Supplementary material to "Technical Note: A new approach to discriminate different black carbon sources by utilising fullerenes and metals in Positive Matrix Factorisation analysis of High-Resolution Soot Particle Aerosol Mass Spectrometer data"

Abstract. Atmospheric aerosol particles are known to have detrimental effects on human health and climate. Black carbon is an important constituent of atmospheric aerosol particulate matter (PM), emitted from the incomplete combustion process and cause significant effects on the air quality and human health. Source apportionment of BC is very important, to identify the fraction of BC that has an anthropogenic origin and to evaluate the influence of different sources. The High-Resolution Soot Particle Aerosol Mass Spectrometer (HR-SP-AMS) instrument uses a laser vaporizer, which allows the real-time detection and characterization of refractory BC and its internally mixed particles such as metals, coating species and rBC subcomponent in the form of fullerene. In this case study, the soot data was collected by using HR-SP-AMS during Guy Fawkes Night on 5th of November 2014. Positive matrix factorization (PMF) was applied in order to positively discriminate between different wood-burning sources for the first time, in this case, BC from domestic wood-burning and bonfires, which no existing black carbon source apportionment technique is currently able to do. Along with this, the use of the fullerene signals in differentiating between soot sources and the use of metals as a tracer for fireworks has also been investigated, which has not significantly contributed to the BC concentrations. The addition of fullerenes signals and successful application of PMF on SP-AMS data apportioned BC into more than two sources. These bonfire sources are hydrocarbon-like Fullerenes, biomass burning organic aerosol, HULIS (humic-like substance) and non-bonfire sources such as hydrocarbon-like OA and domestic burning. The result of correlation analysis between HR-SP-AMS data with previously published Aethalometer, MAAP and CIMS data provides an effective way of quickly gaining insights in relations between the variables and also provide a quantitative estimate of the source contributions to the BC budget during this period. This research study is an important demonstration of using HR-SP-AMS for the purpose of BC source apportionment.

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