Air-quality modelling in the Lake Baikal region.

In this paper, we assess the status of the air quality in the Lake Baikal region which is strongly influenced by the presence of anthropogenic pollution sources. We combined the local data, with global databases, remote sensing imagery and modelling tools. This approach allows to inventorise the air-polluting sources and to quantify the air-quality concentration levels in the Lake Baikal region to a reasonable level, despite the fact that local data are scarcely available. In the simulations, we focus on the month of July 2003, as for this period, validation data are available for a number of ground-based measurement stations within the Lake Baikal region.

Spatial interpolation of ambient ozone concentrations from sparse monitoring points in Belgium.

Due to scientific interest on the one hand and political and regulatory obligations on the other hand the monitoring of ozone in the troposphere is an important issue. To this end, in Belgium as in many other countries, a fixed network of monitoring stations is operated. In order to estimate the ozone concentrations over the whole territory, a model is needed to spatially complement the sparse measurements. This paper describes the development of an interpolation scheme which is aimed at fast operational use. The model uses the population density as auxiliary data to remove a spatial trend due to titration by nitric oxide. The residuals are interpolated by kriging. As a benchmark the inverse distance weighting interpolation method is used with and without the detrending. The proposed model systematically improves the interpolation and makes a significant difference when estimating human exposure to ozone. It is generic in design, easy to implement and flexible to changes in the monitoring network.