Opening Presentation LISST-Technology and performance – challenges and solutions -Team Sequoia
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Transcript of Opening Presentation LISST-Technology and performance – challenges and solutions -Team Sequoia
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OPENING PRESENTATIONLISST-TECHNOLOGY AND PERFORMANCE – CHALLENGES AND SOLUTIONS
-TEAM SEQUOIA
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Scope of Opening Presentation
Technology basics – review Limitations of LD Technology in general Limitations of LISST instruments What can go wrong in data/operations What can go wrong in interpretation Analysis of your experiences –
Tim Straub; Mark Landers
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TECHNOLOGY BASICS
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LD Technology Basics
All LD technology provides PSD and Concentration of an ensemble of particles ‘A view in a flash’
LISST and all other LD instruments are NOT particle counters, and NOT samplers.
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ISO 13320:2009
ISO-13320 was written only for PSD Summing PSD gives concentration over the size range
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How Laser Diffraction Works
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Inverted PSD
Particles of ANY size produce light on ALL rings Light on a particular ring does NOT represent concentration of any
particular size particle. Common misunderstanding
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Randomly Shaped Particles Scattering from randomly shaped
grains differ slightly from same-size spheres; this changes the size scale
All pre-Sequoia work produced PSD of equivalent spheres Only Sequoia offers inversion to give
PSD of ‘sieved sizes’. Using the randomly shaped
matrices enables comparison with existing, historical SIEVE data sets
Randomly shaped
Agrawal et al. 2008 (JGR)
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LIMITATIONS OF LD TECHNOLOGY IN GENERAL
- Upper and lower size limits- Cannot discriminate types of
particles
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Upper and Lower Size Limits
Upper size limit derives from smallest ring Lower size limit derives from largest ring
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Scattering signatures
Smallest ParticleLargest Particle
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How LD sees particles outsidethis range
Particles Leak into the nearest size bins This often produces rising tails in PSD
More so for particles smaller than the smallest size bin of the LISST
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Almost everything scatters
Particles, bubbles, algae, etc. but also density fluctuations caused by temperature variance
Density-related scattering (‘scintillation’) invents large particles. Scintillation is avoided by letting water and LISST reach identical
temperature. This is common to all LD systems.
Sediment flocs in the Po River, Italy
Schlieren / Scintillation
Bubbles Phyto- and zoo-plankton
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Converting volume to mass All LD systems measure volume distribution Converting to mass requires the user to ASSUME an
effective mass density and then apply that Easier in the lab, where all particles can be dispersed
(ISO 13320:2009). Not easy with field data where aggregates, bubbles, low-
density biological particles can be present
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LIMITATIONS OF LISST INSTRUMENTS
Concentration limits Limits exists in the field Optimum accuracy at optical transmission between 0.3 and 0.98 For –SL: upper limit (mg/l) = 300*d[µm] For –SS: 200*d[µm] Lower limit limited by signal-to-noise ratio
Size range may not cover all particles in suspension Clogging of intakes for pumped instruments
LISST-StreamSide LISST-SL
Velocity limits for isokinetic sampling and general operation (-SL only)
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WHAT CAN GO WRONG WHEN COLLECTING
DATA
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Misalignment of optics Low zscat laser power, increased zscat scattering on inner rings
constant in time Dirty windows
Increased zscat scattering on middle rings Poor temperature equilibrium - scintillation
Increased scattering on inner rings, decreasing in time Clogging of intake by debris Clogging of pitot tube by debris (-SL only)
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LISST-SL pump not locked in, still adjusting during sampling Lock-in ~ 2 minutes after immersion when powered After lock-in isokinetic control is better than 10% as set at factory Minimum river velocity for isokinetic operation is 0.5 m/s [1.65 ft/s]
Purging of bleed port not adequate Erratic velocity readings on TCB
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Is swimming a problem? Eddies change instantaneous flow
direction The component of drag normal to
river flow produces side-ways drift of -SL
Because USGS samplers weight >> drag, they are pushed less in sideways direction
A look at video of –SL always shows wake of ‘sail’ aligned with flow.
Even so, for operation in higher velocity rivers, extra weight will be needed. Sequoia to design.
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WHAT CAN GO WRONG WHEN INTERPRETING DATA
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Short LISST-SL time series is an issue Makes interpretation and troubleshooting more difficult Measurement duration should be >> time-scale of local eddies
Presence of loosely aggregated particles Density << 2.65 Affects conversion from volume to mass!
Particles outside the size range Will influence computation of size parameters (mean, median etc.) Will overestimate total concentration
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A common source of error - Mixing
Concentration gradients exist everywhere, in the field and lab [Rouse (1937) showed C ~ z –ku*/wf ]
To avoid, turbulent velocity fluctuations >> settling velocity
Location of intake pump in a gauging station will affect measured PSD [see Cowlitz/Puyallup river data]
Even in the lab, concentration gradients make calibrations and comparisons very difficult.
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Incomplete mixing in a river
Vertical variation of size distribution seen in Cowlitz (also Puyallup) river
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YOUR EXPERIENCES
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Comparing size distributions
Size distributions from different methods CANNOT be compared.
The pipette method will always produce smaller diameters than LD for the same sample: Konert & Vandenberghe 1997
Same applies to Sedigraph and Sieving LD PSD should be compared to LD PSD only Discrepancies WILL occur (except for spheres)
Use literature to evaluate if observed differences > expected Sample analysis in the lab changes the size distribution
compared to the in-situ data (settling, sonification, in-situ aggregation etc.)
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Converting to mass
Mass density of in-situ particles is not the same as the density of the same particles in the lab when disaggregated
Calculating an effective in-situ density using water samples is an effective method for converting in-situ volume to mass
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Effective Density: Definition
Effective Density = It is NOT the density of the individual
particles It changes in time and space
depending upon conditions
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Effective Density: Example
Sediment Grains Flocculated particles
Bubbles
Particle Size (µm) 30 30 30Volume Conc (µl/l) 100 100 100
Filtered and Weighed Mass Conc (mg/l) 260 40 0
Effective Density 2.6 0.4 0
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Flocculation effect on size distribution
Arctic Rivers (Droppo et al., 1998)
No single grains > ~10 µm
All in situ particles > 10 µm were flocs
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Conclusions
LD has strengths and limitations.
Data suggest the possibility of flocs in-situ.
Remains to examine data to be presented.