2016
DOI: 10.4209/aaqr.2015.09.0538
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Chemical Compositions of PM2.5 at Two Non-Urban Sites from the Polluted Region in Europe

Abstract: The study presents the analysis of measurement results for the ambient mass concentrations of fine particulate matter (PM 2.5 ). The 24-h PM 2.5 samples were collected in the heating and non-heating seasons at two regional background sites in Southern Poland in 2011-2013. The percentage of the secondary organic and inorganic matter in PM 2.5 was calculated.Over the whole measurement period, the mean PM 2.5 concentration was 31.56 µg m -3 and 24.92 µg m -3 in Racibórz and Złoty Potok, respectively. Regardless… Show more

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Cited by 21 publications
(42 citation statements)
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“…1.]. It should be mentioned that concentrations of main components in analysed PM2.5 samples were comparable for Trzebinia and Zloty Potok sites from Southern Poland -one of the regions of Poland with the highest degree of urbanization and pollution of all the components of the environment [11]. The combined share of secondary inorganic ions in PM2.5 from investigated areas was lower (eg.…”
Section: Characterization Of Pm25 and Major Componentsmentioning
confidence: 90%
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“…1.]. It should be mentioned that concentrations of main components in analysed PM2.5 samples were comparable for Trzebinia and Zloty Potok sites from Southern Poland -one of the regions of Poland with the highest degree of urbanization and pollution of all the components of the environment [11]. The combined share of secondary inorganic ions in PM2.5 from investigated areas was lower (eg.…”
Section: Characterization Of Pm25 and Major Componentsmentioning
confidence: 90%
“…and Mg 2+ ions were not taken into account, due to a large number of results below the detection limit. Bearing in mind the chemical behaviour of organic carbon [11], the secondary organic carbon (SOC) and primary organic carbon (POC) were considered as independent variables. The method dor the determination of SOC and POC content in PM2.5 was specified in previous works [11].…”
Section: Principal Component Analysis/multiple Linear Regression (Pcamentioning
confidence: 99%
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