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An evaluation of European air pollution regulations for particulate matter monitored from a heterogeneous network

Record type: Article

Statistical methods are needed for evaluating many aspects of air pollution regulations increasingly adopted by many different governments in the European Union. The atmospheric particulate matter (PM) is an important air pollutant for which regulations have been issued recently. A challenging task here is to evaluate the regulations based on data monitored on a heterogeneous network where PM has been observed at a number of sites and a surrogate has been observed at some other sites. This paper develops a hierarchical Bayesian joint space-time model for the PM measurements and its surrogate between which the exact relationship is unknown, and applies the methods to analyse spatio-temporal data obtained from a number of sites in Northern Italy. The model is implemented using MCMC techniques and methods are developed to meet the regulatory demands. These enablefull inference with regard to process unknowns, calibration, validation, predictions in time and space and evaluation of regulatory standards.

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Citation

Sahu, Sujit K. and Nicolis, Orietta (2008) An evaluation of European air pollution regulations for particulate matter monitored from a heterogeneous network Environmetrics, 20, (8), pp. 943-961. (doi:10.1002/env.965).

More information

Published date: 20 October 2008
Keywords: bayesian inference, hierarchical model, markov chain monte carlo, separable spatio-temporal process, stationarity
Organisations: Statistics

Identifiers

Local EPrints ID: 147815
URI: http://eprints.soton.ac.uk/id/eprint/147815
ISSN: 1180-4009
PURE UUID: ddd4e4e0-7184-4f95-bad9-136c20b473c2
ORCID for Sujit K. Sahu: ORCID iD orcid.org/0000-0003-2315-3598

Catalogue record

Date deposited: 26 Apr 2010 13:25
Last modified: 18 Jul 2017 19:33

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Contributors

Author: Sujit K. Sahu ORCID iD
Author: Orietta Nicolis

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