OEMC project use case: Air quality assessment at regional scale
Description
Air pollution is a health risk to millions of people in Europe. Heavier pollution occurs in densely populated or industrial areas where we can observe more combustion of fossil fuels. Relevant indicators for air quality are the concentrations of particles with sizes of ~10 µm (PM10) and ~2.5 µm (PM2.5), ozone (O3), and nitrogen-dioxide (NO2).
The EEA produces and reports annual air quality maps with a resolution of 1 km based on in situ data from official measurement stations in its member states. Although these measurements are reliable, the number and spatial distribution of stations is not optimal. Further, existing maps are too coarse in both the spatial and the temporal dimension to reflect on small-scale anomalies.
Building on top of OEMC Use Case: Air quality assessment at continental scale, we explore the potential of Citizen Science / Civic Tech data to improve air quality predictions in selected areas. These data are acquired with low-cost sensors and served to web platforms (OpenSenseMap, Sensor.Community) by private individuals. Despite larger measurement errors compared to EEA stations, these sensor networks may support predictions through high temporal sampling rates and complementary spatial coverage.
Stakeholder needs:
- Increase the accessibility and uptake of open air quality data
- An open-source workflow that provides high-resolution air quality maps
Planned implementation:
- Access Citizen Science / Civic Tech data through APIs and apply quality filtering
- Produce high-resolution (100 m) air quality maps for selected areas using the RIMM method
- Assess map quality improvements and validate with high-quality EEA measurements