@article{StedingSchneider2021, author = {Steding, Svenja and Schneider, Wilfried}, title = {Prognose des Schadstoffaustrags aus mehrphasigen DNAPL-Pools mittels semi-analytischem Berechnungsmodell}, series = {Grundwasser : Zeitschrift der Fachsektion Hydrogeologie in der Deutschen Gesellschaft f{\"u}r Geowissenschaften (FH-DGG)}, volume = {26}, journal = {Grundwasser : Zeitschrift der Fachsektion Hydrogeologie in der Deutschen Gesellschaft f{\"u}r Geowissenschaften (FH-DGG)}, number = {3}, publisher = {Springer}, address = {Berlin ; Heidelberg}, issn = {1430-483X}, doi = {10.1007/s00767-021-00490-2}, pages = {241 -- 253}, year = {2021}, abstract = {Multicomponent DNAPL pools are among the most common reasons for groundwater contamination and represent highly persistent source areas. Although several studies have already shown that their constituents influence each other's solubility, existing models neglect these interactions. For this reason, a semi-analytical model has been developed, considering the pool composition as temporally variable. Based on Raoult's law, the molar fraction, the effective solubility and finally the mass discharge due to advection, dispersion and diffusion of each component are determined. The results significantly differ from studies on single-phase pools. It is shown that mass discharges can both increase and decrease over time and that the longevity of DNAPL pools as well as the time until threshold values are fullfilled will be significantly underestimated if Raoult's law is neglected. Additionally, a sensitivity analysis reveals that poorly soluble minor components must not be neglected, whereas highly soluble ones can.}, language = {de} } @article{PiroRenard2023, author = {Piro, Vitor C. and Renard, Bernhard Y.}, title = {Contamination detection and microbiome exploration with GRIMER}, series = {GigaScience}, volume = {12}, journal = {GigaScience}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {2047-217X}, doi = {10.1093/gigascience/giad017}, pages = {13}, year = {2023}, abstract = {Background: Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination. Results: We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles. Conclusion: GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.}, language = {en} } @article{KuhnTavaresJacquesTeixeiraetal.2021, author = {Kuhn, Eug{\^e}nia Carla and Tavares Jacques, Maur{\´i}cio and Teixeira, Daniela and Meyer, S{\"o}ren and Gralha, Thiago and Roehrs, Rafael and Camargo, Sandro and Schwerdtle, Tanja and Bornhorst, Julia and {\´A}vila, Daiana Silva}, title = {Ecotoxicological assessment of Uruguay River and affluents pre- and biomonitoring}, series = {Environmental science and pollution research : ESPR}, volume = {28}, journal = {Environmental science and pollution research : ESPR}, number = {17}, publisher = {Springer}, address = {Berlin ; Heidelberg}, issn = {0944-1344}, doi = {10.1007/s11356-020-11986-4}, pages = {21730 -- 21741}, year = {2021}, abstract = {Uruguay River is the most important river in western Rio Grande do Sul, separating Brazil from Argentina and Uruguay. However, its pollution is of great concern due to agricultural activities in the region and the extensive use of pesticides. In a long term, this practice leads to environmental pollution, especially to the aquatic system. The objective of this study was to analyze the physicochemical characteristics, metals and pesticides levels in water samples obtained before and after the planting and pesticides' application season from three sites: Uruguay River and two minor affluents, Mezomo Dam and Salso Stream. For biomonitoring, the free-living nematode Caenorhabditis elegans was used, which were exposed for 24 h. We did not find any significant alteration in physicochemical parameters. In the pre- and post-pesticides' samples we observed a residual presence of three pesticides (tebuconazole, imazethapyr, and clomazone) and metals which levels were above the recommended (As, Hg, Fe, and Mn). Exposure to both pre- and post-pesticides' samples impaired C. elegans reproduction and post-pesticides samples reduced worms' survival rate and lifespan. PCA analysis indicated that the presence of metals and pesticides are important variables that impacted C. elegans biological endpoints. Our data demonstrates that Uruguay River and two affluents are contaminated independent whether before or after pesticides' application season. In addition, it reinforces the usefulness of biological indicators, since simple physicochemical analyses are not sufficient to attest water quality and ecological safety.}, language = {en} }