Search Results (948)

Monitoring water quality is crucial for achieving clean water and sanitation goals, particularly in remote areas. The project “Morbidity vs. Water Quality for Human Consumption in Tonosí: A Pilot Study” aimed to enhance water quality assessments in Panama using advanced analytical techniques to assess volatile organic compounds, heavy metals, and microbiological pathogens. To support this, the Technical Unit for Water Quality (UTECH) was established, featuring a novel mobile laboratory with cutting-edge technology for accurate testing, minimal chemical reagent use, reduced waste generation, and equipped with a solar-powered battery system. The aim of this paper is to explore the design, deployment, and impact of the UTECH. Furthermore, this study presents results from three sampling points in Tonosí, where several parameters exceeded regulatory limits, demonstrating the capabilities of the UTECH and highlighting the need for ongoing monitoring and intervention. The study also assesses the environmental, social, and economic impacts of the UTECH in alignment with the Sustainable Development Goals and national initiatives. Finally, a SWOT analysis illustrates the UTECH’s potential to improve water quality assessments in Panama while identifying areas for sustainable growth. The study showcases the successful integration of advanced mobile laboratory technologies into water quality monitoring, contributing to sustainable development in Panama and offering a replicable model for similar initiatives in other regions. Full article

The maritime sector’s transition to sustainable energy is critical for achieving global carbon neutrality, with container terminals representing a key focus due to their high energy consumption and emissions. This study explores the potential of hydrogen energy as a decarbonization solution for port operations, using the Chuanshan Port Area of Ningbo Zhoushan Port (CPANZP) as a case study. Through a comprehensive analysis of hydrogen production, storage, refueling, and consumption technologies, we demonstrate the feasibility and benefits of integrating hydrogen systems into port infrastructure. Our findings highlight the successful deployment of a hybrid “wind-solar-hydrogen-storage” energy system at CPANZP, which achieves 49.67% renewable energy contribution and an annual reduction of 22,000 tons in carbon emissions. Key advancements include alkaline water electrolysis with 64.48% efficiency, multi-tier hydrogen storage systems, and fuel cell applications for vehicles and power generation. Despite these achievements, challenges such as high production costs, infrastructure scalability, and data integration gaps persist. The study underscores the importance of policy support, technological innovation, and international collaboration to overcome these barriers and accelerate the adoption of hydrogen energy in ports worldwide. This research provides actionable insights for port operators and policymakers aiming to balance operational efficiency with sustainability goals. Full article

Evaporative cooling (EC) offers an energy-efficient alternative to direct expansion (DX) cooling but suffers from high water consumption. This limitation can be mitigated by pre-cooling incoming fresh air using cooler exhaust air via energy recovery. This study presents and optimizes a solar-driven EC system integrated with underfloor air distribution (UFAD) to enhance thermal comfort and minimize water use in a temporary office in Riyadh’s arid climate. A 3D CFD model was developed and validated against published data to simulate indoor airflow, providing data for thermal comfort evaluation using the predicted mean vote model in cases with and without energy recovery. A year-round hourly energy analysis revealed that the solar-driven EC-UFAD system reduces grid power consumption by 93.5% compared to DX-based UFAD under identical conditions. Energy recovery further cuts annual EC water usage by up to 31.3%. Operational costs decreased by 84% without recovery and 87% with recovery versus DX-UFAD. Full article

This study utilises the Open Source Energy Modelling System (OSeMOSYS) in conjunction with the Climate, Land, Energy, and Water systems (CLEWs) framework to investigate Thailand’s energy transition, which is designed to achieve carbon neutrality by 2050. Two scenarios have been devised to evaluate the long-term trade-offs among energy, water, and land systems. Data were sourced from esteemed international organisations (e.g., the IEA, FAO, and OECD) and national agencies and organised into a tailored OSeMOSYS Starter Data Kit for Thailand, comprising a baseline and a carbon neutral trajectory. The baseline scenario, primarily reliant on fossil fuels, is projected to generate annual CO₂ emissions exceeding 400 million tons and water consumption surpassing 85 billion cubic meters by 2025. By the mid-century, the carbon neutral scenario will have approximately 40% lower water use and a 90% reduction in power sector emissions. Under the carbon neutral path, renewable energy takes the front stage; the share of renewable electricity goes from under 20% in the baseline scenario to almost 80% by 2050. This transition and large reforestation initiatives call for consistent investment in solar energy (solar energy expenditures exceeding 20 billion USD annually by 2025). Still, it provides notable co-benefits, including greater resource sustainability and better alignment with international climate targets. The results provide strategic insights aligned with Thailand’s National Energy Plan (NEP) and offer modelling evidence toward achieving international climate goals under COP29. Full article

Hydrogen, as a renewable and clean energy with a high energy density, is of great significance to the realization of carbon neutrality. In recent years, extensive research has been conducted on the electrocatalytic hydrogen evolution reaction (HER) by splitting water, with a focus on developing efficient electrocatalysts that can perform the HER at an overpotential with minimal power consumption. Tungsten oxide (WO₃), a non-noble-metal-based material, has great potential in hydrogen evolution due to its excellent redox capability, low cost, and high stability. However, it cannot meet practical needs because of its poor electrical conductivity and the limited number of active sites; thus, it is necessary to further improve HER performance. In this review, recent advances related to WO3-based electrocatalysts for the HER are introduced. Most importantly, several tactics for optimizing the electrocatalytic HER activity of WO₃ are summarized, such as controlling its morphology, phase transition, defect engineering (anion vacancies, cation doping, and interstitial atoms), constructing a heterostructure, and the microenvironment effect. This review can provide insight into the development of novel catalysts with high activity for the HER and other renewable energy applications. Full article

Microchannel heat sinks (MCHSs) have emerged as an alternative for dissipating high heat rates. However, manufacturing MCHSs can be expensive, so exploring low-cost additive manufacturing using 3D printing is warranted. Before fabrication, the entropy minimization method helps to optimize MCHSs, enhancing their cooling capacity while maintaining their power consumption. We employed this method through computational simulation of laminar water flow in rectangular microchannels ($\mathsf{\mu }$C) and minichannels (mC), considering two heat fluxes (10 and 50 kW/m²). The results showed that the frictional entropy is only appreciable in the smallest and largest channels. These computational results enabled the fabrication of the optimal $\mathsf{\mu }$C and mC, whose experimental implementation validated the computational findings. Moreover, we computationally studied the effect of using rGO-Ag water-based nanofluids as a coolant. In general, a reduction in total entropy generation was observed at a heat flux of 50 kW/m². Although at lower heat flux (10 kW/m²), mC was the best option. Channels with lower heights were more effective at higher heat fluxes (≥50 kW/m²). Our findings offer a cost-effective strategy for fabricating high-performance cooling systems while also highlighting the interplay among heat flux, entropy generation, and nanofluid-enhanced cooling. Full article

The impact of processing time, temperature, and sample on solution ratio parameters, along with pulsing microwave pretreatment, was assessed in the osmotic dehydration of waxy skin highbush blueberries. Fresh blueberries were pre-treated with 20% microwave power for 90 s before being subjected to osmotic dehydration for 8 h in a 60 °Brix sucrose solution, with three different sample to solution ratios (1:4, 1:7, and 1:10). Changes in water loss, solid gain, total anthocyanin content, total phenolic content, and total soluble solid content during osmotic dehydration, as well as color and texture changes, were investigated at four temperature levels (room temperature, 60 °C, 65 °C, and 70 °C). The highest rate of reduction in the total soluble solid content in the osmotic solution was observed during the initial hours (0–4 h) of the process. The most effective combination for reducing the total soluble content of the osmotic agent involved the microwave-pretreatment of the blueberries at 70 °C, using a sample to solution ratio of 1:4, resulting in a decrease of 11.98%, compared to 7.83% for non-pretreated samples. The solid gain was found to be affected by the sample to solution ratio × temperature × pretreatment at a 1% probability level (p ≤ 0.01). The temperature, osmotic solution ratio, and microwave pretreatment interacted together to affect the quality parameters of the osmotically dehydrated blueberries, including total anthocyanin content, total phenolic content, and color. Higher temperatures, along with microwave pretreatment, showed the worst effects on the quality characteristics mentioned. Microwave pretreatment did not change the texture significantly in comparison with non-pretreated blueberry samples. The enhancing effect of microwave pretreatment and higher temperatures on the efficiency of the osmotic dehydration process was obvious. An optimized microwave pretreatment can reduce both the required processing time and temperature for the osmotic dehydration of waxy skinned blueberries, which in turn can lead to the higher quality preservation of processed blueberries and lower energy consumption. This could be especially useful for the large-scale processing of waxy skinned berries. Full article

With the increasing integration of renewable energy and smart technologies in residential energy systems, proactive household energy management (HEM) have become critical for reducing costs, enhancing grid stability, and achieving sustainability goals. This study proposes a ultra-short-term forecasting-driven proactive energy consumption optimization strategy that integrates advanced forecasting models with multi-objective scheduling algorithms. By leveraging deep learning techniques like Graph Attention Network (GAT) architectures, the system predicts ultra-short-term household load profiles with high accuracy, addressing the volatility of residential energy use. Then, based on the predicted data, a comprehensive consideration of electricity costs, user comfort, carbon emission pricing, and grid load balance indicators is undertaken. This study proposes an enhanced mixed-integer optimization algorithm to collaboratively optimize multiple objective functions, thereby refining appliance scheduling, energy storage utilization, and grid interaction. Case studies demonstrate that integrating photovoltaic (PV) power generation forecasting and load forecasting models into a home energy management system, and adjusting the original power usage schedule based on predicted PV output and water heater demand, can effectively reduce electricity costs and carbon emissions without compromising user engagement in optimization. This approach helps promote energy-saving and low-carbon electricity consumption habits among users. Full article

Focusing the over simplification of existing models in simulating river flow evolution process and lack of coordination of hydropower generation and export, this paper proposes a hydropower generation and export coordinated optimal operation model that, at the same time, incorporates dynamic water flow delay by finely modeling the water flow evolution process among cascade hydropower stations within a river basin. Specifically, firstly, a dynamic water flow evolution model is built based on the segmented Muskingum method. By dividing the river into sub-segments and establishing flow evolution equation for individual sub-segments, the model accurately captures the dynamic time delay of water flow. On this basis, integrating cascade hydropower systems and the transmission system, a hydropower generation and export coordinated optimal operation model is proposed. By flexibly adjusting the power export, the model balances local consumption and external transmission of hydropower, enhancing the utilization efficiency of hydropower resources and achieving high economic performance. A case study verified the accuracy of the dynamic water flow evolution model and the effectiveness of the proposed hydropower generation and export coordinated optimal operation model. Full article

Aiming at the economic problems of industrial users with wind power, photovoltaic, and small hydropower resources in clean energy consumption and trading with superior power grids, this paper proposes a distributed pumped storage capacity optimization configuration method considering clean energy systems. First, considering the maximization of the investment benefit of distributed pumped storage as the upper goal, a configuration scheme of the installed capacity is formulated. Second, under the two-part electricity price mechanism, combined with the basin hydraulic coupling relationship model, the operation strategy optimization of distributed pumped storage power stations and small hydropower stations is carried out with the minimum operation cost of the clean energy system as the lower optimization objective. Finally, the bi-level optimization model is solved by combining the alternating direction multiplier method and CPLEX solver. This study demonstrates that distributed pumped storage implementation enhances seasonal operational performance, improving clean energy utilization while reducing industrial electricity costs. A post-implementation analysis revealed monthly operating cost reductions of 2.36, 1.72, and 2.13 million RMB for wet, dry, and normal periods, respectively. Coordinated dispatch strategies significantly decreased hydropower station water wastage by 82,000, 28,000, and 52,000 cubic meters during corresponding periods, confirming simultaneous economic and resource efficiency improvements. Full article

Global building energy consumption is significantly increasing. Utilizing renewable energy sources may be an effective approach to achieving low-carbon and energy-efficient buildings. A combined system incorporating solar photovoltaic–thermal (PV/T) components with an air-source heat pump (ASHP) was studied for simultaneous heating and power generation in a real residential building. The back panel of the PV/T component featured a novel polygonal Freon circulation channel design. A prototype of the combined heating and power supply system was constructed and tested in Fuzhou City, China. The results indicate that the average coefficient of performance (COP) of the system is 4.66 when the ASHP operates independently. When the PV/T component is integrated with the ASHP, the average COP increases to 5.37. On sunny days, the daily average thermal output of 32 PV/T components reaches 24 kW, while the daily average electricity generation is 64 kW·h. On cloudy days, the average daily power generation is 15.6 kW·h; however, the residual power stored in the battery from the previous day could be utilized to ensure the energy demand in the system. Compared to conventional photovoltaic (PV) systems, the overall energy utilization efficiency improves from 5.68% to 17.76%. The hot water temperature stored in the tank can reach 46.8 °C, satisfying typical household hot water requirements. In comparison to standard PV modules, the system achieves an average cooling efficiency of 45.02%. The variation rate of the system’s thermal loss coefficient is relatively low at 5.07%. The optimal water tank capacity for the system is determined to be 450 L. This system demonstrates significant potential for providing efficient combined heat and power supply for buildings, offering considerable economic and environmental benefits, thereby serving as a reference for the future development of low-carbon and energy-saving building technologies. Full article

With the natural evolution of the Arctic route and advancements in related technologies, the development of new green ice-class ships is becoming a key technological breakthrough for the global shipbuilding industry. As a special vessel form that must perform icebreaking operations and undertake long-distance ocean voyages, an ice-class ship requires sufficient icebreaking capacity to navigate ice-covered water areas. However, since such ships operate for most of their time under open water conditions, it is also crucial to consider their resistance characteristics in these environments. Firstly, this paper employs linear interpolation to extract wind, wave, and sea ice data along the route and calculates the proportion of ice-covered and open water area in the overall voyage. This provides data support for hull form optimization based on real sea state conditions. Then, a resistance optimization platform for ice-class ships is established by integrating hull surface mixed deformation control within a scenario analysis framework. Based on the optimization results, comparative analysis is conducted between the parent hull and the optimized hull under various environmental resistance scenarios. Finally, the optimization results are evaluated in terms of energy consumption using a fuel consumption model of the ship’s main engine. The optimized hull achieves a 16.921% reduction in total resistance, with calm water resistance and wave-added resistance reduced by 5.92% and 27.6%, respectively. Additionally, the optimized hull shows significant resistance reductions under multiple wave and floating ice conditions. At the design speed, calm water power and hourly fuel consumption are reduced by 7.1% and 7.02%, respectively. The experimental results show that the hull form optimization process in this paper can take into account both ice-region navigation and ice-free navigation. The design ideas and solution methods can provide a reference for the design of ice-class ships. Full article

There is a consensus that climate change has affected society. The increase in temperature and reduction in precipitation for some regions of the world have had implications for the intensity and frequency of extreme events. This scenario is worrying for various sectors of water use, such as hydroelectric power generation and agriculture. Reduced flows in river basins, coupled with increased water consumption, can significantly affect energy generation and food production. Within this context, this paper presents an analysis of climate change impacts in a large basin of Brazil between the Amazon and Cerrado biomes, considering the effects of water demands. Inflow projections were generated for seven power plant reservoirs in the Tocantins–Araguaia river basin, using projections from five climate models. The results indicate significant reductions in flows, with decreases of more than 50% in the average flow. For minimum flows, there are indications of reductions of close to 85%. The demand for water, although growing, represents a smaller part of the effects, but should not be disregarded, since it impacts the dry periods of the rivers and can generate conflicts with energy production. Full article

This paper presents a method of evaluating energy and environmental factors before and after chilled water production system retrofitting at an industrial facility. A general algorithm was used for the analysis of chilled water system retrofitting at a pharmaceutics factory. Two retrofitting variants based on dual-stage absorption chillers supplied from an existing gas-fueled co-generation plant were identified. The proposed variants, i.e., tri-generation systems, were compared with the basic variant, which relied on electric compression water chillers. An evaluation of the variants was performed on the basis of two criteria: annual primary energy consumption and annual carbon dioxide emission. Variant 2, i.e., with a 1650 kW dual-stage absorption water chiller supplied from an existing gas fueled co-generation plant, was chosen as the optimal variant. It achieved a 370 MWh annual primary energy consumption reduction and a 1140 Mg annual carbon dioxide emission reduction. It was found that increasing the co-generation ratio for the CHP plant powering the pharmaceutical factory resulted in lower consumption of primary energy in variants in which the cooling energy supply system was retrofitted based on absorption water chillers. The threshold values of the co-generation ratio were e = 0.37 for Variant 1 and e = 0.34 for Variant 2. A literature survey revealed that there is limited interest in the application of such a solution in industrial plants. The performed analysis showed that the evaluated systems may nonetheless be an attractive option for pharmaceutics factories, leading to the reduction of primary energy consumption and carbon dioxide emissions, thereby making more electrical power available for core production. The lessons learned during our analysis could be easily transferred to other industrial facilities requiring chilled water production systems. Full article

Predicting water losses and final storage in reservoirs has become increasingly relevant in the efficient control and optimization of water provided to agriculture, livestock, industry, and domestic consumption, aiming to mitigate the risks associated with flash floods and water crises. This research aims to develop a new Machine Learning (ML) algorithm based on a water balance model to simulate the outflow in the Cuchoquesera reservoir in the Ayacucho region. The method uses TensorFlow (TF), a powerful interface for graphing and time series forecasting, for data analysis of hydrometeorological parameters (HMP), inflow (QE_obs), and outflow (QS_obs) of the reservoir. The ML water balance model is fed, trained, and calibrated with daily HMP, QE_obs, and QS_obs data from the Sunilla station. The results provide monthly forecasts of the simulated outflow (QS_sim), which are validated with QS_obs values, with significant validation indicators: NSE (0.87), NSE-Ln (0.83), Pearson (0.94), R² (0.87), RMSE (0.24), Bias (0.99), RVB (0.01), NPE (0.01), and PBIAS (0.14), with QS_obs being slightly higher than QS_sim. Therefore, it is important to highlight that water losses due to evaporation and infiltration increased significantly between 2019 and 2023. Full article