Polar organic compounds in PM10 and PM2.5 atmospheric aerosols from a background Eastern Mediterranean site during the winter period: Secondary formation, distribution and source apportionment

Kanellopoulos, Panagiotis Georgios; Chrysochou, Eirini; Koukoulakis, Konstantinos; Vasileiadou, Emily; Kizas, Christos; Savvides, Chrysanthos; Bakeas, Evangelos

doi:10.1016/j.atmosenv.2020.117622

Cited by 14 publications

(2 citation statements)

References 108 publications

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“…In the present study PCA was carried out utilizing elemental concentration data of 40 samples for the post-monsoon season. Numerous other studies have employed PCA for source apportionment using limited data points viz; Hazarika et al (2015) utilized data from 12 samples for each season (summer, winter and monsoon) to perform PCA analysis, Liu et al (2018) utilized data from 15 day samples, similarly Zhang et al (2019) and Kanellopoulos et al (2020) also utilized limited data set to carry out source apportionment analysis using PCA.…”

Section: Source Apportionment Using Pcamentioning

confidence: 99%

Elemental Characteristics and Source-Apportionment of PM2.5 During the Post-monsoon Season in Delhi, India

Bangar

Mishra

Jangid

et al. 2021

Front. Sustain. Cities

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In this study, we have coupled measurements, modeling, and remote sensing techniques to better delineate the source characteristics and variability of air pollutants in Delhi primarily during the post-monsoon season in 2019. We show a comparison of ambient PM2.5 (particulate matter having aerodynamic diameter ≤2.5 μm) levels and associated elements during the post-monsoon with those during a relatively clean season of monsoon (experiencing frequent wet precipitation). Air-mass back trajectories from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model have been used to infer the possible source pathways of PM2.5 impacting at the receptor site in Delhi. The average concentrations of PM2.5 during monsoon (June–July) and post-monsoon (October–November) were 42.2 ± 15.5 μg m−3 (range: 22–73 μg m−3) and 121.4 ± 53.6 μg m−3 (range: 46–298 μg m−3), respectively. The PM2.5 samples were analyzed for heavy and trace elements (Si, S, Na, Mg, Al, Cl, Ca, K, Ti, V, Cr, Mn, Fe, Ni, Cu, Br, Rb, Zr, and Pb) using an Energy Dispersive X-ray Fluorescence (ED-XRF) technique and their concentrations have been used to carry out the source-apportionment utilizing principal component analysis (PCA) tool. The PCA analysis has identified three major sources of fine aerosols including contributions from the sources viz. vehicular emission, biomass burning, coal combustion, secondary aerosols formation, soil dust, solid-waste burning and industrial emission. The source involving biomass burning contributed largely to the PM2.5 in post-monsoon season through long-range transport of large-scale agriculture-residue burning emissions (occurring in the states of Punjab, Haryana, and western part of Uttar Pradesh). The industrial emissions include primarily, medium- and small-scale metal processing industries (e.g. steel sheet rolling) in Delhi-National Capital Region. Traces of emission from coal based thermal power plants and waste incineration have also been observed in this study.

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Section: Source Apportionment Using Pcamentioning

confidence: 99%

Elemental Characteristics and Source-Apportionment of PM2.5 During the Post-monsoon Season in Delhi, India

Bangar

Mishra

Jangid

et al. 2021

Front. Sustain. Cities

View full text Add to dashboard Cite

show abstract

“…Statistical analysis was performed using SPSS software package (IBM SPSS statistics version 24). This statistical software package was suitable for multivariate analysis of the environmental data [16,[35][36][37][38][39]. Shapiro-Wilk and Kolmogorov-Smirnov tests used to study whether the data followed normal distribution with a value of p > 0.05 indicated normal distribution.…”

Section: Discussionmentioning

confidence: 99%

Atmospheric Concentrations and Health Implications of PAHs, PCBs and PCDD/Fs in the Vicinity of a Heavily Industrialized Site in Greece

et al. 2020

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Background: Thriassion Plain is considered the most industrialized area in Greece and thus a place where emissions of pollutants are expected to be elevated, leading to the degradation of air quality. Methods: Simultaneous determination of polycyclic aromatic hydrocarbons (PAHs), polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs), and polychlorinated biphenyls (PCBs) was performed in PM10 samples. SPSS statistical package was employed for statistical analysis and source apportionment purposes. Cancer risk was estimated from total persistent organic pollutants’ (POPs) dataset according to the available literature. Results: POPs concentrations in particulate matter were measured in similar levels compared to other studies in Greece and worldwide, with mean concentrations of ΣPAHs, ΣPCDD/Fs, dioxin like PCBs, and indicator PCBs being 7.07 ng m−3, 479 fg m−3, 1634 fg m−3, and 18.1 pg m−3, respectively. Seasonal variations were observed only for PAHS with higher concentrations during cold period. MDRs, D/F ratios, and principal component analysis (PCA) highlighted combustions as the main source of POPs’ emissions. Estimation of particles’ carcinogenic and mutagenic potential indicates the increased toxicity of PM10 during cold periods, and cancer risk assessment concludes that 3 to 4 people out of 100,000 may suffer from cancer due to POPs’ inhalation. Conclusions: Increased cancer risk for citizens leads to the necessity of chronic POPs’ monitoring in Thriassion Plain, and such strategies have to be a priority for Greek environmental authorities.

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Regional sources and the economic cost assessment of PM2.5 in Ji'nan, eastern China

Zhang

Zhu

et al. 2021

Atmospheric Pollution Research

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Polar organic compounds in PM10 and PM2.5 atmospheric aerosols from a background Eastern Mediterranean site during the winter period: Secondary formation, distribution and source apportionment

Cited by 14 publications

References 108 publications

Elemental Characteristics and Source-Apportionment of PM2.5 During the Post-monsoon Season in Delhi, India

Elemental Characteristics and Source-Apportionment of PM2.5 During the Post-monsoon Season in Delhi, India

Atmospheric Concentrations and Health Implications of PAHs, PCBs and PCDD/Fs in the Vicinity of a Heavily Industrialized Site in Greece

Regional sources and the economic cost assessment of PM2.5 in Ji'nan, eastern China

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