Daniel Koestner, Dariusz Stramski, and Rick A. Reynolds, "Polarized light scattering measurements as a means to characterize particle size and composition of natural assemblages of marine particles," Appl. Opt. 59, 8314-8334 (2020)
Polarized light scattering measurements have the potential to provide
improved characterization of natural particle assemblages in terms of
particle size and composition. However, few studies have investigated
this possibility for natural assemblages of marine particles. In this
study, seawater samples representing contrasting assemblages of
particles from coastal environments have been comprehensively
characterized with measurements of angle-resolved polarized light
scattering, particle size distribution, and particle composition. We
observed robust trends linking samples containing higher proportions
of large-sized particles with lower values of the maximum degree of
linear polarization and the second element of the scattering matrix at
a scattering angle of 100°, ${p_{22}}({{{100}}^\circ})$. In contrast, lower values
of ${p_{22}}({{{20}}^\circ})$ were found in more
non-phytoplankton—or inorganic--dominated samples. We also determined
that three measurements involving the combinations of linearly
polarized incident and scattered beams at two scattering angles (110°
and 18°) have the potential to serve as useful proxies for estimating
particle size and composition parameters.
Daniel Koestner, Dariusz Stramski, and Rick A. Reynolds, "Polarized light scattering measurements as a means to characterize particle size and composition of natural assemblages of marine particles: erratum," Appl. Opt. 60, 380-382 (2021) https://opg.optica.org/ao/abstract.cfm?uri=ao-60-2-380
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Particulate attenuation coefficient from
LISST-VSF, $\lambda = {{532}}\;{\rm{nm}}$.
Table
4.
Best-Fit Regression Coefficients and Statistical
Variables Evaluating Model Performancea
Regression
Model
Performance
Optical Parameter
Particle Parameter
Eq.
m
b
R
RMSD
MdAPD
MdR
Linear
104.13
5.83 µm
22.9
%
1.02
1.00
Linear
137.02
7.19 µm
29.1
%
1.04
0.99
Linear
133.14
8.66 µm
36.8
%
0.96
0.98
Linear
156.16
6.62 µm
21.5
%
0.98
1.00
POC/SPM
Exp
4.57
0.10
17.0
%
0.98
1.00
POC/SPM
Exp
2.19
0.12
23.6
%
0.96
1.00
Models
are the optically based relationships for estimating particle size
($D_v^{90}$) and
composition (POC/SPM) characteristics. Optical parameters are
independent variables ($x$), and particle parameters
are dependent variables ($y$). Linear equations are of
the form $y = mx + b$, while exponential
equations are of the form $y =
b{e^{{\rm{mx}}}}$. For the exponential (Exp)
relationships, the correlation coefficient
$R$ was
determined using log-transformed POC/SPM and untransformed values of
the optical
parameter.
Particulate attenuation coefficient from
LISST-VSF, $\lambda = {{532}}\;{\rm{nm}}$.
Table
4.
Best-Fit Regression Coefficients and Statistical
Variables Evaluating Model Performancea
Regression
Model
Performance
Optical Parameter
Particle Parameter
Eq.
m
b
R
RMSD
MdAPD
MdR
Linear
104.13
5.83 µm
22.9
%
1.02
1.00
Linear
137.02
7.19 µm
29.1
%
1.04
0.99
Linear
133.14
8.66 µm
36.8
%
0.96
0.98
Linear
156.16
6.62 µm
21.5
%
0.98
1.00
POC/SPM
Exp
4.57
0.10
17.0
%
0.98
1.00
POC/SPM
Exp
2.19
0.12
23.6
%
0.96
1.00
Models
are the optically based relationships for estimating particle size
($D_v^{90}$) and
composition (POC/SPM) characteristics. Optical parameters are
independent variables ($x$), and particle parameters
are dependent variables ($y$). Linear equations are of
the form $y = mx + b$, while exponential
equations are of the form $y =
b{e^{{\rm{mx}}}}$. For the exponential (Exp)
relationships, the correlation coefficient
$R$ was
determined using log-transformed POC/SPM and untransformed values of
the optical
parameter.