Combining Polar Organic Chemical Integrative Samplers (POCIS) with Toxicity Testing on Microalgae to Evaluate the Impact of Herbicide Mixtures in Surface Waters.

Pesticide risk assessment within the European Union Water Framework Directive is largely deficient in the assessment of the actual exposure and chemical mixture effects. Pesticide contamination, in particular herbicidal loading, has been shown to exert pressure on surface waters. Such pollution can have direct impact on autotrophic species, as well as indirect impacts on freshwater communities through primary production degradation. The present study proposes a screening method combining polar organic chemical integrative samplers (POCIS) with mode of action-specific toxicity testing on microalgae exposed to POCIS extracts as a standard approach to effectively address the problem of herbicide mixture effects detection. This methodology has been tested using Luxembourgish rivers as a case study and has proven to be a fast and reliable information source that is complementary to chemical analysis, allowing assessment of missing target analytes. Pesticide pressure in the 24 analyzed streams was mainly exerted by flufenacet, terbuthylazine, nicosulfuron, and foramsulfuron, with occasional impacts by the nonagricultural biocide diuron. Algae tests were more sensitive to endpoints affecting photosystem II and reproduction than to growth and could be best predicted with the concentration addition model. In addition, analysis revealed that herbicide mixture toxicity is correlated with macrophyte disappearance in the field, relating mainly to emissions from maize cultures. Combining passive sampler extracts with standard toxicity tests offers promising perspectives for ecological risk assessment. The full implementation of the proposed approach, however, requires adaptation of the legislation to scientific progress. Environ Toxicol Chem 2022;41:2667-2678. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Performance of Chlorella Vulgaris Exposed to Heavy Metal Mixtures: Linking Measured Endpoints and Mechanisms.

Microalgae growth inhibition assays are candidates for referent ecotoxicology as a fundamental part of the strategy to reduce the use of fish and other animal models in aquatic toxicology. In the present work, the performance of Chlorella vulgaris exposed to heavy metals following standardized growth and photosynthesis inhibition assays was assessed in two different scenarios: (1) dilutions of single heavy metals and (2) an artificial mixture of heavy metals at similar levels as those found in natural rivers. Chemical speciation of heavy metals was estimated with Visual MINTEQ software; free heavy metal ion concentrations were used as input data, together with microalgae growth and photosynthesis inhibition, to compare different effects and explain possible toxicity mechanisms. The final goal was to assess the suitability of the ecotoxicological test based on the growth and photosynthesis inhibition of microalgae cultures, supported by mathematic models for regulatory and decision-making purposes. The C. vulgaris algae growth inhibition test was more sensitive for As, Zn, and Pb exposure whereas the photosynthesis inhibition test was more sensitive for Cu and Ni exposure. The effects on growth and photosynthesis were not related. C. vulgaris evidenced the formation of mucilaginous aggregations at lower copper concentrations. We found that the toxicity of a given heavy metal is not only determined by its chemical speciation; other chemical compounds (as nutrient loads) and biological interactions play an important role in the final toxicity. Predictive mixture effect models tend to overestimate the effects of metal mixtures in C. vulgaris for both growth and photosynthesis inhibition tests. Growth and photosynthesis inhibition tests give complementary information, and both are a fast, cheap, and sensitive alternative to animal testing. More research is needed to solve the challenge of complex pollutant mixtures as they are present in natural environments, where microalgae-based assays can be suitable monitoring tools for pollution management and regulatory purposes.

Characterization of river biofilm responses to the exposure with heavy metals using a novel micro fluorometer biosensor.

River biofilms are a suitable indicator of toxic stress in aquatic ecosystems commonly exposed to various anthropogenic pollutants from industrial, domestic, and agricultural sources. Among these pollutants, heavy metals are of particular concern as they are known to interfere with various physiological processes of river biofilm, directly or indirectly related to photosynthetic performance. Nevertheless, only limited toxicological data are available on the mechanisms and toxicodynamics of heavy metals in biofilms. Pulse Amplitude Modulated (PAM) fluorometry is a rapid, non-disruptive, well-established technique to monitor toxic responses on photosynthetic performance, fluorescence-kinetics, and changes in yield in other non-photochemical processes. In this study, a new micro-PAM-sensor was tested to assess potential acute and chronic effects of heavy metals in river biofilm. Toxicity values across the three parameters considered in this study (photosynthetic yield YII, non-photochemical quenching NPQ, and basal fluorescence F0) were comparable, as determined EC50 were within one order of magnitude (EC50 ∼1-10 mg L-1). However, the stimulation of NPQ was more clearly associated with early acute effects, especially in illuminated samples, while depression of YII and F0 were more prevalent in chronic tests. These results have implications for the development of functional indicators for the biomonitoring of aquatic health, in particular for the use of river biofilm as a bioindicator of water quality. In conclusion, the approach proposed seems promising to characterize and monitor the exposure and impact of heavy metals on river periphyton communities. Furthermore, this study provides a fast, highly sensitive, inexpensive, and accurate laboratory method to test effects of pollutants on complex periphyton communities that can also give insights regarding the probable toxicological mechanisms of heavy metals on photosynthetic performance in the river biofilm.

Water toxicity assessment and spatial pollution patterns identification in a Mediterranean River Basin District. Tools for water management and risk analysis.

In compliance with the requirements of the EU Water Framework Directive, monitoring of the ecological and chemical status of Catalan river basins (NE Spain) is carried out by the Catalan Water Agency. The large amount of data collected and the complex relationships among the environmental variables monitored often mislead data interpretation in terms of toxic impact, especially considering that even pollutants at very low concentrations might contribute to the total toxicity. The total dataset of chemical monitoring carried out between 2007 and 2008 (232 sampling stations and 60 pollutants) has been analyzed using sequential advanced modeling techniques. Data on concentrations of contaminants in water were pre-treated in order to calculate the bioavailable fraction, depending on substance properties and local environmental conditions. The resulting values were used to predict the potential impact of toxic substances in complex mixtures on aquatic biota and to identify hot spots. Exposure assessment with Species Sensitivity Distribution (SSD) and mixture toxicity rules were used to compute the multi-substances Potentially Affected Fraction (msPAF). The combined toxicity of the pollutants analyzed in the Catalan surface waters might potentially impact more than 50% of the species in 10% of the sites. In order to understand and visualize the spatial distribution of the toxic risk, Self Organising Map (SOM), based on the Kohonen's Artificial Neural Network (ANN) algorithm, was applied on the output data of these models. Principal Component Analysis (PCA) was performed on top of Neural Network results in order to identify main influential variables which account for the pollution trends. Finally, predicted toxic impacts on biota have been linked and correlated to field data on biological quality indexes using macroinvertebrate and diatom communities (IBMWP and IPS). The methodology presented could represent a suitable tool for water managers in environmental risk assessment and management.

Integrated modelling of Polycyclic Aromatic Hydrocarbons in the marine environment: coupling of hydrodynamic, fate and transport, bioaccumulation and planktonic food-web models.

Spatio-temporal variability of pollutants in the environment is a complex phenomenon that requires a combined approach for its analysis. Whereas data on measured levels of contaminants in various environmental compartments is essential, it is not always possible to monitor at the necessary frequency and with the adequate spatial sampling distribution to capture this variability. Therefore a modelling approach able to complement experimental data and close the gaps in the monitoring programs is useful for assessing the contaminant dynamics occurring at different time scales. In this work a 1D water column fate model has been developed and tested for Polycyclic Aromatic Hydrocarbons (PAHs). The model has been coupled with a simple ecological model that includes a bioaccumulation module. Afterwards, the model has been used to study the temporal variability of contaminant concentrations as well as the fluxes between compartments. The results evidence the complex coupling between spatio-temporal scales and its influence on environmental concentration levels.

A bioaccumulation model for herbicides in Ulva rigida and Tapes philippinarum in Sacca di Goro lagoon (Northern Adriatic).

A bioaccumulation model to predict concentrations of s-triazine herbicides in the macroalgae Ulva rigida and in clams Tapes philippinarum has been implemented, calibrated and validated. The model uses input data from a 3D biogeochemical model that provides biomasses in the different compartments, i.e. phytoplankton, zooplankton and bacteria; and from a 3D fate model that provides the herbicides concentrations in the water column as well as in the sediments. Simulated data were compared with experimental data collected during a set of sampling campaigns carried out in 2004 and 2005 in the Sacca di Goro lagoon (Northern Adriatic). The model predicts correctly the concentrations of herbicides measured in Ulva rigida and reproduces with good agreement the values of concentration of herbicides found in clams. Furthermore, the simulated spatial and temporal dynamics in the biota compartment, following those of the water and sediments, are also in agreement with the experimental data. This integrated approach combining biogeochemical, fate and bioaccumulation models provide an overall assessment of the importance of the different environmental compartments and it can also support the testing of different management strategies to improve ecosystem state and functioning. Further research is necessary to elucidate the role and importance of the metabolism of these compounds by clams.