| Literature DB >> 30925829 |
Adrian Mallory1, Martin Crapper2, Rochelle H Holm3.
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.Entities:
Keywords: agent-based modelling; design; faecal sludge; reuse; sub-Saharan Africa; system
Mesh:
Substances:
Year: 2019 PMID: 30925829 PMCID: PMC6479626 DOI: 10.3390/ijerph16071125
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Observed Approaches to Implementing Skyloos.
| Project | Financing Approach | Material Contributions by User | Targeted User | Year of Project |
|---|---|---|---|---|
| 1 | 100% subsidized by donor | No | Urban families of orphaned children through faith-based organization | 2014–2015 |
| 2 | Loan for house and Skyloo combined | No | Urban poor | 2010 |
| 3 | Loans to households from donor fund for urban development | No | Urban residents | 2010–2016 |
| 4 | Loans to households with donor collateral | Bricks and sand with optional further contribution | Urban residents | 2012 |
| 5 | Loan for house and Skyloo combined | Mud bricks | Urban poor without housing | 2007–2010 |
Barriers to Faecal Sludge Management. FS: faecal sludge.
| Stage of FS Chain | Physical/Environmental Barriers | Financial Barriers | Political Barriers | Social Barriers |
|---|---|---|---|---|
| Household Sanitation | Latrines often flood or collapse | People struggle to afford improved sanitation without finance source | Lack of awareness of products | |
| Collection | Poor access to some informal areas Poor road condition approaching municipal FS site | Cost of emptying is often prohibitive for households | Lack of awareness of services | |
| Transport | Private sector dump elsewhere to avoid fees | Council unable to enforce safe disposal | People often shamed for handling FS | |
| Treatment | No fence to prevent access | Disposal tariffs deter businesses from safe disposal | Unable to prevent stealing of sludge and public walking through site | Guard does not have facility or authority to collect fees |
| Reuse | Transport of manure is heavy and expensive | Unclear financial value of product | Reuse unsuited to poorest and disabled members of society | Disconnected market for selling compost |
Figure 1Themes from Skyloo Interviewees.
Figure 2Model structure for Skyloo adoption.
Skyloo Agent-Based Modelling (ABM) Details of Model Setup.
| Model Step | Set Up Details | Justification |
|---|---|---|
| Number of Households | 3026 | Balance of sample size with processing time |
| Owner/Tenant Ratio | 50/50 | Data from city council in case study city |
| Household Size (Mean/Standard Deviation (SD)) | 6/2 | Field work found mean of 5.44 and SD of 2.3 |
| Probability of Already Having a Skyloo | 0.3% | Based on field work covering 100 Skyloos |
| Household Monthly Income (Mean/SD) | MK44,000/MK44,000 | Field work identified mean as MK43,500 and SD as MK43,700 |
| Probability of openness to reuse of FS | 64/148 | Based on answers in field work |
| Skyloo Building Cost and Capacity | Cost MK200,000 (USD276) including cost of mason | Based on answers in field work for Project 4 |
| Business Operating Cost | MK85,000 (USD117.26) | Based on wages for three to four people |
| Probability of a household gaining knowledge and becoming open to Skyloos and FS reuse | 25% from marketing by business | It was not possible to derive a %age success value from marketing as it was not clear how many people had initially been marketed to reach 50 adopters. |
| Business initial contacts | 300 households | Based on field work data including photos shown by past projects and interviews with marketing staff |
Figure 3Results of ABM showing average adoption of Skyloos over 1,000 model runs based on start-up finance and monthly repayment charge in Malawi Kwacha.
Figure 4Cash flow of Business Approaches to Building Skyloos in Malawi Kwacha.
Figure 5Cash flow of Business Approaches to Building Skyloos in Malawi Kwacha.
Pseudocode of Probability Adjusting Algorithm in Game Theory Approach for municipal FS site ABM.
| IF |
Model Parameters and Ranges for ABM of municipal FS Site.
| Item | Initial Value with Reason | Range Tested |
|---|---|---|
| Dumping Charges | Observed Per Visit Charge of MK9,000 (USD12.5) | MK6000–MK15,000 |
| Sludge Value (per 50 kg bag) | Assumed at MK5000 | MK500–MK10,000 |
| Bribe for Guard | Assumed at MK3000 | Multipliers of 1 to 8 to explore value of money paid direct to Guard compared with collecting money for authorities |
| Fine to Companies for Illegal Dumping | Noted as MK2000 | MK2000–MK15,000 |
| Fine to Farmers for Stealing Sludge from municipal FS Site | Based on Interviews, with some allowance for inflation, as MK20,000 | N/A |
| Probability of Guard Presence | Not estimated as site was not in operation during field work | Assumed |
| Time to produce saleable compost from FS | Assumed as six months based on time from sludge entering municipal FS Site to production of compost | N/A |
Figure 6Cash flow of municipal FS Site Management.