Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach

Y Hu,M T Odman,A G Russell,J Baek,H Holmes,C Ivey,S Balachandran,J E Pachon,J A Mulholland

doi:10.5194/acp-14-5415-2014

Y Hu, M T Odman + Show 7 more

Open Access

https://doi.org/10.5194/acp-14-5415-2014

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Abstract

Abstract. A hybrid fine particulate matter (PM2.5) source apportionment approach based on a receptor model (RM) species balance and species specific source impacts from a chemical transport model (CTM) equipped with a sensitivity analysis tool is developed to provide physically and chemically consistent relationships between source emissions and receptor impacts. This hybrid approach enhances RM results by providing initial estimates of source impacts from a much larger number of sources than are typically used in RMs, and provides source–receptor relationships for secondary species. Further, the method addresses issues of source collinearities and accounts for emissions uncertainties. We apply this hybrid approach to conduct PM2.5 source apportionment at Chemical Speciation Network (CSN) sites across the US. Ambient PM2.5 concentrations at these receptor sites were apportioned to 33 separate sources. Hybrid method results led to large changes of impacts from CTM estimates for sources such as dust, woodstoves, and other biomass-burning sources, but limited changes to others. The refinements reduced the differences between CTM-simulated and observed concentrations of individual PM2.5 species by over 98% when using a weighted least-squares error minimization. The rankings of source impacts changed from the initial estimates, further demonstrating that CTM-only results should be evaluated with observations. Assessment with RM results at six US locations showed that the hybrid results differ somewhat from commonly resolved sources. The hybrid method also resolved sources that typical RM methods do not capture without extra measurement information for unique tracers. The method can be readily applied to large domains and long (such as multi-annual) time periods to provide source impact estimates for management- and health-related studies.

Highlights

Fine particulate matter (PM2.5) with an aerodynamic diameter less than 2.5 μm is associated with adverse effects on human health (e.g., Dockery et al, 1993)
Rj less than 1 means that the refined impact is reduced from the original, while larger than 1 means that the impact is increased from the initial simulation
Prescribed burning emissions are distributed uniformly over time in the inventories, while in reality burns occur on days with favorable burning conditions

Summary

Introduction

Fine particulate matter (PM2.5) with an aerodynamic diameter less than 2.5 μm is associated with adverse effects on human health (e.g., Dockery et al, 1993). Quantifying the impacts of individual sources on the ambient concentration of fine particulate matter, better known as source apportionment (SA), is challenging. A fundamental issue with any SA method is that there is no way to directly measure source impacts, and it is difficult to assess the accuracy of source apportionment results. Tracer gases such as cyclic perfluoroalkanes and SF6 can be utilized to help quantify source impacts (Martin et al, 2011). Such an approach is typically limited to assess a specific source’s impact in special studies. Source apportionment results are typically evaluated by comparing simulated concentrations of individual components and total mass of PM2.5 with observations (e.g., Watson et al, 2008; Viana et al, 2008b)

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