Bioenergy GHG calculator

The use of forest-based bioenergy to replace fossil fuels in heat and electricity generation, as well as in other applications, has the potential to reduce greenhouse gas (GHG) emissions. Under sustainable forest management practices, forests can provide renewable feedstock for bioenergy. However, the presumed “carbon neutrality” of forest bioenergy has been the subject of much debate recently. The Intergovernmental Panel on Climate Change (IPCC) recognizes that forest bioenergy is not automatically carbon neutral. On most cases, the change in forest practices to harvest and use more biomass for bioenergy will increase GHG emissions and therefore reduce forest carbon stocks, thereby producing a so-called carbon debt. This reduction in forest carbon will eventually be balanced over time by the fossil emissions avoided from the use of bioenergy. Once this period is over, atmospheric GHG benefits are achieved. On some other cases, the change in forest practices to harvest and use more biomass for bioenergy will not increase GHG emissions (carbon neutrality) or will decrease emissions (carbon gain) immediately.

Accordingly, the GHG balance of a forest bioenergy project is highly variable and time dependent. It is influenced by a variety of factors, including biomass feedstock, application, transportation, forest management and what is considered as the baseline (or counterfactual), i.e., what would have happened if bioenergy had not been used? This tool makes it possible to evaluate in a clear and comprehensive way the GHG mitigation potential and timing of GHG emission reductions when forest bioenergy is used as a substitute for fossil energy. The uncertainty related to the timing of GHG emission reductions is also provided. Users are invited to build their own bioenergy project by selecting different options related to the supply chain, forest dynamics and what they consider the most representative baseline to compare their project with. Results are presented over a 100-year time frame, starting from year 0, with the production and use of bioenergy sourced from a sustainably managed forest landscape. By default, scenario emissions from collection, transformation, transport, and combustion stop at 25 years to account for changing technology and the average lifespan of equipment. Emissions that take a long time to be released, such as those associated with decay processes, continue to be monitored until the end of the simulation. Results can be used to provide guidance for promoting the best use of forest bioenergy for GHG mitigation.

The equations, analysis methodology, and error terms are presented in the following papers:

Robert, L.-E., Serra, R., Roussel, J.-R., Thiffault, E., & Laganière, J. (2025). Assessing the greenhouse gas balance of forest bioenergy projects with the Bioenergy GHG R-package. In preparation.
Laganière, J., Paré, D., Thiffault, E., & Bernier, P. Y. (2017). Range and uncertainties in estimating delays in greenhouse gas mitigation potential of forest bioenergy sourced from Canadian forests. GCB Bioenergy, 9: 358–369. https://doi.org/10.1111/gcbb.12327.

Examples of studies using the model:

Steenberg, J. W. N., Laganière, J, Ayer, N. W., & Duinker, P. N. (2023). Life Cycle Greenhouse Gas Emissions from Forest Bioenergy Production at Combined Heat and Power Projects in Nova Scotia, Canada. Forest Science, fxac060. https://doi.org/10.1093/forsci/fxac060.
Buss, J., Mansuy, N., Laganière, J., & Persson, D. (2022). Greenhouse gas mitigation potential of replacing diesel fuel with wood-based bioenergy in an arctic Indigenous community: A pilot study in Fort McPherson, Canada. Biomass and Bioenergy, 159: 106367. https://doi.org/10.1016/j.biombioe.2022.106367.
Serra, R., Niknia, I., Paré, D., Titus, B., Gagnon, B., & Laganière, J. (2019). From conventional to renewable natural gas: can we expect GHG savings in the near term?. Biomass and Bioenergy, 131:105396. https://doi.org/10.1016/j.biombioe.2019.105396.

Calculation form

Feedstock

Harvest residues are defined as all woody debris generated during harvesting operations for traditional wood products, such as branches, tree tops, and bark, but excluding stumps and downed non-merchantable trees. Harvest residues do not include sawmill residues, which provide atmospheric benefits very rapidly. The value is averaged from several studies. Collection emissions are 0.84 kg CO₂-eq/GJ (Laganière et al., 2017).

Salvaged trees are defined as standing trees killed by natural disturbances. The stemwood is harvested for bioenergy, while the residues are left on site and are not considered in the calculation. The value is averaged from several studies. Collection emissions are 2.63 kg CO₂-eq/GJ (Laganière et al., 2017).

Green trees are defined as mature, living trees. The stemwood is harvested for bioenergy, while the residues are left on site and are not considered in the calculation. Harvesting green trees for bioenergy complements rather than competes with traditional forest products (e.g., lumber, pulp, and paper). Green trees used to produce bioenergy are considered "additional biomass", meaning this feedstock would not be utilized otherwise for various reasons (e.g., species not used by the traditional forest industry, fiber quality unsuitable for traditional products but suitable for bioenergy, etc.). When green trees are not harvested for bioenergy, the forest continues to grow and decay at its natural rate. Silvicultural practices (e.g., site preparation, tree planting, weed control) may enhance forest regeneration and growth after biomass harvesting, reducing the time to achieve atmospheric benefits. This option is not included in the present calculator, but its impact is discussed in the scientific paper. Collection emissions are 2.63 kg CO₂-eq/GJ (Laganière et al., 2017).

Generic emissions from mill residues, resulting from the processing of wood within an industrial context, are assumed to be low since the wood has already been collected for other purposes. Collection emissions are 0.01 kg CO₂-eq/GJ.

Generic emissions from the collection of tree harvesting residues in urban environments are yet to be determined but are currently assumed to be similar to the harvest option. Collection emissions are 0.84 kg CO₂-eq/GJ.

Generic emissions from the collection of wood wastes from the construction and demolition sector are yet to be determined but are currently assumed to be similar to the mill residue option. Collection emissions are 0.01 kg CO₂-eq/GJ.

Drying

The annual emissions of biomass during active drying from the temperature, the initial moisture content, the final moisture content and the type of fuel (Natural Gas here) used to dry the biomass according to Haque and Somerville (2013).

Transformation

Emissions are 0.76 kg CO₂-eq/GJ (Lamers et al. 2014).

Emissions are 10.45 kg CO₂-eq/GJ (Lamers et al. 2014).

Biofuel emissions are an average value of many biofuel types from the IPCC Stationary Combustion Report 2006. Emissions are 16 kg CO₂-eq/GJ.

Energy conversion

Bioenergy system efficiency

Base uncertainty percentage applied to all processes

This parameter modifies all processes except the transport process and applies uncertainty. Uncertainty is applied as a +/- percentage on all model parameters to establish minimum and maximum values. The model outputs are then generated based on these minimum and maximum values. The default value is a legacy setting from the previous version of this model, where the minimum and maximum values were typically established as -5% and +10%, respectively.

Transportation

Place of use

Truck

Train

Vessel

Base uncertainty percentage applied to the transport process

This parameter modifies the transport process and applies uncertainty. Uncertainty is applied as a +/- percentage on transport process parameters to establish minimum and maximum values. The model outputs are then generated based on these minimum and maximum values. The default value is a legacy setting from the previous version of this model, where the minimum and maximum values were typically established as -50% and +50%, respectively.

Baseline (counterfactual)

Fossil fuel replaced

Baseline scenario efficiency

Fate of biomass if not used for bioenergy

Fate of biomass options are only applicable to the baseline scenario.

Emissions from the composting of residues and the subsequent decay according to the first order decay function from IPCC (2014).

Describes the decay of residues after harvesting according to the first order decay function as in Smyth et al. (2010).

Residues that are incinerated or open-burned.

Describes the emissions from the decay of mulch in aerobic conditions according to the first order decay function as in Smyth et al. (2010).

Emissions from the combustion of slash piles burning according to Ter-Mikaelian et al. (2016). Residues are assumed to be completely burned.

Mean annual temperature

Substitution

Describes the emissions avoided when using biomass for bioenergy as a substitute for other longer-lived products (e.g., sawnwood, structural panel, non-structural panel, and pulp and paper). Substitution is quantified using a substitution factor, representing the average tons of carbon equivalent avoided per ton of material. This process contributes to the model through negative emissions. In the context of this model, long-lived wood products are assumed to be incinerated at the end of their useful life. Input values in this form represent the percentage of total biomass attributed to each category of usage (sawnwood, structural panel, non-structural panel, pulp and paper, bioenergy, and unmerchantable). "Unmerchantable" refers to any biomass left to the "biomass fate" process. The amount of CO₂-equivalent emissions avoided is then calculated for each category and applied as a negative value in the final result. The substitution process can only be used in cases where there is a displacement of material toward bioenergy compared to a baseline scenario (i.e., non-zero values to bioenergy or unmerchantable parameters in both the baseline and bioenergy scenario).

Include substitution of traditional harvested wood products (HWP)

Bioenergy scenario

Percentage of sawnwood

Percentage of structural panel

Percentage of non-structural panel

Percentage of pulp and paper

Percentage of bioenergy

Percentage of unmerchantable wood

Baseline scenario