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Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated biogenic volatile organic compound (BVOC) measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA, for the year 2020 with emissions estimated by the Model of Emissions of Gases and Aerosols from Nature version 3.2 (MEGANv3.2). The emissions were subjected to oxidation in a 0-D box model (F0AM v4.3) to generate time series of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability in regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDFα-pinene=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using an LDF =0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions–chemistry model constrained by regional concentrations of NOX and O3. 

This dataset includes 182,127 SMILES strings generated by 5 generations of oxidation using the GECKO-A model for alpha-pinene, decane, and toluene under typical continental atmospheric conditions. For each compound, physicochemical parameters (vapor pressure, Henry's law constant, and gas phase reaction rate constant with the hydroxyl radical) are estimated using several structure-activity relationships. Compounds are flagged according to in which oxidation systems they exceed a threshold of 0.1% of total modeled mass of their given molecular formula. Descriptions of this dataset and the parameter estimation are provided in Isaacman-VanWertz and Aumont, "Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters", Atmospheric Chemistry and Physics (2021). The subset of compounds 38,594 compounds used in the core analyses of that work are also flagged. Lifetimes for deposition and oxidation of all compounds are included in Version 3 and beyond, calculated using the approach and assumptions of Bi and Isaacman-VanWertz, Nature Geoscience. The same core compounds are used in that work. 

Abstract. Isoprene has the largest global non-methane hydrocarbon emission, and the oxidation of isoprene plays a crucial role in the formation of secondary organic aerosol (SOA). Two primary processes are known to contribute to SOA formation from isoprene oxidation: (1) the reactive uptake of isoprene-derived epoxides on acidic or aqueous particle surfaces and (2) the absorptive gas–particle partitioning of low-volatility oxidation products. In this study, we developed a new multiphase condensed isoprene oxidation mechanism that includes these processes with key molecular intermediates and products. The new mechanism was applied to simulate isoprene gas-phase oxidation products and SOA formation from previously published chamber experiments under a variety of conditions and atmospheric observations during the Southern Oxidant and Aerosol Studies (SOAS) field campaign. Our results show that SOA formation from most of the chamber experiments is reasonably reproduced using our mechanism, except when the concentration ratios of initial nitric oxide to isoprene exceed ∼ 2, the formed SOA is significantly underpredicted. The SOAS simulations also reasonably agree with the measurements regarding the diurnal pattern and concentrations of different product categories, while the total isoprene SOA remains underestimated. The molecular compositions of the modeled SOA indicate that multifunctional low-volatility products contribute to isoprene SOA more significantly than previously thought, with a median mass contribution of ∼ 57 % to the total modeled isoprene SOA. However, this contribution is intricately intertwined with IEPOX-derived SOA (IEPOX: isoprene-derived epoxydiols), posing challenges for their differentiation using bulk aerosol composition analysis (e.g., the aerosol mass spectrometer with positive matrix factorization). Furthermore, the SOA from these pathways may vary greatly, mainly dependent on the volatility estimation and treatment of particle-phase processes (i.e., photolysis and hydrolysis). Our findings emphasize that the various pathways to produce these low-volatility species should be considered in models to more accurately predict isoprene SOA formation. The new condensed isoprene chemical mechanism can be further incorporated into regional-scale air quality models, such as the Community Multiscale Air Quality Modelling System (CMAQ), to assess isoprene SOA formation on a larger scale.