Mass Extinction Efficiency Approximation for Polydispersed Aerosol Using Harmonic Mean-Type Approximation

• Main Authors: Junshik Um, Seonghyeon Jang, Young Jun Yoon, Seoung Soo Lee, Ji Yi Lee, Kyung Man Han, Won Jun Choi, Yong Pyo Kim, Cheol-Hee Kim, Chang Hoon Jung
• Format: Article
• Language: English
• Published: MDPI AG 2020-12-01
• Series: Applied Sciences
• Subjects: mass extinction efficiency; extinction coefficient; polydispersed aerosol; reconstruction method; Mie scattering; harmonic mean type approximation
• Online Access: https://www.mdpi.com/2076-3417/10/23/8637

Among many parameters characterizing atmospheric aerosols, aerosol mass extinction efficiency (MEE) is important for understanding the optical properties of aerosols. MEE is expressed as a function of the refractive indices (i.e., composition) and size distributions of aerosol particles. Aerosol MEE is often considered as a size-independent constant that depends only on the chemical composition of aerosol particles. The famous Malm’s reconstruction equation and subsequent revised methods express the extinction coefficient as a function of aerosol mass concentration and MEE. However, the used constant MEE does not take into account the effect of the size distribution of polydispersed chemical composition. Thus, a simplified expression of size-dependent MEE is required for accurate and conventional calculations of the aerosol extinction coefficient and also other optical properties. In this study, a simple parameterization of MEE of polydispersed aerosol particles was developed. The geometric volume–mean diameters of up to 10 µm with lognormal size distributions and varying geometric standard deviations were used to represent the sizes of various aerosol particles (i.e., ammonium sulfate and nitrate, elemental carbon, and sea salt). Integrating representations of separate small mode and large mode particles using a harmonic mean-type approximation generated the flexible and convenient parameterizations of MEE that can be readily used to process in situ observations and adopted in large-scale numerical models. The calculated MEE and the simple forcing efficiency using the method developed in this study showed high correlations with those calculated using the Mie theory without losing accuracy.