
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 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.
What is the challenge?
Densely populated areas tend to suffer from poorer air quality than, e.g., rural areas. Existing air quality maps are often too coarse to capture local anomalies because they rely on coarse covariates, e.g. atmospheric transport model outputs. There is a need for air quality maps with a finer spatial resolution that reflect the small-scale differences in urban areas.
Our solution
We propose to increase the level of spatial detail of air quality maps through (1) downscaling predictor data (e.g., atmospheric transport model outputs) to regional and local settings and (2) including Citizen Science / Civic Tech data to improve air quality predictions.
Who will benefit?
European citizens, public health agencies and research, local authorities and the general public in selected urban areas will benefit from this use case.
Scope
Target Partner Organizations
OEMC Leading Partner
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Type of output
High-resolution (100 m) air quality maps for selected areas using the RIMM method and validated with high-quality EEA measurements.
Technology readiness level
TRL3: Experimental proof of concept
Location
Europe