SYRUP: A NOVEL INVERSION METHOD FOR AEROSOL SIZE-DISTRIBUTION PROPERTIES FROM OPTICAL AND CHEMICAL MEASUREMENTS OF PM2.5

Abstract

Accurate knowledge of aerosol mass scattering efficiency (αsp) is essential to the realistic simulation of aerosol radiative forcing effects on climate as well as to the visibility influences of aerosols and also to the interpretation of satellite data. The comparison between measurement and simulation of αsp may act as a prognostic factor in determining how accurately a model is representing optical characteristics and size-distribution parameters for aerosols. This study deals with improving representation of the latter parameters through the development of an inversion algorithm of αsp which yields size-distributions. Through the deployment of 5 measurement sites across Canada the measurement of PM2.5 (Particulate matter under a mean diameter of 2.5 μm) mass and chemical composition through filter-sampling stations was conducted from 2017 to 2019. Concurrently at all sites a 3-wavelength integrating nephelometer measured ambient scattering. By performing a multiple linear regression (MLR) on the data-set, the αsp values for the 5 bulk chemical components of PM2.5 are derived. Utilizing the wavelength sensitivity of αsp, an algorithm is developed that inverts the measurements for aerosol size-distribution properties. The dry geometric mean diameter (Dpg) of organics, secondary-inorganics, black carbon, sea-salt, and dust is found to be 0.56, 0.62, 0.54, 0.46, and 0.51 μm, respectively. The variance of these distributions (σg), ordered as above, is found to be 1.45, 1.30, 1.28, 1.61, and 1.63, respectively (Unitless). The increases in dry diameter compared to values previously used in radiative transfer models is corroborated by the results of scanning mobility particle sizer data. These revised representations of aerosols size-distributions will enable more accurate modeling of radiative processes involving aerosols.