The optimization of co2 sequestration by microalgae in pome medium
Recently, CO2emissions cause a lot of issues such as Green House gas emissions and drastic climate changes. The cultivation of microalgae in POME medium as nutrient sources are believed can help reduce CO2 emission to atmosphere and as well as act a POME treatment process. Microalgae has received a...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2013
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| Online Access: | http://umpir.ump.edu.my/id/eprint/10635/ http://umpir.ump.edu.my/id/eprint/10635/ http://umpir.ump.edu.my/id/eprint/10635/1/FKKSA-DEGREE-THAIBAH%20BINTI%20ALI.pdf |
| Summary: | Recently, CO2emissions cause a lot of issues such as Green House gas emissions and drastic climate changes. The cultivation of microalgae in POME medium as nutrient sources are believed can help reduce CO2 emission to atmosphere and as well as act a POME treatment process. Microalgae has received a lot of attention in recent years due to their fast growth and ability to accumulate high quantity of lipid inside their cells for biodiesel production while acting simultaneous functions for CO2 sequestration (Demirbas, 2011; Rahaman et al., 2011). The aim of the study is to optimize the CO2 sequestration by microalgae cultivation in POME medium. The study dealt with optimization of the level of % v/v of CO2concentration and illumination intensity (lx) for harvesting microalgae by centrifugation and optimization of biomass growth. The method involved are microalgae cultivation, the analysed of dry biomass and optimization process. The biomass is measured by method of dry cell biomass. In the optimization of biomass growth, the 22 factorial designs are used to investigate the effect of variableCO2concentration in the sparging air mixture and illumination intensity. The factorial experiments at the area containing the maximum biomass concentration are complemented with the Yates‟ Method, Linear Regression and Steepest Ascent, respectively. Results showedthat the highest biomass yield (g/L) is 1.129. In the optimization, for Yate‟s method, the illumination intensity shows a significant effect on microalgae growth instead of CO2 concentration. While, by using Linear Regression, the data was confirmed that the area investigated does not contain the maximum yield. The application of the Steepest Ascent method based on the linear equation of the factorial experiments indicate that the biomass yield can be increased as CO2 concentration and illumination intensity is constantly increased. Overall, main factor of illumination intensity and CO2 concentration are important for microalgae growth. |
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