Search

In Switzerland, 9000 tons of tyre wear particles (TWP) enter the environment every year. This corresponds to over 60 % of the total annual microplastic input (Steiner, 2020). Studies about the emission of TPW are mostly based on model calculations and only few direct measurements of TWP loads in soils exist (Baensch-Baltruschat et al., 2020). This lack of empirical data is partly attributed to the limited availability of generally accessible and standardized extraction and analysis protocols. The aim of the presented work was the implementation of a method proposed by Grunder et al. (2023) and Foetisch et al. (2023) for the cost-effective analysis of TWP in soils at the Research Institute of Organic Agriculture (FiBL). 60 soil samples were collected from permanent grassland at 15 different road sites and defined distances from the road (1, 2, 5, 10 m) in the canton Solothurn. The analysis of the extracted TWP was performed optically using a Stereomicroscope at 40fold magnification. For the quantification, a colour-based approach using a machine learning pixel segmentation algorithm was used. This poster presents the results of the analysis of the first 20 soil samples. In the context of my thesis in MAS Environmental Technique and -management at the FHNW, TWP of 20 soil samples from 4 of the 15 sampling areas have been extracted and analysed using the method described above. Numbers of TWP were comparable between sites and particle numbers decreased with increasing distance from the road. The results are presented in this poster

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.

For lake characterisation, top-down typologies are mostly used throughout Europe, including type criteria such as climate, lake area, catchment geology and conductivity. In Germany, a lake typology was applied comprising ecoregion, calcium concentration, Schindler's ratio, stratification type and residence time. However, the relevance of these criteria for the macroinvertebrate fauna has not been conclusively demonstrated till now. Benthic invertebrate community data and related environmental parameters of pristine or near-pristine lakes in Germany were analysed by multivariate analysis techniques to elucidate which environmental parameters are reflected by invertebrate composition. Moreover, benthic invertebrate data were transformed to metrics expressing ecological attributes and species richness (summarising functional composition, diversity and sensitivity measures). Multivariate statistics were used to test whether information relevant to ordination was lost and whether variation decreases using metrics which combine data with ecological attributes. Analysis of lake-type criteria revealed that ecoregions and prevailing substrates were characterized by different taxonomic compositions of macroinvertebrates. In addition, a relationship was found between community composition and lake size. Creating a novel bottom-up lake typology based on ecoregions, lake size and prevailing substrate gives better separation of distinct macroinvertebrate communities and a higher level of homogeneity within groups compared to top-down typology or single environmental parameters alone, both on species and metrics data. Despite some data variation due to methodological differences (e.g. different sampling and sorting techniques) and interannual and seasonal variation in the data set, NMDS ordination presented well-separated groups of bottom-up lake types. Lake types were more precisely separated by species data than by metric data in both top-down and bottom-up typology. However, as

For lake characterisation, top-down typologies are mostly used throughout Europe, including type criteria such as climate, lake area, catchment geology and conductivity. In Germany, a lake typology was applied comprising ecoregion, calcium concentration, Schindler's ratio, stratification type and residence time. However, the relevance of these criteria for the macroinvertebrate fauna has not been conclusively demonstrated till now. Benthic invertebrate community data and related environmental parameters of pristine or near-pristine lakes in Germany were analysed by multivariate analysis techniques to elucidate which environmental parameters are reflected by invertebrate composition. Moreover, benthic invertebrate data were transformed to metrics expressing ecological attributes and species richness (summarising functional composition, diversity and sensitivity measures). Multivariate statistics were used to test whether information relevant to ordination was lost and whether variation decreases using metrics which combine data with ecological attributes. Analysis of lake-type criteria revealed that ecoregions and prevailing substrates were characterized by different taxonomic compositions of macroinvertebrates. In addition, a relationship was found between community composition and lake size. Creating a novel bottom-up lake typology based on ecoregions, lake size and prevailing substrate gives better separation of distinct macroinvertebrate communities and a higher level of homogeneity within groups compared to top-down typology or single environmental parameters alone, both on species and metrics data. Despite some data variation due to methodological differences (e.g. different sampling and sorting techniques) and interannual and seasonal variation in the data set, NMDS ordination presented well-separated groups of bottom-up lake types. Lake types were more precisely separated by species data than by metric data in both top-down and bottom-up typology. However, as