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The Uncontrolled Cooking Test: Measuring Three-Stone Fire Performance in Northern Mozambique J. Robinson 1,2, M. Ibraimo 2,3, C Pemberton-Pigott 1 1.SeTAR.

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Presentation on theme: "The Uncontrolled Cooking Test: Measuring Three-Stone Fire Performance in Northern Mozambique J. Robinson 1,2, M. Ibraimo 2,3, C Pemberton-Pigott 1 1.SeTAR."— Presentation transcript:

1 The Uncontrolled Cooking Test: Measuring Three-Stone Fire Performance in Northern Mozambique J. Robinson 1,2, M. Ibraimo 2,3, C Pemberton-Pigott 1 1.SeTAR Centre, University of Johannesburg 2.Department of Geography, Environmental Management and Energy Studies, University of Johannesburg 3. Department of Physics, Eduardo Mondlane University, Maputo, Mozambique DUE th April 2011

2 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.

3 Study Site DUE 2011 Nampula Province Muculuone Village

4 Cooking Technology and Fuel DUE 2011 Three-stone fire Cooking Xima

5 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? DUE 2011

6 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 DUE 2011

7 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 DUE 2010

8 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

9 UCT Results (2) Specific Fuel Consumption (no char case) DUE 2011 R 2 = 0.79 shows strong correlation Linear relationship Variance around best fit

10 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

11 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.

12 Questions?


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