Exploring greenhouse gas emission reduction potential of microalgae-derived bio-fuel production process

• Main Authors: Jhen-Wei Chen, 陳振偉
• Other Authors: Yasuhiro Fukushima
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/83512523906200717794

碩士 === 國立成功大學 === 環境工程學系碩博士班 === 97 === Application of microalgae cultivation for carbon dioxide (CO2) fixation and bio-fuel production attracts attentions and great expectations as one of the countermeasures to climate change. This is due to the fact that microalgae are the most productive bio-resources considering unit area of land. By utilizing selected productive microalgae and CO2 emitted from an industrial process (ex. power plants), microalgae can be cultivated intensively and provide raw materials for bio-fuel, such as bio-diesel and bio-ethanol. However, additional environmental loads in cultivation (i.e. land area for accepting solar irradiation, consumption of energy, nutrients and water) and conversion to the bio-fuel (i.e. drying, chemical process duties) should be accounted for in highlighting the true potential of this technology. Taking into account of CO2 emission rate from industrial process and other local conditions, choice of microalgal species, cultivation method and its application should be made from a life-cycle point of view. The objective of this study is to evaluate greenhouse gas (GHG) emission reduction potential of this emerging technology using life cycle assessment. Numerous variations in processes, conditions and species are found around this technology: therefore, in this study, a model for evaluation is established. Using the model, various combinations of process and species alternatives become possible by using the case study provided in this thesis as a template. Consumption of chemicals and energy, GHG emission, GHG emission reduction potential is evaluated for individual combination of processes and microalgal species. As a first hypothetical case study, application of Nannochloropsis oculata, the lipid-rich (about 50.4% of lipid content) microalgae for an imaginary industrial process is evaluated using the model. After cultivation in a raceway pond, the extracted lipid is used for bio-diesel production via alkali-catalyzed process. In addition to bio-diesel, there is carbohydrate (about 55%) in microalgal residue, which can be utilized as a substrate for bio-ethanol production via saccharification and fermentation. The technologies (ex. chemicals and energy consumption, and GHG emission) for producing bio-ethanol from microalgal carbohydrate (polysaccharide) are missing so far. To estimate the missing data for ethanol fermentation, sugarcane molasses- and switchgrass (cellulose)-derived bio-ethanol are used as maximum and minimum bounds. Assumption behind is that the efficiency of technique for production of microalgae-derived bio-ethanol could be considered as somewhere between that of molasses- (i.e. sucrose) and cellulose- (long polymer of glucose) derived ethanol. In addition to simulating the inventories of microalgae-derived bio-fuel production process, opportunities in enhancement of GHG emission reduction potential is highlighted. Namely, a shift from lipid extraction using conventional squeezing into solvent extraction is evaluated. Next, comparison of different microalgae-derived bio-fuel production process is made using the model. In this study, the carbohydrate-rich microalgae, Thermosynechococcus sp. is chosen for an alternative to Nannochloropsis oculata. This species is isolated from an alkaline hot spring in eastern Taiwan. The characteristic of Thermosynechococcus sp. has higher tolerance and productivity under high temperature (40~50℃) and high pH conditions. These characteristics could possibly make this species advantageous in carbon fixation from industrial process such as power plant, where utilization of waste heat could be expected. The comparison of the technology provides the researchers of respective technologies with directions of further development and optimization of conditions.