## 4 Discussion  
### Geochemical Indices and So-Called Contamination Classes  
The mean values of geochemical indices used in this study (gI), i.e., _Igeo'C, Igeo'N, nEF'Al'C, nEF'Al'N,_ and nE'N_ (Table S5), in seven evenly distributed sampling sites during four periods from 04.03.2020 to 19.08.2020 are discussed, aiming to compare them with respective values from published data. In each from three paired sampling sites 1 and 2, 3 and 4 and 8 and 9 which are close to each other (Figure 1), the results are averaged for each period to obtain more even distribution of gI values in the study territory. The uncertainty of contamination level estimated by _Igeo_ resulting from different _Cv_ or _Bn_ values in the denominator of formula, was demonstrated by e.g., [PERSON] and [PERSON] [36] and other researchers. It is also obvious for Klaipeda, from comparison of so-called contamination classes (_SCC_) distinguished according to two alternative _Igeo_ indices. If the mean _Igeo'C_ was selected instead of the mean _Igeo'N_, the estimated _SCC_ of nine analytes, i.e., Cl, Cu, Ca, As, Fe, Sr, Ni, Cr, V (with asterisks in Figure 8), would be lower, while by Br would be higher. Hence, the choice of _Igeo'C_ would lead to conclusion about cleaner ambient air in Klaipeda. The answer to the question why most analytes in TSP of Klaipeda have higher _Igeo'N_ values in comparison with _Igeo'C_ and there are only  
Figure 7: Cluster analysis dendrogram of complete dataset of TSP. When using alternative normalized enrichment factors \(nEF\), the differences in assignment to \(SCC\) are also seen. In comparison with \(nEF\)'AI'C, the mean \(nEF\)'AI'N values of Br, S, P, Pb, K, Zr, Rb, Si, and Ti distinguish lower \(SCC\) and the city dust was entitled as less contaminated by them, while the mean \(nEF\)'AI'N values of Ca, V, and Sr resulted in higher \(SCC\) (Figure 9). Similarly, to _Igeo_, these differences were determined by \(Cv\) and \(Bn\) values, but in this case, of two elements: (i) for which the index was calculated; (ii) the reference element used for normalization. In our case, the latter was Al (Formula (4)), therefore for the selected element, the ratio of alternative \(nEF\) values \(nEF\)'AI'C/\(nEF\)'AI'N was a constant value, calculated as follows: \((Cv_{Al}/Bn_{Al})/(Cv/Bn)\) (Table S5). Figure 8: Mean values of _Igeo’C_ and _Igeo’N_. The analytes are sorted by decreasing _Igeo’C_ values. *—analytes for which so-called contamination classes of alternative indices are different. Figure 9: Mean values of \(nEF\)’AI’C and \(nEF\)’AI’N. The analytes are sorted by decreasing \(nEF\)’AI’C values. *—analytes for which so-called contamination classes of alternative indices are different. Since the number of possible different \(SCC\) for two aforementioned indices is not equal (seven for _Igeo_ and four for \(nEF\)), we compared the frequency of attribution of analytes to the \(SCC\) which are higher than \"moderately contaminated\" (Section 2.5), i.e., the number of so-called more strongly contaminating analytes (\(CA\)). When using _Igeo_'C (when \(Cv\) is in the denominator) \(CA=4\), i.e., Zn \(>\) Br \(>\) Cl \(>\) S, while in case of \(nEF\)'\(Al^{\prime}C\), \(CA=12\), i.e., Zn \(>\) Br \(>\) Fe \(>\) S \(>\) Cl \(>\) P \(>\) Cu \(>\) Cr, Pb \(>\) Ca \(>\) As \(>\) Ni. For _Igeo_'N (when \(Bn\) is in the denominator), \(CA=5\), i.e., Cl \(>\) Zn \(>\) Cu \(>\) S \(>\) Ca, for \(nEF\)'\(Al^{\prime}N\), \(CA=13\) (Fe \(>\) Cl \(>\) Zn \(>\) S \(>\) Cu \(>\) Cr \(>\) Ca \(>\) P, Br \(>\) Ni \(>\) Sr \(>\) As \(>\) V). Thus, whichever alternative of _Igeo_ index (either _Igeo_'C or _Igeo_'N) was used for assignment to a specific \(SCC\), the general ambient air state in Klaipeda according to \(SCC\) title would seem better than using each of alternative \(nEF\)'\(Al\) indices. However, the greatest confusion is caused by generalization of results when the study territories were compared only according to the \(SCC\) title.