A multiple regression model for prediction of optimal dose of Moringa Oleifera in faecal sludge dewatering. Issue 1 (18th October 2021)
- Record Type:
- Journal Article
- Title:
- A multiple regression model for prediction of optimal dose of Moringa Oleifera in faecal sludge dewatering. Issue 1 (18th October 2021)
- Main Title:
- A multiple regression model for prediction of optimal dose of Moringa Oleifera in faecal sludge dewatering
- Authors:
- Doglas, Benjamin
Kimwaga, Richard
Mayo, Aloyce - Abstract:
- Abstract: Moringa Oleifera (MO) is a highly effective conditioner in the dewatering of Fecal sludge (FS). However, the model for the prediction of its optimal dose has not yet been documented. This article presents the results of the developed model for the prediction of MO optimal doses. The developed model was based on assessing the FS parameters and MO stock solution. The FS samples were obtained from a mixture of a pit latrine and septic tank and were analyzed at the water quality laboratory of the University of Dar es Salaam. The multiple linear regression model was used to establish a relationship between MO optimal dose as a function of FS characteristics (pH, Electrical Conductivity, Total Solids and Total Suspended Solids) and concentration of MO stock solution. The results indicated that the main contributing factors which determine the MO optimal dose were the concentration of MO stock solution, followed by pH of FS. The model results showed a good agreement between the predicted and observed MO optimal dose with a coefficient of determination of R 2 = 0.72 and 0.9 for calibration and validation respectively. Therefore, the model can be adapted to determine the MO optimal dose without running the Jar-test experiment. HIGHLIGHTS: Effect of physical-chemical Faecal sludge characteristics on Moringa Oleifera dose. Physical-chemical predictor of Faecal sludge dewaterability. Concentration of Moringa Oleifera solution on optimal dose of Moringa Oleifera . MoringaAbstract: Moringa Oleifera (MO) is a highly effective conditioner in the dewatering of Fecal sludge (FS). However, the model for the prediction of its optimal dose has not yet been documented. This article presents the results of the developed model for the prediction of MO optimal doses. The developed model was based on assessing the FS parameters and MO stock solution. The FS samples were obtained from a mixture of a pit latrine and septic tank and were analyzed at the water quality laboratory of the University of Dar es Salaam. The multiple linear regression model was used to establish a relationship between MO optimal dose as a function of FS characteristics (pH, Electrical Conductivity, Total Solids and Total Suspended Solids) and concentration of MO stock solution. The results indicated that the main contributing factors which determine the MO optimal dose were the concentration of MO stock solution, followed by pH of FS. The model results showed a good agreement between the predicted and observed MO optimal dose with a coefficient of determination of R 2 = 0.72 and 0.9 for calibration and validation respectively. Therefore, the model can be adapted to determine the MO optimal dose without running the Jar-test experiment. HIGHLIGHTS: Effect of physical-chemical Faecal sludge characteristics on Moringa Oleifera dose. Physical-chemical predictor of Faecal sludge dewaterability. Concentration of Moringa Oleifera solution on optimal dose of Moringa Oleifera . Moringa Oleifera optimal dose model. Moringa Oleifera optimal model validation. … (more)
- Is Part Of:
- Water practice and technology. Volume 17:Issue 1(2022)
- Journal:
- Water practice and technology
- Issue:
- Volume 17:Issue 1(2022)
- Issue Display:
- Volume 17, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 17
- Issue:
- 1
- Issue Sort Value:
- 2022-0017-0001-0000
- Page Start:
- 405
- Page End:
- 418
- Publication Date:
- 2021-10-18
- Subjects:
- dewatering -- faecal sludge -- model -- Moringa Oleifera -- multiple regression -- optimal dose
Sewerage
Sewerage -- Management
Water-supply
Water-supply engineering
Periodicals
628.205 - Journal URLs:
- https://iwaponline.com/wpt ↗
- DOI:
- 10.2166/wpt.2021.099 ↗
- Languages:
- English
- ISSNs:
- 1751-231X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24549.xml