Scenario studies for algae production

Microalgae are a promising biomass for the biobased economy to produce food, feed, fuel, chemicals and materials. So far, large-scale production of algae is limited and as a result estimates on the performance of such large systems are scarce. There is a need to estimate large-scale biomass productivity and energy consumption, while considering the uncertainty and complexity in such large-scale systems. In this thesis frameworks are developed to assess 1) the productivity during algae cultivation, 2) energy consumption during the transport of resources and processing biomass to biodiesel, and 3) the frameworks are applied to estimate the impact of algae cultivation in the production of algae-based food commodities. Design, location and future scenario are applied to deal with the complexity and uncertainty arising in the various data and models used. The first part of this thesis focuses on the development of a productivity framework for biomass production for flat panels (Chapter 2), horizontal and vertical tubular photobioreactors (Chapter 3) and raceway ponds (Chapter 4). The framework uses bio-physics-based models to simulate the light input on the reactor surface and the light gradient inside the reactor systems. The internal light gradient depends on the reactor geometry and dimensions, and the penetration of diffuse light between parallel reactors, which includes the canyon effect, and the reflection of light from the ground surface to the reactors are incorporated as well. Specific growth rates are derived from this internal light gradient based on species-specific growth characteristics. In raceway ponds the effect of the dynamic water temperature on the specific growth rate is included. The productivity framework enables to study cultivation under a wide range of process conditions and reactor designs, even those which have not been yet developed or tested under outdoor conditions. The results show that regional weather conditions, solar angles and algae species are key factors in making the best choice for the specific reactor design. The productivity framework allows to optimise the reactor design (e.g. geometry, light path, distances between parallel units and height) to the regional light conditions and growth characteristics of the algae species of interest. The best biomass concentration for cultivation varies between the reactor design, location and algae species. We recommend to select species suited to growth well at the regional light angles and weather conditions. An initial global sensitivity analysis shows that the absorption coefficient, maximum specific growth rate and functional cross section of the photosynthetic apparatus are the essential parameters of the model for single flat panels. An important next step is to validate and calibrate the productivity framework using data from outdoor experiments in various reactor designs, at different locations and with several algae species. Algae production is strongly connected to regional weather conditions, but also to the infrastructure for resource supply and to the processing of biomass. The energy consumption for resource supply has not been quantified yet and the energy consumption of biomass processing is mostly based on fixed values. These elements are tackled in part 2 of this thesis. In Chapter 5the productivity framework is combined with logistic models to optimise the supply network for algae cultivation. The results show that the availability, supply and demand of resources has a dominant effect on the feasibility of regions for algae cultivation. Not all locations achieve a positive energy balance for transport and the supply logistics is essential for planning algae cultivation locations. In the Benelux many locations are feasible for algae production due to the availability of large amounts of resources, while the limited supply of CO2in southern France and the Sahara demands for plants which are scattered over the regions. For the Sahara the distance for water transport should be minimal. Still, the average transport distances are higher than commonly assumed and algae cultivation does not necessarily need to take place in proximity of CO2supply. The transport energy consumption is found to be low compared to the energy contained in algae biomass (mostly below 3%). Chapter 6 describesa model-based combinatorial optimisation approach for the energy-efficientprocessing of algae biomass. In this approach, mass and energy balances and additional relations are used to relate the product yield and energy consumption of process units and process routes to the processing conditions. Process routes with the highest net energy ratios are derived by optimising the process conditions of each process unit in a given superstructure. This optimisation leads to 5-38% improvement of the net energy ratio compared to fixed process conditions. The approach moreover allows a bottleneck analysis for each process route. The results show that process design should be tailor-made. The model-based approach proves to be a versatile tool for the design of efficient microalgae processing systems. The developed frameworks combined with scenario studies are a powerful tool to assess algae production. The presented approaches help to reduce the uncertainty in the interpretation of data and are thereby an appropriate basis to use in impact analysis. In Chapter 7this is illustrated for the production of algae protein and oil as food commodities. The design scenarios show the implications of various reactor designs, two algae species and at two locations on biomass productivity, production cost and environmental life cycle indicators. The achievements of this work and the new horizons from this work are discussed in Chapter 8. The results of the developed frameworks demonstrate the power of the scenario approach and show that sensible predictions and projections of biomass productivity and energy consumption for logistics and biomass processing follow from the models.