We analyze the temporal variations which can be observed within time series of variogram parameters (nugget, sill and range). Datasets have been obtained from previous geostatistical analysis of country wide datasets of daily air quality data (PM10) over a ten years time frame. Applying the Kolmogorov-Zurbenko filtering method, time series are being decomposed into their short-, mid-, and long-term component. Furthermore, the significance of a long term trend component is investigated by a block-bootstrap-based approach combined with linear regression. It is discussed if within these datasets the times series of nugget variance can provide information about the evolution of the mean measurement uncertainty of the related air pollutant, whereas the sill and the range parameter could contain information about the spatial representativeness of the monitoring stations.
KRACHT Oliver;
GERBOLES Michel;
2014-12-17
Initiative on "Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes"
JRC90461
http://www.harmo.org/conferences/Proceedings/_Varna/Varna_proceedings.asp,
https://publications.jrc.ec.europa.eu/repository/handle/JRC90461,
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