Detailed Information on Publication Record
2021
Tracing the movement of persistent organic pollutants at a high-mountain sampling site by chemometric assessment
VAKARELSKA, Ekaterina, Miroslava NEDYALKOVA, Nina NIKOLOVA, Christo ANGELOV, Dimitar TONEV et. al.Basic information
Original name
Tracing the movement of persistent organic pollutants at a high-mountain sampling site by chemometric assessment
Authors
VAKARELSKA, Ekaterina, Miroslava NEDYALKOVA, Nina NIKOLOVA, Christo ANGELOV, Dimitar TONEV, Petra PŘIBYLOVÁ (203 Czech Republic, belonging to the institution), Jana KLÁNOVÁ (203 Czech Republic, guarantor, belonging to the institution) and Vasil SIMEONOV
Edition
JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH PART A-TOXIC/HAZARDOUS SUBSTANCES & ENVIRONMENTAL ENGINEERING, PHILADELPHIA, Taylor & Francis, 2021, 1093-4529
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10511 Environmental sciences
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 2.582
RIV identification code
RIV/00216224:14310/21:00124366
Organization unit
Faculty of Science
UT WoS
000685317600001
Keywords in English
POPs; passive sampling; BEO Moussala; multivariate statistical analysis
Tags
Tags
International impact, Reviewed
Změněno: 28/3/2022 09:05, Mgr. Marie Šípková, DiS.
Abstract
V originále
The main objective of the present study was to determine and differentiate the concentration levels, to define the probable sources of persistent organic pollutants (POPs) pollution in the atmospheric air and their seasonal variations in Bulgaria, on the high mountain peak Moussala, Rila Mountain. The study was based on the obtained results from the passive monitoring of POPs in 2014-2017. During this period, the measurements of POPs were performed with passive samplers, advanced instrumental methods analytically determined the concentrations of PAHs, and the analysis of the obtained data was performed by the multivariate statistical analysis (cluster, factor and time-series analysis). It is shown that the POPs species could be correctly classified according to their chemical nature into several patterns of similarity and their concentration profile depends on the annual season.