optimization of tunisian wastewater treatment plant

Sustain. Environ. Res., 21(1), 65-72 (2011) (Formerly, J. Environ. Eng. Manage.)

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OPTIMIZATION OF TUNISIAN WASTEWATER TREATMENT PLANT - THE KELIBIA CASE Cherif Hayet,1,* Touhami Youssef,2 Shayeb Hédi1 and Hamdi Moktar3 1

Department of Civil Engineering National School of Engineering of Tunis Le Belvédère 1002, Tunis 2 Faculty of Engineering Sohar University Sohar 311, Sultanate of Oman 3 Department of Biological and Chemical Engineering National Institute of Applied Sciences and Technology Centre Urbain Nord 1080, Tunis

Key Words: Activated sludge process, COD fractionation, mathematical modeling, calibration, model validation, optimization ABSTRACT Activated sludge process of Kelibia full-scale, situated at the North of Tunisia was calibrated by the activated sludge model No. 1 (ASM1), using STOWA calibration protocol. Wastewater treatment plant layout was implemented in GPS-X software and simulations were performed based on daily measured mean values. Detailed wastewater characterisations required by the process models were performed and four chemical oxygen demand (COD) fractions (SS, XS, XI and SI) were obtained by batch reactor technique. The model calibration was successfully experimentally confirmed for steady-state and dynamic conditions with the mean errors of 26% in COD effluent and 16% in mixed liquor suspended solids and four model parameters were adjusted (μH = 1.65 d-1, YH = 0.74 g COD g-1 COD, KS = 222 g m-3, and bH = 0.25 d-1) . ASM1 model was validated based on measurement campaign and validated model was used to optimize the denitrification process on Kelibia plant. INTRODUCTION In order to response to new legislation aimed at reducing the cost of treatment, computer modeling of wastewater treatment processes is making some progress, and this will lead to a better understanding of the underlying costs. The development of work aiming at the optimization of wastewater treatment processes and the development of tools for simulation for a better control of their design and their exploitation are essential to describe, predict and control the complicated interactions of the process. The activated sludge family models (ASMs) has been successfully applied to full-scale treatment plants and shown to be a good compromise between the complexity of the activated sludge processes and prediction of the plant behavior under dynamic conditions [1-4]. *Corresponding author Email: [email protected]

Numerous research works on activated sludge system modeling were performed in order to optimize and predict the behavior of full-scale plants under varying operating conditions. Nuhoglu et al. [5] have modeled the Erzincan case plant by using ASM No. 1 (ASM1). Beck et al. [6] optimized the Behlenhein activated sludge wastewater treatment plant (WWTP) to face pollution overloads during grape harvest periods. Meijer et al. [7] used metabolic phosphorus integrated in ASM2d for modeling WWTP Hardenberg. Wanner et al. [8] used the activated sludge model no. 3 (ASM3) for studying the effect of a temperature decrease on nitrification and nitrogen removal in the WWTP of Zurich, Switzerland. Siegrist and Gujer [9] have calibrated ASM3 on Swiss WWTP [9]. Deterministic tools of modelling require a characterization which is related to the biological organic

Sustain. Environ. Res., 21(1), 65-72 (2011)

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matter reactivity for describing correctly a microbiological WWTP process. Various methods have been presented in the literature for quantification of chemical oxygen demand (COD) fractions such as physicalchemical [10], respirometric [11,12] and batch aerated reactor [13]. The number of reactions and organism species that are involved in the system may be very large. An accurate description of such systems can therefore result in highly complex models, which may not be very useful from a practical, operational point of view. Optimization of WWTPs necessitates successful calibration of the complex WWTP models. There was no standard approach in performing the calibration study: four systematic calibration protocols including Biomath [14], Hsg [15], Stowa [16] and Werf [17] have recently been proposed to bring guidance to the modelling of activated sludge systems and in particular to the calibration of full-scale models. These protocols have many similarities as well as differences [18]. The major common points of the protocols are: definition of goal for determining the overall calibration procedure; data collection, verification and reconciliation; additional measurements (intensive measurement campaigns) and validation. Calibrated models should be validated using a data set obtained under different operating conditions other than those of the calibration period. In this paper we modeled a full-scale biological carbon removing Kelibia WWTP situated at the North of Tunisia. This WWTP is confronted with successive periods of increase in the influent organic load, variable according to the season, tourist and industrial activities. It is located in a very specific zone, near the sea, surrounded by fisheries, olive oil mills, tomato industries and slaughterhouse. The objective of this study is to validate the ASM1 for further use as a tool for optimization purpose. In the first part, the STOWA protocol [16] was used to calibrate the biological reactor model. Kinetic and stoichiometric parameters were adjusted and predicted model concentrations were compared to measured values. A steady state and dynamic simulations were performed by running GPS-X software [19]. In the second part, the validated model was used to evaluate several scenarios that might lead to improved operation of existing WWTPs and process optimization and control. MATERIALS AND METHODS 1. Description of the Kelibia Plant

The layout of Kelibia full-scale WWTP, simulated in this study, is shown in Fig. 1. It is located at the North of Tunisia and serving 55200 population equivalents. The plant is an extended aeration activated sludge system (nominal load = 0.075 kg BOD

Anoxic tank Aeration tanks Settling tank Influent Effluent

Pre-treatment units

Return activated sludge

Wasted sludge

Fig. 1. Layout of the Kélibia plant.

kg-1 MLSS d-1), constructed in 1990. It is designed for daily mean flow rate of 5540 m3 d-1 and a peak flow rate of 8870 m3 d-1. It includes a grit chamber and a grease remover. It also includes six aeration tanks (7448 m3) consisting of two parallel lines of three series tanks physically separated. The first, functioning as an anoxic zone, is equipped with two mechanical agitators. The last two tanks are equipped with surface turbines, each providing 48 kW and oxygen capacity of 78 kg O2 h-1. A final secondary settling tank (volume: 1530 m3, surface: 490 m2) is used. This WWTP is confronted with period of dysfunction due to very high daily organic flow and variations of influent flow rate. Based on daily reports realized during the 2004 year we notice overload some periods at 16 t COD d-1, 5 t BOD d-1 and 12 t SS d-1. The flow rate presented an important fluctuation (in the range of 2-8 km3 d-1), exceeding sometimes the design flow rate. In addition to this specific influent characterization, the sludge volume index was higher than 150 mL g-1 in the clarifier. 2. Detailed Characterization of Influent Flow

The precision of simulation is closely related to the variation of parameters and it is directly linked to the quality of the wastewater organic matter. Adjustment of parameters related to biochemical process is necessary to determine the COD fractions in the influent flow. The results of dynamic campaign measurement were combined with COD fractionation procedure to characterize the biodegradable, soluble and particulate fractions of COD. 2.1. COD fractionation by batch reactor test A raw sample influent was continuously aerated in the batch reactor. The organic matter was converted into CO2, biomass and inert organic matter. The COD fractions were calculated with raw and filtered COD measurement at the beginning and at the end of the test. Soluble and particular fractions were obtained by filtration (0.45 μm). The Stricker fractionation protocol [13] was referred in the two campaign samples for 48 h at Rosenmmeer WWTP. The same protocol was adopted to characterize the fractions of Kelibia WWTP for mean samples collected during 48 h at in-

Hayet et al.: Optimization of Wastewater Treatment Plant

2.2. Measurement campaign Campaign measurement data were performed on the influent, effluent, recycled sludge, input and output of the aeration tanks with a sampling interval of 2 h. The results of this campaign were used to estimate some parameters related with biochemical process and to validate the model. SS, VSS, COD, PT and TKN were analyzed according to Standard Methods [20]. COD and TKN were analyzed both on total and soluble wastewater. Ammonium was analyzed by steam distillation using NaOH (30%) followed by back titration of boric acid distillate using sulfuric acid (0.1 M). NO3, NO2 and PO4 were performed with commercial test kits. Samples were taken every 2 h to 15 min interval. Three replicates were performed on each sample. Other control variables such as pH, temperature, and flow rates were measured. 3. Models used, Environment

Calibration

and

Simulation

A bioreactor and a final settler are vital parts of a treatment system, two models were employed to simulate these process. For biological processes simulation, the ASM1 was used. The clarification process in the settler was modelled by the one-dimensional model of Takàcs [21]. GPS-X software v. 3.0 [19] was used to simulate the steady state and the dynamic behaviour of the carbon removal process under study. After constructing the layout of the plant, models, physical and operational data were introduced into the program. Next, the control and display variables were specified. The most important step in any modelling is the model calibration. For the WWTP chosen in this work, STOWA calibration protocol developed in the Netherlands was used. In the STOWA calibration protocol, the model structure for the hydraulics of the WWTP is based in the process description but not from tracer experiment. The Kelibia plant was modelled as a loop of three series, equal volume completely mixed stirred reactor, chosen on the basis of the plant configuration which is composed of three tanks physically separated. The optimization approach was used for model cali-

600 Total totalCOD COD

500

Filter COD (1.2(1,2) µm) filtred COD Filter COD (0.45 µm) filtred COD (0,45)

COD m-3)-3) COD(g(g.m

tervals of 15 min. This procedure consists of longterm aeration tests of the raw wastewater seeded with acclimated sludge. Two batch reactors were installed, one filled with raw influent wastewater (4 L) seeded with activated sludge (5 mL), and the other containing 1.2 µm filtered wastewater (GMF3/Whatman). Raw, filtered 1.2 µm and filtered 0.45 µm COD values were measured in these continuously agitated and aerated reactors for 21 d. The evolution of COD in one raw reactor is shown in Fig. 2. The filtrate reactor is only used to calculate the apparent yield of biomass growth with the substrate initially present in the sample. This value is used to calculate the slowly biodegradable COD fraction (XS).

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15

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Time (d)

Fig. 2. Evolution of the COD during an aerated reactor fractionation test.

bration. Differences between predicted and observed values were calculated after adjusting stoichiometric, kinetic and other parameters related to biochemical processes, like COD fractions. The optimizer module of GPS-X was used to minimize the objective function which is the sum square of the residuals. The error between measured and simulated values was evaluated according to the following criteria: ME % =

2 100 ∑ (Vmes − Vcal ) Vm N−K

(1)

RESULTS AND DISCUSSION 1. Wastewater Characterization

The batch reactor protocol, developed by Stricker [13], is used to obtain four fractions of COD out of six fractions of the ASM1 model. This protocol suggested that the heterotrophic biomass (XH) is included in XS and the apparent yield has the same value for filtered and raw wastewater filled in the reactor. Using values of inert fraction of biomass (fP = 0.2) and heterotrophic yield coefficient (YH = 0.67), it was possible to calculate a theoretical value of the apparent yield of biomass growth with the substrate initially present in the sample ϕapp (product of the two values: 0.134). The batch reactor protocol was performed for Kélibia WWTP. Three reactors filled with raw wastewater were used to confirm measurement and protocol reproducibility. The results of the biochemical characterization are presented in Table 1, where the COD fractions (mean and range values) are given in percentage of the respective wastewater total COD and compared to COD fractions from the literature. Experimental apparent yield obtained was 0.14 for Kelibia WWTP. The difference between theoretical and experimental apparent yield (ϕapp) could be justified by the variability to the value of fP and YH. Current literature values of fP are between 0.08 and


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Table 1. COD fractions from batch reactors tests COD fractions (% of CODT) SS XS 21 (21-22) 47 (40-58) 31 50 7-33 40-60 28 9-42 10-48 7-11 53-60 22 42

2. Evaluation of Simulation Results

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4000 3000 2000 1000 0 11

ASM1 model calibration was performed using the daily measured control variables for the year 2001 for Kelibia WWTP, which represents the most stable functioning period. The output variables were the MLSS in aeration tanks (to evaluate the performed biological activities) and the COD effluent (to evaluate the standard conformity). Default values for parameters suggested by the ASM1 have been used to carry out steady state simulation. Results from the simulation, as shown in Fig. 3, proved that adjustment of process model parameters is necessary. It was found that for model evaluation the characterization of the influent was the most important step, followed by knowledge of the effluent concentrations. Therefore, detailed wastewater characterisations required by the process model were performed by batch reactor technique. Wastewater influent fractions for Kelibia showed obviously a higher inert particular COD fraction. The COD fractions obtained are different from those used by default in GPS-X but they are in the common literature values range (Table 1). New steady state simulation executed with theexperimentally determined fractions proved that other kinetic and stoichiometric parameters should be ad-

XI 30 (20-37) 4 8-18 4 23-50 10-20 24

(a)

350


0.2 and YH are between 0.38 and 0.75 g COD g-1 COD [23]. The results proved that wastewater of Kelibia WWTP is mostly particular and slowly biodegradable (XI + XS = 77% of total COD) proving the contribution of some industrial influent. From the results presented by Stricker [13] and Ekama et al. [11] for strictly domestic influent, it is observed that the XI have a smaller value (4%) compared to our value (30%). Kappler and Gujer [24] also presented a result for domestic and industrial influent and reported that XI was more important (10-20% of total COD) compared to the only domestic influent. Our results were similar to that of the east Turkey [5] and especially to the Netherlands [23] fractions. The comparison between COD fractions obtained at Kelibia WWTP and literature fraction showed that the particular inert COD fractions were different. This is related to the specificity of Kelibia region.

-3 -3 MLSS (g m ) ) MLSS (g.m

This work, Kelibia, Tunisia French [13] Denmark [2] South Afrika [11] Netherlands [23] Suisse [24] East of Turkey [5]

SI 2 (1-3) 15 8 3-10 10-20 11

17,8 17.8

34,6 34.6

51,4 51.4

68,2 68.2

85 85

Time (d)

Fig. 3. Experimental (▲) and predicted (⎯) steady state values for: (a) effluent COD and (b) aeration tank MLSS using default GPS-X parameters.

justed. The calibration should only be done under experimental conditions such that the effect of parameters of interest dominates the responses. In this work, the most common parameters in which the response was sensible were: heterotrophic yield (YH), maximum specific growth rate for heterotrophic biomass (μH), half saturation coefficient for heterotrophic biomass (KS) and heterotrophic decay rate (bH). When YH was increased the MLSS in the aeration tank increased, μH and KS had an effect on display variables (effluent COD and MLSS in the aeration tank) and finally when bH was increased the MLSS in the aeration tank decreased. These results of sensibility analysis, from GPS-X analyser, were valid in steady state as well as in dynamic conditions. The mathematic optimizer approach is used to estimate the four selected parameters from Kelibia WWTP. Change in the default values of four model


3. Evaluation to the Validity of ASM1 Model

To confirm calibrated parameters, the validity to the model should be evaluated. There are three types of model validation; predictive, structural and dynamic. Two validation types are used in this work, dynamic and predictive respectively. The dynamic simulation was performed with the same calibrated parameters from the steady state simulation using the same data input, except the flow rate. In dynamic conditions, hourly average values of influent flow rate were introduced and the steady state volume and concentrations were used to initialize the system. As shown in Fig. 5, simulation results in dynamic conditions confirm the dynamic validity of the ASM1 model. A campaign measurement taken from Kelibia WWTP (6 d in year 2006) and calibrated parameters were used to validate the ASM1 model. The predictive validity of the model was confirmed (Fig. 6). 4. Wastewater Treatment Line Optimization

Kelibia WWTP was designed to ensure the removal of organic matter, nitrification and denitrification. Taking into account the current management (aeration time and sludge recycling ratio) the objectives were partially attained in terms of nitrification and denitrification. Kelibia WWTP drains a region characterized by a dense urbanization and an important activity. The influent organic nitrogen and free ammonium were strongly loaded, exceeding some times 100 g m-3 values. The diagnosis, during several years, of the current state of Kélibia WWTP showed that 61% of free ammonium was removed in 2001, 33% in 2004, 30% in

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120

-3

COD(g(g.m COD m-3) )

100 80 60 40 20 0 7000

(b)

6000 5000 -3 MLSS (g m ) -3) MLSS (g.m

parameters gave a reasonable match for the investigated variables. Calibrated parameters and their values are given in Table 2. By comparing the measurements of COD effluent and MLSS concentrations in the aeration tank at the WWTP with the results achieved when running simulations in GPS-X, the model behaviour was evaluated. After elimination of the values which do not check the mass conversion we have obtained a good agreement between simulated and measured concentrations. As shown in Fig. 4, the result of the simulations is similar to the real situation with mean errors of 26% in COD effluent and 16% in MLSS.

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Fig. 4. Experimental (*) and predicted (⎯) steady state values for: effluent COD and (b) aeration tank MLSS using calibrated parameters.

2005 and 26% during the first four months in 2006 (Fig. 7). The average mean value of free ammonium was higher than the standard discharge. It is around 40 g m-3 compared with the standard value of 0.5 g m-3. Thus, the effectiveness of the process is limited according to the aeration management, the sludge age and the influent characteristic which was in majority nonbiodegradable (see Table 1). Successions of anoxic-aerobic period in the same tank are controlled by a timer. The head anoxic tank, in which the recycled sludge and influent are introduced, is used for pre-denitrification. The mixed liquor extracted from the last aerated tank is directly sent to the secondary settler. In the current plant configuration, there is no internal recycle of the mixed liquor to the head tank. In order to seek the best operational conditions for nitrogen removal, several scenarios are tested by running GPS-X software. The modified LudzakkEttinger process [25] was proposed to optimize the denitrification process in Kelibia plant. This process

Table 2. Calibrated parameters and their values Parameters Heterotrophic yield, YH (g COD g-1 COD) Maximum specific growth rate for heterotrophic biomass, μH (d-1) Half saturation coefficient for heterotrophic biomass, KS (g m-3) Heterotrophic decay rate, bH (d-1)

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Time (d)

Kelibia 0.74 1.65 222 0.25

Default GPS-X value [19] 0.67 6 20 0. 62

Range (20 °C) [22] 0.38-0.75 0.60-13.2 5-225 0.05-1.6


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210

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Influent InfluentN-NH N-NH4 4 Effluent EffluentN-Nh N-NH4 4

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150 -3 N-NH ) -3) 4 (g m N-NH4 (g.m


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35,6 35.6

53,4 53.4

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Influent InfluentN-NH N-NH4 4 Effluent EffluentN-Nh N-NH4 4

20

Time (d)

Fig. 5. Experimental (▲) and predicted (⎯) dynamic values for: (a) effluent COD and (b) aeration tank MLSS using calibrated parameters. 250

0 25/11/03 14/1/04

4/3/04

23/4/04 12/6/04

1/8/04

20/9/04 9/11/04 29/12/04 17/2/05

Time

Fig. 7. Evolution of free ammonium concentrations function of the time (a) during several years (b) during 2004 year.

40

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SNO (1) SNO (2)

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Fig. 6. Validation of the predicted values (⎯) for effluent COD from campaign measurement (*).

-3 SNO (g m ) SNO (g.m

-3

)

COD m-3) -3) COD(g(g.m

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R

consists of recycling a fraction of mixed liquor from the last aerated tank to the head anoxic tank. Various internal recycle flow rates were tested using control variables at two days (Nov. 9 and 13, 2001), which reproduced the suitable conditions for denitrification [26] (important C/N ratio). The simulation results, carried out using data input control of the November 9th (C/N ratio equal to 9) indicates that 40% of nitratenitrite removal can be achieved with an internal recycle ratio (R) less than four (Fig. 8, SNO (1)). Further increase in R more than four has no effect on nitratenitrite removal. Data input of the November 13th, are characterized by a C/N ratio more than 9, are also simulated. As shown in Fig. 8 (SNO (2)), there is no limiting R value. Therefore, nitrate and nitrite removal

Fig. 8. Evolution of nitratenitrite concentrations as function of internal recycle to influent flow rates ratio (R) for C/N ratio = 9 (▬,SNO (1)) and for C/N ratio > 9 (─ ─,SNO (2)).

can be continuously improved when R is increasing. In the light of simulation results, it’s recommended the installation of the internal recycle line with a variable recycling ratio depending on influent characteristics and operational conditions. These results proved the importance of simulation tools for operator’s decision making according to the daily conditions.


CONCLUSIONS A Kelibia full-scale wastewater treatment plant situated at North of Tunisia was modeled using GPSX software package. The biological model ASM1 was calibrated with STOWA protocol. Four fractions of COD were obtained by batch reactor (XS, XI, SI, and SS) and four heterotrophic parameters were adjusted by GPS-X optimizer module (YH, KS, μH and bH). The dynamic validity of the biological model was confirmed. The validated model allowed us to undertake an optimization approach of the exploitation of the WWTP by simulating the effect of MLSS internal recycle on the performances of denitrification process. A search to optimize nitrification by rational management of aeration cycles and to adjust this management to another case like overloading constitutes the logical perspective to this work. Improvement of modeling approach, by coupling settler model and kinetic model will be also continued for a better management of the wastewater treatment plant. NOMENCLACTURE ASM BOD bH COD C/N ratio fp K KS ME MLSS N NH4 NO2 NO3 PO4 PT R SNO SS SS SI TKN Vcal Vmes VSS WWTP XH XI XS YH µH

Activated sludge model Biologic oxygen demand heterotrophic decay rate Chemical oxygen demand Carbon nitrogen ratio Inert fraction of biomass number of calibrated parameters half saturation coefficient for heterotrophic biomass mean error Mixed liqueur suspended solids number of observation free ammonium Nitrite Nitrate Orthophosphate Total phosphorus Internal recycles ratio Nitrate-nitrite suspended solids readily biodegradable substrate soluble inert COD Total Kjeldhal nitrogen calculated value measured value Volatile suspended solids Wastewater treatment plant heterotrophic biomass particular inert slowly biodegradable substrate heterotrophic yield maximum specific heterotrophic growth rate

φapp

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Apparent yield REFERENCES

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Discussions of this paper may appear in the discussion section of a future issue. All discussions should be submitted to the Editor-in-Chief within six months of publication. Manuscript Received: July 7, 2010 Revision Received: September 17, 2010 and Accepted: October 5, 2010