The presence of emerging water pollutants such as endocrine-disrupting compounds (EDCs), including 17-ethynylestradiol (EE2), bisphenol A (BPA), and perfluorooctanoic acid (PFOA), in contaminated water sources poses significant environmental and health challenges. This study aims to address this issue by investigating the efficiency of novel calcium-based metal-organic frameworks, known as mixed-linker calcium-based metal-organic frameworks (Ca-MIX), in adsorbing these endocrine-disrupting compounds. This study analyzed the influence of influent concentration, bed height, and flow rate on pollutant removal, with bed height emerging as a crucial factor. From the breakthrough curves, it was determined that the column maximum adsorption capacities followed the order of 17-ethynylestradiol (101.52 μg/g; 40%) > bisphenol A (99.07 μg/g; 39%) > perfluorooctanoic acid (81.28 μg/g; 32%). Three models were used to predict the adsorption process, with the Yan model outperforming the other models. This suggests the potential of mixed-linker calcium-based metal-organic frameworks for removing endocrine-disrupting compounds from water, using the Yan model as an effective predictor. Overall, this study provides valuable insights for the development of effective water treatment methods using mixed-linker calcium-based metal-organic frameworks to remove endocrine-disrupting compounds from contaminated water sources.
In toxicological analysis, the analytical validation method is important to assess the exact risk of contaminants of emerging concern in the environment. Syringe filters are mainly used to remove impurities from sample solutions. However, the loss of analyte to the syringe filter could be considerable, causing an underestimate of the analyte concentrations. The current study develops and validates simultaneous liquid chromatography-mass spectrometry analysis using a direct filtration method to detect four groups of contaminants of emerging concern. The adsorption of the analyte onto three different matrices and six types of syringe filters is reported. The lowest adsorption of analytes was observed in methanol (16.72%), followed by deionized water (48.19%) and filtered surface lake water (48.94%). Irrespective of the type of the matrices, the lowest average adsorption by the syringe filter was observed in the 0.45 μm polypropylene membrane (15.15%), followed by the 0.20 μm polypropylene membrane (16.10%), the 0.20 μm regenerated cellulose (16.15%), the 0.20 μm polytetrafluoroethylene membrane (47.38%), the 0.45 μm nylon membrane (64.87%) and the 0.20 μm nylon membrane (71.30%). In conclusion, the recommended syringe filter membranes for contaminants of emerging concern analysis are polypropylene membranes and regenerated cellulose, regardless of the matrix used.