Bassam Tawabini

The growing global demand for clean and sustainable energy has increased interest in hydrogen as an alternative fuel that is both affordable and widely accessible. While substantial research has focused on hydrogen generation through serpentinization, the potential of organic-rich systems remains largely unexplored. Addressing this gap requires systematic analysis of various organic-rich materials such as shale, carbonate rocks, and coal to evaluate their capacity to release hydrogen gas under different geological conditions. Such investigations could significantly advance our understanding of their roles in natural hydrogen systems. This study investigates the hydrogen generation potential of selected organic-rich rock samples through pyrolysis experiments conducted under controlled laboratory conditions. The samples were analyzed using X-ray diffraction (XRD), X-ray fluorescence (XRF), Rock-Eval pyrolysis, Thermogravimetric analysis (TGA), and Fourier transform infrared (FTIR), while the evolved gases were analyzed using gas chromatography (GC). Hydrogen yields ranged from 0.22 to 0.71 mg/g rock, with TOC-normalized yields between 4.2 and 29.4 mg/g TOC for all of the samples. Shale exhibited the highest hydrogen index (HI) of 885 mgHC/gTOC and contained type II kerogen, while coal, despite its high TOC of about 30.71%, produced lesser hydrogen gas with an HI of 387 mgHC/gTOC. TGA and FTIR analyses confirmed the progressive decomposition of organic functional groups associated with the release of hydrogen-rich gases. These findings suggest that organic-rich sedimentary formations, particularly those overlain by low-permeability caprocks such as tight shale, mudstone, or evaporites, may contribute to natural hydrogen systems and support hydrogen retention under favorable geological conditions.

In this study, polymer-functionalized carbon nanofibers (PNCNF) were developed from agricultural palm waste through nitrogen-assisted pyrolysis (600–700 °C), and in situ graft polymerization of acrylamide and N-(aminopropyl)acrylamide. The grafting process introduced amide- and amine-rich functional groups onto the carbon framework, providing chemically active sites for interactions with lamotrigine (LTG), an emerging pharmaceutical contaminant. TGA, XRD, FTIR, SEM, and TEM characterizations were used to identify the physicochemical properties of the PNCNF. Polymer functionalization dramatically enhanced the affinity of the carbon nanofibers toward LTG: under screening conditions of 20 mg/L LTG, 0.25 g/L adsorbent dosage, and 24 h contact time, PNCNF achieved 78.2% removal, whereas the unmodified CNF removed <1%, demonstrating the significant contribution of the introduced surface functionalities. The effects of pH (5–9), PNCNF dosage (0.1–0.3 g/L), and LTG concentration (10–50 mg/L) were systematically evaluated using Response surface method RSM with a central composite design CCD. A reduced cubic response-surface model adequately described the experimental response (R² = 0.9008) and identified solution pH as the most influential parameter. Adsorption kinetics were best described by the pseudo-second-order model (R² = 0.9464), with an equilibrium adsorption capacity of 63.11 mg/g, while equilibrium data followed the Langmuir model (R² = 0.9726), yielding a maximum monolayer capacity of 90.66 mg/g. An artificial neural network further demonstrated good predictive performance (overall R² = 0.936), supporting data-driven prediction of adsorption behavior. A preliminary production-cost estimate of 2.2 USD/g further indicated the potential practical applicability of the PNCNF. The findings demonstrate that polymer grafting transforms biomass-derived carbon nanofibers into a functional material, highlighting the potential of polymer-modified carbon materials for contaminant removal and related separation applications.

The decarbonization of hard-to-abate sectors remains a significant challenge in achieving net-zero emissions targets. These industries depend on energy-dense fuels, making direct electrification and the direct use of hydrogen technically and economically challenging. Electrofuels present a promising pathway to reducing emissions while leveraging surplus renewable energy. This review evaluates the feasibility of electrofuels for deep decarbonization, focusing on production processes, energy demands, and economic viability. Environmental performance is discussed in terms of lifecycle greenhouse gas (GHG) emissions, carbon circularity considerations, and energy conversion efficiencies, while techno-economic feasibility is evaluated using metrics such as levelized cost of hydrogen (LCOH), CO₂ capture costs, and projected fuel production costs. The review indicates that while electrofuels can achieve substantial lifecycle emission reductions up to 40–90%, depending on pathway and electricity source, their deployment remains constrained by high energy demand, conversion losses, and capital costs. Projected reductions in LCOH to below $2.1/kg by 2030 and declining renewable electricity costs could significantly improve competitiveness, particularly in regions with abundant solar and wind resources. However, substantial trade-offs exist between efficiency, infrastructure compatibility, scalability, and carbon neutrality across different electrofuel routes. The review identifies key technological bottlenecks, cost drivers, and research priorities necessary to position electrofuels as a strategic solution for deep decarbonization in sectors where direct electrification is not feasible.

Groundwater resources worldwide are under increasing stress, particularly in arid and semi-arid regions. Urbanisation, intensive agriculture, and industrial development place heavy pressure on the fossil groundwater, resulting in depletion of major aquifers worldwide, with more severe consequences in arid regions such as Saudi Arabia. This study aims to evaluate the feasibility of Treated Wastewater (TWW) for sustainable managed aquifer recharge (MAR) in the eastern coastal region of Saudi Arabia using an experimental approach. Twelve 1D MAR experiments were conducted to assess the efficiencies of various treated wastewater effluents for groundwater replenishment in the coastal sandy aquifer in the eastern region of Saudi Arabia. Three recharge scenarios (low, medium, and high) and two types of TWW (tertiary and secondary) were evaluated to optimise the MAR system. Clogging materials and water quality change were evaluated to determine the optimal recharge scenario. The results showed that the tertiary treated wastewater with low recharge scenarios was the optimal case with minimal impact on groundwater quality and aquifer integrity. In contrast, the high recharge scenarios with either tertiary or secondary treated wastewater showed a significant reduction in the hydraulic performance of aquifer materials, thus, the efficiency of the recharge system. The study found that the tertiary treated wastewater from the eastern region of Saudi Arabia is suitable for aquifer recharge with minimal pretreatment to remove nutrients, ions, and emerging contaminants (e.g., microplastics). The study findings provide insights into effective water resource management strategies that reduce water scarcity risks and strengthen long-term water security in arid environments. Moreover, the study demonstrated that implementing MAR with TWW can reduce non-renewable groundwater withdrawals by up to 30% in eastern Saudi Arabia, mitigating aquifer depletion and ensuring a more sustainable water supply.

The global pursuit of clean and sustainable energy has increased interest in hydrogen as a key energy carrier for achieving carbon neutrality. Consequently, global demand for hydrogen is anticipated to grow significantly in both the near and long term, necessitating the development of hydrogen production methods. While several researches have examined hydrogen generation through inorganic processes such as serpentinization, the potential of organic-rich sedimentary formations remains underexplored. This study investigates hydrogen-rich gas generating potential and fracture evolution of organic-rich rocks, with a particular focus on immature shales under controlled thermal treatment, aiming to enhance the yield of clean hydrogen gas. Pyrolysis experiments were conducted to simulate subsurface geological conditions, supported by comprehensive characterization using X-ray diffraction (XRD), X-ray fluorescence (XRF), thermogravimetric analysis (TGA). Gas Chromatography (GC) was used to analyze the gases generated at various heating temperatures and micro-CT imaging was used to examine the samples subjected to varying temperatures. The results show that hydrogen generation increases with temperature, with yields rising from 0.31% at 100°C to 36.02% at 450°C. High-resolution micro-CT imaging shows that thermally induced fractures developed predominantly parallel to bedding planes, enhancing permeability and facilitating gas migration. The progressive decomposition of organic matter, coupled with fracture development, significantly improved hydrogen release efficiency. These findings highlight the potential of organic-rich rocks, as viable and cost-effective targets for natural hydrogen exploration and in situ hydrogen gas generation and offering a pathway toward sustainable subsurface hydrogen exploitation strategies.

While desalination is indispensable for freshwater security in arid regions, the ecological consequences of hypersaline brine discharge remain a concern. This study assesses the environmental conditions and benthic foraminiferal response near the Al-Dur Power and Desalination Plant in Bahrain, western Arabian Gulf. By analyzing physico-chemical parameters in water and sediment along a spatial gradient, we utilized foraminiferal community composition, diversity indices, and test preservation as proxies for environmental stress. Proximal to the discharge, we observed extreme hypersalinity (above 40 psu), reduced pH, and elevated concentrations of total organic carbon and heavy metals. These conditions correspond to a significant decline in biological status: living assemblages near the outflow exhibited reduced abundance and lower Shannon diversity (less than 2) compared to reference sites (above 2). Additionally, test discoloration, a key stress indicator, affected more than 50% of specimens near the discharge, versus lower than 50% at downstream sites. Our results delineate a localized impact zone where, despite the persistence of stress-tolerant taxa such as Ammonia, Elphidium, and Peneroplis, overall biodiversity is markedly reduced. As the first record of desalination-driven impacts on foraminifera in the western Arabian Gulf, this research provides a vital baseline and emphasizes the need for targeted mitigation strategies to protect vulnerable marine ecosystems amidst expanding desalination infrastructure.

Air quality degradation poses significant risks to human health and ecosystems, particularly in rapidly urbanizing and industrialized arid regions. Meteorological conditions strongly influence the formation, transport, and dispersion of air pollutants, yet their relationships are highly nonlinear and difficult to quantify using conventional statistical approaches. This study investigates the influence of meteorological parameters on key air pollutants in the Eastern Region of Saudi Arabia using machine learning techniques. Five years of observational data (2017–2021), including temperature, humidity, wind speed, wind direction, dew point, and atmospheric pressure, were analyzed alongside concentrations of nitrogen dioxide (NO₂), carbon monoxide (CO), and particulate matter (PM₁₀). Four machine learning algorithms including Neural Networks (NN), Decision Trees (DT), Random Forests (RF), and Gradient Boosting (GB) were evaluated using standard performance metrics; mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and the coefficient of determination (R²). The results indicate that meteorological parameters exert pollutant-specific influences. The GB model achieved the highest predictive accuracy for NO₂ (R² ≈ 0.83), highlighting the dominant role of humidity, dew point, and seasonal variation. Moderate predictive performance was observed for CO (R² ≈ 0.46), suggesting a combined influence of meteorology and emission-driven processes. In contrast, PM₁₀ exhibited weak correlations with meteorological variables, reflecting the dominance of episodic dust events and non-meteorological factors in arid environments. These findings demonstrate the effectiveness of ensemble machine learning models in capturing nonlinear meteorological-pollutant relationships. The study provides valuable insights for air quality forecasting and supports data-driven environmental management in arid and semi-arid regions.

Groundwater (GW) is a vital source of freshwater worldwide. However, the increasing occurrence of pharmaceutical contaminants originating from various anthropogenic activities, posing significant health risks. This study investigates the efficiency of using colloidal activated carbon (CAC) in- removing carbamazepine (CBZ), lamotrigine (LTG), and caffeine (CAF) under a simulated in-situ remediation of groundwater. The study conducted through a series of fixed-bed column experiments. Several characterization techniques, including SEM/EDX, BET surface area, particle size distribution, and zeta potential, were used to identify the physiochemical properties of the CAC. Water samples spiked with a mixture of the three pharmaceutical compounds were allowed to pass through a column filled with a mixture of a bed and CAC materials. Inflow and outflow concentrations of the pharmaceuticals were measured by High-Performance Liquid Chromatography (HPLC) system. The effect of several parameters on the removal efficiency were investigated, including water flow rate, inlet concentration, CAC dosage, and bed type. SEM/EDX results revealed that CAC has a porous surface with 95.68% carbon and 4.32% potassium. The CAC has a surface area of 1112.24 m²/g, particle size ranges between 6.68 and 39.44 μm, and a negative surface charge. The optimal Dose-Response model breakthrough curve was developed at a flow rate of 1 mL/min, 2 g CAC, an initial concentration of 20 mg/L, and 50:50 sand-carbonate mixture showed a removal efficiency of around 40% of the pharmaceuticals. The study demonstrates that the use of colloidal activated carbon adsorption is a promising technology for the in-situ remediation of groundwater contaminated with pharmaceuticals.