A comparison of predicted and measured levels of runoff-related pesticide concentrations in small lowland streams on a landscape level

Short-term pollution events via runoff are typical of streams in agricultural areas. Existing runoff models that simulate pesticide loss from agricultural fields require extensive input of information. There is thus a need for a simple model that can predict runoff-related pesticide concentrations in many streams on a landscape level when only limited data are available. To validate such a model, the runoff-related pesticide load of 18 small lowland streams was predicted with an extended version of the model "simplified formula for indirect loadings caused by runoff" (available from the Organisation for Economic Cooperation and Development, OECD). The authors suggest that the model presented here is suitable for use in routine exposure assessment of pesticides on a landscape level, as all input data (soil, slope, precipitation, pesticide application) are readily available from public authorities or could be generated by simple regional flood hydrograph curves. The predicted concentrations were compared with measured concentrations obtained by runoff-triggered sampling. Fungicides, insecticides and herbicides were detected in 17 streams, with max. concentrations measuring up to 29.7 microg/l for the fungicide azoxystrobin and 0.3 microg/l for the insecticide parathion-ethyl. Herbicides were detected in 16 streams, with max. concentrations between 13.7 and 1.2 microg/l. The linear regression between the predicted and measured concentrations (log-values) shows significant correlations for the following pesticides: azoxystrobin: r2=0.43; p=0.03; epoxiconazole: r2=0.71; por=0.5 microg/l).     

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.     

Beach macro-litter monitoring on southern Baltic beaches: results,experiences and recommendations

Major objectives were to provide a comprehensive dataset on beach macro-litter for parts of the southern Baltic Sea and to analyse if the methodology is fully applicable and a suitable monitoring method in the Baltic. We carried out a regular macro litter beach monitoring (OSPAR methodology, 4 time a year) on 35 beaches along the German and Lithuanian Baltic coast over 2–5 years. Additional experiments addressed the subjectivity of the field surveys and spatio-temporal variability on different scales. We observed no seasonality of the data and a monthly compared to a 3-monthly sampling resulted in 3 times higher annual item numbers. Along the Lithuanian coast, the average number of items per survey varied between 138 and 340 and along the German Baltic coast between 7 and 404, with a median value of 47. All data showed a very high spatio-temporal variability. Using the Matrix Scoring Technique we assessed beach litter sources. With 50% tourism and recreation was the most important source. 3D–transport simulations helped to explain the minor role of shipping as a source and, compared to the North Sea, the low numbers of items on German Baltic beaches. Floating litter had a short duration time in the western Baltic Sea and offshore drift dominated. Further, the common regular beach cleanings reduced the potential for local litter accumulation and translocation. We suggest a monitoring system on 14 Baltic beaches in Germany and 2 in Lithuania and provide cost calculations. The analysis of macro-litter in cormorant nesting material and the search for beached dead animals did not show any result. We can conclude that the macro-litter beach monitoring method is less suitable for Baltic beaches and should only serve as a complementary method in combination with others.