Development of an Automatic system for Mapping Air quality risks in Space and Time (DAMAST)

The DAMAST project uses data from the ILM air quality monitoring network in Eindhoven which is part of the AiREAS civil initiative. This dataset contains the data from 2013-2017 on a number of air pollutants (PM10, PM2.5, PM1, UFP, NO2, O3) and additional variables measured (temperature, relative humidity, GPS location). It also contains the code used for data quality analysis, outlier detection, calibration, spatio-temporal modelling and mapping, and health impact assessment.

Air quality, Sensor network, Probability theory, Statistics, Atmospheric sciences, Air, Computer science