Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading

Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored t...

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Main Authors: Tang-Huang Lin, Si-Chee Tsay, Wei-Hung Lien, Neng-Huei Lin, Ta-Chih Hsiao
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/8/1544
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spelling doaj-fed735ab7d18454b9bb8e372ef278bab2021-04-16T23:04:11ZengMDPI AGRemote Sensing2072-42922021-04-01131544154410.3390/rs13081544Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and LoadingTang-Huang Lin0Si-Chee Tsay1Wei-Hung Lien2Neng-Huei Lin3Ta-Chih Hsiao4Center for Space and Remote Sensing Research, National Central University, Taoyuan City 320, TaiwanGoddard Space Flight Center, NASA, Greenbelt, MD 20771, USAGraduate Institute of Space Science, National Central University, Taoyuan City 32001, TaiwanDepartment of Atmospheric Sciences, National Central University, Taoyuan City 320, TaiwanGraduate Institute of Environmental Engineering, National Taiwan University, Taipei City 106, TaiwanQuantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (<i>f</i>AOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying <i>f</i>AOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.https://www.mdpi.com/2072-4292/13/8/1544aerosol partitionAOD spectral derivativesparticle sizecomplex refractive indexnormalized derivative aerosol indexfractions of total AOD
collection DOAJ
language English
format Article
sources DOAJ
author Tang-Huang Lin
Si-Chee Tsay
Wei-Hung Lien
Neng-Huei Lin
Ta-Chih Hsiao
spellingShingle Tang-Huang Lin
Si-Chee Tsay
Wei-Hung Lien
Neng-Huei Lin
Ta-Chih Hsiao
Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading
Remote Sensing
aerosol partition
AOD spectral derivatives
particle size
complex refractive index
normalized derivative aerosol index
fractions of total AOD
author_facet Tang-Huang Lin
Si-Chee Tsay
Wei-Hung Lien
Neng-Huei Lin
Ta-Chih Hsiao
author_sort Tang-Huang Lin
title Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading
title_short Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading
title_full Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading
title_fullStr Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading
title_full_unstemmed Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading
title_sort spectral derivatives of optical depth for partitioning aerosol type and loading
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-04-01
description Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (<i>f</i>AOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying <i>f</i>AOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.
topic aerosol partition
AOD spectral derivatives
particle size
complex refractive index
normalized derivative aerosol index
fractions of total AOD
url https://www.mdpi.com/2072-4292/13/8/1544
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