Bioenergy from forestry and changes in atmospheric CO2: Reconciling single stand and landscape level approaches

Analyses of global warming impacts from forest bioenergy systems are usually conducted either at a single stand level or at a landscape level, yielding findings that are sometimes interpreted as contrasting. In this paper, we investigate and reconcile the scales at which environmental impact analyses of forest bioenergy systems are undertaken. Focusing on the changes caused in atmospheric CO2 concentration of forest bioenergy systems characterized by different initial states of the forest, we show the features of the analyses at different scales and depict the connections between them. Impacts on atmospheric CO2 concentration at a single stand level are computed through impulse response functions (IRF). Results at a landscape level are elaborated through direct application of IRFs to the emission profile, so to account for the fluxes from all the stands across time and space. Impacts from fossil CO2 emissions are used as a benchmark. At a landscape level, forest bioenergy causes an increase in atmospheric CO2 concentration for the first decades that is similar to the impact from fossil CO2, but then the dynamics clearly diverge because while the impact from fossil CO2 continues to rise that from bioenergy stabilizes at a certain level. These results perfectly align with those obtained at a single stand for which characterization factors have been developed. In the hypothetical case of a sudden cessation of emissions, the change caused in atmospheric CO2 concentration from biogenic CO2 emissions reverses within a couple of decades, while that caused by fossil CO2 emissions remains considerably higher for centuries. When counterfactual aspects like the additional sequestration that would have occurred in the forest if not harvested and the theoretical displacement of fossil CO2 are included in the analysis, results can widely differ, as the CO2 debt at a landscape level ranges from a few years to several centuries (depending on the underlying assumptions considered).