We developed a methodology able to automatically estimate of measurement uncertainty in the air pollution data sets of AirBase. The figures produced with this method were consistent with expectations from laboratory and field estimation of uncertainty and with the Data Quality Objectives of European Air Quality Directives. The proposed method based on geostatistical analysis is not able to estimate directly the measurement uncertainty. It estimates the nugget effect from variogram modelling together with a micro-scale variability which must be minimized by accurate selection of the type of station. Based on the results obtained so far, it is likely that measurement uncertainty is best estimated using all background stations of whatever area type. So far the methodology has been used to estimate measurement uncertainty in datasets from 4 different countries independently.
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