ORIGINAL RESEARCH
Outlier Identification of Concentrations
of Pollutants in Environmental Data Using
Modern Statistical Methods
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1
University of Defence, Department of Quantitative Methods, Brno, Czech Republic
2
University of Pardubice, Faculty of Transport Engineering, Pardubice, Czech Republic
3
Lublin University of Technology, Faculty of Mechanical Engineering, Department of Machine Design
and Mechatronics, Lublin, Poland
4
University of Life Sciences in Lublin, Faculty of Production Engineering, Lublin, Poland
Submission date: 2018-06-12
Final revision date: 2019-09-24
Acceptance date: 2019-09-25
Online publication date: 2019-12-04
Publication date: 2019-12-09
Corresponding author
Petr Veselík
Department of Quantitative Methods, University of Defence, Czech Republic
Pol. J. Environ. Stud. 2020;29(1):853-860
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ABSTRACT
The article is focused on identification of outlier measurements in environmental data which may
significantly affect the future results of the analysis and interpretation of results. For this reason, their
identification forms an integral part of data analysis. The aim of this article is to perform statistical
analysis that automatically identifies segments of outlier measurements. The results were demonstrated
on real concentration data. The methodological procedure was used to evaluate particulate matter of the
PM10 fraction size from two monitoring stations located in Brno, Czech Republic.