Search Results (106)

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

The article describes an Arduino-based, portable, remotely usable weather monitoring station capable of measuring temperature, relative humidity, pressure, and carbon monoxide (CO) concentration and transmitting the collected data to the Cloud through the mobile telephony network. The main modules of the station are as follows: a DHT11 sensor for temperature and relative humidity sensing, a BMP180 sensor for pressure monitoring (with temperature compensation), a MQ7 sensor for the monitoring of the CO concentration, an Arduino Uno board, a GSM SIM900 module, and a buzzer, which is activated when the temperature exceeds 35 °C. The station operates as follows: the Arduino Uno board gathers the data collected by the sensors and, by means of the GSM SIM900 module, it transmits the data to the Cloud by using the mobile telephony network as well as the ThingSpeak software which is an open-code IoT application that, among others, enables saving and recovering of sensing and monitoring data. The main novelty of this work is the combined use of the GSM network and the Cloud which enhances the portability and usability of the proposed system and enables remote collection of data in a straightforward way. Additional merits of the system are the easiness and the low cost of its development (owing to the easily available, low-cost hardware combined with an open-code software) as well as its modularity and scalability which allows its customization depending on specific application it is intended for. The system could be used for real-time, remote monitoring of essential environmental parameters in spaces such as farms, warehouses, rooms etc. Full article

Smart cities are widely regarded as a promising solution to urbanization challenges; however, environmental aspects such as outdoor thermal comfort and urban heat island are often less addressed than social and economic dimensions of sustainability. To address this gap, we developed and evaluated an affordable, scalable, and cost-effective weather station platform, consisting of a centralized server and portable edge devices to facilitate urban heat island and outdoor thermal comfort studies. This edge device is designed in accordance with the ISO 7726 (1998) standards and further enhanced with a positioning system. The device can regularly log parameters such as air temperature, relative humidity, globe temperature, wind speed, and geographical coordinates. Strategic selection of components allowed for a low-cost device that can perform data manipulation, pre-processing, store the data, and exchange data with a centralized server via the internet. The centralized server facilitates scalability, processing, storage, and live monitoring of data acquisition processes. The edge devices’ electrical and shielding design was evaluated against a commercial weather station, showing Mean Absolute Error and Root Mean Square Error values of 0.1 and 0.33, respectively, for air temperature. Further, empirical test campaigns were conducted under two scenarios: “stop-and-go” and “on-the-move”. These tests provided an insight into transition and response times required for urban heat island and thermal comfort studies, and evaluated the platform’s overall performance, validating it for nuanced human-scale thermal comfort, urban heat island, and bio-meteorological studies. Full article

To study the mantle structure of the North China Craton (NCC) and its tectonic implications, in particular, the evolution of the rift systems in the Trans-North China Orogen (TNCO), we used teleseismic data recorded by 250 portable seismic stations to invert for the P-wave velocity (Vp) structures of the mantle beneath the NCC. Our results show a large-scale low-Vp anomaly in the shallow mantle and high-Vp anomalies in the deeper upper mantle beneath the eastern NCC, with fine-scale high-Vp anomalies at the lithosphere–asthenosphere boundary, indicating multi-stage lithospheric delamination during the Cenozoic. In the Yan Mountains (YanM), an east–west striking high-Vp anomaly between 60 to 200 km depths and low heat flow suggest the preservation of a thick mantle root. In the TNCO, high-Vp bodies in the upper mantle and the upper part of the mantle transition zone (MTZ) are imaged. The shallower high-Vp anomaly located beneath the Shanxi–Shaanxi Rift (SSR), along with an overlying local-scale low-Vp anomaly, indicates local hot material upwelling due to lithospheric root removal. The India–Eurasia collision’s far-field effects are proposed to cause lithospheric thickening, subsequent root delamination, and the formation and evolution of the SSR. Full article

Harnessing solar energy offers a sustainable alternative for powering electrolysis for green hydrogen production as well as wastewater treatment. The high costs and logistical challenges of electrolysis have resulted in limited widespread investigation and implementation of electrochemical technologies on an industrial scale. To overcome these challenges, this study designs and tests a new approach to chemical experiments and wastewater treatment research using a portable standalone open-source solar photovoltaic (PV)-powered station that can be located onsite at a wastewater treatment plant with unreliable electrical power. The experimental system is equipped with an energy monitoring data acquisition system. In addition, sensors enable real-time monitoring of gases—CO, CO₂, CH₄, H₂, H₂S, and NH₃—along with temperature, humidity, and volatile organic compounds, enhancing safety during electrochemical experiments on wastewater, which may release hazardous gases. SAMA software was used to evaluate energy-sharing scenarios under different grid-connected conditions, and the system can operate off the power grid for 98% of the year in Ontario, Canada. The complete system was tested utilizing a laboratory-scale electrolyzer (electrodes of SS316L, Duplex 2205, titanium grade II and graphite) with electrolyte solutions of potassium hydroxide, sulfuric acid, and secondary wastewater effluent. The electrolytic cell specifically developed for testing electrode materials and wastewater showed a Faraday efficiency up to 95% and an energy efficiency of 55% at STP, demonstrating the potential for use of this technology in future work. Full article

The isometric mid-thigh pull (IMTP) is a reliable method to assess lower limb isometric muscle strength. A portable device (FysioMeter C-station) could serve as a suitable alternative. The reliability and concurrent validity of the FysioMeter C-station have not been evaluated for the IMTP unilateral test. The aims of this study were to (1) examine the between-session reliability of the unilateral IMTP test for the left and the right legs using the C-station, and (2) explore the concurrent validity of these measures when compared to gold standard force plates (AMTI). Twenty healthy, recreationally active males (age: 23 ± 4 years, height: 1.81 ± 0.60 m, weight: 79.6 ± 10.8 kg) participated and completed test sessions one week apart. The participants performed the following: (i) three bilateral IMTPs on dual force plates (AMTI_BI); (ii) three unilateral IMTPs on each leg on a single force plate (AMTI_RIGHT, AMTI_LEFT); and (iii) three unilateral IMTPs on each leg on the C-station (CS_RIGHT, CS_LEFT). The peak force was measured in all the testing modalities and an Intraclass Correlation Coefficient (ICC) and Pearson Correlation Coefficient (PCC) were used to evaluate the reliability and validity. The C-station showed good between-session reliability for CS_LEFT (ICC = 0.84) and CS_RIGHT (ICC = 0.85). A strong concurrent validity (PCC ≥ 0.82) was found for the C-station compared to the gold standard (AMTI). The C-station appears to be reliable for measuring unilateral IMTP in recreationally active males. Furthermore, strong concurrent validity of the C-station compared to the gold standard was demonstrated. Full article

Increasing demand for clean energy power generation is a direct result of the rapid depletion of fossil fuel reserves, the volatility of fossil commodity prices, and the environmental damage caused by burning fossil fuels. Fuel cell vehicles, portable power supplies, stationary power stations, and submarines are just some of the applications where proton exchange membrane (PEM) fuel cells are a prominent technology for power generation. PEM fuel cells have several advantages over conventional power sources, including a higher power density, lower emissions, a lower operating temperature, higher efficiency, noiseless operation, ease of design, and operation. The catalyst layer of the membrane electrode assembly is discussed in this paper as a vital part of the proton exchange membrane fuel cell. Along with that, the platinum (Pt)-based catalyst, carbon support, and nafion ionomer found in the catalyst layer often degrade. Catalyst growth, agglomeration, Pt loss, migration, active site contamination, and other microscopic processes are all considered in the degradation process. Employing experimental and numerical research with a focus on enhancing the material properties was suggested as a possible solution to understanding the problem of catalyst layer degradation. Ultimately, this review aims to prevent catalyst layer degradation and lower the high costs associated with replacing catalysts in proton exchange membrane fuel cells through the recommendations provided in this study. Full article

Air pollution remains a critical global health concern, with 91% of the world’s population exposed to air quality exceeding World Health Organization (WHO) standards and indoor pollution causing approximately 3.8 million deaths annually due to incomplete fuel combustion. Subways, as major public transportation modes in densely populated cities, can exhibit fine particulate matter (PM) levels that surpass safety limits, even in developed countries. Contributing factors include station location, ambient air quality, train frequency, ventilation efficiency, braking systems, tunnel structure, and electrical components. While elevated PM levels in underground platforms are recognized, the vertical and horizontal variations within stations are not well understood. This study examines the vertical and horizontal distribution of PM2.5 and PM10 levels at Shibuya Station, a structurally complex hub in the Tokyo Subway System. Portable sensors were employed to measure PM concentrations across different platform levels—both above and underground—and at various locations along the platforms. The results indicate that above-ground platforms have significantly lower PM2.5 and PM10 levels compared to underground platforms (17.09 μg/m³ vs. 22.73 μg/m³ for PM2.5; 39.54 μg/m³ vs. 56.98 μg/m³ for PM10). Notably, the highest pollution levels were found not at the deepest platform but at the one with the least effective ventilation. On the same platform, PM levels varied by up to 63.72% for PM2.5 and 120.23% for PM10, with elevated concentrations near the platform extremities compared to central areas. These findings suggest that ventilation efficiency plays a more significant role than elevation in vertical PM variation, while horizontal differences are likely influenced by piston effects from moving trains. This study underscores the risk of exposure to unsafe PM2.5 levels in underground platforms, particularly at platform extremities, highlighting the need for improved ventilation strategies to enhance air quality in subway environments. Full article

Lowcost sensors are widely used for air quality monitoring due to their affordability, portability and easy maintenance. However, the performance of such sensors, such as PurpleAir Sensors (PAS), is often affected by changes in environmental (e.g., temperature and humidity) or emission conditions, and hence the resulting measurements require corrections to ensure accuracy and validity. Traditional correction methods, like those developed by the USEPA, have limitations, particularly for applications to geographically diverse settings and sensors with no collocated referenced monitoring stations available. This study introduces BaySurcls, a Bayesianoptimised surrogate model integrating deep learning (DL) algorithms to improve the PurpleAir sensor PM2.5 (PAS2.5) measurement accuracy. The framework incorporates environmental variables such as humidity and temperature alongside aerosol characteristics, to refine sensor readings. The BaySurcls model corrects the PAS2.5 data for both collocated and noncollocated monitoring scenarios. In a case study across multiple locations in New South Wales, Australia, BaySurcls demonstrated significant improvements over traditional correction methods, including the USEPA model. BaySurcls reduced root mean square error (RMSE) by an average of 20% in collocated scenarios, with reductions of up to 25% in highvariation sites. Additionally, BaySurcls achieved Nash–Sutcliffe Efficiency (NSE) scores as high as 0.88 in collocated cases, compared to scores below 0.4 for the USEPA method. In noncollocated scenarios, BaySurcls maintained NSE values between 0.60 and 0.78, outperforming standalone models. This improvement is evident across multiple locations in New South Wales, Australia, demonstrating the model’s adaptability. The findings confirm BaySurcls as a promising solution for improving the reliability of lowcost sensor data, thus facilitating its valid use in air quality research, impact assessment, and environmental management. Full article

This study evaluates the performance of the ZEB Horizon RT portable mobile laser scanner (MLS) in simulating silvicultural thinning operations across three different Tuscan forests dominated by Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), Italian cypress (Cupressus sempervirens L.), and Stone pine (Pinus pinea L.). The aim is to compare the efficiency and accuracy of the MLS with traditional dendrometric methods. The study established three marteloscopes, each covering a 50 m × 50 m plot area (0.25 ha). Traditional dendrometric methods involved a team georeferencing trees using a total station and measuring the diameter at breast height (DBH) and selected tree heights (H) to calculate the growing stock volume (GSV). The MLS survey was carried out by a two-person team, who processed the point cloud data with LiDAR 360 software to automatically identify the tree positions, DBH, and H. The methods were compared based on the time, cost, and simulated felling volume. The MLS method was more time-efficient, saving nearly one and a half hours per marteloscope, equivalent to EUR 170. This advantage was most significant in denser stands, especially the Italian cypress forest. Both methods were comparable in terms of accuracy for Douglas-fir and Stone pine stands, with no significant differences in felling number or volume, although greater differences were noted for the Italian cypress forest. Full article

Diagnostics often require specialized equipment and trained personnel in laboratory settings, creating a growing need for point-of-care tests (POCTs). Among the genetic testing methods available, Loop-mediated Isothermal Amplification (LAMP) offers a viable solution for developing genetic POCT due to its compatibility with simplified devices. This study aimed to create a genetic test that integrates all steps from sample processing to analyzing results while minimizing the complexity, handling, equipment, and time required. Several challenges were addressed to achieve this goal: (1) the development of a buffer for bacterial DNA extraction that is compatible with both LAMP and immunochromatographic tests; (2) the adaption of the LAMP protocol for use with the SPID device; and (3) the optimization of the detection protocol for specific test conditions, with a lateral flow immunoassay format selected for its POCT compatibility. Following these developments, the test was validated using Escherichia coli (E. coli) and non-E. coli strains. A portable heating station was also developed to enable amplification without costly equipment. The resulting genetic POCT achieved 100% sensitivity and 85% specificity, with results available in 60 to 75 min. This study demonstrated that our POCT efficiently performs DNA extraction, amplification, and detection for bacterial identification. The test’s simplicity and cost-effectiveness will support its implementation in various settings. Full article

Field positioning (FP) is a key technique in the digitalization of agriculture. By integrating sensors and mapping techniques, FP can convey critical information such as soil quality, plant distribution, and topography. Utilizing vehicles for field applications provides precise control and scientific management for agricultural production. Compared to conventional methods, which often struggle with the complexities of field conditions and suffer from insufficient accuracy, this study employs a novel approach using self-developed multi-sensor array hardware as a portable field topographic surveying device. This innovative setup effectively navigates challenging field conditions to collect raw data. Data fusion is carried out using the Unscented Kalman Filter (UKF) algorithm. Building on this, this study combines the good point set and Opposition-based Differential Evolution for a joint improvement of the Slime Mould Algorithm. This is linked with the UKF algorithm to establish loss value feedback, realizing the adaptive parameter adjustment of the UKF algorithm. This reduces the workload of parameter setting and enhances the precision of data fusion. The improved algorithm optimizes parameters with an efficiency increase of 40.43%. Combining professional, mapping-grade total stations for accuracy comparison, the final test results show an absolute error of less than 0.3857 m, achieving decimeter-level precision in field positioning. This provides a new application technology for better implementation of agricultural digitalization. Full article

Solar energy can mitigate the power supply shortage in remote regions for portable irrigation systems. The accurate prediction of solar irradiance is crucial for determining the power capacity of photovoltaic power generation (PVPG) systems for mobile sprinkler machines. In this study, a prediction method is proposed to estimate the solar irradiance of typical irrigation areas. The relation between meteorological parameters and solar irradiance is studied, and four different parameter combinations are formed and considered as inputs to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict solar radiation. The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. The differences between the prediction performances of models trained based on single-station data and mixed data from multiple stations are also compared. The obtained results show that the proposed model achieves the highest prediction accuracy when the maximum temperature, minimum temperature, sunshine hours ratio, relative humidity, wind speed, and extraterrestrial radiation are used as input parameters. In the model testing, the RMSE and MAE of WOA-XGBoost are 2.142 MJ·m⁻²·d⁻¹ and 1.531 MJ·m⁻²·d⁻¹, respectively, while those of XGBoost are 2.298 MJ·m⁻²·d⁻¹ and 1.598 MJ·m⁻²·d⁻¹. The prediction effectiveness is also verified based on measured data. The WOA-XGBoost model has higher prediction accuracy than the XGBoost model. The model developed in this study can be applied to forecast solar irradiance in different regions. By inputting the meteorological parameter data specific to a given area, this model can effectively produce accurate solar irradiance predictions for that region. This study provides a foundation for the optimization of the configuration of PVPG systems for mobile sprinkler machines. Full article

This article is about better wireless network connectivity. The main goal is to provide wireless service to several use cases and scenarios that may not be adequately covered today. Some of the considered scenarios are home connectivity, street-based infrastructure, emergency situations, disaster areas, special event areas, and remote areas that suffer from problematic/inadequate network and possibly power infrastructure. A target system that we consider for such scenarios is that of an energy-efficient self-backhauled base station (also called a “portable access point—PAP”) that is mounted on a drone to aid/expand the land-based network. For the wireless backhaul link of the PAP, as well as for the fronthaul of the street-mounted base station, we consider newly built multi-active/multi-passive parasitic antenna arrays (MAMPs). These antenna systems lead to increased range/signal strength with low hardware complexity and power needs. This is due to their reduced number of radio frequency chains, which decreases the cost and weight of the base station system. MAMPs can show a performance close to traditional multiple input/multiple output (MIMO) systems that use as many antenna elements as RF chains and to phased arrays. They can produce a directional beam in any desired direction with higher gain and narrow beamwidth by just tuning the load values of the parasitic elements. The MAMP is designed based on radiation conditions which were produced during the research to ensure that the radiation properties of the array were good. Full article

This study considered using insect families as bioindicators to establish the health status of an ecosystem of lentic bodies. The water quality in urban lentic bodies in the Metropolitan Region, Chile, was evaluated from aquatic insect family assemblages and physicochemical variables for conserving aquatic life. Evaluations were carried out in parallel at four sampling stations of three water bodies (Batuco Wetland, Carén Lagoon, and Chada Reservoir) in a 2–3-year series, spring (2015, 2017, and 2018) and fall (2016 and 2018), with three replicates. Families were randomly sampled and aquatic insects were identified; abundance and richness differences were compared with non-parametric tests. Physicochemical variables were measured using portable multiparametric and laboratory chemical analyses to determine the water quality. A Canonical Correspondence Analysis was applied for insect families and the physical–chemical variable. In order to categorize the health of these water bodies based on aquatic insect composition and abundance, the Family Biotic Index (FBI), British Biological Monitoring Work Party (BMWP), and Stream Invertebrate Grade Number—Average Level (SIGNAL), adapted for Chile by Figueroa et al. (2007), were calculated. The eudominant insect families were Corixidae and Chironomidae in Batuco, Chironomidae and Corixidae in Carén, and Corixidae in Chada. Baetidae was dominant in Carén and Chada. The water bodies were classified in descending order of water quality by Chilean physicochemical standards: Chada > Carén > Batuco. The TSS (total suspended solids), phosphorus, and electrical conductivity were strongly positively correlated and negatively associated with dissolved oxygen. The TSS level was the most significant influential factor. The BMWP value and the SIGNAL differed from the FBI, but the first was more restrictive, contributing to the conservation of these ecosystems. Based on the nitrogen and phosphorus levels in the water bodies, all of them were eutrophic. Given the ecosystem diversity and complexity, studies should delve deeper into wetlands to establish methods that contribute to determining water quality, using insect families as bioindicators and physicochemical variables. Full article