We contribute to the international scientific community through peer-reviewed publications and publicly accessible reports, developed in collaboration with leading universities, research institutes, and environmental authorities.
Below is a selection of scientific studies and expert contributions involving our team.
PEER-REVIEWED PUBLICATIONS BY YEAR
2024
📄 Comparison of PM Source Profiles Identified by Different Techniques and the Potential of Utilizing Single-Particle Analysis Data in Source Apportionment
Authors: In collaboration with PSI (Switzerland), Demokritos (Greece), IGE (France), IDAEA-CSIC (Spain), and Gradiom (Switzerland)
Journal/Platform: SSRN preprint, 2024
Summary: This study compares and cross-validates PM coarse source profiles from bulk PMF analysis with single-particle ASPA-MC2®. It shows how combining both techniques improves source identification and has the potential of strengthening PMF result for primary particles.
2023
📄 Analytical challenges and possibilities for the quantification of tire-road wear particles
Authors: Collaboration with scientists from Norway, Germany, Sweden, and Australia
Journal: Trends in Analytical Chemistry, 2023
Summary: Review article on current techniques, analytical limitations, and opportunities for quantifying tire wear particles (TWP/TRWP) in environmental samples.
🔗 Read article
2022 I
📄 On airborne tire wear particles along roads with different traffic characteristics using passive sampling and optical microscopy, single particle SEM/EDX, and µ-ATR-FTIR analyses
Authors: In collaboration with scientists from the University of Mississippi
Journal: Frontiers in Environmental Science, 2022
Summary: Scientific article on the quantification of non-exhaust particles along roads with varying traffic characteristics using a combination of passive sampling and advanced analytical techniques.
🔗 Read article
📄 Concentrations of tire wear microplastics and other traffic-derived non-exhaust particles in the road environment
Authors: In collaboration with VTI (Swedish National Road and Transport Research Institute) and Chalmers University of Technology
Journal: Environment International, 2022
Summary: Characterization and quantification of non-exhaust particles in a Swedish road environment, with a focus on tire wear microplastics and traffic-related dust.
🔗 Read article
2022 II
📄 Differentiating and quantifying carbonaceous (tire, bitumen, and road marking wear) and non-carbonaceous (metals, minerals, and glass beads) non-exhaust particles in road dust samples from a traffic environment
Authors: Järlskog, I., Jaramillo-Vogel, D., Rausch, J., Perseguers, S., Gustafsson, M., Strömvall, A.-M., Andersson-Sköld, Y.
Journal: Water, Air, & Soil Pollution, 2022
Summary: Scientific article on the chemical and morphological differentiation of traffic-related non-exhaust particles, including tire wear, bitumen, and mineral-based constituents, using road dust sampling.
🔗 Read article
2021
📄 Automated identification and quantification of tire wear particles (TWP) in airborne dust: SEM/EDX single particle analysis coupled to a machine learning classifier
Authors: Internal team-led study
Journal: Science of The Total Environment, 2021
Summary: First presentation of the automated SEM/EDX methodology for identifying and quantifying tire wear and other primary non-exhaust particles in airborne dust samples using single-particle analysis and machine learning classification.
🔗 Read article
2020
📄 Decrypting silicic magma/plug fragmentation at Azufral crater lake, Northern Andes: insights from fine to extremely fine ash morpho-chemistry
Authors: In collaboration with scientists from Universidad de los Andes (Colombia)
Journal: Bulletin of Volcanology, 2020
Summary: Scientific article on the morpho-chemical characterization of volcanic ash particles using automated SEM/EDX single particle analysis. The study provides new insights into magma fragmentation processes based on ultra-fine ash morphology and composition.
🔗 Read article
2018
📄 A model based two-stage classifier for airborne particles analyzed with Computer Controlled Scanning Electron Microscopy
Authors: Meier MF, Mildenberger T, Locher R, Rausch J, Zünd T, Neururer C, Ruckstuhl A, Grobéty B
Journal: Journal of Aerosol Science, 2018
Summary: Development of a two-stage machine learning classifier for airborne particles using CCSEM, enhancing the robustness and accuracy of automated environmental particle classification.
🔗 Read article
2015
📄 Eifel maars: Quantitative shape characterization of juvenile ash particles (Eifel Volcanic Field, Germany)
Authors: Rausch J, Grobéty B, Vonlanthen P
Journal: Journal of Volcanology and Geothermal Research, 2015
Summary: Study applying quantitative image analysis techniques to characterize the shape and morphology of volcanic ash particles from Eifel maars.
🔗 Read article
📄 High-resolution 3D analyses of the shape and internal constituents of small volcanic ash particles: the contribution of SEM micro-computed tomography (SEM micro-CT)
Authors: Vonlanthen P, Rausch J, Ketcham RA, Putlitz B, Baumgartner LP, Grobéty B
Journal: Journal of Volcanology and Geothermal Research, 2015
Summary: Application of SEM micro-CT to analyze the internal structure and shape of volcanic ash particles in high-resolution 3D.
🔗 Read article

PUBLIC REPORTS
📄 Characterization of airborne dust fractions in Switzerland (PM10–2.5, PM2.5–1, and >PM10)
Commissioned by: Swiss Federal Office for the Environment (FOEN)
Published: 2020
Summary: Public report on the morpho-chemical characterization of coarse and fine airborne particles in Switzerland. The study includes source attribution insights and a detailed overview of different PM fractions. An English summary is available on pages 24–31.
🔗 Download report (PDF) (replace "Details" with actual URL if available)
