Experience, Insights and Opportunities Using ZAPS Technologies

Experience, Insights and Opportunities
Using ZAPS Technologies
LiquID Station
Dan Hanthorn
WWRP Operations Supervisor
City of Corvallis, Oregon
Key Points Today
•  ZAPS Technologies, Inc.
•  What the LiquID Station does
•  How the LiquID Station works
•  LiquID Station applications
•  Testing and validation
•  Corvallis’ experience
Chapter 1
ZAPS Technologies, Inc.
About ZAPS
ZAPS Technologies Inc. is based in Corvallis, Oregon, which has developed and
patented the LiquID Station for continuous Real Time on line monitoring of a wide
range of water quality parameters.
The LiquID is based on over 25 years of research and development by Dr. Gary
Klinkhammer, a preeminent global geochemist with over 25 years of experience in
environmental monitoring and earth sciences.
Detect. Respond. 5 ZAPS Technologies, Inc.
•  Founded and based in Corvallis, Oregon
•  Technology developed at Oregon State University
•  Roots in oceanography
•  US Navy and Defense Advanced Research Projects
Agency (DARPA) funded 17 years of research and
development
•  Brought to market for water, wastewater, industrial
and environmental monitoring
Chapter 2
ZAPS LiquID Station
Liquid Station
Parameters
Detect. Respond. 9 Liquid Station
Web Interface
Liquid Station
Corvallis Data
Chapter 3
How it works
•  High Energy
flash lamp
•  Fiber optic
light path
•  144
configurable
optical filter
pairings
•  Sensitive
photon
receptor
How the Liquid Station Works
•  Zero Angle Photon Spectroscopy (ZAPS)
•  Optical based, solid state
•  Broad multi-spectrum (hyperspectral)
•  Deep UV
•  Visible
•  Infrared
•  4 to 7 optical pairings per parameter
•  400 individual tests per optical pair
•  No chemical or reagents
How the Liquid Station Works
Advanced Optical Analysis
•  Hybrid
•  Absorption,
fluorescence,
and reflectance
measurements
from a single
optical platform
•  Hyperspectral
•  Deep UV,
Visible, Infrared
Z.-M. Zhang et al.
sform technique to Raman spectral
et al.[16] used a numerical method
transform (DWT) for the analysis of
ectroscopy measurements performed
uld overcome the presence of noise and
aused by light diffusion or fluorescence
ison between derivative preprocessing
ial baseline correction [Lieber and
Leger and Ryder[17] found that neither
e other, but the LMJ method simplifies
preprocessed spectra. With the help
filtration, Clupek et al.[18] treated the
tively, but high computing power was
ultiresolution advantages provided by
ate the varying background of spectral
eliminate the background in Raman
o et al.[20] have developed an improved
orescence removal based on modified
hich used a peak-removal procedure
d a statistical method to take the signal
by some parameters [signal-to-noise ratio (SNR), ridge length,
differences and etc.].
The paper is organized as follows. In next section, the
principles of peak detection based on wavelet, wavelet derivatives
calculation method for peak-width estimation, and penalized least
squares for background fitting are presented. In the following
section, our results are presented and discussed. Starting with
two simulated data, we use them to demonstrate the intelligence
of the proposed algorithm for correction of various backgrounds
(slope, curve, etc.). Then, through applications to real Raman
spectra, we demonstrate the validity of our algorithm. Finally,
some conclusions and outlooks are drawn from this paper.
How the Liquid Station Works
•  Thin slices of light probe the sample
•  Molecular bonds selectively react
•  Absorbed light detected
Materials and Methods
•  Fluorescent
light detected
Peak detection
Therelight
are various
criteria to detect peaks, such as SNR, intensity
•  Reflected
detected
threshold, slopes of peaks, local maximum, shape ratio, ridge lines,
model-based criterion, peak width, etc.[21] In this study, we follow
the SNR and ridge lines method proposed by Du et al.[22]
Let us start with a brief introduction to continuous wavelet
transformation (CWT). CWT is defined as the sum over all time
of the signal multiplied by scaled, shifted versions of the wavelet
function ψ. Mathematically, this process of CWT is represented as
follows:
•  Photons counted – all of them
wavelet
mial
fitting,[13,14,17,20]
[4,12,17]
d derivatives
are three maund-correction algorithms in Raman
widely used in Raman applications,
hortcomings in certain aspects. For
nomial fitting is not so effective and
s on the user’s experience.[13] For the
ng, the performance is poor in low
o-background ratio environments.[20]
change original peak shapes after the
use difficulty in the interpretation of
7]
Wavelet is a powerful tool in signal
ound-correction algorithms based on
m the signals into different frequency
remove the varying low-frequency
•  Data processed on-board LiquID Station
•  Algorithm for each parameter
C(a, b) =
!+∞
−∞
1
t−b
s(t)ψ a,b (t)dt, ψ a,b (t) = √ ψ(
), a ∈ R+ , b ∈ R
a
a
(1)
where s(t) is the signal, a is the scale, and b is the shifting. Here
ψ(t) is the mother wavelet, while ψ a,b (t) is the scaled and shifted
one. The result C is a two-dimensional (2D) matrix of wavelet
coefficients.
Unlike the nonredundant, more efficient DWT, CWT allows
How the Liquid Station Works
400 “Tests” Per Filter Pairing
Absorbance
Signal
400 Replicates
2 Minute Intervals
Fluorescence
Signal
Biofouling Management
Self Cleaning - Self Calibrating
Signal strength recovered following manual
clean and automatic self-calibration
Starting signal strength
Signal decay due to
biofouling
User defined Alert point at
50% signal loss
Over 1600 automatic cleans and calibrations checks
during the month without operator intervention
Detect. Respond. Chapter 4
Applications
LiquID Station Applications
•  Source water (drinking water) protection
•  Drinking water process monitoring
•  Wastewater process and effluent monitoring
•  Recycled/Reuse water applications
•  Wastewater pretreatment & source control
•  Treatment process modeling
LiquID Station Applications
•  Food processing
•  Research
•  Industrial processes
•  Environmental monitoring and detection
•  Public Health applications
•  Agricultural irrigation monitoring
Applications
Sea Water Aquarium
Sea water intake, multiple compounds monitored to
ensure water quality (LiquID in shed)
Pulp and Paper Mill
Pre-treated effluent,
primarily monitoring
BOD load
Agriculture
Rinse water used to
wash produce, primarily
monitoring chlorine
Research Vessel
Sea water, multiple compounds monitored to map
coastal water quality (LiquID in ship)
22
Chapter 5
Testing and Validation
Validation Trials
•  4 years of NELAC accredited lab comparisons
•  Third-party “blind” proficiency testing
•  Algorithm tuning
•  Build and replicate a 24-hr composite sample
•  Robust and reliable service record
•  Documented low O&M expense
•  Proven low maintenance history
Validation Trials
LiquID Brief – TOC Sensitivity
Sensitivity andZAPS
Accuracy
October 2011
Calibration of the LiquID system used in the clean water test discussed above was
performed using ZAPS – Yabby, our in-house designed and constructed automated reactor cell
system. The Yabby system allows for precise aliquots of standard materials to be added to a
continuously flowing sample at constant volume, resulting in an extremely well defined linear
standard regression. The graph below is an example of a 30-point, 15 hour low-level TOC
calibration experiment for potassium hydrogen phthalate (KHP) standard, further
demonstrating the unmatched sensitivity and resolving power of the ZAPS LiquID.
concentration TOC (mg/L)
LiquID ultra-low TOC concentration calibration
1.2
1.0
0.8
0.6
R² = 0.998
2- measurement errors
LOD = 0.015 (mg/L)
0.4
0.2
0.0
0.00
0.05
0.10
0.15
0.20
Absorption
0.25
0.30
0.35
0.40
BOD (mg/l) – ZAPS using HMA LiquID vs 5210B
600 500 400 300 200 100 0 0 100 200 300 400 BOD (mg/l) – standard method 5210B 500 600 LiquID Data vs Standard Method 5210B
Installation Locations
7
Number of LiquID Stations
11
Grab Samples (N)
100
Correlation (R2)
0.94
Detect. Respond. 26 cBOD (mg/L)
Regulatory Composites
350 300 250 200 150 100 50 0 12/1/2012 5/30/2013 Technique
Municipal Lab
ZAPS LiquID
Report Type
Daily Composite
Daily average
# of Days
78 (43%)
181 (100%)
# of Readings
78
82,165
Average Value
145.2
156.7
Detect. Respond. 27 Chapter 6a
Corvallis’ Experience
About Corvallis
Corvallis, Oregon WWTP
•  Population 55,000
•  Combined sewers
•  6 operators
•  One shift -10 hrs/day
•  Less than 1,000 kW per MGD w/Influent pumping
•  Landfill leachate
•  Oregon State University
•  Selective Trickling Filter/Selective Activated Sludge
Corvallis Unit Processes
Trickling Filters X 2
160’ X 8
161,000 cu. ft. each
Speed controlled
distributors
TF Circulation Pumps X 2
11.5 MGD each
40 hp each
Snail Sumps X 2
Aeration Basins X 2
75’ X 40’ X 15’ each
Process Blower
35 hp
Secondary Clarifiers X 2
115’ X 18’
Inboard Weirs
Process Flow Diagram – STF/SAS
Corvallis’ Experience - Matrices
•  4 years monitoring with ZAPS LiquID Stations
•  Raw/Screened Influent
•  Primary Effluent
•  Aeration Basin MLSS
•  Secondary Clarifier effluent
•  Final Effluent
Corvallis Process Flow Diagram
Chapter 6c
Corvallis’ Experience
O&M and Data Capabilities
Corvallis’ Experience
LiquID Station O&M
•  Simple installation
•  No membranes, no chemicals, no reagents
•  Multi-parameters - simultaneously
•  Auto cleaning
•  Self calibrating
•  Very low maintenance
•  Infrequent manual clean
•  Station preventative maintenance 1/yr
•  Robust and reliable – think appliance
35
Corvallis’ Experience – Lab & Data
•  Eliminates sample degradation, handling errors and
chain of custody
•  Continuous data – new values every 2 minutes
•  Real-time vs. composite data
•  Build a flow weighted composite sample
•  Diurnal impacts
•  Seasonal variations
•  Event detection
Chapter 6d
Corvallis’ Experience
Event Detection
Oregon State University
Football Event
kickoff
tailgating
half-time
Oak Creek Event – E.coli
Dairy Waste Spill
Cheese Whey Discharge - cBOD
Food Processor Discharge - cBOD
Chapter 6e
Corvallis’ Experience
Selector TF/AS Process
– Before ZAPS
Process Control - BEFORE
§  Low energy requirements
§  Low maintenance
§  Effective snail control
§  Enhanced process control
§  Controlled sloughing – consistent TSS & BOD
loading
§  Eliminated filter fly episodes
§  Improved “SRT” or biofilm persistence
§  Enhanced but uncontrolled nitrification & high Cl2
demand
Trickling Filters
BNR Selector
Activated Sludge
BNR Selector - BEFORE
Challenge & Opportunities
•  Optimal nitrification mode
•  Partial nitrification Cl2 demand
•  Partial de-nitrification
•  Filaments
•  Carbon source control
•  TF odors
Challenge & Opportunities
(continued)
•  Optimize alkalinity recovery
•  Real-time vs. composite data
•  Diurnal impacts
•  Seasonal variations
•  Automated process control opportunities
•  Wastewater Master Planning projects
Chapter 6f
Corvallis’ Experience
Selector TF/AS
Process Understanding
Diurnal Loading
•  Influent monitoring has led to the identification and
tracking down of two significant source control
problems - both were food processors with illicit
discharges
•  Diurnal BOD range is significantly greater than
diurnal flow
•  Very low BOD values at night
Trickling Filter cBOD Loading
Diurnal Loading
•  BOD removal rates in the primaries of up to 90%
before 6:30 a.m.
•  Between 6:30 a.m. and 7:00 a.m. the removal
efficiency drops to 10%.
•  Limited testing of chemically enhanced primary
settling has demonstrated that night time removal is
not complete - without the chemical addition.
•  Material is settling just enough to keep most BOD,
TSS & E.coli inside the tanks at low flow
•  Material is carried over the launders in the morning
with the slightest increase in plant flow.
Diurnal Loading
•  The carryover results in a sudden and very high
increase in loading to the biological processes
•  At 7:00 a.m. the highest loading rate of the day is
experienced
•  Peak loading occurs 3 hours ahead of peak diurnal
flow rates
•  The sudden change in loading ripples through the
plant in a cascade of consequences…including
increased E.coli and an increased demand for
sodium hypochlorite
Diurnal Loading of Effluent
Ammonia vs. Nitrite+Nitrate
Effluent Ammonia vs. Nitrite+Nitrate
Impacts of Flow & Temperature
11.20C
rain event
Nitrification Affected by Flow
and Temperature
rain event
Low pH
11.20C
Trickling Filter Loading & Ventilation
•  TFs operated in series optimize and stabilize BOD
and NH3 removal.
•  Compartmentalizing the process enhances the
removal of both constituents and reduces the
incidence of partial nitrification
•  Transient dips in TF BOD & NH3 removal were linked
to insufficient TF ventilation from two separate cause/
effect relationships.
•  The most common is a sharp reduction in natural
draft when the ambient air temperature is less than
+/-2 degrees F from the process water temperature
Trickling Filter Ventilation
•  Insufficient temperature differential to generate a draft
- either up or down.
•  Most commonly this occurs as air temperature swings
past the water temperature in the morning and
evening and usually lasts less than an hour
•  May persist more than a day during times of "just
right" atmospheric temperature stability.
Trickling Filter De-nitrification
Trickling Filter Ventilation
•  The other occurrences of insufficient ventilation is
during a combination very warm weather with near
100% nitrification across the TFs.
•  Demand outstriped O2 provided by a strong natural
draft
•  To the extent that anoxic conditions and denitrification are evident across the filters.
Activated Sludge Loading
•  Soluble BOD is only about 1-2 mg/L following the TFs
•  Methanol and crude glycerol have been as a
supplemental carbon source in the past
•  Using primary clarifier effluent, bypassed around the
TFs
•  15% bypass rate during the day; at night the bypass
rate is nearly doubled due to the low BOD in the PE
at low flow conditions.
•  A LiquID Station identified the optimal dose rate of
PE VFAs
Activated Sludge DO Control
•  Nitrification can be successfully sustained in the A/Bs
during the night with much lower D.O. residuals than
needed during the day
•  Within a reasonable D.O. range, maintaining a similar
"oxidation pressure" (intensity X duration) at low flows
does not inhibit the conversion of NH3.
•  A LiquID Station monitors the secondary effluent as
well, used as a sentinel for BOD & TSS anomalies.
Activated Sludge
BNR Selector Optimization - AFTER
Process Control - AFTER
•  Enhanced primary clarification and control
•  Improved process understanding
•  Process diagnosis
•  Blower control based on CBOD or NH3
•  BNR selector optimization
•  Nitrification/de-nitrification chemical control – VFAs,
methanol, glycerol
•  Disinfection optimization (hypo & UV)
•  Process modeling
Chapter 6f
Corvallis’ Experience
Other Process Enhancements
LiquID Station - Other Uses
•  Monitors final effluent E.coli
•  Began dosing hypo based on E.coli rather than Cl2
residual
•  Cut hypo and NaBs consumption by more than half
•  Use to provide continuous BOD & TSS data for
modeling the existing secondary clarifiers
•  The MLSS Station and SE Station were used to
document clarifier stress testing alongside the
customary grab samples
•  Event monitoring and Pretreatment Program Source
Control
Prior To Disinfection Optimization
High Cl2 Consumption & Cost Cl2 Initial Cl2 Residual Nabs Nabs Residual Initial Cl2 Dose = 1.9 – 2.1 mg/L Initial Cl2 Residual = 0.9 – 1.1 mg/L Final Cl2 Residual = 0.4 mg/L Nabs Dose = 0.7mg/L Nabs Residual = 0.3 mg/L Final Cl2 Residual Process Optimization
Lower Initial Cl2 Demand Cl2 2 - Cl2 Feed
3 - Low Range Analyzer
1 – Real time E.coli data
Initial Low-­‐range (LR) Cl2 Residual 4 - Partial Nitrification
Cl2 Nabs Final Cl2 LR Residual + ZAPS 5 – Hypo Degradation
Nabs Residual Initial Cl2 Dose = 1.0 – 1.1 mg/L Initial Cl2 Residual = 0.2 mg/L Final Cl2 Residual = 0.0 mg/L Nabs Dose = 0.0mg/L Nabs Residual = 0.0 mg/L Process stabilization minimizes 1) partial nitrification, and 2) false-­‐positive E.coli counts using approved test methods. 0 3/7/13 0:00 3/7/13 1:03 3/7/13 2:05 3/7/13 3:02 3/7/13 4:06 3/7/13 5:02 3/7/13 6:04 3/7/13 7:01 3/7/13 8:08 3/7/13 9:15 3/7/13 10:17 3/7/13 11:13 3/7/13 12:19 3/7/13 13:16 3/7/13 14:16 3/7/13 15:12 3/7/13 16:17 3/7/13 17:21 3/7/13 18:22 3/7/13 19:18 3/7/13 20:22 3/7/13 21:20 3/7/13 22:21 3/7/13 23:17 Reduced Chemical Consumption
120 100 80 60 40 20 ZAPS LiquID IDEXX Colilert-­‐24 Hach ColiBlue Reduced Chemical Consumption
Annual chemical
savings are
$75,000 or 62% of
the former annual
chemical budget;
15% of the M&S
budget
Effluent BOD is Strongly Tied
to TSS
Effluent TSS (floc carryover)
Tied to Limited De-nitrification
Future Process Enhancement Projects
And Lessons Learned
•  Combined systems have complex interactions
•  Consider the insults
•  Use primary sludge fermentation to generate VFAs
•  Mixed liquor recycle at 3-4X
•  Trickling filter forced ventilation
•  If you are non measuring it, you can’t fix it
Corvallis’ Experience - Savings
•  Lab testing
• 
COD test reagent - $2,400/year
• 
BOD – fewer bottles used
• 
E.coli – IDEXX Quanti-Tray - $2,340/year
• 
Lab labor down 33%
•  Chemical savings down 62% for Hypo and Sodium
Bisulfite - $76,000 per year
•  Energy – reduced A/B dissolved oxygen - $22,500/
year
•  BNR Capital Project $50M
74
Common Questions
•  Are the same algorithms used in every LiquID Station?
•  Yes….and no
•  Are the results approved for compliance monitoring?
•  Pending for BOD, cBOD, COD, TSS…..
•  Phosphorus?
•  No – similar to most other metals
•  Other parameters?
•  Under development
• 
raBOD (VFAs), bio-available iron, free Cl2, soluble
parameters
Common Questions
•  How much?
•  Standard configurations: water & environmental;
wastewater; water reuse; industrial
•  Custom configurations available
•  Communications options
•  Cost to operate?
•  ~$0.30 per day – same as a 120 watt light bulb
•  Outputs?
•  web page
•  4-20ma
•  Modbus
Questions?
Dan Hanthorn
Operations Supervisor
City of Corvallis, Oregon
PO Box 1083, Corvallis Oregon 97339
dan.hanthorn@hotmail.com