Accuracy Required in Measurements of Refractive Index and Hygroscopic Response to Reduce Uncertainties in Estimates of Aerosol Radiative Forcing Efficiency

Abstract

The magnitude of aerosol radiative forcing resulting from the scattering and absorption of radiation is still uncertain. Sources of uncertainty include the physical and optical properties of aerosol, reflected in uncertainties in real and imaginary refractive indices (n and k) and relative humidity (RH). The effect of RH on the geometrical size of aerosol particles is often reported as a hygroscopic kappa parameter (κ). The objective of this study is to explore the sensitivity of radiative forcing efficiency (RFE) to changes in particle properties in order to better define the accuracy with which optical and hygroscopic measurements must be made to reduce uncertainties in RFE. Parameterizations of precise values of n and k are considered as functions of RH for ammonium sulfate (AS) and brown carbon (BrC). The range of the RFE estimated for typical uncertainties of n and κ for AS of 0.1 μm dry radius is less than ±7% and is not affected by an increase of RH. For typical sizes of AS in the atmosphere (0.35 μm dry radius), the range of the RFE increases to ±20% at 90% RH and ±15% at 99% RH. Absorbing small BrC particles (0.1 μm dry radius) cause cooling at the top of the atmosphere, and as RH and κ increase, the RFE is more negative compared to the usual assumptions of dry unhygroscopic BrC. For larger BrC particles (0.35 μm dry radius), the change in RFE for RHs~100% compared to dry conditions can take values around À100%.where θ is the angle between incident light and scattering direction and P(θ) is the angular distribution of scattered light (the phase function). The values of g range between À1 for entirely backscattered light and +1 for entirely forward scattered light (Boucher, 1998). The determination of n and k can be very challenging because of the mixed composition of aerosol in the atmosphere, their dynamic change through chemical processing and change in mixing state, and the hygroscopic response of particles as the ambient relative humidity (RH) varies. In addition, the solid-aqueous particle phase transition affects the size and the shape of the particle. Not only does this have implications for the aerosol properties (Wang et al., 2008), but departures from sphericity make the determination of n and k challenging.

Complexity of Measuring and Representing the Hygroscopicity of Mixed Component Aerosol

“…More generally, the predictions of these properties must be robust in order to relate mass concentrations to size distributions of ambient aerosols and to calculate the radiative impacts of atmospheric aerosols. 45,46 Thus, a rigorous assessment of estimation methods based on solutions of known properties is of considerable value.…”

“…The potential interplay of the resulting uncertainties in representing the degree of hygroscopic growth, the RH dependence of the refractive index, and the impact on optical growth factor must be more fully explored to better quantify uncertainties in radiative forcing efficiency. 46 In addition to examining the agreement of the mixing rules for κ, UManSysProp has been used to predict the hygroscopicity parameter κ as a function of water activity, shown in Figure 7(a). 43 For every mixture considered in this work, UManSysProp overpredicts the hygroscopic response (solid lines in Figure 6(a)).…”

Method to measure the size-resolved real part of aerosol refractive index using differential mobility analyzer in tandem with single-particle soot photometer

“…The SP2 is a widely used instrument that can measure the optical properties of every single particle. The measurement principle and instrumental setup of the SP2 have been discussed in detail previously (Stephens et al, 2003;Schwarz et al, 2006) and will be briefly described here. When the sample aerosol particles pass through the continuous Nd:YAG laser beam at 1064 nm with the circulating power of about 1 mW cm −2 in the cavity, eight sensors distributed at four directions synchronously detect the emitted or scattered light by using an avalanche photodetector (APD) at different angles (45 and 135 • ).…”

“…Moise et al (2015) estimated that the RF would increase by 12 % if the RRI varies from 1.4 to 1.5. Valenzuela et al (2018) reported that the uncertainties in RF are estimated to be 7 % when the aerosol RRI varies by 0.1. Therefore, it is pressing that the uncertainties of the RI be reduced when estimating the RF.…”

“…The RRI could be retrieved from the known particle size from the DMA and the aerosol-scattering intensity from the OPC for aerosol particles larger than 500 nm. The scanning mobility particle sizer (SMPS) and OPC were used in combination to derive the RRI by aligning the particle size distributions in the instrument-overlap regions (Hand and Kreidenweis, 2002;Vratolis et al, 2018). The aerosol-effective RRI was also retrieved by applying the Mie scattering theory to the aerosol particle number size distribution (PNSD), aerosol bulk scattering coefficient and aerosol absorbing coefficient data (Cai et al, 2011;Liu and Daum, 2000).…”