How to Implement User-Friendly BLMs in the Absence of DOC Monitoring Data: A Case Study on Bulgarian Surface Waters

Following the evidence and using the appropriate regulatory tools: A European-wide risk assessment of copper in freshwaters

The ecological risks of copper (Cu) in freshwaters have been the focus of regulatory assessments for several decades. Recently, it has been suggested by the European Commission that Cu represents a continent-wide risk to freshwaters. We assessed to what extent this suggestion is supported by the available evidence if Cu bioavailability is considered in the assessment of risk. We used several evidence-driven metrics to assess the continental-wide risks of Cu to European freshwaters. Such an approach is recommended and readily applicable where comprehensive data sets are available. We confirmed the validity of a bioavailability-based Environmental Quality Standard of 1 µg L-1 for Cu and used this to characterize the risks of Cu in 286 185 regulatory monitoring samples from 17 307 sites across 19 European countries between 2006 and 2021. These data show that risks, based on site averages and accounting for bioavailability, were identified in only two countries (Spain and Portugal). Investigation of these risks showed them to be highly localized to a single region in Spain and not reflective of the country-wide risks for either country. The 95th percentile of all the risk quotients for the continent-wide data set is 0.35. The relatively low levels of risk associated with Cu are supported by long-term trend data from sites on two large European rivers (Rhine and Meuse), where highly significant (p < 0.001) decreases in Cu concentrations over the last 40 years can be observed. We conclude that it is critical to consider metal bioavailability in both effects and exposures in assessments of potential risk to ensure ecological relevance. Integr Environ Assess Manag 2023;19:1570-1580. © 2023 WCA Environment Ltd. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Development of a Machine Learning Model to Estimate the Biotic Ligand Model-Based Predicted No-Effect Concentrations for Copper in Freshwater

The copper (Cu) biotic ligand model (BLM) has been used for ecological risk assessment by taking into account the bioavailability of Cu in freshwater. The Cu BLM requires data for many water chemistry variables, such as pH, major cations, and dissolved organic carbon, which can be difficult to obtain from water quality monitoring programs. To develop an optimized predicted no-effect concentration (PNEC) estimation model based on an available monitoring dataset, we proposed an initial model that considers all BLM variables, a second model that requires variables excluding alkalinity, and a third model using electrical conductivity as a surrogate for the major cations and alkalinity. Furthermore, deep neural network (DNN) models have been used to predict the nonlinear relationships between the PNEC (outcome variable) and the required input variables (explanatory variables). The predictive capacity of DNN models was compared with the results of other existing PNEC estimation tools using a look-up table and multiple linear and multivariate polynomial regression methods. Three DNN models, using different input variables, provided better predictions of the Cu PNECs compared with the existing tools for the following four test datasets: Korean, United States, Swedish, and Belgian freshwaters. Consequently, it is expected that Cu BLM-based risk assessment can be applied to various monitoring datasets, and that the most applicable model among the three different types of DNN models could be selected according to data availability for a given monitoring database. Environ Toxicol Chem 2023;42:2271-2283. © 2023 SETAC.

Chemometric Evaluation of WWTPs’ Wastewaters and Receiving Surface Waters in Bulgaria

Wastewater treatment plant (WWTP) installations are designed and operated to reduce the quantity of pollutants emitted to surface waters receiving treated wastewaters. In this work, we used classical instrumental studies (to determine chemicals and parameters under obligations put with Directive 91/271/EEC), ecotoxicological tools (Sinapis alba root growth inhibition (SA-RG) and Heterocypris incongruens mortality (MORT) and growth inhibition (GRINH)) and multivariate statistical analysis to gain information on feature profiles of WWTPs’ effluents and the possible burden of surface water bodies receiving treated wastewaters in eleven locations of Bulgaria. Initial screening of results has shown that only phosphorus content exceeds the admissible level in 5 out 11 WWTP effluents, while As, Cr, Cu, Mn, and Zn show exceedance at several locations. The multivariate statistical analysis reveals the discriminating water quality parameters and outlines the ability of Heterocypris incongruens to evaluate the ecotoxicological potential of different groups of waters.