has an SGR greater than 50%, and the caprock has a continuous lateral distribution with a thickness range from 53 to 78 m and a permeability of less than 0.05 mD. Within the operational pressure ranging from 8 MPa to 12.8 MPa, the mechanical properties of the caprock shale had no obvious changes after 1000 fatigue cycles, which demonstrated the good sealing capacity of the caprock. (2) The main water-producing formations were identified, and the sub-layers with inactive edge water and low levels of water intrusion were selected. After the comprehensive analysis, the I-2 and I-6 sub-layer in the M 8 block and M 14 block were selected as the target layers. The numerical simulation results indicated an effective working gas volume of 263 million cubic meters, demonstrating the significant potential of these layers for UGS construction and their positive impact on energy storage capacity and supply stability. Full article

The water–energy nexus (WEN) is of great significance due to the strong interdependence between the energy and water sectors. Nevertheless, water leakage in water distribution networks (WDNs), which is often ignored in existing WEN operation models, causes notable water and energy losses. In this research, a cooperative operation model for WEN considering WDN water leakage is put forward. A hybrid stochastic–information gap decision theory (IGDT) method was tailored in this study to properly manage the probabilistic uncertainties associated with renewable generation, electrical and water demand in the WEN, and water leakage with limited information to enhance the robustness of the operation strategies of the WEN under complex operational conditions. The proposed model and method were validated on a modified IEEE 33-bus system integrated with a 15-node commercial WDN. The co-optimization model reduced the operational cost by 23.01% compared to the independent operation model. When considering water leakage, the joint optimization resolved the water supply shortage issue caused by ignoring leakage and reduced the water purchase volume by 94.44 cubic meters through coordinated optimization. These quantitative results strongly demonstrate the effectiveness of the proposed framework. Full article

Groundwater storage refers to the water stored in the pore spaces of underground aquifers, which has been increasingly affected by both climate change and anthropogenic activities in recent decades. Therefore, monitoring their changes and the factors that affect it is of great importance. Although the influence of natural factors on groundwater is well-recognized, the impact of human activities, despite being a major contributor to its change, has been less explored due to the challenges in measuring such effects. To address this gap, our study employed an integrated approach using remote sensing and the Google Earth Engine (GEE) cloud-free platform to analyze the effects of various anthropogenic factors such as built-up areas, cropland, and surface water on groundwater storage in the Lake Urmia Basin (LUB), Iran. Key anthropogenic variables and groundwater data were pre-processed and analyzed in GEE for the period from 2000 to 2022. The processes linking these variables to groundwater storage were considered. Built-up area expansion often increases groundwater extraction and reduces recharge due to impervious surfaces. Cropland growth raises irrigation demand, especially in semi-arid areas like the LUB, leading to higher groundwater use. In contrast, surface water bodies can supplement water supply or enhance recharge. The results were then exported to XLSTAT software2019, and statistical analysis was conducted using the Mann–Kendall (MK) non-parametric trend test on the variables to investigate their potential relationships with groundwater storage. In this study, groundwater storage refers to variations in groundwater storage anomalies, estimated using outputs from the Global Land Data Assimilation System (GLDAS) model. Specifically, these anomalies are derived as the residual component of the terrestrial water budget, after accounting for soil moisture, snow water equivalent, and canopy water storage. The results revealed a strong negative correlation between built-up areas and groundwater storage, with a correlation coefficient of −1.00. Similarly, a notable negative correlation was found between the cropland area and groundwater storage (correlation coefficient: −0.85). Conversely, surface water availability showed a strong positive correlation with groundwater storage, with a correlation coefficient of 0.87, highlighting the direct impact of surface water reduction on groundwater storage. Furthermore, our findings demonstrated a reduction of 168.21 mm (millimeters) in groundwater storage from 2003 to 2022. GLDAS represents storage components, including groundwater storage, in units of water depth (mm) over each grid cell, employing a unit-area, mass balance approach. Although storage is conceptually a volumetric quantity, expressing it as depth allows for spatial comparison and enables conversion to volume by multiplying by the corresponding surface area. Full article

The design of channel geometry plays a critical role in the performance of proton exchange membrane electrolytic cells (PEMECs), particularly in addressing challenges such as bubble accumulation and pressure drop, which hinder efficient hydrogen production. This study introduces an innovative uneven wave-like protrusion channel structure for PEMECs, designed to optimize mass transfer and bubble removal while minimizing energy losses. A combination of three-dimensional numerical simulations and the Taguchi design method is employed to systematically investigate the impact of protrusion height, width, and spacing on key performance metrics, including pressure drop, oxygen output, and volumetric gas content. The effects of different water supply flow rates and temperatures on the electrolytic cell were also investigated through visualization experiments. The results show that the channel with inhomogeneous waveform protrusions has superior PEMEC performance compared with the conventional single serpentine channel. In addition, the waveforms of the waveform protrusions were optimized using the Taguchi design method. The results obtained further optimized the PEMEC performance by increasing the outlet oxygen volume by 8.97%, reducing the average pressure drop by 4.4%, and decreasing the volumetric gas content by 20.26%. Full article

Spring waters (n = 103) from locations surrounding Great Salt Lake (GSL) were mapped, collected, and analyzed to determine their chemical compositions. A ternary Ca-SO₄-alkalinity plot was used to group these waters into compositional types based on the principle of chemical divides. Different spring water types were mixed with Bear, Jordan, and Weber River waters to determine the amount of spring inflow needed to reproduce the chemical composition of GSL. The Pitzer-based computer program EQL/EVP was used to simulate evaporation of spring-river water mixtures. The goal was to find spring-river water mixtures that, when evaporated, reproduced the chemical composition of modern GSL. This approach yielded GSL brine composition from a starting mixture of 12% spring inflow and 88% river water, by volume. The calculated spring inflow–river water mixture contains, on a molar percentage basis, greater than 50% of the B, K, Li, Na, and Cl supplied by springs and greater than 50% of the Ba, Ca, Sr, SO₄, and alkalinity derived from rivers. Understanding GSL spring inflow and brine evolution as lake elevation drops is critical to lake environments, ecosystems, and industrial brine shrimp harvesting and mineral extraction. Full article

Dam breaks can lead to important economic and human losses. Design floods, which are useful to assess possible dam breaks, are usually estimated through statistical analysis of rainfall and streamflow observed data. However, such available samples are commonly limited and, consequently, high uncertainties are associated with the design flood estimates. In addition, climate change is expected to increase the frequency and magnitude of extreme rainfall and flood events in the future. Therefore, a methodology based on a stochastic rainfall generator is proposed to assess hydrological dam safety by considering climate change. We selected the Eugui Dam on the Arga river in the north of Spain as a case study that has a spillway operated by gates with a maximum capacity of 270 m³/s. The stochastic rainfall generator STORAGE is used to simulate long time series of 15-min precipitation in both current and future climate conditions. Precipitation projections of 12 climate modeling chains, related to the usual three 30-year periods (2011–2024; 2041–2070 and 2071–2100) and two emission scenarios of AR5 (RCP 4.5 and 8.5), are used to consider climate change in the STORAGE model. The simulated precipitation time series are transformed into runoff time series by using the continuous COSMO4SUB hydrological model, supplying continuous 15-min runoff time series as output. Annual maximum flood hydrographs are selected and considered as inflows to the Eugui Reservoir. The Volume Evaluation Method is applied to simulate the operation of the Eugui Dam spillway gates, obtaining maximum water levels in the reservoir and outflow hydrographs. The results show that the peak outflows at the Eugui Dam will be lower in the future. Therefore, maximum reservoir water levels will not increase in the future. The methodology proposed could allow practitioners and dam managers to check the hydrological dam safety requirements, accounting for climate change. Full article

The water issue is undoubtedly one of the most fundamental challenges and controversial issues of the current century. These days, the best options for managing water resources can be chosen by considering several indexes, such as political, social, and environmental criteria. The overall goal of this research is to propose an integrated model of fuzzy Shannon entropy and Fuzzy Additive Ratio Assessment (ARAS) that uses risk indexes to manage water resources in drought conditions. To achieve the goal of this research, first, risk factors are identified and selected based on the literature review. In previous studies, risk indicators were employed for water resource management, separately. However, this paper extracted an extensive list of risk indicators from prior studies and employed all these indicators for water resource management. Furthermore, four scenarios for water resource management in Chaharmahal and Bakhtiari province are introduced according to the geographical characteristics, climate, economic and agricultural conditions in this province. Then, a questionnaire is designed and distributed among experts in the field of water resource management. After collecting data, the proposed method is implemented on the data. The fuzzy Shannon entropy method is used to determine the weights of risk indicators, while the fuzzy ARAS method is applied for ranking water resource management scenarios. The results of applying fuzzy Shannon entropy reveal that the three indicators of volume reliability, vulnerability, and sustainability of the water supply system, with weight values of 0.124, 0.119, and 0.118, respectively, are the most effective risk indexes. The results of implementing fuzzy ARAS show that changing the cultivation pattern with a score of 0.936 is placed in the first priority, reducing the demand of the agricultural sector with a score of 0.922 is placed in the second priority, and the type of irrigation system with a score of 0.896 is placed in the third priority, and the reduction of industrial and drinking water consumption with a score of 0.882 is placed in the fourth priority. Finally, the results of implementing the proposed model of fuzzy Shannon entropy and fuzzy ARAS reveal an increase in volume reliability in the field of cropping pattern change in the studied province. Full article

The combined effects of rapid urbanization and climate change are increasingly exacerbating the risk of urban flooding. This study develops a data-efficient framework for estimating a city’s Urban Stormwater Carrying Capacity (USCC)—the maximum stormwater volume that can be safely infiltrated, stored, and conveyed. The framework couples three rainfall scenarios—frequent, heavy, and extreme—with nine widely adopted drainage and storage measures, ranging from green spaces and permeable pavements to pipes and underground emergency reservoirs, and expresses USCC through a streamlined water-balance equation. Applied to the 24 km² Zhangmian River district in Weifang, China, the framework yields capacities of 4.84, 5.86, and 9.80 × 10⁶ m³ for the three scenarios, respectively; underground reservoirs supply ≈ 40% of the extreme-event capacity. Sensitivity analysis shows that increasing the imperviousness coefficient from 0.65 to 0.85 raises peak drainage demand by 30.8%, whereas halving reservoir depth lowers total capacity by 27.8%. Because the method requires only rainfall depth, land-cover data, and basic facility dimensions, it enables rapid, transparent scenario testing and helps planners prioritize cost-effective upgrades. The approach is transferable to other cities and can be extended to incorporate water quality or digital-twin modules in future research. Full article

This study evaluates the feasibility of repurposing produced water—an abundant byproduct of hydrocarbon extraction—for green hydrogen production in Wyoming, USA. Analysis of geospatial distribution and production volumes reveals that there are over 1 billion barrels of produced water annually from key basins, with a general total of dissolved solids (TDS) ranging from 35,000 to 150,000 ppm, though Wyoming’s sources are often at the lower end of this spectrum. Optimal locations for hydrogen production hubs have been identified, particularly in high-yield areas like the Powder River Basin, where the top 2% of fields contribute over 80% of the state’s produced water. Detailed water-quality analysis indicates that virtually all of the examined sources exceed direct electrolyzer feed requirements (e.g., <2000 ppm TDS, <0.1 ppm Fe/Mn for target PEM systems), necessitating pre-treatment. A review of advanced treatment technologies highlights viable solutions, with estimated desalination and purification costs ranging from USD 0.11 to USD 1.01 per barrel, potentially constituting 2–6% of the levelized cost of hydrogen (LCOH). Furthermore, Wyoming’s substantial renewable-energy potential (3000–4000 GWh/year from wind and solar) could sustainably power electrolysis, theoretically yielding approximately 0.055–0.073 million metric tons (MMT) of green hydrogen annually (assuming 55 kWh/kg H₂), a volume constrained more by energy availability than water supply. A preliminary economic analysis underscores that, while water treatment (2–6% LCOH) and transportation (potentially > 10% LCOH) are notable, electricity pricing (50–70% LCOH) and electrolyzer CAPEX (20–40% LCOH) are dominant cost factors. While leveraging produced water could reduce freshwater consumption and enhance hydrogen production sustainability, further research is required to optimize treatment processes and assess economic viability under real-world conditions. This study emphasizes the need for integrated approaches combining water treatment, renewable energy, and policy incentives to advance a circular economy model for hydrogen production. Full article

Managed Aquifer Recharge (MAR) is increasingly being adopted across Europe to enhance water security in semiarid regions, with over 230 operational sites. The Akrotiri MAR system in Limassol, Cyprus, comprises 17 recharge ponds operating since 2016 to counteract saltwater intrusion. This study evaluates MAR effectiveness by analyzing spatial and temporal variations in water quality from 2016 to 2020. Parameters analyzed include nutrients, metals, pesticides, pharmaceuticals, fecal indicators, physicochemical characteristics, recharge and pumping volumes, and groundwater levels. The results show that soil aquifer treatment (SAT) generally improves groundwater quality but certain boreholes exhibited elevated nitrate (range 12.70–31 mg/L), electrical conductivity (range 936–10,420 μs/cm), and chloride concentrations (range 117–1631 mg/L), attributed to recharge water quality, seawater intrusion, and nearby agricultural activities. Tertiary treated wastewater used for recharge occasionally exceeds permissible limits, particularly in E. coli (up to 2420/100 mL), chloride (up to 385 mg/L), and nitrogen (up to 41 mg/L). Supplementing recharge with dam-supplied freshwater improves groundwater quality and raises water levels. These findings underline the importance of continuous monitoring and effective management, adopting sustainable farming practices, and the strict control of recharge water quality. The study offers valuable insights for optimizing MAR systems and supports integrating MAR into circular water management frameworks to mitigate pollution and seawater intrusion, enhancing long-term aquifer sustainability. Full article

Jordan is a relatively small country with limited natural resources, but it faces a burgeoning demand for water, energy, and food to accommodate a growing population, refugee migration, and the challenges of climate change that will persist through the rest of this century. Jordan’s Main Water Conveyance System is the backbone of distributing scarce water resources to meet domestic and agricultural demands. Therefore, understanding how the future energy requirements of this system may change is critical for managing the country’s water, energy, and food resources. This paper applied a water balance model to calculate the energy consumption of Jordan’s Main Water Conveyance System between 2015 and 2050, and the results point to high energy requirements for the future of distributing Jordan’s water. In the base year of 2015, the unmet water demand was 134.55 MCM, and the supplied water volume delivered was 438.75 MCM, while the energy consumption was 1496.7 GWh. The energy intensities for water conveyance and water treatment were 7.11 kWh/m³ and 0.5 kWh/m³, respectively. We examined five scenarios of future water and energy demand within Jordan: a reference scenario, a continuation of current behavior, two scenarios incorporating improved water management strategies, and a pessimistic scenario with no interventions. According to all scenarios, the energy consumption is expected to be doubled by the year 2050, reaching approximately 3172 GWh. It is recommended that Jordan prioritizes solar-powered conveyance and pumping to reduce the projected doubling of energy demand by 2050. Across all scenarios, the demand for nonrenewable energy associated with water conveyance is projected to rise significantly, particularly in the absence of renewable integration or efficiency interventions. Total water demand is expected to increase by up to 35% by 2050, with urban and agricultural sectors being the primary contributors. Full article

From the urban sustainability perspective and from the steps essential for regulating/balancing the microclimate features, the creation and maintenance of urban green spaces (UGS) are vital. The UGS include vegetation of any kind in urban areas such as parks, gardens, vertical gardens, trees, hedge plants, and roadside plants. This “urban green infrastructure” is a cost-effective and energy-saving means for ensuring sustainable development. The relationship between urban landscape patterns and microclimate needs to be sufficiently understood to make urban living ecologically, economically, and ergonomically justifiable. In this regard, information on diverse patterns of land use intensity or spatial growth is essential to delineate both beneficial and adverse impacts on the urban environment. With this background, the present study aimed to address water requirements of UGS plants and trees during the non-rainy months from Panaji city (Koppen classification: Am) situated on the west coast of India, which receives over 2750 mm of rainfall, almost exclusively during June–September. During the remaining eight months, irrigating the plants in the UGS becomes a serious necessity. In this regard, the daily water requirements (DWR) of 34 tree species, several species of hedge plants, and lawn areas were estimated using standard methods that included primary (field survey-based) and secondary (inputs from key-informant survey questionnaires) data collection to address water requirement of the UGS vegetation. Monthly evapotranspiration rates (ET_o) were derived in this study and were used for calculating the water requirement of the UGS. The day–night average ET_o was over 8 mm, which means that there appears to be an imminent water stress in most UGS of the city in particular during the January–May period. The DWR in seven gardens of Panaji city were ~25 L/tree, 6.77 L/m² hedge plants, and 4.57 L/m² groundcover (=lawns). The water requirements for the entire UGS in Panaji city were calculated. Using this information, the estimated total daily volume of water required for the entire UGS of 1.86 km² in Panaji city is 7.10 million liters. The current supply from borewells of 64,200 L vis a vis means that the ET_o-based DWR of 184,086 L is at a shortage of over 2.88 times and is far inadequate for meeting the daily demand of hedge plants and lawn/groundcover. Full article

In citriculture, inputs like water and fertilizer are applied through traditional basin methods, thereby incurring reduced use-efficiency. The response of conventional crop coefficient-based fertigation scheduling continues to be inconsistent and complex in its field implementation, thereby necessitating the intervention of sensor-based (Internet of Things; IoT) technology for fertigation scheduling on a real-time basis. The study aimed to investigate fertigation scheduling involving four levels of irrigation, viz., I₁ (100% evapotranspiration (ET) as the conventional practice), I₂ (15% volumetric moisture content (VMC)), I₃ (20% VMC), and I₄ (25% VMC), as the main treatments and three levels of recommended doses of fertigation, achieved by reappropriating different nutrients across phenologically defined critical growth stages, viz., F₁, F₂, and F₃ (conventional fertilization practice), as sub-treatments, which were evaluated through a split-plot design over two harvesting seasons in 2021–2023. Nagpur mandarin (Citrus reticulata Blanco) was used as the test crop, which was raised on Indian Vertisol facing multiple nutrient constraints. Maximum values for physiological growth parameters (plant height, canopy area, canopy volume, and relative leaf water content (RLWC)) and fruit yield (characterized by 9% and 5%, respectively, higher A-grade-sized fruits with the I₄ and F₁ treatments over corresponding conventional practices, viz., I₁ and F₃) were observed with the I₄ irrigation treatment in combination with the F₁ fertilizer treatment (I₄F₁). Likewise, fruit quality parameters, viz., juice content, TSS, TSS: acid ratio, and fruit diameter, registered significantly higher with the I₄F₁ treatment, featuring the application of B at the new-leaf initiation stage (NLI) and Zn across the crop development (CD), color break (CB), and crop harvesting (CH) growth stages, which resulted in a higher leaf nutrient composition. Treatment I₄F₁ conserved 20–30% more water and 65–87% more nutrients than the I₁F₃ treatment (conventional practice) by reducing the rate of evaporation loss of water, thereby elevating the plant’s available nutrient supply within the root zone. Our study suggests that I₄F₁ is the best combination of sensor-based (IoT) irrigation and fertilization for optimizing the quality production of Nagpur mandarin, ensuring higher water productivity (WP) and nutrient-use-efficiency (NUE) coupled with the improved nutritional quality of the fruit. Full article