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Abstract
Atmospheric transport processes and conditions can cause primary aerosols to interact, giving rise to secondary aerosols with unique chemical and physical properties. These new species of aerosols can potentially influence the light-scattering properties of the aerosol ensemble and thus the climate system in ways that are not yet fully understood. In this study, the effects of different aerosol types on the scattering of incident solar radiation are modeled and the contribution of secondary aerosols to the aerosol scattering ensemble is highlighted. Using the discrete dipole approximation method, the scattering properties of freshwater droplets, sea salts (liquid, dry, and wet solids), ice crystals, clay minerals, clay particles coated with a thin film of water and sea salt droplets, black carbon (BC), and a complex particle of clay, sea salt, and BC with sulphate coating are calculated and compared. The calculations assume a spherical particle shape model for marine aerosols, a distorted cube for wet salts and ice, and a distorted ellipse with an induced surface roughness length for terrestrial aerosols at a size parameter of x=5 and a wavelength range of 400 to 750 nm. The results show that tiny ice crystals trapped in freshwater droplets are the most efficient atmospheric scatterers, followed by sea salt droplets, while BC absorbs the most compared to other aerosols studied. On average, the atmospheric interaction between marine and terrestrial aerosols is able to enhance atmospheric light scattering and polarisation by aerosols compared to terrestrial aerosols. This study suggests that the scenario in which there are many freshwater aerosols in the atmosphere can be very healthy for the Earth’s system compared to other aerosols. Therefore, we suggest that when formulating the radiative properties of aerosols in climate models, the scenarios of dominant freshwater aerosols and the contribution of secondary aerosols should not be ignored. The results presented here may be useful in the fields of Geoengineering and Aerosol-cloud microphysics.
© 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
The cloud-forming layers of the atmosphere can range from 0 km up to 20 km above ground level, depending on the atmospheric temperature and pressure [1]. In this region of the atmosphere, water vapor from surface evaporation can condense, forming tiny cloud droplets, ice crystals, or a combination of both. This region also contains trillions of terrestrial aerosols from the earth’s surface carried by wind erosion such as mineral dust, volcanic ash [2,3], and anthropogenic aerosols from the combustion of fossil fuels such as soot. During atmospheric transport processes, these different aerosol species can interact [4], giving rise to new species of aerosols (secondary aerosols) [5]. These secondary aerosols can give rise to some unique optical properties that have not yet been captured through experiments or studied in the literature.
Under anthropogenic forcing, surface evaporation has been found to intensify, giving rise to more water vapor in the atmosphere (atmospheric rivers) [6–11]. These marine aerosols, which have been found to be the most dominant in nature [12], mostly come from oceans and sea surface evaporation because of the surface area covered by oceans compared to land. This evaporated ocean water has a significant amount of salt content that can make it have unique optical properties compared to freshwater vapor from land surface evaporation. Also, both freshwater and ocean aerosol’s optical properties strongly depend on the atmospheric conditions (temperature and pressure). At sub-zero temperatures in the cloud-forming layers, there is a possibility that the salt in the sea salt water vapor can crystallize, further affecting its optical properties. Furthermore, freshwater vapor can also crystallize, forming microscopic ice crystals that might have similar optical properties as snow aerosols. In these moist atmospheric conditions, there is also the possibility that the solid aerosol particles can be engulfed in the water droplets and they can also physically coalesce, forming more complex or aggregated particles. For a practical example, we consider the Transmission Electron Microscopy (TEM) images published by Kandler et al [13] that show sulphate particle with soot inclusion, soot particle adhering to sulphate particle, soot particle with a thin coating, and silicate particles with a sulphate coating. Similar soot with sulphate coating images have been published in the paper by Lieke et al [14].
Many research works have focused on modeling the impacts of different sea salt shapes on their optical properties while others have also studied the optical properties of black carbon composite and mineral dust aerosols. Lei et al [15] investigated the effects of nonsphericity and inhomogeneity of sea salt aerosols using invariant imbedding T-matrix simulations by modeling both wet and dry sea salts. The main finding was that the effect of inhomogeneity on optical properties is pronounced for coarse-mode sea salt. Kanngießer et al also modeled the optical properties of non-cubical sea-salt particles [16]. Their optical calculations were performed at a wavelength of 532 nm using the discrete dipole approximation and the T-matrix method. Their main finding was that convex polyhedra shapes of sea salts are a promising candidate for modeling random errors compared to Gaussian random cubes. Using a clay mineral as a case study, Arreyndip et al [17] studied the impacts of the various photosensitive parameters of aerosols on their optical properties. Their main finding was that the single-particle mixing state that is often ignored in most aerosol optical modeling experiments is also a major photosensitive parameter. Xiaolin et al [18] have characterized the optically effective complex refractive index of black carbon composite aerosols that exist as aggregated particles with sulphate coating. They compared the volume weighted average (VWA) method and Bruggeman effective medium (BEM) theory to retrieve the optically effective aerosol complex refractive index (ACRI) of this composite particle. Their findings recommend the application of the optically effective ACRI, rather than the ACRI given by the VWA, to account for coarse BC-containing particles in the state-of-the-art aerosol-climate models.
Modeling the optical properties of a broad spectrum of aerosols and carrying out a comparative study between the various species, will significantly contribute in areas such as Lidar remote sensing and fine-turning of aerosol model parameters presented in Global Climate Models (GCMs). Additionally, modelers and experimenters working in the area of aerosol-cloud Physics and Geoengineering will also find the results here useful for further studies. This work models the optical properties of a full spectrum of atmospheric aerosols in a stream of air moving with a certain group velocity. The modeling framework considers each aerosol species already studied in the literature and also considers the case where two or more species interact. Since shape, size, and wavelength are parameters that can significantly affect aerosol light-scattering abilities, we fixed these parameters across the various aerosol types under study.
In the remaining sections, we revisit the Discrete Dipole Approximation (DDA) method in section 2 and describe in detail the modeling we performed with the Discrete Dipole Approximation Scattering version 7.3 (DDSCAT-7.3) software. Section 3 is dedicated to the results of our findings, followed by a discussion in Section 4, and finally we conclude our findings in Section 5.
2. Method
Many aerosol scattering studies have either used the T-Matrix method or the Discrete Dipole Approximation (DDA) method [19–39]. In general, most electromagnetic scattering problems require solving a matrix equation given by,
The scattering ($C_{scat}$), absorption ($C_{abs}$), and extinction ($C_{ext}$) cross sections are related by the expression
To compute the single-scattering albedo($\omega _0$) we used the expression
While the linear depolarization $\chi$ and the lidar ratios $\varphi$ expressions are given by [20] and where $S_{11}(180)$ is an indicator of the intensity of backscattered light. The value of the linear depolarization commonly called the asymmetric parameter gives us an idea about the shape of the particle, for when $\chi \longrightarrow 0$ implied the particle is more spherical. The single-scattering albedo is an indicator of the particle’s ability to absorb incoming solar radiation. For $\omega _0 = 1$, the particle is nonabsorbing. The smaller the values of $\omega _0$($\omega _0 \ll 1$) imply the particle is more absorbing [17]. For atmospheric scatterers like aerosols, the lidar ratio $\varphi$ is the ratio of the extinction-to-backscatter coefficient and also strongly depends on the particle’s shape and size.2.1 Scattering calculations performed in DDSCAT-7.3
To model the optical properties of sea salts (liquid), we consider a spherical particle with 3.5% Sodium Chloride (NaCl) concentration and 96.5% water in the bubble while the spherical shape freshwater droplet is assumed to be made up of 100% water (Fig. 1 (a)).
Fig. 1. Shape of marine aerosols (a) used to model sea salt and freshwater droplet, (b) is the shape used to model wet salt and wet ice, (c) is the scenario where there is a mixture of the ice-crystal and liquid phase in the atmosphere, (d) is the shape used to model dry salt grains and frozen water (snowlike particles). (e) is the shape of the terrestrial aerosol (dust, BC), (f) is the scenario where a dust particle is trapped in a molecule of water or sea salt droplet, and (g) is the scenario where we consider a sulphate particle internally mixed with clay mineral, BC, and sea salts.
For wet salt/ice, we assume a distorted cubic shape resulting from the melting of a cubic crystal, which is the shape usually used to model ice or dry salt particles (Fig. 1(b)). For microscopic dry ice/salt particles, we approximate the shape to spherical (Fig. 1(d)). For mineral dust aerosols, the literature shows that dominant aerosol shapes are either spherical or elliptic depending on the composition mixing [41,42] but a large population of mineral dust shapes are elliptic. Hence in this study, we consider a distorted ellipse with an induced surface roughness length to model the shape of realistic mineral dust aerosols (Fig. 1(e)). To model secondary aerosols, we consider a scenario where microscopic ice/sea salt crystals are formed inside water/sea salt droplets (Fig. 1(c)). We also consider cases where dust or any other terrestrial aerosol is trapped in a bubble of fresh water or sea salt droplet (Fig. 1(f)) and finally, to model an aggregated particle, we consider a complex particle made up of a sulphate coating of clay minerals and black carbon (BC) which has been studied in the paper by Zhang et al [18] but with an additional sea salt core (Fig. 1(g)). For the single-particle mixing state, we consider the lump particle model presented in the paper by Arreyndip et al [17] for the internal mixing of the different components of the sulphate particle. For all particles, we apply the method of Orientation Averaging to eliminate uncertainties in the calculations induced by the particle’s irregular shape. For the three angles, $\beta$, $\Theta$, and $\Phi$ used to describe the angular orientation of the particle in space, we set $\beta$ and $\Phi$ to run from $0<(\beta, \Phi )<360^o$ with $N = 4$ intervals and $\Theta$ varies in the interval $0<\Theta <180^o$ with $N = 3$. We average the calculations over 48 angular orientations of the target, two (2) incident polarizations, and x=5 size parameter at 400 to 750 nm incident wavelength range.
Additionally, to investigate the impact of iron concentration in mineral dust, we consider three kaolinite-like particle models with 0%, 2%, and 4% hematite concentration uniformly, internally mixed. The Volume Weighted Average (VWA) method was applied to calculate the final complex refractive index of the particles. Details of the complex refractive indices (Real and Imaginary) of each aerosol species and their compositions used in this study have been presented in Table 1. Figure 2 shows sections of tomographic images when the particles in Fig. 2 are sliced along the z-axis in the x-y plane to show the location of crystallized water/salt in the water/salt bubble Fig. 2(a), Fig. 2(b) shows the scenario where polluted dust with 2% hematite is trapped in a water/salt droplet, Fig. 2(c) is the scenario where there is a uniform mixture of 96% kaolinite (purple) and 4% hematite (yellow), and Fig. 2(d) is the scenario where we consider a sulphate particle (gray) internally mixed with clay mineral (15%, red), BC (5%, black), and dry sea salts (2%, blue). In this figure (Fig. 2), only the z-levels with the highest inclusion content are shown.
Fig. 2. Sections of tomographic images when the particles in Fig. 1 are sliced along the z-axis in the x-y plane to show the location of crystallized water/salt(gray) in the water/salt bubble (blue)(a), Fig. 2(b) shows the scenario where polluted dust (gray and red) with 2% hematite is trapped in a water/salt droplet (blue), Fig. 2(c) is the scenario where there is a uniform mixture of 96% kaolinite (purple) and 4% hematite (yellow), and 2(d) is the scenario where we consider a sulphate particle (gray) internally mixed with clay mineral (15%, red), BC (5%, black), and dry sea salts (2%, blue). In this figure, only the z-levels with the highest inclusion content are shown.
Table 1. Optical parameters summary table and comparative analysis between different aerosol species. The calculations were averaged over 400 nm to 750 nm wavelength of visible light and a size parameter x=5.
3. Results
A comparative analysis of the scattering abilities of freshwater and its derivatives (water droplets, ice forming in water droplets (ice water), melting ice (wet ice), and dry ice has been presented in Fig. 3 and Table 1. In Table 1, we find that the formation of ice crystal in a freshwater droplet(ice-water) has the highest scattering, absorption, and extinction efficiencies (3.96, 5.63E-8, and 3.96) followed by freshwater droplet (3.92, 5.41E-8, and 3.92). In this family, wet ice is shown to have the least scattering efficiency but with the highest absorbing potential and backscattering intensity compared to dry ice, water, and ice water. Figure 3 shows that freshwater droplet has the strongest effect on linear polarization of light while wet ice and ice water have similar polarizabilities. This analysis shows the formation of ice in a freshwater droplet, can significantly enhance the scattering ability of freshwater droplets.
Fig. 3. Scattering matrix elements for water and its derivatives. The method of Orientational Averaging has been used with the scattering computation averaged over 48 target orientations and 2 incident polarizations. The calculations were averaged over 400 nm to 750 nm wavelength of visible light and a size parameter x=5. The real and imaginary parts of the complex refractive indices for these plots have been presented in Table 1. (a) is a plot of the Log of the scattering phase function or the angular distribution of intensity while (b)-(f) plots the ratio of the various polarization states to the intensity.
In Fig. 4 and Table 1, we equally compare the scattering abilities of sea salt droplets and their derivatives(sea salt droplets, a salt crystal trapped in sea salt droplets, wet sea salts, and dry sea salt). In this figure and table, we see that sea salt droplet has the strongest effect on linear polarization of light with the highest scattering efficiencies and least absorbing power. Compared to other members of the family, dry sea salts have the least scattering efficiencies but the highest backscattering intensities. A comparative analysis between freshwater drops, fresh ice water, sea salt droplets, and a mixture of salt and sea salt droplets in Fig. 5 shows that there is a strong similarity in linear polarization potentials between fresh ice water and a mixture of salt and sea salt droplets. This figure also shows freshwater droplets have a much higher polarizability compared to sea salt droplets but with a slightly lower scattering efficiency. Overall, fresh ice-water aerosols have the highest scattering efficiencies compared to other aquatic aerosols.
Fig. 4. Scattering matrix elements for Sea Salt and its derivatives. The method of orientational averaging has been used with the scattering computation averaged over 48 target orientations and 2 incident polarizations. The calculations were averaged over 400 nm to 750 nm wavelength of visible light and a size parameter x=5. The real and imaginary parts of the complex refractive indices for these plots have been presented in Table 1. (a) is a plot of the Log of the scattering phase function or the angular distribution of intensity while (b)-(f) plots the ratio of the various polarization states to the intensity.
Fig. 5. Scattering matrix elements to compare the impact of fresh water and Sea Salt in their abilities to scatter light. The method of orientational averaging has been used with the scattering computation averaged over 48 target orientations and 2 incident polarizations. The calculations were averaged over 400 nm to 750 nm wavelength of visible light and a size parameter x=5. The real and imaginary parts of the complex refractive indices for these plots have been presented in Table 1. (a) is a plot of the Log of the scattering phase function or the angular distribution of intensity while (b)-(f) plots the ratio of the various polarization states to the intensity.
Figure 6 simulates the interactions of different clay minerals with aquatic aerosols. We compare the scattering potentials of clay minerals and their derivatives (Pure clay, polluted clay with 2% hematite, polluted clay with 4% hematite, polluted clay with 2% hematite when trapped in freshwater bubble, polluted clay with 2% hematite when trapped in sea salt droplets). From the results in Table 1, the comparative analysis shows that increasing the iron content of clay minerals can significantly decrease their scattering efficiencies while increasing their absorbing abilities. The presence of more iron in clay particles can enhance their ability to backscatter light. The table results also show that a polluted clay mineral trapped in a freshwater bubble has a higher scattering efficiency but with lower absorbing power compared to polluted clay with this efficiency even higher when the polluted clay is trapped in a sea salt bubble. Moreover, a combination of polluted clay and sea salt droplets will increase the absorptivity and polarizability of the complex aerosol particle. Figure 6 also shows that a mixture of polluted clay (most common in nature) and water or sea salt droplets has a higher polarization potential compared to polluted clay.
Fig. 6. Scattering matrix elements for Pure Clay, Clay with 2% hematite, Clay with 4% hematite, Clay with 2% hematite when trapped in a water bubble, and Clay with 2% hematite when trapped in a salt droplet. The method of orientational averaging has been used with the scattering computation averaged over 48 target orientations and 2 incident polarizations. The calculations were averaged over 400 nm to 750 nm wavelength of visible light and a size parameter x=5. The real and imaginary parts of the complex refractive indices for these plots have been presented in Table 1. (a) is a plot of the Log of the scattering phase function or the angular distribution of intensity while (b)-(f) plots the ratio of the various polarization states to the intensity.
Figure 7 compares the scattering abilities of the different solid aerosols under study. The figure shows an aggregated particle composed of sulphate with a BC, clay, and dry salt as the core has very high polarizability while black carbon (BC) has the highest absorbing potential. Both pure and polluted clay is shown to be the most efficient back scatterer followed by the complex particle. Figure 8 shows the scattering matrices when all the marine, terrestrial, and secondary aerosols are aggregated and their averages calculated. This figure shows the interaction between aquatic and terrestrial (secondary aerosols) can significantly enhance the scattering intensities and polarization of light of terrestrial aerosols.
Fig. 7. Scattering matrix elements for Clay with 2% hematite, Black carbon (BC), Sea Salt, and a complex particle of clay, sea salt, and BC internally mixed in a sulfate bubble. The method of orientational averaging has been used with the scattering computation averaged over 48 target orientations and 2 incident polarizations. The calculations were averaged over 400 nm to 750 nm wavelength of visible light and a size parameter x=5. The real and imaginary parts of the complex refractive indices for these plots have been presented in Table 1. (a) is a plot of the Log of the scattering phase function or the angular distribution of intensity while (b)-(f) plots the ratio of the various polarization states to the intensity.
Fig. 8. Scattering matrix elements to compare the scattering capabilities between marine and terrestrial aerosols and their interaction. The plot shows that on average, the atmospheric interaction between marine and terrestrial aerosols can enhance atmospheric light-scattering by aerosols. (a) is a plot of the Log of the scattering phase function or the angular distribution of intensity while (b)-(f) plots the ratio of the various polarization states to the intensity.
4. Discussions
In an ensemble of aerosol particles, different chemical and physical processes may occur that can transform primary aerosols into secondary aerosols. These transformations can make the process of quantifying the radiative properties of aerosols even more complex and increase the uncertainty of the results or models. Modeling the scattering properties of fifteen (15) different aerosol types and carrying out comparative analyses has helped in isolating some of the most efficient atmospheric scatterers. Tiny ice crystals trapped in freshwater droplets have been shown to be the most efficient atmospheric scatterers, followed by sea salt droplets. This implies that an atmosphere dominated by freshwater aerosols will be very healthy for the climate. One of the most useful areas that this finding can contribute to is in the area of Geoengineering. In the field of Geoengineering, some technological methods have been in existence to remove atmospheric CO2 or reflect part of incoming radiation back into the atmosphere. These techniques can be grouped into two main groups:
4.1 Solar Geoengineering
This method requires the reflection back into space part of incoming solar radiation using techniques such as Albedo enhancement, Space reflectors, and the use of stratospheric aerosols which are reflective particles introduced into the upper atmosphere to reflect some sunlight before it reaches the surface of the Earth [43].
4.2 Carbon geoengineering
This method is geared towards the capture and removal of atmospheric CO2 and other GHGs. Some existing GHG removal techniques are Afforestation, Biochar, Bio-energy, Ambient Air Capture, Ocean Fertilisation, Enhanced Weathering, and Ocean Alkalinity Enhancement [43].
In addition to these technological processes to remove atmospheric CO2 and reflect part of the solar radiation back into the atmosphere, our proposed method of injecting freshwater aerosols given their effectiveness in reflecting solar radiation with the least absorbing abilities or some artificial particles with material properties similar to freshwater aerosols with ice core, may fall under Albedo enhancement and/or Stratospheric aerosols techniques.
5. Conclusion
To address the uncertainties in the implementation of aerosols in global climate models to estimate radiative transfer, we have modeled and compared the scattering efficiencies of naturally occurring terrestrial and aquatic aerosols, anthropogenic aerosols, and their interactions leading to new aerosol species (secondary aerosols). In this study, the scattering properties of fifteen (15) different aerosol species were analyzed and compared. To calculate and compare their scattering matrices, phase functions, scattering efficiencies, albedos, backscattering intensities, and asymmetric parameters, we used the discrete dipole approximation method of DDSCAT developed by Draine and Flatau. The calculations were performed assuming a spherical particle shape model for marine aerosols, a distorted cube for wet salts and ice, and a distorted ellipse with an induced surface roughness length for terrestrial aerosols at a size parameter of x=5 and an incident wavelength range of 400 to 750 nm. The method of Orientation Averaging was used to overcome uncertainties arising from the asymmetry of the particles. We averaged the calculations over 48 angular orientations of the target and two (2) incident polarizations. For complex interacting particles, we also used the volume-weighted moments to calculate the final complex refractive indices. For all aerosols studied, we found that tiny ice crystals trapped in freshwater droplets are the most efficient atmospheric scatterers, followed by sea salt droplets, while BC absorbs the most compared to other aerosols studied. On average, the atmospheric interaction between marine and terrestrial aerosols is able to enhance atmospheric light scattering and polarisation by aerosols compared to terrestrial aerosols. The large amount of anthropogenic aerosols in the atmosphere poses a serious problem as they have the potential to act as a blanket, shielding the Earth from incoming shortwave radiation and outgoing longwave radiation by absorbing much of this radiation and emitting more thermal radiation, which increases the temperature of the Earth. The study suggests that an atmosphere dominated by freshwater aerosols can be very healthy for the climate system, as they have a very high potential to scatter light with the lowest absorption capacity.
This study suggests that when formulating the radiative properties of aerosols in climate models, the scenarios of dominant freshwater aerosols and the contribution of secondary aerosols should not be ignored. Modelers and experimenters working on aerosol-cloud interactions and Geoengineering may find the results presented here useful.
Funding
Alexander von Humboldt-Stiftung.
Acknowledgements
The authors would like to thank B. T. Draine and P. J. Flatau for developing the DDSCAT and making it publicly available. The authors also extend their sincere gratitude to Prof. Dr. Konrad Kandler, Dr. Aryasree Sudharaj, and all the members of the Atmospheric Aerosol Research Group of the Institute of Applied Geosciences of the Technical University of Darmstadt, Darmstadt, Germany for the exchange of ideas and resources that led to the development of the paper’s methodology.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request. The implementation of the DDSCAT-7.3.3 model is available in [23].
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