## 3 Results and Discussion
In this comparison, Case V1-V2 definitely returns the least diverse results, as it shows the lowest MG values for all average times, and a  
Figure 4: Comparison of spatial distributions of maximum 1-h NO\({}_{2}\) concentrations in the air near the land surface (\(\mu\)g/m\({}^{3}\)), received in the CALMET/CALPUFF modeling system, in the case of the computational grids with the resolution of: **(a)** 100 m; **(b)** 250 m; **(c)** 500 m; and **(d)** 1000 m.  
maximum underestimation of the calculation results at 7.5% of the reference value for the maximum daily concentrations. The values of normalized mean square error (NMSE) and geometrical variance (VG) presented in Table 4, measuring both systematic and random errors, are within the so-called good models (NMSE <1.5; VG < 4.0), which in this case means good compliance. They show that, along with prolongation of the concentrations averaging time, the compared variants have smaller dispersion in relation to the average value. The largest deviation from the average value was obtained for Case V1-V3, while the lowest for Case V1-V2. However, for none of the analyzed cases, the twofold deviation of the results was reached in relation to the average value (NMSE > 0.5), therefore the deviations are very small. The above statements are reflected in the values obtained for the correlation coefficient (R) and FAC2. The values of FAC2 indicate that, in the case of average annual concentrations, two times the standard overestimations and underestimations of the calculation results, as compared to Variant V1, are very rarely observed. The highest number of double overestimations and underestimations of the results were recorded for Case V1-V4, with regard to the maximum 24-h concentrations. On the other hand, in Case V1-V2, only 1% of discrete receptors showed twofold overestimations or underestimations of the calculation results of the maximum 1-h concentrations, while there were no observed double overestimations or underestimations of the calculation results of the maximum 24-h and average annual concentrations. Figure 5: Comparison of spatial distributions of maximum 24-h NO\({}_{2}\) concentrations in the air near the land surface (\(\upmu\)g/m\({}^{3}\)), received in the CALMET/CALPUFF modeling system, in the case of the computational grids with the resolution of: (**a**) 100 m; (**b**) 250 m; (**c**) 500 m; and (**d**) 1000 m.  
Since the FB ratio is based on the average deviation, it is possible to obtain FB values = 0.0 for the compared variants (perfect convergence), even though, in reality, the modeling results are not convergent. Therefore, it has been decided to additionally present the FB values for each discrete calculation receptor to ensure better presentation of the differences between particular calculation variants. The fractional bias variability (FB), presented in Figure 7 for 676 discrete calculation receptors, shows a high diversity of the modeling results for different types of concentrations in the air obtained for grids of lower resolution, as compared to Variant V1 (the grid with the resolution of 100 m). An analysis of the examined cases indicates that Variants V2, V3 and V4 are characterized by a similar deviation, as compared to the reference variant. Furthermore, the standard deviations decrease along with the prolongation of the averaging period. It should be emphasized that the highest FB value ratios were recorded in each concerned averaging period for Case V1-V3, and the lowest--for Case V1-V2. This fact indicates that the mapping of Variant V4 is better than in the case of Variant V3, as compared to Variant V1. The indicator value FB = 0 means a perfect convergence, and negative values mean an overestimation of the concentrations, as compared to the reference value (V1). The greatest spread of the calculation results occurred in the case of the maximum 1-h concentrations. In most receptors there is an overestimation of the modelled concentrations in the relation to Variant V1.