Understanding long-term microbial dynamics in semi-enclosed coastal systems is essential for evaluating wastewater-related impacts and informing management responses. This study applies an integrated nonparametric diagnostic framework to characterize seven years (2010–2016) of total coliform (TC) variability at two shoreline stations in Kuwait. Annual mean TC concentrations were analyzed using Mann–Kendall trend tests, Sen’s slope estimation, Pettitt change-point detection, percentile-based anomaly classification, and first-order decay modeling. Station S07 exhibited exceptionally high TC levels during 2010–2011, followed by a statistically significant change point and lower annual concentrations from 2012 onward. Trend diagnostics confirmed a significant downward trajectory, and decay modeling indicated rapid attenuation (λ = 0.327 year⁻1; half-life = 2.12 years). In contrast, station S09 remained consistently lower in magnitude, showed no clear structural shift, and displayed a slower but measurable long-term decline (λ = 0.188 year⁻1; half-life = 3.69 years). The analyses indicate contrasting annual contamination patterns between the two stations, with S07 reflecting a more dynamic, contamination-prone setting and S09 a comparatively stable, lower-intensity setting. Interpreted within the limits of annual summary data and restricted environmental covariate information, these findings provide a cautious basis for evaluating broad microbial contrasts in data-limited coastal systems and can guide future studies using higher-resolution observations.
Solar desalination has become a viable way to address the world's water shortage using renewable energy. This review comprehensively analyzes solar desalination systems to examine the several modified designs that can improve their efficiency. Incorporation of reflectors, wick materials, different types of fins, absorbers, solar collectors, and heat localization materials into the solar desalination system has been studied in detail. The incorporation of solar collectors with a desalination system provides the dual advantage, i.e., enhancing the water productivity and simultaneously producing the hot water which can be utilized for different household chores. A comparison of the efficiencies for different developed solar desalination systems with and without reflectors was also carried out. The use of nano-materials/biomaterials to enhance the performance of solar desalination systems and their impact on improving evaporation rates and overall system efficiency was also reviewed. To achieve the sustainable development goals through solar desalination, and comprehensive search for the bibliometric analysis has been carried out through the Scopus database. Furthermore, solar desalination potential for wastewater treatment is discussed, highlighting its feasibility for industrial and domestic applications. The review also explores the integration of artificial intelligence in optimizing system performance, predictive modelling, and process automation. This study provides a comprehensive evaluation of solar desalination systems, offering insights into scalable, cost-effective solutions and future direction for the sustainable management of water resources.
Dead oil viscosity is critical for modeling crude oil flow in porous media and pipelines, designing production facilities, and enhancing oil recovery. However, most dead oil viscosity models fail to consider the effects of asphaltene and resin content. This study introduces a novel nonlinear regression-based model that predicts dead oil viscosity as a function of temperature, API gravity, asphaltene content, and resin contents using a dataset of 357 experimental measurements obtained from three heavy oil samples and their reconstituted derivatives tested between 77-176 degrees F at atmospheric pressure. The saturates, aromatics, resins and asphaltenes (SARA) fractions of these oil samples were determined using thin-layer chromatography and validated with both automated SARA high-performance liquid chromatography and absorption spectroscopy following the Japan Petroleum Institute (JPI-5S-45-95) standards. The results confirm that variations in asphaltene and resin contents significantly influence oil viscosity. A new viscosity correlation was developed using 250 datasets for model training and validated with the remaining 107 datasets from the total dataset. By incorporating asphaltene and resin contents, the model demonstrates superior accuracy and reliability compared to 19 existing viscosity correlations. It achieved the lowest average absolute relative errors of 18.53 % and 20.83 % for the training and validation datasets, respectively, along with the highest coefficients of determination (R2 = 0.97 and 0.96). These findings indicate that the proposed model offers a more robust and accurate alternative for predicting dead oil viscosity, particularly for heavy oils where polar components play a critical role. This improved predictive capability can significantly enhance the accuracy of flow modeling, production system design, and enhanced oil recovery planning, especially in fields dealing with complex heavy oil systems.
Nanoporous carbon materials were synthesized from asphaltenes using a thermo-chemical treatment under an inert atmosphere and in-situ KOH activation. N-doping was also employed in certain samples to reveal the impact of nitrogen on the properties of materials. The synthesized materials were fully characterized to disclose their textural properties, structural parameters, surface functional groups, elemental compositions, and morphologies. Textural property analysis revealed a remarkable increase in surface areas after alkaline treatment (similar to 1500-2000 m(2)/g), which was mainly ascribed to the formation of micro- and mesopores. The measurements of structural parameters endorse and complement the findings on textural properties. The asphaltene-derived porous carbons have been employed in energy storage and carbon capture applications. The materials exhibit specific capacitances ranging from 130 to 180 F/g at 0.2 A/g in a 3 M KOH. These results suggest that nitrogen doping significantly enhances the pseudocapacitive behavior of the electroactive materials by promoting Faradaic redox reactions and improving ion diffusion and adsorption rates. Asphaltene-derived porous carbons also exhibit notable CO2 adsorption capacities of 3-4 mmol/g at 25 degrees C and 1 bar. Also, breakthrough experiments confirm that the N-doped material exhibits remarkable stability, reusability, and increased surface basicity, achieving an impressive CO2 uptake of 0.446 mmol/g. These results highlight the potential of asphaltene-based porous carbons as efficient materials for carbon capture and energy storage applications.
Here, we review compiled field evidence on Digital Twins and Edge AI for small off-grid water systems. We examined 28 studies from 2018-2025, including 19 peer-reviewed papers and 9 gray literature sources. All included works reported experimental pilots, edge deployments, or testbeds implemented in decentralized environments. Three reference architectures were identified: edge-only DTs for ultra-off-grid settings, federated DT networks for community-scale coordination, and hybrid edge-cloud DTs for intermittent connectivity. Common hardware included Raspberry Pi Zero, sub-$15 sensors, and ESP32, typically operating within 10-30 Wh/ day energy budgets powered by solar systems. Results consistently indicated that simplified models outperform complex alternatives. Reduced-order physics models form the foundation, and lightweight ML correctors make them adaptable. Deployed models remain static and are updated seasonally using Bayesian recalibration. Popular uses include atmospheric water harvesting, containerized wastewater treatment, leak detection, brackish water filtration, and small-scale irrigation. Empirical results across pilots were consistent: energy or water consumption dropped 18-40%, downtime or repair time fell by 27-55%, and component life grew by over four months. This review proposes a standard comparison tool for future studies, which identifies key nontechnical problems and presents a practical guide for field trials. We outline a research pathway for self-healing models, including discussions on shared standards, integration of social and technical aspects, and long-term testbed development. Researchers, policymakers, and NGOs may find clear, actionable steps for improving access to reliable and affordable water services in resource-limited areas.
