IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i7p1125-d218097.html
   My bibliography  Save this article

Agent-Based Modelling for Simulation-Based Design of Sustainable Faecal Sludge Management Systems

Author

Listed:
  • Adrian Mallory

    (School of Water, Environment and Engineering, Cranfield University, Cranfield MK43 0AL, UK)

  • Martin Crapper

    (Department of Mechanical and Construction Engineering, Northumbria University, Ellison Place, Newcastle Upon Tyne NE1 8ST, UK)

  • Rochelle H. Holm

    (Centre of Excellence in Water and Sanitation, Mzuzu University, P/Bag 201, Mzuzu 2, Malawi)

Abstract

Re-using faecal sludge (FS) to generate value has the potential to contribute towards solving the issue of long term sanitation solutions in growing urban areas across sub-Saharan Africa; however, hitherto, no design tools have been available that are capable of simulating a system involving economic factors, complex social issues and environmental circumstances. We hypothesized that Agent-Based Modelling (ABM), when deployed with appropriate rigour, can provide such a tool. Extensive field work was carried out in a Malawian city, investigating the adoption of Skyloo above-ground composting toilets by households, and the operation of the municipal FS site. 65 semi-structured interviews and 148 household interviews, together with observations, were carried out to characterize these processes, with the data acquired being used to construct two separate ABMs. The Skyloo ABM was run for various scenarios of start-up capital for business and payback of loans against the toilet cost to households. The municipal FS Site ABM was run for different patterns of dumping fee and enforcement structure. The field work demonstrated that there is potential for further expansion of FS reuse, with a market for agricultural application. The Skyloo ABM identified the significance of start-up capital for a business installing the toilet technology; the municipal FS Site ABM showed that existing fees, fines and regulatory structure were insufficient to reduce illegal dumping of FS to any useful degree, but that a monthly permit system would provide enhanced revenue to the city council compared with per-visit charging of disposal companies at the municipal FS site. Whilst each ABM ideally requires some additional data before full application, we have, for the first time, shown that ABM provides a basis for the simulation-based design of FS management systems, including complex social, economic and environmental factors.

Suggested Citation

  • Adrian Mallory & Martin Crapper & Rochelle H. Holm, 2019. "Agent-Based Modelling for Simulation-Based Design of Sustainable Faecal Sludge Management Systems," IJERPH, MDPI, vol. 16(7), pages 1-19, March.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1125-:d:218097
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/7/1125/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/7/1125/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rochelle Holm & Jealous Mwangende & Mavuto Tembo & Wales Singini, 2017. "Bacteriological quality of fresh produce and link to water and sanitation service access from informal markets in Mzuzu, Malawi," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(6), pages 2487-2497, December.
    2. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    3. Laciana, Carlos E. & Oteiza-Aguirre, Nicolás, 2014. "An agent based multi-optional model for the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 254-265.
    4. Charles F. C. Chirwa & Ralph P. Hall & Leigh-Anne H. Krometis & Eric A. Vance & Adam Edwards & Ting Guan & Rochelle H. Holm, 2017. "Pit Latrine Fecal Sludge Resistance Using a Dynamic Cone Penetrometer in Low Income Areas in Mzuzu City, Malawi," IJERPH, MDPI, vol. 14(2), pages 1-13, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rich, Karl M. & Ross, R. Brent & Baker, A. Derek & Negassa, Asfaw, 2011. "Quantifying value chain analysis in the context of livestock systems in developing countries," Food Policy, Elsevier, vol. 36(2), pages 214-222, April.
    2. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    3. Claudia Dislich & Elisabeth Hettig & Jan Salecker & Johannes Heinonen & Jann Lay & Katrin M Meyer & Kerstin Wiegand & Suria Tarigan, 2018. "Land-use change in oil palm dominated tropical landscapes—An agent-based model to explore ecological and socio-economic trade-offs," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-20, January.
    4. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
    5. Shahadha, Saadi Sattar & Wendroth, Ole & Zhu, Junfeng & Walton, Jason, 2019. "Can measured soil hydraulic properties simulate field water dynamics and crop production?," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    6. Ruiyao Ying & Li Zhou & Wuyang Hu & Dan Pan, 2017. "Agricultural technical education and agrochemical use by rice farmers in China," Agribusiness, John Wiley & Sons, Ltd., vol. 33(4), pages 522-536, September.
    7. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    8. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    9. Jason Wood & James Nolan, 2021. "Plant location decisions in the ethanol industry: a dynamic and spatial analysis," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 103-132, June.
    10. Elodie Letort & Pierre Dupraz & Laurent Piet, 2017. "The impact of environmental regulations on the farmland market and farm structures: An agent-based model applied to the Brittany region of France," Working Papers SMART 17-01, INRAE UMR SMART.
    11. Nicholas R. Magliocca, 2020. "Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus," Land, MDPI, vol. 9(12), pages 1-25, December.
    12. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    13. Andersen, Lykke E. & Groom, Ben & Killick, Evan & Ledezma, Juan Carlos & Palmer, Charles & Weinhold, Diana, 2017. "Modelling Land Use, Deforestation, and Policy: A Hybrid Optimisation-Heterogeneous Agent Model with Application to the Bolivian Amazon," Ecological Economics, Elsevier, vol. 135(C), pages 76-90.
    14. Balmann, A. & Happe, K. & Kellermann, K. & Kleingarn, A., 2001. "Agricultural policy switchings – an agent-based approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 37.
    15. Berger, Thomas, 2015. "Adaptation of farm-households to increasing climate variability in Ethiopia: Bioeconomic modeling of innovation diffusion and policy interventions," 2015 Conference, August 9-14, 2015, Milan, Italy 229062, International Association of Agricultural Economists.
    16. Carauta, Marcelo & Troost, Christian & Guzman-Bustamante, Ivan & Hampf, Anna & Libera, Affonso & Meurer, Katharina & Bönecke, Eric & Franko, Uwe & Ribeiro Rodrigues, Renato de Aragão & Berger, Thomas, 2021. "Climate-related land use policies in Brazil: How much has been achieved with economic incentives in agriculture?," Land Use Policy, Elsevier, vol. 109(C).
    17. Bert, Federico E. & Rovere, Santiago L. & Macal, Charles M. & North, Michael J. & Podestá, Guillermo P., 2014. "Lessons from a comprehensive validation of an agent based-model: The experience of the Pampas Model of Argentinean agricultural systems," Ecological Modelling, Elsevier, vol. 273(C), pages 284-298.
    18. Rich, Karl M. & Rich, Magda & Dizyee, Kanar, 2018. "Participatory systems approaches for urban and peri-urban agriculture planning: The role of system dynamics and spatial group model building," Agricultural Systems, Elsevier, vol. 160(C), pages 110-123.
    19. Holderieath, Jason, 2016. "Spatiotemporal management under heterogeneous damage and uncertain parameters. An agent-based approach," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235850, Agricultural and Applied Economics Association.
    20. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1125-:d:218097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.