Scholarly article on topic 'Optimization of Time Requirement for Rapid Mixing During Coagulation Using a Photometric Dispersion Analyzer'

Optimization of Time Requirement for Rapid Mixing During Coagulation Using a Photometric Dispersion Analyzer Academic research paper on "Chemical engineering"

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Aluminium sulphate / Photometric Dispersion Analyser / PDA / coagulation / flocculation

Abstract of research paper on Chemical engineering, author of scientific article — S. Ramphal, S. Muzi Sibiya

Abstract Coagulation involves the rapid mixing of chemicals with raw water to facilitate particle destabilization. This study used a photometric dispersion analyzer (PDA) coupled to a jar stirrer to monitor kinetics during the optimization of alum. The optimal conditions were as follows: sample pH 8; alum dosage, 6mg/l as Al3+; G-value, 116 s-1, rapid mixing time, 15seconds. Kinetic data revealed that the aggregation rate and steady-state variance significantly influenced coagulation-flocculation performance; while average steady-state ratio displayed a minor influence on performance. The results indicated that the PDA instrument can be employed as an additional tool in the optimization of coagulation conditions.

Academic research paper on topic "Optimization of Time Requirement for Rapid Mixing During Coagulation Using a Photometric Dispersion Analyzer"

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ScienceDirect Procedia

Engineering

Procedia Engineering 70 (2014) 1401 - 1410 -

www.elsevier.com/locate/procedia

12th International Conference on Computing and Control for the Water Industry, CCWI2013

Optimization of time requirement for rapid mixing during coagulation using a photometric dispersion analyzer

S. Ramphal8*, S. Muzi Sibiyaa

aRand Water, Process Technology Department, 52 Impala Road, Glen Vista, 2058, South Africa

Abstract

Coagulation involves the rapid mixing of chemicals with raw water to facilitate particle destabilization. This study used a photometric dispersion analyzer (PDA) coupled to a jar stirrer to monitor kinetics during the optimization of alum. The optimal conditions were as follows: sample pH 8; alum dosage, 6 mg/l as Al3+; G-value, 116

data revealed that the aggregation rate and steady-state variance significantly influenced coagulation-flocculation performance; while average steady-state ratio displayed a minor influence on performance. The results indicated that the PDA instrument can be employed as an additional tool in the optimization of coagulation conditions.

© 2013 TheAuthors.PublishedbyElsevier Ltd.

Selectionandpeer-reviewunderresponsibilityofthe CCWI2013Committee Keywords: Aluminium sulphate, Photometric Dispersion Analyser, PDA, coagulation, flocculation

1. Introduction

Rapid mixing is practiced during coagulation; a unit process, whereby chemical coagulants are mixed with raw water to facilitate particle destabilization. The laboratory procedure for determining the treatability of a water source and determining the optimum parameters (most effective coagulant, required dose rates, pH and coagulation and flocculation time required) is by use of standard jar test experiments. The coagulation-flocculation process, an essential and critical process in potable water treatment facilities, has seen an increase in research efforts focussed towards improving process efficiency by monitoring various parameters (Staaks et al., 2011; Zouboulis et al., 2009).

* Corresponding author. Tel.: +27-16-430-8865. E-mail address: sramphal@randwater.co.za

CrossMark

1877-7058 © 2013 The Authors. Published by Elsevier Ltd.

Selection and peer-review under responsibility of the CCWI2013 Committee

doi:10.1016/j.proeng.2014.02.155

An important design and control parameter during coagulation-flocculation is the size distribution of floc aggregates (Spicer et al., 1996). Aggregation size distribution as well as aggregate structure and density are of great importance in solid-liquid separation processes such as sedimentation (Selomulya et al., 2001). Floc size and structure are determined by several operational parameters and directly influences floc density which controls solid removal efficiency during sedimentation (Spicer and Pratsinis, 1996).

In practise, during coagulation-flocculation, there is a rapid period of floc growth in which the size and structure of the floc aggregates are dynamic in nature. This is followed by a steady state region or equilibrium between particle growth and fragmentation for a specific period, during which, the particle size distribution does not change. The shape of the particle size distribution curve is critical as it influences coagulation-flocculation kinetics, the rate of floc growth, floc characteristics and the solids removal process (Selomulya et al., 2001; Spicer et al., 1996). It is therefore very important to rapidly quantify both size and structure of aggregates to generate a particle size distribution curve with a reasonable amount of accuracy (Selomulya et al., 2001).

One of the most widely used techniques used to determine aggregate structure and size distribution are light scattering techniques. These techniques are advantageous as they offer the estimation of a wide range of particle sizes in a rapid and non-destructive manner (Selomulya et al., 2001). A photometric dispersion analyser (PDA) has become an important instrument that has been widely used in monitoring coagulation-flocculation kinetics (Mixon et al., 2013; Ball et al., 2011; Staaks et al. 2011; Zoubolis and Tzoupanos, 2010, 2009; Xiao et al., 2009; Huang and Liu, 1996).

A PDA is a fibre-optical monitor which measures the fluctuations in the intensity of light transmitted through a flowing suspension (Huang and Liu; 1996). More specifically, it measures the root mean square of the fluctuating signal (Vrms) and the average transmitted light intensity (dc). The ratio of Vrms to dc is a valuable tool in coagulation-flocculation studies as it permits quantification of aggregation or disaggregation of the suspension to be monitored (Huang and Liu; 1996). This ratio can be derived as follows (Xiao et al., 2009):

Ratio =

(C J" (1)

where L is the optical path length, A is the effective cross sectional area of the light beam, Ni is the number and concentration class of size class i and Ci is particle scattering cross-section of size class i respectively. The ratio values obtained from the PDA is affected only byQ] Ni Q2), and is almost entirely unaffected by contamination of the tube walls in the flow cell and by drift in electrical components (Xiao et al., 2009). This study used a PDA instrument to optimize coagulation conditions and monitor coagulation-flocculation kinetics as well as floc growth rate of alum. Standard jar test experiments were performed concurrently with PDA experiments to determine the degree of particle destabilization.

2. Methodology

2.1. Experimental

Fig.1 shows the experimental set up of this study. Jar tests were carried out using a variable speed ZR 4-6 Jar tester (Zhongrun Water Industry Technology Development Co. Ltd, China) fitted with six flat paddle impellors. For each jar test the following procedure was performed. One liter of sample was added to each Perspex jar and adjusted to required pH using either 1 M hydrochloric acid or 1 M sodium hydroxide. Appropriate dosages of alum were dosed into each jar using plastic syringes. Coagulation-flocculation kinetics was determined using the PDA 2000 (Rank Brothers, England). Clear plastic tubing of 3mm in diameter was used to transport samples to the fiber optic probes at a flow rate of 20 ml/min. Sample flow rate was controlled by a peristaltic pump which was placed after the PDA instrument to prevent floc breakage. To ensure comparison of PDA experiments, the DC output of source water was maintained at a constant voltage by adjusting the DC gains on the instrument. A HACH 2100P turbidimeter and a Cary 50-Conc Varian UV-Vis Spectrophotometer was used to measure turbidity and UV300 values respectively. The temperature and pH were measured using a Metrohm 692 pH/ion meter. All titrations were performed using a Schott Titronic 96 auto-titrator while the conductivity was measured using a Labotec 197i conductivity meter.

Tubing

O O n I n I

Jar stirrer

PDA 2000

• •

Peristaltic pump

PDA interface

Computer

Fig. 1. Experimental set up

2.2. Analysis of PDA data

The time dependent ratio values collected during the coagulation-flocculation experiments were represented as a ratio curve (Fig.2). Fig.2 shows that there are two distinct regions with each indicating the evolution of

aggregate size with time at various shear rates (Selomulya et al., 2001). In the initial growth phase, fluid shear promotes particle collision which results in aggregate growth. As these aggregates grow, breakage becomes a more significant factor as the size range of the aggregate is more susceptible fragmentation by turbulent eddies. This results in the attainment of steady state region. During this phase, due to the attainment of a dynamic equilibrium between aggregate growth and aggregate fragmentation, aggregates are of equal size as ratio values remain constant over time (Hopkins and Ducoste, 2003; Spicer and Pratsinis, 1996; Oles, 1992).

Fig. 2. Time dependent ratio curve

In this study, three calculations were used to analyse the data obtained during the coagulation-flocculation experiments. These calculations included the aggregation rate of rapid mixing, average steady-state ratio and steady state variance as described by Mixon et al. (2013); Staaks et al. (2011); Xiao et al. (2009) and Hopkins and Ducoste (2003). The aggregation rate (AR) during coagulation was calculated by:

(Ratio - Ratio0)

AR = ±-i-oJ- (2)

where Ratio0 is the initial ratio value at t0, timei is the time when PDA output reached its maximum value of Ratiov In accordance to work performed by Staaks et al. (2011), initial calculations determined the aggregation rate of the first minute, first to fifth minute and the entire first five minutes. It was found that the aggregation rate for the first minute yielded the best results; hence, this parameter was used for the rest of the study. The average steady-state ratio was determined by:

(Ratiol ,timel)

Ratio = ^' =^N---(3)

¿i =i i

Eq. (3) represents the state of aggregation during the steady state period of coagulation-flocculation. The final calculation used in this study was the steady state variance, which was also computed using the data from the steady state period as follows:

Steady state var iance =

(Ratio. — average Ratio) .time.

Zf= xtimei

Eq. (4) was used as a measure of floc size and structural differences. According to Hopkins and Ducoste (2003), smaller variance is indicative of a tighter floc size distribution and a more homogenous, dense and less porous floc structure.

3. Results and Discussion

3.1. Optimization of pH

Jar test experiments were performed to assess turbidity and UV300 removal at various pH values. This was achieved by adding a constant alum dosage of 10 mg/l to samples adjusted to pH 6 - 9. According to Pernitsky and Edzwald (2006), favorable pH conditions for alum coagulation is generally between a pH of 6 - 7. Fig.3 indicates that the lowest residual turbidity and UV300 was observed at an initial sample pH of 8; corresponding to a coagulation pH of 6.3. The optimal pH also coincided with the minimum solubility of alum, indicating that sweep flocculation is the primary coagulation mechanism through the formation of aluminum hydroxide precipitates (Pernitsky and Edzwald, 2006; Gregor et al., 1997).

Fig. 3. Optimization of pH

One would expect that the largest floc size will correspond to highest coagulation efficiency; in other words, largest floc size should result in the lowest residual turbidity and colour. However, this has not been observed in this experiment as the lowest residual turbidity corresponded to the lowest average steady state ratio and aggregation rate (data not show). Further, at the optimal coagulation of 6.3, sweep flocculation should be the primary coagulation mechanism; hence, one can expect the largest floc sizes to form under these conditions. However, a trend of increasing ratio values was observed with decreasing pH, which corresponds to a shift in aluminum hydrolysis speciation to ionic forms. This strongly suggests the presence of interfering contaminants within the source water. Although there was a lack of correspondence between residual and PDA data, the residual data provided sufficient evidence to indicate that an initial sample pH of 8 was optimal. This sample pH was used for the rest of the study.

3.2. Optimization of dosage

The optimization of alum dosage was performed by adjusting sample pH to 8 while varying the alum dosage from 2 - 12 mg/l. Fig.4a indicates that an alum dosage of 6 mg/l as Al3+ resulted in the lowest residual turbidity and colour. This dosage reduced the pH from 8 to 6.7 which favored sweep flocculation through the formation of aluminum hydroxide precipitates (Srinivasan et al., 1999). Further, the isoelectric point of alum occurs at pH 8

indicating that pH values less than 8 yield positively charged precipitates, which are able to neutralize the negatively charged particles in the water sample (Gregory and Duan, 2001).

Dosage (mg/l)

Dosage (mg/l)

Fig. 4. Optimization of dosage - (a) Residual turbidity and colour; (b) Average steady state ratio; Aggregation rate; (c) Aggregation rate (d) Steady state variance

Fig.4b shows that the largest average steady state ratios were obtained for alum dosage 4 and 6 mg/l as Al3+. Although an alum dosage of 6 mg/l as Al3+ did not represent the largest average steady state ratio value, it displayed the highest efficiency in terms of turbidity and colour removal. This indicates that floc size, although important n coagulation-flocculation processes, is not the most significant parameter. Fig.4c and 4d show an alum dosage of 6 mg/l as Al3+ displayed a higher aggregation rate and lower steady state variance to that of 4 mg/l as Al3+. According to Mixon et al. (2013) and Hopkins and Ducoste (2003) larger steady state variance indicates the existence of a wider range of floc sizes as well as weaker flocs at a particular location. This means that an alum dosage of 6mg/l as Al3+ resulted in a higher floc growth rate and flocs size displayed greater degree of strength and floc size homogeneity. Based on these results, it is possible that these two variables contributed to the enhanced performance of the alum dosage of 6 mg/l as may possible be primary parameters for consideration in

coagulation-flocculation kinetic studies.

3.3. Optimization of mixing intensity

In this experiment, the rapid mixing intensity was varied while applying optimal alum dosage and initial sample pH of 6 mg/l as Al3+ and a pH of 8 respectively. Fig.5a shows that the lowest residual turbidity and colour was obtained during the application of a rapid mixing intensity of 116 s-1. At this velocity gradient, an optimal level of energy is dissipated to ensure efficient coagulation through the instantaneous and even distribution of alum (Degremont, 2007).

Average steadty state ratio ) M -p* CT^ 00 O M ♦ + +

39 67 116 171 212 297

Velocity gradient (s1 )

8 -7 - +

ST 6 -

■.c 5 -

(U 4 -

.E 3 -

> 2 -1 - + . i rfr . . , . | . . , .| . . . i

0 1 1 1 1 | . . . . . . . |i

39 67 116 171 212 Velocity gradient (s1) 297

Fig. 5. Optimization of velocity gradient - (a) Residual turbidity and colour; (b) Average steady state ratio; (c) Aggregation rate; (d) Steady state variance

It may seem appropriate to use high G-values to maximize efficient use of the coagulant; however, there is an upper limit (Bratby, 2006). Once G-values exceed this limit, there is a delay in floc formation and size. This trend can be seen in Fig. 5b and 5c in which the average steady state ratios and aggregation rate peaked at a specific G-value; with further increases in G-values resulting in lower average steady state ratio and aggregation rate values. It can be expected that higher energy dissipation will increase the number of particle collisions; hence the rate of floc break up will increase (Selomulya et al., 2001). This results in the formation of smaller; denser and less porous aggregates which are structurally tolerant of higher shear forces, leading to a lower steady state mean floc size being attained in a shorter period of time (Hopkins and Ducoste, 2003; Spicer and Pratsinis, 2001, Oles 1992). This trend has been observed by various researchers (Hopkins and Ducoste, 2003; Selomulya et al., 2001; Spicer and Pratsinis, 1996).

Fig.5d shows that the steady state variance was significantly higher at lower velocity gradients (< 67 s-1). Mixon et al. (2013) and Hopkins and Ducoste (2003) explained that high steady state variation at lower G values was due to larger aggregates being sheared due to settling into the impellor region. It was observed that as the G value increased, the steady state variance decreased. Increasing shear rate reduced steady state variance indicating the formation of more homogenous floc suspension (Mixon et al., 2013). As observed in prior experiments, the largest average steady state ratio obtained at a velocity gradient of 67 s-1 did not result in the highest efficiency in terms of turbidity and colour removal. Rather, a velocity gradient of 116 s-1 displayed the highest efficiency as it exhibited a higher aggregation rate and lower variance when compared to a velocity gradient of 67 s-1.

3.4. Optimization of rapid mixing time

For this phase of the study, rapid mixing time was varied while applying optimal alum dosage, sample pH and rapid mixing intensity of 6 mg/l as

turbidity and colour was obtained when a rapid mixing time of 15 seconds was applied. This implies that a velocity gradient of 116 s-1 was applied for an optimal period to ensure efficient coagulation through the instantaneous and even distribution of alum.

5 15 30 45

Rapid mixing time (s)

0.25 - +

0.20 - c o ■-C .¡50.15 -> 0.10 - + + + +

0.05 -

5 15 30 45 60

Fig. 6.: Optimization of rapid mixing time - (a) Residual turbidity and colour; (b) Average steady state ratio; Aggregation rate; (d) Steady state variance

Similar to rapid mixing intensity, it may be desirable to apply an optimal velocity gradient for an extended period of time to maximize efficient use of coagulants. However, according to Bratby (2006), extended periods of rapid mixing may give rise to deleterious effects in the coagulation-flocculation process. As such, each application will have an optimal rapid mixing time which is dependent on the rapid mixing intensity and coagulant concentration. The negative effect of prolonged rapid mixing time can be seen in Fig.6a as higher residual turbidity and colour were obtained at longer rapid mixing times.

Fig. 6b indicates that the average steady state ratio values gradually decrease with increasing rapid mixing times. This was expected as prolonged rapid mixing times will expose aggregates to fluid shear rates for a longer period of time. This will delay the floc growth process and allow for a longer period of particle collision; increasing the rate of floc breakup. Selomulya et al. (2001) explained that higher circulation times reduces the time aggregates have to form larger structures prior to fragmentation induced by the high shear stress, hence, a decrease in steady state equilibrium sizes is observed.

In line with observations from previous experiments, the highest average steady state ratio value, obtained from a rapid mixing time of 5 seconds, did not result in the highest coagulation-flocculation performance in terms of turbidity and colour removal. Rather, an optimal rapid mixing time of 15 seconds displayed the highest performance. Kinetic data represented in Fig.6c and 6d indicate that a rapid mixing time of 15 seconds produced the highest aggregation rate and lowest variance. This places further significance on the importance of the aggregation rate and steady state variance in coagulation-flocculation studies.

4. Conclusion

This bench-scale experimental research used a PDA to optimize coagulation conditions; specifically, coagulation pH, coagulant dosage, rapid mixing intensity and rapid mixing time, and monitor coagulation-flocculation kinetics as well as floc growth rate during coagulation-flocculation using alum. Residual turbidity and colour values were also used to rate performance of the coagulation-flocculation process. The results of this study indicate that optimal coagulation-flocculation conditions; i.e. the conditions which yielded the lowest residual turbidity and colour values, were as follows: initial sample pH of 8, alum dosage of 6 mg/l as Al3+, rapid mixing intensity of 116 s-1 and rapid mixing time of 15 seconds. Additional kinetic parameters, namely, the aggregation rate, average steady state ratio and steady state variance were generated using PDA ratio data to gain further understanding of the coagulation-flocculation process.

The kinetic data revealed that in all optimization experiments, the average steady state ratio was a secondary parameter as the largest average steady state ratio did not result in the most efficient coagulation-flocculation performance in terms of turbidity and colour removal. It was found that the aggregation rate and steady state variance were more suitable parameters to assess coagulation-flocculation performance as they had a direct influence on removal efficiency. These parameters may be seen as primary kinetic parameters and should be given greater attention during coagulation-flocculation studies. The results of this study showed that the PDA instrument is an important tool in coagulation kinetic studies and can be employed as an additional tool in the optimization of coagulation conditions.

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