By Le Bellac M.
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Extra info for A short introduction to quantum information and quantum computation: solutions of exercises
Comparison of the distribution of the concentrations in the different parts of the space domain with the distribution of related emissions can give us some qualitative estimation of the reliability of the results. Comparing the results in Fig. 1 with the distribution of the NOX emissions in Europe (the distribution of the NOX emissions in Europe can be seen in upper right-hand-side plot in Fig. 2; see also Bastrup-Birk et al. , ) we can conclude that DEM is producing highest levels of the nitrogen dioxide pollution precisely in the parts of the space domain where the NOX emissions are highest, and in the large European cities (which are in general also big sources of NOX emissions), the levels of the nitrogen dioxide pollution is also high.
Monte Carlo techniques were used in Dimov and Zlatev  in order to find the rate coefficients to the variation of which the model results are most sensitive, and to study in a more systematic way the variation of the model results caused by random variations in a prescribed range of the selected rate coefficients. A simple box-model (one grid-point only and no other processes except the chemical reactions) is quite sufficient in the first part. The second part is much more complicated, because it requires a large number of runs of the whole air pollution model.
Of course, quantitative correctness of the model results is the most desirable property of an air pollution model. Most of the unresolved problems become immediately visible when one attempts to validate quantitatively the model results. The best that we can do at present (in the attempts to validate quantitatively the model results) is to compare model results with measurements taken at representative measurement stations located in different parts of the space domain. There are two major ways to present the results which are obtained when calculated by the model concentrations are compared with corresponding measurements.