Methods for Biomass Resource Assessments
Existing biomass resource assessments use a broad variety of approaches, methodologies, assumptions and datasets that lead to different estimates of future biomass potentials.
A database of circa 250 bioenergy potential assessments was compiled, out of which 28 studies were selected for detailed analysis. The 28 studies were chosen so that they, among others, cover the variability found in the literature with respect to the type of biomass, the type of bioenergy potential and the approach and the methodology.
Table A shows the categorisation of the approaches and methodologies that are distinguished in this study. Each approach and methodology has specific (dis)advantages, which are summarised in Table B.
Table A. An overview of the combinations of approaches and methodologies that are used in existing biomass energy assessments to investigate different types of biomass potentials.
General approach
General methodology
Type of biomass potential
Theoretical-technical
Economic-implementation
Resource-focussed
Statistical analysis
Yes
No
Resource-focussed
Spatially explicit analysis
Yes
No
Demand-driven
Cost-supply analysis
Noa
Yes
Demand-driven
Energy-economics and energy-system model analysis
No
Yes
Integrated assessment modelling
Integrated assessment model analysis
Yesb
Yesb
a Some demand-driven cost-supply analysis start with a statistical analysis or spatially explicit analysis of technical biomass energy potentials, although this is not the key focus of these studies.
b Some demand-driven energy-economics and energy-system model analysis use the results of cost-supply analysis.
c IAMs typically focus on the economic and/or implementation potential, although IAMs are also used for the theoretical and/or technical biomass energy potential
Table B. The advantages and disadvantages of different methodologies used in existing biomass resource assessments.
Methodology
Disadvantages
Advantages
Statistical analysis
No economic mechanisms, no spatially explicit information, no integration, based on crude assumptions, sometimes inaccurate
Simple, transparent, cheap, data are easily available
Spatially explicit analysis
No economic mechanisms, no integration, complex tool
Spatially explicit, transparent, based on data on land use and climate, soil characteristics
Cost-supply analysis
No economic mechanisms, no integration
Cheap, transparent
Energy-economics /energy-system model analysis
No integration with other markets (agricultural markets), not spatially explicit, no integration, no validation based on bottom-up data on land use and climate, soil characteristics, untransparent
Economics mechanisms are included
Integrated assessment model analysis
Complex, untransparent, expensive, results are difficult to interpret, model is user unfriendly, level of details is limited
Integrated/consistent, spatially explicit
In theory, an integrated assessment model would be best suited to include all different aspects and facets of sustainability of biomass energy production, including all relevant feedback mechanisms as well as synergies and trade-offs. Integrated assessment models thereby allow for the use of multi-dimensional scenarios, whereby a large variety of assumptions on the different parameters (population growth, economic growth, food consumption, environmental policies, trade patterns etc.) are consistent. Integrated assessment models combine bottom up data on land use and productivity with energy models and agricultural economics models. As such, integrated assessment models provide an appropriate framework to estimate the potential of biomass energy, the impacts on agricultural markets and food security, greenhouse gas emissions and land use. An important handicap is the complexity of these models, which makes these models relatively non-transparent, expensive to develop and user unfriendly in operation.
Furthermore, the analysis also shows that sustainability aspects are inadequately taken into account in existing biomass potential assessments. There is no study that includes all three dimensions of sustainability (environmental, social, and economic) nor is there a study that covers all relevant aspects of one dimension. Generally, environmental factors are overrepresented whereas social and economic aspects are taken into account far less frequently.
For climate change similar conclusions can be drawn. The impacts of land use changes are (potentially) crucial due to the direct and indirect changes in above and below ground biomass and soil organic matter. These are, however, uncertain. Ideally, these direct and indirect changes in land use are assessed using models that include a land use component.
Related project reports Methods & Data Sources for Biomass Resource Assessments for Energy (D4.5 & D4.6)