Researchers seek ‘commodity-style grading system for biomass’ 

Source: Amanda Peterka, E&E reporter • Posted: Wednesday, April 29, 2015

The national laboratories are discovering that not all biofuel inputs are created equal.

Some non-food crops that are being explored for biofuels production have higher yields on the farm field, while others yield more fuel at the end of the biofuels production process.

In their “Field to Fuel” project, researchers from three national labs are trying to identify all the trade-offs in biofuel production and to find the blends and ratios of plant inputs that would result in the biggest bang for the buck.

“The ultimate goal is to develop a commodity-style grading system for biomass based on its conversion performance,” said Daniel Howe, a chemical engineer at Pacific Northwest National Laboratory and leader of the project. “An example would be in the oil industry. They have light and heavy and sweet and sour grading of crude, and different products.”

Scientists from PNNL, Idaho National Laboratory and the National Renewable Energy Laboratory are all participating, and the Department of Energy’s Bioenergy Technologies Office is providing funding.

The research was prompted by DOE’s Billion Ton Study, which was first conducted in 2005 and updated in 2011. The study identified all the biomass that would be available to produce non-food biofuels in the country.

Though the study found that the country would produce a billion dry tons of biomass annually in a sustainable manner, researchers from the labs began to recognize that the performance of individual feedstocks varies in the full life cycle of biofuels production, Howe said. So the national labs launched a project to “performance test” feedstocks using different biofuel technologies.

“What are the best feedstocks we could possibly use? What are the worst? How do we define boundaries, and how do we define and test where on the spectrum different types of biomass fit in?” Howe asked.

Earlier this month, the team from the three labs published a report in the journal Energy & Fuels that evaluated the performance of two blends and six pure cellulosic biofuel feedstocks: pine without bark, whole-tree pine with bark, tulip poplar, hybrid poplar, switchgrass and corn stover.

The researchers ran all the inputs through a small-scale biorefining process that uses a high-temperature process called fast pyrolysis to produce a bio-oil that is upgraded into a hydrocarbon fuel.

“Understanding conversion performance is a critical element of both the design and successful operation of an integrated biorefinery,” the authors wrote.

The team discovered a lot of variation in the performance of the different inputs and identified several trade-offs. Overall, switchgrass yielded the least fuel, while the pine without bark yielded the most.

One of the goals was to identify the trade-offs between plant inputs to help farmers and refiners better judge the worth of different feedstocks.

Farmers “make their money by maximizing yield, and so the more that they can grow, the happier they are,” Howe said. “But that doesn’t take into effect the quality of the biomass they are producing.”

For example, farmers can grow a lot of switchgrass on a plot of land, but if that switchgrass has a lot of dirt in it that needs to be removed, it will have a detrimental effect on the overall biofuels process.

One surprising discovery in the report published earlier this month was that blends of different types of feedstocks behave in a nonlinear manner — meaning individual performance levels of feedstocks couldn’t just be added up to determine how the blend would act in the biofuel process.

The team hopes to hammer down the various factors that are causing the relationship.

Howe said that future research would also focus on examining how municipal solid waste and construction and demolition waste perform in hydrothermal biofuel technology. The team is also trying to develop a computer model that would allow a user to plug in an input into a biofuel process to see how it would perform.