 Transfer of Technology
As one of an initial portfolio of six technologies, ODOURsim® has
been released into the international water market following the
recent launch of Water Innovate Limited, a spin out from the
School of Water Sciences at Cranfield University. Water Innovate
is providing a conduit for the transfer of new technologies out
of the laboratory and into the water industry, bridging the innovation
gap that has existed in the environmental sector.
Water Innovate’s initial focus is on marketing ODOURsim® as
well as N-Tox® (a new nitrification toxicity monitoring technique)
and a novel high performance chemical additive for water and
wastewater treatment. It also has three advanced tertiary treatment
process technologies in the development pipeline.
Annoyance Pathway
We can consider the odour annoyance pathway as having formation,
emission, dispersion and perception stages as depicted
in Figure 1.
The use of dispersion models to predict the odour concentrations
originating from sewage treatment works is commonplace. Dispersion
models available include ADMS, a common model used in the
UK, and ISC and Aermod, developed by the USEPA. The resulting
odour
contour plots produced are often used in support of planning
applications to show that nuisance will be minimal or non-existent.
Such models can also be used to make decisions about odour
control technologies at specific sites.
However, it is important to consider that each element in the
annoyance pathway is equally important. An over-emphasis on dispersion
modelling, where the other elements of the pathway are treated
simplistically, can give inaccurate predictions, even though
the graphically impressive odour contour plot provides a perception
of accuracy and precision.
Odour Measurement & Perception
Modelling the entire annoyance pathway is difficult. One of
the main problems is the difficulty in measuring odours.
We can
either measure odorant concentration using analytical means
or we can measure the effect of the odorants on the sense
of smell using dilution methods.
The relationship between odorant concentration and perceived
odours is complicated because sewage emissions may contain
huND-R™eds of different odorants. Hydrogen sulphide (H2S)
is commonly used
as a proxy indicator of overall odour strength because it
is one of the most common odorants associated with wastewater
and it is easily measured in gas and liquid phases.
Sensitivity and attitude to odours vary significantly amongst
individuals, although on aggregate it is possible to produce
dose-response curves for odour perception and annoyance.
Typically, odour exposure is estimated using dispersion
modelling, and
the degree of annoyance felt (the response) is assessed
using questionnaires. Dose-response study results have been
used to determine odour limits. These are usually specified
on a concentration
and
percentile basis and are also influenced by the averaging
period used in
the dispersion model.
Improving Accuracy
Because of the over-emphasis on dispersion modelling and the
lack of attention given to inputs to dispersion models,
the School of Water Sciences developed ODOURsim®. Using H2S
as a proxy indicator for odour, the software concentrates
on accurate mechanistic modelling of the formation and emission
stages of the annoyance pathway.
The software employs a liquid-phase H2S model and uses mass-transfer
calculations for various wastewater process components such
as weirs, channels, sedimentation tanks, aeration tanks
and trickling
filters. As well as the influence of different processes,
the software allows flow, quality and meteorological variables
to be examined in detail. Because the software is dynamic,
changes
in the impact of these variables on emission rates can be
examined
over time.
Hence, ODOURsim® avoids the inaccuracies inherent in using
a constant H2S dispersion rate, through mechanistic modelling
of variable H2S formation and emission at source. To illustrate
the potential for emission rate variability, the following examples
demonstrate where ODOURsim® can be used to determine the
effect of emissions from primary sedimentation tanks.
: Wind Effects
For sedimentation tanks, surface emissions are largely driven
by wind-induced turbulence. It is very uncommon for this
to be taken account of in odour modelling exercises.
To illustrate the importance of wind-influenced emission,
two cases have been considered. The first utilises a constant
emission
rate derived for the average wind speed of a one-year meteorological
data set used for dispersion modelling. The average wind
speed was 3.96 ms-1 which gives a fixed surface H2S emission
rate
of 2.42 x 10-7 g s-1 m-2. The second case allows emission
rates
to vary with wind speed, as illustrated in Figure 2.
Figure 2 shows that wind and emission rate distributions
are significantly skewed with lower values being more common
than
higher values. Dispersion modelling results using the ISC
model are shown in Figure 3.
Figure 3: Constant Emission Rate [Left], Variable
Emission Rate [Right]
There is a significant difference between odour footprints
for the two cases. For the constant emission rate case
the 1 ppb
H2S contour extends approximately twice as far as for
the variable emission rate case. The reason for this is the
skewed nature
of the emission distribution.
This means lower emission rates are more common than
higher ones. Also, when higher emission rates do occur,
this is
when wind
speeds are higher and dispersion improved. This is
why the use of a simple average fixed emission rate, as per
the traditional
input into dispersion models, can result in an over-estimate
of odour impact.
: Flow and Quality Variations
Because of variations in wastewater flow and quality at the
inlet to a treatment works, significant differences in
influent odorant concentrations and subsequent emissions
in the downstream
treatment processes will result. To investigate these effects,
ODOURsim® sewer and sedimentation tank models have
been used to model a set of primary sedimentation tanks
at the
end of a 10 km sewer.
The simulation was engineered so the sewer flows full at
flow rates above the average daily flow, and conditions
would become anaerobic in the sewer, allowing H2S to form.
For
flow rates below the daily average, the sewer flows part
full and aerobic conditions return, allowing the H2S formed
to be oxidised.
Figure 4 shows emission rate variations predicted by ODOURsim® for
the sewer and sedimentation tank system. Emission peaks are
observed relating to high flow conditions, because the sewer
flows full during this time and H2S is formed, and also because
emissions from the sedimentation tank weirs are enhanced
by high flows.
Figure 4: Emission peaks for the sewer and sedimentation
tank system
These large variations have implications for when
odour measurements are taken; if spot emission rate measurements
were being
used as inputs to dispersion models, the time of
the measurement would be crucial. Figure 5 shows the different
ISC predicted
odour footprints that would result from emission
measurements
taken at 9 and 16.00 hrs. The resulting odour footprints
are very different.
Figure 5: Odour emission at two different times
of the day, 09:00 [left]
and 16:00 hrs [right].
Conclusions
Where there are significant variations in emission rate, as
is the case in wastewater treatment, the deviations can radically
alter the odour footprint. Therefore, it is essential for emission
variations to be included in odour modelling exercises, and integrated
odour modelling approaches developed.
We have shown that as ODOURsim® is dynamic, the impact over
time of variables on emission rate changes can be predicted.
No other commercial software modelling tool is currently available
that deals with H2S formation and emission to accurately calculate
odours arising from different wastewater unit processes.
ODOURsim® is intended to be complimentary to existing odour
dispersion models, and improve the accuracy and validity of the
final output by providing a precise and mechanistic method for
inputting odour formation and emission data.
Because the software is compatible with existing dispersion
models its adoption is relatively simple. The improved
level of confidence
from dispersion modelling exercises will be important to
water utilities, plant operators and regulatory authorities
alike
in the cost effective management of odour abatement and
public perception
issues.
References
Gostelow, P, Parsons, S A and Cobb, J (2001) Development of
an odorant emission model for sewage treatment works, Water
Science
and Technology 44(9): 181-188.
Gostelow, P, Parsons, S A and
Lovell, M (2003) Integrated odour modelling for sewage
treatment works, 2nd IWA International
Workshop
/Conference on Odour and VOCs, Singapore, September 14-17.
Hvitved-Jacobsen,
T, Vollertsen, J and Tanaka, N (2000) An integrated aerobic/anaerobic
approach for prediction of sulphide
formation
in sewers, Water Science and Technology 41, 107-115.
Authors’ Notes
Steve Callister is Managing Director and Pete Gostelow is
ODOURsim® Product
Manager at Water Innovate Limited. Visit www.waterinnovate.co.uk
or telephone 01234 756014 for further details.
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