Transformation of logwood combustion emissions in a smog chamber: formation of secondary organic aerosol and changes in the primary organic aerosol upon daytime and nighttime aging

Abstract

Abstract. Organic aerosols (OA) derived from small-scale wood combustion emissions are not well represented by current emissions inventories and models, although they contribute substantially to the atmospheric particulate matter (PM) levels. In this work, a 29 m3 smog chamber in the ILMARI facility of the University of Eastern Finland was utilized to investigate the formation of secondary organic aerosol (SOA) from a small-scale modern masonry heater commonly used in northern Europe. Emissions were oxidatively aged in the smog chamber for a variety of dark (i.e., O3 and NO3) and UV (i.e., OH) conditions, with OH concentration levels of (0.5–5) × 106 molecules cm−3, achieving equivalent atmospheric aging of up to 18 h. An aerosol mass spectrometer characterized the direct OA emissions and the SOA formed from the combustion of three wood species (birch, beech and spruce) using two ignition processes (fast ignition with a VOC-to-NOx ratio of 3 and slow ignition with a ratio of 5).Dark and UV aging increased the SOA mass fraction with average SOA productions 2.0 times the initial OA mass loadings. SOA enhancement was found to be higher for the slow ignition compared with fast ignition conditions. Positive matrix factorization (PMF) was used to separate SOA, primary organic aerosol (POA) and their subgroups from the total OA mass spectra. PMF analysis identified two POA and three SOA factors that correlated with the three major oxidizers: ozone, the nitrate radical and the OH radical. Organonitrates (ONs) were observed to be emitted directly from the wood combustion and additionally formed during oxidation via NO3 radicals (dark aging), suggesting small-scale wood combustion may be a significant ON source. POA was oxidized after the ozone addition, forming aged POA, and after 7 h of aging more than 75 % of the original POA was transformed. This process may involve evaporation and homogeneous gas-phase oxidation as well as heterogeneous oxidation of particulate organic matter. The results generally prove that logwood burning emissions are the subject of intensive chemical processing in the atmosphere, and the timescale for these transformations is relatively short, i.e., hours.

Secondary organic aerosol formation from smoldering and flaming combustion of biomass: a box model parametrization based on volatility basis set

“…In the same way, we also observe a higher SOA production for Set 1 compared to Set 2 at comparable OH exposure. The SOA-to-POA ratio ranges between 2 and 6, similar to ratios observed in previous studies (Heringa et al, 2011;Bruns et al, 2015;Grieshop et al, 2009;Tiitta et al, 2016).…”

Production of Secondary Organic Aerosol During Aging of Biomass Burning Smoke From Fresh Fuels and Its Relationship to VOC Precursors

“…They observed good agreement between measured SOA mass and predictions based on the oxidation of mostly pyrogenic VOCs, that is, benzene, naphthalene, and toluene. Tiitta et al (2016) and Bruns et al (2016) studied a more controlled form of combustion and burned only dried hardwood, and they did not observe any monoterpene emissions. In our experiments with coniferous canopy fuels (e.g., black spruce and ponderosa pine) we burned freshly harvested whole branches with foliage.…”

Six-year source apportionment of submicron organic aerosols from near-continuous highly time-resolved measurements at SIRTA (Paris area, France)

“…Only m/z values ranging from 13 to 100 were applied in the PMF analysis due to larger uncertainties for larger m/z ions and large interferences of naphthalene (m/z 128) signals (Sun et al, 2012). Down-weighting of the m/z 44 group of ions for the PMF model analysis was performed following procedures implemented in the ACSM Local software and following the data treatment strategy proposed by Ulbrich et al (2009).…”

“…Online aerosol characterization techniques, such as aerosol mass spectrometry (AMS), have demonstrated their capacity to improve our knowledge of key aerosol chemical components -such as OA -by providing highly timeresolved mass spectral data for the nonrefractory PM 1 fraction (NR-PM 1 ) (Jayne et al, 2000;Canagaratna et al, 2007). Using receptor model approaches, especially positive matrix factorization (PMF) (Paatero and Tapper, 1994), OA measured by AMS techniques can be further portioned into various source factors using statistic models (Ulbrich et al, 2009;Zhang et al, 2011). For example, hydrocarbon-like OA (HOA) is frequently identified within urban environments and attributed to primary emissions from fuel consumption (Zhang et al, 2007;Jimenez et al, 2009), while biomass burning OA (BBOA) is often resolved specifically during cold seasons or within wild fire plumes Lanz et al, 2010;Zhou et al, 2017).…”