Understanding the sorption of pharmaceuticals to sewage sludge during waste water treatment processes is important for understanding their environmental fate and in risk assessments. The degree of sorption is defined by the sludge/water partition coefficient (Kd). Experimental Kd values (n = 297) for active pharmaceutical ingredients (n = 148) in primary and activated sludge were collected from literature. The compounds were classified by their charge at pH 7.4 (44 uncharged, 60 positively and 28 negatively charged, and 16 zwitterions). Univariate models relating log Kd to log Kow for each charge class showed weak correlations (maximum R2 = 0.51 for positively charged) with no overall correlation for the combined dataset (R2 = 0.04). Weaker correlations were found when relating log Kd to log Dow. Three sets of molecular descriptors (Molecular Operating Environment, VolSurf and ParaSurf) encoding a range of physico-chemical properties were used to derive multivariate models using stepwise regression, partial least squares and Bayesian artificial neural networks (ANN). The best predictive performance was obtained with ANN, with R2 = 0.62–0.69 for these descriptors using the complete dataset. Use of more complex Vsurf and ParaSurf descriptors showed little improvement over Molecular Operating Environment descriptors. The most influential descriptors in the ANN models, identified by automatic relevance determination, highlighted the importance of hydrophobicity, charge and molecular shape effects in these sorbate-sorbent interactions. The heterogeneous nature of the different sewage sludges used to measure Kd limited the predictability of sorption from physico-chemical properties of the pharmaceuticals alone. Standardization of test materials for the measurement of Kd would improve comparability of data from different studies, in the long-term leading to better quality environmental risk assessments.
Assessment of the fate of pharmaceutical residues in the environment involves the measurement or prediction of their sewage sludge partition coefficient (K d ). Sewage sludge can be classified into four types: primary, activated, secondary and digested, each one with different physical and chemical properties. Published studies have measured K d for pharmaceuticals in a variety of sludge types. This paper discusses the variability of reported K d values of pharmaceuticals in different types of sewage sludge, using a dataset generated from the literature. Using a meta-analysis approach, it was shown that the measured K d values depend on the type of sludge used in the test. Recommendations are given for the type of sludge to be used when studying the partitioning behaviour of pharmaceuticals in waste water treatment plants. Activated sludge is preferred due to its more homogenous nature and the ease of collection of consistent samples at a plant. Weak statistical relationships were found between K d values for activated and secondary sludge, and for activated and digested sludge. Pooling of K d values for these sludge types is not recommended for preliminary fate and risk assessments. In contrast, statistical analyses found stronger similarities between K d values reported for the same pharmaceutical in primary and activated sludges. This allows the pooling of experimental values for these two sludge types to obtain a larger dataset for modelling purposes.154 | Environ. Sci.: Water Res. Technol., 2016, 2, 154-163 This journal is Active pharmaceutical ingredients (API) in waste water treatment plants partition between aqueous and sludge phases. Understanding this behaviour is important for regulatory purposes. A partition coefficient (K d ) describes how chemicals distribute between these phases and can be measured experimentally using specific tests. A number of K d values have been published for APIs in a range of sludge types. This paper undertakes a meta-analysis of these K d values to investigate how the partitioning is affected by the different sludge types and if there are correlations between the datasets. This information is useful to make initial predictions of the fate of an API during treatment processes and may reduce the need to undertake time-consuming OECD tests in preliminary environmental risk assessments.
Catechins are most commonly analyzed by liquid chromatography using a C 18 column and reversed mobile phases, involving hydrophobic interactions. It is showed that a b-cyclodextrin (b-CD) column can separate five catechins (catechin, epicatechin, epigallocatechin, epicatechin gallate and epigallocatechin gallate) as well as gallic acid in the reversed phase mode with methanol-water mobile phases and in the polar organic mode with acetonitrile-methanol mobile phases. 0.1% v/v of acetic acid had to be added to all mobile phases to improve peak shapes. The selectivity (order of retention of the catechins) is completely different between classical C 18 columns and the b-CD column. This is due to a classical hydrophobic mechanism on C 18 column compared to a H-bond dominated mechanism with b-CD column in both RPLC and polar organic mode. It is shown that the catechin solutes could be analyzed ten times faster using the low viscosity polar organic mode and a b-CD column compared to RPLC with a C 18 column.
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