A global meta‐analysis of forest bioenergy greenhouse gas emission accounting studies

Abstract

The potential greenhouse gas benefits of displacing fossil energy with biofuels are driving policy development in the absence of complete information. The potential carbon neutrality of forest biomass is a source of considerable scientific debate because of the complexity of dynamic forest ecosystems, varied feedstock types, and multiple energy production pathways. The lack of scientific consensus leaves decision makers struggling with contradicting technical advice. Analyzing previously published studies, our goal was to identify and prioritize those attributes of bioenergy greenhouse gas (GHG) emissions analysis that are most influential on length of carbon payback period. We investigated outcomes of 59 previously published forest biomass greenhouse gas emissions research studies published between 1991 and 2014. We identified attributes for each study and classified study cases by attributes. Using classification and regression tree analysis, we identified those attributes that are strong predictors of carbon payback period (e.g. the time required by the forest to recover through sequestration the carbon dioxide from biomass combusted for energy). The inclusion of wildfire dynamics proved to be the most influential in determining carbon payback period length compared to other factors such as feedstock type, baseline choice, and the incorporation of leakage calculations. Additionally, we demonstrate that evaluation criteria consistency is required to facilitate equitable comparison between projects. For carbon payback period calculations to provide operational insights to decision makers, future research should focus on creating common accounting principles for the most influential factors including temporal scale, natural disturbances, system boundaries, GHG emission metrics, and baselines.

Range and uncertainties in estimating delays in greenhouse gas mitigation potential of forest bioenergy sourced from Canadian forests

“…To date, studies have mostly focused on estimating a unique and precise C debt repayment time or C parity time for particular case studies without addressing any sources of variation. For correct accounting, however, estimates need to take uncertainty into account, from variations in the biomass supply chain to the realism of the counterfactual scenario (Johnson et al ., ; Bowyer et al ., ; Buchholz et al ., , ). We found that the length of the uncertainty period can be short and inconsequential for some scenarios (e.g., harvest residues).…”

“…Factors regulating the GHG mitigation potential of bioenergy projects and the underlying large variation in C parity times include biomass feedstock source and processing, the type of fossil fuel replaced, energy conversion efficiency, tree growth rate, and the definition of the counterfactual ‘reference’ scenario, that is, what would have happened to the forest land if biomass had not been sourced and used for bioenergy? (Lamers et al ., ; Buchholz et al ., , ). Because many of those factors usually differ among studies, it is often difficult to compare C parity times among a variety of forest bioenergy uses.…”

Opportunities and risks for sustainable biomass export from the south‐eastern United States to Europe

“…A critical consideration with most of these studies is that in their calculations of the life‐cycle GHG emissions from bioenergy systems they consider combustion of biogenic fuels to be carbon neutral provided there is no loss of carbon stock in the forest. Some stakeholders have raised concerns with this approach . However, as this is the current approach of the EC, we do not consider GHG balance to be a practical constraint on biomass sourcing from the US SE for this study.…”

Carbon balances of bioenergy systems using biomass from forests managed with long rotations: bridging the gap between stand and landscape assessments

“…Risks and consequences of storms, wildfires, forest pests and diseases are also not considered in this study, although we acknowledge that such events can have a strong influence on net carbon balances (cf. Buchholz et al ., ).…”