Modeling uncertainty in greenhouse gas emissions of biomass feedstocks

Abstract

IN the near future, the energy sector may have to use alternatives to fossil fuels to reduce life cycle greenhouse gas (GHG) emissions. Biomass-derived energy is one potential pathway to achieving this objective. However, the GHG-intensity of biomass-based energy is highly dependent on how the biomass is produced, transported, processed, and converted into liquid fuels or electricity. Thus, uncertainty in the actual upstream GHG emissions associated with a biomass feedstock or process could lead to the adoption of government policies and industrial practices that increase expenditures but yield only marginal GHG emissions reductions, if any. To understand the implications of biomass use on the GHG-intensity of the energy system, it is important to assess these uncertainties and to incorporate them into estimates of GHG emissions [1].