The occurrence of sand and dust storms (SDSs) is essential for the geochemical cycling of nutrients; however, it is considered a meteorological hazard common to arid regions because of the adverse impacts that SDSs brings with them. One common implication of SDSs is the transport and disposition of aerosols coated with anthropogenic contaminants. Studies have reported the presence of such contaminants in desert dust; however, similar findings related to ubiquitous emerging contaminants, such as per- and poly-fluoroalkyl substances (PFAS), have been relatively scarce in the literature. This article reviews and identifies the potential sources of dust-associated PFAS that can accumulate and spread across SDS-prone regions. Furthermore, PFAS exposure routes and their toxicity through bioaccumulation in rodents and mammals are discussed. The major challenge when dealing with emerging contaminants is their quantification and analysis from different environmental media, and these PFAS include known and unknown precursors that need to be quantified. Consequently, a review of various analytical methods capable of detecting different PFAS compounds embedded in various matrices is provided. This review will provide researchers with valuable information relevant to the presence, toxicity, and quantification of dust-associated PFAS to develop appropriate mitigation measures.
Zeolitic imidazolate frameworks (ZIFs) are increasingly gaining attention in many application fields due to their outstanding porosity and thermal stability, among other exceptional characteristics. However, in the domain of water purification via adsorption, scientists have mainly focused on ZIF-8 and, to a lesser extent, ZIF-67. The performance of other ZIFs as water decontaminants is yet to be explored. Hence, this study applied ZIF-60 for the removal of lead from aqueous solutions; this is the first time ZIF-60 has been used in any water treatment adsorption study. The synthesized ZIF-60 was subjected to characterization using FTIR, XRD and TGA. A multivariate approach was used to investigate the effect of adsorption parameters on lead removal and the findings revealed that ZIF-60 dose and lead concentration are the most significant factors affecting the response (i.e., lead removal efficiency). Further, response surface methodology-based regression models were generated. To further explore the adsorption performance of ZIF-60 in removing lead from contaminated water samples, adsorption kinetics, isotherm and thermodynamic investigations were conducted. The findings revealed that the obtained data were well-fitted by the Avrami and pseudo-first-order kinetic models, suggesting that the process is complex. The maximum adsorption capacity (qmax) was predicted to be 1905 mg/g. Thermodynamic studies revealed an endothermic and spontaneous adsorption process. Finally, the experimental data were aggregated and used for machine learning predictions using several algorithms. The model generated by the random forest algorithm proved to be the most effective on the basis of its significant correlation coefficient and minimal root mean square error (RMSE).
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