Application of Dimensionality Reduction and Machine Learning Methods for the Interpretation of Gas Sensor Array Readouts from Mold-Threatened Buildings  
[PERSON]  
1 Faculty of Environmental Engineering, Lublin University of Technology, 20-618 Lublin, Poland;  
[EMAIL_ADDRESS] (Z.S. ); [EMAIL_ADDRESS] (L.G.) [PERSON]  
2 Faculty of Technology Fundamentals, Lublin University of Technology, 20-618 Lublin, Poland;  
[EMAIL_ADDRESS] (D.M. ); [EMAIL_ADDRESS] (E.L.)  
[PERSON]  
2 Faculty of Civil Engineering, Czech Technical University in Prague, 166 29 Prague, Czech Republic;  
[EMAIL_ADDRESS] (V.K. ); cernypftsv.cvut.cz (R.C.) [PERSON]  
2 Faculty of Civil Engineering, Czech Technical University in Prague, 166 29 Prague, Czech Republic;  
[EMAIL_ADDRESS] (V.K. ); cernypftsv.cvut.cz (R.C.) [PERSON]  
1 Faculty of Environmental Engineering, Lublin University of Technology, 20-618 Lublin, Poland;  
[EMAIL_ADDRESS] (Z.S. ); [EMAIL_ADDRESS] (L.G.) [PERSON]  
1 Faculty of Environmental Engineering, Lublin University of Technology, 20-618 Lublin, Poland;  
[EMAIL_ADDRESS] (Z.S. ); [EMAIL_ADDRESS] (L.G.) [PERSON]  
3 Faculty of Civil Engineering, Czech Technical University in Prague, 166 29 Prague, Czech Republic;  
[EMAIL_ADDRESS] (V.K. ); cernypftsv.cvut.cz (R.C.) [PERSON]  
3 Faculty of Civil Engineering, Czech Technical University in Prague, 166 29 Prague, Czech Republic;  
[EMAIL_ADDRESS] (V.K. ); cernypftsv.cvut.cz (R.C.) Footnote 22: email: [EMAIL_ADDRESS] (M.P.-R.)  
Footnote 23: email: [EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (M.P.-R.)  
Footnote 24: email: [EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (M.P.-R.)  
Footnote 25: email: [EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (M.P.-R.)  
Footnote 26: email: [EMAIL_ADDRESS] (M.P.-R.)  
Footnote 20: emailrange in size, from a few micrometers to tens of micrometers; they are smaller than pollen grains and can enter the respiratory tract more deeply [5], causing allergic reactions from both the upper and lower respiratory tracts. It is possible to distinguish more than a few dozen species of mold, which are among the dangerous factors in building infrastructures. This is because of their low requirements for development conditions, resulting in their occurrence in many different places. The most commonly mentioned mold fungi include the genera _Penicillium_, _Aspergillus_ (_Aspergillus_ _Basticus_ _flavus_, _Aspergillus_ _fumigatus_, and _Aspergillus niger_), _Strachyotrys_ (_Stachybotrys chartarum_ and _Stachybotrys chartarum_) _Cladosporium_, _Alternalia_, and _Fusarium_[6; 7; 8]. Mold fungi are heterotrophic organisms with a eukaryotic structure. They feed on dead or living organic matter, and their enzymes enable the decomposition of complex organic compounds. Contamination of the indoor environment by fungi, and thus the increased occurrence of SBS, is mainly due to the presence of microbial volatile organic compounds (mVOCs) [9]. These substances are metabolites formed during the life processes of fungi and are volatile compounds due to their physicochemical properties [10; 11]. These compounds cause the characteristic odor of mold and the sensory indications of the presence of filamentous fungi in buildings. The toxins considered most harmful to human and animal health are metabolites of fungi from the genera _Stachybotrys chartarum_, _Fusarium_, and _Aspergillus_ _versicolor_[12]. The most dangerous mycotoxins produced by fungi include ochtaoxin a (OT), zearalenone (ZEN), aflat (AF), trichothecenes, and fumonisins (F) [13]. Other toxins produced by fungi include ketones, alcohols, esters, terpenes, and sulfur compounds, including the following [14]: ketones: 2-heptanone, 2-pentanone, and 3-octanone; alcohols: 2-methyl-1-butanol, 3-methyl-1-butanol, 2-methylpropanol, 3-octanol, 1-octonen-3-ol, 1-hexanol, 1-pentanol, 2-methylisoborneol, and geosmin; terpenes and sesquiterpenes: limonene and pinene; furams: 3-methylfuran; sulfur: 296 compounds; and hydrocarbons: alkanes, olefins, dienes, and trienes.