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Chemosphere ◽  
2021 ◽  
Vol 278 ◽  
pp. 130429
Author(s):  
Yingze Tian ◽  
Xiao Liu ◽  
Ruiqing Huo ◽  
Zongbo Shi ◽  
Yueming Sun ◽  
...  

Chemosphere ◽  
2021 ◽  
Vol 274 ◽  
pp. 129913
Author(s):  
Sarkawt Hama ◽  
Prashant Kumar ◽  
Mohammed S. Alam ◽  
Daniel J. Rooney ◽  
William J. Bloss ◽  
...  

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 554
Author(s):  
Yasmany Mancilla ◽  
Gerardo Medina ◽  
Lucy T. González ◽  
Pierre Herckes ◽  
Matthew P. Fraser ◽  
...  

Source attribution of airborne particulate matter (PM) relies on a host of different chemical species. Organic molecular markers are a set of particularly useful marker compounds for estimating source contributions to the fine PM fraction (i.e., PM2.5). Although there are many source apportionment studies based on organic markers, these studies heavily rely on the few studies that report region-specific emission profiles. Source attribution efforts, particularly those conducted in countries with emerging economies, benefit from ad hoc information to conduct the corresponding analyses. In this study, we report organic molecular marker source profiles for PM2.5 emitted from 12 major sources types from five general source categories (meat cooking operations, vehicle exhausts, industries, biomass and trash burning, and urban background) for the Monterrey Metropolitan Area (Mexico). Source emission samples were obtained from a ground-based source-dominated sampling approach. Filter-based instruments were utilized, and the loaded filters were chemically characterized for organic markers by GC-MS. Levoglucosan and cholesterol dominate charbroiled-cooking operation sources while methoxyphenols, PAHs and hopanes dominate open-waste burning, vehicle exhaust and industrial emissions, respectively. A statistical analysis showed values of the Pearson distance < 0.4 and the similarity identity distance > 0.8 in all cases, indicating dissimilar source profiles. This was supported by the coefficient of divergence average values that ranged from 0.62 to 0.72. These profiles could further be utilized in receptor models to conduct source apportionment in regions with similar characteristics and can also be used to develop air pollution abatement strategies.


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