Removal and pre-concentration of phenolic species onto beta-cyclodextrin modified poly(hydroxyethylmethacrylate-ethyleneglycoldimethacrylate) microbeads

Poly(Hydroxyethylmethacrylate-Ethyleneglycoldimethacrylate), poly(HEMA-EGDMA), microbeads with 150-200 microm in size, was prepared by suspension polymerization. Beta-cyclodextrin was modified onto the polymeric microbeads using glutaraldahyde activation in an acidic medium at pH=2.5. FT-IR and TGA were used for the characterization of modified polymers and the determination of the nature of the interaction between phenolic compounds and the modified polymeric microbeads. Plain and beta-cyclodextrin modified microbeads were used in adsorption-desorption studies of phenolic species in single solution. Adsorption capacities of the phenolic species onto the plain microbeads were found to be 28.2, 17.0, 14.3, 9.8, and 1.92 mg/g polymer for o-chloro phenol, p-nitro phenol, p-chloro phenol, o-nitro phenol, and phenol, respectively. However, for beta-cyclodextrin modified microbeads, adsorption capacity of phenolic species was determined as 274, 365, 128, 182, and 87 mg/g for phenol, o-nitro phenol, p-nitro phenol, o-chloro phenol, and p-chloro phenol, respectively. Desorption ratio for the phenolic species was more than 90%, except for o-nitro phenol. Detection limits of the phenolic species were improved at least 500-fold for UV-Vis spectrophotometric detection, after the pre-concentration of all phenolic species used in this study. Adsorption time for the phenolic species onto beta-cyclodextrin-modified poly(HEMA-EGDMA) microbeads was found to be reasonable short (10-60 min) and suitable for the applications. Also, synthesized microbeads were useful for the repeated use for the removal and pre-concentration of phenolic species.     

Correction to: Evaluation of hydrochar efficiency for simultaneous removal of diclofenac and ibuprofen from aqueous system using surface response methodology

Environmental Science and Pollution Research - The original publication of this paper contain typographical mistakes.     

Evaluation of hydrochar efficiency for simultaneous removal of diclofenac and ibuprofen from aqueous system using surface response methodology

Environmental Science and Pollution Research - Pharmaceutically active compounds like diclofenac (DFS), ibuprofen (IBP), and other drugs that persist in the environment are listed as emerging...     

Monitoring spatiotemporal variations of diel radon concentrations in peatland and forest ecosystems based on neural network and regression models

Concentrations of outdoor radon-222 (²²²Rn) in temperate grazed peatland and deciduous forest in northwestern Turkey were measured, compared, and modeled using artificial neural networks (ANNs) and multiple nonlinear regression (MNLR) models. The best-performing multilayer perceptron model selected out of 28 ANNs considerably enhanced accuracy metrics in emulating ²²²Rn concentrations relative to the MNLR model. The two ecosystems had similar diel patterns with the lowest ²²²Rn concentrations in the afternoon and the highest ones near dawn. Mean level (5.1?+?2.5 Bq?m^?3 h^?1) of ²²²Rn in the forest was three times smaller than that (15.8?+?9.7 Bq?m^?3) of ²²²Rn in the peatland. Mean ²²²Rn level had negative and positive relationships with air temperature and relative humidity, respectively.