Search Results (27)

Against the backdrop of the steady advancement of the national rural revitalization strategy and the dual-carbon goals, the low-carbon transformation of rural energy systems is of critical importance. This study first proposes a comprehensive architecture for rural energy supply systems, incorporating four key dimensions: investment, system configuration, user demand, and policy support. Leveraging the abundant wind, solar, and biomass resources available in rural areas, a low-carbon optimization model for rural energy system operation is developed. The model accounts for diverse load characteristics and the integration of elevated water towers, which serve both energy storage and agricultural functions. The optimization framework targets the multi-energy demands of rural production and daily life—including electricity, heating, cooling, and gas—and incorporates the stochastic nature of wind and solar generation. To address renewable energy uncertainty, the Fisher optimal segmentation method is employed to extract representative scenarios. A representative rural region in China is used as the case study, and the system’s performance is evaluated across multiple scenarios using the Gurobi solver. The objective functions include maximizing clean energy benefits and minimizing carbon emissions. Within the system, flexible resources participate in demand response based on their specific response characteristics, thereby enhancing the overall decarbonization level. The energy storage aggregator improves renewable energy utilization and gains economic returns by charging and discharging surplus wind and solar power. The elevated water tower contributes to renewable energy absorption by storing and releasing water, while also supporting irrigation via a drip system. The simulation results demonstrate that the proposed clean energy system and its associated operational strategy significantly enhance the low-carbon performance of rural energy consumption while improving the economic efficiency of the energy system. Full article

The Qinghai–Tibet Plateau (QTP), a critical hydrological regulator for Asia through its extensive glacier systems, high-altitude lakes, and intricate network of rivers, exhibits amplified sensitivity to climate-driven alterations in precipitation regimes and ice mass balance. While the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have revolutionized monitoring of terrestrial water storage anomalies (TWSAs) across this hydrologically sensitive region, spatial resolution limitations (3°, equivalent to ~300 km) constrain process-scale analysis, compounded by mission temporal discontinuity (data gaps). In this study, we present a novel downscaling framework integrating temporal gap compensation and spatial refinement to a 0.25° resolution through Gated Recurrent Unit (GRU) neural networks, an architecture optimized for univariate time series modeling. Through the assimilation of multi-source hydrological parameters (glacier mass flux, cryosphere–precipitation interactions, and land surface processes), the GRU-based result resolves nonlinear storage dynamics while bridging inter-mission observational gaps. Grid-level implementation preserves mass conservation principles across heterogeneous topographies, successfully reconstructing seasonal-to-interannual TWSA variability and also its long-term trends. Comparative validation against GRACE mascon solutions and process-based hydrological models demonstrates enhanced capacity in resolving sub-basin heterogeneity. This GRU-derived high-resolution TWSA is especially valuable for dissecting local variability in areas such as the Brahmaputra Basin, where complex water cycling can affect downstream water security. Our study provides transferable methodologies for mountainous hydrogeodesy analysis under evolving climate regimes. Future enhancements through physics-informed deep learning and next-generation climatology–hydrology–gravimetry synergy (e.g., observations and models) could further constrain uncertainties in extreme elevation zones, advancing the predictive understanding of Asia’s water tower sustainability. Full article

Cooling water towers are commonly used in industrial and commercial applications. Industrial sites frequently have harsh environments, with certain characteristics such as poor air quality, close proximity to the ocean, large quantities of dust, or water supplies with a high mineral content. In such environments, the quality of electrical conductivity in the cooling water towers can be significantly negatively affected. Once minerals (e.g., calcium and magnesium) form in the water, conductivity becomes too high, and cooling water towers can become easily clogged in a short time; this leads to a situation in which the cooling water host cannot be cooled, causing it to crash. This is a serious situation because manufacturing processes are then completely shut down, and production yield is thus severely reduced. To solve these problems, in this study, we develop a practical designation for a photovoltaic industry company called Company-L. Three control methods are proposed: the motor control method, the PID control method, and the fuzzy PID control method. These approaches are proposed as solutions for successfully controlling the forced replenishment and drainage of cooling water towers and controlling the opening of proportional control valves for water release; this will further dilute the electrical conductivity and control it, bringing it to 300 µS/cm. In the experimental processes, we first used practical data from Company-L for our case study. Second, from the experimental results of the proposed model for the motor control method, we can see that if electrical conductivity is out of control and the conductivity value exceeds 1000 µS/cm, the communication software LINE v8.5.0 (accessible via smartphone) displays a notification that the water quality of the cooling water towers requires attention. Third, although the PID control method is shown to have errors within an acceptable range, the proportional (P) controller must be precisely controlled; this control method has not yet reached this precise control in the present study. Finally, the fuzzy PID control method was found to have the greatest effect, with the lowest level of errors and the most accurate control. In conclusion, the present study proposes solutions to reduce the risk of ice-water host machines crashing; the solutions use fuzzy logic and can be used to ensure the smooth operation of manufacturing processes in industries. Practically, this study contributes an applicable technical innovation: the use of the fuzzy PID control model to control cooling water towers in industrial applications. Concurrently, we present a three-tier monitoring checkpoint that contributes to the PID control method. Full article

Understanding the water and carbon cycles within terrestrial ecosystems is crucial for effective monitoring and management of regional water resources and the ecological environment. However, physical models like the SEB- and LUE-based ones can be complex and demand extensive input data. In our study, we leveraged multiple variables (vegetation growth, surface moisture, radiative energy, and other relative variables) as inputs for various regression algorithms, including Multiple Linear Regression (MLR), Random Forest Regression (RFR), and Backpropagation Neural Network (BPNN), to estimate water (ET) and carbon fluxes (NEE) in the Haihe River Basin, and compared the estimated results with the observations from six eddy covariance flux towers. We aimed to (1) assess the impacts of different input variables on the accuracy of ET and NEE estimations, (2) compare the accuracy of the three regression methods, including three machine learning algorithms and Multiple Linear Regression, and (3) evaluate the performance of ET and NEE estimation models across various regions. The key findings include: (1) Increasing the number of input variables typically improved the accuracy of ET and NEE estimations. (2) RFR proved to be the most accurate for both ET and NEE estimations among the three regression algorithms. Of these, the four types of variables used together with RFR resulted in the best accuracy for ET (R² of 0.81 and an RMSE of 1.13 mm) and NEE (R² of 0.83 and an RMSE of 2.83 gC/m²) estimations. (3) Vegetation growth variables (i.e., VIs) are the most important inputs for ET and NEE estimation. (4) The proposed ET and NEE estimation models exhibited some variation in accuracy across different validation sites. Despite these variations, the accuracy levels across all six validation sites remained relatively high. Overall, this study lays the groundwork for an efficient approach to agricultural water resources and ecosystem monitoring and management. Full article

When heating units are operated in winter, the extreme conditions, such as deep peak regulation and large extraction, can easily lead to a low unit load and severe icing in the wet cooling tower, which threatens the safe operation of the unit. Therefore, it is necessary to study the anti-freezing characteristics of the wet cooling tower. In this paper, a three-dimensional numerical model of a high-level, natural draft wet cooling tower is developed based on the constant heat load method. The influence of withdrawing a certain percentage of circulating water into the bypass on the cooling performance and anti-freezing characteristics of the high-level, natural draft wet cooling tower is investigated. The results show that as the percentage of circulating water bypass extraction increases, the temperature drop of circulating water in the tower continues to increase, but the lowest and the average water temperatures at the bottom of the packing continue to decrease. At the same time, the amount of circulating water entering the tower decreases, the pressure difference between the inside and outside of the tower under the same environmental conditions decreases, and the pumping force of the cooling tower decreases. If the circulating water bypass extraction percentage is less than 10%, it can prevent the circulating water from freezing at the bottom of the packing and, at the same time, try to reduce the temperature of the circulating water entering the condenser to ensure the efficiency of the unit. Full article

Thermal power units play a crucial role in the deep peak regulation of power generation. During deep peak regulation, the load of the unit changes significantly, causing fluctuations in the inlet water temperature of the cooling tower and the water temperature in the filler. Therefore, in cold regions in winter, cooling towers have a high risk of freezing, which threatens the economic and safe operation of the unit. This paper establishes a three-dimensional numerical model based on constant heat dissipation and explores the average and minimum water temperatures at the bottom of filler under different water distribution methods, crosswind velocities, and ambient temperatures. The results show that the water distribution method has a significant impact on the water temperature at the filler bottom. Reducing the water distribution area can significantly increase the minimum water temperature at the filler bottom and reduce the risk of freezing. Although the presence of crosswind is not conducive to the cooling performance of the cooling tower, the higher the crosswind velocity, the higher the minimum outlet water temperature at the filler bottom and the lower the risk of freezing. The minimum water temperature at the filler bottom is approximately linearly related to the ambient temperature and is less affected by the unit load at the same temperature. Full article

There is a height drop in the rain area of the circulating cooling water in mechanical ventilation circulating cooling towers, resulting in the ineffective use of gravitational potential energy. High-level water collection is an effective way to reduce the energy consumption of the cooling tower. Based on this, aiming to solve the gravity energy waste problem of circulating water in the cooling tower of a steel plant, this paper innovatively puts forward the high-level water tank to utilize the energy-saving transformation technology of turbine power generation and pump power saving. Additionally, this paper explores the energy-saving effects of the two methods under different height drops. The results show that the maximum utilizable rain area height of the cooling tower is 5 m, while the annual electric energy output of turbine technology can reach 4.704 million kW·h. The high water collection technology can reduce pump power consumption and save up to 7.35 million kW·h per year of electric energy, maintaining a more significant energy-saving ability compared with the turbine power generation technology. In terms of performance, the design of a high-level water tank is to help eliminate rain areas and improve the heat exchange efficiency of water and gas, so that the water temperature of the outgoing tower is 0.13 °C lower than that of the conventional cooling tower. Meanwhile, the ventilation resistance in the rain area is weakened, the resistance coefficient can be reduced by about 40–50%, and the noise can be reduced by about 10 dB (A) under the action of the water collection device. According to the economic evaluation, the total cost of turbine power generation technology is 0.563 million dollars and the total cost of high-level water collection technology is 0.446 million dollars. The cost can be realized within two years, but the high-level water collection technology avoids additional pump maintenance costs and has better economy. This study provides a theoretical basis for the transformation and optimization design of mechanical ventilation cooling towers, and has important reference value. Full article

Biological testing on the International Space Station (ISS) is necessary in order to monitor the microbial burden and identify risks to crew health. With support from a NASA Phase I Small Business Innovative Research contract, we have developed a compact prototype of a microgravity-compatible, automated versatile sample preparation platform (VSPP). The VSPP was built by modifying entry-level 3D printers that cost USD 200–USD 800. In addition, 3D printing was also used to prototype microgravity-compatible reagent wells and cartridges. The VSPP’s primary function would enable NASA to rapidly identify microorganisms that could affect crew safety. It has the potential to process samples from various sample matrices (swab, potable water, blood, urine, etc.), thus yielding high-quality nucleic acids for downstream molecular detection and identification in a closed-cartridge system. When fully developed and validated in microgravity environments, this highly automated system will allow labor-intensive and time-consuming processes to be carried out via a turnkey, closed system using prefilled cartridges and magnetic particle-based chemistries. This manuscript demonstrates that the VSPP can extract high-quality nucleic acids from urine (Zika viral RNA) and whole blood (human RNase P gene) in a ground-level laboratory setting using nucleic acid-binding magnetic particles. The viral RNA detection data showed that the VSPP can process contrived urine samples at clinically relevant levels (as low as 50 PFU/extraction). The extraction of human DNA from eight replicate samples showed that the DNA extraction yield is highly consistent (there was a standard deviation of 0.4 threshold cycle when the extracted and purified DNA was tested via real-time polymerase chain reaction). Additionally, the VSPP underwent 2.1 s drop tower microgravity tests to determine if its components are compatible for use in microgravity. Our findings will aid future research in adapting extraction well geometry for 1 g and low g working environments operated by the VSPP. Future microgravity testing of the VSPP in the parabolic flights and in the ISS is planned. Full article

The classical solar chimney offers passive electricity and water production at a low operating cost. However, the solar chimney suffers from high capital cost and low energy output density per construction area. The high capital investment increases the levelized cost of energy (LCOE), making the design less economically competitive versus other solar technologies. This work presents a new noteworthy solar chimney design for high energy density and maximizing water production. This was achieved by integrating a cooling tower with the solar chimney and optimizing the operating mood. The new design operated day and night as a hybrid solar double-chimney power plant (HSDCPP) for continuous electricity and water production. During the daytime, the HSDCPP operated as a cooling tower and solar chimney, while during the night, it operated as a cooling tower. The annual energy output from the cooling towers and solar chimney (i.e., the HSDCPP) totaled 1,457,423 kWh. The annual energy production from the cooling towers alone was 1,077,134 kWh, while the solar chimney produced 380,289 kWh. The annual energy production of the HSDCPP was ~3.83-fold greater than that of a traditional solar chimney (380,289 kWh). Furthermore, the HSDCPP produced 172,344 tons of fresh water per year, compared with zero tons in a traditional solar chimney. This led to lower overall capital expenditures maximizing energy production and lower LCOE. Full article

Rapid industrialization and urbanization have accelerated land-use changes in mountainous areas, with dramatic impacts on ecosystem health. In particular, the Qinling-Daba Mountains, as China’s central water tower, ecological green lung, and biological gene bank, have rich resource endowments and extremely high ecological value and are an important protective wall to China’s ecological security. Therefore, understanding the level of ecosystem health and its drivers in the research area contributes to the conservation and restoration of the mountain ecosystem. Based on remote sensing image data and land-use data from 2000 to 2020, we explored the spatial characteristics of ecosystem health, and supplemented with socio-economic data to explore its driving factors. The results show that (1) the ecosystem health in the study area has been continuously improved during the study period, and the regional differences in ecological organization are the most prominent; (2) the level of ecosystem health in the Qinling-Daba Mountains has been spatially improved from the peripheral areas to the central area, showing significant spatial autocorrelation and local spatial aggregation; (3) the ecosystem health is influenced by a combination of natural and anthropogenic factors, among which the negative effect of GRDP is mainly concentrated in the eastern region, the negative effect of the proportion of built-up land gradually spreads to the western region, and the positive effect of the proportion of forest land has a large scale. This study contributes to a better understanding of ecosystem health in mountainous counties in China and provides useful information for policymakers to formulate ecological and environmental management policies. Full article

Our modern society is becoming increasingly reliant on transportation networks, as well as the interdependent infrastructures and technologies that interact with them. The increasing complexity and interconnectedness of infrastructure networks make them susceptible to impact not only directly from external shocks but also indirectly from the failure of dependent infrastructures. This research study was conducted in Padang city, one of the most disaster-prone areas in Indonesia. Based on the literature review, it is no doubt that research study on seismic risk assessment is insufficient and outdated. In fact, a study about the interdependency between Critical Infrastructures (CIs) is yet to be done in this region. In this study, there are two approaches used for data gathering which is by surveying existing CIs using Google Earth and by an online questionnaire survey via Google Form. Based on the qualitative survey, a functionality rating method is done to obtain the level of outage/loss functionality which is an indicator for the damage occurred to the structure and infrastructure. Following that, a seismic risk analysis was conducted to assess the interdependency between investigated CIs and facilities. Respondents’ judgement from the questionnaire were used to identify the base criticality of each critical infrastructure. Based on the qualitative survey, the level of loss in functionality for the substation and the telecommunication tower is rated as “High”, but the loss in functionality for the water supply system is rated as “Moderate”. Moreover, the findings used from the respondents’ judgements were used to establish the initial level of criticality for each vital infrastructure. According to the findings, hospitals, power substations, and communication towers all have a criticality level of “5-Vital”, while police stations and fire stations both have a “3-medium” criticality rating. Eventually, the results of this assessment of interdependence are displayed in a criticality map, which shows how the interdependency relationship affects the initial criticality of a certain upstream infrastructure. Understanding the potential consequences of infrastructure failure, especially in regard to dependent infrastructures, can help emergency response teams formulate more targeted strategies for managing risks. As a consequence of this, the resilience of the wider community is improved, which contributes toward the implementation of Sustainable Development Goal (SDG) 11: Sustainable cities and communities particularly in reducing disasters and people in vulnerable situation. Full article

A field study was conducted in the Mojave Desert (USA) to assess the influence of a large photo voltaic facility on heat and water transport into an adjacent creosote (Larrea tridentata) bursage (Ambrosia dumosa) plant community. Air temperature, plant physiological status, soil water in storage and precipitation were monitored over a two to four year period. A service road built 27 years before the construction of the PV facility decoupled the wash system at the site leading to a significant decline in soil moisture, canopy level NDVI values and mid-day leaf xylem water potentials (p < 0.001) down gradient from the PV facility. Measurements along a 900 m gradient suggested that plants closer to where the wash was decoupled were placed under significantly greater stress during the higher environmental demand summer months. Air temperatures measured at three 10 m meteorological towers revealed warmer night time temperatures at the two towers located in close association with the solar facility (Inside Facility—IF and Adjacent to facility—AF), compared to the Down Gradient Control tower (DGC). As the warmer air was displaced down gradient, the temperature front advanced into the creosote—bursage plant community with values 5 to 8 °C warmer along an east west front just north of tower AF. Based on our research in Eldorado Valley, NV, USA, a down gradient zone of about 300 m was impacted to the greatest extent (water and heat), suggesting that the spacing between solar facilities will be a critical factor in terms of preserving high quality habitat for the desert tortoise and other species of concern. Greater research is needed to identify habitat zones acceptable for animal populations (especially the desert tortoise) within areas of high solar energy development and this should be done prior to any fragmentation of the ecosystem. Full article

On 16 September 2018, the Yangtze River Delta (YRD) experienced heavy precipitation, with the local daily precipitation exceeding 250 mm. Using ERA5 reanalysis data and satellite observations from the GPM, we review this heavy rain event in terms of its meteorological triggers and water vapor transport. As the high-level water vapor produced by Typhoon Mangkhut continued to be transported northward, the precipitation in the YRD gradually increased, and stratus precipitation played a major role in this event. The high-level water vapor continued to be transported northward to the east of Taiwan Island without falling, so heavy precipitation did not appear to the east of Taiwan Island. In the present study, we suggest that the meteorological trigger of this event was mainly the gradual falling of ice particles moving northward from a high altitude. The high-level ice particles originated from the “water tower” at the center of Typhoon Mangkhut, which pumped low-level water vapor into the high-level water vapor. In general, the appearance of abnormal values of high-level water vapor transport is an important atmospheric disturbance related to heavy precipitation in the downstream areas of high-level wind, and the typhoon water tower can be used as an important forecast signal for long-distance heavy precipitation in China during the active typhoon period. Full article

Based on the data from a French outbreak of legionellosis, a probabilistic approach was developed to analyze and assess the potential role of several suspected sources of contamination. Potential dates of exposure of all cases were determined using back-calculation, using two probability distribution functions to model incubation period. A probabilistic analysis and risk assessment were then used to determine the most probable sources of contamination for each wave of the outbreak. The risk assessment was based on parameters representing emission and dispersion of Legionella: level and duration of emission; aerosol dispersion capacity; and probability of potential exposure for each patient. Four types of facilities containing the Legionella epidemic strain were analyzed: cooling towers, aerated wastewater basins, high pressure water cleaners, and car wash stations. The results highlighted the potential role of an aerated wastewater basin in the outbreak in addition to cooling towers. The role of high-pressure water cleaners and car wash stations appeared to be non-significant. This study also reveals the lack of knowledge on facility parameters that can be useful for microbial risk assessments. This type of probabilistic analysis can be used to quantitatively assess the risk for various facilities in order to manage a legionellosis outbreak. Full article

Regarding the ice periods of the Yellow River, it is difficult to obtain ice data information. To effectively grasp the ice evolution process in the ice periods of the typical reach of the Yellow River, a fixed-point air-coupled radar remote monitoring device is proposed in this paper. The device is mainly composed of an air-coupled radar ice thickness measurement sensor, radar water level measurement sensor, temperature measurement sensor, high-definition infrared night vision instrument, remote switch control, telemetry communication machine, solar and wind power supply, lightning protection, and slewing arm steel tower. The integrated monitoring device can monitor ice thickness, water level, air temperature, ice surface temperature, and other related parameters in real time. At present, devices have obtained the ice change process of fixed points in ice periods from 2020 to 2021. Through a comparison with manual data, the mean error of the monitoring results of the water level and ice thickness was approximately 1 cm. The device realizes the real-time monitoring of ice thickness and water level change in the whole cycle at the fixed position. Through video monitoring, it can take pictures and videos regularly and realize the connection between the visual river and monitoring data. The research results provide a new model and new technology for hydrological monitoring in the ice periods of the Yellow River, which has broad application prospects. Full article