The Uncontrolled Cooking Test: Measuring Three-Stone Fire Performance in Northern Mozambique
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Transcript of The Uncontrolled Cooking Test: Measuring Three-Stone Fire Performance in Northern Mozambique
The Uncontrolled Cooking Test: Measuring Three-Stone Fire
Performance in Northern Mozambique
J. Robinson1,2, M. Ibraimo2,3, C Pemberton-Pigott1
1. SeTAR Centre, University of Johannesburg2. Department of Geography, Environmental Management and Energy Studies, University of
Johannesburg3. Department of Physics, Eduardo Mondlane
University, Maputo, Mozambique
DUE 2011 13th April 2011
Background
•Importance of domestic biomass use in Mozambique•80% energy consumed is biomass•71% live in rural areas•Characterize energy baseline of rural villages
•2010 field research programme•2008 socio-economic study by M. Ibraimo•Muculuone village, Nampula Province, northern Mozambique•Rural, poor, off-grid, subsistence farming•Heavy reliance (92%) on firewood and three-stone fire
•Aims•Measure baseline cooking energy patterns •Provide data and experience for testing methodology devt.
Study Site
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Nampula Province Muculuone Village
Cooking Technology and Fuel
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Three-stone fire Cooking Xima
Measuring Stove Performance
•Laboratory or Field•Trade-off between variability and relevance (task)•Kitchen Performance Test (KPT)
• Fuel savings averaged over 3-7 days (kg/person/day)• Resource intensive• High variance (CoV 30-50%)
•Controlled Cooking Test (CCT)• Fuel consumed in cooking a standard meal (kg wood/Kg food)• Less intensive• Moderate variance (CoV 10-30%), representative?
•Middle ground?
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The Uncontrolled Cooking Test (UCT)
•Measure real world performance of a cooking system•Meal not constrained, measuring as a household cooks•Wood used, food cooked (MJ wood/kg food)•Shorter time per test = more tests or less people
•Stronger and more representative data set with a better measure of inherent variability of real world use
•But can the test method show less variance than the KPT and in doing so use the same or less resources?
• i.e. Detect a significant difference between a baseline and ‘improved’ scenario with a smaller sample size
•If yes, of real use to carbon and development projects
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General Results
•29 UCT’s in 24 households over 4 days, 3 tests rejected
•Wood Average MCwet 13.1%, LHV (ARAF) 16.7 MJ kg-
1
•General observations•All households disposed of char•Average 5.0 ± 1.6 people per household•77% households cooked using 2 pots sequentially•58% cooked indoors•Uniform operating method for three stone fire
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UCT Results (1)
•Results presented as ‘no char’ and ‘with char’
•High variance for time and food mass
•20% difference in SFC due to char
•SFC (no char) of 12.1 MJ wood per kg food
•SFC CoV 25-30% is less than for KPT
UCT Results (2)
Specific Fuel Consumption (no char case)
DUE 2011
•R2 = 0.79 shows strong correlation
•Linear relationship
•Variance around best fit
Conclusions and Recommendations
•UCT proved a capable and viable method• Captured key user behaviour• Less variation than typically reported by KPT (one case)• Offers potential to detect a statistically significantly
difference between baseline and ‘improved’ stove by using less resources
•Future work• Variability, error and sample size• Statistical treatments (non linear)• Correlate laboratory and field performance
Acknowledgements
• Vincent Molapo (UJ SeTAR) and Fabiano Simao (UEM)
• Village elders and households in Muculuone
• NRF/ NRI funded SAMOZ programme - Prof H. Winkler
(UJ) and Prof M. Falcão (UEM)
• UJ Quick Wins Programme, Volkswagen Stiftung
Biomodels project through the IER, Uni. of Stuttgart
• GTZ BECCAP/ProBEC for funding of UJ SeTAR centre
and loan of vehicle.
[email protected] 559 1901