Abstract

Over the last two decades, effect-directed analysis (EDA) gained importance as a seminal screening tool for tracking biological effects of environmental organic micro-pollutants (MPs). As EDA using high-performance liquid chromatography and bioassays is costly and time consuming, recent implementations of this approach have combined high-performance thin-layer chromatography (HPTLC) with effect-based methods (EBMs) using cell-based bioassays, enabling the detection of estrogenic, androgenic, genotoxic, photosystem II (PSII)- inhibiting, and dioxin-like sample components on a HPTLC plate. In the present study, the developed methodologies were applied as a HPTLC-based bioassay battery, to investigate toxicant elimination efficiency of wastewater treatment plants (WWTPs), and to characterize the toxic potential of landfill leachates. Activity levels detected in untreated landfill leachates, expressed as reference compound equivalence (EQ) concentration, were up to 16.8 µg β-naphthoflavone-EQ L−1 (indicating the degree of dioxin-like activity), 1.9 µg estradiol-EQ L−1 (estrogenicity) and 8.3 µg diuron-EQ L‑1 (PSII-inhibition), dropping to maximal concentrations of 47 ng β-naphthoflavone-EQ L−1, 0.7 µg estradiol-EQ L−1 and 53.1 ng diuron-EQ L−1 following treatment. Bisphenol A (BPA) is suggested to be the main contributor to estrogenic activity, with concentrations determined by the planar yeast estrogen screen corresponding well to results from chemical analysis. In the investigated WWTP samples, a decrease of estrogenic activity of 6–100% was observed following treatment for most of the active fractions, except of a 20% increase in one fraction (Rf = 0.568). In contrast, androgenicity with concentrations up to 640 ng dihydrotestosterone-EQ L−1 was completely removed by treatment. Interestingly, genotoxic activity increased over the WWTP processes, releasing genotoxic fractions into receiving waters. We propose this combined HPTLC and EBM battery to contribute to an efficient, cheap, fast and robust screening of environmental samples; such an assay panel would allow to gain an estimate of potential biological effects for prioritization prior to substance identification, and its routine application will support an inexpensive identification of the toxicity drivers as a first tier in an EDA strategy.

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