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Bioproducts such as advanced biofuels and biomaterials are seen by many as the forest industry’s products of the future. They are widely recognized by researchers and policy makers for the socio-economic and ecological benefits linked to their production processes, for example reduced greenhouse gas emissions. Currently, the by-products generated from processing solid wood are largely used for traditional or low-end products such as paper or as a direct heat source to power the mill. Harvesting residue, trees that have been damaged due to epidemics or fires, and other feedstock are used in very limited quantities for manufacturing bioproducts even though they are available in very large quantities. It is not yet clear how this huge supply of feedstock material could be supplied from the public forests and allocated to users within the future biomass-based bioproduct value chains. To maximize the socio-economic and ecological benefits from forest biomass in the context of increased and possibly conflicting demands, upstream value chain decisions related to biomass allocation are of primary importance.

This is why the BioFuelNet team at l’Université Laval proposes an integrated approach for the forest biomass allocation problem with the perspective of maximizing the value generated from public forest resources, in terms of sustainability (economic, environmental, and social benefits).

Our approach is based on three main steps:

1) The first step specifies the allocation criteria to be used in the decision process. These are inspired by Forest Stewardship Council’s (FSC) principles and the Global Reporting Initiative’s (GRI’s) guidelines. The allocation criteria reflect the sustainability performance of candidate mills, for example the expected impacts on the local economy, ecosystems, and affected stakeholders.

2) The second step evaluates the sustainability performances of the candidate mills based on a multi-criteria decision making method called AHP, short for Analytic Hierarchy Process. Each mill obtains a score for the economic, environmental and social performances and a priority weight is also assigned to each of the sustainability performance dimensions.

AHPHierarchy-wikimedia commons

The analytic hierarchy process (AHP)

3) These scores and weights are then used, in the third and final step, as inputs in a linear programming model (PL) that determines the optimal feedstock volume to allocate to each mill. The overall “sustainability value” modelled as an objective function is maximized while some constraints related the maximum allowable biomass, such as the maximum processing capacities of the mills, are satisfied.

In our future work, we intend to explore simulation techniques based on scenario analysis (“what happens if …?”) in the third step of our approach to account for uncertainties related to the availability and quality of biomass supplied from disturbed forests. Results from this project will contribute to guidelines for feedstock allocation in the context of a developing biofuel and bioproducts industry.

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