Parisa A. Bahri

This study investigates the effect of indirect greenhouse gas (GHG) emissions on the optimal long-term planning and short-term operational scheduling of a desalination-based water supply system. The system was driven by grid-electricity and surplus output from residential rooftop photovoltaics to deliver water and energy to urban areas. The interactive two-level mixed integer linear programming model took into account demands, system configurations, resources capacities and electricity tariffs as well as GHG emission factor associated with the source of grid electricity. Both system and carbon abatement costs were considered in the formulation of the objective function. The optimal decisions for Perth (Australia) resulted in $47,449,276 higher discounted total cost but 51,301.3 tCO2eq less GHG emissions over 15 years planning horizon compared to when only system costs were minimised. Finally, the predominant effect of the indirect GHG emissions costs over system costs on the optimal solutions indicated their high sensitivity towards the source of purchased grid electricity.

Models are useful and cost effective tools for understanding the behaviour of a system. As microalgae are potential raw material sources for biofuel production, the need for a rigorous model to predict their growth performance in various conditions is critical. Despite good agreements between models and indoor microalgal experiments, when it comes to the real life outdoor cultivation of microalgae most of these models have not been validated and hence cannot be trusted. Among all the conditions affecting microalgal growth, light is the most significant one and its role in outdoor culture becomes more important as the light intensity varies significantly during the day. In this study a new microalgal growth model is derived based on the energy balance of an outdoor raceway pond, to predict the growth rate of Tetraselmis in terms of cell density as a function of daily light exposure. Two sets of data are used in this study, one for training the model and estimating its parameters and the other to test the model and validate its performance. The results indicate that despite a few cases of inaccuracy, in most cases the model is able to accurately predict culture cell density.

Microalgae biofuels have been under development for the last 40 years; however, in the last 6 years, this development has intensified due to higher oil prices and wider acceptance of anthropogenic climate change. Despite the excellent potential of algal biofuels, they are not yet commercially viable. The reason for this lack of progress is examined in this chapter by firstly reviewing the range of different technology options for biofuels from microalgae. Secondly, an analysis of the available techno-economic and energy assessments is performed highlighting the effect that each system element has on the overall viability.

Microalgae cultivation is a promising methodology for solving some of the future problems of biomass production (i.e. renewable food, feed and bioenergy production). There is no doubt that in conjunction with conventional growth systems, novel technologies must be developed in order to produce the large-scale sustainable microalgae products. Here, we review some of the most promising existing microalgae biomass growth technologies and summarise some of the novel methodologies for sustainable microalgae production.