In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)


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    Titel :

    Spatio-temporal modelling for assessing air pollution in Santiago de Chile


    Beteiligte:
    Nicolis, Orietta (Autor:in) / Camaño, Christian (Autor:in) / Maŕın, Julio C. (Autor:in) / Sahu, Sujit K. (Autor:in) / Sivasundaram, Seenith (Herausgeber:in)

    Kongress:

    ICNPAA 2016 WORLD CONGRESS: 11th International Conference on Mathematical Problems in Engineering, Aerospace and Sciences ; 2016 ; La Rochelle, France


    Erschienen in:

    Erscheinungsdatum :

    27.01.2017


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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