Mixed deterministic statistical modelling of regional ozone air pollution

Authors

  • S. Kalenderski,

    Corresponding author
    1. Building 1, Office # 3144, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
    • Building 1, Office # 3144, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.
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  • D.G. Steyn

    1. Atmospheric Science Program, Department of Earth and Ocean Sciences, The University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada
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Abstract

We develop a physically motivated statistical model for regional ozone air pollution by separating the ground-level pollutant concentration field into three components, namely: transport, local production and large-scale mean trend mostly dominated by emission rates. The model is novel in the field of environmental spatial statistics in that it is a combined deterministic-statistical model, which gives a new perspective to the modelling of air pollution. The model is presented in a Bayesian hierarchical formalism, and explicitly accounts for advection of pollutants, using the advection equation.

We apply the model to a specific case of regional ozone pollution—the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate that the model vastly outperforms existing, simpler modelling approaches. Our study highlights the importance of simultaneously considering different aspects of an air pollution problem as well as taking into account the physical bases that govern the processes of interest. Copyright © 2011 John Wiley & Sons, Ltd.

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