Research
Overview
Most significant global drivers that affect low-productivity farming in sub-Saharan Africa are Climate Change (Gbetibouo et al. 2006) and global energy demand (Von Braun 2007). Simulations on long- and medium-term global energy demands have high forecast uncertainty but will likely disproportionately affect sub-Saharan regions. Biofuels have the potential to provide communities in sub-Saharan Africa with multiple energy services (e.g, heating, lighting, cooking and transportation) as well as income generating and educational activities. This can bring significant benefit to rural populations (United Nations 2007). However, if biofuel value chains are developed improperly, the effects could include increased food prices and reduced supply (Von Braun 2007), displacement of vulnerable people from productive land, and negative environmental impacts can occur (Thornton et al. 2006). Thus, pathways on biofuel value chains across sub-Saharan Africa from (1) biomass resources to (2) supply systems, (3) conversion and (3) processing end products provide potential intervention points to assist rural poor (Leuenberger & Wohlgemuth 2006). To be able to respond to changing conditions, profound knowledge for decision making is required (Renn et al. 1993); on how to maximize profit by producing feedstock for external markets, on optimal mix of energy carriers and supply for domestic and industrial users at rural (local) level, and on adequate strategies to ensure food security (Omamo et al. 2006). Only knowledge on biofuel value chains taking into account production technologies, human capacities, feedstock and processed goods under alternative energy scenarios can cope with the negative effects of global problems.
The major objective is the development of an integrated assessment framework combining interdisciplinary research methods for decision support in biomass value chain management. Throughout all methodological components the analytical objective of the analysis will reveal impacts from state-of-the-art-situation (current state) towards the long-term future perspective subject to most-likely developments under given scenario assumptions. Based on these findings suggested responses support stakeholders in decision making. Global effects of energy scenarios will be linked spatially explicit to meso-scale case study-levels as regional analysis of biomass production. Outcomes of global energy scenarios are energy demand, implications on prices and technological assumptions including yields, land use changes on crop production between traditional food crops and biomass production. Please also see the output flow chart on the title page. Output 1: Top-down global modelling approaches will be applied to downscale implications for energy demand, excess supply or gaps in supplies. The scenario solving will be achieved by the agricultural sector model IMPACT that accounts for country-level food outcomes in sub-Saharan Africa related to the global food situation in medium- and long-term analysis (Von Braun 2007). Output 2: The evaluation of energy biomass production as well as consumption patterns focuses on competing biomass uses (food, material, energy) and resulting options for cascading systems. This results in energy and climate balances which link both, outputs from the top-down approach on global scenarios and the bottom-up approach of biomass value chains (output 3). Energy balances are calculated at national level, while identified value chains also calculate CO2- balances and energy (KWh) supply-demand accounting. Output 3: Bottom-up biomass value chains in the Tanzanian case study region will be assessed through feasibility studies on potential pathways of linking low-productivity farming to SME on local, decentralized biomass concepts. Microeconomic calculations on costs, benefits and risks including marginal analysis of economies of scales and sizes underline technological and infrastructural feasibility. For this, methods on participatory stakeholder analysis and involvements by means of adequate appraisal methods (ICRAF- TULSEA tool kit) will be applied. The transferability of the case study region-results to other regions in Sub-Saharan Africa will be tested. Output 4: Sustainability Impact Assessments (SIA) in the case study region reflect trade offs between socio-economic and environmental indicators related to production and side conditions on the basis of identified biomass value chains. It results in assessing the situation of food security (Reilly & Schimmelpfennig. 1999). To conduct Impact Assessment for trade-off analysis, each sustainability dimension (social, environmental, economic) must be represented by methodologically sound and consistent indicators. Output 5: A digital Information System of feasible value chain concepts is provided as advice packages and will be tailored for later activities for capacity building and dissemination strategies; for the Tanzanian case and main findings on the transferability test to other representative Sub-Saharan regions.
