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Published January 2019 | Supplemental Material
Journal Article Open

Black Carbon Aggregates: A Database for Optical Properties

Abstract

Black carbon (BC) aerosol plays an important role in the atmosphere as an absorber of solar radiation and contributes significantly to global warming. The optical properties of BC are fundamental for both direct radiative effect studies and remote sensing of BC properties. However, due to the complex aggregation structures of BC particles, accurate simulations of their optical properties are limited and computationally expensive, while equivalent spherical models or approximate methods could easily introduce relative errors up to 30%. This study generates a comprehensive database to calculate aggregate optical properties efficiently and accurately. The database covers a wide range of BC properties including aggregation structure, refractive index, and particle size (both monomer size and number of monomers). An accurate numerical model, i.e. the multiple-sphere T-matrix method, is used to calculate the single-scattering properties of BC clusters in the form of fractal aggregates. By interpolation, the database can be used to give the scattering properties of aggregates with monomer number from 1 up to 3000, monomer size parameter from 0.05 to 0.5, real part of refractive index from 1.2 to 2.0, and imaginary part from 0.2 to 1.0. The relative errors caused by the interpolation are much less than 1% for the single scattering properties. The pre-calculated database and the implementation used to calculate the required aggregate optical properties are publicly available for users interested in remote sensing of BC aerosols and performing radiative effect calculations.

Additional Information

© 2018 Elsevier Ltd. Received 5 July 2018, Revised 12 October 2018, Accepted 14 October 2018, Available online 16 October 2018. The database developed in this study is available upon request from Chao Liu (chao_liu@nuist.edu.cn). We thank Daniel W. Mackowski and Michael I. Mishchenko for the MSTM code. This work was supported by the R&D Special Fund for Public Welfare of China (Meteorology) (GYHY201506002), the Natural Science Foundation of China (41505018), the Young Elite Scientists Sponsorship Program by CAST (2017QNRC001), the State Scholarship Fund by the China Scholarship Council (201708320049), and the Helmholtz Research Program Atmosphere and Climate. The computation of this study was supported by the National Supercomputer Center in Guangzhou (NSCC-GZ).

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