The increasing organic loads, specifically biochemical oxygen demand (BOD5) and chemical oxygen demand (COD), in water bodies has necessitated greywater treatment before disposal. Limited studies have explored sorption kinetics of BOD5 and COD removal using activated carbon from palm kernel shell in fixed-bed columns. This study investigated continuous sorption using activated carbon from palm kernel in removing BOD5 and COD from domestic greywater. The activated carbon had a density of 0.46 g cm−3 and a surface area of 584 m2 g−1. The experiment was conducted in a 37 cm high, 2.5 cm diameter Perspex column, with varying flowrates of 5–15 mL min−1, and bed depths of 10, 15, and 20 cm. Greywater with BOD5 concentration of 251 mg L−1 and COD of 421 mg L−1 was used for this study. Effluent was collected at specified time intervals, analyzed for BOD5 and COD, and fitted to the Thomas, Yoon–Nelson, Adams–Bohart, and Bed Depth Service Time (BDST) models. The Yoon–Nelson model exhibited good agreement, as compared to Thomas and BDST while the Adams–Bohart model showed lower fit. The adsorbent demonstrated sorption capacities of 34 mg g−1 for BOD5 and 56 mg g−1 for COD, suggesting its potential for greywater treatment, particularly in BOD5 and COD removal.

  • The research explored the use of palm kernel activated carbon in a column experiment to reduce BOD and COD in domestic grey water.

  • No research has explored this reduction in a column experiment.

  • Adsorption data were fitted to the column models.

  • The research established that it is possible to reduce BOD and COD to acceptable levels using a local waste material.

  • Using waste materials is environmentally beneficial.

Increasing concerns regarding the impact of untreated greywater on the environment have prompted the need for stricter environmental regulations governing the discharge of both industrial and domestic wastewater. Greywater, which can differ in both volume and quality, is influenced by various factors. It has been noted that the composition of greywater is influenced by elements such as cooking and cleaning methods, personal hygiene habits, biodegradability, frequency of water usage prior to disposal, and sanitary practices (Oteng-Peprah et al. 2018). Over the past few decades, growing recognition of the ecological consequences associated with organic loads has resulted in heightened requests for the treatment of greywater before it is released into natural bodies of water (Kurniawan et al. 2021). Of particular interest is the concentration of BOD5 and COD in greywater discharged into the environment. High levels of BOD5 and COD in water can lead to oxygen depletion, altered ecosystem balance, nutrient imbalance and impaired water quality (Ademiluyi et al. 2009; Alewi et al. 2021). These can lead to pollution and may have detrimental effect on aquatic life and water quality. The Ghana Environmental Protection Agency (Ghana. 2000) has set the limit for the concentration of the discharge of BOD5 and COD at 50 mg L−1 and 150 mg L−1 respectively. However, wastewater discharged into the environment are mostly above this regulatory limit. To meet the discharge guidelines, greywater from households and industrial settings will require an appreciable level of treatment. Chemical, biological, and physical methods are the conventional approaches employed to treat wastewater containing organic substances. Among the various physico-chemical processes utilized in wastewater treatment, adsorption techniques have emerged as the most extensively employed and effective means (Patel et al. 2021). One of the most efficient and simple methods for removal of BOD5 and COD from greywater is adsorption which is much preferred due to its ease of use and wide-scale application. This technique is quite popular due to its simplicity as well as the availability of a wide range of adsorbents. Activated carbon remains one of the most widely used range of adsorbents. It remains one of the most effective and widely used adsorbents because of its excellent adsorption ability (Mohammad-Khah & Ansari 2009). It has been prepared from many substrates over the years, however, commercial grade activated carbon comes with a higher price tag as compared to those prepared with low-cost materials (Bulut et al. 2007; Errais et al. 2011; Sartape et al. 2013; Nayl et al. 2017). Batch adsorption experimental designs are the most commonly utilized tests by many researchers in assessing the suitability of potential adsorbents because of its simplicity and low cost (Crini et al. 2008). Data obtained from batch studies are usually used to construct isotherms which are considered a critical step in the design and optimization of the adsorption process (Hamdaoui & Naffrechoux 2007; Behnamfard & Salarirad 2009). Many studies have reported removal of BOD5 and COD in batch systems using various adsorbents (Bansode et al. 2004; Devi et al. 2008; Nayl et al. 2017) but little has been known on the removal of BOD5 and COD in a fixed-bed column application. Of particular interest is the batch study by Oteng-Peprah et al. (2019) which reported BOD5 and COD removal from domestic greywater using activated carbon prepared from palm kernel shell. It has been reported that the data obtained under batch conditions are generally not applicable in most systems or do not mimic what happens in the real world (Patel & Vashi 2012). Therefore, in order to validate the data obtained in this batch study there is the need to perform column studies to provide data for direct application to large scale use. There exist many studies that have assessed batch and column studies of many contaminants in wastewater. However, little has been known on column study on greywater targeting the continuous removal of BOD and COD. The aim of this study is therefore to investigate the adsorption capacity of the Palm Kernel Activated Carbon (PKAC) in a fixed-bed column with regards to BOD5 and COD removal. The PKAC investigated in this study has previously been shown to be effective in removing BOD5 and COD from greywater in a previous study under batch conditions (Oteng-Peprah et al. 2019). The breakthrough curves are analyzed using Adams–Bohart, Thomas, Yoon–Nelson and the BDST models to determine the characteristic parameters of the column useful for process design.

Column adsorption model

To design a column adsorption process, it is important to predict the breakthrough curve or concentration-like profile and adsorption capacity of the adsorbent for the selected adsorbate under a given set of operating conditions. It is also necessary to determine the maximum sorption column capacity which is a significant parameter for any sorption system. For analysis of the experimental breakthrough curves under different conditions, these common models were used, thus, the Thomas, Yoon–Nelson, Adams–Bohart models and the bed-depth service time (BDST) model.

The Thomas model

The Thomas model (Thomas 1944) is one of the most general and widely used models in column performance theory. It is based on the assumption that the process follows Langmuir kinetics with no axial dispersion and the rate driving force follows second order reversible kinetics (Futalan et al. 2011). It is represented by Equation (1) as shown:
(1)
where kTh is the Thomas rate constant (mL min−1 mg−1) qo is the maximum solid-phase concentration of solute (mg g−1); w is the mass of the adsorbent in the column (g); Q is the flow rate (ml min−1); Ci is effluent concentration (mg L−1) and Co is the influent concentration (mg L−1).

A plot of ln(Co/Ct – 1) against t gives a straight line from which the values of kTh and qo are determined from the intercept and the slope respectively.

Adams–Bohart

This model assumes that the adsorption rate is proportional to both the residual capacity of the adsorbent and the concentration of the adsorbing species. The model is mostly used for the description of the initial part of the breakthrough curve (Han et al. 2008). It is expressed by Equation (2) as shown:
(2)
where Ct is the effluent concentration (mg L−1), Co is the influent concentration (mg L−1), kAB is the kinetic constant (L mg−1 min−1), No is the sorption capacity (mg L−1), Z is the bed-depth (cm), u the linear velocity (mmh−1) and t is the time (h).

A plot of ln(Co/Ct – 1) against t gives a straight line from which the model constants kAB and No can be determined from the slope and intercept.

Yoon–Nelson

This model is based on the assumption that the rate of decrease in the probability of adsorption for each adsorbate molecule is proportional to the probability of adsorbate adsorption and the probability of adsorbate breakthrough on the adsorbent (Han et al. 2008). This model is less complicated and requires no detailed data concerning the characteristics of sorbate, the type of adsorbent and the physical properties of the sorption bed (Yoon & Nelson 1984). It is expressed by Equation (3) as shown:
(3)
where Ct is the effluent concentration (mg L−1), Co is the influent concentration (mg L−1), KYN is the rate constant (min−1), τ the time required for 50% sorbate breakthrough and t is the time (min).

A linear plot of ln(Ct/C0-Ct) against time t gives a straight line where KYN and τ are determined from the intercept and slope.

Bed depth service time (BDST)

This is a simple semiempirical model used in fixed-bed analysis to predict the performance of an adsorbent. It is based on the assumption that the rate of adsorption is controlled by surface reaction between the adsorbate and the unused capacity of the adsorbent (Han et al. 2008; Singha & Sarkar 2015). It is expressed by Equations (4) and (5) as:
(4)
A plot of t versus bed-depth Z gives a straight line from where No and Ko can be evaluated from the slope and intercept respectively
(5)
where Ci is the effluent concentration (mg L−1), Co is the influent concentration (mg L−1), Zo is the critical bed-depth, Ko is the rate constant, Z is the bed-depth (cm), F is the vertical velocity (cm min−1).

Greywater samples

Greywater for this experiment was obtained from domestic sources within University of Cape Coast community, Ghana.

The samples were stored, refrigerated and transported to the laboratory in an ice chest after the field parameters were analysed onsite. The greywater was filtered to remove large and floating objects and their initial concentrations determined. The pH was determined using a Horiba U-50 multiparameter water quality meter; the BOD5 was measured using the Lovibond BD 606 system, and the concentration of chemical oxygen demand (COD) was determined using the closed reflux colorimetric method as stated in (APHA) 5220D. To ensure quality assurance, blank sample was prepared using 50 mL of distilled water and treating it with the same reagents for both BOD5 and COD analysis.

Material processing

The palm kernel shell was obtained from a local palm oil mill in Cape Coast Ghana. The material is cleaned several times with distilled water to eliminate any dirt and water-soluble impurities. The cleaned shells were then airdried in a laboratory drier for 8 hours and then further oven dried at 110 °C in a Heratherm gravity convection laboratory oven for 24 hours in order to remove any surface moisture. The dried samples were then size reduced to desired sizes (2–6 mm) using a laboratory crusher and sieves. The activated carbons were prepared by physical activation with steam at 800 °C and steam flowrate at 120 mL hr−1. After the activation process, the samples were taken out and washed with distilled water to remove any residual ash that might be on the carbons.

The density of the materials was determined by using an ultra-pycnometer 1000 after it had been dried at 105 °C in an oven for 24 hours. The surface area Brunauer–Emmet–Teller SBET was determined using a Micromeritics tristar 3000 system.

Fixed-bed column experiments

The fixed-bed column experiments were carried out to assess the performance of palm kernel activated carbon in removing BOD5 and COD from greywater. This was conducted in a 25 mm inner diameter and 37 cm length Perspex glass column. Palm kernel activated carbon of average particle size of 2 mm was loaded into the Perspex glass column. Glass beads were placed at the bottom of the column to provide support for the adsorbents and placed at the top to prevent the adsorbents from being pulled with the overflow. All experiments were conducted at room temperature with a pH of 7.3 and the direction of flow was from top to bottom using a peristaltic pump. The effluents were collected at regular intervals and the BOD5 and COD concentrations determined. Flowrate and bed-depth were varied in these experiments. Flowrates of 5, 10 and 15 mL min−1 were used to analyze the effect of flowrate variations while bed-depth of 10, 15 and 20 cm were used to analyze the effect of different bed-depth on the column performance. Before the column experiment, deionized water was circulated through the column in order to wet the entire adsorbate and remove any dirt residue on the surface of the carbon.

Physical characteristics of the activated carbon

The apparent density of palm kernel activated carbon (PKAC) was determined to be 0.46 g cm−3. The recommended range of densities for activated carbon is within 0.4–0.5 g cm−3 (TIGG 2019) which implies that PKAC falls within the recommended densities for commercial activated carbon. The BET surface area obtained for PKAC was 620 m2 g−1. The recommended range of surface area of commercial activated carbon has been estimated to be 500–1,500 m2/g. this shows that the surface area for PKAC falls within the recommended surface area for commercial grade activated carbon. A similar study by Hidayu & Muda (2016) on characterization of activated carbon using palm kernel shell obtained surface area of 584 m2 g−1. The slight variations in the surface area recorded for this study may be due to the activation method that was used. A higher BET generally suggests higher adsorption capacity because the carbon has wider surface to allow for adsorption under different conditions.

Effect of flow rate on BOD5 and COD removal

The effect of BOD5 and COD removal in a fixed bed column by using three different flowrates was studied. The breakthrough curves obtained at different flowrates (5, 10, 15 mL min−1), constant inlet concentration (BOD5 = 252 mg L−1, COD = 421 mg L−1) and bed-depth of 20 cm are presented in Figures 1 and 2 respectively. As can be seen from the figures, the breakthrough time, as well as the exhaustion time, increased with decreasing flowrate for both BOD5 and COD removal. The slopes of these plots show a decrease in duration from breakthrough time to exhaustion time as the flowrate is increased from 5 to 15 mL min−1. This is supported by the increase in the steepness of the breakthrough curves as the flowrate decreases. The reason for the high breakthrough time associated with low flowrates can be due to increased contact time of the greywater with the activated carbon which results in higher removal of BOD5 and COD. At high flowrates, the mass transfer rate increases which lead to fast saturation and this is characterized by a reduction in the slope of the curve which is an indication of a high volume of unsaturated zone due to insufficient contact time (Lopez-Cervantes et al. 2018). At lower flowrate, the adsorbate has more time to contact with the adsorbent and this results in high removal of adsorbate in the column (Sheng et al. 2018). Generally, breakthrough points occur faster with higher flowrate for both BOD5 and COD removal. The breakthrough and exhaustion time for BOD5 occurred faster than COD for all the flowrates studied. Results obtained in this study are in agreement with similar studies that used activated carbon from different biomasses (Ademiluyi et al. 2009; Nekoo & Shohreh 2013; Amale et al. 2014) and agricultural waste (Ghaed et al. 2015) to reduce BOD5 and COD concentrations in fixed bed studies.
Figure 1

Breakthrough curves of BOD5 removal by PKAC (pH = 7.3, bed-depth = 20cm, temperature = 25 °C, inlet concentration = 252mg L−1).

Figure 1

Breakthrough curves of BOD5 removal by PKAC (pH = 7.3, bed-depth = 20cm, temperature = 25 °C, inlet concentration = 252mg L−1).

Close modal
Figure 2

Breakthrough curve COD removal by PKAC (pH = 7.3, bed-depth = 20cm, temperature = 25 °C, inlet concentration = 421mg L−1).

Figure 2

Breakthrough curve COD removal by PKAC (pH = 7.3, bed-depth = 20cm, temperature = 25 °C, inlet concentration = 421mg L−1).

Close modal

Effect of bed-depth on BOD5 and COD removal

The effect of bed-depth on the breakthrough curve was studied by using three different bed-depths (10, 15, 20 cm). These were achieved by charging 15, 20 and 26 g representing 10, 15 and 20 cm respectively of the activated carbon into the column. Greywater with initial BOD5 and COD concentrations of 252 mg L−1 and 421 mg L−1 respectively was used as feed to the fixed-bed column at a constant flowrate of 5 ml min−1. The breakthrough curves for BOD5 and COD are presented in Figures 3 and 4 respectively. As it can be seen from the shapes and slopes of each curve, there are slight variations for the different bed-depths. Generally, the breakthrough time increases at higher bed-depths of the adsorbent. As the bed-depth increases from 10 to 20 cm, there is a corresponding decrease in the slope of the breakthrough curve that is observed. The breakthrough time for BOD5 and COD also increased when the bed-depth was increased from 10 to 20 cm. This, therefore, implies that breakthrough and exhaustion times are longer with increasing bed-depth. An increase in bed-depth implies an increase in the surface area and the number of binding sites available for adsorption. This then leads to higher contact time needed for adsorption to take place as suggested by Teutscherova et al. (2018). The exhaustion time which is the time taken for the adsorbent to be totally used up also increased with the increase in height for both BOD5 and COD. There was however a remarkably high exhaustion time for the 20 cm bed-depth for both BOD5 and COD. This could be attributed to increased utilization of the bed. Generally, breakthrough time for BOD5 is shorter than for COD for all the bed-depths studied. From the figures, it can be said that a higher bed-depth indicates a higher BOD5 and COD can be removed due to increase in the surface area of the adsorbent, hence providing more vacant sites for adsorption to take place (Ahmad & Hameed 2010; Futalan et al. 2011). Other researchers have reported similar changes in breakthrough curves with changes in bed-depth using activated neem leaf powder (Patel & Vashi 2015), activated carbon from different biomasses (Ademiluyi et al. 2009; Nekoo & Shohreh 2013; Amale et al. 2014) and agriculture waste (Ghaed et al. 2015) to reduce BOD and COD in similar studies.
Figure 3

Breakthrough curve and bed depth BOD5 removal by PKAC (pH = 7.3, flowrate = 5mL min−1, temperature = 25 °C, inlet concentration = 252mg L−1).

Figure 3

Breakthrough curve and bed depth BOD5 removal by PKAC (pH = 7.3, flowrate = 5mL min−1, temperature = 25 °C, inlet concentration = 252mg L−1).

Close modal
Figure 4

Breakthrough curve and bed depth for COD removal by PKAC (pH = 7.3, flowrate = 5mL min−1, temperature = 25 °C, inlet concentration = 421mg L−1).

Figure 4

Breakthrough curve and bed depth for COD removal by PKAC (pH = 7.3, flowrate = 5mL min−1, temperature = 25 °C, inlet concentration = 421mg L−1).

Close modal

Dynamic models

The Thomas models

The model was applied to the experimental data under conditions of constant influent concentration, different bed-depth and different flowrates. The linearized form of the model was used to determine the Thomas rate constant (kTH) and the bed capacity (qo) of the Thomas equation for both BOD5 and COD. The model parameters which were determined have been presented in Table 1. From the table, it can be seen that kTh for BOD5 and COD decreased with increasing bed-depth at constant flowrate, but increased with increasing flowrate at constant bed-depth. On the other hand, qo for BOD5 and COD increased with increase in bed-depth at constant flowrate, whereas an increase in flowrate at constant bed-depth saw a corresponding decrease in qo. Other studies have reported similar findings in fixed-bed column (Chowdhury et al. 2013; Lin et al. 2013; Nguyen et al. 2015). A maximum bed capacity of 34.4 mg g−1 and 56.93 mg g−1 were obtained for BOD5 and COD respectively at flowrate of 5 mL min−1 and a bed-depth of 20 cm. This maximum bed capacity was obtained at the lowest flowrate and a highest bed-depth. The maximum bed capacity occurring at this point can be due to the fact that at lower flowrates and maximum height, the adsorption capacity is high due to sufficient residence time which allows for effective utilization of the vacant sites before equilibrium is reached as suggested by Tan et al. (2008). A good fit (R2 > 0.98) was obtained for both BOD5 and COD as shown in Table 1. Comparing the kTH between BOD5 and COD, it can be seen that BOD5 has a higher kTH which is an indication of good column adsorption for BOD5 as compared with COD. Comparing the qo, it can also be seen that the qo for COD is higher than BOD5 indicating a higher uptake capacity of the Palm kernel activated carbon to reduce higher proportions of COD than BOD5.

Table 1

Thomas model parameters at different conditions

ParameterInitial concentration (mg L−1)Flowrate (mL min−1)Bed height (cm)kTh (mL min-mg−1) × 10−5qo (mg g−1)R2
BOD5 252 10 7.18 11.13 0.92 
252 15 5.99 13.19 0.96 
252 20 3.61 34.40 0.95 
252 10 20 4.05 31.50 0.96 
252 15 20 4.92 21.26 0.95 
COD 421 10 4.04 23.53 0.89 
421 15 2.92 26.41 0.88 
421 20 2.30 56.93 0.96 
421 10 20 2.85 49.73 0.96 
421 15 20 3.82 32.82 0.97 
ParameterInitial concentration (mg L−1)Flowrate (mL min−1)Bed height (cm)kTh (mL min-mg−1) × 10−5qo (mg g−1)R2
BOD5 252 10 7.18 11.13 0.92 
252 15 5.99 13.19 0.96 
252 20 3.61 34.40 0.95 
252 10 20 4.05 31.50 0.96 
252 15 20 4.92 21.26 0.95 
COD 421 10 4.04 23.53 0.89 
421 15 2.92 26.41 0.88 
421 20 2.30 56.93 0.96 
421 10 20 2.85 49.73 0.96 
421 15 20 3.82 32.82 0.97 

The Yoon–Nelson model

The experimental data were fitted to the Yoon–Nelson model. The linear form of the Yoon–Nelson model was used to determine the mass transfer coefficient (KYN) and the time for 50% breakthrough (τ) and is presented in Table 2. Generally, as the flowrate increases at constant bed-depth, it can be seen that there is a corresponding increase in KYN for BOD5 and COD. Greater mass transfer coefficient (KYN) implies narrower mass transfer zone, greater transfer coefficient between the phases and therefore lower mass transfer resistance. This implies adsorption of BOD5 and COD is easier with higher values of KYN. There is also a corresponding decrease in the time taken to reach 50% breakthrough as flowrate is increased. Brion-Roby et al. (2018) have reported similar changes in the Yoon–Nelson model parameters in a similar study. The changes observed can be attributed to reduced residence time associated with high flowrates. An increase in bed-depth leads to a corresponding reduction in the mass transfer coefficient but an increase in the time taken for 50% breakthrough to be achieved. This could be due to more vacant sites for adsorption to take place and hence a longer time to reach 50% of the breakthrough period. A comparatively good fit (R2 > 0.89) was obtained for both BOD5 and COD as shown in Table 2 which suggests that the Yoon–Nelson model fitted the experimental model for BOD5 and COD in the sorption experiment.

Table 2

Yoon–Nelson parameters at different conditions

ParameterInitial concentration (mg L−1)Flowrate (mL min−1)Bed height (cm)KYN (mL min-mg−1) × 10−2τ (mins)R2
BOD5 252 10 1.81 426.66 0.92 
252 15 1.51 209.38 0.96 
252 20 0.91 521.90 0.95 
252 10 20 1.02 312.57 0.96 
252 15 20 1.24 227.48 0.98 
COD 421 10 1.70 285.02 0.89 
421 15 1.71 365.89 0.96 
421 20 0.95 389.83 0.96 
421 10 20 1.20 295.31 0.96 
421 15 20 1.61 225.36 0.98 
ParameterInitial concentration (mg L−1)Flowrate (mL min−1)Bed height (cm)KYN (mL min-mg−1) × 10−2τ (mins)R2
BOD5 252 10 1.81 426.66 0.92 
252 15 1.51 209.38 0.96 
252 20 0.91 521.90 0.95 
252 10 20 1.02 312.57 0.96 
252 15 20 1.24 227.48 0.98 
COD 421 10 1.70 285.02 0.89 
421 15 1.71 365.89 0.96 
421 20 0.95 389.83 0.96 
421 10 20 1.20 295.31 0.96 
421 15 20 1.61 225.36 0.98 

The Adams–Bohart model

The linear form of the Adams–Bohart model was applied to the experimental data by plotting Ci/Co against t for both BOD5 and COD. This model is based on surface reaction theory and assumes that equilibrium is not instantaneous therefore the adsorption rate is proportional to both the residual capacity of the adsorbent and the adsorbate concentration (Lopez-Cervantes et al. 2018). The values of maximum adsorption capacity (No) and the kinetic constant (KAB) of the model have been calculated and presented in Table 3. Comparatively, the values for BOD5 are higher than COD for all the studied conditions. The values of KAB and No increase with an increase in flowrate for both BOD5 and COD. Additionally, as the bed-depth is increased, the value of KAB decreases while No increases. Similar findings have been obtained in a fixed bed column study (Brion-Roby et al. 2018; Mondal et al. 2018; Xavier et al. 2018). The values of the R2 > 0.78 recorded are lower as compared to the other models studied and thus suggests that the Adams–Bohart model would not be the best model to be used to predict the experimental data in the range of conditions used. This may be due to the fact that the Adams–Bohart model is applied in regions of low concentration and large discrepancies can be found between the experimental and predicted curve if applied outside the concentration range (Karimi et al. 2012).

Table 3

Adams–Bohart model parameters at different conditions

ParameterInitial Concentration (mg L−1)Flowrate (mL min−1)Bed height (cm)kAB (mL min-mg−1) × 10−5No (mg g−1) × 104R2
BOD5 252 10 3.69 .97 0.78 
252 15 3.45 .89 0.87 
252 20 2.26 1.26 0.87 
252 10 20 2.34 1.97 0.91 
252 15 20 2.62 2.34 0.88 
COD 421 10 2.85 1.64 0.86 
421 15 2.40 1.46 0.87 
421 20 1.31 2.05 0.88 
421 10 20 1.62 3.16 0.87 
421 15 20 2.21 3.49 0.92 
ParameterInitial Concentration (mg L−1)Flowrate (mL min−1)Bed height (cm)kAB (mL min-mg−1) × 10−5No (mg g−1) × 104R2
BOD5 252 10 3.69 .97 0.78 
252 15 3.45 .89 0.87 
252 20 2.26 1.26 0.87 
252 10 20 2.34 1.97 0.91 
252 15 20 2.62 2.34 0.88 
COD 421 10 2.85 1.64 0.86 
421 15 2.40 1.46 0.87 
421 20 1.31 2.05 0.88 
421 10 20 1.62 3.16 0.87 
421 15 20 2.21 3.49 0.92 

The BDST model

The experimental results obtained from the column sorption experiment is fitted with the BDST model to determine the sorption capacities and kinetic constants for BOD5 and COD. This is mostly used to predict the relationship between bed-depth (Z) of a fixed bed column and service time. The service time corresponding to bed-depth 10, 15 and 20 cm at a constant flowrate of 5 ml/l at constant inlet concentration of 252 mg L−1 BOD5 and 421 mg L−1 COD were recorded. A plot of the service time versus bed-depths at the different bed-depth is presented in Figure 5. From the slope and intercept of Figure 5, the BDST parameters viz sorption rate constant (k), sorption capacity (No) and critical bed-depth (Zo) were calculated and presented in Table 4. The high values of R2 imply a probable linear relationship for the systems and show that the BDST model can be applied to the continuous column studies.
Table 4

BDST model parameters for BOD5 and COD

NoKaZoR2
BOD5 19,353.60 3.96 × 10−5 4.58 .92 
COD 24,249.60 2.61 × 10−5 5.56 .98 
NoKaZoR2
BOD5 19,353.60 3.96 × 10−5 4.58 .92 
COD 24,249.60 2.61 × 10−5 5.56 .98 
Figure 5

Bed Depth Service Time for BOD5 and COD.

Figure 5

Bed Depth Service Time for BOD5 and COD.

Close modal

The removal of BOD5 and COD from domestic greywater by sorption using PKAC was investigated in a fixed bed column under conditions of fixed inlet concentration, different inlet flowrate and different bed-depths. Based on the experimental results, PKAC has shown to be a very efficient adsorbent in the removal of BOD5 and COD under the studied conditions. The sorption of BOD5 and COD was strongly dependent on flowrate and bed-depth. An increase in bed-depth resulted in increased uptake capacity while an increase in flowrate resulted in a reduced uptake capacity for both BOD5 and COD. A maximum uptake capacity of 35 mg g−1 and 54 mg g−1 was achieved for BOD5 and COD respectively based on the Thomas model. The experimental data fitted well the Thomas, Yoon–Nelson and BDST models. The fit with Adams–Bohart model was comparatively low as compared to the other models used in this study. The Yoon–Nelson provided a better description of the experimental kinetic data in comparison to the Thomas model. This study has established the potential of using a free, locally and abundantly available waste material for the preparation of activated carbon in reducing BOD5 and COD in domestic greywater.

The authors acknowledge funding from the Netherlands government under the NUFFIC project NICHE 194-01.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.

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