## 4 Conclusions  
As the results from the CALMET/CALPUFF modeling system assessment conducted by [PERSON] et al. [37] using high-resolution grids (200 m) show, this system is characterized by some underestimation of the calculation results in the vicinity of the emitter. On the other hand, the research performed by [PERSON] and [PERSON] [39] for gaseous substances (SO\({}_{2}\)) indicated that, with the grid resolution of 200 m, the CALPUFF model underestimates the maximum 1-h concentration values, at the same time allowing for obtaining very good results in a short range, for the averaging period of 24 h. On the basis of the calculations and studies presented in this paper, it was possible to obtain a partial answer to the question regarding to what extent the results of the gaseous pollutant dispersion in the CALMET/CALPUFF modeling system can vary for point sources with the height of 80 m, depending on the adopted computational grid resolution in the research area of 26 km \(\times\) 26 km (the region of the Krakow Urban Area). Increase in the grid spacing, from 100 to 250, 500 or 1000 m, resulted in a general (area average) overestimation of calculation results during all analyzed averaging periods, and thus their overestimation in the calculation area. The relatively smallest overestimation, as compared to a grid with the resolution of 100 m, occurred in the case of calculations made for a grid with the resolution of 250 m. For medium area values of maximum 1-h and 24-h and average annual concentrations, it amounted to, respectively, 4.2%, 6.1%, and 3.2%. On the other hand, in the case of a grid with the resolution of 500 m, the overestimation was the highest and reached, for these averaging periods, respectively, 12.8%, 23.9%, and 17.5%. From the point of view of assessing the impact on the air quality, performed for point emission sources, obtaining the most reliable information about the level and location of the highest concentration values in the air requires the use of a computational grid with possibly the highest resolution. For this purpose, it is recommended to use a grid with the resolution of 100 m. Only in the case of a grid with such spacing is it possible to reflect the potentially least favorable situations, including coinciding of the local maximum with the calculation point. Unfortunately, along with the increase in the number of calculation points, a growth in calculation duration occurs (calculation costs), which, in the case of grids with high density and considering many point emitters in the analysis, may prove to be too great of a barrier. Application of a grid with the resolution of 100 m is characterized by a ca. 16-times longer calculation time, as compared to a grid with the resolution of 250 m, and as much as a 1600-times longer as compared to a grid with the resolution of 1000 m. Making these calculations for a possibly greater number of emitters will also contribute to an additional extension of the calculation time. The size of the calculation area is also significant here, as an increase in it leads to an increase in the number of receptors in a grid of a given density. High labor consumption, related to the preparation of the model input data, creates an additional barrier. The use of a grid with the resolution of approximately 250 m seems to be good solution in the assessment of the impact on the air quality, as it is characterized by a slight general overestimation of the results as compared to a grid with the resolution of 100 m, and a relatively short duration of the calculations. Furthermore, the grid should reflect the close-range maxima results very well for long averaging periods. It is confirmed by the conducted statistical analysis of the modeling results of concentrations in the air obtained with various computational grid resolutions, especially in the analysis of average values of the examined statistical indicators and the variability of the fractional bias (FB) in the adopted discrete receptors.