TRACER STUDIES AT A FULL-SCALE LAGOON USED AS PRE-TREATMENT FACILITY FOR A WATER TREATMENT PLANT

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1 Proceedings of the 13 th International Conference on Environmental Science and Technology Athens, Greece, 5-7 September 213 TRACER STUDIES AT A FULL-SCALE LAGOON USED AS PRE-TREATMENT FACILITY FOR A WATER TREATMENT PLANT B. RUFFINO*, S. FIORE*, A. CEDRINO*, D. GIACOSA**, L. MEUCCI** AND G. GENON* * DIATI, Dipartimento di Ingegneria dell Ambiente, del Territorio e delle Infrastrutture Politecnico di Torino, corso Duca degli Abruzzi, Torino, Italy barbara.ruffino@polito.it **Società Metropolitana Acque Torino, corso Unità d Italia 235/ Torino, Italy EXTENDED ABSTRACT The water treatment plant (WTP) of Turin (Italy), fed by water of river, has a lagoon as pre-treatment facility. Since the effectiveness of the lagoon treatment towards the removal of contaminants from water depends on the residence time of the system, and the mixing aspects for the limitation of peak concentration are also very important, this led to an investigation of the internal hydraulics of the lagoon. A tracer study using sodium fluoride (NaF) was performed to determine the stimulus response output and an extensive internal sampling of the tracer was also performed to better understand the movement of the tracer through the system. The lagoon investigated in the study had a surface of 1516 m 2, a volume of about m 3 and a nominal residence time of 18 d at average daily flow (115 L/s). An amount of NaF equal to 18 kg was diluted with about 5 m 3 of the lagoon water and introduced in the lagoon in 12 hours, in order to simulate a pulse injection. The amount of tracer added was fixed in order not to exceed the threshold concentration of 1.5 mg/l (maximum concentration value allowed in drinking water) under the hypothesis that the lagoon was not mixed at all (plug flow modality). Samples were taken from the outlet channel every 45 minutes and analyzed using a fluoride selective probe. The sampling campaign at the outlet channel was stopped after 29 days from the introduction of the tracer, when the outlet concentration dropped under the detection limit of the fluoride selective probe. Samples were also taken at 15 points (over 3 depth values, for a total of 45 sampling points) throughout the lagoon, 1, 7 and 14 days after the tracer introduction. From the interpretation of the tracer response and the tracer distribution in the lagoon in the three days of sampling, it appears that the system was efficiently mixed without relevant short circuits. In fact the first detection of the tracer at the outlet channel occurred after very few hours from the beginning of the test and the mean residence time of the lagoon, determined using the Levenspiel formula, in the presence of the flow rate used for the test, was about 13 days compared with a theoretical hydraulic residence time of 18 days. This assured that dissolved contaminants, like fluoride, from the river were efficiently diluted by the lagoon before entering the WTP. Keywords: lagooning, drinking water, tracer study, mass balance, retention time.

2 1. INTRODUCTION The WTP of the city of Turin treats about m 3 /y of raw water from Po river; while a half of the inflow is directly sent to the plant, the second half undergoes a lagooning process in a 15-ha artificial basin. Lagooning is a process that employs natural or artificial basins to make a pretreatment on natural waters to be destined to WTPs or WWTPs (wastewater treatment plants). The last use is far more applied than the first. During the permanence in the lagoon, wastewater receives treatment through a series of physical, biological and biochemical processes. Much of the treatment occurs naturally, but some systems are designed to use also aeration devices in order to increase the amount of oxygen in the wastewater. On the other hand, in the field of water treatment, lagooning is used with three main purposes: homogenization of the physical and chemical characteristics of the water then sent to the WTP with the aim of keeping constant the dosage of chemicals; water self-purification with the reduction of the chemical and biological pollutant load and turbidity (suspended solid content) with the subsequent improvement of the raw water quality and decrease in the chemical consumption; emergency feed of the WTP in the case of accidental contamination of the river or low water. The efficiency of a basin for lagooning processes on drinking water or wastewater primarily depends on its internal hydrodynamic behavior that, in its turn, is influenced by shape and depth of the basin, characteristics of inlet and outlet, climatology and direction of dominant winds in the zone where the basin is situated (Torres et al., 1999). Tracer tests were commonly used to derive hydraulic properties of treatment ponds (Broughton and Shilton, 212; Delatolla and Babarutsi, 25; Teixeira Costa and Siquiera do Nascimento, 28; Torres et al., 1999). In particular they are aimed to estimate the average actual residence time, as a consequence of the possible anomalies in the flow (dead zones, short circuits) and their relation with the phenomena which influence the hydrodynamics of the basin. With reference to the 15-ha full-scale lagoon employed as a pretreatment in the Turin WTP, this study was aimed to evaluate the efficiency of the lagooning process through the assessment of the internal hydrodynamic behavior of the basin. Basin hydraulic properties were gathered from the results of a tracer test performed with sodium fluoride. 2. MATERIALS AND METHODS The study was carried out on a lagoon of ha, 1,787,95 m 3, located in La Loggia ( N, E), near the town of Turin. The average daily flow throughout the period of the study was 115 L/s, with a nominal residence time of 18 days. The length of the basin in the axial direction was 7 m, the mean width in the transverse direction about 217 m and the mean depth 11.8 m. The tracer study was carried out in October 211, when in the basin no thermal stratification was observed. The tracer study employed an amount of NaF equal to 18 kg that was diluted with about 5, m 3 of the lagoon water and introduced in the basin in 12 hours, in order to simulate a pulse injection. The amount of tracer added was fixed in order not to exceed the threshold concentration of 1.5 mg/l (maximum concentration value allowed in drinking water, Italian D.Lgs. 31/1) under the hypothesis that the lagoon was not mixed at all (plug flow modality). Fluoride concentration values at the outlet channel of the basin were recorded, using a fluoride selective probe (ISE25F, Radiometer Analytical), every 45 minutes, until day 29 th from the introduction of the tracer, when the observed concentration values were lower than the probe detection limit. Samples were also collected at 15 points (over 3 depth values, for a total of 45 sampling points) throughout the lagoon, 1, 7 and 14 days after the introduction of the tracer. The determination of fluoride concentration was performed using a Dionex DX 32 ion chromatograph.

3 2.1. RTD curve development and actual residence time calculation The record of the fluoride concentration versus time at the outlet channel of the basin produces the RTD (Residence Time Distribution) curve (or E curve, Levenspiel, 1999), which is the record of the length of time that each fluid element takes to pass through the system. RTD curves are usually normalized in order to permit the comparison of the results from different experimentation campaigns (Teixeira Costa and Siqueira do Nascimento, 28). The normalization is done by dividing the measured concentrations (C) by the initial average concentration (C ), which is the ratio between the mass of the tracer that was injected into the flow and the effective volume of the lagoon, and the time (t) by the theoretical retention time ( ), which is the ratio between the effective volume (V) and the flow rate (Q). The fluoride concentration values recorded at the outlet channel of the basin were averaged on daily base, in order to obtain a single concentration value for each day. According to Levenspiel (1999), the actual mean residence time (t ) of the fluid in the lagoon could be calculated by determining the value of the first moment of the RTD distribution, as in (1): t = t C dt C dt 2.2. Mass balance development - Comparison between the mass of the tracer found in the lagoon and the mass predicted by a mass balance The amount of fluoride found in the basin during the sampling campaign, 1, 7 and 14 days after the introduction of the tracer, calculated by multiplying each of the 45 concentration values for the portion of basin volume of competence, was compared with the amount of fluoride resulting from the mass balance equation, as in (2): C i V = C i-1 V - Q C i-1 t (2) where C i V is the mass of fluoride in the basin at the i-day (with i = 1 29); C i-1 V is the mass of fluoride in the basin at the (i-1)-day; Q is the inflow and outflow rate, equal to 115 L/s; C i-1 is the concentration of fluoride at the outlet channel of the basin at the (i-1)day; t is the discretization time, equal to 1 day. The balance described in (2) may be applied under the hypothesis that the concentration at the outlet channel of the basin, at the i-day, is constant for all the length of the day (that is the concentration recorded by the fluoride selective probe every 45 minutes was daily averaged) CSTR Model The data obtained as in paragraph 2.2 were compared with the data gathered from the CSTR (continuous stirred-tank reactor) model. The application of the CSTR model considers that the mass of fluoride introduced in the basin (68,4 g) was perfectly mixed with the whole volume to obtain the so-called initial average concentration, C, with an identical concentration value in every point of the basin and, consequently, at the outlet channel of the basin. The discretization time employed was one day Axial dispersion coefficient According to several authors (Nameche and Vasel, 1998; Burrows et al., 1999; Levenspiel, 1999; Makinia and Wells, 25), the dispersion model is based on the ideal plug flow model and deviations caused by back mixing or random fluctuations. By (1)

4 applying Fick s law in the longitudinal (x) direction only and assuming steady state conditions, equation (3) describes the concentration for a general point in a tank at time t, D x 2 C t x 2 = u C t + C t x t where Dx is the axial dispersion coefficient, Ct the concentration of tracer at time t, and u the average longitudinal velocity. The ratio Dx/uL is the dispersion number (or mixing parameter or inverse Peclet number, dimensionless), where L is the length of the basin in the axial direction. It indicates if the flow patterns in the basin are described as plug flow or completely mixed or an intermediate situation. If the dispersion number tends towards zero, the reactor approximates to the ideal of plug flow. According to Levenspiel (1999), the dispersion number is directly linked to the variance of the RTD. The RTD curve obtained in a tracer study with an impulse signal can be used to estimate the D x value by the relationship between t 2 and D x using Laplace transforms for a closed system (D x( C/ x) = at inlet and outlet) and constant D x value through the basin (Makinia and Wells, 25): (3) σ 2 t = 2 D x 2 ul (D x ul ) [1 exp ( )] (4) ul D x Variance, t2, for any experimental response curve can be calculated from a dimensionless plot of concentration and time: σ 2 t = (t t 1)2 Cdt Cdt Where t is the actual mean residence time for the C vs. t distribution. Combining and rearranging equations (4) and (5), a value of the dispersion coefficient, D x, can be calculated from field data of C and t. 3. RESULTS AND DISCUSSION The initial average concentration, C, as defined in paragraph 2.1, was equal to g/l. This value was obtained by dividing the mass of fluoride introduced in the lagoon (68,4 g) by the volume of the basin. The normalized RTD curve is shown in Figure 1. The actual mean residence time (t ) was calculated as in (1) and was equal to about 12.8 days. The calculated actual mean residence time value is consistent when almost 1% of the tracer is recorded at the exit of the basin. In fact, according to Broughton and Shilton (212), a common mistake in tracer studies is that they are finished too early and the missing tracer leads to misreporting of the mean residence time and, as a consequence, of dead space. Even though, according to Delatolla and Babarutsi (25) there is currently no consensus on the correct method of developing the tail portion of a RTD curve, Levenspiel (1999) illustrated that in systems with non-ideal flow patterns such as dead zones, the tracer concentration at the outlet often begins to decrease exponentially after a certain amount of time elapses. (5)

5 1,2 1 Dimensionless tracer response mass of F- in the lagoon (g),8,6,4,2,2,4,6,8 1 1,2 1,4 1,6 1,8 Dimensionless time Figure 1. Normalized hydraulic residence time distribution. With reference to the calculation of t, it has to be taken into account that the results of the mass balance on the fluoride ion, described in detail in paragraph 2.2, demonstrated that at the end of the monitoring campaign (day 29 th from the introduction of the tracer) the mass of fluoride in the lagoon was still 755 g, a bit less than 12% of the amount introduced. For this reason, we thought it was necessary to develop the tail portion of the RTD curve by interpolating the experimental data from day 1 st to day 29 th with a best-fit curve. The equation of the best-fit curve was C =.519 e -.72 t (R 2 =.9427) The tail portion of the curve was then developed from day 29 th to day 43 th, when the residual mass of fluoride in the lagoon was about 3 g, less than 5% of the amount introduced experimental data calculated from mass balance calculated from CSTR model day Figure 2. Comparison between the mass of the tracer found in the lagoon, the mass predicted by the mass balance and the mass predicted by CSTR model The actual mean residence time at the outlet channel of the basin, where closed conditions are respected, can be compared with the theoretical residence time. This comparison gives some information about the flow pattern such as the magnitude of the dead volume or the short circuiting flow rate. Thus, the existence of a dead volume is indicated by t / < 1, while it is possible to conclude that a short circuiting flow rate exists if the same ratio is greater than unit. In our case the ratio t / was.71 and, according to

6 mg F-/L Delatolla and Babarutsi (25), the basin active volume, Va, that may be calculated as in the equation Va = Qa t, where Qa is the active flow, usually equal to the theoretical flow, Q, was about 1,27, m 3, 7% of the theoretical volume. a b c Figure 3. Distribution of the fluoride concentration in the lagoon at the depth of 1 m - at the day 1 st (a), 7 th (b) and 14 th (c) after the tracer introduction The amount of fluoride detected in the basin during the sampling campaign, 1, 7 and 14 days after the tracer introduction, was compared with the amount calculated using the mass balance developed as in (2). There is a very good agreement between the values predicted by the mass balance and those found in the lagoon. In particular, with reference to the three couples of values, it can be seen that at the day 1 st the mass balance overestimated the real amount of about 3.5%; on the other hand, the values calculated at days 7 th and 14 th were lower than the real ones of about 16% and 1% respectively (see Figure 2). The results of the lagoon monitoring at day 1 st, 7 th and 14 th after the introduction of the tracer, processed by means of Surfer software, are shown in Figure 3. The distribution of the fluoride concentration in the basin during the monitoring period is such that may be assumed a good mixing in the whole basin volume. In fact, Figure 2 shows a good correspondence between the masses of fluoride in the basin calculated from the mass balance described as in (2) and the masses of fluoride predicted by the CSTR model. However, the results of Figure 2 highlight that CSTR model slightly overestimated the amount of fluoride in the basin particularly after the first part of the monitoring period.,45,4,35,3 experimental data Dx 2 m2/d Dx 5 m2/d Dx 2 m2/d Dx 328 m2/d Dx 5 m2/d,25,2,15,1, day Figure 4. Comparison between the tracer concentration found at the exit of the lagoon and the values predicted by the one-dimensional model for different Dx values

7 With reference to the determination of dispersion number and axial dispersion coefficient, the variance of the RTD calculated as in (5) resulted to be equal to Consequently, the dispersion number was 1.25 and the axial dispersion coefficient, considering the average longitudinal velocity equal to 38.9 m/d and the length of the basin in the axial direction 7 m, about 32,8 m 2 /d. According to Burrows et al. (1999), a basin which approximates to a single CSTR will have a larger dispersion number (greater than.2), indicating a high degree of longitudinal mixing. The obtained value of the dispersion number is in line with both the trend of Figure 2 and the distribution of fluoride concentration in the basin shown in Figure 3, thus suggesting that the behaviour of the basin could be reliably described by a CSTR model. The obtained Dx value has been inserted in the analytical solution of (3), also known as Sauty equation, c(x, t) = M (x ut)2 exp [ ] 4D x t 4πD x t and the curves for Dx = 2,; 5,; 2,; 32,8 and 5, m 2 /d have been calculated (M, mass per unit of transversal surface, 26.8 g/m 2 and u, water velocity in the lagoon, 38,9 m/d). As in Figure 4, there was not a good correspondence between the curve at Dx equal to 32,8 m 2 /d (axial dispersion coefficient calculated from the tracer test results) and the outline of the fluoride concentration in time at the outlet channel of the basin. The marked difference between the two curves may be due to the inappropriateness of the model employed, which was a one-dimensional dispersion model. In fact the conditions required for the appropriate application on the afore mentioned model are that the longitudinal dispersion must be independent of position, the transverse dispersion must be very high with respect to the longitudinal dispersion and there should be no flow variations along the flow path. We can probably say that in our case conditions number 1 and 3 are fulfilled but, because of the width extent and the characteristics of the basin inflow, condition 2 is far from being complied.,5,45,4 experimental data calculated by means of Wilson and Miller equation,35,3 mg F-/L,25,2,15,1, day Figure 5. Comparison between the tracer concentration found at the exit of the lagoon and the values predicted by the two-dimensional model (Dx = 48, m 2 /d; Dy = 7 m 2 /d) Due to the failure of the one-dimensional model, a two-dimensional model was applied. Under the hypotheses of a linear vertical source and a pulse injection, the twodimensional model can be solved by the so-called Wilson and Miller equation, as in (6):

8 m c(x, y, t) = exp [ (x ut)2 y2 ] 4πbt D x D y 4D x t 4D y t (6) Where: m, amount of fluoride introduced in the lagoon, 68,4 g; b, vertical extent of the fluoride source, i.e. lagoon depth, 11.8 m (calculated as the ratio between the volume and the surface of the lagoon); u, water velocity in the lagoon, 38,9 m/d; Dx and Dy axial and transverse dispersion coefficient, unknown. The best Dx and Dy coefficients were found 48, m 2 /d and 7 m 2 /d, respectively (see Figure 5). With reference to Figure 4, this result shows that it is necessary to use a twodimensional model, in fact the one-dimensional model predicted concentrations lower than the real ones, hypothesizing a very quick mixing along the y direction. On the contrary, the three-order of magnitude difference between the Dx and Dy coefficients, found by applying the two-dimensional model, underlined a slower mixing along the y direction and, as a consequence, the failure of the one-dimensional model. 4. CONCLUSIONS This study was aimed to investigate the internal hydrodynamic behavior of a 15-ha artificial basin employed by the WTP of the city of Turin as a pretreatment on natural waters destined to the potabilization treatment processes. From the interpretation of the tracer response (determination of the actual residence time and mixing parameter) and tracer distribution in the lagoon during a one-month monitoring period, it appears that the system was efficiently mixed without relevant short circuits. In fact the first detection of the tracer at the outlet channel occurred after very few hours from the beginning of the test and the mean residence time of the lagoon, determined using the value of the first moment of the RTD distribution, in the presence of the flow rate used for the test, was about 13 days compared with a theoretical hydraulic residence time of 18 days. This assured that dissolved contaminants (like fluoride) brought to the drinking water treatment plant from the river were efficiently diluted by the lagoon before entering the plant. REFERENCES 1. Arceivala S.J. (1981) Hydraulic modeling for waste stabilization ponds (discussion). J. Environ. Eng. 19 (19), Broughton A. and Shilton A. (212) Tracer studies on an aerated lagoon, Wat. Sci. Tech., 65 (4), Burrows L.J., Stokes A.J., West J.R., Forster C.F. and Martin A.D. (1999) Evaluation of different analytical methods for tracer studies in aeration lanes of activated sludge plant, Wat. Res., 33 (2), Delatolla R.A. and Babarutsi S. (25) Parameters Affecting Hydraulic Behavior of Aerated Lagoons, ASCE J. Environ. Eng., 131 (1), Levenspiel O. (1999) Chemical Reaction Engineering, 3 rd Ed. Wiley, New York. 6. Makinia J, and Wells S.A. (25) Evaluation of empirical formulae for estimation of the longitudinal dispersion in activated sludge reactors. Wat. Res., 39, Marecos do Monte M.H.F. and Mara D.D. (1987) The Hydraulic Performance of Waste Stabilization Ponds in Portugal, Wat. Sci. Tech. 19 (12), Nameche TH. and Vasel J.L. (1998) Hydrodynamic studies and modelization for aerated lagoons and waste stabilization ponds. Wat. Res. 32 (1), Polprasert C. and Bhattarai K.K. (1985) Dispersion model for waste stabilization ponds, ASCE J. Environ. Eng. Div. 111 (1), Teixeira Costa E. and Siqueira do Nascimento R. (28) Performance Assessment of Hydraulic Efficiency Indexes, ASCE J. Environ. Eng., 134 (1), Torres J.J., Soler A., Sáez J., Leal L.M. and Aguilar M.I. (1999) Study of the internal hydrodynamics in three facultative ponds of two municipal WSPS in Spain, Wat. Res. 33 (5),