Environmental impact prediction of microalgae to biofuels chains using artificial intelligence: A life cycle perspective

A. P. Mayol, J. L.G. San Juan, E. Sybingco, A. Bandala, E. Dadios, A. T. Ubando, A. B. Culaba, W. H. Chen, J. S. Chang

研究成果: Conference article同行評審

7 引文 斯高帕斯(Scopus)


Biofuels derived from microalgae is an emerging technology that can supply fuel demand and alleviate greenhouse gas emissions. However, exclusively producing biofuels from microalgae remains to be commercially unsustainable because of its high investment and operating costs. A promising opportunity to address this are algal bio-refineries. Nonetheless, there is still a need to verify the environmental sustainability of this system along its entire process chain, from raw material acquisition to end-of-life. This study utilizes a life-cycle perspective approach to assess the sustainability of the algal bio-refinery and developed environmental impact prediction model using artificial intelligence, particularly adaptive neuro fuzzy inference system. Results will indicate the environmental impacts of a bio-refinery system identifying its major hotspots on different environmental impact categories. Results show that in the investigated proposed algal bio-refinery, the transesterification process had a huge contribution on the overall environmental impact having over 51.5 % of the total weight. In addition, ANFIS results showed the correlation of input parameters with respect to the environmental impact of the system. The model also indicated that there is a perfect correlation between the two parameters. The model and its accuracy should be further validated with the use of real data.

期刊IOP Conference Series: Earth and Environmental Science
出版狀態Published - 2020 4月 6
事件International Conference on Sustainable Energy and Green Technology 2019, SEGT 2019 - Bangkok, Thailand
持續時間: 2019 12月 112019 12月 14

All Science Journal Classification (ASJC) codes

  • 一般環境科學
  • 一般地球與行星科學


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