Time-Dependent Climate Impact of Utilizing Residual Biomass for Biofuels—The Combined Influence of Modelling Choices and Climate Impact Metrics

Abstract

Understanding the influence of method choices on results in life-cycle assessments is essential to draw informed conclusions. As the climate impact of bioenergy remains a debated topic, the focus of this study is how the chosen temporal framing influences a comparison of the climate impact of utilizing residual biomass for biofuel production to that of leaving the biomass to decay. In order to compare the biofuel scenario to its corresponding reference scenario where biomass is left to decay, a variety of analytical approaches were used: using time-aggregated and time-dependent life-cycle inventories and climate-impact assessment methods, assuming biogenic carbon to be climate neutral or not, using metrics for cumulative or instantaneous climate impact, and with different time horizons. Two cases of residual biofuel feedstocks were assessed: logging residues from Norway spruce forest, and straw from wheat cultivation. Consideration of the studied method choices appears to be especially relevant for forest residual biomass, as illustrated by the ranges of parity times for logging residues (25 to 95 years), and the results which vary with the chosen climate-impact metric, time-horizon, and approach for including biogenic carbon. Illustrating the time-dependence of results can, in general, provide a better understanding of the climate impact of utilizing residual biomass for biofuels.

Supply Chain Management for Bioenergy and Bioresources: Bridging the Gap between Theory and Practice

“…There are numerous issues that need to be investigated. Biomass harvesting time [13], biomass moisture and loss of dry material [14], seasonality, dependance on weather/microclimatic conditions as well as the impact on these conditions [15], distance from bioresources' source to energy recovery facilities [16], cultivation energy requirements [17], operational practices and machinery performance [18,19], and market maturity [20] are only a few examples of unpredictable parameters in the case of bioresources that transform the relatively easy-to-handle task of supply chain management into a difficult problem.…”