Ecotoxicological risk assessment of contaminants of emerging concern identified by "suspect screening" from urban wastewater treatment plant effluents at a territorial scale.

Urban wastewater treatment plants (WWTP) are a major vector of highly ecotoxic contaminants of emerging concern (CECs) for urban and sub-urban streams. Ecotoxicological risk assessments (ERAs) provide essential information to public environmental authorities. Nevertheless, ERAs are mainly performed at very local scale (one or few WWTPs) and on pre-selected list of CECs. To cope with these limits, the present study aims to develop a territorial-scale ERA on CECs previously identified by a "suspect screening" analytical approach (LC-QToF-MS) and quantified in the effluents of 10 WWTPs of a highly urbanized territory during three periods of the year. Among CECs, this work focused on pharmaceutical residue and pesticides. ERA was conducted following two complementary methods: (1) a single substance approach, based on the calculation for each CEC of risk quotients (RQs) by the ratio of Predicted Environmental Concentration (PEC) and Predicted No Effect Concentration (PNEC), and (2) mixture risk assessment ("cocktail effect") based on a concentration addition model (CA), summing individual RQs. Chemical results led to an ERA for 41 CEC (37 pharmaceuticals and 4 pesticides) detected in treated effluents. Single substance ERA identified 19 CECs implicated in at least one significant risk for streams, with significant risks for DEET, diclofenac, lidocaine, atenolol, terbutryn, atorvastatin, methocarbamol, and venlafaxine (RQs reaching 39.84, 62.10, 125.58, 179.11, 348.24, 509.27, 1509.71 and 3097.37, respectively). Mixture ERA allowed the identification of a risk (RQmix > 1) for 9 of the 10 WWTPs studied. It was also remarked that CECs leading individually to a negligible risk could imply a significant risk in a mixture. Finally, the territorial ERA showed a diversity of risk situations, with the highest concerns for 3 WWTPs: the 2 biggest of the territory discharging into a large French river, the Rhône, and for the smallest WWTP that releases into a small intermittent stream.

Dataset of natural metal background levels inferred from pre-industrial palaeochannel sediment cores along the Rhône River (France).

Natural metal background levels in sediments are critical to assess spatial and temporal trends of contamination in hydrosystems and to manage polluted sediments. This is even more sensitive that multi-factors such as geogenic basement, depositional context, and past or long-term pollution can affect the level of metals in sediments. This article provides natural metal background levels and ancillary data (location, chronology, grain-size, total organic carbon - TOC) in pre-industrial sediments along the Rhône River (France). Two distinct areas were selected to take into account the geological variability of the watershed: the Dauphiné Lowlands (Upper Rhône River) and the Tricastin Floodplain (Middle Rhône River). On each area, the sediment cores were retrieved from palaeochannel sequences and the sampled sections were dated by radiocarbon from the Roman to the Modern Times (AD 3-1878). Regulatory metals (Al, Fe, Cd, Cr, Cu, Ni, Pb, and Zn) and other trace elements (Ba, Co, Li, Mg, Mn, Na, P, Sr, Ti, V) were analysed following both Aqua Regia (AR) and Total Extraction (TE) procedures. Classically, TE provides metal concentrations greater than AR because TE includes crystalline lattice, while AR is close to the potentially bio-accessible part of metals (used for ecotoxicological purposes). Due to the small number of samples and to the non-normal distribution of the results, a median-based approach was chosen to establish the geochemical background values and ranges (MGB) for each sample and area. These MGBs are valuable to identify pollution sources, to characterise a contamination (spread and timing), and to estimate the state of rivers regarding pollution legacy. Along the Rhône River, these two continental MGBs were used to reconstruct the metal geo-accumulation trajectories in river sediments from 1965 to 2018 [1].