Determinación de los recursos necesarios

The differences between the stoichiometric and kinetic model parameters in GPS-X and AQUASIM are shown in Table 7.10. The greatest variance was between the heterotrophic growth rates, 13.2 d-1 in GPS-X and 5 d-1 in AQUASIM. The default for the heterotrophic growth rate in GPS-X was 6 d-1; however, this had to be increased to 13.2 d-1 in GPS-X in order to achieve good calibration. It is important to note that all the kinetic and stoichiometric parameters were kept within the literature ranges. It is not clear why there is a difference between the two sets of figures, but it is probably due to two different pieces of modelling software being used.

Table 7.10 – Differences in stoichiometric and kinetic model parameters between GPS-X and AQUASIM

Parameter (Units) GPS-X AQUASIM

Heterotrophic maximum specific growth rate (d-1) 13.2 5

Autotrophic maximum specific growth rate (d-1) 1.0 1.0

Heterotrophic yield (g COD/g COD) 0.75 0.54

Autotrophic yield (g COD/g N) 0.25 0.19

Heterotrophic decay rate(d-1_{) 0.62 0.1}

Autotrophic decay rate(d-1) 0.04 0.05

The heterotrophic maximum specific growth rate was higher in GPS-X than in AQUASIM. The explanation for this could possibly be the fact that in GPS-X the PFBR was modelled as an activated sludge unit whereas in AQUASIM the PFBR was modelled as a biofilm unit.

The heterotrophic yield in GPS-X was adjusted as the heterotrophic growth rate was already at the upper end of the accepted literature range. In GPS-X the heterotrophic yield

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was high at 0.75 g COD/g COD. The high heterotrophic yield could be due to the fact that other organisms could have contributed to the carbon removal, such as phosphorus accumulating organisms (PAOs) and these were modelled as heterotrophs and therefore led to a high heterotrophic yield (Gray, 2004). In the model only heterotrophs and autotrophs were modelled and no other type of microorganism, this is not the case in the PFBR or indeed any other type of wastewater treatment plant as other microorganisms would also be present.

7.8 CONCLUSION

This study examined the application of the existing FS-PFBR1 AQUASIM and GPS-X models to a PFBR system installed at Moneygall, County Offaly. The objective of the study was to assess the ability of the models to predict the treated effluent quality of the Moneygall PFBR by adapting existing models. By carrying out this process, it was hoped to achieve a more universal PFBR model that can be used in commercial applications, end user design products and licensing in the future.

This chapter investigated the possibility of (1) using the previously developed simple activated sludge-based model developed in Chapter 5 and adapting it to FS-PFBR2, and (2) using the previously developed biofilm-based model discussed in Chapter 6 and adapting it to FS-PFBR2.

The main conclusions are:

 This work shows that it is possible to apply a GPS-X model originally designed for a specific plant (FS-PFBR1) to a similar PFBR plant (FS-PFBR2) by following a sequence of steps to modify, calibrate and validate the original model against new experimental data. The new model was then applied to accurately predict the treated effluent quality of the new plant.

 The existing GPS-X model developed for FS-PFBR1 was successfully adapted to predict the treated effluent quality of FS-PFBR2.

 The existing AQUASIM model developed for FS-PFBR1 was successfully adapted to predict the treated effluent quality of FS-PFBR2.

 These models could be applied to future experimental and pilot scale units for design purposes.

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 The models could be used to run different scenarios to predict the optimal scenario, i.e. contaminants removed using the minimum of inputs (cost of energy).

 The models could be used to enhance and improve reactor operation and inform future studies.

 It is recommended that further experimental work be carried out estimating the exact KLa of FS-PFBR2.

The ability of the models were assessed based on the two software programs used to predict the treated effluent quality of FS-PFBR2 and the results show that once a PFBR model is built and calibrated correctly, it can be easily adapted and applied to other PFBR plants. This demonstrates that the model presented in this study is sufficiently adaptable, making the technology more accessible and attractive to stakeholders in the wastewater treatment sector.

A generic model has now been developed for the PFBR that is more cost effective than initiating a new model for every new WWTP. Further work will focus on improving model results by modelling the experimental measurements of biofilm mass and applying the model to a wider range of field scale systems.

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8 UNCERTAINTIES ENCOUNTERED IN WWTP MODELLING

8.1 INTRODUCTION

This Chapter investigates some of the modelling uncertainties that were encountered while undertaking this research.

The five main causes of uncertainty identified during this thesis were:

1. modelling the hydraulics of new technologies

2. modelling the passive aeration process in new technologies 3. modelling new technologies with minimal performance datasets 4. accurate undertaking/execution of the calibration process 5. scaling up laboratory-scale data to full-scale models

This chapter describes the method used to model process hydraulics and the passive aeration process and discusses the accuracy and uncertainty surrounding these parameters. This chapter also discusses different types of calibration required in modelling and also the importance of influent characterisation. The issue of scaling up laboratory-scale data to full-scale models was also addressed. Finally the PFBR was modelled using both GPS- X and AQAUSIM and a comparison of these modelling packages is presented.