Principal Investigator


At a Glance

Researchers in Eric Larson’s group have developed a framework for assessing the dynamic lifecycle greenhouse gas (GHG) impacts of hypothetical forest-based bioenergy projects and applied it to case studies involving utilization of feedstocks from forest basins in the southern U.S. Understanding the carbon impacts of using woody feedstocks from this region (called the “wood basket of the country”) is important to ensure that such projects are climate friendly.

 


Research Highlight

When biomass is used for energy, the biogenic carbon released into the atmosphere is often assumed to be carbon net-neutral. This is a reasonable assumption for biowastes and for foodcrop residues harvested and used on an annual basis. In contrast, using biomass from managed forests for energy can result in an initial “carbon debt.” This term refers to net carbon emissions to the atmosphere relative to a counterfactual scenario where there is no new demand for bioenergy feedstocks. The carbon debt may be “paid back” over time through forest growth and the substitution of fossil energy with bioenergy. Some studies suggest that the use of forest bioenergy can often sequester more carbon than in the counterfactual scenario (Daigneault et al., 2012). However, other studies suggest that forest bioenergy will generate a carbon debt that can never be paid back (Schulze et al., 2012). Such widely varying conclusions are due in part to differences in methodologies and assumptions (Bentsen, 2017; Cowie et al., 2021; Galik and Abt, 2012; Ter-Mikaelian, 2015). Equally important factors include the geographic location, existing market conditions, and the age class profile and dominant species of the forest resource under consideration.

To help illustrate the complexities of forest-bioenergy GHG emissions accounting, Larson and his group developed a framework (Figure 6.1) for assessing the lifecycle GHG impacts of hypothetical bioenergy projects. They applied the framework to case studies involving utilization of feedstocks from different specific forest basins in the U.S. south (Figure 6.2). The extent of each basin represents a plausible area from which a bioenergy facility might source feedstock. There are some 87 million hectares of managed forests across the U.S. south that today provide feedstocks for forest product industries and serve a variety of other purposes. Nearly 90% of this area is privately held. Private timberland owners are known to adjust their forest management practices based on changes in prices they receive for wood and policy incentives (Amacher et al., 2009). This, in turn, determines harvest rates, forest growth conditions, and ultimately forest carbon storage (Mei, 2023).

 

Figure 6.1.
Framework for dynamic lifecycle greenhouse gas emissions analysis of forest-biomass use for energy, considering forest carbon storage, non-biogenic carbon emissions in supply chains, bioenergy substituting fossil energy, carbon storage in forest products (and landfills at end of life), and any geological storage of biogenic carbon associated with a bioenergy facility.
Figure 6.2.
Eight case-study forest basins were analyzed. Each includes all counties that lie wholly or partially within a 75-mile radius of a central hypothetical bioenergy facility site.

The researchers captured such owner behavior through use of the Sub-Regional Timber Supply model (Henderson et al., 2023). This model was developed specifically for timber market conditions unique to the U.S. South. These conditions include the region’s predominantly commercial use of southern yellow pine, its reliance on harvests from private land, and the capacity at the margin for forest area to expand or contract and/or be converted from natural to managed regeneration depending on changes in timber prices. The model uses data from the U.S. Forest Service Forest Inventory and Analysis (US Forest Service, 2024) and the Timber Products Output database (Coulston et al., 2018). These provide baseline quantities of forest biomass by age and size classes, forest types (e.g., natural pine vs managed pine), and private ownership groups (corporate and non-corporate, which manage forests differently).

Figure 6.3.

Difference in cumulative stored carbon in a bioenergy scenario versus a counterfactual (no bioenergy) scenario in three case-study basins. In each case, a hypothetical bioenergy facility is assumed to use two million green tonnes per year of pulpwood quality biomass from the basin. Results are shown for bioenergy facilities producing sustainable aviation fuel either with or without CO2 capture and storage (CCS). See Figure 6.2 for basin locations.

Figure 6.3 shows differences, relative to counterfactual (i.e., non-bioenergy) scenarios, in cumulative carbon stored away from the atmosphere over a 30-year operating life of a bioenergy project. The figure illustrates this for a hypothetical bioenergy facility with and without CO2 capture and storage (CCS) in three of the modeled forest basins. In each basin, the carbon stored in the forest and in forest products, emitted from supply chain activities and avoided by fossil substitution, are identical for the case with and without CCS. Additional carbon is stored when CCS is employed. In Basin 2, CCS reduces the carbon-debt repayment period from 11 years without CCS to eight years, and the net cumulative carbon stored over the project lifetime is nearly double with CCS versus without. Basins 1, 3, 4, and 7 demonstrate similar carbon behavior as in Basin 2. In Basin 5, the carbon debt without CCS is repaid in 26 years. With CCS, it is repaid in 16 years. In Basin 6, without CCS, the carbon debt was found to not be repaid after 30 years, and with CCS it is repaid in about 25 years. Finally, in Basin 8, forest carbon loss is substantial because of the particular forest conditions found there, and the carbon debt is never repaid even with CCS.

The work of Larson and his group shows that forest-based bioenergy projects in the southern U.S. can display relatively short carbon debt repayment times when drawing feedstocks from certain forest basins, but not when drawing from others. Case-by-case assessments are therefore necessary. In some cases, new wood demands for bioenergy drive expansion of planted forests, which can shorten the carbon debt repayment period. In general, carbon debt repayment will be faster for bioenergy projects that employ CCS than those that do not.

Finally, because forests and associated forest-product markets change over time, assessments of the climate impact of a bioenergy facility are specific to the year in which a facility is envisioned to start operation. For a given forest basin, the climate impact of a project that begins operating in 2040 might be different from the same project starting operation in 2030. These are important considerations for policymakers and bioenergy project developers alike.

 


References

Amacher, G.S., M. Ollikainen, and E. Koskela, 2009. Economics of Forest Resources, MIT Press Cambridge.

Bentsen, N.S., 2017. Carbon debt and payback time – Lost in the forest? Renewable and Sustainable Energy Reviews 73:1211– 1217 (https://doi.org/10.1016/j.rser.2017.02.004)

Coulston, J.W. et al., 2018. Annual monitoring of US timber production: Rationale and design. Forest Science 64(5):533– 543. (https://doi.org/10.1093/forsci/fxy010).

Cowie, A.L. et al., 2021. Applying a science-based systems perspective to dispel misconceptions about climate effects of forest bioenergy. GCB Bioenergy 13(8):1210–1231. (https://doi.org/10.1111/gcbb.12844).

Daigneault, A., B. Sohngen, and R. Sedjo, 2012. Economic approach to assess the forest carbon implications of biomass energy. Environmental Science and Technology 46(11):5664–71. (https://doi.org/10.1021/es2030142).

Galik, C.S., and R.C. Abt, 2012. The effect of assessment scale and metric selection on the greenhouse gas benefits of woody biomass. Biomass and Bioenergy 44:1–7. (https://doi.org/10.1016/j.biombioe.2012.04.009).

Henderson, J.D., R.C. Abt, and D. Rossi, 2023. “Sub-Regional Timber Supply Model (SRTS): User Guide and Documentation,” Oct. 5, 2023. (accessed Feb. 16, 2024).

Larson, E. et al., 2021. Net-Zero America: Potential pathways, infrastructure, and impacts final report. Princeton University.

Mei, B., 2023. Quantifying carbon additionality for unevenaged forests. Journal of Forest Business Research 2(2):33-41. (https://doi.org/10.62320/jfbr.v2i2.29).

Schulze, E. et al., 2012. Large-scale bioenergy from additional harvest of forest biomass is neither sustainable nor greenhouse gas neutral. GCB Bioenergy 4(6):611–616. (https://doi.org/10.1111/j.1757-1707.2012.01169.x).

Ter-Mikaelian, M.T., S.J. Colombo, and J. Chen, 2015. The burning question: Does forest bioenergy reduce carbon emissions? A review of common misconceptions about forest carbon accounting. Journal of Forestry 113(1):57-68. (http://dx.doi.org/10.5849/jof.14-016).

U.S. Forest Service, Forest Inventory Analysis, US Dept. of Agriculture (accessed Feb. 16, 2024).