EPA/600/R-12/672 | October 2012 | www.epa.gov/ord
United States
Environmental Protection
Agency
              Detection of contamination
              in drinking water using
              fluorescence and  light
              absorption based online sensors

Office of Research and Development
National Homeland Security Research Center

-------
Disclaimer

The United States Environmental Protection Agency (EPA) through its Office of Research and
Development created this report. EPA funded and collaborated in the research described herein
under contract number EP-C-09-041 with Shaw Environmental and Infrastructure, Inc. This
report has been subjected to technical and administrative reviews but does not necessarily reflect
the views of the Agency. EPA does not endorse the purchase or sale of any commercial products
or services.

Questions concerning this document or its application should be addressed to:

Jeffrey Szabo, Ph.D., P.E.
National Homeland Security Research Center (NG-16)
Office of Research and Development
United States Environmental Protection Agency
26 W. Martin Luther King Dr.
Cincinnati,  OH 45268
(513)487-2823
szabo.j eff@epa.gov
John Hall
National Homeland Security Research Center (NG-16)
Office of Research and Development
United States Environmental Protection Agency
26 W. Martin Luther King Dr.
Cincinnati, OH 45268
(513)569-2814
hall.john@epa.gov

-------

-------
Foreword

The U.S. Environmental Protection Agency (EPA) is charged by Congress with protecting the
nation's air, water, and land resources. Under a mandate of federal environmental laws, the
Agency strives to formulate and implement actions leading to a balance between human activity
and the ability of natural systems to support and nurture life.  To meet this mandate, the
Agency's Office of Research and Development provides data and scientific support needed to
solve environmental problems and to build the scientific knowledge base needed to manage our
resources wisely, understand how pollutants affect our health, and prevent or reduce
environmental risks.

In September 2002, the  Agency announced the formation of the National Homeland Security
Research Center (NHSRC), which is part of the Office of Research and Development's
Homeland Security Research Program. Guided by a roadmap set forth in the Agency's
Homeland Security Strategy, NHSRC researchers manage, coordinate, support, and conduct
research and provide technical assistance. The research is designed to provide appropriate,
affordable,  effective, and validated technologies and methods to address risks posed by chemical,
biological, and radiological terrorist attacks. The EPA Homeland Security Research Program's
water security research includes prevention, protection, detection, containment, treatment, and
decontamination. Additional information on the program and its research products can be found
at http://www.epa.gov/nhsrc.
                                           IV

-------
 Abbreviations and Acronyms

ADF       Airplane De-icer Fluid
ATCC     American Type Culture Collection
cfu        Colony Forming Unit
Ct         Concentration of Disinfectant Multiplied by Contact Time
CWA      Chemical Warfare Agent
DPD       N,N-diethylphenylenediamine
DSS       Distribution System Simulator
EPA       United States Environmental Protection Agency
FU        Fluorescence Units
HSPD     Homeland Security Presidential Directive
GCWW    Greater Cincinnati Water Works
gpm       Gallons per Minute
LED       Light Emitting Diode
NHSRC    National Homeland Security Research Center
NTU       Nephelometric Turbidity Units
ORP       Oxidation-Reduction Potential
PVC       Polyvinyl Chloride
RFU       Relative Fluorescence Units
S/N       Signal-to-Noise Ratio
T&E       Test and Evaluation
TOC       Total Organic Carbon
UV254      Ultraviolet Light at 254 nm Wavelength
UVAS sc   Hach Ultraviolet Light Absorbance/Transmittance Sensor
UV-Vis    Ultraviolet and Visible light wavelengths
WIPD     Water Infrastructure Protection Division
WRF       Water Research Foundation (formerly known as American Water Works Association
           Research Foundation)
YSI       Yellow Springs Instruments (6920 Multi parameter sonde water quality logging
           system)

-------
Table of Contents

Disclaimer	ii
Foreword	iv
Abbreviations and Acronyms	v
Acknowledgements	vii
Introduction	1
Materials and Methods	3
  Single Pass Pipe System	3
  Online Sensors	3
  Contaminants	7
  Data Analysis	8
Results and Discussion	10
Conclusions	16
References	17
  Appendix 1	20

List of Tables

Table 1: Sensors Used for Testing	5
Table 2. Contamination Detection Results (DET = detect; nd = no detect)	19
                                            VI

-------
Acknowledgements
Contributions of the following individuals and organization to the development of this document
are gratefully acknowledged:

Shaw Environmental and Infrastructure, Inc.
                                        VII

-------
Introduction
After the events of September 11, 2001,
improving the security of our nation's water
infrastructure became a priority. Research
on water quality monitoring for drinking
water distribution systems has increased in
scope and importance. Homeland Security
Presidential Directive 7 (HSPD-7), issued on
December 17, 2003, established a national
policy for federal departments and agencies
to identify and prioritize the United States
critical infrastructure and to protect the
infrastructure from terrorist attacks. HSPD-
9, issued on January 30, 2004, directed U.S.
Environmental Protection Agency (EPA) to
"develop robust, comprehensive, and fully
coordinated surveillance and monitoring
systems that provide early detection and
awareness of disease, pest, or poisonous
agents." EPA now plays a critical role as the
lead federal agency for water security.  In
2005, EPA released the peer-reviewed
Water Security Research and Technical
Support Action Plan [1], which identified
high priority water security data gaps and
outlined research and technical support
projects to address these gaps.  The technical
support and action plan also identified
research products that would summarize
data and discuss how this data enhanced the
security of drinking water and wastewater
systems.

The EPA's National Homeland Security
Research Center's (NHSRC) team of
scientists and engineers is dedicated to
understanding the terrorist threat,
communicating the risks, and mitigating the
environmental impacts of attacks. The
NHSRC's Water Infrastructure Protection
Division (WIPD) performs research on
contaminant detection, containment,
mitigation, and  decontamination in drinking
water systems. This document focuses on
fluorescence and light absorption based
detection technologies that could be used to
detect a contamination event within a water
distribution system.

EPA has tested  several sensors that relied on
optical principles of operation in previous
research at the Test and Evaluation (T&E)
Facility. However, the past work was
focused on measuring contaminant
absorption of ultraviolet (UV) light alone, or
UV-visible (UV-Vis) light as a surrogate
measurement of total organic carbon (TOC),
or on measuring turbidity changes  due to
contamination using optical devices [2-4].
Fluorometry is a mature technology and has

-------
been used extensively for the detection of
hydrocarbons in the oil and gas industry and
for the detection of algae in source water.
This established track record and the recent
advances in light emitting diode (LED)
technology, which can substantially lower
the overall cost of ownership for these
devices, prompted water security
stakeholders and drinking water utility
partners to propose this additional
evaluation of online absorption and/or
fluorescence-based monitoring devices for
contaminant detection purposes.  The
fluorescent sensors were tested alongside
conventional water quality monitors
previously tested [5] at the Agency's Test
and Evaluation (T&E) Facility in Cincinnati,
Ohio.

-------
Materials and Methods

Single Pass Pipe System
The drinking water distribution system
simulator (DSS) used in this study has been
described previously [4, 6].  A drinking
water distribution pipe was represented
using a once-through (or single pass) pipe.
The pipe consists of 1,200 feet of 3-inch
diameter fiberglass lined ductile iron.
Experiments were conducted at 22 gallons
per minute (gpm), which corresponds to an
average velocity of 1 foot per second (ft/sec)
in the pipe.  This flow rate will produce
turbulent flow (Reynolds number
approximately 26,000) in the relatively
smooth pipe.  Although the pipe is lined
with fiberglass, sections have chipped away,
exposing ductile iron.  These sections were
heavily corroded and were more
representative of an iron drinking water pipe
than the lined sections. Note that English
standard units, commonly used by the U.S.
water utility personnel, have been used
throughout this report. For example, volume
is reported in U.S. gallons and velocity in
feet per second (ft/s). However, in keeping
with industry usage, contaminant
concentrations are reported in metric units,
in milligrams per liter (mg/L).
Chlorinated tap water was introduced
directly from the Greater Cincinnati Water
Works (GCWW) distribution system into a
750 gallon storage tank from where it was
fed by gravity into the 3-inch pipe system.
An air gap was maintained between the
GCWW system and this experimental setup
to ensure that there was no back flushing of
the injected contaminant.  Free chorine was
generally 1.0 ± 0.1  mg/L, with temperature
ranging from 10° to 30° C depending upon
the season.  Turbidity was 0.1 nephelometric
turbidity units (NTU) or less throughout the
year.  The water fed from the 750 gallon
overhead tank provided 10 to 12 pounds per
square inch (psi) inside the pipe.
Contaminant injections were performed for
20 minutes by injecting a 10 L mixture of
contaminant and tap water at the rate of 0.5
L/min. Contaminant concentration in the
pipe was varied by  altering the amount of
contaminant mixed in the  10 L volume.
Control experiments were performed by
injecting  10 L of tap water without the
contaminant at the same injection rate.

Online Sensors

In order to cover a broad range of
fluorometric sensors, two commercially
available devices were chosen to represent

-------
the low- and high-end of the cost and
complexity spectrum. A Turner Designs
(Turner Designs Hydrocarbon Instruments
Inc., Fresno, California) online fluorometer
(model TD1000C) with a single  excitation
and emission wavelength was utilized as an
example of a relatively simple off-the-shelf
fluorometric sensor. A multiple wavelength
ZAPS LiquID™ unit (ZAPS Technologies
Inc., Corvallis, Oregon) was used to
represent a more complex instrument. Both
instruments were inexpensive to operate and
maintain (similar to the other optical
sensors) but the capital cost of the ZAPs unit
was five times higher than the Turner
sensor. However, the ZAPS unit also has
the capability to perform absorbance
measurements (i.e., spectrophotometry).

Sensors based on various detection
principles are in continual operation at the
T&E facility, and  data were collected from
them during testing of the fluorometric
devices.  Sensors used during testing, along
with calibration procedures and principles of
detection are summarized in Table 1, below.

-------
Table 1: Sensors Used for Testing
Manufact Parameter Method Citation
urer
YSI*
Specific 2510 A
conductance
YSI* Oxidation- 2580 A
reduction
potential
YSI* pH 150.1
YSI* Temperature 170.1
YSI* Turbidity 180.1
Hach® Free chlorine 4500-CI G
CL17
Hach Free chlorine 334.0
CL10
Hach UVAS sc DIN 38404 C3
and Standard
Methods #5910
Hach TOC 415.1
Astro
Model
4195/103
0
Method Reporting
Source Units
Standard mS/cm
methods[7]
Standard mV
methods[7]
EPA/600/4-79- pH
020[8]
EPA/600/4-79- °C
020[8]
EPA/600/4-79- NTU
020[8]
Standard mg/L
methods[7]
EPA/81 5/B/09/
013[9]
German UVA m"n
Institute of
Standardization
and Standard
Methods
EPA/600/4- mg/L
79/020[8]
Principle of
Detection
4 nickel
electrodes
Potentiometric,
platinum
electrode,
Ag/AgCI
reference
electrode
Proton selective
glass electrode
(non-fouling
version)
Sintered metallic
oxide thermistor
Nephelometric
signal 860 nm
LED (90
degrees) with
integral wiper
Hach CL17
(DPD reaction)
colorimetric
Amperometric
sensor with Cb
permeable
membrane (0-to
20-ppm)
UV absorption
measurement
(2-beam
technique),
reagent-free.
Determines the
Spectral
Absorption
Coefficient
(SAC) at 254 nm
UV-persulfate
oxidation
method coupled
with the NDIR
CO2 detection
Calibration
Technique
1 000 nS/cm
standard
Zobell
solution,
temperature-
corrected,
single point
offset
adjustment
2-point - pH 7
and pH 10
buffers
Not applicable
2-pont: zero
and 20 NTU
formazin
Factory
calibrated
Set to known
value based
on Hach
DR2010DPD
colorimetric
method
Optical Filter -
Lambda M
254 nm;
Lambda R
550 nm
25 ppm span
calibration
with Hach
certified KHP.
Zero
calibration
with Hach
certified zero
TOC
standard.
NDIR
calibration

-------
Manufact Parameter Method Citation Method
urer Source




GE/Sieve TOC 415.3 EPA/600/R-
rs On-line 09/1 22 [10]
900
Series
Model
5310C








RealUV2 UV254 Standard Standard
54 (Hi- Methods #5910 Methods[7]
Pure)
M4000






Turner fluorescence No standard Not applicable
Designs method
Hydrocar
bon
Instrume
nts
TD1000C
, Oil in
Water
Monitor
ZAPS carbon Not specified Not specified
LiqulD
Station **



Reporting
Units




mg/L












UVA m'n









Relative
fluorescenc
e units
(RFU)






Carbon
Indicator
(counts)
Tryptophan
(mg/L)
UVA (m'1)
Principle of
Detection




UV-persulfate
oxidation
method coupled
with
conductometric
detection of CO2








UV absorption
measurement
(with anti drift
compensation),
reagent-free.
Determines the
spectral
absorption
coefficient (SAC)
at 254 nm
Fluorescent
hydrocarbons
light absorption
and emission.
(ppm-ppb
range)




UV-Vis
absorption,
fluorescence
and reflectance
measurements

Calibration
Technique
with certified
CO2
standards in
nitrogen
balance.
Single point
calibration
with KHP at 5
ppm with a
single point
sucrose
verification at
2 ppm. Also
required is a
check of the
inorganic
carbon
remover with
Na2CO3.
Set to known
water
absorption at
254 nm






Calibrated
with a
fluorescent
dye to the oil
equivalent of
#6 fuel oil at
11.5 ppm



Factory
calibration




Manufacturers' locations: GE Analytical Instruments, Boulder, Colorado; Hach Co., Loveland, Colorado; Real
Tech Inc., Whitby, ON, Canada; Turner Designs (Fresno, California;  YSI Inc., Yellow Springs, Ohio,  ZAPS
Technologies, Corvallis, Oregon
Acronyms: SAC, spectral absorption coefficient; TOC, total organic carbon; UV-Vis, ultraviolet and visible
light wavelength
*YSI is the model 6920DW multi parameter sonde
** See specification sheet from ZAPS for other channel units at http://www.zapstechnologies.com/wp-
content/uploads/2012/05/LiqulD-2012-Product-Brochure.pdf

-------
Contaminants
Contaminants were selected based on their
widespread use by businesses, industry, and
individuals, as well as input from the sensor
manufacturers.  Except for Escherichia. coll
and sodium thiosulfate, there has been little
online detection data available for these
contaminants prior to this study.

Airplane De-icer/Antifreeze: The ZAPS
device has been used to detect airplane de-
icer in runoff form airports. Accordingly,
used airplane de-icer fluid was obtained
from the Lunken airport (Cincinnati, OH)
ground crew. The composition of the used
de-icer was reported to be 60% propylene
glycol and 40% water. Another commercial
off-the-shelf antifreeze product (Prestone®,
Prestone Products Corp., Danbury,
Connecticut) containing ethylene glycol and
diethylene glycol was also utilized. Finally,
solutions of laboratory grade (99.8+%)
ethylene glycol (Fisher Scientific, Thermo
Fisher Scientific Inc., Waltham,
Massachusetts) were investigated.

Herbicide: Basagran® herbicide (44%
benzaton) (Southern Agricultural
Insecticides, Inc., Palmetto, Florida) is a
sedge-control herbicide. It was chosen since
it represents the herbicide class of
chemicals.  It also has a fluorescence
emission wavelength similar to fuel oil #2
and the Turner device was calibrated to
detect fuel oil #2. The ZAPS unit was not
available during the Basagran herbicide
injections.

Chlorine Bleach: Injection of chlorine beach
(Sno-Glo 10% Bleach, Brenntag Mid-South,
Mulheim an der Ruhr, Germany) into the
piping is meant to represent an increased
level of free chlorine in a drinking water
distribution system, similar to a
decontamination scenario or accidental over-
dosing of chlorine.

Dechlorination Chemical: Sodium
thiosulfate (ACS grade, 99+%, Fisher
Scientific) is a common dechlorination
chemical.

Biological agent: E. coli strain K-12
(ATCC™ 25204) represented a vegetative
biological agent. E. coli cultures contain
tryptophan, which has fluorescent properties
and may be detectable by the ZAPS or
Turner devices. E. coli would be quickly
inactivated by free chlorine in the tap water
flowing through the DSS; it could not be
repeatedly injected and quantified without
dechlorination.  Thus, E. coli was always

-------
injected with free chlorine.  Sodium
thiosulfate, described above, was chosen for
dechlorination.

Diesel Fuel: Diesel fuel is an automotive
fuel and was obtained from a local Sunoco®
gas station in April 2011.  The Turner
equipment is used to detect hydrocarbons
within the diesel fuel and the dispersant
described below.

Dispersant:  Polychem DISPERSIT®
dispersant (U.S. Polychemical Corp.,
Chestnut Ridge, New York) was used as a
model oil dispersant. The composition is
proprietary, but it contains emulsifiers,
dispersants and water soluble coupling
solvents. Large amounts of dispersant could
be used in an oil spill remediation and
present a crossover hazard from source
water to drinking water.

Toxin Surrogate: Pepsin dry powder (Acros
Chemicals) was chosen as a surrogate for
ricin because both have similar tryptophan
contents.

Data Analysis
Sensor response to contamination was
evaluated by calculating the change of the
sensor output signal from a stable baseline
to the peak value recorded as the
contaminant passed the sensor. Baseline
values were calculated by averaging the
sensor signal over a one-hour period before
contaminant injection, with baseline noise
represented by standard deviation. Absolute
change was calculated as the difference
between the peak sensor value recorded
during contamination and the stable baseline
value. Percent change was calculated by
dividing the absolute change by baseline
value and multiplying by 100.  Calculating
percent change yields the system specific
response of water quality parameters to each
contaminant; note that the same absolute
change will yield different percent changes
in drinking water systems with different
baseline water quality values. Sensor
response was also characterized as a signal-
to-noise ratio (S/N). The absolute change
recorded during injection was normalized by
the baseline standard deviation. The S/N
ratio accounts for baseline variation before
contaminant injection.

Sensor response values provide metrics of
sensor change after contamination, but
whether sensor changes constitute a
detection of the contaminant depends on
how detection is defined.  Often, the
definition of detection will be drinking water

-------
system specific and will depend on whether
an event detection algorithm is used or if
system-derived detection thresholds are
determined. In practice, some degree of
subjective data interpretation must be
performed to define a detection threshold.
In this report, the study contributors
determined detection thresholds by manually
examining sensor changes and, based on
their experience with on-line sensor changes
that have indicated contamination [4, 11],
judging whether the change was large
enough relative to the baseline to detect the
contaminant. The detection thresholds are
summarized in Table Al (Appendix 1). A
contaminant was considered detected if the
absolute change, percent change, and S/N
thresholds were surpassed. It is important to
note that although these detection thresholds
were determined by the contributors to this
study; others could come to different
conclusions.

Sensors were polled two every minutes
during test runs, so 30 pre-injection data
points were used to determine baseline mean
and standard deviation. Contamination
injections were performed in duplicate, and
results are presented as the average of those
duplicates.  The time period when the
injected contaminant was in contact with the
sensors was determined based on the flow
rate and injection duration, and was
confirmed through dye injections. Injections
were 20 minutes long and flow velocity was
1 ft/sec, so the injection reached the 80 ft
sampling point in 1.3 minutes after injection
and continued passing the sensors for 20
minutes. Sensors typically responded to
contamination 3-4 minutes after injection
due to the time it takes water to travel from
the sampling point to the sensor manifold.
Sensor responses usually lasted longer than
20 minutes at this station due to dispersion,
which elongated the contaminant plume in
the pipe. Peak sensor responses were
recorded from the time periods when the
contaminants were in contact with the
sensors.

Although water quality sensors typically
respond within seconds of water quality
change, the Hach CL17 and TOC analyzers
had run cycles of 2.5 and 8 minutes,
respectively.  These instruments were polled
every two minutes, but only returned new
values at the end of their cycles.  Still, new
values were returned frequently enough that
the changes in water quality were seen for
both devices while the contaminant was
passing the sampling point.

-------
Results and Discussion
Table 2 (located at the end of the report)
summarizes the detection test results in
terms of whether the contaminant was
detected or not. As discussed in the
Materials and Methods section, detection of
contamination is determined by calculations
of absolute change, percent change and S/N,
and whether all three values surpass
detection thresholds.  The detection
threshold values that define detection of
contamination are in Table Al. The results
of absolute change, percent change and S/N
are included in Tables A2-A4 in the
appendices.

Online Water Quality Sensors Detection
As determined in past  studies, free chlorine
and TOC are the most effective widely used
online water quality parameters for detection
of contamination [4, 5, 11-13].
Antifreeze/ethylene  glycol, de-icer,
dispersant, pepsin, and Basagran herbicide
all have organic components and were
detected by online TOC analyzers. Diesel
fuel was not introduced into the TOC
analyzers since it would have permanently
contaminated their complex plumbing
systems.  Diesel fuel is organic, but it is not
miscible with water, so whether the TOC
analyzers would have detected it is
uncertain. The Sievers and Hach Astro TOC
analyzers detected the same contaminants at
the same concentration except for Basagran
herbicide at 1 mg/1, which the Hach unit did
not detect. The Sievers and Hach TOC
analyzers both detected absolute changes of
0.41  and 0.44 mg/L and percent changes of
57.5  and 73.2, respectively. The main
difference was in  S/N, which was 74.8 and
7.0 for the Sievers and Hach units,
respectively.  The difference comes from
noise in the baseline of the Hach unit.

As expected, the free chlorine analyzer
values  increased when chlorine bleach was
injected at 5 mg/L. Dispersant, pepsin, and
Basagran herbicide have organic
components that react with free chlorine to
lower the free chlorine levels in the water
flowing through the DSS. Thiosulfate is a
common dechlorinating agent and reduced
free chlorine to zero when injected at 9
mg/L.  E. coli co-injected with 9 mg/L
thiosulfate also reduced free chlorine to
zero. This reduction was due to the
thiosulfate and not E. coli. Previous work
established thatE1. coli and Bacillus spores
were not detected by free chlorine or TOC
sensors at 103-104 colony forming units
(cfu)/ml, and that  more sophisticated online
                                           10

-------
sensors were required to detect biological
agents at these levels [4].

The only discrepancy between the Hach
CL17 and Hach CLIO analyzers'
capabilities was with Basagran herbicide.
The Hach CL17 detects free chlorine
through a color change reaction between
free chlorine and N,N-
diethylphenylenediamine (DPD), and is an
online version of the laboratory method.
The CL17 signal did not decrease when
Basagran herbicide was injected. The Hach
CLIO analyzer is an amperometric
electrochemical sensor, and its output signal
did decrease when Basagran herbicide was
injected. The Basagran solution (either
benzaton or other ingredients) may have
interfered with the CLIO sensor and  gave
the appearance of free chlorine changing
even though it did not. Even though this is
not a true free  chlorine change, it is
interesting to note that the presence of
Basagran herbicide can be detected with  an
amperometric free chlorine sensor.
conductivity increased when bleach and
sodium thiosulfate were injected due to the
high concentration of ions in these solutions.
The oxidation-reduction potential (ORP)
decreases when free chlorine decreases since
the oxidation potential of the water
decreases.  Thiosulfate with and without E.
coli depleted the free chlorine in the tap
water, which was enough of a change to
trigger a detection with ORP. Bleach
increased free chlorine, and pepsin and
dispersant reacts with and decreases free
chlorine, but not enough to detect either with
ORP. The pH increased when bleach was
injected since chlorine bleach typically has a
pH between 11.0-11.5.

Turbidity sensors were effective at detecting
de-icer, diesel fuel, dispersant and pepsin.
The used de-icer fluid has particulate matter
which contributed to the turbidity increase.
Diesel fuel does not dissolve in water and
turbidity increased due to the bubbles and
drops of diesel circulating in the water
column.
The remaining online water quality sensors
did not detect the wide range of
contaminants that free chlorine and TOC
parameters indicated, which is consistent
with past research [4, 5, 11-14]. Specific
UV-Vis Spectrophotometric Sensor
Detection
The same contaminants were detected by the
Real UVT and the Hach UVAS sensors, and
each sensor detected the same
                                           11

-------
concentrations. Results were the same for
the UV254 absorption channel on the ZAPS,
except for dispersant at 1 mg/L. Antifreeze
(commercial Prestone®) was detected at 10
mg/L, but ethylene glycol, which is a
component of commercial antifreeze
products, was not detected, suggesting
another component in the commercials
product is responsible for the detection.
According to the MSDS, the other
component of Prestone antifreeze is
di ethyl ene glycol [15].  Thus, the detection
observed by devices utilizing UV light
absorption at 254 nm may have come from
diethylene glycol or perhaps a dye added to
the formulation.  Bleach was also detected
by both sensors.  Hypochlorous acid and
hypochlorite ion have UV absorption peaks
at 236 and 292 nm, but enough absorption
occurs at 254 nm for detection to take place.
Similarly, dispersant, thiosulfate, E.
co//'/thiosulfate, pepsin, and Basagran
herbicide also have sufficient absorption at
254 nm to be detected. De-icer fluid and
diesel fuel did not exhibit sufficient
absorption at 254 nm at the concentration
used in this study to be detected.

UV254 and UV-Vis (ultraviolet and visible
light wavelength) sensors have been
examined as possible replacements for TOC
analyzers in water security applications. One
study showed that UV based sensors
detected five out of sixteen contaminants
(inorganic, culture media, organics), while
traditional online TOC analyzers detected
ten out of sixteen [16]. Fewer contaminants
are detected since some organic compounds
do not have an absorption peak at 254 nm or
in the UV-Vis range. However, sensors
based on light absorption are simpler in
design and have significantly lower
maintenance costs than online TOC
analyzers.

In this study, UV254 and TOC analyzers both
detected Basagran herbicide, pepsin,
dispersant and antifreeze. UV254 sensors
detected bleach because its components
have absorption wavelengths, but it is
inorganic so it is not detectable with TOC
sensors. Airplane de-icer fluid (ADF) was
detected using the TOC parameter since it
has a large organic concentration.  However,
like antifreeze, a significant component of
ADF is ethylene or propylene glycols, which
do not have absorption peaks at 254 nm.
Interestingly,  the Real UVT, Hach UVAS
and ZAPS-UVA channel sensors detected E.
coli with 9 mg/L sodium thiosulfate present.
It has been previously shown that UV-Vis
and UV254 sensors do not detect E. coli at
                                           12

-------
103-104 cfu/ml or the associated growth
media, so sodium thiosulfate was being
detected [3,4].  However, E. coll will
survive in disinfected tap water if the water
is dechlorinated, and a common, effective
dechlorinating agent is sodium thiosulfate.
So, sensors based on light absorption may be
an effective way to detect biological
contamination that includes sodium
thiosulfate, which is not the case for
traditional online TOC analyzers.

Fluorometric Sensor Detection
Fluorescence was evaluated as a
contaminant detection tool by using the
Turner fluorometer and the ZAPS unit
(tryptophan channel) in DSS contamination
experiments.  The Turner and ZAPS sensors
were calibrated to detect fluorescence
excitation emission wavelengths for fuel oil
#2 and tryptophan, respectively.  This is
important to consider since neither of these
units was calibrated to detect specific
contaminants used in this study. In practice,
calibrating a fluorometric (or UV-Vis)
sensor to a specific contaminant may not be
useful since there are numerous
contaminants that could be introduced into a
drinking water system and contaminant
specific excitation and fluorescence
wavelength may vary. The standard
fluorescence setup/configuration as provided
by the vendor was used during testing.

Compared to TOC, free chlorine and UV254
sensors, the fluorometric sensors detected
fewer contaminants.  This is somewhat
expected as only a subset of the
contaminants will fluoresce. However,
fluorescence measurement is more specific
than a simple absorption measurement,
which can reduce signal-to-noise ratios.
Dispersant, E. coli with thiosulfate, and
thiosulfate alone were detected by both
sensors at the same concentrations.
Basagran herbicide was detected by the
Turner fluorometer, but the ZAPS
instrument was not available for testing
during these injections. The ZAPS unit
detected diesel fuel and pepsin through the
channel selected to detect the fluorescence
from tryptophan.  The ZAPS unit was not
optimized for these contaminants, but the
fluorescence response in the tryptophan
channel was large enough to detect them.

Fluorescence has been used as a detection
method for microbiological agents such as
E. coli and Bacillus spores in previous
research studies [17-19]. These  studies were
laboratory and field based experiments that
used microbial concentrations that ranged
                                           13

-------
from 107-109 cfu/ml. This concentration
range is likely higher than what would be
experienced in a microbial contamination
event in a drinking water system, which
precludes the direct detection of these
microorganisms. More advanced sensor-
based technology needs to be developed that
could detect contaminants as well as the
various concentration levels of the microbial
agents [20]. As noted, if thiosulfate were in
a preparation of microbiological agents used
for intention injection, the preparation could
be detected because thiosulfate has UV
absorption and fluorescence emission
signals, which could be detected by
fluorescence and UV based detectors.

A limited number of contaminants were
detected via fluorescence in either the ZAPS
or Turner units.  The ZAPS device has
numerous "channels" utilizing UV-Vis
absorption, fluorescence and reflectance that
can be used for detection. If multiple
channels are used for contamination
detection simultaneously, the number of
detectable contaminants increases. Thus, if a
UV254 and carbon indicator channel had
been included in these tests, all of the
contaminants might have been detected
except for de-icer. According to the
manufacturer, the ZAPS unit has been used
to detect deicing fluid at airports [21]. The
concentration was likely too low for
detection in drinking water in the
experiments described in this report,
although variations in de-icing fluid
composition, particularly the presence of
dyes, may have influenced the results, too.

An alternative to utilizing multiple detection
channels with different detection principles
is utilizing more fluorescence emission
wavelengths (note the Turner unit only
utilizes one). Currently, the monitoring of
specific excitation and emission
wavelengths are the basis of detecting
contamination using fluorescence-based
sensor.  Simultaneous detection with
multiple absorption wavelengths in a UV-
Vis sensor may also be beneficial.  Further
adoption of fluorescence based sensors for
water security applications could require
employing a single or several discrete
wavelengths that are useful for detection and
using inexpensive light emitting diodes
(LED) as excitation source(s). Future
research could include determining the key
fluorescence emission wavelengths for
priority contaminants, then assessing
whether a manageable number of
wavelengths could be used to detect a wide
range of contaminants.
                                            14

-------
Costs
Capital and maintenance costs for online
TOC, free chlorine, pH, ORP, conductivity
and turbidity detectors are well documented
[5]. The Real UVT sensor "as tested"
capital cost was $7,000 and the Hach UVAS
sensor was $15,000. Little maintenance is
needed for either sensor and would likely
not exceed $200/yr, which would include
labor and disposable items such as new
tubing.  The ZAPS unit was leased for one
month during this testing for $3,000. The
ZAPS capital cost was quoted at $60,000.
No maintenance was performed on this unit
during that time period. The Turner device
cost $12,000 and maintenance is estimated
to be $200/yr based on labor costs and
replacement of disposable items such as
tubing.
                                          15

-------
Conclusions

As seen in past studies, free chlorine and
TOC sensors responded to the widest range
of contaminants compared to other online
water quality sensors.  UV254 instruments
responded to many of the contaminants
detected by traditional online TOC. Sodium
thiosulfate as part of the biological
suspension was detected by the UV254
sensors, but not by online TOC sensors,
although the response is related to
thiosulfate itself.  The low capital and
maintenance costs of UV254 sensors coupled
with their contaminant detection ability may
increase their potential for long-term
deployment in the field.

In general, the tested fluorometers alone
were not as effective at detecting
contaminant injections as traditional water
quality sensors such as free  chlorine and
TOC sensors, mainly due to the need to
optimize the fluorometer settings to the
contaminant of interest.  There were several
positive outcomes from this study. First, the
ZAPS unit that employed multiple detection
principles and absorption/fluorescence
wavelengths detected eight out of nine
contaminants. Using only a single
wavelength, the Turner device was limited
to detecting eight out often contaminants
that fluoresce similarly to fuel oil #2, which
is what the unit was designed to detect.
Future fluorescence and absorption-based
detection research in water could focus on
lower ranges of wavelengths capable of
being produced by LEDs (i.e., capable of
emitting between 200 and 400 nm) and/or
several key excitation and emission
wavelengths that can detect a wide range of
contaminants. Developing lower capital cost
LED fluorometer and/or UV-Vis  absorption-
based optical devices with several robust
wavelengths would enhance the contaminant
detection capability of online TOC and free
chlorine sensors.
                                           16

-------
References
       USE PA, Water Security Research and
       Technical Support Action Plan, Progress
       Report for 2005, EPA/600/R-05/104,
       USEPA, Editor 2005: U.S. EPA:
       Cincinnati, OH.
       Szabo, J.G., J. Hall, and G. Meiners,
       Sensor Response to Contamination in
       Chloraminated Drinking Water. Journal
       of the American Water Works
       Association, 2008. 100(4): p. 33-40.
       Szabo, J.G., J.S.  Hall, and G.C. Meiners.
       Detection of biological suspensions
       using on-line detectors in a model
       drinking water distribution system
       simulator. \r\AWWA Water Security
       Congress. 2008. Cincinnati, OH: AWWA.
       USEPA, Detection of biological
       suspensions using on-line detectors in a
       drinking water distribution system
       simulator, EPA/600/R-10/005, 2010:
       U.S. EPA: Cincinnati, OH.
       Hall, J.S., et al.,  Distribution System
       Water Quality Monitoring: Sensor
       Technology Evaluation Methodology
       and Results, EPA/600/R-09/076, 2009:
       U.S. EPA: Cincinnati, OH
       Yang, Y.J., et al., Modeling and testing
       of reactive contaminant transport in
       drinking water pipes: Chlorine response
       and implications for online contaminant
       detection. Water Research, 2008. 42(6-
       7): p.  1397-1412.
       Eaton, A.D.,  et al., eds. Standard
       methods for the examination of water
       and wastewater. 21st ed., ed. A.W.W.A.
       American Public Health Association,
       Water Environment Federation. 2005:
       Washington, DC.
       USEPA, Methods for Chemical Analysis
       of Water and Wastes, Revised, EPA-
       600/4-79-020, 1983: U.S.EPA:
       Washington, DC.
       USEPA, Method334.0: Determination of
       Residual Chlorine in Drinking Water
       Using and On-line Chlorine Analyzer,
       EPA/815/B-09/013, 2009: U.S. EPA:
       Washington, DC
10.     USEPA, Determination of Total Organic
       Carbon and Specific UVAbsorbance at
       254 nm in Source Water and Drinking
       Water, EPA/600/R-09/122, 2009: U.S.
       EPA: Washington, DC.
11.     USEPA, Detection of radioisotope
       contamination in drinking water,
       EPA/600/R-11/005, 2011: U.S. EPA:
       Cincinnati, OH.
12.     Shaw Environmental, I., Evaluation of
       Water Quality Sensors as Devices to
       Warn of Intentional Contamination in
       Water Distribution Systems, EPA/600/R-
       05/10, 2005: U.S. EPA: Cincinnati, OH.
13.     Szabo, J.G., J.S. Hall, and G.C. Meiners,
       Water Quality Sensor Responses to
       Contamination in a Single Pass Water
       Distribution System Simulator,
       EPA/600/R-07/001, 2007: U.S. EPA:
       Cincinnati, OH.
14.     USEPA, WaterSentinel Online Water
       Quality Monitoring as an Indicator of
       Drinking Water Contamination, EPA
       817-D-05-002, 2005: U.S. EPA:
       Washington, D.C.
15.     Prestone,  Products Corporation
       Material Safety Data Sheet (MSDS)for
       Prestone Antifreeze/Coolant, Prestone
       Products Corporation.
16.     Allgeier, S.C., et al. Selection of water
       quality sensors for a drinking water
       contamination warning system, in
       AWWA Water Quality Technology
       Conference. 2010. Savannah, GA:
       AWWA.
17.     Anderson, J., et al., In-situ detection of
       the pathogen indicator E. coli using
       active laser-induced fluorescence
       imaging and defined substrate
       conversion. Journal of Fluorescence,
       2002. 12(1): p. 51-55.
18.     Smith, C.B., et al., Stability of green
       fluorescent protein using luminescence
       spectroscopy: is GFP applicable to field
       analysis of contaminants?
                                              17

-------
       Environmental Pollution, 2002. 120: p.
       517-520.
19.    Smith, C.B., J.E. Anderson, and S.R.
       Webb, Detection of Bacillus endospores
       using total luminescence spectroscopy.
       Spectrochimica Acta Part A, 2004. 60: p.
       2517-2521.
20.    Anderson, M.J., et al., Rapid detection
       of Escherichia coli O157:H7 using
       competitive exchange of fluorescent
       surrogate modified surfaces in liquid
       media. Sensors and Transducers
       Journal, 2012.  137(2): p. 254-262.
21.    Klinkhammer, G., Analysis of EPA's
       LiqulD™ Test Results, 2011, ZAPS
       Technologies.
                                              18

-------
Table 2. Contamination Detection Results (DET = detect; nd = no detect)
Parameter/Instrument/Units of Measurement
Contaminant
Antifreeze
Bleach
De-icer
Diesel Fuel
Dispersant
£ co// with thiosulfate
(9 mg/L)
Sodium Thiosulfate
Ethylene Glycol
Pepsin
b
Basagran®
Concentration .

mg/L
1
10
5
1
10
1
5
1
10
1150 (cfu/ml)
11500 (cfu/ml)
9
1
10
1
10
1
10
Free
Chlorine
CLIO
mg/L
nd
nd
DET
nd
nd
nd
nd
DET
DET
DET
DET
DET
nd
nd
DET
DET
DET
DET
Free
Chlorine
CL17
mg/L
nd
nd
DET
nd
nd
nd
nd
DET
DET
DET
DET
DET
nd
nd
DET
DET
nd
nd
Specific
Conductivity
YSI
US/cm
nd
nd
DET
nd
nd
nd
nd
nd
nd
nd
nd
DET
nd
nd
nd
nd
nd
nd
Fluorimeter
Turner
mg/L
nd
nd
nd
nd
nd
nd
nd
nd
DET
DET
DET
DET
nd
nd
nd
nd
DET
DET
ORP
YSI
mV
nd
nd
nd
nd
nd
nd
nd
nd
nd
DET
DET
DET
nd
nd
nd
nd
nd
nd
PH
YSI
PH
nd
nd
DET
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
TOC
Sievers
mg/L
DET
DET
nd
DET
DET
n/a
n/a
DET
DET
nd
nd
nd
DET
DET
DET
DET
DET
DET
TOC
Astro
mg/L
DET
DET
nd
DET
DET
n/a
n/a
DET
DET
nd
nd
nd
DET
DET
DET
DET
nd
DET
Turbidity
YSI
mNTU
nd
nd
nd
nd
DET
DET
DET
DET
DET
nd
nd
nd
nd
nd
DET
DET
nd
nd
Absorbance
RealUVT
m1
nd
DET
DET
nd
nd
nd
nd
DET
DET
DET
DET
DET
nd
nd
DET
DET
DET
DET
UVAS
Hach
m1
nd
DET
DET
nd
nd
nd
nd
DET
DET
DET
DET
DET
nd
nd
DET
DET
DET
DET
Carbon
Indicators
ZAPS
counts
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
DET
DET
nd
nd
n/a
n/a
Tryptophan
ZAPS
mg/L
nd
nd
nd
nd
nd
nd
DET
nd
DET
DET
DET
DET
nd
nd
nd
DET
n/a
n/a
UVA
ZAPS
m1
nd
DET
DET
nd
nd
nd
nd
nd
DET
DET
DET
DET
nd
nd
nd
DET
n/a
n/a
Acronyms: DET, detect; n/a, not available; nd, no detect; ORP, oxidation-reduction potential; TOC, total organic carbon; UVAS,
a, surrogate for ricin; b, surrogate for #2 fuel oil
                                                                              19

-------
Appendix 1
                                             Table Al: Detection Thresholds
Threshold
Criteria
Absolute
Change
Percent
Change
Signal to
Noise
Free
Chlorine
(CLIO)
(mg/L)
0.1
5%
5
Free
Chlorine
(CL17)
(mg/L)
0.1
5%
5
Specific
Conductivity
(US/cm)
5
2%
5
Turner
Fluorimeter
(mg/L)
0.05
10%
4
ORP
(mV)
5
4%
10
PH
0.1
1%
10
TOC
(Sievers)
(mg/L)
0.1
10%
10
TOC
(Astro)
(mg/L)
0.1
10%
10
Turbidity
(mNTU)
1
10%
10
Absorbance
(RealUVT)
(m1)
0.005
8%
10
Hach UVAS
(m1)
0.005
10%
5
ZAPS
Carbon
Indicator
(counts)
0.1
2%
2
ZAPS
Tryptophan
(mg/L)
3
N/A
N/A
ZAPS
UVA
(m1)
0.005
10%
4
                                                          20

-------
Table A2: Absolute Change Results
Contaminant
Antifreeze
Bleach
De-icer
Diesel Fuel
Dispersant
£ co// with
thiosulfate
Sodium
Thiosulfate
Ethylene Glycol
Pepsin
Basagran
Concentration
(mg/L)
1
10
5
1
10
1
5
1
10
1150
(cfu/ml)
11500
(cfu/ml)
9
1
10
1
10
1
10
Free
Chlorine
(CLIO)
(mg/L)
0.04
0.08
3.06
0.01
0.01
0.01
0.01
0.16
0.90
1.12
1.21
1.05
0.00
0.01
0.17
1.02
0.13
0.65
Free
Chlorine
(CL17)
(mg/L)
0.00
0.05
3.64
0.01
0.01
0.01
0.00
0.12
0.91
1.06
1.14
1.00
0.00
0.02
0.14
1.10
0.02
0.03
Specific
Conductivity
(uS/cm)
0.47
2.26
30.29
1.27
0.78
0.50
0.07
0.34
0.00
5.21
3.10
7.09
0.22
0.67
0.81
1.57
0.15
2.70
Hydrocarbon
(Turner
Fluorimeter)
(mg/L)
0.04
0.04
0.06
0.04
0.04
0.04
0.07
0.04
0.20
0.10
0.11
0.09
0.04
0.03
0.04
0.06
0.74
7.85
Oxidation
Reduction
Potential
(mV)
0.29
1.00
21.12
0.78
0.38
0.11
0.58
3.37
7.82
67.00
49.23
32.68
0.60
0.27
1.07
9.95
0.50
0.63
PH
0.01
0.02
0.16
0.02
0.01
0.02
0.02
0.01
0.04
0.09
0.09
0.06
0.01
0.01
0.03
0.06
0.00
0.00
TOC
(Sievers)
(mg/L)
0.72
7.31
0.00
0.77
7.62
N/A
N/A
0.61
6.29
0.05
0.04
0.05
0.74
7.26
0.38
3.83
0.41
4.93
TOC
(Astro)
(mg/L)
0.59
7.42
0.05
0.76
7.51
N/A
N/A
0.58
5.42
0.04
0.04
0.11
0.74
7.25
0.31
3.46
0.44
4.34
Turbidity
(mNTU)
1.15
2.22
1.53
0.87
19.03
14.00
38.24
49.26
438.36
0.62
0.58
0.77
0.80
2.13
8.74
49.13
1.12
1.32
Absorbance
(RealUVT)
(m1)
0.02
0.14
0.26
0.01
0.04
0.03
0.05
0.08
0.89
0.83
0.82
0.81
0.00
0.00
0.12
1.00
2.22
3.23
Hach UVAS
(m1)
0.03
0.11
0.23
0.03
0.06
0.03
0.03
0.14
1.65
1.19
1.22
1.21
0.02
0.02
0.14
1.06
2.27
21.64
ZAPS
Carbon
Indicator
(counts)
0.76
0.09
14.45
0.17
1.01
0.63
0.15
0.36
0.77
0.45
1.02
0.72
1.81
1.45
0.10
0.43
N/A
N/A
ZAPS
Tryptophan
(mg/L)
0.00
0.00
0.82
0.00
0.00
0.87
3.31
2.29
50.42
17.74
16.01
14.14
0.00
0.00
0.00
19.57
N/A
N/A
ZAPS
UVA
(m1)
0.00
0.20
0.66
0.30
0.31
0.07
0.04
0.13
0.49
0.33
0.22
0.29
0.51
0.07
0.24
0.76
N/A
N/A
               21

-------
Table A3: Percent Change Results
Contaminant
Antifreeze
Bleach
De-icer
Diesel Fuel
Dispersant
£ co// with
thiosulfate
Sodium
Thiosulfate
Ethylene
Glycol
Pepsin
Basagran
Concentration
(mg/L)
1
10
5
1
10
1
5
1
10
1150
(cfu/ml)
11500
(cfu/ml)
9
1
10
1
10
1
10
Free
Chlorine
(CLIO)
(mg/L)
4.4%
8.5%
282.5%
1.6%
1.0%
0.6%
0.7%
16.8%
100.0%
100.0%
100.0%
99.5%
0.5%
0.9%
17.0%
100.0%
11.3%
57.4%
Free
Chlorine
(CL17)
(mg/L)
0.3%
4.7%
334.8%
1.5%
1.5%
1.0%
0.1%
11.2%
87.5%
99.1%
99.1%
98.0%
0.3%
1.4%
12.9%
94.8%
1.3%
2.6%
Specific
Conductivity
(uS/cm)
0.2%
0.8%
9.7%
0.5%
0.3%
0.2%
0.0%
0.1%
0.0%
1.8%
1.1%
2.6%
0.1%
0.2%
0.3%
0.6%
0.0%
0.7%
Hydrocarbon
(Turner
Fluorimeter)
(mg/L)
34.6%
29.7%
72.3%
25.4%
33.7%
31.0%
49.7%
28.7%
150.1%
81.1%
80.0%
58.2%
52.2%
43.9%
46.8%
57.2%
421.6%
4329.5%
Oxidation
Reduction
Potential
(mV)
0.0%
0.1%
2.8%
0.1%
0.1%
0.0%
0.1%
0.5%
1.1%
9.4%
7.5%
4.7%
0.1%
0.0%
0.2%
1.4%
0.1%
0.1%
PH
0.1%
0.2%
1.9%
0.3%
0.1%
0.2%
0.2%
0.1%
0.5%
1.1%
1.0%
0.7%
0.1%
0.1%
0.4%
0.7%
0.0%
0.0%
TOC
(Sievers)
(mg/L)
98.2%
1068.7%
0.6%
103.2%
1008.5%
N/A
N/A
84.4%
840.8%
5.6%
4.3%
6.6%
100.8%
1014.1%
48.4%
496.0%
57.5%
669.2%
TOC
(Astro)
(mg/L)
82.6%
1221.0%
0.6%
102.2%
1076.7%
N/A
N/A
75.8%
720.1%
3.7%
3.8%
15.3%
75.6%
838.3%
35.5%
388.3%
73.2%
789.7%
Turbidity
(mNTU)
5.8%
9.0%
6.6%
3.9%
90.8%
66.7%
184.1%
237.4%
2122.2%
2.4%
2.5%
3.8%
3.5%
8.8%
36.0%
198.4%
4.5%
5.3%
Absorbance
(RealUVT)
(m1)
1.8%
16.1%
28.3%
0.6%
3.9%
3.1%
5.8%
8.8%
104.8%
84.4%
83.5%
93.5%
0.4%
0.6%
13.7%
110.8%
289.9%
422.6%
Hach
UVAS
(m1)
4.3%
16.3%
29.1%
4.1%
8.2%
4.8%
3.9%
18.3%
220.2%
139.8%
141.9%
168.4%
2.3%
3.5%
19.0%
142.7%
143.8%
1425.2
ZAPS
Carbon
Indicator
(counts)
1.38%
0.16%
24.19%
0.30%
1.82%
1.12%
0.26%
0.64%
1.37%
0.91%
2.03%
1.25%
3.18%
2.48%
0.18%
0.75%
N/A
N/A
ZAPS
Tryptophan
(mg/L)
0.00%
0.00%
#DIV/0!
0.00%
0.00%
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
546.68%
0.00%
0.00%
#DIV/0!
#DIV/0!
N/A
N/A
ZAPS
UVA
(m1)
0.11%
40.05%
1259.21
13.63%
8.61%
2.67%
1.33%
9.71%
31.64%
20.90%
18.46%
17.94%
11.36%
1.17%
11.68%
91.33%
N/A
N/A
              22

-------
Table A4: Signal to Noise Results
Contaminant
Antifreeze
Bleach
De-icer
Diesel Fuel
Dispersant
£ co// with
thiosulfate
Sodium
Thiosulfate
Ethylene
Glycol
Pepsin
Basagran
Concentration
(mg/L)
1
10
5
1
10
1
5
1
10
1150 (cfu/ml)
11500 (cfu/ml)
9
1
10
1
10
1
10
Free
Chlorine
(CLIO)
(mg/L)
8.7
9.2
337.4
1.5
0.6
0.7
0.8
34.5
148.0
227.2
181.0
128.5
0.5
1.0
17.7
72.9
23.1
134.2
Free
Chlorine
(CL17)
(mg/L)
0.0
2.6
733.6
2.4
1.6
1.4
0.3
40.8
317.8
75.7
52.0
111.7
0.6
1.9
35.3
180.8
3.6
6.3
Specific
Conductivity
(uS/cm)
0.8
2.9
64.7
1.7
1.9
2.0
0.4
0.7
0.0
11.3
5.7
18.5
0.5
1.0
1.2
2.7
0.4
6.3
Hydrocarbon
(Turner
Fluorimeter)
(mg/L)
2.3
1.9
2.7
2.0
2.2
2.1
3.3
1.7
9.3
6.2
4.4
4.6
1.9
1.5
2.3
3.2
29.7
415.9
Oxidation
Reduction
Potential
(mV)
0.4
1.2
5.7
2.5
0.8
0.2
0.8
6.7
10.5
60.3
27.6
59.9
0.8
0.6
1.2
18.4
1.0
0.4
PH
1.6
1.7
22.5
2.4
1.4
2.3
2.1
0.8
7.3
7.1
6.5
10.5
1.0
1.1
3.4
6.2
0.4
0.5
TOC
(Sievers)
(mg/L)
158.0
1039.2
1.8
355.0
2956.8
N/A
N/A
50.2
1176.4
8.3
14.3
9.6
576.6
4389.0
88.1
2208.6
74.8
915.0
TOC
(Astro)
(mg/L)
11.1
66.6
0.9
28.5
276.4
N/A
N/A
26.5
521.6
1.8
3.6
2.4
31.8
321.9
26.3
143.5
7.0
77.5
Turbidity
(mNTU)
2.6
1.8
1.9
0.8
29.3
54.1
92.3
95.9
730.8
0.6
1.0
1.6
1.7
3.8
22.5
125.6
2.7
2.6
Absorbance
(RealUVT)
(m1)
7.34
20.29
132.04
3.03
8.84
17.58
25.11
23.18
498.21
362.90
329.24
372.35
1.54
2.37
74.38
192.19
1029.6
1561.4
Hach UVAS
(m1)
2.2
8.0
17.6
2.1
4.5
2.1
1.9
8.6
55.3
84.2
63.9
73.4
1.0
1.7
6.7
55.7
143.9
1342.1
ZAPS
Carbon
Indicator
(counts)
1.7
0.2
1.5
0.4
2.0
1.2
0.4
0.8
2.4
1.1
1.9
1.9
3.4
3.8
0.3
1.0
N/A
N/A
ZAPS
Tryptophan
(mg/L)
0.0
0.0
#DIV/0!
0.0
0.0
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
#DIV/0!
23.0
0.0
0.0
#DIV/0!
#DIV/0!
N/A
N/A
ZAPS
UVA
(m1)
0.1
4.0
6.4
3.0
3.4
2.4
1.1
3.2
16.0
9.3
6.5
6.8
2.6
0.7
3.3
6.5
N/A
N/A
              23

-------
United States
Environmental Protection
Agency
PRESORTED STANDARD
 POSTAGE & FEES PAID
         EPA
   PERMIT NO. G-35
Office of Research and Development (8101R)
Washington, DC 20460

Official Business
Penalty for Private Use
$300

-------