Scientists from the University of Nottingham and CSIRO Australia have developed a cutting-edge model to evaluate the energy efficiency of walnut and pistachio shells as low-carbon fuels and better predict how these agricultural residues would perform in power plants.
As explained in a press release from the university, the model combines milling and combustion performance to optimize fuel selection for power generation. The tool enables energy producers to predict the burnout efficiency of different fuels — which refers to the extent to which carbon is burned during combustion — and thereby improve performance and conserve resources.
For the study, which was published in the Journal of the Energy Institute, the team analyzed the milling and burnout performance of four agricultural residues — pistachio shells, walnut shells, rice husks, and palm kernel shells — along with white wood pellets. All of these are considered biomass, which is organic matter derived from plants and animals that can be used as renewable energy sources.
In the United Kingdom, where the research was conducted, biomass is the second-largest source of clean energy, with over 9 million tons of biomass used annually for pulverized fuel combustion. This process involves grinding solid fuels, such as coal, into a fine powder and then burning it in suspension with air.
However, wood pellets and wood chips account for the majority of biomass in the U.K., and much of it is imported from the United States and Canada. Other forms of biomass make up just 1% of the country's renewable resources, which isn't ideal if there are supply chain bottlenecks. Using wood for biomass is also detrimental to the environment, as it contributes to deforestation and increased air pollution, and often releases carbon dioxide into the atmosphere faster than trees can regrow, thereby exacerbating climate change.
Adding other sources of energy, such as those derived from pistachio and walnut shells, to the energy mix could reduce the U.K.'s carbon output and improve air quality, benefiting both people and the planet.
The researchers' novel burnout prediction tool could play a role in these efforts because it utilizes char morphology, which uses image analysis to analyze the properties of the solid residue remaining after combustion, providing power operators with an easy way to assess the carbon loss of various fuels. If power plants are able to reduce emissions, it will contribute to the U.K.'s goal of becoming a net-zero country by 2050.
"By combining milling and combustion modelling, we can now predict fuel performance more accurately, helping power plants improve efficiency and reduce emissions, whilst diversifying their supply chains," Dr. Orla Williams, from the University of Nottingham's department of mechanical, materials and manufacturing engineering, said in the news release.
"It's a significant step forward in diversifying and decarbonizing the U.K.'s bioenergy portfolio but can also be applied to any country which … generates electricity on a large scale using coal, enabling other coal dependent economies to decarbonize."
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