Forest Bioenergy or Forest Carbon? Assessing Trade-Offs in Greenhouse Gas Mitigation with Wood-Based Fuels

Abstract

The potential of forest-based bioenergy to reduce greenhouse gas (GHG) emissions when displacing fossil-based energy must be balanced with forest carbon implications related to biomass harvest. We integrate life cycle assessment (LCA) and forest carbon analysis to assess total GHG emissions of forest bioenergy over time. Application of the method to case studies of wood pellet and ethanol production from forest biomass reveals a substantial reduction in forest carbon due to bioenergy production. For all cases, harvest-related forest carbon reductions and associated GHG emissions initially exceed avoided fossil fuel-related emissions, temporarily increasing overall emissions. In the long term, electricity generation from pellets reduces overall emissions relative to coal, although forest carbon losses delay net GHG mitigation by 16-38 years, depending on biomass source (harvest residues/standing trees). Ethanol produced from standing trees increases overall emissions throughout 100 years of continuous production: ethanol from residues achieves reductions after a 74 year delay. Forest carbon more significantly affects bioenergy emissions when biomass is sourced from standing trees compared to residues and when less GHG-intensive fuels are displaced. In all cases, forest carbon dynamics are significant. Although study results are not generalizable to all forests, we suggest the integrated LCA/forest carbon approach be undertaken for bioenergy studies.

Forest carbon accounting methods and the consequences of forest bioenergy for national greenhouse gas emissions inventories

“…These results are similar to prior studies McKechnie et al, 2011), with a small improvement in GHG emissions reductions due to lower upstream emissions from wood pellet manufacture in the present study. Relative to the coal reference pathway, domestic use of wood pellets reduces GHG emissions by 92%.…”

“…The Incremental Carbon Impact baseline is defined based on continued forest management activities in the absence of any harvesting for wood pellet production, as in McKechnie et al (2011). Harvest for wood pellet production is considered additional to the baseline.…”

“…The flexibility of bioenergy as a potential alternative energy source for heat, transport, and electricity applications has led to its inclusion in national strategies for reducing GHG emissions and increasing renewable energy penetration (e.g., UK DECC, 2012). Risks associated with forest bioenergy production, in particular the impact on forest carbon sequestration and potential GHG emissions consequences, have been identified in several studies (e.g., Searchinger et al, 2009;McKechnie et al, 2011;Vanhala et al, 2013). Of particular importance to national GHG inventories is how trade-offs between forest carbon stocks and bioenergy production are accounted for within current and future international climate change mitigation agreements.…”

“…Research has highlighted the possible shortcomings of this accounting approach, as it risks omitting potentially significant carbon stock changes resulting from bioenergy production (e.g., Searchinger et al, 2008). Recent studies of bioenergy have developed integrated life cycle and forest carbon analysis methods to include forest carbon impacts within life cycle studies (e.g., McKechnie et al, 2011;Helin et al, 2013). Net GHG emissions, inclusive of life cycle activities and forest carbon impacts, are time dependent: forest carbon removals at harvest are compensated by forest regrowth, which occurs over a comparatively long timescale.…”

“…Net GHG emissions, inclusive of life cycle activities and forest carbon impacts, are time dependent: forest carbon removals at harvest are compensated by forest regrowth, which occurs over a comparatively long timescale. Trade-offs between forest biomass-based bioenergy production and forest carbon stocks have been found to result in increased GHG emissions relative to fossil fuels lasting decades to more than 100 years (e.g., Kayo et al, 2011;McKechnie et al, 2011;Ter-Mikaelian et al, 2011).…”