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Abstract

Light-absorbing organic matter, known as brown
carbon (BrC), has previously been found to significantly en-
hance the absorption of solar radiation by biomass burning
(BB) aerosol. Previous studies have also proposed methods
aimed at constraining the BrC contribution to the overall
aerosol absorption using the absorption Ångström exponents
(AAEs) derived from the multi-wavelength remote observa-
tions at Aerosol Robotic Network (AERONET). However,
representations of the BrC absorption in atmospheric mod-
els remain uncertain, particularly due to the high variabil-
ity in the absorption properties of BB organic aerosol (OA).
As a result, there is a need for stronger observational con-
straints on these properties. We extend the concept of the
established AAE-based methods in the framework of our
Bayesian method, which combines remote optical observa-
tions with Monte Carlo simulations of the aerosol absorp-
tion properties. We propose that the observational constraints
on the absorption properties of BB OA can be enhanced by
using the single-scattering albedo (SSA) as part of the ob-
servation vector. The capabilities of our method were first
examined by using synthetic data, which were intended to
represent the absorption properties of BB aerosol originat-
ing from wildfires in Siberia. We found that observations of
AAEs and SSA can provide efficient constraints not only
on the BrC contribution to the total absorption but also on
both the imaginary part of the refractive index and the mass
absorption efficiency of OA. The subsequent application of
our method to the original multi-annual data from Siberian
AERONET sites, along with the supplementary analysis of
possible biases in the a posteriori estimates of the inferred
absorption properties, indicates that the contribution of BrC
to the overall light absorption by BB aerosol in Siberia at
the 440 nm wavelength is most likely to range, on average,
from about 15 % to 21 %, although it is highly variable and,
in some cases, can exceed 40 %. Based on the analysis of the
AERONET data, we also derived simple nonlinear param-
eterizations for the absorption characteristics of BB OA in
Siberia as functions of the AAE