• Characterization and quantification of particles at road (tunnel) sites

    Characterization and quantification of particles at road (tunnel) sites

  • Determination of the railway traffic immissions in PM10

    Determination of the railway traffic immissions in PM10

  • Particle measurements using passive samplers

    Particle measurements using passive samplers

  • Provenience determination of particles causing polluted house walls

    Provenience determination of particles causing polluted house walls

  • Where is the pollution on the window sill coming from?

    Where is the pollution on the window sill coming from?

  • Powerless passive sampling for dust characterization

    Powerless passive sampling for dust characterization

  • PM Coarse mode characterization and differentiation

    PM Coarse mode characterization and differentiation

  • Source-differentiated dust monitoring of quarries, gravel pits, dump and contruction sites

    Source-differentiated dust monitoring of quarries, gravel pits, dump and contruction sites

Particle classifier (PACLA)

Automated single particle scanning electron microscopy analysis coupled to energy dispersive x-ray spectroscopy (SEM/EDX) deliver multidimensional and very complex data sets making data treatment tedious and time consuming.

In the past, the classification of the different morpho-chemical groups, which can be related to specific sources, was done manually.

In order to overcome this issue, we have developed in cooperation with the Zürich School of Applied Sciences and the University of Fribourg an extremely useful tool for efficient data treatment.

Here, we present the prototype of the so called PACLA (PArticle CLAsifier software), which enables an arbitrary number of particles to be efficiently analyzed and grouped in chemical classes (=sources) based on cluster analysis.

Particle Vision Network