Application of multivariate statistical analysis using organic compounds: Source identification at a local scale (Napajedla, Czechia)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F19%3A10241998" target="_blank" >RIV/61989100:27730/19:10241998 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0301479719303378" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0301479719303378</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jenvman.2019.03.035" target="_blank" >10.1016/j.jenvman.2019.03.035</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of multivariate statistical analysis using organic compounds: Source identification at a local scale (Napajedla, Czechia)

Popis výsledku v původním jazyce

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 PM 10 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. (C) 2019 Elsevier Ltd

Název v anglickém jazyce

Application of multivariate statistical analysis using organic compounds: Source identification at a local scale (Napajedla, Czechia)

Popis výsledku anglicky

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 PM 10 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. (C) 2019 Elsevier Ltd

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

<a href="/cs/project/LO1404" target="_blank" >LO1404: Trvale udržitelný rozvoj Centra ENET</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Environmental Management

ISSN

0301-4797

e-ISSN

—

Svazek periodika

238

Číslo periodika v rámci svazku

15. May 2019

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

8

Strana od-do

434-441

Kód UT WoS článku

000464296400046

EID výsledku v databázi Scopus

2-s2.0-85062616947