Assessing Regional Model Predictions of Wintertime SOA from Aromatic Compounds and Monoterpenes with Precursor-specific Tracers
Jie Zhang, Xiao He, Yaqin Gao, Shuhui Zhu, Shengao Jing, Hongli Wang, Jian Zhen Yu, Qi Ying
Abstract
The Community Multiscale Air Quality (CMAQ) model, with modifications to track precursor-specific SOA, was applied to model SOA formation from aromatic compounds and monoterpenes in Shanghai in November 2018. The modeled total aromatic SOA showed a strong correlation with measured 2,3-dihydroxy-4-oxopentanoic acid (DHOPA) concentrations in the ambient aerosols (R > 0.5 for hourly data and R > 0.75 for daily average data). The ratios of observed DHOPA and modeled aromatic SOA with all components included is around 0.5-1.6 × 10-3, lower than the commonly used ratio of 4 × 10-3 determined for toluene in a series of smog chamber experiments. This suggests that aromatic SOA could be underestimated when directly using the chamber-derived ratios. The predicted monoterpene SOA shows a stronger correlation with the sum of two α-pinene tracers (α-pinT), pinic acid and 3-MBTCA, with R > 0.6 and R > 0.8 for hourly and daily data, respectively. The α-pinT to modeled monoterpene SOA ratios are 0.13-0.25, which generally match the ratio of 0.168 ± 0.081 reported in chamber studies. However, since the current model does not treat α-pinene and its SOA explicitly, future modeling studies should include a more detailed treatment of monoterpene emissions and reactions to predict SOA from these important precursors and compare with the ambient precursor-specific SOA-tracers.