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Modelling mercury deposition through latent space-time processes

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  • Ana G. Rappold
  • Alan E. Gelfand
  • David M. Holland

Abstract

The paper provides a space-time process model for total wet mercury deposition. Key methodological features that are introduced include direct modelling of deposition rather than of expected deposition, the utilization of precipitation information (there is no deposition without precipitation) without having to construct a precipitation model and the handling of point masses at 0 in the distributions of both precipitation and deposition. The result is a specification that enables spatial interpolation and temporal prediction of deposition as well as aggregation in space or time to see patterns and trends in deposition. We use weekly deposition monitoring data from the National Atmospheric Deposition Program-Mercury Deposition Network for 2003 restricted to the eastern USA and Canada. Our spatiotemporal hierarchical model allows us to interpolate to arbitrary locations and, hence, to an arbitrary grid, enabling weekly deposition surfaces (with associated uncertainties) for this region. It also allows us to aggregate weekly depositions at coarser, quarterly and annual, temporal levels. Copyright Journal compilation (c) 2008 Royal Statistical Society. No claim to original US government works.

Suggested Citation

  • Ana G. Rappold & Alan E. Gelfand & David M. Holland, 2008. "Modelling mercury deposition through latent space-time processes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 187-205.
  • Handle: RePEc:bla:jorssc:v:57:y:2008:i:2:p:187-205
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    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9876.2007.00608.x
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    Cited by:

    1. Sujit K. Sahu & Alan E. Gelfand & David M. Holland, 2010. "Fusing point and areal level space-time data with application to wet deposition," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 77-103.

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