# Effect of Attached Growth on Treatment Performance in Waste Stabilization Ponds

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Study Site

^{3}day

^{−1}. An aerial map of the two ponds is shown in Figure 2.

#### 2.2. Attached Growth Baffle Selection and Installation

_{m}(the mean residence time) has been reported in Coggins et al. [26] and t

_{n}(the nominal residence time) was calculated by the ratio of pond volume and ideal flow.

#### 2.3. Application of First-Order Kinetics to Determine the Contribution of Baffles on Pond Performance

_{e}, mg L

^{−1}) was estimated by three forms of first-order kinetic models. Model validation was carried out by comparing the modelled results with observed data, then the equation with both accuracy and a simpler calculation formula could be used for the further analysis. Model formulas are as shown in Polprasert and Agarwalla [21], Muttamara and Puetpaiboon [22], and Polprasert and Bhattarai [29]:

_{i}is influent BOD concentration (mg L

^{−1}), the value of ${a}_{1}$ is calculated as ${a}_{1}=\sqrt{1+4ktd}$, where ${a}_{1}$ is one of the terms in kinetic model expression, k (day

^{−1}) is the overall reaction rate, t (day) is residence time, and $d$ is dispersion number. Equation (2) is a more simplified version and suitable for estimating BOD reduction if dispersion number ($d$) is less than 2 [29]. In this study, the value of $d$ was determined by the range obtained from two different formulas in Polprasert and Agarwalla [21] and Polprasert and Bhattarai [29]:

_{*}is shear velocity, which is equal to $u\sqrt{f/8}$; flow velocity (u, m day

^{−1}) is obtained from measured data; $f$, friction factor is equal to 24/Re; Re, Reynolds number, could be calculated by $\left(4LWh\right)/\left[\left(W+2h\right)tv\right]$, where L, W, h are pond dimensions; kinematic viscosity, v (m

^{2}day

^{−1}) was obtained from Von Sperling [30] and determined by 0.325 × T

^{−0.450}for T

_{median}= 20 °C.

^{−1}) in this study as:

_{fs}(day

^{−1}) is the first-order rate constant of suspended biomass, and can be estimated when there is lack of harmful industrial pollutants in ponds as:

_{fss}(day

^{−1})is the standard first-order rate constant, which is equal to 0.056 per day at 20 °C; and L

_{0}(kg ha

^{−1}day

^{−1}) is organic loading rate.

_{s}(m

^{2}m

^{−3}) was calculated for biofilm attached area without attached growth after Polprasert and Agarwalla [21] and Polprasert and Bhattarai [29] as:

_{f}/D

_{w}was chosen as 0.5, that is, between the reported ratio of aerobic and anaerobic biomass, which is similar to pond conditions [21]. The ratio of D

_{f}/D

_{w}is used for determining the values of D

_{f}and D

_{w}, which were taken as 24.45 × 10

^{−6}m

^{2}day

^{−1}and 48.9 × 10

^{−6}m

^{2}day

^{−1}, respectively. D

_{f}is used for the calculation of the characteristic biofilm parameter ∅.

_{s}, m), biofilm thickness (L

_{f}, m), and first-order constant rate of biofilm biomass (k

_{fa}) are derived from Polprasert and Agarwalla [21]. k

_{fa}is adjusted based on the biofilm density range of 0.027–0.115 g cm

^{−3}[31]. L

_{f}is adjusted based on the phenomenon found in Muttamara and Puetpaiboon [22], that is, an increase in baffle number would lead to an increase in total biofilm biomass but a decrease in biofilm thickness. θ is the temperature coefficient, with Mara [32] and Thirumurthi [33] calculating the value of θ as 1.05 and 1.036, respectively, and this is used for adjusting k

_{fa}and k

_{fs}. All equations are summarized in the Supplementary Material in Table S1.

#### 2.4. Baffle Impacts Analysis and Generalization of Kinetic Model

^{−1}day

^{−1}. To extend the application of the kinetic model for a more generalized expression of pond performance, three loading rates, shown in Table 2, were used to further analyse the impacts of hydraulics and biofilm on BOD reduction. Equation (5) was utilised for calculating the dispersion number (d) as previously validated with full-scale pond data [21]. The hydraulic retention time was modelled from 0 to 30 days.

^{−3}m, and (2) to reduce the thickness of the biofilm. The increment uses for both increased and decreased conditions selected in this study was 5 × 10

^{−5}m.

#### 2.5. Statistical Analysis

## 3. Results

#### 3.1. Hydraulics and Attached Growth

#### 3.2. Application of Kinetic Model

#### 3.2.1. Model Validation

#### 3.2.2. Calculating BOD Reduction of Different Scenarios

#### 3.2.3. Generalisation of Kinetic Model

^{2}m

^{−3}, which is approximately equal to the area of one installed baffle. The degradation efficiency of BOD increases with the increasing residence time but the rate gradually slows down (Figure 8b). Overall, the pond is more efficient in treating influent with higher organic loading, and the increasing biofilm area has a more obvious effect in ponds with lower organic loadings. The largest efficiency improvement is in the 0.5× loading scenario, which is about 6%. The maximum values for improvement under 1× and 3× organic loading are ~4% and ~1.4%, respectively.

#### 3.3. Water Quality

## 4. Discussion

#### 4.1. Hydraulic Improvement and Attached Growth

#### 4.2. Analysis of the Improvement of Pond Performance

#### 4.3. The Influence of Biofilm Thickness Changes on Pond Performance

#### 4.4. The Influence of Increasing Biofilm Area on Pond Performance

^{2}m

^{−3}to 1.64 m

^{2}m

^{−3}and it was found that BOD treatment efficiency increased by ~12%. This result shows that it is possible to have an obviously positive effect on pond performance if the specific surface area is increased a significant amount. However, for a water hyacinth pond unit as presented in Polprasert and Khatiwada [51], the increased specific surface area is related to the stocking density of the water hyacinth plant [51], which is rare in operational WSPs. Additionally, in the study pond, an increase in biofilm area from 0.82 m

^{2}m

^{−3}to 1.64 m

^{2}m

^{−3}is equivalent to the surface area of more than 82 baffles—this is very unrealistic. In general, although the increase in biofilm area does not significantly improve the treatment efficiency at the experimental scale of this study, a considerable improvement could be achieved when the biofilm area is significantly increased. Thus, further investigation is required to determine how this could be realistically applied in WSPs to maximize improvement in pond performance while improving hydraulics.

#### 4.5. The Analysis of First-Order Kinetic Model Formula

_{fa}, D

_{w}, D

_{f}, L

_{f}, and L

_{s}were varied by ±10%, and d was adjusted based on the range of two different formulas. The results showed that d and k

_{fa}are the most sensitive parameters to the model results but the differences with the initial results are not significant and both are within the range of ±1.5%. The parameters D

_{w}, D

_{f}, L

_{f}, and L

_{s}produced less variation (within ±0.5%) in BOD removal efficiency. Furthermore, the effluent concentration will vary within ±1 mg L

^{−1}depending on the precision of the values used in the calculation. The results of the sensitivity analysis provide a direction for the further improvement of the kinetic model, such as adjusting the d value more carefully and measuring the value of k

_{fa}in experiments.

#### 4.6. The Relationship among Water Quality Indicators

#### 4.7. Recommendations

- Exploring and considering the interplay between hydraulics and suspended biomass in the kinetic model.
- Including the correlation between biofilm structure and development in the model formula.
- Performing longer field experiments and increasing the frequency of water quality data collection. In this study, the attached growth baffles were installed in Pond 2 at the study site for 13 months, however, the water quality data was limited after removing the outliers.
- Measuring all the result-sensitive values in the first-order kinetic model formula (e.g., k
_{fa}). - The choice of baffle material would be more flexible: choosing baffles without the ability of attached growth, which will lower their cost.
- Exploring methods and materials to greatly increase attached growth area to maximize the effect of both hydraulics improvement and attached growth.

## 5. Conclusions

## Supplementary Materials

^{−1}) of Equations (2)–(4).

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 1.**A conceptual illustration of a biofilm model in a facultative pond. This model involves substrate mass balances in bulk liquid flow and biofilm. Waste transportation is governed by diffusion and dispersion [21,22]. R

_{suspended}and R

_{biofilm}represent the biological oxygen demand (BOD) removal efficiency when considering suspended or biofilm biomass only, respectively. L

_{f}refers to the biofilm attached on baffles and pond floor and walls. In this study, the total removal is considered as the sum of R

_{suspended}and R

_{biofilm}.

**Figure 2.**Aerial view of the study site with two facultative ponds (Image: NearMap). Three perpendicular baffles were installed in Pond 2 in 2014. Inlets and outlets are indicated by white arrows, and the ponds equally share a total inflow of up to 770 m

^{3}day

^{−1}.

**Figure 3.**Process for selecting the material for the attached growth baffles used in this study. (

**a**) Strips of different geotextiles were deployed in pond for two months, and then samples (

**b**) were taken of each to determine which had the best adhesion ability. In determining best adhesion ability, samples were subject to (

**c**) nutrient and chlorophyll-a analysis and (

**d**) biomass analysis after filtration.

**Figure 4.**Temporal comparison of biofilm matrices formed on the test baffle strips using scanning electron microscopy (SEM) collected after (

**a**) two and (

**b**) seven months. After two months the biofilm shows greater microbial diversity, whereas the biofilm at seven months is rich in extracellular polymer substances (EPS).

**Figure 5.**Spatial change in biofilm matrix in the water column (along the baffle test strip) after seven months, shown using scanning electron microscopy (SEM). At the top of the water column (

**a**) a thicker biofilm developed that decreased towards the middle (

**b**) and bottom (

**c**) of the water column.

**Figure 6.**Relationship between selected water quality variables and the baffle samples taken at three points through the water column. Five variables were selected for analysis: volatile suspended solids (VSS); total suspended solids (TSS), including TSS samples and TSS values recorded from particulate carbon and nitrogen samples; attached carbon content (C); and chlorophyll-a (chl-a). Here, it can be seen that (

**a**) VSS, (

**c**) C, and (

**e**) chl-a are more abundant and have a larger range in the upper water (top) column (b, d, f, respectively). Samples collected in the middle and lower parts of the water column (middle and bottom) have similar interquartile ranges for VSS (

**b**) and chl-a (

**f**) content. In the linear analyses (

**a**,

**c**,

**e**), dashed lines represent the line of best fit and R

^{2}reflects the strength of fit. Log transformations for chl-a values are natural log. In boxplots (

**b**,

**d**,

**f**), boxes show quartiles 1 (25%) and 3 (75%) with the median, whiskers show the minimum and maximum values, and dots indicate outliers.

**Figure 7.**Comparison of biological oxygen demand (BOD) removal efficiency under three scenarios, 0.5× (red), 1× (green), and 3× (blue) loading, shown as: (

**a**) hydraulic improvement only, (

**b**) hydraulic improvement with a decrease in biofilm thickness, and (

**c**) effect of decreasing biofilm thickness only, calculated as the difference between scenarios shown in (

**a**,

**b**). The reduction of biofilm thickness within a certain range does not have a significant impact on final effluent quality.

**Figure 8.**Comparison of biological oxygen demand (BOD) removal efficiency under three scenarios, 0.5× (red), 1× (green), and 3× (blue) loading, shown as: (

**a**) hydraulic improvement only, (

**b**) hydraulic improvement with an increase in biofilm area, and (

**c**) effect of increasing biofilm area only, calculated as the difference between scenarios shown in (

**a**,

**b**). The increase in biofilm area has a more obvious impact on ponds receiving lower organic loading.

**Figure 9.**Biplots of results of principle component analysis (PCA) for (

**a**) Pond 1 and (

**b**) Pond 2 (baffled pond). In Pond 1 (

**a**), all the selected water quality parameters are negatively correlated with PC1 but positively correlated with each other. In Pond 2 (

**b**), TN, TP, and TSS show an inverse trend along PC1, whereas PC2 has higher loadings in temperature, BOD, and COD and shows a positive relationship.

**Figure 10.**Biplot from PCA analysis of the distribution of water samples collected in Pond 1 and Pond 2. Compared with Pond 1, samples collected in the baffled pond have a smaller weighting in PC1 and similar significance in PC2.

**Table 1.**BOD removal scenarios for the application of kinetic model of Pond 2. Some of the scenarios are derived from Coggins et al. [26].

Scenario | Characteristics |
---|---|

1 | No baffles (control pond) |

2 | Three perpendicular baffles, no attached growth |

3 | Three perpendicular baffles with attached growth |

4 | One island + three perpendicular baffles, no attached growth |

5 | One island + three perpendicular baffles with attached growth |

**Table 2.**Scenarios for generalising the kinetic model in BOD removal efficiency prediction. There are three organic loading rates and each were tested with three distinct sets of characteristics, making nine scenarios.

Organic Loading Rate | Characteristics |
---|---|

As in the experiment (1×) | With hydraulic improvement but no attached growth. |

Three times that of the experiment (3×) | With hydraulic improvement and change in biofilm thickness. |

Half that of the experiment (0.5×) | With hydraulic improvement and increased in biofilm area. |

**Table 3.**Best computed (using Equation (2)) and observed BOD concentration of effluent (mg L

^{−1}) and removal efficiency (%).

Parameter | Pond 1 | Pond 2 (Baffle) |
---|---|---|

Raw water | 200 | 200 |

Observed | 89 | 64 |

Estimated | 89.68 | 65.48 |

Suspended biomass only | 134 | 116 |

Actual treatment efficiency | 55.5% | 68% |

Estimated treatment efficiency | 55.16% | 67.3% |

BOD reduction by suspended biomass only | 34% | 42% |

Parameters | Unit | Pond 1 | Pond 2 (Baffled) | Comment |
---|---|---|---|---|

d | - | 0.35 | 0.39 | Equations (5) and (6) give the range of 0.336–0.445 for Pond 1 and 0.383–0.400 for Pond 2. |

a_{s} | m^{2} m^{−3} | 0.822 | 0.858 | Equations (9) and (10) |

k_{fs} | day^{−}^{1} | 0.0366 | 0.0366 | Equation (8) |

k_{fa} | day^{−}^{1} | 199 | 199 | Adjusted based on the assumed biofilm density 0.03 g cm^{−3}. |

D_{f} | m^{2} day^{−}^{1} | 24.45 × 10^{−6} | 24.45 × 10^{−6} | Assumed based on reasonable principle. |

D_{w} | m^{2} day^{−}^{1} | 48.9 × 10^{−6} | 48.9 × 10^{−6} | Assumed based on reasonable principle. |

L_{f} | m | 1.54 × 10^{−3} | 1.386 × 10^{−3} | Assumed based on reasonable principle. |

L_{s} | m | 200 × 10^{−6} | 200 × 10^{−6} | Assumed based on reasonable principle. |

Scenario | Residence Time (days) | Specific Surface Area (m^{2}/m^{3}) | BOD Removal Efficiency | Compared to Control Pond | Comparison of with and without Attached Growth |
---|---|---|---|---|---|

No baffles | 14 | 0.822 | 60.4% | 0 | ---- |

Three perpendicular baffles, no attached growth | 17 | 0.822 | 65.6% | +5.3% | 0 |

Three perpendicular baffles with attached growth | 17 | 0.858 | 67.3% | +6.9% | +1.6% |

One island + three perpendicular baffles, no attached growth | 22.4 | 0.822 | 74.4% | +14.1% | 0 |

One island + three perpendicular baffles with attached growth | 22.4 | 0.882 | 75.7% | +15.3% | +1.2% |

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## Share and Cite

**MDPI and ACS Style**

Lian, Y.; Coggins, L.X.; Hay, J.; van de Ven, A.; Ghadouani, A.
Effect of Attached Growth on Treatment Performance in Waste Stabilization Ponds. *Water* **2022**, *14*, 3245.
https://doi.org/10.3390/w14203245

**AMA Style**

Lian Y, Coggins LX, Hay J, van de Ven A, Ghadouani A.
Effect of Attached Growth on Treatment Performance in Waste Stabilization Ponds. *Water*. 2022; 14(20):3245.
https://doi.org/10.3390/w14203245

**Chicago/Turabian Style**

Lian, Yirui, Liah X. Coggins, Jessica Hay, Andrew van de Ven, and Anas Ghadouani.
2022. "Effect of Attached Growth on Treatment Performance in Waste Stabilization Ponds" *Water* 14, no. 20: 3245.
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