Spatial model for daily air quality high resolution estimation

Abstract

In air quality modeling, fine-scale daily mapping is generally calculated from dispersion models involving multiple parameters linked in particular to emissions, which require regular updating and a long computation time. The aim of this work is to provide a simpler model, easily adaptable to other regions and capable of estimating nitrogen dioxide concentrations to a good approximation. To this end, we examine the relationship between daily and annual nitrogen dioxide values. We find that this relationship depends on the range of daily values. Then we provide a statistical model capable of estimating daily concentrations over large areas on a fine spatial scale. The model’s performance is compared with standard geostatistical method such as external drift kriging with cross-validation over one year. The reduced computation time means that daily maps can be produced for use by French air quality observatories.