Abstract
Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.
Highlights
Organic aerosol (OA) accounts for a substantial fraction of atmospheric particulate matter (Jimenez et al, 2009), which is closely associated with human health impacts and climate change (Cohen et al, 2017; Kanakidou et al, 2005; Lelieveld et al, 2015)
One of the major reasons for underestimated OA is the absence of semi-volatile organic compounds (SVOCs) from residential biomass burning in the current emission inventories (Denier van der Gon et al, 2015)
Increasing evidence from chamber experiments has demonstrated that losses of semi-volatile vapors to chamber walls could lead to a substantial underestimation of OA (Akherati et al, 2020; Bertrand et al, 2018; Bian et al, 2015; Krechmer et al, 2016; Loza et al, 2010; Matsunaga and Ziemann, 2010; Zhang et al, 2014)
Summary
Organic aerosol (OA) accounts for a substantial fraction of atmospheric particulate matter (Jimenez et al, 2009), which is closely associated with human health impacts and climate change (Cohen et al, 2017; Kanakidou et al, 2005; Lelieveld et al, 2015). We (1) developed a VBS-based box model and fit the vapor-wall-loss-corrected SOA yields of biomass burning IVOCs based on 14 chamber experiments under different temperature and emission loads, (2) implemented the vaporwall-loss-corrected VBS parameters in the regional chemical transport model Comprehensive Air Quality Model with extensions (CAMx), and (3) investigated the role of vapor wall loss correction in model performance by comparing modeled organic aerosols from traditional and modified VBS OA schemes with ambient observations at multiple European sites. Biomass burning in this study refers to residential biomass burning, while wildfires and prescribed burning are not included
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