Work in this cluster (a) comprises an analysis of current and potential future demand for biomass products in Africa and globally, comprising quantities and different qualities (nutritional quality of food); (b) identifies the actors in consumption (manufacturers, investors and end consumers) and the role of lead consumers in raising future demand, and (c) investigates at which scale the demand occurs (local, regional or global) and where the demand originates to address questions of transport and storage. In other words, this cluster asks: What is the current and will be the future demand (in 2030) for food and non-food biomass, and who needs which biomass-based products for which purpose, when and where, and how much?
Work package 1.1 “Global and regional modeling of biomass markets” addresses long-term world market trends and global repercussions of biomass expansion in Africa. It will develop a quantitative biomass outlook for the study region and whole SSA until 2030, based on global agricultural model simulations. It identifies global drivers and feedbacks; for example, it will investigate how international scarcities increase world market prices for biomass, how this affects the expansion of food and non-food biomass production in Africa, and how the feedback from SSA to world biomass markets may look like. It further addresses the impact of expanding biomass webs on the economies of the study countries. Goals are to identify impacts of biomass production expansion, triggered by increasing international demand, and technology advancements, on the economies of the study countries, particularly job markets, food and fuel prices, and land resources. It identifies competition and synergies between food and non-food production, and specifically assesses effects on rural poor, food security and on macroeconomics.
Work Package 1.2 “Nutritional quality” investigates local and regional food quality. Energy, protein, vitamin and micronutrient (vitamin A, iron and zinc) supply in the diet will be identified and analyzed in selected foodstuffs. Gaps between supply and nutritional demand will be identified with the help of software (CIMIP) developed specifically to pinpoint “hidden hunger” (imbalanced diets with regard to micronutrients even under satisfactory energy supply) and suggest shifts in the production and post-harvest management of food.