Sep 12, 2022

Measurements and perceptions of air quality

First Name
Last Name
What is the name of your organization?
What best describes the type of organisation that you are representing?
Type of organization – Other
Accredited Independant Association with mixed funding
Where are you based?
7 Rue Crillon
Paris 75004
Map It
What is the name of your initiative?
Measurements and perceptions of air quality
How would you describe the main mission of your initiative?
  • Measure/monitor air quality
  • Raise awareness/education
  • Air quality modelling


Please provide a short description of your initiative* (What is being done? Who is participating? What are your main goals?) This text will appear on the main page.
The aim of the project is to improve knowledge of the levels of pollution at the heart of traffic, while testing a new network of measurements, and to understand the perception of Ile-de-France residents with regard to air quality. These innovations will make it possible to raise awareness of air quality in Ile-de-France, and ultimately to identify the levers of commitment of Ile-de-France residents to reduce air pollution.
Who is your main audience?
  • Citizens
  • Other government administrations


If possible, provide the list of partners involved in the initiative.
It is piloted by AIRLAB, the innovation platform of Airparif, in partnership with Geoptis, La Poste and Atmotrack and funded by the Île-de-France Region .
How is this initiative funded?
  • Other


Context – Other
Regional funding
Please provide an estimation of the total budget of the initiative:
More than 1 000 000€
What is the status of the initiative?
What is the duration of the initiative?
1 to 5 years
How many participants (citizen scientists, volunteers, etc.) have been involved (approximately)?
I don’t know
Website that presents your initiative’exp%C3%A9rimentation%20%22Mesures%20et%20Perceptions,R%C3%A9gion%20%C3%8Ele%2Dde%2DFrance.
Please upload a picture to illustrate your initiative


Technical Details
Name of the equipment
The number of these devices used in your initiative (estimation):
  • Commercial product


Measured parameter (you can select several)
  • PM1
  • PM2.5
  • PM10
  • New Option


PM1 – Unit
PM1 – Technology
Optical counter
PM1 – Range of measurement
PM1 – Service life
> 2 years
PM1 – Detection limit
PM2.5 – Unit
PM2.5 – Technology
Optical counter
PM2.5 – Range of measurement
PM2.5 – Service life
> 2 years
PM2.5 – Detection limit
PM10 – Unit
PM10 – Technology
Optical counter
PM10 – Range of measurement
PM10 – Service life
> 2 years
PM10 – Detection limit
New option
New Option – parameter’s name
Particle count
Are there any other technical details you would like to share?
Manufacturer website:
Results for the device in the AIRLAB Microsensors Challenge:
Communication type
  • 2G-3G


Energy type
  • Other


Energy type – Other
12 V – car plug
Does your device allow SD cards?
  • No


Temporal resolution
Temporal resolution – Other
10 seconds
Where are you measuring air quality?
Device’s location
  • Street – public domain
  • Mobile : Bike mounted
  • Mobile : Car mounted
  • Public building
  • Mixed


Level of expertise required to operate
Simple if you take the time to read the documentation
What is the approximate market price per unit?
800 EUR
Are there any other costs related to this equipment?
3480 EUR over 3 years including device purchase, data subscription and maintenance costs.


Are you using a platform for data visualisation?
Yes, we have created our own data platform
Is your platform open source?
Are there any other interesting links related to the data platform?
From 0 (the lowest) to 5 (the highest), how easily accessible and user-friendly is your platform?
Are you providing open data?
How is the data made accessible?
  • The data is NOT made accessible


How frequently is the data refreshed in the data platform?
How long does it take before the newest data is available on your platform?
1 day
Do you give access to historical data?
What type of data visualisation do you provide?
  • Statistics / Indicators / Charts
  • Maps
  • Report


Would you like to share with us any additional information? (Max 300 words)
The large scale of the sensor deployment (600 devices over more than 18 months) generated a very large amount of data, which tested the limits of our usual data representation formats making the fast accesibility of data difficult. This has motivated us to adapt our approaches and include more big-data capabilities (e.g., NoSQL databases) for future projects.
For this type of deployment the ability to deploy real-time diagnosis tools is critical in order to reduce costs and data loss. Effective communication between technical and operational partners was key to be able to react to events like sensor malfunctions.

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