Background: Particulate matter (PM) air pollution is a serious concern in the city of Ostrava. Thus, in 2018, a project entitled "Validation of the relationships between PM 10 , PM 2.5 and PM 1 concentrations, and morbidity and mortality, in the heavily polluted region in the Czech Republic," was launched. The relationship between hospital admissions and mortality in the said region is based primarily on short-term PM 10 and PM 2.5 concentrations and indicative PM 1 measurement. The analysis of spatiotemporal variations and the relationship between PM 10 , PM 2.5 and PM 1 data from 3 measurement sites within the city of Ostrava is presented., Material and Methods: The analysis was based on the daily average PM concentrations for 5 and 6 months at 2 sites, and on the annual average values (2018-2019) at the baseline station. The correlations of and variability between PM fractions, seasonal differences and explanation of the differences found were the objectives of a detailed analysis. Especially, the potential PM 1 variability and its causes were analyzed with respect to the location of the site., Results: The study findings confirmed good correlations between the PM fractions. Compared to PM 10 , PM 2.5 concentrations were more predictive for PM 1 concentrations. The annual means of PM 10 , PM 2.5 and PM 1 reached 37.5, 29.9 and 27.1 μg/m 3 in 2018, respectively, and 25.8, 19.9 and 17.9 μg/m 3 in 2019, respectively. The concentration levels in the non-heating season were significantly lower than in the heating season in the 2 years under consideration. The levels of PM 10 , PM 2.5 and PM 1 were significantly correlated (the correlation coefficient, r > 0.96). The levels of PM 2.5 represented about 0.82-0.86 of PM 10 , and the levels of PM 1 about 0.92-0.93 of PM 2.5 . These ratios were found to differ in the heating and non-heating seasons, with the PM 2.5 -PM 10 ratio ranging 0.61-0.63 in the non-heating seasons., Conclusions: The correlations found will be used for indicative PM 1 measurements in other areas of the region. Seasonal variability should be taken into account as well. Med Pr. 2021;72(3):249-58., (This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.)