J 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.