Enhancing efficiency of biofuels from microalgae using a statistical and mathematical approach.

Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2012.

Algae are primary producers in aquatic ecosystems and are thus the most important organisms in maintaining ecosystem functioning and stability. The usage of algae by humans is quite extensive; they act as an ingredient in aquaculture feed, a potential biomedical resource, as a fertiliser and as a nutritional source. Recently, algae have been identified as a third generation biofuel feedstock for fuel generation which essentially means that algae are more efficient, net carbon neutral and have less impacts on the environment. Algae as organisms are extremely sensitive to changes in the immediate environment. The interaction of parameters with each other causes minute changes in the environment which may alter the algae biomass present and the lipids that can be extracted from the biomass. The focus of this study is to model and determine which conditions maximise algal biomass and the subsequent lipids that can be extracted from the biomass. This will allow biofuel producers to understand which conditions are the best for harvesting algae in artificial conditions or harvesting algae from the wild. Furthermore, the model developed has broad application for biofuel specialists, pollution remediation specialists and biologists. This model developed is able to determine the present state of the algal bloom and uses the present state to predict the future state of bloom hence determining the optimal conditions to harvest. The model was developed under optimal ranges described by the Food and Agriculture Organisation (FAO) and designed to replicate the most common combinations of parameters present in the wild. For the purposes of this study, various combinations of parameters within their optimal ranges that is temperature (18 – 24°C), salinity (20 – 24 p.p.t.) and photoperiod (25 – 75% light exposure) were assessed. The model was run for 72 hours with sampling every 6 hours. Every six hours, algal growth was measured by the biomass present (chloro-pigments used as estimators); this was done by fluorescence. Lipids were then extracted from algal biomass using the Bligh and Dyer method (1959). Spline curves were fitted to the data and analysis performed using Mathematica 8.0. It was found that photoperiod was the most important variable in controlling algal growth. Furthermore, lipids extracted from biomass were at their highest when algae were exposed to the conditions 75% light exposure, 21°C and 22 p.p.t. These conditions would allow for the highest amount of biofuel to be produced. Generally, algae biomass trend graphs mimic lipid trend graphs over the 72 hour period that is when lipids are at their maximum, biomass concentrations are at their maximum. It can be concluded from time model that the best time to harvest biomass is 48 hours from the initial start time of algal growth to gain the highest amount of lipids for biofuel production.