An evaluation of global organic aerosol schemes using airborne observations
Authors: Pai Sidhant J. , Heald Colette L. , Pierce Jeffrey R. , Farina Salvatore C. , Marais Eloise A. , Jimenez Jose L. , Campuzano-Jost Pedro , Nault Benjamin A. , Middlebrook Ann M. , Coe Hugh , Shilling John E. , Bahreini Roya , Dingle Justin H. , Vu Kennedy 
Published: March 2020

Abstract. Chemical transport models have historically struggled to
accurately simulate the magnitude and variability of observed organic
aerosol (OA), with previous studies demonstrating that models significantly
underestimate observed concentrations in the troposphere. In this study, we
explore two different model OA schemes within the standard GEOS-Chem
chemical transport model and evaluate the simulations against a suite of 15
globally distributed airborne campaigns from 2008 to 2017, primarily in the
spring and summer seasons. These include the ATom, KORUS-AQ, GoAmazon,
FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC
campaigns and provide broad coverage over a diverse set of
atmospheric composition regimes – anthropogenic, biogenic, pyrogenic and
remote. The schemes include significant differences in their treatment of
the primary and secondary components of OA – a “simple scheme” that models
primary OA (POA) as non-volatile and takes a fixed-yield approach to
secondary OA (SOA) formation and a “complex scheme” that simulates POA as
semi-volatile and uses a more sophisticated volatility basis set approach
for non-isoprene SOA, with an explicit aqueous uptake mechanism to model
isoprene SOA. Despite these substantial differences, both the simple and
complex schemes perform comparably across the aggregate dataset in their
ability to capture the observed variability (with an R2 of 0.41 and
0.44, respectively). The simple scheme displays greater skill in minimizing
the overall model bias (with a normalized mean bias of 0.04 compared to 0.30 for the
complex scheme). Across both schemes, the model skill in reproducing
observed OA is superior to previous model evaluations and approaches the
fidelity of the sulfate simulation within the GEOS-Chem model. However,
there are significant differences in model performance across different
chemical source regimes, classified here into seven categories.
Higher-resolution nested regional simulations indicate that model resolution
is an important factor in capturing variability in highly localized
campaigns, while also demonstrating the importance of well-constrained
emissions inventories and local meteorology, particularly over Asia. Our
analysis suggests that a semi-volatile treatment of POA is superior to a
non-volatile treatment. It is also likely that the complex scheme
parameterization overestimates biogenic SOA at the global scale. While this
study identifies factors within the SOA schemes that likely contribute to OA
model bias (such as a strong dependency of the bias in the complex scheme on
relative humidity and sulfate concentrations), comparisons with the skill of
the sulfate aerosol scheme in GEOS-Chem indicate the importance of other
drivers of bias, such as emissions, transport and deposition, that are
exogenous to the OA chemical scheme.