Economic factors influence net carbon emissions of forest bioenergy expansion

The study investigates whether and under what conditions expanding forest bioenergy demand creates a sustained forest carbon debt and how long payback periods last. The context is an ongoing debate over the climate impacts of forest bioenergy: stand-level analyses often project long payback times, while market-scale dynamic models suggest investments and land-use responses can increase sequestration. The paper highlights methodological differences among models (single-stand, static FSMs, dynamic FSMs) and emphasizes the importance of price expectations and market-mediated responses. The purpose is to use a dynamic global forest sector model to quantify carbon debt and payback across numerous bioenergy demand pathways and to assess how accounting choices and supply regulations shape outcomes. The importance lies in informing climate, renewable energy, and forest policy with system-wide estimates that account for market, management, and land-use feedbacks.

The paper reviews strands of literature with differing conclusions about forest bioenergy. Stand-level analyses often find carbon debts that can take decades to repay, focusing on site-specific dynamics and ignoring broader market responses, disturbance risks, and declining sequestration in aging stands (e.g., Nabuurs et al. 2017; Bentsen 2017). Some market-scale static equilibrium models also find reduced sequestration with increased forest product demand but typically fix land base and management responses (e.g., Nepal et al. 2012; Wear & Coulston 2015). Dynamic forest sector models allow endogenous land-use and management responses and have shown that increased bioenergy demand can raise carbon storage depending on private investments, policies, and land-use change (e.g., Latta et al. 2013; Baker et al. 2019; Favero et al. 2020). Empirical evidence shows forward-looking timber market behavior and expansion of plantations (e.g., Sweden’s historical trend; FAO FRA 2020; Korhonen et al. 2021), and that higher forestry returns induce planting and management shifts (Hashida & Lewis 2019). The authors argue that carbon neutrality should be assessed across space and markets, not just time at a single site, and that product substitution and energy-sector emissions need system perspectives.

The analysis uses the dynamic Global Timber Model (GTM), a partial equilibrium model optimizing global timber market welfare over a 200-year horizon across ~350 supply regions. The model endogenizes land use (competition with agriculture via a land rental function), forest area (conversion to/from forests), management intensity, planting, and harvest timing. It clears in a global market with traded products and is solved in decadal steps in GAMS (MINOS). Forest carbon accounting includes four pools: aboveground biomass, soil, harvested wood products (market C), and slash, with pool dynamics specified (e.g., product decay rates 0.4–2%/yr; slash decomposition 3–7%/yr by biome). Carbon is proportional to biomass via species coefficients. Forest carbon debt is defined as any period when total forest carbon stock (sum of the four pools) under a biomass demand scenario is below the contemporaneous baseline; payback period is years from demand introduction until the stock rises above baseline. Scenarios: 51 exogenous global forest biomass demand pathways varying initial levels from 50 Mm³/yr to 1.2 Bm³/yr and average annual growth rates from 0 to 5%. Low/no-growth pathways mimic constant reallocation assumptions typical of LCA; 1–5% growth aligns with IAM pathways under rising carbon prices. Baseline: SSP2 (“middle of the road”), no additional bioenergy demand or carbon policies, but growing pulpwood/sawtimber demand with income and population growth; baseline prices rise, management intensifies, unmanaged forest converts partly to cropland; global forest carbon stock increases from 958 GtC to 981 GtC by 2100. Supply of biomass to meet exogenous demand can come from logging/mill residues (capped at 30% of yield), substitution from industrial products, and new harvesting via extensification (area) and intensification (management). The model tracks price responses and investment feedbacks. Additional experiments test alternative accounting (excluding market C from debt) and supply constraints limiting sources (e.g., no natural forest biomass, limits on plantation expansion, no residues), assessing effects on payback across representative growth scenarios.

- All 51 biomass demand pathways produce an initial forest carbon debt (lower total forest+product carbon than baseline) in the decade of policy implementation. - Magnitude: carbon debts range from modest to about 1 GtCO2e/yr, scaling with removals in low-growth scenarios. - Growth threshold: scenarios with biomass demand growth below ~3%/yr generally do not recover the carbon debt over the century (some worsen slightly), whereas scenarios with growth >3%/yr always recover the initial debt. Growth >4%/yr recovers within ~20 years; 3–3.5%/yr recovers between mid- and end-of-century. - End-of-century gains: faster growth scenarios yield additional forest carbon stocks of ~0.2–5.5 GtCO2e/yr by 2100 relative to baseline. - Price–investment mechanism: Higher biomass demand growth raises average timber price growth above baseline, inducing greater forest area and management intensity, which accelerates sequestration and debt recovery. When average timber prices (including biomass) grow faster than baseline, carbon debt is very likely recovered within 70 years or less. - Supply composition: In very low-demand/low-growth cases (<500 Mm³/yr; <0.5%/yr growth), residues supply on average ~93% of bioenergy. As demand rises, residues’ share declines and substitution/new harvests increase, affecting carbon outcomes. - Production response: Supplying 100 Mm³/yr of forest biomass increases total timber production by ~60 Mm³/yr (on average). A 700 Mm³/yr biomass demand increases average timber prices by ~16% (2020–2050) and ~6% (2050–2100). - Land and management effects per m³ under high growth (>3%/yr): +0.0015% forestland, +5% production intensity (m³/ha), +0.4% management investment ($/ha) vs baseline; under low growth (<3%/yr): +0.0002% forestland, +3% intensity, +0.06% investment. - Pool contributions: Most carbon debt arises from reduced market C (harvested wood products) due to substitution toward biomass when demand is flat/low-growth; recovery is driven primarily by gains in aboveground biomass from expanded area and intensification. Soil C generally increases with forest area; slash C declines as more residues are removed. Estimated emissions from consuming 1 m³ of forest residues: 0.2–0.7 tC released. - Accounting sensitivity: Excluding market C from the debt calculation greatly reduces apparent debt. Only fixed-demand (n=11) scenarios exhibit long-term debt; all others (n=39) have carbon debt for 0–10 years. - Supply constraints: Regulations limiting biomass sourcing (e.g., excluding natural forests or limiting plantation expansion) reduce payback time (e.g., from ~20 to ~10 years in high-growth cases) but do not eliminate initial carbon debt. Scenarios with growth <3% still show persistent debt even with constraints.

The findings show that market-mediated responses—price increases leading to greater forest area and intensified management—are pivotal for overcoming initial carbon debts associated with bioenergy expansion. This challenges stand-level or static analyses that omit investment and land-use feedbacks. Importantly, the study evaluates only forest and product carbon stocks and does not include energy system emissions displacement. Therefore, a sustained forest carbon debt should not be interpreted as a definitive net climate negative, particularly where bioenergy displaces fossil fuels or incorporates carbon capture (BECCS). Conversely, scenarios yielding long-term increases in total forest carbon imply net climate benefits from a land-sector perspective and likely net negative emissions in combination with realistic energy system assumptions. Policy implications include: (1) timing and growth trajectory of biomass demand are critical to outcomes; (2) stand-level accounting is insufficient for policy evaluation; (3) constraints on biomass sourcing can shorten payback periods; (4) complementary carbon policies (payments for sequestration, conservation incentives, reforestation/improved management) can reinforce positive outcomes; and (5) promoting productivity in managed systems (new planting, genetics, silviculture) can increase biomass supply per hectare, aiding climate goals. The study also notes potential biodiversity and ecosystem service trade-offs from shifting unmanaged to managed forests, underscoring the need for integrated assessments that include non-carbon outcomes.

Using a dynamic global forest sector framework, the study demonstrates that forest carbon debt from bioenergy expansion is not inevitable or permanent; it persists mainly under low or zero biomass demand growth, low relative price growth, and accounting approaches that heavily weight reductions in harvested wood product carbon. When biomass demand grows faster than ~3%/yr, market responses expand forest area and management intensity sufficiently to recover initial carbon debts within decades, with some scenarios generating substantial end-of-century net increases in forest carbon. Supply-side regulations can shorten payback times but do not eliminate initial debts. The results support systems modeling over stand-level assessments for policy design and indicate that combining bioenergy expansion with carbon and forest management policies can deliver long-term climate benefits. Future research should link forest sector dynamics with energy-system IAMs to quantify full life-cycle climate impacts and assess trade-offs across product pools and ecosystem services, including biodiversity and other non-carbon values.

- The modeling focuses on forest and harvested wood product carbon pools and does not quantify energy system emissions displacement or full life-cycle impacts (no explicit coupling to IAMs in this study). - The GTM version used does not include prospective climate change impacts on forest growth within the simulation horizon (though baseline yield functions reflect current climate); nuanced soil carbon dynamics from forest operations are simplified. - Results are reported in decadal time steps and depend on assumptions about demand trajectories, elasticities, and residue availability (residues capped at 30% of yield). - Potential biodiversity and broader ecosystem service impacts from shifting unmanaged to managed forests are not modeled. - Accounting choices (e.g., inclusion/exclusion of market C) materially affect estimated carbon debt and payback periods.