We offer the following three-fold product and project portfolio:
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Providing a command-line interface of the enviMass workflow for Docker-based server integration, along with assistance in parametrising enviMass for different labs. Part of the K2IXplore project on using artificial and collective intelligence for tracking organic trace contaminants in surface waters for sustainable drinking water production.
Software optimization and adapations for the LC-HRMS routine monitoring at AUE Basel.
Self-parameterized algorithms for high-precision and high-throughput profiling of hyphenated mass spec data sets.
Aligns, groups and smoothes chromatograms of re-occuring analytes, while separating isobaric ones.
Testing for high levels of noise and different instrument types and applications (groundwater, surface water monitoring, different STP effluents).
Replacement or supplement for existing greedy approaches in enviMass.
R-packaged reimplemenation of the Swiss micropollutant and nutrient routing model for the Swiss Association of Experts on Wastewater and Water Protection.
NTS4UBA for combining json-based NTS data exports, compound lists with toxicity data and,
optionally, enviMass projects into a common database. Includes a shiny UI for the synchronization and data query.
Commissioned by the
Umweltbundesamt Berlin.
Providing a command-line interface of the enviMass workflow for Docker-based server integration for the first and completed stage of the K2I project.
Processing of LC-HRMS measurements, multivariate statistical data analysis and comprehensive reporting for two
sampling campaings at two river locations in Germany and Switzerland (ERMES project).
Commissioned by
AUE Basel
and
LUBW Karlsruhe.
Customized LC-MS data analysis, support and extensions assigned by the Department of Environmental Chemistry at Eawag Dübendorf.
Multivariate data analysis on emerging NTS pollutants for different landfill sites in the Canton Zürich (CH). Commissioned by the department for waste, water, energy and air (Amt für Abfall, Wasser, Energie und Luft, AWEL, Zürich, CH).
NTS data analysis for the interlaboratory trial of cantonal laboratories, Switzerland. Commissioned by the Federal Office for the Environment FOEN (BAFU).
NTS data analysis for the interlaboratory trial of drinking water producers, Germany. Commissioned by the state water supply Langenau (Zweckverband Landeswasserversorgung).
Data analysis for a spatiotemporal monitoring campaign in the Furtbach catchment (CH, Canton Zürich). Extraction of main and clustered intensity variations for mass spec target and nontarget profiles. Elucidation of patterns with discharge characteristics in the catchment. Commissioned by the cantonal department for waste, water, energy and air (Amt für Abfall, Wasser, Energie und Luft, AWEL, Zürich, CH).
Assistance with the data analysis for an international interlaboratory trial of monitoring stations along the Rhine River. Commissioned by the IKSR/SANA.
Suspect screening plus prioritization of industrial emissions. Spatial and process-based data clustering of selected sewage treatment plant effluents. Commissioned by the cantonal department for waste, water, energy and air (Amt für Abfall, Wasser, Energie und Luft, AWEL, Zürich, CH).
Sample data processing and prioritization of known and unknown trace organic compound time series. Summer monitoring campaign at the River Thur catchment, canton St Gallen. Commissioned by the cantonal department for water and energy (Amt für Wasser und Energie, AWE, St Gallen, CH), and in collaboration with the cantonal laboratory for the protection of water and soil (AWA/GBL, Bern, CH).
Industrial partner for a project on outlier detection as part of a bachelor-thesis, in collaboration with the Institute of Data Analysis and Process Design at the ZHAW School of Engineering, Winterthur, CH.
Detection of characteristic ESI in-source fragments for perfluorinated compounds, based on customized enviMass scripts. Commissioned for HS Fresenius / IFAR .
Automated LC/LC- and GC/GC-MS noise removal and signal detection (peak picking). Extension of the above enviPick R package for an additional dimension and for larger raw data sets.