Simulation of the behavior of indicator microorganisms in combined sewer system

Abstract

A number of researches have pointed out that the behavior of pathogenic microorganisms in combined sewer system (CSS) is closely related with that of suspended solids (SS) including in-sewer deposits. Moreover, the transport process in CSS during wet weather events is so complex that it is crucial to develop a detailed model for the simulation of the runoff behavior of microorganisms in wet weather flows (WWFs). In this study, two key parameters of the Ackers-White model, i.e. representative particle size and specific gravity, and attached fractions of each microorganism to solids were experimentally determined and calibrated. Through the simulation using a distributed runoff model software (InfoWorks CS), it clearly demonstrated that it is difficult to reproduce the whole diurnal variation of dry weather flow and WWFs with the assumption of only a single set value of representative particle size and specific gravity. Therefore, solid particles were classified into coarse and fine fractions, considering particle volume distribution, different specific gravities and microbial attachment ratios to solids. The measurement results in diurnal variation of SS and indicator microorganisms are in good agreement with simulation results. The new simulation technique was successfully applied for the behavior indicator microorganisms in WWFs.

Full text

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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

Simulation of the behavior of indicator microorganisms in
combined sewer system

W.J. Kim12
*, S. Managaki , H. Furumai2 and F. Nakajima3

1 Environment Research Division, Korea Institute of Construction Technology, 2311, Daehwa-Dong,
Ilsanseo-Gu, Goyang-Si, Gyeonggi-Do, 411-712 Republic of Korea
2 Research Center for Water Environment Technology, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan
3 Environmental Science Center, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan

* Corresponding author, e-mail wjkim1@kict.re.kr


ABSTRACT
A number of researches have pointed out that the behavior of pathogenic microorganisms in
combined sewer system (CSS) is closely related with that of suspended solids (SS) including
in-sewer deposits. Moreover, the transport process in CSS during wet weather events is so
complex that it is crucial to develop a detailed model for the simulation of the runoff behavior
of microorganisms in wet weather flows (WWFs). In this study, two key parameters of the
Ackers-White model, i.e. representative particle size and specific gravity, and attached
fractions of each microorganism to solids were experimentally determined and calibrated.
Through the simulation using a distributed runoff model software (InfoWorks CS), it clearly
demonstrated that it is difficult to reproduce the whole diurnal variation of dry weather flow
and WWFs with the assumption of only a single set value of representative particle size and
specific gravity. Therefore, solid particles were classified into coarse and fine fractions,
considering particle volume distribution, different specific gravities and microbial attachment
ratios to solids. The measurement results in diurnal variation of SS and indicator
microorganisms are in good agreement with simulation results. The new simulation technique
was successfully applied for the behavior indicator microorganisms in WWFs.


KEYWORDS
Indicator microorganisms; combined sewer system; simulation of wet weather flows;
distributed runoff model


INTRODUCTION
Recently, various problems originating from combined sewer overflows (CSOs) during wet
weather events have been becoming social issues. Numbers of research on the behavior of
pathogenic microorganisms including bacteria and viruses, and their risks have been reported
(Hall et al., 1998; Steets et al., 2003; EPA, 2004; Fong et al., 2005). However, more exact
comprehension for the dynamics of microorganisms in CSOs is required.

Furthermore, many researches have indicated that the deposits in combined sewer system
(CSS) and the runoff behavior of pathogenic microorganisms are strongly correlated (Ellis et
al., 1995; Wilkinson et al., 1995; Meschke et al., 1998; Kim et al., 2007). The pathogenic
microorganisms with considerable concentrations are transported with the form adhering to
solid particles, deposited and concentrated in the sediment of CSS in dry weather, and during
wet weather events such sediment is flowed out rapidly. Although there have been a number
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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

of researches on the concentration variations of microorganisms in CSOs, they do not result in
quantitative comprehension for the runoff behavior of microorganisms actually.

Because of the complexity of the origins which have their own runoff characteristics, in order
to simulate the dynamics of CSOs comprehensively, various computational simulation
techniques have been introduced (e.g. Schellart et al., 2006). In particular, distributed runoff
models have been utilized extensively, which are able to consider rainfall conditions, landuse
patterns, and structural properties of CSS respectively (e.g. Jamieson et al., 2004). While the
distributed runoff models can expect reasonable results for hydraulic conditions, serious
disagreements have still being shown in the results for other pollutants such as SS, several
parameters related with particles and especially microorganisms.

In order to assess the behavior of pathogenic microorganisms in wet weather flows (WWFs)
including CSOs, it is necessary to investigate the runoff characteristics of them and to apply a
detailed model for the simulation. In this study, a sewer runoff model composing a distributed
runoff model was modified. The values of key parameters, i.e. representative size and specific
gravity of particles, particle size distribution and attached fractions of microorganisms to
suspended solids, were experimentally determined. Instead of simulation method using one
set of representative size and specific gravity, the simulation considering two particle groups
with different representative sizes, specific gravities and attached fractions of each
microorganism was applied. The runoff behavior of indicator microorganisms in WWFs were
simulated and assessed with respect to their origins for various rainfall conditions.


METHODS
Study area
The study was carried out at a small subcatchment located in Chiba city which lies to the east
of Tokyo, Japan. A brief summary of the study area is shown in Figure 1. It is the typical
urban residential area of the utmost upper region with CSS. Figure 1 (A) represents the
satellite image of the study area. It clearly shows the landuse property of the area as a typical
residential one. Figure 1 (B) shows the map of sewer pipes. The monitoring was conducted at
the overflow manhole at the utmost downstream of the study subcatchment.

Sample collection
Twenty-four hour monitoring of dry weather flow (DWF) was conducted from 12 p.m. on
December 20 (Tuesday), 2005 to the next day 12 p.m. The previous rainfall had fallen on
December 4 with total rainfall of 3.5 mm. The sampling was carried out every 30 minutes in a
whole day. All samples were collected at the center of the pipe using a stainless steel
sampling bucket.

Monitoring and analytical method
Flow rate. Water level was measured using a pressure sensor (ED552, Haenni, Germany) and
logged automatically every 5 minutes using a Grant SQ1000 Series Meter/Logger (England).
Flow rate was calculated using the stage-discharge rating curve.

Suspended solids. SS was measured as the portion of total solids by filtration using a glass
fiber filter (1.0 µm pore size, WHATMAN GF/B) after drying at 105℃ for 2 hours (Std.
Meth., 2540 D.).

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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008
sampling point
200 m
200 m
(A)
(B)
? total area: 67.4 ha
? drainage area: 56.2 ha
? population: 5,518
? total length of pipes: 15,814 m
? range of pipe diameter:
200-1200 mm
? number of manholes: 325




Particle size distribution. Particle size distribution was measured using the instrument which
can detect the particle settling velocity by the variation of optical transparency (CAPA 300
particle analyzer, HORIBA, Japan). Each measurement was triplicated.

Particle image. Photograph of particles in sewage was taken using a particle size analyzer
(DPA 4100 Micro-Flow Imaging™ (MFI™), BRIGHTWELL, Canada) which can measure
the physical properties of particle populations by capturing of the images of particles in
fluids.

Specific gravity. Specific gravity of particles in DWF was measured using a particle size
analyzer (CAPA 300 particle analyzer, HORIBA, Japan). Serial filtration was carried out
using a nylon filter (MILLIPORE) with the mesh size of 180, 100, 41, 20 and 11 µm. Specific
gravity is calculated by Stokes’ law using the relationship between the particle settling
velocity and their size for each filtrate. Every measurement was repeated 5 times.

Indicator bacteria and coliphages. All the samples were assayed for total coliforms (TC),
fecal coliforms (FC), Escherichia coli (E.coli) and coliphages (CP). Total coliforms and
E.coli were determined by the single agar layer method incubated at 37℃ using chromocult
coliform agar (Merck, Germany). Fecal coliforms were determined by the double agar layer
method incubated at 44.5℃ using desoxycholic acid agar (PEARLCORE, Japan). Coliphages
were also plaque assayed by the double layer method at 37℃ using 1 mL of sample on the
host strain E.coli K 12F+(A/λ). All the samples were incubated for 18 hours and every assay
was duplicated.

Attached fractions of microorganisms to solids. In order to measure the attached fractions of
microorganisms to solids, centrifugation pretreatment for solid-liquid separation at 1,164 g for
10 minutes at 4℃ was carried out (Characklis et al., 2005). After the pretreatment,
‘unsettleable (suspended)’ fractions of each microorganism were determined using the
supernatant of 70% of upper part in the centrifuge tube.

Simulation of DWF and WWFs
In this study, InfoWorks CS ver. 7.5, which is one of the well-known distributed runoff model
software, was utilized to simulate the behavior of each pollutant and microorganism in DWF
and WWFs.
Figure 1. Study area: (A) satellite image of the study area (referred from Google Earth); and (B) map
of pipes (the circle at the utmost downstream represents the sampling point).
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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

RESULTS AND DISCUSSION
Characterization of particles in dry weather flow
Diurnal discharge property of particles in DWF. Figure 2 showed diurnal fractional
variations of suspended solids with different sizes (<50 µm, 50-100 µm, and >100 µm). It was
observed that the concentration of SS becomes low at the dawn and is increasing rapidly in
the morning. Moreover, while particles smaller than 50 µm were discharged constantly
throughout the day, the variation of larger particles than 50 µm was significant. Especially,
the increase of SS concentration in the morning was mainly resulted from the larger particles.

Particle size distribution in DWF. Figure 3 showed volumetric distribution of the particles
with different sizes. It clearly indicated that there were small and large particle groups with
the size of 50 µm or less and 100 µm or more. It was distinctively observed that there exist
relatively a small number of particles with the size ranging 50 µm-100 µm. The median size
of total suspended solids in DWF was about 50 µm (n = 25).

Variation of specific gravity with different size ranges of particles in DWF. Figure 4 showed
the variation of specific gravity of the size-fractionated particle groups based on their settling
velocity. Size fractionation was done with mesh size of 180, 100, 41, 20 and 11 µm. It showed
that specific gravity of suspended solids in DWF ranged from 1.1 to 1.45 g/cm3. It
demonstrated that specific gravity of the solids with the size of 100 µm or more decrease.

Ratios of attached microorganisms to suspended particles in DWF. Using the centrifugation
pretreatment procedure already described, the unsettleable and attached fractions of each
microorganism were determined. Figure 5 showed the unsettleable fractions of each
microorganism in DWF sampled on another day. The average value of all of three bacterial


250
0
10
20
30
40
50
60
70
0 - 10
10 - 2020 - 3030 - 4040 - 5050 - 60 60 - 7070 - 8080 - 90
90 - 100
100 - 200200 - 300 300 - 400400 - 500
500 <
Particle size (㎛)Particle size (㎛)
Particle volume distribution (%)Particle volume distribution (%)
Max.Max.
75 percentile75 percentile
MedianMedian
25 percentile25 percentile
Min.Min.
0
50
100
150
200
12:0014:0016:0018:0020:0022:00
0:002:004:006:008:00
10:0012:00
TimeTime
SS (mg/L)SS (mg/L)
≧100µm
50 - 100µm
0 - 50µm
Figure 2. Diurnal fluctuation of SS composition
according to particle size range (n=3).
Figure 3. Volumetric distribution of particles
with different sizes in DWF (n=25).

1.0
1.2
1.4
1.6
0 - 11
11 - 20 20 - 41
41 - 100
100 - 180
Particle size (µm)Particle size (µm)
Specific gravity (g/cm Specific gravity (g/cm3 3) )
0.00
0.25
0.50
0.75
1.00
1.25
total
coliforms
E.coli
fecal
coliforms
coliphages
Unsettleable ratio
total
coliforms
E.coli
fecal
coliforms
coliphages
Unsettleable ratio
E.colE.coli i
Figure 4. Specific gravity of particles in
different size ranges (n=5). Error bars indicate
standard deviations.
Figure 5. Unsettleable fractions of bacterial
indicators and coliphages in DWF (n=3). Error
Bars show both lower and upper errors.

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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008
indicators and coliphages were 78% and 96% respectively. These results are quite similar to
those of several previous works (Gannon et al., 1989; Characklis et al., 2005; Jeng et al.,
2005).

Determination of principal parameter values of sewer runoff model
In order to simulate the pollution runoff dynamics in WWFs, the principal parameter values
of the sewer runoff model in InfoWorks CS were determined. SS, bacterial indicators such as
total coliforms, fecal coliforms and E.coli, and coliphages as an indicator of enteric viruses
were selected for simulation parameters.

Parameter values of surface pollutant build-up, surface pollutant washoff and rainfall loss
models. The runoff characteristics of each pollutant both in surface pollutant washoff process
and in sewer runoff process are closely related with the behavior of solid materials. The
physico-chemical properties of particles are different from each other between in surface
deposits and in in-sewer deposits in CSS distinctly. Therefore, the physical characteristics of
surface deposits and DWF should be set up differently.

In the study, Wallingford model, one of the double linear reservoir model, was used as the
default for rainfall runoff model. The parameter values of surface pollutant build-up, surface
pollutant washoff and rainfall loss models were summarized in Table 1 and Table 2. The main
parameter values of each submodel followed the values already published through the
previous studies of our research group in Japan and the default values of InfoWorks CS
(Wallingford Software Ltd., 2006). The potency factors of bacterial indicators and coliphages
deposited on urban surface to SS used the recommended values of event mean concentrations
(EMCs) by EPA which were summarized for the typical values of urban area (EPA, 2005) and
surveyed values through this study.

Parameter values of sewer runoff model. Parameter values of the sewer runoff model were
summarized in Table 3. For the 24 hour profiles, which imply the diurnal concentration
variation curves, of SS and each microorganism, the diurnal monitoring data were inputted.
The representative size, specific gravity of SS and the attached fractions of indicator
microorganisms to SS were determined from the measured values. In particular, in order to
simulate with more accuracy, solid materials in DWF were divided into two groups; coarse
and fine particles, and each measured value of representative size and specific gravity was
given. The attached fractions of bacterial indicators and coliphages to coarse and fine particles
were also derived from the experimental results. It was assumed that free-suspended bacterial
indicators and coliphages flow out like dissolved substance.

Simulation of the behavior of microorganisms in DWF
Simulation conditions. Some limitations of the Ackers-White formula (1991) have been
founded. Because this equation was derived from a large number of experiments using
particles with a fixed size range at a laboratory, it contains severe limitations which can not
reflect exactly their broad distribution of the size and specific gravity altering variously.
While applying this formula in the InfoWorks CS, the representative particle size and specific
gravity are crucial adjustment parameters to express solids dynamics (sedimentation and
resuspension). On the other hand, as mentioned above, particle distribution in DWF are
divided into two groups; the majority of particles with the size smaller than 50 µm and the
minority of larger particles more than 100 µm. Since their behavior in sewer would be clearly
different, it is judged that there is a limit to simulate using single set of representative size and
specific gravity (Ashley et al., 2000; Rushforth et al., 2003; Schellart et al., 2005).
Kim et al. 5