Real-time retrieval of aerosol chemical composition using effective density and the imaginary part of complex refractive index
2020
Abstract Knowledge of aerosol chemical composition is essential for the research on aerosol climate effect, air quality and health issues. With the development of optical remote-sensing technology, numerous aerosol chemical composition retrieval methods based on optical properties were developed. However, the existing algorithms lack the verification with similar measurements of aerosol chemical. In this work, a novel algorithm based on effective density (ρe) and imaginary part (k) of the complex refractive index (CRI) at λ = 365 and 532 nm was developed to retrieve four main aerosol components, including black carbon (BC), organic matter (OM), mineral dust (MD), and sum of sulfate, nitrate and ammonium (SNA). ρe was derived by converting aerodynamic to electrical mobility diameter. CRI was retrieved from Mie code and simultaneous measurement of particle number size distribution (PNSD) and the extinction and scattering coefficients (bext and bscat). Comprehensive sensitivity tests were performed to estimate the retrieval uncertainties from the measurements and a priori inputs. Validation of the algorithm was demonstrated using a series of observations at Shouxian (China) from November 30 to December 12, 2016. The measured and retrieved aerosol chemical compositions were compared and the two results showed good agreements, proving the reliability of the method. During one clean and two pollution periods, the variation of measured aerosol physical and optical properties and retrieved chemical composition were analyzed. The aerosol chemical composition changes can be well described by the transition of air mass sources for different pollution levels. This study provides a reliable, in-situ method for better constraining the relationship between aerosol chemical compositions and optical properties. This method will help monitor the pollution event, identify aerosol sources and verify the retrievals from remote sensing data.
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