World Water & Environmental Engineering

Dynamic ODOURsim®software from Water Innovate accurately predicts odour emission

Dr Steve Callister & Dr Peter Gostelow
In this article, Steve Callister and Peter Gostelow describe Water Innovate Limited’s revolutionary odour emission modelling software. Developed at Cranfield University’s School of Water Sciences, ODOURsim® predicts the formation and emission of hydrogen sulphide from sewage treatment works.
The software is unique in producing dynamic predictions that demonstrate the variation of emission rate over time in response to changing flow, load and meteorological conditions.

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].


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.


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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