Estimating mass-absorption cross-section of ambient black carbon aerosols: Theoretical, empirical, and machine learning models
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Estimating mass-absorption cross-section of ambient black carbon aerosols: Theoretical, empirical, and machine learning models

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  • Journal Title:
    Aerosol Science and Technology
  • Personal Author:
  • NOAA Program & Office:
    OAR (Oceanic and Atmospheric Research)
  • Description:
    The mass-absorption cross-section of black carbon (MACBC) is an essential parameter to link the atmospheric concentration of black carbon (BC) with its radiative forcing. When a direct calculation of MACBC based on observations of aerosol light absorption and BC mass concentration is impossible, we rely on modeling and simulations to estimate MACBC, but currently, there is no consensus model that can be relied on for accurate predictions across all atmospheric environments when BC particles have different coating thicknesses. Here, we applied five MACBC prediction models (including three light scattering theories, an empirical model based on observations of particle mass concentrations, and a machine learning model developed in our previous work) to aerosols from three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) field campaigns. While many studies have found that increasing the complexity of the models helps to constrain biases of the estimated MACBC, our effort is to evaluate the models based on the criteria of simplicity and accuracy. We find that our machine learning model (support vector machine for regression, SVM) generally performs well across all DOE ARM field campaign data, while the accuracy of core-shell Mie theory depends on the bias correction algorithm applied to filter-based light absorption data. Generally, the empirical model for internally mixed particles that we considered tends to over-predict MACBC, while Mie theory for externally mixed particles tends to under-predict MACBC. An examination of the influence of coating material on BC cores suggests that the performance of our current SVM model is degraded when the BC is thickly coated (e.g., it has undergone aging and mixing with other materials in the atmosphere).
  • Keywords:
  • Source:
    Aerosol Science and Technology, 56(11), 980-997
  • DOI:
  • ISSN:
    0278-6826;1521-7388;
  • Format:
    PDF
  • Publisher:
    Informa UK Limited
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA16OAR4310109
  • License:
  • Rights Information:
    CC BY-NC-ND
  • Compliance:
    Library
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