scholarly journals Influence of relative humidity upon pollution and dust during ACE-Asia: Size distributions and implications for optical properties

Author(s):  
S. G. Howell ◽  
A. D. Clarke ◽  
Y. Shinozuka ◽  
V. Kapustin ◽  
C. S. McNaughton ◽  
...  
2011 ◽  
Vol 11 (2) ◽  
pp. 723-740 ◽  
Author(s):  
G. Chen ◽  
L. D. Ziemba ◽  
D. A. Chu ◽  
K. L. Thornhill ◽  
G. L. Schuster ◽  
...  

Abstract. As part of the international project entitled "African Monsoon Multidisciplinary Analysis (AMMA)", NAMMA (NASA AMMA) aimed to gain a better understanding of the relationship between the African Easterly Waves (AEWs), the Sahara Air Layer (SAL), and tropical cyclogenesis. The NAMMA airborne field campaign was based out of the Cape Verde Islands during the peak of the hurricane season, i.e., August and September 2006. Multiple Sahara dust layers were sampled during 62 encounters in the eastern portion of the hurricane main development region, covering both the eastern North Atlantic Ocean and the western Saharan desert (i.e., 5–22° N and 10–35° W). The centers of these layers were located at altitudes between 1.5 and 3.3 km and the layer thickness ranged from 0.5 to 3 km. Detailed dust microphysical and optical properties were characterized using a suite of in-situ instruments aboard the NASA DC-8 that included a particle counter, an Ultra-High Sensitivity Aerosol Spectrometer, an Aerodynamic Particle Sizer, a nephelometer, and a Particle Soot Absorption Photometer. The NAAMA sampling inlet has a size cut (i.e., 50% transmission efficiency size) of approximately 4 μm in diameter for dust particles, which limits the representativeness of the NAMMA observational findings. The NAMMA dust observations showed relatively low particle number densities, ranging from 268 to 461 cm−3, but highly elevated volume density with an average at 45 μm3 cm−3. NAMMA dust particle size distributions can be well represented by tri-modal lognormal regressions. The estimated volume median diameter (VMD) is averaged at 2.1 μm with a small range of variation regardless of the vertical and geographical sampling locations. The Ångström Exponent assessments exhibited strong wavelength dependence for absorption but a weak one for scattering. The single scattering albedo was estimated at 0.97 ± 0.02. The imaginary part of the refractive index for Sahara dust was estimated at 0.0022, with a range from 0.0015 to 0.0044. Closure analysis showed that observed scattering coefficients are highly correlated with those calculated from spherical Mie-Theory and observed dust particle size distributions. These values are generally consistent with literature values reported from studies with similar particle sampling size range.


2021 ◽  
Author(s):  
Maria Ángeles Burgos Simón ◽  
Elisabeth Andrews ◽  
Gloria Titos ◽  
Angela Benedetti ◽  
Huisheng Bian ◽  
...  

<p>The particle hygroscopic growth impacts the optical properties of aerosols and, in turn, affects the aerosol-radiation interaction and calculation of the Earth’s radiative balance. The dependence of particle light scattering on relative humidity (RH) can be described by the scattering enhancement factor f(RH), defined as the ratio between the particle light scattering coefficient at a given RH divided by its dry value.</p><p>The first effort of the AeroCom Phase III – INSITU experiment was to develop an observational dataset of scattering enhancement values at 26 sites to study the uptake of water by atmospheric aerosols, and evaluate f(RH) globally (Burgos et al., 2019). Model outputs from 10 Earth System Models (CAM, CAM-ATRAS, CAM-Oslo, GEOS-Chem, GEOS-GOCART, MERRAero, TM5, OsloCTM3, IFS-AER, and ECMWF) were then evaluated against this in-situ dataset. Building on these results, we investigate f(RH) in the context of other aerosol optical and chemical properties, making use of the same 10 Earth System Models (ESMs) and in-situ measurements as in Burgos et al. (2020) and Titos et al. (2021).</p><p>Given the difficulties of deploying and maintaining instrumentation for long-term, accurate and comprehensive f(RH) observations, it is desirable to find an observational proxy for f(RH). This observation-based proxy would also need to be reproduced in modelling space. Our aim here is to evaluate how ESMs currently represent the relationship between f(RH), scattering Ångström exponent (SAE), and single scattering albedo (SSA). This work helps to identify current challenges in modelling water-uptake by aerosols and their impact on aerosol optical properties within Earth system models.</p><p>We start by analyzing the behavior of SSA with RH, finding the expected increase with RH for all site types and models. Then, we analyze the three variables together (f(RH)-SSA-SAE relationship). Results show that hygroscopic particles tend to be bigger and scatter more than non-hygroscopic small particles, though variability within models is noticeable. This relationship can be further studied by relating SAE to model chemistry, by selecting those grid points dominated by a single chemical component (mass mixing ratios > 90%). Finally, we analyze model performance at three specific sites representing different aerosol types: Arctic, marine and rural. At these sites, the model data can be exactly temporally and spatially collocated with the observations, which should help to identify the models which exhibit better agreement with measurements and for which aerosol type.</p><p> </p><p>Burgos, M.A. et al.: A global view on the effect of water uptake on aerosol particle light scattering. Sci Data 6, 157. https://doi.org/10.1038/s41597-019-0158-7, 2019.</p><p>Burgos, M.A. et al.: A global model–measurement evaluation of particle light scattering coefficients at elevated relative humidity, Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, 2020.</p><p>Titos, G. et al.: A global study of hygroscopicity-driven light scattering enhancement in the context of other in-situ aerosol optical properties, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-1250, in review, 2020.</p>


2019 ◽  
Vol 19 (24) ◽  
pp. 15483-15502 ◽  
Author(s):  
Yicheng Shen ◽  
Aki Virkkula ◽  
Aijun Ding ◽  
Krista Luoma ◽  
Helmi Keskinen ◽  
...  

Abstract. The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS <1.1 %, without any theoretical reasoning. The relationship between NCCN and AOPs was parameterized as NCCN≈((286±46)SAE ln(SS/(0.093±0.006))(BSF − BSFmin) + (5.2±3.3))σsp, where BSFmin is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS ≈0.1 %), the average bias, defined as the ratio of the AOP-derived and measured NCCN, varied from ∼0.7 to ∼1.9 at most sites except at a Himalayan site where the bias was >4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.


2020 ◽  
Vol 10 (23) ◽  
pp. 8637
Author(s):  
Junshik Um ◽  
Seonghyeon Jang ◽  
Young Jun Yoon ◽  
Seoung Soo Lee ◽  
Ji Yi Lee ◽  
...  

Among many parameters characterizing atmospheric aerosols, aerosol mass extinction efficiency (MEE) is important for understanding the optical properties of aerosols. MEE is expressed as a function of the refractive indices (i.e., composition) and size distributions of aerosol particles. Aerosol MEE is often considered as a size-independent constant that depends only on the chemical composition of aerosol particles. The famous Malm’s reconstruction equation and subsequent revised methods express the extinction coefficient as a function of aerosol mass concentration and MEE. However, the used constant MEE does not take into account the effect of the size distribution of polydispersed chemical composition. Thus, a simplified expression of size-dependent MEE is required for accurate and conventional calculations of the aerosol extinction coefficient and also other optical properties. In this study, a simple parameterization of MEE of polydispersed aerosol particles was developed. The geometric volume–mean diameters of up to 10 µm with lognormal size distributions and varying geometric standard deviations were used to represent the sizes of various aerosol particles (i.e., ammonium sulfate and nitrate, elemental carbon, and sea salt). Integrating representations of separate small mode and large mode particles using a harmonic mean-type approximation generated the flexible and convenient parameterizations of MEE that can be readily used to process in situ observations and adopted in large-scale numerical models. The calculated MEE and the simple forcing efficiency using the method developed in this study showed high correlations with those calculated using the Mie theory without losing accuracy.


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