ORIGINAL RESEARCH
Outlier Identification of Concentrations of Pollutants in Environmental Data Using Modern Statistical Methods
Petr Veselík 1  
,   Marie Sejkorová 2  
,   Aleksander Nieoczym 3  
,   Jacek Caban 4  
 
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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
CORRESPONDING AUTHOR
Petr Veselík   

Department of Quantitative Methods, University of Defence, Czech Republic
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
 
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.
eISSN:2083-5906
ISSN:1230-1485