Abstract
The occurrence, partitioning, and spatio-temporal distribution of seven pharmaceuticals for human use, three steroid hormones and one personal care product were determined in surface water, suspended particulate matter (SPM), and sediment of Piraí Creek and Jundiaí River (Jundiaí River Basin, São Paulo, Brazil). The maximum average detected concentrations of the compounds in the Piraí River samples were < 30 ng L−1, except for caffeine (222 ng L−1). In Jundiaí River samples, most of the compounds were frequently detected, wherein caffeine had the highest concentration, with maximum average concentrations of 14,050 ng L−1, followed by atenolol (431 ng L−1), ibuprofen (268 ng L−1) and diclofenac (214 ng L−1). Atenolol, propranolol, estrone, and triclosan were the contaminants most frequently detected in sediment and SPM samples. Triclosan had the highest average proportion of SPM as opposed to in the aqueous phase (> 75%). Contaminants with acid functional groups showed, in general, a lower tendency to bind to particulate matter and sediments. In addition, hydrophobicity had an important effect on their environmental partitioning. The spatial distribution of contaminants along the Jundiaí River was mainly affected by the higher concentration of contaminants in water samples collected downstream from a sewage treatment plant (STP). The results obtained here clearly showed the importance of the analysis of some contaminants in the whole water, meaning both dissolved and particulate compartments in the water, and that the partitioning is ruled by a set of parameters associated to the physicochemical characteristics of contaminants and the matrix properties of the studied, which need be considered in an integrated approach to understand the fate of emerging chemical contaminants in aquatic environments.
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The authors are grateful to the São Paulo Research Foundation (FAPESP), Grant nos. 2010/01731-0 and 2014/21871-2, CNPq, and PETROBRAS-ANP.
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de Sousa, D.N.R., Mozeto, A.A., Carneiro, R.L. et al. Spatio-temporal evaluation of emerging contaminants and their partitioning along a Brazilian watershed. Environ Sci Pollut Res 25, 4607–4620 (2018). https://doi.org/10.1007/s11356-017-0767-7
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DOI: https://doi.org/10.1007/s11356-017-0767-7