Source apportionment of organic pollutants in fine and coarse atmospheric particles in Doha, Qatar

Abstract

In this study, we investigated the sources of organic pollutants associated with fine (PM 2.5) and coarse (PM 2.5-10) atmospheric particulate matter in Doha, Qatar based on an eight-month sampling campaign conducted from May to December 2015. Multiple organic compound tracers including 36 PAH members, 25 n-alkane homologs, 17 hopanes, and 12 steranes were used for organic aerosols source apportionment. Source apportionment based on specific molecular markers, molecular diagnostic ratios/indices, and positive matrix factorization (PMF) modeling showed that similar sources are responsible for both fine-and coarse-particle organic pollutants. PMF analysis showed that biogenic aerosols, fugitive dust emissions, gasoline engine emissions, diesel engine emissions, and heavy oil combustion were the five main pollution sources of organic aerosols, which agreed well with the results from the diagnostic ratios analysis. The conditional bivariate probability functions (CPF) and potential source contribution function (PSCF) indicated that both regional (i.e., mixed biogenic/secondary particles and oil refinery/shipping emissions) and local sources contributed to airborne organic aerosol concentrations observed at the site, depending on the wind speed and direction. It appears that the relatively high levels of organic pollutants were contributed by local anthropogenic sources, such as fossil fuel combustion, vehicular emissions, and fugitive dust emissions. The high levels of local contributions indicated that there might be great opportunities for Qatar to considerably reduce emissions so that population exposures to carbonaceous aerosols and the public health risks associated with air pollution can be minimized. Implications: Multiple organic tracers and various source apportionment techniques have been used for convincing source apportionment. It was found that both long-range and local sources have a significant impact on atmospheric carbonaceous particles in the area, depending on the wind conditions. Relatively high levels of organic pollutants attributed to local anthropogenic sources indicate that there are great opportunities for Qatar to establish and implement more efficient pollution control measures and policies. Regional sources such as petroleum refineries and shippingvessels emissions in the Gulf region should also be regulated and managed through regional cooperation to improve the air quality in the region.

Annual exposure to PAHs in urban environments linked to wintertime wood-burning episodes

“…The factor was characterized by stronger contributions to HMW PAHs (e.g., IP, BghiP and Cor), over lower-MW members (Figure 2). This feature has been used to differentiate the gasoline source from general traffic sources in several PAH source apportionment studies (Callén et al, 2013;Javed et al, 2019;Sofowote et al, 2008;Wu et al, 2014). The OC/EC ratio in the source profile was 1.9, within the range (1.7-2.3) typically reported for fresh emissions from 290 gasoline vehicles (Grivas et al, 2012).…”

Investigating the concentration levels, distribution patterns, source identification and health risk assessment of PAHs, n-alkanes, hopanes, and steranes in deposited dust of Mashhad, Iran

“…In this research, widely used DRs for PAHs, hopanes, steranes, and n-alkanes indices were measured and compared to the literature to get an initial implication of the organic aerosol emission sources (Javed et al 2019, Mostafa et al 2009, Omar et al 2007. DRs have been effectively used as indicators of PAH sources by various studies (Al Ali et al 2017, Dong &Lee 2009, Mon et al 2020, Ravindra et al 2008, Wang et al 2011) by considering the relative thermodynamic stability of different parent PAHs and the characteristics of different sources (Bian et al 2016).…”

“…CPI values are used to compare the contribution of vehicular and human activities to biological sources (Moeinaddini et al 2014a, Ravindra et al 2008, with values close to unity indicating vehicle emissions and other human activities, and values >3 indicating a predominant origin from biological materials. The WNA% value (WNA = C n -[(C n+1 + C n−1 )/2] where n is the odd carbon congener, WNA% = (∑WNA/∑n-alkanes)*100) is calculated for odd carbon number homologues, and it is used to indicate biogenic as opposed to petrogenic sources (Javed et al 2019, Omar et al 2007, Zhang et al 2017. (Andreou et al 2008, Rogge et al 1993a).…”

“…Molecular marker analysis may also be used to classify organic matter origins, allowing for comparing identi ed sources and observed atmospheric organic compound mixtures (Mostafa et al 2009, Omar et al 2007, Zhang et al 2017. PAHs and other organic pollutants may be adsorbed onto PM (Ghanavati et al 2019, Javed et al 2019. PAH compounds are biodegradable and may not be stable in the environment after they have been released.…”

“…Some of these compounds, such as PAHs, hopanes, and steranes, are persistent and potentially harmful, posing a signi cant health risk as they can cause mutagenic and carcinogenic effects (Liu et al 2015). These various organic compounds, on the other hand, can be used as a source recognition and health risk assessment marker (Javed et al 2019).…”