SPATIAL TEMPORAL MODELLING OF PARTICULATE MATTER FOR HEALTH EFFECTS STUDIES

We present a Bayesian estimation of uncertainty in half-hourly GPP partitioned from flux tower measurements of NEE. The results show that it is possible to do this at any desirable time step. This, in turn, can be used to quantify the propagated uncertainty when validating process-based simulators. We further show the importance of using non-informative priors compared to informative priors of the parameters of flux partitioning model as they speed up calculation without loss of precision.