Estimation of PM10 concentration in Italy with spatio-temporal statistical models: application examples
The report describes the use of a Bayesian hierarchical space-time model for the high spatial resolution estimate (1km x 1km) of daily PM10 concentrations, in order to give a demonstrative overview of possible applications. The model was applied, separately for each month, to the PM10 concentrations measured since 2013 to 2020 by the Italian regional air quality monitoring networks.
Tools like this, which allow to estimate the ground concentrations of atmospheric pollutants with high spatial resolution, in a homogeneous and reliable way over a supra-regional domain, can represent an interesting integration to the modeling tools already available and routinely used for air quality assessment, to estimate population exposure and in the health effect estimates that can be inferred from these.
Publication available only on-line
Download the publication(pdf - 7 mb)