Infiltrated pits: using regional groundwater data to estimate methane emissions from pit latrines

Olivia Reddy*, A S M Mostaquimur Rahman, Anisha Nijhawan, Maria Pregnolato, Guy Howard

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)


On-site sanitation systems (OSS), such as pit latrines, are an important source of methane (CH4), with emissions increasing when they are wet, and this occurs when anaerobic conditions dominate. This paper presents the development of a model, which uses seasonal changes in groundwater to account for the fluctuating inundation of pit latrines, and, therefore, the associated CH4 emissions from varying degrees of anerobic conditions are examined. Given that observed timeseries of groundwater table depth at high enough spatial and temporal resolutions are often difficult to obtain in low- and middle-income countries (LMICs), inverse distance weighted (IDW) interpolation is used to generate values for a whole region, which is then used, alongside average pit latrine depth, to determine areas of pit latrine inundation. Outcomes are further informed with open-source contextual data, covering population, urban/rural split, and sanitation facility data, before using methodologies from the Intergovernmental Panel on Climate Change (IPCC) to generate CH4 emissions data. As a case study, we use data from Senegal to illustrate how this model works. Results show total CH4 emissions for the month of January to be ~1.69 kt CH4. We have also discussed the potential use of satellite remote sensing data in regions where access to historical groundwater data is limited. Understanding when the pit conditions are most likely to change could lead to incentives for better management strategies, as well as a reduction in CH4 production.
Original languageEnglish
Article number114
Number of pages14
Issue number5
Publication statusPublished - 19 May 2023

Bibliographical note

Funding Information:
This model requires validation using empirical CH emission data collected from pit latrines to determine how similar direct measurements are to model predictions. Under an ongoing project funded by the Bill & Melinda Gates Foundation (grant No: INV-015713), steps are being undertaken to do just this, including assessing emptying practices and the amount of sludge in OSS in both urban and rural regions. The initial steps of this empirical data collection and research from Senegal were presented by Ngom et al. (2022) []. 4

Publisher Copyright:
© 2023 by the authors.

Structured keywords

  • Water and Environmental Engineering


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