Using diagnostic ratios to characterize sources of polycyclic aromatic hydrocarbons in the Great Lakes atmosphere

The present study characterized source profiles of polycyclic aromatic hydrocarbons (PAHs) for the Great Lakes atmosphere using nine PAH diagnostic ratios (DRs). The samples were collected from six sites in the Great Lakes basin during 1996-2018 within the Integrated Atmospheric Deposition Network (IADN). In general, pyrogenic sources, including coal combustion and vehicular emissions, were the most important contributors to atmospheric profiles, in particular at the urban sites. Diesel emissions accounted for a larger portion of the traffic-originated PAHs than gasoline emissions at all sites, but this compositional pattern was less obvious at the urban sites. Temporal analyses for DRs revealed that the relative contribution of petrogenic sources and volatilization from surfaces has been increasing gradually, and that the gaps in PAH emissions between diesel- and gasoline-engines appeared to be further amplified in recent years. Coal combustion and non-pyrogenic emissions were the main PAH sources for winter and summer air, respectively, but none of the DRs responded to these changes. DRs were generally different between vapor and particle phases. Our findings shed light on spatial and temporal trends of PAH DRs and PAH source characterization in the Great Lakes basin. Additionally, this study confirmed the usefulness of DRs, especially when combined with the PMF analysis, while also highlighting the limitation of multiple DRs. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study characterized PAH source profiles in the Great Lakes atmosphere using nine PAH diagnostic ratios, highlighting the importance of pyrogenic sources and the significant contribution of diesel emissions to traffic-originated PAHs. Temporal analyses revealed increasing contributions from petrogenic sources and volatilization from surfaces, as well as amplified gaps in PAH emissions between diesel and gasoline engines in recent years. The study also confirmed the usefulness of DRs, especially when combined with PMF analysis, while pointing out the limitations of using multiple DRs.