Publication Details

Title : Carbon dynamics for biofuels produced from woody feedstocks
Publication Date : May 01, 2018
Authors : J. Han, C. Canter, H. Cai, M. Wang, Z. Qin, J. Dunn
Abstract : Growing biomass incorporates atmospheric carbon and stores it as biogenic carbon. In a biorefinery, some portion of this biogenic carbon is converted into a biofuel, which then emits biogenic CO2 through the biofuel combustion. In the Life Cycle Analysis (LCA) of biofuels, it is generally assumed that this biogenic CO2 emission is offset by atmospheric carbon uptake during biomass growth, establishing the so-called carbon neutrality of biogenic carbon. When the elapsed time between biomass growth and biofuel combustion is short, this assumption is defensible. In the case of slower-growing forestry-derived bioenergy feedstocks, however, this time window may be significantly longer and the assumption of carbon neutrality is weaker. To address the carbon neutrality issue of woody-biomass-derived biofuels, this study investigated the carbon dynamics of producing bioenergy from woody biomass. Specifically, key factors affecting the net GHG emissions results, such as biomass species, land analysis framework, and the sequencing of the planting and harvest steps, were examined.

This study examined two different types of analysis frameworks: stand-level and landscape-level analyses. A stand-level analysis examines the impacts of temporal carbon dynamics of carbon emissions/sequestration over time, which is a critical issue in LCAs of woody biomass products. The stand-level analysis is based on a narrowly defined biomass growth scenario and harvest geographic boundary. The specific growth scenario may have high variability, especially with long growth cycles. A landscape-level analysis, on the other hand, is appropriate for conducting LCAs of products from managed forest assuming sustainable forestry management, e.g., the overall carbon fluxes associated with forest growth and harvest/mortality are balanced. A landscape-level analysis can represent managed (or private) forests that are intended to provide a constant supply of biomass to their customers, including bioenergy plant operators.

This study included two general types of forest biomass: managed softwoods, represented by Douglas fir, loblolly pine, and spruce/fir mixtures, and dedicated short-rotation woody crops (SRWCs), represented by poplar, willow and eucalyptus. The softwoods were selected to represent the dominant wood species found in the Pacific Northwest (Douglas fir), the southern United States (loblolly pine), and the northeastern U.S. (spruce/fir). The SRWCs were selected to represent systems that have been commercially deployed in the Pacific Northwest (poplar), the southern U.S. (eucalyptus), and the northeastern U.S. (willow).

The sequencing of the planting and harvest, and biogenic carbon release steps, also had a major impact on the carbon accounting. One analysis framework (Cycle 1) starts with 1) the “harvest” of standing trees, followed by 2) the production and use of the biofuels, and 3) replanting, and recapture of the released carbon. An alternative framework (Cycle 2) starts with 1) the planting of the wood and the capture of atmospheric carbon, followed by 2) harvesting of the trees, and 3) release of the biogenic carbon in the production and use of the biofuel. With Cycle 1, the carbon emissions released from biofuel production and combustion are allocated before biomass growth and harvest, and handled accordingly by the CO2 emission-discounting method; the slow growth of softwoods (especially Douglas fir and spruce/fir) results in a large portion of the upfront carbon debt being recovered slowly. With discounting, the carbon uptake during biomass regrowth becomes less significant. Cycle 2 is appropriate for SRWCs because these will be established dedicatedly for bioenergy or bioproducts production, which starts with the silviculture, and Cycle 1 is more appropriate for softwoods because it is more realistic to collect the thinnings and residues when they are readily available for bioenergy production than to wait for decades to grow a mature softwood stand when the thinnings and residues could be made available.

Using both stand- and landscape-level analyses, this work shows that biofuels derived from woody biomass with longer growth cycles and slower growth rates, e.g., Douglas fir and spruce/fir, have much larger variations in GHG emissions depending on the land analysis framework and CO2 emission cycle compared to biofuels derived from woody biomass with shorter growth cycles and faster growth rate, e.g., SRWCs. For example, the GHG emissions associated with renewable gasoline from eucalyptus, poplar, and willow range from 40 to 47, 37 to 41, and 45 to 50 g CO2e/MJ, respectively, depending on the analysis cycles, in comparison to 94 g CO2e/MJ for petroleum gasoline. On the other hand, the renewable gasoline from loblolly pine, Douglas fir, and spruce/fir generate GHG emissions ranging from 19 to 42, 13 to 67, and -10 to 56 g CO2e/MJ, respectively, depending on the analysis cycles. Thus, much caution is needed to handle the temporal carbon dynamics issue for biofuels from woody biomass with long growth cycles and slow growth rates.

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