(310b) Optimization of Bioenergy with Carbon Capture and Storage in the USA Transportation Sector Under Governmental Policies | AIChE

(310b) Optimization of Bioenergy with Carbon Capture and Storage in the USA Transportation Sector Under Governmental Policies

Authors 

Geissler, C. - Presenter, Princeton University
Maravelias, C. T., Princeton University
Ryu, J., University of Wisconsin-Madison
While electrification of transportation can reduce the need for fossil fuels, there is still significant demand for liquid fuels, especially for heavy duty transportation and aviation. Cellulosic biomass is a promising source for these fuels because of very low, and when coupled with carbon capture and storage (CCS), negative emissions. Significant research in this area has led to many potentially viable conversion options for biomass to fuels, such as fermentation, gasification and Fischer-Tropsch synthesis, gasification and methanol-to-gasoline, and pyrolysis and hydrotreating. Each conversion option also results in one or multiple streams of differing concentration of CO2 that could be captured: pyrolysis generates only a flue gas stream with dilute CO2, gasification results in a nearly pure CO2 from the cleaning of syngas and a dilute flue gas stream, and fermentation produces nearly pure CO2 while producing ethanol, CO2 in a biogas stream from anaerobic digestion of wastewater.

There are several government policies and incentives that are relevant to biofuel production. First, there is the Renewable Fuel Standard (RFS), which dictates that the transportation fuel sold in the USA must contain a minimum volume of renewable fuels. These minimum volumes are set for conventional corn ethanol, biomass-based diesel, and other cellulosic biofuels. Second, the passing of the Inflation Reduction Act (IRA) renewed production credits of $1/gallon of many biofuels, with a higher credit of $1.25-$1.75/gallon for sustainable aviation fuel (SAF), depending on its life-cycle emissions. The IRA also increased the existing sequestration credit for CO2 sequestered in secure geological storage to $85/Mg CO2.

While previous studies have examined the CCS options for bioenergy with carbon capture and storage (BECCS) technologies individually or in comparison to a few others, the many combinations of biofuel conversion and CCS technologies have not yet been comprehensively studied on a large scale in the USA, nor have they been studied in the context of the many recently updated government policies. To consider the competition between BECCS and other existing energy technologies, we use The Integrated MARKAL-EFOM System (TIMES) model, a long-term energy systems optimization that can be coupled with a database of energy resources and technologies in the commercial, industrial, residential, transportation, and electricity generation sectors in nine different regions of the USA. We improve the model to include a rich suite of potential biomass conversion and CCS technologies for a wide range of biomass feedstocks, including agricultural residues, corn stover, urban wood waste, forest resources, and grassy and woody energy crops. We also add region-specific CO2 transportation costs and marginal injection cost curves based on the location of potential biorefineries from the EPA’s RE-Powering America Land Initiative Mapper and locations, capacity, and injection cost of saline aquifers from the National Energy Technology Laboratory’s CO2 Saline Storage Cost Model. Lastly, we apply a projected RFS and current USA tax credits updated in the IRA to study the potential of bioenergy in the USA under realistic cost scenarios.

We first examine the impact that a continuation of the Renewable Fuel Standard (RFS) would have on USA transportation emissions and the portfolio of selected biofuel technologies without any CCS. We find that the projected RFS standard for advanced biofuels is primarily met by the production of gasoline and diesel from pyrolysis, and the remaining RFS requirements are met by corn ethanol. In scenarios where there is increased availability of biomass and increased oil price, advanced biofuel production increases to exceed the total RFS minimum, and corn ethanol production decreases to its RFS minimum. However, we find that even under high biomass availability and oil price, USA transportation emissions would decrease by a maximum of 20% in 2055 compared to 2020 levels.

We then remove the RFS constraints, and instead include all liquid biofuel production and CO2 sequestration credits in the IRA. To take full advantage of the SAF production, we also add additional conversion options to the biofuel sector to produce SAF from the separation of the diesel fraction produced by gasification and pyrolysis, or by the upgrading of ethanol. We find that under these credits, gasification and Fischer-Tropsch synthesis is the technology installed with the greatest capacity, with the amount of CCS depending on the region, and the corn ethanol quickly phases out of production. However, with existing credits, transportation emissions still do not decrease by more than 20% in 2055 compared to 2020. Therefore, we examine the impact of increased credits for CO2 sequestration and SAF production and find that the optimal biomass conversion technology and level of CCS are dependent on both credits. The optimal technology and level of CCS are especially dependent on the CO2 sequestration credit, and we show that a relatively minor increase in the credit for CCS from biorefineries could lead to a dramatic increase in bioenergy production, and a 50% decrease in total USA transportation emissions from BECCS alone. We also study the impact of increased oil price and increased biomass availability with IRA credits, which lead to dramatic changes in which biomass sources are primarily used within each region. Overall, we find that while current incentives would likely lead to relatively small amounts of bioenergy production in the context of the entire USA, there are many different scenarios that could lead to bioenergy playing a significant role in the USA transportation sector.