The Intergovernmental Panel on Climate Change (IPCC) has suggested that large-scale use of carbon-neutral or low-carbon biomass-derived energy will be essential in order to limit carbon emissions from the world's energy sector in the future. The IPCC envisions as much as 400 million ha being devoted to biomass energy plantations by 2050. To realize production of biomass energy at such levels - in a manner that would be both biogeophysically sustainable and socially beneficial - will require planning and policy development at sub-national levels, taking into account biogeophysical, social, cultural, economic, institutional, and other factors. This paper presents a method for spatially explicit calculations for estimating potential biomass yields over relatively large geographic regions. The calculations use geo-referenced data inputs that include rainfall, insolation, temperature, soil quality, and soil depth. The methodology is applied to the Northeast region of Brazil, which accounts for 10% of the area of South America. Northeast Brazil is an interesting site for illustrative purposes in part because it is biologically, geologically, and socio-economically diverse and in part because the main electric utility serving the region is exploring the development of biomass-based electricity generation to meet future increases in electricity demand. Results from a spatially explicit, biogeophysical model like that presented here could be combined with other spatially explicit information such as road layouts, existing land uses, population densities and growth rates, distributions of endangered species, archeologically significant areas, etc. to inform planning and policy development related to biomass energy at a regional or national level. One illustration of such an analysis is included here. For on-the-ground implementation of biomass production systems, finer-resolution analysis and intimate local participation is essential.
All Science Journal Classification (ASJC) codes
- Animal Science and Zoology
- Agronomy and Crop Science
- Biomass Energy
- Spatial analysis