Methods for spatially misaligned environmental data

We work on statistical methods to improve the characterisation of air pollution. In particular, we are developing Bayesian models to integrate data sources coming from measurements as well as numerical model outputs or satellites and accounting for misalignment that naturally occur when dealing with separate sources. We are also extending the framework to a multi-pollutant approach.

Marta Blangiardo
Marta Blangiardo
Professor of Biostatistics

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