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1. The color of aerosol particles

   https://doi.org/10.1038/s41598-023-28823-6  

   Giri, Ramesh; Berg, Matthew J. (December 2023, Scientific Reports)

   Abstract Digital in-line holography (DIH) is an established method to image small particles in a manner where image reconstruction is performed computationally post-measurement. This ability renders it ideal for aerosol characterization, where particle collection or confinement is often difficult, if not impossible. Conventional DIH provides a gray-scale image akin to a particle’s silhouette, and while it gives the particle size and shape, there is little information about the particle material. Based on the recognition that the spectral reflectance of a surface is partly determined by the material, we demonstrate a method to image free-flowing particles with DIH in color with the eventual aim to differentiate materials based on the observed color. Holograms formed by the weak backscattered light from individual particles illuminated by red, green, and blue lasers are recorded by a color sensor. Images are reconstructed from the holograms and then layered to form a color image, the color content of which is quantified by chromaticity analysis to establish a representative signature. A variety of mineral dust aerosols are studied where the different signatures suggest the possibility to differentiate particle material. The ability of the method to resolve the inhomogeneous composition within a single particle in some cases is shown as well. 

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2. Aerosol Hygroscopicity and Surface-Active Coverage for the Droplet Growth of Aerosol Mixtures

   https://doi.org/10.1021/acsestair.4c00303  

   Ferdousi-Rokib, Nahin; A_Malek, Kotiba; Mitchell, Ian; M_Fierce, Laura; Asa-Awuku, Akua_A (July 2025, ACS ES&T Air)
3. Parameterization of size of organic and secondary inorganic aerosol for efficient representation of global aerosol optical properties

   https://doi.org/10.5194/acp-23-5023-2023  

   Zhu, Haihui; Martin, Randall V; Croft, Betty; Zhai, Shixian; Li, Chi; Bindle, Liam; Pierce, Jeffrey R; Chang, Rachel Y-W; Anderson, Bruce E; Ziemba, Luke D; et al (January 2023, Atmospheric Chemistry and Physics)

   Abstract. Accurate representation of aerosol optical properties is essential for the modeling and remote sensing of atmospheric aerosols. Although aerosol optical properties are strongly dependent upon the aerosol size distribution, the use of detailed aerosol microphysics schemes in global atmospheric models is inhibited by associated computational demands. Computationally efficient parameterizations for aerosol size are needed. Inthis study, airborne measurements over the United States (DISCOVER-AQ) andSouth Korea (KORUS-AQ) are interpreted with a global chemical transport model (GEOS-Chem) to investigate the variation in aerosol size when organicmatter (OM) and sulfate–nitrate–ammonium (SNA) are the dominant aerosol components. The airborne measurements exhibit a strong correlation (r=0.83) between dry aerosol size and the sum of OM and SNA mass concentration (MSNAOM). A global microphysical simulation(GEOS-Chem-TOMAS) indicates that MSNAOM and theratio between the two components (OM/SNA) are the major indicators for SNA and OM dry aerosol size. A parameterization of the dry effective radius (Reff) for SNA and OM aerosol is designed to represent the airborne measurements (R2=0.74; slope = 1.00) and the GEOS-Chem-TOMAS simulation (R2=0.72; slope = 0.81). When applied in the GEOS-Chem high-performance model, this parameterization improves the agreement between the simulated aerosol optical depth (AOD) and the ground-measured AOD from the Aerosol Robotic Network (AERONET; R2 from 0.68 to 0.73 and slope from 0.75 to 0.96). Thus, this parameterization offers a computationally efficient method to represent aerosol size dynamically. 

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4. Chemistry of hydroperoxycarbonyls in secondary organic aerosol

   https://doi.org/10.1080/02786826.2018.1511046  

   Pagonis, Demetrios; Ziemann, Paul J. (September 2018, Aerosol Science and Technology)
5. Aerosol Synthesis of High Entropy Alloy Nanoparticles

   https://doi.org/10.1021/acs.langmuir.9b03392  

   Yang, Yong; Song, Boao; Ke, Xiang; Xu, Feiyu; Bozhilov, Krassimir N.; Hu, Liangbing; Shahbazian-Yassar, Reza; Zachariah, Michael R. (March 2020, Langmuir)