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Abstract
Abstract. Open biomass burning is a significant source of primary air pollutants such as particulate matter (PM) and non-methane organic gases (NMOG). However, the physical and chemical atmospheric processing of these emissions during transport is poorly understood. Atmospheric transformations of biomass burning emissions have been investigated in environmental chambers, but there have been limited opportunities to investigate these transformations in the atmosphere. In this study, we deployed a suite of real-time instrumentation on a Twin Otter aircraft to sample smoke from prescribed fires in South Carolina, conducting measurements at both the source and downwind to characterize smoke evolution with atmospheric aging. Organic aerosol (OA) within the smoke plumes was quantified using an aerosol mass spectrometer (AMS); refractory black carbon (rBC) was quantified using a single-particle soot photometer, and carbon monoxide (CO) and carbon dioxide (CO2) were measured using a cavity ring-down spectrometer. During the two fires for which we were able to obtain aerosol aging data, normalized excess mixing ratios and "export factors" of conserved species (rBC, CO, CO2) suggested that changes in emissions at the source did not account for most of the differences observed in samples of increasing age. An investigation of AMS mass fragments indicated that the in-plume fractional contribution (fm/z) to OA of the primary fragment (m/z 60) decreased downwind, while the fractional contribution of the secondary fragment (m/z 44) increased. Increases in f44 are typically interpreted as indicating chemical aging of OA. Likewise, we observed an increase in the O : C elemental ratio downwind, which is usually associated with aerosol aging. However, the rapid mixing of these plumes into the background air suggests that these chemical transformations may be attributable to the different volatilities of the compounds that fragment to these m/z in the AMS. The gas–particle partitioning behavior of the bulk OA observed during the study was consistent with the predictions from a parameterization developed for open biomass burning emissions in the laboratory. Furthermore, we observed no statistically significant increase in total organic mass with atmospheric transport. Hence, our results suggest that dilution-driven evaporation likely dominated over the chemical production of secondary organic aerosol (SOA) within our smoke plumes, presumably due to the fast dilution and limited aging times (< ~ 5 h) that we could sample.
Highlights
Open biomass burning is estimated to be the largest contributor to atmospheric fine carbonaceous particulate matter (PM) (Bond et al, 2013) and the second largest contributor to atmospheric non-methane organic gases (NMOG) on a global scale (Akagi et al, 2011)
We report and interpret observations from the South Carolina fiRe Emissions And Measurements (SCREAM) campaign conducted in October–November 2011 (Akagi et al, 2013, 2014; May et al, 2014; Sullivan et al, 2014)
Data near the source are presented as box-and-whisker plots (25th–75th and 10th–90th percentiles); these data were collected during roughly 2.5 h of sampling during which the modified combustion efficiency (MCE) (Ward and Radke, 1993) varied between 0.900 and 0.930, which explains some of the variability in the data
Summary
Open biomass burning is estimated to be the largest contributor to atmospheric fine carbonaceous particulate matter (PM) (Bond et al, 2013) and the second largest contributor to atmospheric non-methane organic gases (NMOG) on a global scale (Akagi et al, 2011). May et al.: Observations and analysis of organic aerosol evolution mary emissions from biomass burning and the development of emission inventories (Akagi et al, 2011; Burling et al, 2010, 2011; Christian et al, 2003; Hosseini et al, 2013; May et al, 2014; McMeeking et al, 2009; Reid et al, 2005; Urbanski, 2013; Urbanski et al, 2011; Watson et al, 2011; van der Werf et al, 2010; Wiedinmyer et al, 2006, 2011; Yokelson et al, 2013). These emissions are integrated into chemical transport models used to predict regional air quality and global climate impacts
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