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Monitoring biological samples at trace levels of chemicals from anthropogenic actions such as pesticides, pharmaceuticals, and hormones has become a very important subject. This work describes a method for the determination of eight compounds of different chemical classes in human urine samples. Dispersive liquid-liquid microextraction based on magnetic ionic liquids was used as the sample preparation procedure. The main parameters of the method, such as sample dilution, type, and volume of disperser solvent, amount of magnetic ionic liquids, extraction time, and pH were optimized by univariate and multivariate procedures. Validation was performed using a urine sample of a male volunteer in order to obtain a calibration curve and the main analytical parameters of merit such as limits of detection and quantification. Values varied from 3.0 to 7.5 µg/L and from 10 to 25 µg/L, respectively. Satisfactory precisions of 21% for intraday (n = 3) and 16% for interday (n = 9) were achieved. Accuracy was evaluated by relative recovery assays using different urine samples and ranged from 75 to 130%. Robustness was assured by the Lenth method. The validated procedure was applied to five urine samples from different volunteers and the hormone estrone was found in one sample., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

To predict sewage influent and effluent concentrations of the steroid estrogens 17beta-estradiol, estrone, and 17alpha-ethinylestradiol, a review of human excretion was carried out. This included conjugation and metabolism of the natural and synthetic steroid estrogens within the body, together with quantities excreted in the urine and feces by different members of the population. This has been combined with fate and behavior information for conjugated and unconjugated estrogens in the sewage treatment system to enable sewage works influent and effluent concentration predictions to be made. The model has proved to be reasonably accurate when tested against recent measurements of these steroid estrogens in the influent and effluent of sewage treatment works. The model may be used with river dilution ratios to predict which sewage treatment works are most likely to cause the greatest endocrine disruption due to steroid estrogens.