Abstract

Abstract. In this study we provide a first estimate of the Aethalometer multiple scattering correction Cref for mineral dust aerosols. Cref is an empirical constant used to correct the aerosol absorption coefficient measurements for the multiple scattering artefact of the Aethalometer; i.e. the filter fibres on which aerosols are deposited scatter light and this is miscounted as absorption. The Cref at 450 and 660 nm was obtained from the direct comparison of Aethalometer data (Magee Sci. AE31) with (i) the absorption coefficient calculated as the difference between the extinction and scattering coefficients measured by a Cavity Attenuated Phase Shift Extinction analyser (CAPS PMex) and a nephelometer respectively at 450 nm and (ii) the absorption coefficient from a MAAP (Multi-Angle Absorption Photometer) at 660 nm. Measurements were performed on seven dust aerosol samples generated in the laboratory by the mechanical shaking of natural parent soils issued from different source regions worldwide. The single scattering albedo (SSA) at 450 and 660 nm and the size distribution of the aerosols were also measured. Cref for mineral dust varies between 1.81 and 2.56 for a SSA of 0.85–0.96 at 450 nm and between 1.75 and 2.28 for a SSA of 0.98–0.99 at 660 nm. The calculated mean for dust is 2.09 (±0.22) at 450 nm and 1.92 (±0.17) at 660 nm. With this new Cref the dust absorption coefficient by the Aethalometer is about 2 % (450 nm) and 11 % (660 nm) higher than that obtained by using Cref = 2.14 at both 450 and 660 nm, as usually assumed in the literature. This difference induces a change of up to 3 % in the dust SSA at 660 nm. The Cref seems to be independent of the fine and coarse particle size fractions, and so the obtained Cref can be applied to dust both close to sources and following transport. Additional experiments performed with pure kaolinite minerals and polluted ambient aerosols indicate Cref of 2.49 (±0.02) and 2.32 (±0.01) at 450 and 660 nm (SSA = 0.96–0.97) for kaolinite, and Cref of 2.32 (±0.36) at 450 nm and 2.32 (±0.35) at 660 nm for pollution aerosols (SSA = 0.62–0.87 at 450 nm and 0.42–0.76 at 660 nm).

Highlights

  • Mineral dust is abundant and widespread in the atmosphere and strongly contributes to the global and regional direct radiative effect and climate forcing (Highwood and Ryder, 2014; Miller et al, 2014)

  • Data from the MAAP, CAPS, nephelometer, OPC and SMPS were averaged over 2 min, so they could be reported as having the same resolution as the Aethalometer

  • In this paper we presented an intercomparison study between an Aethalometer and a MAAP, a nephelometer, and two CAPS with the aim of determining a two-wavelength multiple scattering correction (Cref) for Aethalometer measurements for weakly absorbing mineral dust aerosols

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Summary

Introduction

Mineral dust is abundant and widespread in the atmosphere and strongly contributes to the global and regional direct radiative effect and climate forcing (Highwood and Ryder, 2014; Miller et al, 2014). The evaluation of the direct effect of mineral dust and its climate implications is still limited by knowledge of the intensity of dust absorption in the shortwave spectral range (Miller et al, 2004; Balkanski et al, 2007; Solmon et al, 2008; Jin et al, 2016), represented by the light absorption coefficient (βabs, units of Mm−1). Sandradewi et al, 2008; Formenti et al, 2011; Di Biagio et al, 2016), which corresponds to the mean of observations at 660 nm for soot aerosols (W2003) Both W2003 and C2010, found a dependence of Cref on the aerosol single scattering albedo, with Cref decreasing for increasing SSA. Control experiments on pure kaolinite mineral, ambient aerosols sampled in the polluted environment of the suburbs of Paris, and purely scattering ammonium sulfate were performed to investigate the dependence of Cref on the aerosol single scattering albedo

Experimental set-up
Strategy for data analysis
Scattering effect correction
Loading effect correction
Multiple scattering correction
Number size distribution and effective fine and coarse diameter
Data integration and error analysis
Results
Quality control data
Estimate of Cref
Dependence of Cref on SSA
Dependence of Cref on particles size
Conclusions
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