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  • PartiCollect screenshot 1
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About PartiCollect

Take part in the mapping of fine-particle air pollution in your city! The PartiCollect (powered by NanoObs and PartiCiTaE) project allows you take part in mapping fine-particle air pollution in the city by collecting samples in your environment. These samples are then sent to the scientific team, made up of researchers based at three universities in the Paris region. Using magnetic and chemical measurements, the scientific team can identify and quantify metallic pollutants, which are largely linked to car traffic and are known to have harmful effects on health. These metallic particles come from exhaust fumes, but some are also emitted by braking and tire wear. They are then deposited on surrounding objects, such as plants. Plane tree bark is particularly well suited to this type of study. Plane trees are very common in  cities, especially along or near streets, and they are therefore particularly exposed. These trees renew their bark every year, so it is possible to take samples without damaging them, in order to assess the quantity of particles accumulated over a year. The precise location of the samples is a crucial parameter. Using the PartiCollect app, you can geolocate each tree sampled and associate a unique code with it, as well as descriptive and environmental parameters. You can then mark this code on the freezer bag used to collect your bark sample (one per tree).

What’s new

Version 4.0.7 · Updated April 23, 2025

* PartiCollect is now available in Dutch * Bug fixes and improvements

App privacy

The developer, SPOTTERON Gmbh, reported these privacy practices to Apple.

Data Linked to You

The following data, which may be collected and linked to your identity, may be used for the following purposes:

  • Contact Info: Email Address
  • User Content: Emails or Text Messages, Photos or Videos
  • Identifiers: User ID

Used for: App Functionality

Data Not Linked to You

The following data, which may be collected but is not linked to your identity, may be used for the following purposes:

  • Location: Precise Location, Coarse Location

Used for: App Functionality

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