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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/13073

Title: Optimising ventilation to control odour in the ventilated improved pit latrine
Authors: Obeng, Peter A.
Oduro‑Kwarteng, Sampson
Keraita, Bernard
Bregnhøj, Henrik
Abaidoo, Robert C.
Awuah, Esi
Konradsen, Flemming
Keywords: VIP latrine
Ventilated improved pit
Ventilation rate
Dry sanitation technology
Issue Date: 11-Oct-2018
Publisher: Modeling Earth Systems and Environment
Citation: Modeling Earth Systems and Environment
Abstract: The rate of ventilation through the vent pipe of a ventilated improved pit latrine is the main technical factor that determines its efficiency in odour control aside the maintenance and cleaning practices of the users. Even though the factors affecting the ventilation rate have been well researched, they have not been previously related in a mathematical model to quantify the relative effect of the various factors on the ventilation rate. The objective of this paper is to develop such a model that could be used to optimise and predict the ventilation rate as a function of relevant design criteria and weather conditions. The ventilation rates produced by various design modifications in an experimental ventilated improved pit latrine were measured under monitored weather conditions. A linear regression model was used to assess the relative effect of the various design modifications and the elements of weather on the ventilation rate. It was found that the diameter of the vent pipe is the most important factor which accounts for 53% of variations in the ventilation rate, followed by the external wind speed, which accounts for 25% of changes in ventilation. The provision of windows in other sides of the superstructure other than the windward side leads to a reduction of 32% in the ventilation rate and accounts for 9% of the variations in the ventilation rate. A regression model developed in this study could be used to optimise and predict the ventilation rate based on a set of design criteria and meteorological data.
Description: This article has been published in Modeling Earth Systems and Environment and is available at https://doi.org/10.1007/s40808-018-0523-0
URI: 10.1007/s40808-018-0523-0
Appears in Collections:College of Science

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