Tier II: WISDOM Honduras – Analysis of woodfuel supply, demand and sustainability in Honduras
The study “Geospatial Analysis and Modeling of Non-Renewable Biomass: WISDOM and beyond”, commissioned by the Global Alliance for Clean Cookstoves (the Alliance) and supported by UN Foundation, is implemented by the Yale School of Forestry and Environmental Studies (FES) in partnership with the Centro de Investigaciones en Geografía Ambiental (CIGA) and the Centro de Investigaciones en Ecosistemas (CIEco) of the National Autonomous University of Mexico (UNAM).
Scope of the project is to develop and, in select cases, validate multi-scalar geospatial estimates of the fraction of non-renewable biomass (fNRB) harvested for woodfuel, including firewood and charcoal, at national and sub-national levels in Sub-Saharan Africa, Tropical Asia and Latin America. This will enable clean cookstove and fuel substitution programs to better understand their impact on land use/land cover change (LU/LCC) and allow for more accurate and consistent accounting of carbon offsets.
At the national and regional level, there are large variations in location, method, and volume of biomass harvesting. Country-level estimates based on national statistics cannot capture the geographic specificity of biomass harvesting and may result in incorrect assumptions about the impact of fuelwood on land cover change. In contrast, spatially explicit estimates of fNRB reflect the variability that characterizes woodfuel demand, supply potential and harvesting intensity, but require more complex analyses. Geospatial approaches like the Woodfuel Integrated Supply/Demand Overview Mapping (WISDOM) methodology support strategic planning and prioritize areas for project implementation.
The project follows a 3-tiers approach to draw comparisons between three different geographic scales of analysis:
Kenya, Honduras, and Karnataka, India has been selected for Tier 2 analyses. Tier 2 analysis, object of the present report, is based on the national level analysis of woodfuels supply and demand through the application of the WISDOM model.