Environmental Impact Optimization of Microalgae Biorefinery Using Life Cycle Assessment and Evolutionary Computing

Abstract

Technology has paved the way for economic growth and the reduction of poverty. To achieve this, an enormous amount of energy is required to sustain one’s economic activity. However, due to industrialisation, global energy demand has been an issue for global sustainability. Biofuels from microalgae can be a potential alternative fuel for various applications to mitigate climate change. However, producing biofuels from microalgae is economically unfeasible due to its high capital and operation cost. Hence, a bio-refinery concept is a promising opportunity to valorise microalgae biomass to fill this gap. To investigate the environmental impact of microalgae bio-refinery with different scenarios, a Life Cycle Assessment (LCA) methodology will be utilised. Using computational intelligence (CI) algorithms such as genetic programming (GP) and genetic algorithm (GA) determined the relationships between the input parameters of the system and the environmental impact generated. LCA results showed that the transesterification process has the largest contribution, with 51.5 % of the total weight, followed by the cultivation process of the system. Lastly, environmental factors were minimised using GA, giving the best combination of input parameters.