Absorption Angstrom Exponent in AERONET and related data as an indicator of aerosol composition

Abstract

Abstract. Recent results from diverse air, ground, and laboratory studies using both radiometric and in situ techniques show that the fractions of black carbon, organic matter, and mineral dust in atmospheric aerosols determine the wavelength dependence of absorption (often expressed as Absorption Angstrom Exponent, or AAE). Taken together, these results hold promise of improving information on aerosol composition from remote measurements. The main purpose of this paper is to show that AAE values for an Aerosol Robotic Network (AERONET) set of retrievals from Sun-sky measurements describing full aerosol vertical columns are also strongly correlated with aerosol composition or type. In particular, we find AAE values near 1 (the theoretical value for black carbon) for AERONET-measured aerosol columns dominated by urban-industrial aerosol, larger AAE values for biomass burning aerosols, and the largest AAE values for Sahara dust aerosols. These AERONET results are consistent with results from other, very different, techniques, including solar flux-aerosol optical depth (AOD) analyses and airborne in situ analyses examined in this paper, as well as many other previous results. Ambiguities in aerosol composition or mixtures thereof, resulting from intermediate AAE values, can be reduced via cluster analyses that Correspondence to: P. B. Russell (philip.b.russell@nasa.gov,) supplement AAE with other variables, for example Extinction Angstrom Exponent (EAE), which is an indicator of particle size. Together with previous results, these results strengthen prospects for determining aerosol composition from space, for example using the Glory Aerosol Polarimetry Sensor (APS), which seeks to provide retrievals of multiwavelength single-scattering albedo (SSA) and aerosol optical depth (and therefore aerosol absorption optical depth (AAOD) and AAE), as well as shape and other aerosol properties. Multidimensional cluster analyses promise additional information content, for example by using the Ozone Monitoring Instrument (OMI) to add AAOD in the near ultraviolet and CALIPSO aerosol layer heights to reduce heightabsorption ambiguity.

Relating aerosol absorption due to soot, organic carbon, and dust to emission sources determined from in-situ chemical measurements

“…Detailed studies of the chemical composition and size distribution of aerosol particles, and how they relate to the optical properties is therefore essential to evaluate their impact on climate. Russell et al (2010) highlighted that many recent studies have shown the persistent connections between aerosol absorbing species and the wavelength dependence of absorption. Thus, numerous studies have classified absorbing aerosol types from optical properties measured on ground stations (Eck et al, 1999;Dubovik et al, 2002;Collaud Coen et al, 2004;Fialho et al, 2005;Meloni et al, 2006;Kalapureddy et al, 2009;Mielonen et al, 2009;Giles et al, 2011Giles et al, , 2012 and from satellites (Higurashi and Nakajima, 2002;Barnaba and Gobbi, 2004;Jeong and Li, 2005;Kaufman et al, 2005;Torres et al, 2005;Kaskaoutis et al, 2007;Kim et al, 2007;Yu et al, 2009).…”

“…Positive and negative ion mass spectra resulting from individual particles are measured in a dualpolarity time-of-flight mass spectrometer. Russell et al (2010) used the Absorption Ångström Exponent (AAE) as an indicator of aerosol chemical composition and they showed a clustering by absorbing aerosol types on an AAE vs. EAE (Extinction Ångström Exponent) scatter plot. In this study, we apply a similar methodology, based on a previous study by Bahadur et al (2012), dividing the 9340 A. Cazorla et al: Relating aerosol absorption AAE vs. SAE (Scattering Ångström Exponent) space, the Ångström matrix, in different regions that are associated with different absorbing aerosol types.…”

Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China

“…Generally, an AAE < 1 indicates mixing, coating and coagulation of black carbon with organic and inorganic materials; an AAE close to 1 indicates absorbing black carbon aerosols from the fossil fuel burning; and an AAE > 1.10 indicates absorbing aerosols mainly from biomass burning or mineral dust (Russell et al, 2010;Bergstrom et al, 2007;Lack and Cappa, 2010). The annual mean AAEs at Hangzhou, Xiaoshan, Fuyang, LinAn, Tonglu, Jiande and ChunAn were 1.13 ± 0.46, 0.88 ± 0.42, 0.85 ± 0.43, 0.98 ± 0.35, 1.11 ± 0.49, 1.16 ± 0.44 and 0.93 ± 0.31, respectively (Table 1), and for discussion purposes, the seven sites were grouped into three categories based on their average AAEs.…”

Perturbations of the optical properties of mineral dust particles by mixing with black carbon: a numerical simulation study

“…Key results for bare mineral dust aerosol include (i) a strong sensitivity of dust optical properties to shape (DDSCAT predicts at 550 nm an average difference between spheroids and prisms of about 20 % for MEC and MSC, while of about 5 % for MAC); (ii) a consistency between DDSCAT-predicted and observed values of MAC, MSC and SSA reported by Hand and Malm (2007); and (iii) a typical decrease in the SSA magnitude for wavelengths shorter than 500 nm (also found to be characteristic of organics and the aerosol mixtures of sodium chloride and BC; see also Scarnato et al, 2013;Russell et al, 2010).…”