1. Single-particle Optics Approach in Studying the IOPs of Mineral Particles and Optical Variability
Feng Peng and Steven Effler
Upstate Freshwater Inst., Syracuse, New York
May 2015
IAGLR Annual Conference, Univ. Vermont, Burlington

2. The Forward and Inverse Problems in Hydrologic Optics
Dissolved material
Particulate material
Inherent
Optical
Properties
Apparent
Optical
Properties
Our research has been focusing on the first step

3. Why Are We Still Focusing on the First Step?
Case 1 vs. Case 2 waters
IOPs of Case 1 waters modeled by a single index
Case 2 waters (inland lakes) optically more complex
multiple contributing constituents, not co-varying
regional and spatial differences
Suspended particles are especially important to optical variability and remotely sensed optical signals
need better understanding of bp and bbp for Case 2 waters
mineral particles more efficient in scattering light
bb = bbw + bbp
bbw known and « bbp

4. Individual Particle Analysis (IPA)
Scanning electron microscopy coupled with Automated image and X-ray analyses (SAX)
detailed morphological and compositional characterizations
inputs for Mie calculations of bm and bb,m
partitioning bm (bb,m) into contributing particle type components (clay minerals, calcite, quartz)

5. Modeling Mineral Particle Scattering: SAX–Mie Approach
single-particle optics to bulk properties
Qb,i : scattering efficiency factor
f (size, composition, l); Mie
PAi : projected area of a particle
V: sampling volume
N: number of mineral particles
in sampled volume
Stramski et al. (2007) “… basic laboratory studies of particle types … with a detailed characterizations of particle populations with the use of … individual particle analysis, must be pressed further …”
We’re the only research group with demonstrated capability

6. Partitioning bp and bbp into Contributing Components: Reductionist Approach
two-component (mineral and organics) approach
bp = bo bm
Clay
Calcite
phytoplankton
empirical,
bio-optical models
mineral particles
mechanistic, Mie theory
based on IPA results

7. 2007 Lake Ontario Optics Study
R/V Lake Guardian Cruises (EPA stations)
field optical instruments (WET Labs)
ac-s: attenuation & absorption; bp
BB-9: backscattering; bbp
Laboratory measurements
Chlorophyll-a
particle analysis by SAX
Citation: Peng and Effler, J. Great Lakes Res., 2011, 37, 672682

8. ell done! Modeling Closure with Measurements Particulate scattering
bp(650)
Particulate backscattering
bbp(650)
Two pictures are worth two-thousand words!
ell done!

9. 2007 Lake Ontario: Partitioning of bbp
Mineral particles were important to backscattering
bb,m/(bb,o + bb,m): 4584% (avg. 66%)
calcite dominant at eastern sites
calcite
clay
diatom

10. Microscopic View on Calcite Precipitation
CaCO3 in Lake Ontario
supersaturation when stratified
‘whiting’ well-documented
What served as nucleation sites?
‘differential’ IPA
SAX before and after acid treatment to remove CaCO3

11. Mineral Particles in Western Lake Erie (2007)
Particle size distribution (PSD) and spectral absorption
Implications for spectral (back)scattering
Iterative Mie calculations
PSD
aNAP
Citation: Peng and Effler, Limnol. Oceanogr., 2013, 58, 17751789

12. 2013 Cayuga Lake Optics Study
developing system-specific bio-optical models
bulk measurements
ac-s and BB9
single-particle optics
bm and bb,m
residual scattering (bp – bm)  POC (particulate organic carbon), at 660 nm
consistent with Case 1 oceanic models, ① and ②(Stramski et al. Biogeosciences 2008)

13. Summary The SAX–Mie approach provides credible support for
partitioning bulk IOPs into contributing components
our better understanding of optical variability
the pursuit of closure in forward optical modeling
‘ground-truthing’ for remote-sensing applications
The success of the two-component approach has been demonstrated in multiple inland water systems
Mineral particles are important to light scattering and remote-sensing signals for many study systems
Single-particle optics approach offers an indispensable tool for advancing hydrologic optics