The transition to a bio-economy is widely viewed as a promising pathway to decouple our energy supply from fossil fuels — more specifically, from the petroleum resources used in the transportation and chemicals sectors. Biomass offers a means of replacing fossil carbon with circular biogenic carbon, potentially providing a way to help stabilize atmospheric CO2 levels. Moreover, when combined with BECCS (bioenergy with carbon capture and storage), bioenergy has been described as a significant carbon-negative opportunity1. Yet, this transition relies on — and imposes many changes on — existing supply chains that support the agricultural and forestry sectors and the landscape itself. Optimizing parameters that minimize greenhouse gas (GHG) emissions through cost minimization at the landscape, supply chain and biorefinery levels is necessary for minimizing GHG emissions from bioenergy (Fig. 1). However, evaluating all three requires processing large spatial datasets and applying a nuanced optimization approach.
Now, writing in Nature Energy, Eric O’Neill, Caleb Geissler and Christos Maravelias at Princeton University offer valuable insights on opportunities to incentivize CO2 avoidance from biomass supply landscapes and biomass logistics supply chains2. They find that valuation of carbon capture and storage (CCS) alone at biorefineries, as described in current policy, does not lead to a global minimum in GHG emissions. Instead, the researchers suggest policy should incentivize GHG offset all along the field-to-fuel-product chain. Economic incentives targeted at agricultural and supply chain stakeholders can help to avoid GHG emissions before the biomass enters a proposed biorefinery, which may or may not include CCS. These incentives can take the form of a subsidy for biomass growers to motivate best management practices3 or for supply chain operators, all to minimize GHG emissions.
Previously, researchers have quantified the potential for sequestering carbon in marginal soils (land not suitable for growing food crops) when planting perennial grasses (bioenergy crops) at large scale4. Others have integrated those findings into life cycle assessments of biofuel pathways that, when combined with engineering techno-economic tools, quantify5 the benefits and costs of near-commercial technology alternatives, supporting investment decisions for carbon abatement. While techno-economic and life cycle assessments provide the critical data for characterizing the cost and environmental footprint of biofuel production pathways, they do not predict the likelihood of technology investment and adoption by location. However, optimization methods can offer this kind of insight.
Previous optimizations have sought to minimize biofuel GHG emissions through selecting portfolios of biomass from targeted soils6 that yield low carbon feedstocks. Although demonstrating a vast range of biomass GHG intensity resulting from diverse soils in the landscape, and the opportunity to select the best-performing land7 to minimize the feedstock’s carbon footprint, previous estimates did not also control for parameters related to biomass supply chain logistics or the biorefinery’s design. Similarly, studies focused on supply chain8 or biorefinery optimization9 assumed uniform biomass and landscape characteristics. To date, research has not tackled all three parameters: landscape, supply chain and biorefinery.
Focusing on the US Midwest, O’Neill and colleagues calculate the cost and GHG mitigation potential for the full supply chain needed to produce cellulosic biofuel. To do this, they simultaneously consider the three elements that define the set of processes that span a field-to-gate input to economic use of bioproducts.
The researchers use mixed-integer linear optimization to model the system. From the model they obtain predictions of biofuel technology adoption by location within the bioenergy supply region under alternative policy incentives. The model predicts technology portfolio, biorefinery siting, and biomass supply from marginal lands by minimizing annual costs; low GHG emissions help to minimize those costs when avoidance credits are part of the biorefinery’s total costs. Whether a biorefinery includes CCS depends on the cost of electricity, a factor dictated by the supply chain. Furthermore, high-GHG-emitting-electricity derived from fossil fuels tends to lower operating costs to biorefineries, which can compromise the CCS benefit when sequestering the CO2 and also consumes power derived from fossil fuel. Locating the biorefinery where electricity costs are low may also miss the opportunity to seek biomass resources with the lowest GHG footprint.
The team finds that if policy does not credit GHG avoidance at the landscape level and along the supply chain as it credits CCS, biorefineries may be sited in areas with high-emitting electricity grids and biomass supplies with large GHG footprints, potentially losing the carbon negative benefit of bioenergy. Given that biomass feedstock logistics influence the cost and GHG emissions of biofuel supply, the researchers demonstrate that policy incentives that credit GHG emissions avoidance all along the field-to-product chain will lead to globally minimal emissions. In particular, they find that carbon abatement policy that includes CO2 sequestration credits priced at a minimum of US$100 per Mg can lead to selecting technology-landscape and supply chain components that minimize GHG emissions over the biofuel production cycle. Previous optimizations of emerging biofuel technology have considered only a small set of control parameters that mostly focused on the biorefinery or the supply chain and assume a fixed biomass supply landscape: O’Neill and colleagues now capture all three with a message that is eye-opening; one that, if ignored, could lead to failed policy for biofuels.
The scenarios modelled by the researchers reveal the tradeoff for bioenergy investment trajectories with rising CO2 sequestration credits across the supply chain in contrast to when that credit is applied only to biorefineries that invest in CCS. Only when GHG offsets are incentivized along the full supply chain beginning at the biomass production landscape do we attain a carbon mitigation trajectory that leads to large-scale carbon mitigation. With current policies, monetary values are only applied to CCS at cellulosic biorefineries. Thus, a holistic GHG avoidance policy that acknowledges the field-to-gate is needed for CO2 stabilization through a bioeconomy.
The work by O’Neill and colleagues considers investment with today’s electricity grid — a grid still largely comprised of natural gas and coal power plants. However, future electricity grids are moving towards wind and solar renewable energy10. Thus, supply chains are operating under dynamic conditions, and locations having a high GHG-emitting electricity supply may also undergo decarbonization in the near term. Additionally, there is uncertainty in the GHG emissions intensity of electricity supplied from the whole Midwest regional grid and O’Neill et al. consider state-averaged GHG emission factors for the supplied power. Therefore, in the future we need to better understand location factors for bioenergy investment decisions in a decarbonizing economy. In spite of that uncertainty, the researchers uncover an important policy conclusion: incentivizing GHG mitigation beginning from the landscape and continuing along the supply chain can lead to a significant carbon negative bio-economy.