Methane from Onsite Sanitation

: Empirical Model Development in Sub-Saharan Africa

Abstract

Onsite sanitation (OSS) containments, produce greenhouse gas (GHG) emissions. Global modelling shows that 5% of total anthropogenic methane (CH4) may come from OSS, with ~2% from pit latrines. Few studies have undertaken empirical data collection, with most occurring in high income countries in temperate climates. Most of the 3.3 billion people that use OSS live in low- and middle-income countries (LMICs) in tropical environments, therefore it is important to quantify emissions in these settings.
Using data and methodologies developed in collaboration with an international research project, CH4 from OSS containments in Ethiopia, Senegal and Uganda was quantified. Data was collected from 197 containments using an improved flux chamber, taking real-time measurements of CH4. The influence of individual components of containment infrastructure on CH4 production showed that unsealed walls (32.1 g CH4/cap/day), no outlet (16.7 g CH4/cap/day), and blackwater influent (31.9 g CH4/cap/day) resulted in the highest CH4 emission rates.
A subset of 17 containments were emptied and monitored over seven months, as they re-filled, to determine if CH4 emissions increased over time. Containments with the deepest sludge produced the most CH4, with emissions from pit latrines being the only containment type where emissions increased over time.
The Intergovernmental Panel on Climate Change (IPCC) methodology was used as the basis to make national estimates of CH4 from OSS in five African countries, with improved datasets and empirical data added. These estimates indicate that using IPCC default values underestimates emissions from pit latrines but may over-estimate emissions from tanks. As CH4 production is optimal under wet conditions, likely groundwater inundation of pit latrines was modelled and integrated into national estimates. Results indicate that while groundwater effects emissions, it is unlikely to be a driving factor.
As access to sanitation in LMICs increases, this research can be used to inform decision making around technology type, management and logistics to minimise CH4 emissions.

Date of Award	13 May 2025
Original language	English
Awarding Institution	University of Bristol
Supervisor	Guy Howard (Supervisor), Maria Pregnolato (Supervisor) & Anita L Ganesan (Supervisor)