Radiative properties of coated black carbon aggregates: numerical simulations and radiative forcing estimates

Abstract

Abstract. The formation of black carbon fractal aggregates (BCFAs) from combustion and subsequent aging involves several stages resulting in modifications of particle size, morphology, and composition over time. To understand and quantify how each of these modifications influences the BC radiative forcing, the radiative properties of BCFAs are modelled. Owing to the high computational time involved in numerical modelling, there are some gaps in terms of data coverage and knowledge regarding how radiative properties of coated BCFAs vary over the range of different factors (size, shape, and composition). This investigation bridged those gaps by following a state-of-the-art description scheme of BCFAs based on morphology, composition, and wavelength. The BCFAs radiative properties were investigated as a function of the radius of the primary particle (ao), fractal dimension (Df), fraction of organics (forganics), wavelength (λ), and mobility diameter (Dmob). The radiative properties are calculated using the multiple sphere T-matrix (MSTM) method. Amongst size, morphology, and composition, all the radiative properties showed the highest variability with changing size. The cross-sections varied from 0.0001 μm2 to 0.1 μm2 for BCFA Dmob ranging from 24 nm to 810 nm. After size or Dmob, the absorption cross-section (Cabs) and BC mass absorption cross-section (MACBC) showed the highest sensitivity towards composition or forganics, whereas the asymmetry parameter (g) showed higher dependence on morphology, which is represented by Df. The Ångstrom absorption exponent varied from 1.06 up to 3.6 and increases with the fraction of organics (forganics). The values of the absorption enhancement factor (Eλ) were found between 1.01 and 3.28 in the visible spectrum. The Eλ was derived from Mie calculations for coated volume equivalent spheres, and from MSTM for coated BCFAs. Mie calculated enhancement factors were found to be larger by a factor of 1.1 to 1.5 than their corresponding values calculated from the MSTM method. It is shown that radiative forcings are highly sensitive towards modifications in morphology and composition. The black carbon radiative forcing ΔFTOA (Wm−2) decreases up to 61 % as the BCFA becomes more compact in morphology. Whereas, there is a decrease of > 50 % in ΔFTOA as the organic content of the particle increase up to 90 %. Based on our results, which showed a significant effect of coating and morphology on the BC radiative properties, a parametrization scheme for radiative properties of BC fractal aggregates was developed, which is applicable for modelling, ambient, and laboratory-based BC studies. The parameterization scheme for the cross-sections (extinction, absorption, and scattering), single scattering albedo (SSA), and asymmetry parameter (g) of pure and coated BCFAs as a function of Dmob were derived from tabulated results of the MSTM method. Spanning over an extensive parameter space, the developed parametrization scheme showed promisingly high accuracy up to 98 % for the cross-sections, 97 % for single scattering albedos (SSA), and 82 % for asymmetry parameter (g).

Improving the predictions of black carbon (BC) optical properties at various aging stages using a machine-learning-based approach

“…The dataset of simulated physio-chemical and optical properties that we describe in Section 2 is available at https: //doi.org/10.5281/zenodo.7523058 (Romshoo et al, 2023a). In case they want to reproduce any of the results in this work, readers may find the entire source code that we used to perform the ML-based experiments and generate figures included in this work on https://github.com/jaikrishnap/Optical-properties-of-black-carbon-aggregates (Romshoo et al, 2023b).…”

Zero-Shot Learning of Aerosol Optical Properties with Graph Neural Networks

“…However, these approaches are computationally expensive, often requiring hours or even days to compute the optical properties of single aerosol particles with complex morphologies [23]. To mitigate this computational bottle-neck, pre-calculated databases of fractal aggregate optical properties using these exact analytical methods have recently been created [23,24,25,26], but such approaches are limited to linear interpolation within the data-bases' optical and morphological properties. There is still significant uncertainty about the fundamental properties of BC from different emission sources and under different combustion conditions, and the additional complexity of internal mixing with nonabsorbing and absorbing materials during atmospheric aging [2] would require these databases to cover a very large parameter space to accurately represent the range of conditions for BC aerosols observed in the atmosphere.…”