• MeSH
• Atherosclerosis epidemiology   classification   mortality   MeSH
• Circle of Willis pathology   MeSH
• Child MeSH
• Adult MeSH
• Factor Analysis, Statistical MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Aged MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Geographicals
• Cuba MeSH

• MeSH
• Discriminant Analysis MeSH
• Air Pollutants analysis   MeSH
• Environmental Monitoring MeSH
• Data Collection MeSH
• Cluster Analysis MeSH
• Air Pollution MeSH
• Publication type
• Database MeSH

• MeSH
• Factor Analysis, Statistical MeSH
• Carcinoma MeSH
• Breast Neoplasms MeSH
• Prognosis MeSH

• MeSH
• Factor Analysis, Statistical MeSH
• Respiration Disorders analysis   physiopathology   MeSH
• Models, Theoretical MeSH

• MeSH
• Biometry MeSH
• Statistics as Topic MeSH

• Conspectus
• Statistika
• NML Fields
• statistika, zdravotnická statistika
• management, organizace a řízení zdravotnictví

• MeSH
• Behavior, Animal MeSH
• Rats MeSH
• Pentobarbital MeSH
• Psychophysiology MeSH
• Sleep analysis   MeSH
• Statistics as Topic MeSH
• Check Tag
• Rats MeSH

• MeSH
• Statistics as Topic utilization   MeSH
• Higher Nervous Activity MeSH

• MeSH
• Humans MeSH
• Statistics as Topic MeSH
• Educational Measurement methods   MeSH
• Check Tag
• Humans MeSH

The study aimed to apply novel source classification tool for local scale air pollution assessment reducing the total number of organic compounds in the model. Samples of particulate matter (PM) were collected in the town of Napajedla (South-eastern Czech Republic) in 2016. The industrial sector of the town is represented by plastics processing and manufacturing, as well as by mechanical engineering. Analytical technique of pyrolysis chromatography with mass spectroscopy detection was employed to identify organic species in the PM10 fraction. Two datasets (465 determined organic compounds and 50 selected organic markers) were used and compared by multivariate analysis - principal component analysis followed with hierarchical clustering on principal components incorporating compositional data approach. Three resulting clusters were observed in both cases. The cluster representing measurements near plastic processing and manufacturing plants was identical in both the analysed datasets with the same organic compounds that characterized resulting cluster Consequently, leading markers for plastic processing and manufacturing sources were suggested (bumetrizole, bis(tridecyl)phthalate, mono(2-ethylhexyl)phthalate). Other two clusters varied among the analysed datasets, however, dataset with selected markers showed more reliable outcomes. The results imply that concept of using only selected organic marker species with the compositional approach in multivariate statistical methods is sufficient and allows properly distinguishing the main air pollution sources between sampling locations even at a small urban scale.

• MeSH
• Air Pollutants * MeSH
• Environmental Monitoring MeSH
• Multivariate Analysis MeSH
• Particulate Matter MeSH
• Air Pollution * MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH

• MeSH
• Diagnostic Techniques, Surgical methods   instrumentation   statistics & numerical data   MeSH
• Endoscopy MeSH
• Humans MeSH
• Microspectrophotometry methods   instrumentation   statistics & numerical data   MeSH
• Minimally Invasive Surgical Procedures MeSH
• Multivariate Analysis MeSH
• Brain Neoplasms diagnosis   surgery   MeSH
• Check Tag
• Humans MeSH