Groundwater contamination with per- and polyfluoroalkyl compounds (PFASs) has become a growing worldwide environmental issue. The current review comprehensively evaluates the global perspective of PFAS pollution in groundwater. Data from 224 recent research articles covering various land use and source types were reviewed, including industrial facilities, landfills, biosolids applications, and firefighting training sites. The bibliographic analysis shows an exponential increase in publications on PFAS pollution in groundwater in the last five years, with more than 50% coming from the USA, followed by Australia, Canada, China, and Sweden. The recent groundwater PFAS pollution research provides insight into the analytical techniques, absorbing materials, treatment strategies, field tests, and enhanced natural attenuation. Nevertheless, the current review identified significant research gaps in the areas of precursor characterization, subsurface behavior, model validation with field data, and long-term and sustainable solutions. Moreover, a global cross-disciplinary approach is required to reduce and regulate PFASs’ risks to humans and the ecological system. This review presents a case study of PFASs in Saudi Arabian groundwater, revealing elevated levels of PFOA and PFOS and highlighting the need for region-specific studies and remediation strategies. The review results will guide global efforts to protect drinking water supplies from life-threatening contaminants.

Efficient oil–water separation using membranes directly aligns with removing oil pollutants from water sources, promoting water quality. Hence, mitigating environmental harm from oil spills and contamination and fostering ecosystem health for sustainable development. Computational learning, such as artificial intelligence (AI), enhances membrane oil flux and separation efficiency by optimizing process parameters, leading to improved oil–water separation and aligning AI with sustainable environmental protection and resource efficiency solutions. This study employed phase-inversion coupled with sintering to create the ceramic membrane. The Stöber method was adopted to prepare the superhydrophobic silica sol-gel solutions. The data from the mentioned experiment were imposed into regression models, namely, multilinear regression analysis (MLR), support vector regression (SVR), and robust linear regression (RLR), to simulate three different scenarios (oil flux, separation efficiency, and oil flux and separation efficiency). The outcomes were validated and evaluated using several statistical (R², MSE, R, and RMSE) and graphical visualizations. For oil flux, the results show that the most effective simulation was achieved in SVR-M2 and the statistical criteria for the testing phase were R² = 0.9847, R = 0.9923, RMSE = 0.0333, and MSE = 0.0011. Similarly, SVR-M2 was superior to other modeling techniques for the separation efficiency in the testing phase (R² = 0.9945, R = 0.9972, RMSE = 0.0282, MSE = 0.0008). Reliability outcomes promise to revolutionize how we model and optimize membrane-based oil–water separation processes, with implications for various industries seeking sustainable and efficient solutions.

The potential of photocatalytic CO₂ conversion is significant for the production of fuels and chemicals, while simultaneously mitigating CO₂ emissions and addressing environmental concerns. Despite the current drawbacks of single metal-based photocatalysts, such as lower performance, uncontrollable selectivity, and instability, this study focuses on the synthesis of Ag₃VO₄ nanorods using the sol–gel method. The goal is to create a highly effective catalyst for visible light-responsive CO₂ conversion. The successful synthesis of Ag₃VO₄ nanorods with a nanorod structure, functional under visible light, resulted in the highest yields of CH₄ and dimethyl ether (DME) at 271 and 69 µmole/g-cat, respectively. The optimized Ag₃VO₄ nanorods demonstrated performance improvements, with CH₄ and DME production 6.4 times and 4.5 times higher than when using V₂O₅ samples. This suggests that Ag₃VO₄ nanorods facilitate electron transfer to CO₂, offer short pathways for electron transfer, and create empty spaces within the nanorods as electron reservoirs, enhancing the photoactivity. The prolonged stability of Ag₃VO₄ in the CO₂ conversion system confirms that the nanorod structure provides controllable selectivity and stability. Therefore, the fabrication of nanorod structures holds promise in advancing high-performance photocatalysts in the field of photocatalytic CO₂ conversion to solar fuels.