LAUSR

Abstract Increasing demand for energy, the food versus fuel debate, and competitive market pressure for environmental sustainability are driving bioethanol supply chain decision-makers to use second-generation biomass feedstocks and reduce carbon emissions. Currently, most biomass supply chains use edible first-generation feedstocks to produce bioethanol, therefore incentivizing them to switch to a non-edible second-generation feedstock seems necessary and motivating in this context. Implementing various carbon policy mechanisms to curb carbon emissions plays a vital role in planning bioethanol supply chains. This research proposes a quantitative optimization model for designing and planning biomass bioethanol supply chains considering monetary incentives. The model is developed further by investigating the impact of four different carbon policies including carbon tax, carbon cap, carbon cap-and-trade, and carbon offset policy on the supply chain decisions. Also, the proposed model compares a first-generation (corn) and two different second-generation (corn stover and switchgrass) bioethanol supply chain networks to identify a better alternative for first-generation bioethanol producers. The presented methodology is implemented by applying a case study for the state of North Dakota to derive more realistic results and policies. The results show that switchgrass is a better alternative for corn rather than corn stover both economically and environmentally. A minimum incentive of $0.204/liter and $0.167/liter of bioethanol are needed to switch from corn-based to corn-stover-based and switchgrass-based bioethanol supply chains, respectively. Also, carbon cap-and-trade is the best carbon policy since it causes the lowest profit loss (31.5%) and the highest reduction in emissions (up to 1.98%) compared to other policies.