Abstract

Abstract. Residential wood combustion remains one of the most important sources of primary organic aerosols (POA) and secondary organic aerosol (SOA) precursors during winter. The overwhelming majority of these precursors have not been traditionally considered in regional models, and only recently were lignin pyrolysis products and polycyclic aromatics identified as the principal SOA precursors from flaming wood combustion. The SOA yields of these components in the complex matrix of biomass smoke remain unknown and may not be inferred from smog chamber data based on single-compound systems. Here, we studied the ageing of emissions from flaming and smoldering-dominated wood fires in three different residential stoves, across a wide range of ageing temperatures (−10, 2 and 15 ∘C) and emission loads. Organic gases (OGs) acting as SOA precursors were monitored by a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS), while the evolution of the aerosol properties during ageing in the smog chamber was monitored by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). We developed a novel box model based on the volatility basis set (VBS) to determine the volatility distributions of the oxidation products from different precursor classes found in the emissions, grouped according to their emission pathways and SOA production rates. We show for the first time that SOA yields in complex emissions are consistent with those reported in literature from single-compound systems. We identify the main SOA precursors in both flaming and smoldering wood combustion emissions at different temperatures. While single-ring and polycyclic aromatics are significant precursors in flaming emissions, furans generated from cellulose pyrolysis appear to be important for SOA production in the case of smoldering fires. This is especially the case at high loads and low temperatures, given the higher volatility of furan oxidation products predicted by the model. We show that the oxidation products of oxygenated aromatics from lignin pyrolysis are expected to dominate SOA formation, independent of the combustion or ageing conditions, and therefore can be used as promising markers to trace ageing of biomass smoke in the field. The model framework developed herein may be generalizable for other complex emission sources, allowing determination of the contributions of different precursor classes to SOA, at a level of complexity suitable for implementation in regional air quality models.

Highlights

  • Atmospheric aerosols impact visibility, human health, and climate on a global scale (Stocker et al, 2013; World Health Organization, 2013)

  • We developed a novel box model based on the volatility basis set (VBS) to determine the volatility distributions of the oxidation products from different precursor classes found in the emissions, grouped according to their emission pathways and secondary organic aerosol (SOA) production rates

  • Results from these studies consistently show that the measured concentrations of secondary organic aerosol (SOA), formed upon oxidation and partitioning of the oxidized vapours, greatly exceed estimated concentrations based on the oxidation of volatile organic compounds (VOCs) traditionally assumed to be the dominant SOA precursors (Jathar et al, 2012)

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Summary

Introduction

Atmospheric aerosols impact visibility, human health, and climate on a global scale (Stocker et al, 2013; World Health Organization, 2013). Bruns et al, 2016; Bian et al, 2017), car exhaust (Gordon et al, 2014a, b; Platt et al, 2017; Gentner et al, 2017; Pieber et al, 2018), aircraft exhaust (Miracolo et al, 2011; Kılıç et al, 2018) or cooking emissions (Klein et al, 2016) Results from these studies consistently show that the measured concentrations of secondary organic aerosol (SOA), formed upon oxidation and partitioning of the oxidized vapours, greatly exceed estimated concentrations based on the oxidation of volatile organic compounds (VOCs) traditionally assumed to be the dominant SOA precursors (Jathar et al, 2012). Robinson et al (2007) suggested that a significant fraction of the unexplained SOA is due to the oxidation of lower-volatility organics, i.e. semi-volatile and intermediate-volatility organic compounds (SVOC and IVOC, respectively), collectively referred to as non-traditional SOA (NT-SOA) precursors (Donahue et al, 2009)

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