Biofuels, as a renewable energy is clean and environmentally friendly. Global advocacy for climate change mitigation aims to minimize fossils fuel usage to support cleaner energy. While alternative energies (e.g., biofuels) extracted from feedstock (e.g., micro-algae), represent a promising role, their production requires reliably modelled Photosynthetically-Active Radiation (PAR). PAR models predict energy parameters (e.g. algal carbon fixation) to aid in decision-making at PAR sites

Critical to the biosphere is the PAR (400 = PAR = 700) nm utilised by microcellular organisms to develop chemical constituents that are the building blocks of marine and terrestrial food webs that in turn, regulate and sustain biomass production systems. Subsequently, the availability of PAR affects crop yield, biodiversity and ecosystems and CO2, water and energy control in plant-atmospheric systems through the carbon cycle. PAR predictions are important in biofuel-based renewable energy systems.

Biofuels provide 46 EJ of bioenergy globally, and drive a source of food, fodder and fibre, and hydrocarbons used for heat, electricity, liquid fuels and chemicals. Future knowledge of PAR is crucial to support increasing demand for sustainable energy, supporting agriculture, biological functions of plants and other bio-physical applications.

In this project, the students will utilise models to predict photosynthetically active radiation where ground based measured and satellite datasets are used. Artificial intelligence algorithms will be applied to simulate PAR and the predictive models will be improved by application of several, mathematical and statistical tools.

The project is suitable for students interested in renewable energy, engineering, biology, agriculture, atmospheric science, mathematics, physics and data science. The project is scalable for further research, such as to a Masters or a PhD program to advance research careers, acquire programming skills and modelling. The project present opportunity to develop new modelling & computational skills and research-publications within the Environmental Modelling and Simulation Research Group.

Professor Ravinesh Deo

• Assoc Prof Nathan Downs
• Professor Alfio Parisi
• Dr Nawin Raj

• Institute for Agriculture and the Environment
• International Centre for Applied Climate Sciences
• School of Agricultural and Environmental Sciences

• Agricultural Biotechnology
• Agriculture, Land and Farm Management
• Atmospheric Sciences
• Ecological Applications
• Environmental Biotechnology
• Environmental Science and Management
• Forestry Sciences
• Other Agricultural and Veterinary Sciences
• Other Biological Sciences
• Other Environmental Sciences

• Doctor of Philosophy (DPHD)
• Doctor of Philosophy (DPHD)
• Master of Research (MRES)
• Master of Research (MRES)