Impact of Temperature on Sludge Dewatering ... - ACS Publications

Jan 18, 2012 - Civil Engineering Research Centre, School of Computing, Science and Engineering, The University of Salford, Newton Building,. Salford M...
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Impact of Temperature on Sludge Dewatering Properties Assessed by the Capillary Suction Time Ola Sawalha and Miklas Scholz* Civil Engineering Research Centre, School of Computing, Science and Engineering, The University of Salford, Newton Building, Salford M5 4WT, England, United Kingdom ABSTRACT: The impact of temperature on the filterability of synthetic sludge, using the capillary suction time (CST) test, was investigated. The CST was measured at five temperatures, six total suspended solid (TSS) concentrations, and two funnel geometries. The results were not consistent with the hypothesis that the CST declines at higher temperatures through the lowering of the sludge viscosity. The impact of temperature on the results of CST tests was moderated by other physicochemical properties of the sludge (desorptivity, particle size composition, and chemical constituents) associated with the efficiency of flocculation.

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but also the flocculation properties of the sludge.7 At higher temperatures, the rate of formation and the viscosity of polymers decreases, while the hydrolysis of the polymers into soluble compounds increases.8,9 Consequently, higher temperatures result in changes in flocculation, influencing the density and chemical composition of the suspended particles, and altering settlability and desorptivity.10−12 The implications are that the impact of temperature on sludge dewaterability, and hence the results of CST tests, may not only be due to a change in sludge viscosity, but also the result of temperature induced changes in the efficiency of flocculation. Rationale, Aim, and Objectives. Studies on the impact of temperature on the variability in the results of CST tests are limited, providing the rationale for this study. The overall aim was to test the hypothesis that an Arrhenius-type equation relating temperature to changes in viscosity is inadequate to predict the results of CST tests, and that changes in the density and the chemical composition of the suspended solids must be incorporated into models devised to predict the impact of temperature. Accordingly, the objectives of this study were to determine whether (a) the variability in the CST test results with respect to temperature could be predicted using an Arrhenius-type equation (b) the relationships between the CST test results and the temperature were moderated by changes in the TSS concentration of the sludge (c) temperature induced changes in desorptivity influenced the CST test results (d) the relationships between the CST test results and the temperature were moderated by changes in the chemical composition and particle size distribution of the sludge

INTRODUCTION Background. The dewatering of sludge, defined as “the removal of enough of the liquid portion of the sludge so that it behaves as a solid”1 is a routine process at wastewater treatment plants. The results of dewaterability tests underpin the selection of appropriate dewatering processes including the use of conditioners.1,2 One of the most commonly applied procedures is the CST test.3 The capillary suction time is known to be sensitive to variations in temperature, tending to become lower at higher temperatures.4 It it is possible that the lowering of the CST is caused by the decrease in sludge viscosity with respect to an increase in the temperature, which can be defined using an Arrehenius type equation:5 η(T ) = μ0 e E /(RT )

(1)

where η = the viscosity, T = the temperature, μ0 = a constant coefficient, E = the activation energy, and R = the universal gas constant. This model predicts an exponential decrease in the viscosity with respect to the reciprocal of the temperature.5 For example, eq 1 was calibrated with respect to the viscosity and the solid content of a sample of digested wastewater sludge with the empirical model6 defined by eq 2.

η = Ke1286/ T

(2)

where η = the viscosity, K = an empirical function of the solid volume fraction, and T = the absolute temperature (°C + 273). The parameter K can be defined empirically by eq 3. (3) K = e107C − 9.1 where K = an empirical function of the solid volume fraction, and C = the volumetric fraction of solids. Equation 2 describes a nonlinear decrease in viscosity with respect to a linear increase in temperature for an activated sludge sample having a solid volume fraction of 0.01524 and a shear rate of 3.5 1/s. An Arrehenius-type equation may, however, be inaccurate to predict the impact of temperature on the results of CST tests. This is because temperature not only influences the viscosity, © 2012 American Chemical Society

Received: Revised: Accepted: Published: 2782

August 4, 2011 January 12, 2012 January 18, 2012 January 18, 2012 dx.doi.org/10.1021/ie202381r | Ind. Eng. Chem. Res. 2012, 51, 2782−2788

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Article

MATERIALS AND METHODS

relationships between the log CST and 1/temperature were examined to test this hypothesis. Changes in CST with Respect to Temperature Moderated by TSS. The results of the CST tests were modeled using multiple linear regression (MLR). CST was the dependent variable, and the TSS concentrations, temperature, and funnel geometry (circular or rectangular) were the independent variables. Dummy binary variables were included to represent the funnel geometry, where 0 = circular and 1 = rectangular. Attempts were made to ensure that the model did not violate any theoretical assumptions of MLR.20 The BoxCox test was applied to determine which transformations of the dependent variable would create the best-fitting model.21 A logarithmic transformation was justified since the optimum Box-Cox transformation parameter was λ = 0.0. Polynomial relationships involving squared terms were incorporated to simulate the nonlinear relationships between the CST, TSS, and temperature. The transformations and the exclusion of nine outliers were essential to linearize the relationships between the variables, normalize the residuals, and homogenized the variances. Changes in Desorptivity with Respect to Temperature. Desorptivity characterizes the water retention properties of sludge and is known to influence CST test results. Equation 4 was defined to relate the CST to the water movement through the filter paper.22,23

CST Apparatus. The tests were conducted using a multiradii CST apparatus (model 319) supplied by Triton Electronics Ltd., Essex, United Kingdom. The apparatus consisted of a funnel fitted on a Whatman No. 17 filter paper placed between two plates. The upper plate had one starting and five stopping electrode sensors located at standard distances. The sensors were connected to a digital automated timer. Two types of funnels were used: the standard circular 18 mm (diameter) funnel, and a rectangular funnel (18 × 18 × 20 mm), because previous studies13−17 have indicated that funnel geometry influences the results of CST tests. Synthetic Sludge. The CST tests were carried out using a surrogate synthetic sludge, because real sludge presents problems for experimentation. The filtration properties of real sludge may change over time due to the biological activities of microorganisms. Furthermore, different sludge samples may have different physicochemical properties depending on the age and stage of the treatment, and the environmental conditions at the time of sampling. The synthetic sludge used in this study was developed by modification of published formulas.15,18,19 A 5 g sample of sodium alginate was suspended in 1 L of distilled water, followed by adding 6 g of cellulose fibres. kaolin (23.3 g) and bentonite (11.7 g) were mixed and added to the suspension. The suspension was stirred at 10 rpm for 120 min. A 250 mL aliquot of 146 g/L potassium chloride solution was added, and the mixtures was stirred for 2 min at 10 rpm. Subsequently, calcium chloride (250 mL of 5 g/L) was added, and the mixture was stirred for 3 min at 10 rpm. The final suspension had a TSS concentration of 31.6 g/L. Another five TSS concentrations were prepared by diluting this suspension with different ratios of distilled water. The six TSS concentrations used in this study were 2.30, 5.64, 8.80, 12.10, 15.30, and 31.60 g/L. The physicochemical and dewatering properties of the synthetic sludge (pH, supernatant turbidity, TSS, and viscosity) were compared with those of real (waste activated and digested) sludge samples. Activated sludge with a solid content of 2.2 g/L, waste activated sludge with a solid concentration of 6.3 g/L, and digested sludge with a solid content of 27.4 g/L were found to have similar properties to synthetic sludge with TSS concentrations of 2.3 g/L, 8.8 g/L, and 31.6 g/L, respectively. Experimental Procedure. A replicated multifactorial design was used to measure the impact of temperature and TSS on the results of the CST tests. The sludge samples and the CST apparatus were placed in the laboratory at four or five different temperatures (10, 15, 20, 25°, and 30 °C) for a 24 h period prior to carrying out the CST tests. The target temperatures of the filtrate and the laboratory were monitored, and stabilized over the course of the CST testing sessions. A total of 278 measurements of CST were made, with 5 to 10 replicate measurements for each combination of factors. All CST tests were made using Whatman No.17 papers, with both types of funnel (circular and rectangular) at six sludge TSS concentrations between 2.30 and 31.60 g/L. Prediction of Changes in CST Using an ArrheniusType Equation. If the CST varies with temperature following the Arrhenius model, then it was hypothesized that the relationships between the logarithms of CST and the reciprocals of temperature should be linear.6 Accordingly, the

2

⎛ εh ⎞ CST = ⎜ 2 ⎟ (R2 4 − R14) ⎝a S⎠

(4)

where ε and h = the porosity and the thickness of the filter paper, respectively, a = the inner radius of the circular funnel, S = the desorptivity of the suspension, and R1 and R2 = the radii of the circles associated with the starting and stopping electrode sensors, respectively. When the loss of water is controlled by capillary suction, the amount of filtered water increases proportionally to the square root of time.24 The desorptivity of synthetic sludge samples at four temperatures was therefore estimated in this study from the slope of the line between the cumulative desorbed volume of water per unit area versus the cumulative desorption time, defined in eq 5:

i=S t

(5)

where i = the cumulative desorbed volume of water per unit area (mm = mm3/mm2), t = the cumulative desorption time (min), and S = the desorptivity (mm/min0.5). Changes in CST with Respect to Temperature Moderated by Sludge Composition. Simplified synthetic sludge mixtures were composed by adding each sludge component one at a time, and measuring the CST at five different temperatures for each formula. The CST estimates were obtained using the standard apparatus with a circular funnel. The logarithmically transformed CST values with respect to five temperatures (°C) and eight different formulations of synthetic sludge were compared using multifactorial ANOVA. The logarithmic transformations homogenized the variances and normalized the residuals. The relative sizes of floc particles in synthetic sludge samples containing different ingredients were estimated using the image analyzing device Malvern Master Sizer Laser Radiation class 3B laser product. The samples were exposed to a He−Ne laser 2783

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with respect to the reciprocals of the temperature. The results were therefore not consistent with the hypothesis that the CST declines at higher temperatures through the lowering of the sludge viscosity.4−6 It is evident that other processes moderated the relationship between the temperature and the CST test results, These processes are considered below. Changes in CST with Respect to Temperature Moderated by TSS. MLR was performed to construct the model defined by eq 6:

with a wavelength of 632.8 nM. The particle size detection range of the device was between 0.05 and 880 μm.

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RESULTS AND DISCUSSION Prediction of Changes in CST Using an ArrheniusType Equation. The plots of log CST versus 1/temperature were nonlinear and did not reflect Arrhenius-type relationships (Figure 1). The logarithms of CST did not consistently decline

log CST = 4.22 + 0.301TSS − 0.005TSS2 − 0.229T + 0.006T 2 − 0.206F

(6)

where CST = the capillary suction time (s), T = temperature (°C), TSS = the total suspended solids (g/L), and F = funnel geometry (0 = circular and 1 = rectangular). The R2 value was 96.3% implying an excellent fit of the experimental data to the model. All the regression coefficients were significantly different from zero at p < 0.01. The model predicted that the CST varied nonlinearly with respect to both the temperature and the TSS concentration. The CST was predicted to decrease when the temperature increased from 10 to 20 °C, but to increase when the temperature increased from 20 °C to 25° variations in the TSS moderated the impact of temperature on the CST. This empirical model could not explain how temperature induced physical and chemical processes were associated with variations in the sludge dewaterability. Consequently, further data are provided below to describe some of these processes. Changes in Desorptivity with Respect to Temperature. The estimates of desorptivity varied nonlinearly with respect to the TSS concentrations and the temperatures of the synthetic sludge (Figure 2). Log−linear relationships were, however, visualized between the desorptivity estimates and the sludge concentrations at the four temperatures (Figure 3). The desorptivity consistently declined with respect to an increase in

Figure 1. Relationships between log mean CST (s) with respect to the total suspended solids concentration of synthetic sludge at (a) 2.3, (b) 5.6, (c) 8.8, (d) 12.1, (e) 15.3, and (f) 31.6 g/L and 1/temperature (°C) using circular and rectangular funnels.

Figure 2. The relationships between desorptivity, total suspended solids (TSS), and temperature. 2784

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whereas a high desorptivity indicated that the sludge exhibited low water retention ability. The CST estimates would decrease when the temperature of the sludge increased from 10 to 20 °C, but would increase when the desorptivity of the sludge decreased from 20 to 25 °C. Consequently, the observed relationships between temperature and desorptivity were consistent with the predictions of the empirical model defined in eq 6. Temperature induced variations in desorptivity and hence the CST test results were associated with temperature induced changes in sludge composition as described below. Changes in CST Moderated by Sludge Composition. The results of the CST tests (mean CST(s) ± 95% confidence intervals) with respect to temperature (°C) using eight different sludge formulas are presented in Figures 4a and 4b. Lower CST estimates were obtained for sludges which did not contain KCl (formulas 1, 2, 3, and 4) compared with sludges that contained KCl (formulas 5, 6, 7, and 8). The lowest CST estimates were for formula 1 (sodium alginate + CaCl2) followed progressively by formula 2 (sodium alginate + CaCl2 + bentonite), formula 3 (sodium alginate + CaCl2 + bentonite + kaolin), and formula 4 (sodium alginate + CaCl2 + kaolin). The CST estimates then increased progressively for formula 5 (sodium alginate + CaCl2 + KCl), formula 6 (sodium alginate + CaCl2 + bentonite + KCl), and formula 7 (sodium alginate + CaCl2 + kaolin + KCl). The highest CST estimates were

Figure 3. The relationships between log desorptivity, log total suspended solids (TSS), and temperature.

TSS concentration. The desorptivity tended to increase between temperatures of 10 and 20 °C, but to decrease between temperatures of 20 and 25 °C. A low desorptivity indicated that the sludge exhibited high water retention ability,

Figure 4. Mean capillary suction times(s) ± 95% confidence intervals with respect to temperature (°C) using eight formulations of synthetic sludges: (a) 1 = sodium alginate + CaCl2; 2 = sodium alginate + CaCl2 + bentonite; 3 = sodium alginate + CaCl2 + bentonite + kaolin; 4 = sodium alginate + CaCl2 + kaolin; (b) 5 = sodium alginate + CaCl2 + KCl; 6 = sodium alginate +CaCl2 + bentonite + KCl; 7 = sodium alginate + CaCl2 + kaolin + KCl; 8 = sodium alginate + CaCl2 + kaolin + bentonite + KCl. 2785

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obtained using formula 8 (sodium alginate + CaCl2 + kaolin + bentonite + KCl). The results of multifactorial ANOVA indicated that the log CST estimates varied significantly (p < 0.01) with respect to the different sludge formulas at temperatures between 10 and 30 °C. A significant interaction between temperature and the sludge formulas was found (p < 0.001). This interaction arose because the relationships between the CST estimates and the temperatures varied depending on the composition of the sludges. Figure 5a illustrates that the logarithms of CST

Figure 6. The relative volumes of different particle diameters in different synthetic sludge formulations.

The size distribution of kaolin and bentonite clay particles was unimodal with a maximum particle diameter of 222 μm. The particle size range of sodium alginate was bimodal, with local modes at 30 and 409 μm. Others have reported that the mean floc sizes in samples of activated sludge ranged from 55 to 311 μm.26 The mean particle size of 222 μm observed in the synthetic activated sludge formulated in this study was therefore within the expected range for real sludge. The addition of calcium chloride or potassium chloride to sodium alginate resulted in changes in the particle size distribution, with modes at 16 and 647 μm, including relatively higher frequencies of larger particles between 400 and 700 μm. The elevated frequency of larger particles was assumed to be associated with the influence of calcium and potassium ions on the flocculation behavior of the sodium alginate, kaolin, and bentonite particles. This process has been demonstrated in previous studies25, and is defined by the Divalent Cation Bridging theory. 27 High concentrations of monovalent potassium cations displace the divalent calcium cations within the flocs, causing deterioration in floc formation, due to a lack of bridging by the potassium ions. The presence of potassium ions weakens the bridging of the flocs. Larger flocs are broken up into smaller flocs, resulting in an increase in the number of smaller particles, with a reduction in sludge filterability, and a consequent increase in the CST test results. In addition, there are several surface interactions that affect colloid suspensions behavior such as electrostatic repulsion which result in complex system behavior including floc deterioration.27 Practical Implications. The main purpose of conducting the CST tests at a wastewater treatment plant is to save operational costs by evaluating the optimal dose of the sludge conditioner, defined as the dose of coagulant that yields the minimum capillary suction time or resistance to filtration.28 A reduction in the CST by over 50% can be achieved by an optimal use of conditioners.29−32 The total cost of sludge treatment at a wastewater treatment plant is highly variable, because of the different amounts of conditioner needed and the different methods used for dewatering.32 Low operational costs can be achieved if the most efficient conditioning and dewatering processes are used. Any evaluation of the conditioning process must therefore take into account the reduction in the cost of dewatering that can be achieved, offset against the cost of dosing with the conditioner.32 A recent report estimated that current sludge disposal costs are about $US 130 per cubic yard (£GB 65 per m3).33 Because waste disposal requirements are becoming more

Figure 5. Relationships between log CST(s) and temperature using eight different formulations of synthetic sludges. The synthetic sludge formulations were as follows: (a) 1 = sodium alginate + CaCl2; 2 = sodium alginate + CaCl2 + bentonite; 3 = sodium alginate + CaCl2 + bentonite + kaolin; 4 = sodium alginate + CaCl2 + kaolin, (b) 5 = sodium alginate + CaCl2 + KCl; 6 = sodium alginate +CaCl2 + bentonite + KCl; 7 = sodium alginate + CaCl2 + kaolin + KCl; 8 = sodium alginate + CaCl2 + kaolin + bentonite + KCl.

declined linearly with respect to the temperatures when the four sludges (formula 1, 2, 3, and 4) did not contain KCl. Figure 5b illustrates, in contrast, that the log CST increased linearly with respect to temperature using formula 5 (sodium alginate + CaCl2 + KCl). The CST estimates remained consistently high using formulas 6, 7, and 8, which included KCl, bentonite and/or kaolin. The results indicated that KCl in the presence of kaolin and bentonite was the most important ingredient responsible for promoting consistently high measurements of CST at temperatures between 10 and 30 °C. An increase in temperature from 10 to 25 °C was associated with an increase in the CST in the synthetic sludge consisting of sodium alginate, CaCl2, and KCl. These results confirmed the results of other studies that sludge dewaterability is strongly influenced by the presence of cations, specifically potassium and calcium.25−26 The relative volumes of different particle sizes in the sludge formulas containing different ingredients were estimated. The results are illustrated in Figure 6. 2786

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restrictive, and disposal sites are filling up rapidly, the cost of waste sludge disposal is likely to rise. It is therefore very important for wastewater treatment plants to optimize the conditioning process. If the estimates of the CST are inaccurate and imprecise, then operational costs could be elevated. The relationship between CST and temperature has an impact on evaluating the conditioner dosage. The mean CST estimates in this study were found to generally decline between 10 and 20 °C, but generally increased between 20 and 25 °C. The calibration and interpretation of the dose−response curves used by water treatment operators to predict the optimum dose of conditioner could therefore be influenced by fluctuations in the ambient temperature in the laboratory. The CST of synthetic waste activated sludge was found in this study to vary by as much as 50% when the temperature varied by as little as 5 °C. This implies that if a dose−response curve was calibrated using CST values estimated at 15 °C in the laboratory, but the temperature of the sludge in the treatment plant was actually 20 °C, then the CST of the plant sludge would be less, and the conditioner dose would be in excess. If the dose−response curve was calibrated when the laboratory sludge temperature was 20 °C, but the temperature of the plant sludge was 25 °C, then the conditioner dosage would be insufficient.

REFERENCES

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CONCLUSIONS The findings are significant because the interpretation of all CST test results performed at different temperatures is questionable. However, it might be possible to estimate temperature-adjusted CST values in cases where temperature and other sludge quality variables have been measured. The nonlinear relationships observed between the CST test estimates and the temperature were the consequence of multivariate interactions between several temperature-controlled processes. The variability in the CST test results with respect to temperature could not be predicted using an Arrhenius- type equation. The relationships between the CST test results and the temperature were moderated by changes in the suspended solids concentration, desorptivity, chemical composition, and particle size distribution of the sludge associated with variations in the flocculation behavior of bentonite, kaolin, and sodium alginate induced by the presence of cations. The results of this study have practical implications with respect to the interpretation of the dose−response curve of CST versus conditioner concentration used at wastewater treatment plants. If the estimates of the CST are inaccurate and imprecise due to the impact of temperature on the variability of the test results, then operational costs could be elevated.

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Article

AUTHOR INFORMATION

Corresponding Author

*Tel.: +44 161 295 5921. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors would like to thank Triton Electronics (Essex, England, United Kingdom) and Christopher Hall (The University of Edinburgh) who provided very valuable feedback regarding earlier paper drafts. Andy Hollis proof-read this paper. 2787

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(27) Nguyen, T. P.; Hankins, N. P.; Hilal, N. A comparative study of the flocculation behaviour and final properties of synthetic and activated sludge in wastewater treatment. Desalination 2007, 204, 277. (28) Wu, C. C.; Lee, D. J.; Huang, C. Determination of optimal dose of polyelectrolyte sludge conditioner considering particle sedimentation effects. Adv. Environ. Res. 2000, 4, 245. (29) Guan, J.; Amal, R.; Waite, T. D. Effect of floc size and structure on biosolid capillary suction time. Water Sci. Technol. 2003, 47, 255. (30) Hou, C.-H.; Li, K.-C. Assessment of sludge dewaterability using rheological properties. J. Chin. Inst. Eng. 2003, 26, 221. (31) Lai, C. K.; Chen, G.; Lo, M. C. Salinity effect on freeze/thaw conditioning of activated sludge with and without chemical addition. Sep. Purif. Technol. 2004, 34, 155. (32) Wang, J. S.; Liu, J. C.; Lee, D. J. Dual conditioning of sludge utilizing polyampholyte. J. Environ. Eng. 2005, 131, 1659. (33) Watersense Inc. Reducing sludge volume with organic polymer. Available on line at: http://www.gowatersense.com/reducingsludge. html (accessed August 2011).

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