Preprints
https://doi.org/10.22541/au.177368350.03675968/v1
https://doi.org/10.22541/au.177368350.03675968/v1
08 Apr 2026
 | 08 Apr 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Asymptotic Behavior of Lidar Scattering Properties of Absorbing Dust Aerosols Across Rayleigh and Geometrical-Optics Regimes: Theory and Implications

Anthony La Luna, Zhibo Zhang, Qianqian Song, Hongbin Yu, John E. Yorks, and Ping Yang

Abstract. Lidar ratio (S), linear depolarization ratio (δ), and single-scattering albedo (ω) are central quantities for dust typing and property retrieval in lidar remote sensing. We investigate their dependence on size parameter (x) and iron oxide fraction of mineral dust using TAMUdust2020 and triaxial-ellipsoid calculations. Results show a consistent asymptotic structure that is weakly sensitive to particle shape in both limits of scattering theory. In the Rayleigh limit (x≪1), S ∝ x−3 and ω ∝x3, while δ remains small. In the geometrical-optics limit (x≫1), δ decreases toward low values and ω →1/2, whereas S increases because backscatter is reduced relative to extinction by strong absorption and diffraction-dominated scattering. These asymptotic constraints provide a unified physical interpretation of multiwavelength dust-lidar behavior and help explain observed spectral variability of dust depolarization and lidar ratio. A key implication is that large, strongly absorbing dust can produce optical signatures that overlap with weakly depolarizing aerosol classes, which may bias standard classification and inversion schemes toward underestimation of coarse and super-coarse dust contributions.

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Anthony La Luna, Zhibo Zhang, Qianqian Song, Hongbin Yu, John E. Yorks, and Ping Yang

Status: open (until 20 May 2026)

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Anthony La Luna, Zhibo Zhang, Qianqian Song, Hongbin Yu, John E. Yorks, and Ping Yang
Anthony La Luna, Zhibo Zhang, Qianqian Song, Hongbin Yu, John E. Yorks, and Ping Yang
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Latest update: 13 Apr 2026
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Short summary
Mineral dust blown from deserts affects air quality and climate worldwide. Scientists use laser instruments on satellites to detect and measure dust. We discovered that very large, iron-rich dust particles produce signals that fool these instruments into misidentifying them as pollution or smoke. Using light scattering theory, we showed this confusion follows universal physical laws regardless of dust shape – helping scientists better interpret next-generation satellite measurements.
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