Model for prediction of the optimal dose of Jatropha curcas in FS dewatering. Issue 11 (3rd November 2022)
- Record Type:
- Journal Article
- Title:
- Model for prediction of the optimal dose of Jatropha curcas in FS dewatering. Issue 11 (3rd November 2022)
- Main Title:
- Model for prediction of the optimal dose of Jatropha curcas in FS dewatering
- Authors:
- Benjamin, Doglas Mmasi
Kimwaga, Richard - Abstract:
- Abstract: Jatropha curcas (JC) is a highly effective conditioner in dewatering fecal sludge (FS); however, there are limited studies on the model predicting its optimal dose. This study presents the results of the developed model for predicting JC optimal doses. The developed model assessed the FS parameters and JC stock solution. We analyzed the FS samples from a mixture of a pit latrine and septic tank at the water quality laboratory of the University of Dar es Salaam. The multiple linear regression model was used to establish a relationship between JC optimal dose as a function of FS characteristics (pH, electrical conductivity, total solids, total suspended solids and concentration of the JC stock solution). The results indicated that 90.4% of the JC optimum dosage was determined and contributed by FS characteristics and JC stock solution concentrations. Also, the main explanatory factors determining the JC optimal dose were the JC stock solution concentration, followed by the pH of FS. The model results showed a good agreement between the predicted and observed JC optimal dose with a coefficient of determination of R 2 = 0.904 and 0.7879 for calibration and validation, respectively. Therefore, the model can be adapted to determine the JC optimal dose without running the jar test experiment. HIGHLIGHTS: Effects of physical–chemical characteristics of fecal sludge on Jatropha curcas dose. Physical–chemical predictor of fecal sludge on dewaterability. Concentration of J.Abstract: Jatropha curcas (JC) is a highly effective conditioner in dewatering fecal sludge (FS); however, there are limited studies on the model predicting its optimal dose. This study presents the results of the developed model for predicting JC optimal doses. The developed model assessed the FS parameters and JC stock solution. We analyzed the FS samples from a mixture of a pit latrine and septic tank at the water quality laboratory of the University of Dar es Salaam. The multiple linear regression model was used to establish a relationship between JC optimal dose as a function of FS characteristics (pH, electrical conductivity, total solids, total suspended solids and concentration of the JC stock solution). The results indicated that 90.4% of the JC optimum dosage was determined and contributed by FS characteristics and JC stock solution concentrations. Also, the main explanatory factors determining the JC optimal dose were the JC stock solution concentration, followed by the pH of FS. The model results showed a good agreement between the predicted and observed JC optimal dose with a coefficient of determination of R 2 = 0.904 and 0.7879 for calibration and validation, respectively. Therefore, the model can be adapted to determine the JC optimal dose without running the jar test experiment. HIGHLIGHTS: Effects of physical–chemical characteristics of fecal sludge on Jatropha curcas dose. Physical–chemical predictor of fecal sludge on dewaterability. Concentration of J. curcas solution on the optimal dose of J. curcas . J. curcas optimal dose model. J. curcas optimal modal validation. … (more)
- Is Part Of:
- Water practice and technology. Volume 17:Issue 11(2022)
- Journal:
- Water practice and technology
- Issue:
- Volume 17:Issue 11(2022)
- Issue Display:
- Volume 17, Issue 11 (2022)
- Year:
- 2022
- Volume:
- 17
- Issue:
- 11
- Issue Sort Value:
- 2022-0017-0011-0000
- Page Start:
- 2296
- Page End:
- 2316
- Publication Date:
- 2022-11-03
- Subjects:
- dewatering -- fecal sludge -- Jatropha curcas -- model -- 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.2022.135 ↗
- 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:
- 24490.xml