Photoacoustic-Driven Retrieval of Complex Refractive Indices for Absorbing Aerosols

Accurate determination of the aerosol complex refractive index (RI) is crucial for modeling atmospheric radiative forcing, yet it remains challenging due to limitations in conventional measurement techniques. This study demonstrates a novel and robust methodology for retrieving wavelength-dependent complex RI (<i>m</i> = <i>n</i> + <i>ik</i>) through integrated, simultaneous measurements of aerosol absorption, scattering, and size distribution. We combine multiwavelength photoacoustic spectroscopy (PAS) for filter-free absorption coefficients, integrating nephelometry for angular-resolved scattering, and scanning mobility particle sizing (SMPS) for high-resolution size distribution measurements. Using diethyl-hexyl-sebacate (DEHS) aerosols as a benchmark, we introduce an inverse algorithm based on Rayleigh theory in the near-IR to visible range and Modified Anomalous Diffraction Theory (MADT) in the UV wavelength regime for RI retrieval, overcoming Mie theory instabilities for RI retrieval in the so-called transition region, where particle dimensions are comparable to wavelength. The retrieved RI values agree with bulk ellipsometry measurements within Δ<i>n</i> = 0.0011 and Δ<i>k</i> = 0.00025. The integrated PAS-nephelometer-SMPS approach establishes a new paradigm for in situ aerosol RI determination with direct applications in climate modeling and remote sensing validation.

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Journal
Analytical Chemistry
Published
2025-11-26
DOI
https://doi.org/10.1021/acs.analchem.5c04788
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Photoacoustic-Driven Retrieval of Complex Refractive Indices for Absorbing Aerosols

Zoltán Bozóki, Szabolcs Hodovány, Cheng Tung Chong, Jamshed Saeed Shah et al.
Analytical Chemistry
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article

Photoacoustic-Driven Retrieval of Complex Refractive Indices for Absorbing Aerosols

Zoltán Bozóki, Szabolcs Hodovány, Cheng Tung Chong, Jamshed Saeed Shah, P. Petrík, Jichuan Xiong, Abdul Rahman, Tibor Ajtai, Muhammad Qasim Mehmood, Muhammad Raza, Gábor Szabó, Boglarka Nyerges, Rana Khawar Ashfaq
article en

Abstract

Accurate determination of the aerosol complex refractive index (RI) is crucial for modeling atmospheric radiative forcing, yet it remains challenging due to limitations in conventional measurement techniques. This study demonstrates a novel and robust methodology for retrieving wavelength-dependent complex RI (<i>m</i> = <i>n</i> + <i>ik</i>) through integrated, simultaneous measurements of aerosol absorption, scattering, and size distribution. We combine multiwavelength photoacoustic spectroscopy (PAS) for filter-free absorption coefficients, integrating nephelometry for angular-resolved scattering, and scanning mobility particle sizing (SMPS) for high-resolution size distribution measurements. Using diethyl-hexyl-sebacate (DEHS) aerosols as a benchmark, we introduce an inverse algorithm based on Rayleigh theory in the near-IR to visible range and Modified Anomalous Diffraction Theory (MADT) in the UV wavelength regime for RI retrieval, overcoming Mie theory instabilities for RI retrieval in the so-called transition region, where particle dimensions are comparable to wavelength. The retrieved RI values agree with bulk ellipsometry measurements within Δ<i>n</i> = 0.0011 and Δ<i>k</i> = 0.00025. The integrated PAS-nephelometer-SMPS approach establishes a new paradigm for in situ aerosol RI determination with direct applications in climate modeling and remote sensing validation.

Analytical ChemistryVol. 97(49)
Information Technology University (PK), Shanghai Jiao Tong University (CN), University of Szeged (HU), Nanjing University of Science and Technology (CN), HUN-REN Centre for Energy Research (HU), Istanbul Technical University (TR)
Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, Szegedi Tudományegyetem, Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, National Research, Development and Innovation Office
Openalex Percentile: Top 65%
Atmospheric aerosols and clouds
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