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Influence of selected variables on trihalomethane
removals by spray aeration
AIDAN R. CECCHETTI,1 HARRISON ROAKES,2 AND M. ROBIN COLLINS2
1University
2University
of California, Berkeley, Calif.
of New Hampshire, Durham, N.H.
The widespread use of chlorine and the reluctance of drinking
water providers to alter their disinfection systems have sparked
increased investigation into posttreatment removal of trihalomethanes (THMs). One posttreatment method is spray aeration,
in which water is sprayed through showerheads in storage tanks.
In this research the influence of various parameters on THM
removals was evaluated using a mass balance–based model and
sensitivity analysis. THM formation and the configuration (droplet
size, travel distance, and spray pattern) and magnitude (percent
recycle) of the sprayed water flow were determined to be the most
influential parameters, whereas temperature, spray angle for
uniform cone flow distribution, and THM species were the least
influential factors. Practitioners should find these results helpful in
determining the most important design parameters for spray
aeration systems. In addition, the study elucidates the advantages
of spray aeration in removing brominated THM species.
Keywords: modeling, sensitivity analysis, spray aeration, trihalomethanes, volatile organic compounds
Trihalomethanes (THMs) are among the most commonly
formed and studied disinfection by-products (DBPs) in drinking
water treatment. Currently, the US Environmental Protection
Agency (USEPA) regulates four species of THMs: chloroform
(CHCl3), bromodichloromethane (CHBrCl2), dibromochloromethane (CHBr2Cl), and bromoform (CHBr3). The four regulated species of THMs typically are present in the ~ 10- to
100-µg/L range in drinking water and form a significant majority of total THMs (TTHMs). Other THM species rarely occur
at levels higher than the levels of the regulated THM species
(Richardson et al, 2007).
The USEPA regulates THMs because of concerns about their
potentially negative health effects. It has been shown that consumption of drinking water containing high concentrations of
THMs may lead to liver, kidney, and central nervous system
problems (USEPA, 2012). Furthermore, CHCl3 is listed as a
Class 2B possible human carcinogen (IARC, 2013), and TTHMs
have been linked to an increased risk of cancer in mammalian
assays (Richardson et al, 2007; Ge et al, 2001; Pereira et al,
2001; Coffin et al, 2000).
CHCl3 was the first DBP to be identified in the 1970s and the
first to be regulated. In the past, water utilities were required to
meet the maximum contaminant level (MCL) for THMs as an
average over all sampling points throughout their distribution
systems. In 2006, however, the USEPA issued expanded regulations—the Stage 2 Disinfectants/Disinfection Byproducts Rule—
that require water utilities to analyze the levels of DBPs on a
“local running average” (USEPA, 2006). Under these new rules,
utilities must achieve compliance with the MCL at every sampling
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point (USEPA, 2012) because additional THM formation within
the distribution system may lead to high concentrations at the far
reaches of the system. The current regulations are spurring drinking water utilities to look for options to reduce THMs throughout
their distribution systems.
BACKGROUND
Management of THMs. There are three general approaches to
decreasing THM concentrations in drinking water systems.
• Reduce the amount of organic precursors and natural organic
matter (NOM) in drinking water before disinfection is undertaken.
• Reduce the amount of chlorine (Cl2) used, which can be
achieved either by lowering the chlorination dose or by modifying
disinfection systems at the treatment plant.
• Reduce the amount of THMs in drinking water after they
have been formed, either before distribution or throughout the
distribution system.
For various reasons, posttreatment reduction of THMs has the
greatest potential to reduce THM concentrations at the lowest
cost and with the least intensive renovations. The primary reason,
however, is that with posttreatment reduction of THMs, only a
small fraction of the water supply needs to be treated at the most
problematic locations. Typically, additional reductions in NOM
concentrations at water treatment plants can be difficult to
achieve and are both costly and energy-intensive. Modified disinfection schemes can also be difficult to achieve and maintain.
Additionally, alternative disinfection systems may produce other
potentially harmful DBPs that haven’t been as widely studied as
those produced by chlorination.
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Dimensionless Henry’s law constants (at 20oC) for the THM
species of interest are 0.0126 for CHCl3, 0.076 for CHBrCl2, 0.035
for CHBr2Cl, and 0.018 for CHBr3 (Staudinger & Roberts, 2001).
It can reasonably be assumed that other volatile organic compounds (VOCs) with similar Henry’s law constants can also be
removed by the posttreatment method(s) discussed in this article.
Posttreatment removal of THMs. Because of their relative simplicity and effectiveness, aeration treatment systems are widely used
for VOC removal. Recent research has focused mainly on the
potential to remove THMs after formation, especially in small
systems (Brooke & Collins, 2011). Posttreatment THM removal
can be highly flexible and has the potential to significantly
decrease expenses incurred by conforming to the new DBP rules.
The primary methods currently being investigated include various
forms of aeration, such as surface aeration, vacuum membrane
systems, spray aeration, and diffused aeration.
Spray aeration systems comprise numerous droplet air–water
contactors, which enhance removal of VOCs by spraying small
droplets of water through the air to achieve rapid mass transfer.
VOCs are transferred to the atmosphere because of the droplets’
high ratio of surface area to volume, which increases contact
between the water interface and the air. Although many other
types of aeration and air-stripping systems are available—such
as packed towers, tray aerators, and cascade aerators (LaBranche
& Collins, 1996)—spray aeration has been investigated as a
prospective mechanism for THM removal because of the potential for installation in existing water storage tanks (Brooke &
Collins, 2011) and is the focus of the current discussion.
Modeling THM removal by spray aeration systems. In this study,
a model for THM removal using spray aeration was developed
to investigate the most influential factors and design variables on
THM removal via a sensitivity analysis. The model combines
mass balance principles and empirical relationships to estimate
removals in drinking water treatment tanks by spray aeration
systems. The model also requires the input of various physical
and water quality parameters related to the specific storage tank
system being modeled. It is essential to draw a distinction between
two types of parameters within the model: water quality parameters, over which operators have little control (although some of
these parameters can be partially controlled by altering previous
water treatment processes), and operational parameters, which
can be controlled through design and operation of spray aeration
systems. Table 1 lists selected water quality and operational
parameters used in the spray aeration model.
MODEL DEVELOPMENT FOR THM REMOVAL BY SPRAY
AERATION
Study objectives. The objectives of the current study were to
evaluate the relative influence of various water quality and
operation design variables on THM removals by storage tank
spray aeration systems. The model used in this study was developed as a tool to assist drinking water utilities in investigating
the potential efficacy of spray aeration systems in reducing
THM levels in drinking water storage tanks. Using this model,
researchers and drinking water providers can obtain specific
information regarding proposed spray aeration systems, such
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TABLE 1
Water quality parameters versus operational parameters
used in the spray aeration model
Water Quality Parameters
Operational Parameters
Temperature
Angle of spray
THM speciation
Spray pattern
THMFP
Water droplet diameter
THM formation rate
Height of spray nozzle
Amount of recycle flow
Recycle withdrawal location
Percent turnover
THM—trihalomethane, THMFP—trihalomethane formation potential
as whether such systems would be feasible from a technical
standpoint or how a system would best be configured to achieve
the required THM removals.
Spray aeration is a form of air-stripping and as such is governed
by the principles of mass transfer and Henry’s law. Spray aeration
systems can be effective in removing the regulated THM species
because of the Henry’s law constants of THMs. However, while
Henry’s law provides the theoretical basis for THM removal, the
model was developed from empirically derived equations based
on temperature and selected operational variables (primarily
water droplet size and travel distance), which were discussed in
a previous study (Brooke & Collins, 2011). The following sections discuss the mass balance basis of the model, predictions of
THM removals and their basis, and various other procedures that
were required to develop the model.
Mass balance basis of the model. As stated previously, the model
was developed primarily based on mass balance principles. A simple
mass balance was developed for a drinking water storage tank, in
which it was important to account for and quantify all mass fluxes
entering and leaving the tank. Figure 1 shows the general schematic
of flows entering and leaving a generic water storage tank. From
the figure, a mass balance—as stated in words in Eq 1 and expressed
numerically in Eq 2—was developed to represent the overall mass
balance. The terms on the left side of Eqs 1 and 2 represent the sum
of all inflows and THMs formed within the tank, with outflows
subtracted from that sum. The sum of these values is equated with
the change in the amount of TTHMs present in the tank, which is
represented by the right side of the equations:
Influent + Treated Recycle – Effluent – Recycle
+ THMs Formed in Tank = ΔTHMs
(1)
V
V
QiCi + QRCe – QeCe – QRCe + THMFP (e–kt – e–kt0)  = Ce  (2)
t
t
in which Qi is the influent water flow (L/h), Ci is the concentration of TTHMs in the influent flow (μg/L), Qe is the effluent
water flow (L/h), Ce is the concentration of TTHMs in the storage
tank and effluent (μg/L), QR is the recycled water flow through
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FIGURE 1
Mass balance diagram of a spray aeration system
QR, C'e
the concentration of THMs present in the storage tank headspace
would not significantly decrease the mass flux rate of THMs from
the water to the air.
Furthermore, under the assumption that the formation of THMs
generally follows a first-order reaction after an initial incubation
period (which accounts for the more rapid THM formation after Cl2
is initially added), the THMFP term was simplified to a TTHMformed
term (described further in subsequent sections). The rearranged
model for predicting Ct is shown in Eq 3:
Ct =
(3)
tQeC0 + tQRC0 – 2TTHMformed – 2tQiCi – 2C0V0 – tQRC0%R

tQR%R – tQe – tQR – 2Vt
Qi, Ci
Qe, Ce
Adapted from Brooke & Collins, 2011
Ce—concentration of TTHMs in the storage tank and effluent,
C'e—concentration of TTHMs after the spray aeration system,
Ci—concentration of TTHMs in the influent flow, Qe—effluent water
flow, Qi—influent water flow, QR—recycled water flow through the
spray aeration system, TTHMs—total trihalomethanes
the spray aeration system (L/h), Ce is the concentration of
TTHMs after the spray aeration system (μg/L), THMFP is the
THM formation potential (μg/L), V is the volume of water in the
storage tank (L), t is time (h), and k is the first-order THM formation constant (d–1).
As with any model, various simplifying assumptions were made
in order to ensure the usability of the model. These assumptions
included the following.
• The tank was assumed to be a perfect continuously stirred
tank reactor, and as such, any storage tank system would require
thorough mixing to replicate model predictions.
• The model was iterated in 1-h time steps (although time steps
of any length can be used), and variables were assumed to remain
constant over each time step.
• The concentration in the tank, Ce, for a given time step was
assumed to be equal to the average of the concentration at the
beginning of any given time step, C0, and the concentration at the
end of the time step, Ct.
• It was assumed that V0 is the tank volume at the beginning
of the time step and Vt is the volume of the tank at the end of the
individual time step.
• The concentration of THMs in the return flow, Ce, was
assumed to be simply the concentration in the tank, Ce, multiplied
by the percent remaining following treatment (%R).
• The headspace in each system was assumed to be adequately
ventilated to maintain the driving force. Thus it was assumed that
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Using the model shown in Eq 3 requires a few basic pieces of
information regarding the system being modeled. First the influent and effluent flow regimes must be known. Certain systems,
particularly those with only one pipe accessing the storage tank,
function on alternating “fill” and “drain” cycles, which will affect
the model calculations (i.e., during a fill cycle, the effluent flow
would be zero, whereas during drain cycles, the influent flow
would be zero). This model could be used in systems in which
reactor conditions more closely resemble a plug-flow reactor with
dispersion through modifications based on tracer analyses.
Additionally, dimensions of the tank, seasonal temperature
variations, influent TTHM concentrations, and overall THMFPs
must be determined in order for the model to be used. Spray
aeration system specifications—the Sauter mean diameter (dsmd)
of water droplets produced, the droplet travel distance, and the
FIGURE 2
THM species removal as measured and calculated by
model based on unit A/W at 22°C
CHCl3 (data)
CHCl3 (model)
CHBrCl2 (data)
CHBrCl2 (model)
CHBr2Cl (data)
CHBr2Cl (model)
CHBr3 (data)
CHBr3 (model)
100
90
80
70
Removal—%
QR, Ce
60
50
40
30
20
10
0
0
10,000
20,000
30,000
40,000
50,000
Unit A/W (dimensionless)
CHBr3—bromoform, CHBrCl2—bromodichloromethane,
CHBr2Cl—dibromochloromethane, CHCl3 chloroform,
THM—trihalomethane, unit A/W—unit volumetric air-to-water ratio
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angle of the spray cone, if known—can be used with the model
to determine the predicted removals. However, even without
certain pieces of information, the model can still be used to
evaluate the influence of the remaining spray aeration parameters.
THM removal predictions and temperature dependence. An
approach for predicting the removal efficiency of THMs in spray
aeration systems (Brooke & Collins, 2011) was used in the development of the model. Because of the relative dearth of literature
pertaining to mass transfer coefficients for spray aeration systems,
empirical constants were developed to relate percent removal of
THMs to air-to-water ratios. These were shown to be temperature-dependent and were performed at various temperatures (2,
22, and 36oC) in a previous study (Brooke & Collins, 2011). The
general relationship is linearized according to Eq 4:
%Rem = m ln (unit A/W) + b
(4)
in which %Rem is the fractional percent removal of the respective
THM species, m is the empirical slope constant (dimensionless),
unit A/W is the unit volumetric air-to-water ratio (dimensionless),
and b is the empirical intercept constant (dimensionless).
Using Eq 4, the percent remaining (%R), which is used to
determine the final concentrations of THMs (on the basis of their
initial concentrations), can be determined according to Eq 5:
%R = 1 – %Rem
(5)
Spray aeration experimental runs conducted at the University
of New Hampshire at Durham evaluated the influence that temperature, THM species, droplet diameter, droplet travel distance,
and spray angle have on THM removals. Brooke and Collins
(2011) concluded that these last three parameters—droplet diameter, droplet travel distance, and spray angle—could be reasonably
combined into a unit volumetric air-to-water ratio as an independent parameter to assess removals by each THM species and
selected temperatures. The resulting empirical THM-removal
relationships (an example of which is shown in Figure 2) can be
used to estimate the removal efficiency for various configurations
of spray aeration systems, given their unit volumetric air-to-water
ratios. These empirical relationships have been summarized as
regression equations that are listed in Table 2. In developing this
method, it was assumed that each droplet from a spray aeration
nozzle travels as a discrete sphere of water through a cylinder of
air. It was also assumed that within the model the droplets, on
average, travel at an angle halfway between the maximum spray
angle and falling vertically below the spray nozzle. With the use
of these assumptions, the unit A/W was determined according to
Eq 6 (Brooke & Collins, 2011):
eter, which is an average diameter of a droplet produced by the
spray device. The dsmd for a given spray nozzle was obtained from
the manufacturer’s specifications1 and was used as a surrogate
for water droplet diameter.
It is important to distinguish between the unit volumetric airto-water ratio, i.e., unit A/W, in Eq 6 and air-to-water ratios based
on air and water flows that are used in other aeration system
designs. Although similar in concept, these two air-to-water ratios
are not the same; the unit volumetric air-to-water ratio, unit A/W,
was developed to produce the empirical relationships among
temperature, air-to-water ratio, and removal efficiency in spray
aeration systems for modeling purposes presented elsewhere
(Brooke & Collins, 2011).
Estimation of in-tank THM formation. Various steps were taken to
account for THMs formed in drinking water storage tanks.
Theoretically, in order to find the mass of THMs formed over a
time step, TTHMformed, the volume of the tank is multiplied by
the difference between the concentration of THMs at the end of
the time step, TTHMt, and the original influent concentration,
C0. However, the concentration of THMs at the end of the time
step must be known or calculated. Thus in the model Eq 7
approximates TTHMt.
TTHMt = C0 + (THMFP – C0) (1 – e–kt)
in which C0 is the concentration of TTHMs at the beginning of the
time step (μg/L), THMFP is THM formation potential (μg/L), t is
time (h), and k is the first-order THM formation constant (d–1).
Multiplying Eq 7 by the average volume in a time step yields
Eq 8, which is used to determine the mass of THMs formed,
TTHMformed:
TTHMformed = (THMFP – C0) (1 – e–kt)Vt
TABLE 2
CHCl3
CHBrCl2
CHBr2Cl
(6)
dsmd2havg/4
1.5 h
1.5 havg
air cylinder volume
=  = 
 = 
cos (/4)dsmd
dsmd3/6
dsmd
droplet volume
in which h is the vertical height of the spray aeration device above
the water surface, havg is the average droplet travel distance,  is
the total spray angle, and dsmd is the droplet Sauter mean diamJOURNAL AWWA
(8)
Spray aeration THM specie removal model regressions
THM
Temperature
o
C
Species
CHBr3
Unit A/W =
(7)
R2
n*
2
%Rem = 12.689 ln (unit A/W) – 41.706
0.82
7
22
%Rem = 13.035 ln (unit A/W) – 38.929
0.94
7
36
%Rem = 8.459 ln (unit A/W) – 8.3222
0.85
7
2
%Rem = 16.862 ln (unit A/W) – 82.652
0.72
7
22
%Rem = 14.487 ln (unit A/W) – 53.596
0.91
7
36
%Rem = 9.7368 ln (unit A/W) – 3.5544
0.88
7
2
%Rem = 17.962 ln (unit A/W) – 97.092
0.75
7
22
%Rem = 15.111 ln (unit A/W) – 61.488
0.92
7
36
%Rem = 10.761 ln (unit A/W) – 15.55
0.84
7
Regression
2
%Rem = 17.148 ln (unit A/W) – 88.556
0.73
7
22
%Rem = 14.698 ln (unit A/W) – 56.863
0.93
7
36
%Rem = 9.9984 ln (unit A/W) – 7.6133
0.87
7
Adapted from Brooke & Collins, 2011; Brooke, 2009
CHBr3—bromoform, CHBrCl2—bromodichloromethane, CHBr2Cl—dibromochloromethane,
CHCl3—chloroform, %Rem—fractional percent removal of the respective THM species, THM—
trihalomethane, unit A/W—unit volumetric air-to-water ratio
*Number of data points used to develop the regression equation
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SENSITIVITY ANALYSIS—A CASE STUDY
TABLE 3
Model parameters evaluated with typical ranges
and values
Model Parameter
Typical Value
Typical Range
Temperature— oC
20
2–36
Angle of spray— o
60
0–180
Water droplet diameter, dsmd—μm
690
100–1,200
8
1–45
Height of spray nozzle—ft
Influent TTHM concentration—μg/L
100
80–200
THM formation rate constant—d–1
0.08
0.01–0.1
THM formation potential—μg/L
180
100–300
dsmd—Sauter mean diameter, THM—trihalomethane, TTHM—total THM
These models for THM formation were developed primarily
based on work by Nuckols et al (2001) and Amy and colleagues
(1987), who related the THMFP to various water quality parameters such as Cl2 dose, dissolved organic carbon, pH, and temperature. On the basis of their work, a good approximation of
THM formation after the initial incubation period just following
Cl2 addition in drinking water is a simple first-order relationship.
Alternatively, THM formation could be predicted using moreextensive models presented by these authors (Amy et al, 1987).
However, those models require additional inputs (such as pH, Cl2
residual, and NOM) and may be impractical compared with the
relative ease of the first-order approximation shown in Eqs 7 and
8. Because THM formation is temperature-dependent, the model
described may require adjustments in order to account for seasonal temperature changes.
Hydraulic profiles of systems modeled. In light of how THM
removals and formation are predicted within the model, it is clear
that the hydraulic (drain-and-fill cycles) and physical profiles of
spray aeration systems are important. The hydraulic profile of each
system can be determined using the physical dimensions of the
storage tank systems being modeled (i.e., the tank diameter and
height) as well as parameters that affect the height of the spray
nozzle above the water surface (i.e., the height of the spray nozzles
within the tank and the drain-and-fill cycles). These physical
parameters are essential to the THM removal model because the
drain-and-fill cycles affect the volume of water within the tank over
time and thereby the mass of THMs within the tank. For example,
as the volume of water decreases within the tank, the mass of
THMs decreases accordingly. Furthermore, lower tank volumes
typically correspond to lower THM formation.
Additionally, the lower the volume of water in the tank, the
greater the distance between the spray nozzle and the water surface. Lower volumes of water therefore correspond to greater
air-to-water ratios and consequently more-efficient THM removals. In order to model THM removals, the change in the water
height over time (and therefore the change in distance between
the spray nozzle and the water surface) can be determined simply
by dividing the flow of water (into or out of the tank) by the
surface area of the tank.
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A common approach in evaluating the effects of various parameters on the output of a model is to conduct a sensitivity analysis.
In a sensitivity analysis, parameters in a model are isolated in
order to facilitate observation of any changes in the model’s
output when a single parameter is altered. For example, a sensitivity analysis could be performed in the given model with respect
to temperature by assuming values for all other parameters and
then, while holding these assumptions constant, varying the input
value for temperature and plotting the resultant outputs against
each other. Depending on the variability of the outputs, researchers can judge the relative importance of each parameter tested
with respect to the performance of the model and subsequently
the expected efficiency of designed systems.
In the analysis performed in this research, many of the model
parameters were evaluated to determine their relative importance
to the output of the model. Table 3 lists the parameters evaluated
and the typical values and ranges observed. Additionally the
model was evaluated at different water temperatures for various
THM speciations (e.g., 100% CHCl3, 100% CHBr3) in order to
evaluate the effect of speciation on the model output.
General sensitivity analysis assumptions. In order to perform the
sensitivity analysis, it was essential to select a base set of assumptions to be used for the variables not being evaluated. Although
these parameters are site-specific when actual systems are modeled, for the purposes of this case study some basic assumptions
were made. These assumptions were primarily based on previous
TABLE 4
Assumptions used for parameters (other than the
independent variables in each parameter analysis)
Model Parameter
Influent TTHM concentration
CHCl3 concentration
Assumed Value
130 μg/L
78 μg/L (60%)
CHBrCl2 concentration
13 μg/L (10%)
CHBr2Cl concentration
26 μg/L (20%)
CHBr3 concentration
13 μg/L (10%)
Sauter mean diameter
690 μm
Spray angle
60°
Temperature
22°C
THM formation potential
180 μg/L
THM formation constant
0.08 d–1
Nozzle height above water surface
Influent flow
4.5 ft
141 gpm
Effluent flow
70.7 gpm
Recycle flow
50% of influent flow
Maximum volume of storage tank
Fill cycle duration
230,000 gal
8h
Drain cycle duration
16 h
Daily turnover
30%
Configuration of recycle flow
Continuous recycle
CHBr3—bromoform, CHBrCl2—bromodichloromethane, CHBr2Cl—dibromochloromethane,
CHCl3—chloroform, THM—trihalomethane
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FIGURE 3
but tends to increase during fill cycles (because of the higher
concentration of THMs in the influent).
Influence of input parameters. The amount of influence exerted
by each parameter on the model’s output was determined using
the figures from the sensitivity analysis. The parameters can be
broken down into three general categories: the most influential
parameters, parameters that exert some or a fair amount of influence, and parameters that exert minimal influence on the model
output. From a design perspective, such information is important
because practitioners can use these data to determine which
parameters must be most carefully specified and controlled.
Additionally a simple quantifiable measure of the variance in
outputs observed for each parameter was achieved by determining
the average percent difference between the high and low output
values. These were averaged across a full 24-h oscillation of the
model output once it had reached equilibrium. As shown in Figures 3 through 9, steady-state conditions typically were achieved
after approximately 100 h. For example, in the sensitivity analysis
Sensitivity analysis of model based on recycling
configuration
Continuous QR
Q R during Qi
QR directly from Qi
140
120
TTHMs—µg/L
100
80
60
40
20
0
0
25
50
75
100
125
150
175
Time From Initial Conditions—h
FIGURE 4
Qi—influent water flow, QR—recycled water flow through the spray
aeration system, TTHMs—total trihalomethanes
Sensitivity analysis of model based on variance of spray
angle and spray pattern
Angle = 0°
Angle = 120°
Angle = 60°
Angle = 180°
A Fully distributed spray pattern
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140
TTHMs—µg/L
120
100
80
60
40
20
0
0
25
50
75
100
125
150
175
150
175
Time From Initial Conditions—h
Angle = 0°
Angle = 120°
Angle = 60°
Angle = 180°
B Hollow spray pattern
140
120
TTHMs—µg/L
studies and are outlined in Table 4. As noted previously, two
underlying assumptions with modeling spray aeration removals
of THMs in relatively confined spaces (e.g., water storage tanks)
are that the water in the storage tanks will be completely mixed
and that the storage tank will be adequately ventilated to maintain maximum water-to-air transfer conditions, regardless of
aqueous THM concentrations.
Sensitivity analysis outputs. Outputs developed for the sensitivity analysis are shown in the figures. Figure 3 models withdrawal configurations; Figures 4 through 9 model spray angle
and spray pattern, temperature, water droplet diameter, nozzle
height, THM speciation (at various temperatures), and magnitude of recycle flow, respectively. Each figure shows the analysis
of a single variable, within a practical range of input values.
Figures 4 through 9 yield important information regarding the
model and spray aeration systems in general. From these figures,
the most influential parameters can be determined on the basis
of the variation in output caused by changing those parameters
and the range of parameter values assumed within this study.
Stated more simply: the greater the spread of the plots, the more
influential the parameter.
The oscillatory patterns observed in the sensitivity analysis
charts occurred because of the nature of the daily drain-and-fill
cycles modeled in water storage tanks. Although THMs are consistently removed by recycling water into the tank, the model
assumes that the tank influent flow contains THMs at the same
initial concentration during each time step. Therefore the tank
influent concentration is often higher than what is found in the
tank (which makes sense, given expected THM removals). As
such, the THM concentration typically decreases during drain
cycles (because additional THMs are not being added to the tank)
100
80
60
40
20
0
0
25
50
75
100
125
Time From Initial Conditions—h
TTHMs—total trihalomethanes
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FIGURE 5
Sensitivity analysis of model based on variance of
temperature
T = 2°C
T = 22°C
TABLE 5
Percent removal differences for each parameter of
interest after equilibrium conditions have been met
High Value
Maximum
Removal
Difference
33%
100%
54.0%
Continuous QR
QR during Qi
37.2%
100 μg/L
300 μg/L
26.0%
T = 36°C
140
Parameter
120
Percent recycle flow
Recycle configuration
TTHMs—µg/L
100
THM formation
potential
80
60
40
20
Nozzle height
1 ft
45 ft
23.9%
Water droplet
diameter
100 μm
1,200 μm
20.4%
First-order THM
formation constant
0.01 d–1
0.10 d–1
17.8%
Temperature
0
0
25
50
75
100
125
150
175
200
Time From Initial Conditions—h
Spray angle (spray
pattern)
Speciation
T—temperature, TTHMs—total trihalomethanes
Low Value
2°C
36°C
10.3%
0° (full cone)
180° (hollow cone)
3.0% (17.0%*)
100% CHBr2Cl
100% CHCl3
3.3–1.3%
CHBr2Cl—dibromochloromethane, CHCl3—chloroform, Qi—influent water flow, QR—
recycled water through the spray aeration system, THM—trihalomethane
*The 17.0% difference refers to the model when performed for hollow cone spray regimes.
performed on temperature (Figure 5), the parameter variance can
be determined by using the values from the models produced for
temperature = 2°C and temperature = 36°C and finding the average percent difference for each time step over a 24-h time period
after 100 h from the initial conditions. An average percent difference of approximately 10% was found. In other words, after the
system has reached equilibrium, the concentration of THMs is
10% higher on average in systems at 2°C than in systems at 36°C.
Table 5 shows the average percent differences for each of the
parameter sensitivity analyses using the given extreme values.
From the sensitivity analyses and the given case study’s
extreme values shown in Table 5, the most influential parameters were determined to be the withdrawal location of the
recycle flow and the amount of the recycle flow. As can be seen
in Figures 3 and 9, these two parameters yielded the greatest
variance in outputs in the model and were the only parameters
with overall percent differences greater than 35% between the
low and high values that were modeled. In this study, a configuration with continuous recycling from within the tank was
clearly more efficient at removing THMs than configurations
in which recycling occurred only during fill cycles or when the
recycle flow was sprayed directly from the influent line during
the fill cycle (Figure 3). Additionally, as shown in Table 5,
increasing the recycle flow in a spray aeration system can significantly reduce the THM concentrations. This result, while
straightforward, is important because it highlights the recycle
flow as the most influential parameter.
Additional parameters that were shown to exert influence over
the efficiency of spray aeration systems include THMFP, the firstorder formation constant, water droplet diameter, nozzle height,
spray pattern when assuming a hollow cone spray pattern (i.e., a
longer nominal travel distance), and temperature. Although not as
influential as some parameters previously discussed, all of these
parameters were shown to have the potential to effect between a
10 and 26% change in THM removal efficiency. The significant
JOURNAL AWWA
influence of THM formation potential and first-order rate constant
(in relation to the THM levels entering the storage tank) is reflective of the reactivity of the organic precursor material and chlorine
dose, suggesting that the placement of the storage tank in relation
to the treatment facility should be taken into consideration. It is
reasonable to assume a higher THMFP and rate constant for storage tanks located near the treatment facility than for storage tanks
located at the far ends of the distribution system.
In certain cases, even a 10% change could constitute the difference between compliance and violation of the regulations.
However, certain parameters—such as THMFP, first-order formation constant, and temperature—cannot be controlled or are
difficult to control through engineered systems. For example,
THMFP largely depends on the influent water composition and
therefore would likely require costly alterations to drinking water
treatment plant processes, making such alterations impractical
for small systems.
Conversely, nozzle height, water droplet diameter, and spray
pattern have the potential to be controlled because these parameters are functions of the design of the spray aeration system and
as such, can be engineered. Some interesting trends, however, can
be discerned from the sensitivity analysis charts for these parameters. For example, with regard to nozzle height (see Figure 7),
removal efficiency increases with increasing height; however, the
magnitude of the effect of nozzle height on removal efficiency
decreases with increasing height. As the nozzle height increases,
the model outputs tend to converge. Although a 23.9% difference
was observed between model outputs from a 45- and a 1-ft nozzle
height, only 5.7% of this increase in THM removal efficiency was
observed between the nozzle heights of 20 and 45 ft. Such information could be helpful in the design of spray aeration system because
2014 © American Water Works Association
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Peer-Reviewed
FIGURE 6
Sensitivity analysis of model based on water droplet
diameter
H = 1 ft
H = 8 ft
H = 20 ft
140
140
120
120
100
100
80
60
60
40
20
20
0
25
50
75
100
125
Time From Initial Conditions—h
150
175
d—diameter, TTHMs—total trihalomethanes
0
0
25
50
75
100
125
Time From Initial Conditions—h
150
175
H—height, TTHMs—total trihalomethanes
practitioners would be aware that although increasing the height
of the spray nozzle within a tank can help optimize removal efficiency, additional heights beyond 15–20 ft may not increase
removal efficiency significantly. It is probable that at heights greater
than 15–20 ft, THM removal is no longer limited by rate kinetics
but rather is controlled by Henry’s law equilibrium conditions
having been reached. If full-tank ventilation is assumed, the lack
of measurable THMs in the gaseous phase implies that the THMs
in the aqueous phase will also approach very low concentrations,
if not complete removals, thereby explaining why enhanced removals are not observed with additional travel distance.
A similar trend can be seen with water droplet diameter
shown with the sensitivity analysis in Figure 6. Although a 20%
difference was observed between the large and small droplet
diameters used in this study, as the water droplet diameter
increased, the effect of this parameter on removal efficiency
decreased. Between dsmd of 900 and 1,200 μm, only a minimal
decrease in removal efficiency (2.7%) was observed. It is important for practitioners to know that at larger droplet diameters,
changes in diameter have minimal effects on the removal efficiency, whereas at smaller diameters, changes may exert a more
significant influence on the model output and subsequently on
system removal efficiency. This is likely attributable to the fact
that as droplet diameters increase, changes in the surface-areato-volume ratios of the droplets decrease, which would lead to
lower declines in removal efficiency. Additionally, dsmd is related
to flow and pressure through spray nozzles, and these factors
will need to be considered as well in the evaluation and design
of spray aeration systems.
The least influential parameters investigated in this study were
the spray angle (when a uniform cone distribution spray pattern
is assumed) and THM speciation. As can be seen from Figure 4
JOURNAL AWWA
H = 4.5 ft
H = 15 ft
H = 45 ft
80
40
0
Sensitivity analysis based on the nozzle height above
the water surface in the tank
d = 300 μm
d = 900 μm
TTHMs—µg/L
TTHMs—µg/L
d = 100 μm
d = 600 μm
d = 1,200 μm
FIGURE 7
(part A), Figure 8, and the variances listed in Table 5, these
parameters exerted minimal influence on the output of the model.
These findings may discourage design engineers from investigating or proposing the use of specialized spray nozzles with greater
spray angles. Rather than choose spray nozzles on the basis of
price, spray angle, and dsmd, practitioners can focus on nozzles
that do not require elevated pressures and are not prone to clogging, because these may incur additional expenses. However,
when a hollow spray cone was modeled (Figure 4, part B), the
spray angle had a far more significant effect on THM removal.
The hollow spray cone pattern used here assumed the water flows
only on the outer edge of the cone and that typical travel paths
have a 10-ft radius before falling at a 45° angle until reaching the
water surface (BETE, 2013; Wallace, 2013). With this alternative
configuration, the effects of spray angle are amplified and become
a significant design consideration.
The fact that THM speciation had minimal effect on the
removal output of the model (see Figures 2 and 8) is significant
for the following reasons. First, previous studies showed that
other aeration systems, such as diffused aeration systems (Zwerneman, 2012; Zwerneman & Collins, 2012; Brooke, 2009), may
experience significantly lowered removal efficiency of brominated species. Efficient removal of brominated species constitutes a potential advantage of spray aeration systems over other
systems, because these systems appear to have minimal difficulty
in removing brominated species (Brooke & Collins, 2011).
Additionally, it was shown that the THM speciation did not
have a significant effect at any temperature, a factor that is
potentially advantageous, especially for systems treating waters
with high bromide concentrations.
The crossover range of the Henry’s law constants for THMs
explains why differences in removal efficiencies have been
2014 © American Water Works Association
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Peer-Reviewed
FIGURE 8
Sensitivity analysis of model based on THM species at
various temperatures (2, 22, and 36°C)
CHCl3 (22°C)
CHBr2Cl (22°C)
FIGURE 9
Sensitivity analysis of model based on recycle flow
percentage
QR = 33% of Qi
QR = 100% of Qi
CHBrCl2 (22°C)
CHBr3 (22°C)
QR = 67% of Qi
140
A
100
120
90
80
100
TTHMs—μg/L
Removal—%
70
60
50
40
30
80
60
40
20
20
10
0
0
25
50
75
100
125
150
175
0
0
Time From Initial Conditions—h
25
50
75
100
125
150
175
200
Time From Initial Conditions—h
CHCl3 (2°C)
CHBr2Cl (2°C)
Qi—influent water flow, QR—recycled water flow through the spray
aeration system, TTHMs—total trihalomethanes
CHBrCl2 (2°C)
CHBr3 (2°C)
B
100
90
80
Removal—%
70
60
50
40
30
20
10
0
0
25
50
75
100
125
Time From Initial Conditions—h
CHCl3 (36°C)
CHBr2Cl (36°C)
100
150
175
CHBrCl2 (36°C)
CHBr3 (36°C)
C
90
Removal—%
80
70
60
50
40
30
20
10
0
0
25
50
75
100
125
Time From Initial Conditions—h
CHBr3—bromoform, CHBrCl2—bromodichloromethane,
CHBr2Cl—dibromochloromethane, CHCl3—chloroform,
THM—trihalomethane
JOURNAL AWWA
150
175
observed among the various species in diffused aeration systems
(Zwerneman, 2012; Zwerneman & Collins, 2012; Brooke &
Collins, 2011). When the liquid phase controls mass transfer,
increased air-mixing has minimal effect on removal, whereas
when the gas phase controls mass transfer, increased air-mixing
will have a greater effect on removal. In other words, more soluble gases (with low Henry’s law constants) are gas film–controlled. Conversely, more volatile gases with higher Henry’s law
constants are liquid film–controlled. Because of the range of the
Henry’s law constants of THMs, certain species (such as CHBr3)
are considered to be more gas film–controlled, whereas other
species with higher Henry’s law constants (such as CHCl3) are
considered to be more liquid film–controlled. Because there is less
air-mixing in diffused aeration systems, the more highly brominated species (which are more gas film–controlled than CHCl3)
are less efficiently removed. Conversely, in spray aeration systems,
where there is greater air mixing, these differences in removal are
less pronounced because the more gas film–controlled species are
removed at efficiencies similar to those for the more liquid film–
controlled species.
Last, the current evaluation of the individual parameters for
THM removals did not take into account the possible enhancement of overall removals by combining multiple parameter influences. These additive removals achieved through making favorable changes to selected parameters offer numerous possibilities
for achieving target THM removals. Figure 10 provides an example depicting gradually increasing THM removals from stepwise
modifications to height, droplet diameter, and recycle ratio. The
possibility of achieving desired removals by various combinations
of selected parameters offers flexibility for utilities considering
site-specific conditions.
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FIGURE 10
Sensitivity analysis based on simultaneous variance of
QR, nozzle height above water, and droplet diameter
QR = 50%, H = 4.5 ft, d = 690 µm (baseline)
QR = 50%, H = 15 ft, d = 690 µm
QR = 50%, H = 15 ft, d = 300 µm
QR = 100%, H = 15 ft, d = 300 µm
140
120
TTHMs—µg/L
100
80
60
40
20
0
0
25
50
75
100
125
150
175
Time From Initial Conditions—h
d—diameter, H—height, QR—recycled water flow through the spray
aeration system, TTHMs—total trihalomethanes
Recommendations. Although the model used here was based
on empirical relationships, the results of this study should be
verified in the laboratory and especially in the field in order
to calibrate and enhance the value of the proposed model.
Further study would be useful in confirming the applicability
of model predictions to real-world spray aeration systems.
Confirmation of the assumed first-order relationship between
time and THM formation also requires additional study and
verification in the field.
Furthermore, these results should be made tangible and applicable to practice. Although the study results clearly demonstrated
that increasing the recycle ratio in a spray aeration system
increases THM removals, this finding does not necessarily provide practitioners with a substantive metric for designing and
evaluating the potential of these systems. A high recycle ratio may
be appropriate in certain systems but may not be feasible in others because of long-term energy costs related to pumping. Additional research could increase the accessibility of these results by
providing a cost–benefit analysis framework that engineers could
use to prioritize the controllable parameters in order to maximize
efficiency and minimize cost. A suggested starting point that was
demonstrated by another water utility (Chaplin & Adams, 2011)
would be to install a recycle pump system that is affordable and
enhances tank mixing conditions and to develop and install a
spray aeration manifold system in which the selected nozzles are
operating in the manufacturer’s recommended ranges and achieving an available droplet travel distance greater than 5 to 8 ft.
CONCLUSION
Findings of the current study. This study investigated the use of a
mass balance model to predict THM removals using spray aeration. Empirical THM removal equations based on design parameters for spray aeration systems (Brooke & Collins, 2011) as well
as mass balance principles were used to develop an iterative model
that can take into account various water quality and design parameters in drinking water storage tanks to make predictions of THM
concentrations over time. Although the model described here was
developed for use in storage tanks, similarly designed clearwell
systems could be modeled using the same method.
From the developed model and the sensitivity analysis performed, it was determined that the most influential parameters
in spray aeration systems are the configuration of the recycle flow
and the magnitude of that flow. It was also shown that additional
parameters—such as height of spray nozzle, water droplet diameter, THMFP, THM formation first-order rate constant, spray
cone pattern, and temperature—were fairly influential on model
outcomes, whereas spray angle for a uniformly distributed spray
cone pattern and THM speciation had minimal effect on model
predictions. These results are significant because they can help
practitioners determine which parameters should be meticulously
controlled when designing spray aeration systems.
Additionally the results of this study elucidated the potential
utility of spray aeration in systems with high concentrations of
brominated species of THMs. Although other systems, such as
diffused aeration systems, have demonstrated minimal effectiveness in the removal of brominated THMs, the findings of this
spray aeration study predicted excellent removals.
JOURNAL AWWA
ACKNOWLEDGMENT
The authors acknowledge Ethan Brooks for his initial efforts
investigating spray aeration; Peter Dwyer, Kellen Sawyer, and
Damon Burt of the New England Water Treatment Technology
Assistance Center at the University of New Hampshire, Durham,
for their assistance in the experimental setups; and Erik Rosenfeldt of Hazen and Sawyer, Ashland, Va., and Rick Gell of O’Brien
and Gere, Syracuse, N.Y., for the opportunity to model specific
storage tanks.
ABOUT THE AUTHORS
Aidan R. Cecchetti is a graduate student at
the University of California at Berkeley,
where he is currently pursuing a master’s
degree as part of a joint MS/PhD program in
environmental engineering. He holds a BS
degree in environmental engineering from the
University of New Hampshire in Durham,
N.H. Harrison Roakes is a graduate student
in the department of civil engineering at the University of New
Hampshire in Durham. M. Robin Collins (to whom
correspondence should be addressed) is a professor at the
University of New Hampshire, Department of Civil and
Environmental Engineering, 348 Gregg Hall, Durham, NH
03824 USA; robin.collins@unh.edu.
FOOTNOTE
1BETE,
Greenfield, Mass.
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LaBranche, D.F. & Collins, M.R., 1996. Stripping Volatile Organic Compounds and
Petroleum Hydrocarbons From Water. Water Environment Research,
68:3:348.
PEER REVIEW
Date of submission: 08/15/2013
Date of acceptance: 11/26/2013
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