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Resource-Efficient Characterisation of Pit Latrine Sludge for Use in Agriculture

Author

Listed:
  • Khumbo Kalulu

    (Department of Environmental Health, Faculty of Applied Sciences, University of Malawi—The Polytechnic, P/Bag 303, Chichiri, Blantyre 312225, Malawi)

  • Bernard Thole

    (Department of Physics and Biochemical Sciences, Faculty of Applied Sciences, University of Malawi—The Polytechnic, P/Bag 303, Chichiri, Blantyre 312225, Malawi)

  • Theresa Mkandawire

    (Department of Civil Engineering, Faculty of Engineering, University of Malawi—The Polytechnic, P/Bag 303, Chichiri, Blantyre 312225, Malawi)

  • Grant Kululanga

    (Department of Civil Engineering, Faculty of Engineering, University of Malawi—The Polytechnic, P/Bag 303, Chichiri, Blantyre 312225, Malawi)

Abstract

Resource recovery through reuse of by-products of the sanitation chain presents a great potential towards ensuring universal access to safely managed sanitation. Many developing countries are faced with uncertainty over public and environmental health concerns associated with use of faecal sludge in agriculture. Due to resource constraints, limited data exists on the characteristics of faecal sludge to inform proper and safe use in agriculture. Despite predictive characterisation being demonstrated to be a resource-efficient approach to generate data in other fields, its application in agricultural resource recovery from faecal sludge is lacking in the literature. This paper explored predictive modelling as a less resource-intensive approach for characterisation of nutrients and pathogens in faecal sludge. Specifically, it investigated the extent to which gravimetric parameters could predict nutrients and pathogens in pit latrine sludge from informal settlements in the cities of Malawi. The study explored predictive models to estimate total ammoniacal nitrogen (TAN), total phosphorus (TP), E.coli and helminth eggs from gravimetric parameters (total solids [TS] and total volatile solids [TVS]) in pit latrine sludge. The models developed in the study allow substantially reliable estimation of TAN (R 2 pred = 75.4%) and TP (R 2 pred = 78.2%); they also provide moderately reliable predictions for E.coli (R 2 pred = 69.1%) and helminth eggs (R 2 pred = 74.3%) from total solids. Since total solids are easy and inexpensive to measure, the models present an option that can reduce resource requirement for characterisation of pit latrine sludge for informed decision-making when using pit latrine sludge in agriculture. In the absence of data on faecal sludge characteristics at the national level, the models provide a starting point for estimation of pathogens and nutrients in sludge for agricultural use. However, stepwise refinement of the models needs to be done through their validation for different types of sludge and inclusion of spatially available demographic, technical and environmental (SPA-DET) data.

Suggested Citation

  • Khumbo Kalulu & Bernard Thole & Theresa Mkandawire & Grant Kululanga, 2021. "Resource-Efficient Characterisation of Pit Latrine Sludge for Use in Agriculture," Sustainability, MDPI, vol. 13(9), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4702-:d:541556
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    References listed on IDEAS

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    1. Koottatep, Thammarat & Fakkaew, Krailak & Tajai, Nutnicha & Pradeep, Sangeetha V. & Polprasert, Chongrak, 2016. "Sludge stabilization and energy recovery by hydrothermal carbonization process," Renewable Energy, Elsevier, vol. 99(C), pages 978-985.
    2. Katherine Junglen & Leandra Rhodes-Dicker & Barbara J. Ward & Emily Gitau & Wali Mwalugongo & Lindsay Stradley & Evan Thomas, 2020. "Characterization and Prediction of Fecal Sludge Parameters and Settling Behavior in Informal Settlements in Nairobi, Kenya," Sustainability, MDPI, vol. 12(21), pages 1-13, October.
    3. Christophe BELLEGO & Louis-Daniel PAPE, 2019. "Dealing with the log of zero in regression models," Working Papers 2019-13, Center for Research in Economics and Statistics.
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