Spatial–temporal modellization of the $$\hbox {NO}_{2}$$ NO 2 concentration data through geostatistical tools

Raquel Menezes (), Helena Piairo, Pilar García-Soidán and Inês Sousa

Statistical Methods & Applications, 2016, vol. 25, issue 1, 107-124

Abstract: The nitrogen dioxide is a primary pollutant, regarded for the estimation of the air quality index, whose excessive presence may cause significant environmental and health problems. In the current work, we suggest characterizing the evolution of $$\hbox {NO}_{2}$$ NO 2 levels, by using geostatistical approaches that deal with both the space and time coordinates. To develop our proposal, a first exploratory analysis was carried out on daily values of the target variable, daily measured in Portugal from 2004 to 2012, which led to identify three influential covariates (type of site, environment and month of measurement). In a second step, appropriate geostatistical tools were applied to model the trend and the space–time variability, thus enabling us to use the kriging techniques for prediction, without requiring data from a dense monitoring network. This methodology has valuable applications, as it can provide accurate assessment of the nitrogen dioxide concentrations at sites where either data have been lost or there is no monitoring station nearby. Copyright Springer-Verlag Berlin Heidelberg 2016

Keywords: $$\hbox {NO}_{2}$$ NO 2; Geostatistics; Time series analysis; Space–time analysis (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10260-015-0346-3

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