Microalgae can be used to produce high-value compounds, such as pigments or high value fatty acids, or as a feedstock for lower value products such as food and feed compounds, biochemicals, and biofuels. In order to produce these bulk products competitively, it is required to lower microalgae production cost. Production costs could be reduced by employing microalgae biofilms as a production platform. The main advantages of microalgae biofilms are a direct harvest of concentrated microalgae paste, and the uncoupling of the hydraulic retention time from the microalgal retention time. The latter allows to decrease the liquid volume or to employ dilute waste streams. To successfully employ biofilms, however, it is required that microalgal biofilms can be cultivated at high productivity and high photosynthetic efficiency. The aim of this thesis was to optimize the productivity of microalgal biofilms. Light energy drives microalgal growth. Sunlight is free and abundant, but sunlight intensity varies over the day and the seasons. This makes it impossible to maintain optimal production conditions throughout the day. These fluctuations in irradiance can be prevented by applying artificial lighting. Although, artificial lighting will supply a constant light intensity and thus increase productivity and simplify process control, it will also increase microalgae production cost. A quantitative evaluation of lighting costs and energy requirement was still missing and this was the topic of Chapter 2. The costs related to artificial lighting were identified as 25.3 $ per kilogram of dry-weight biomass, with only 4% to 6% of the electrical energy required to power the lamps eventually stored as chemical energy in microalgal biomass. Energy loss and increased production cost may be acceptable for the production of high value products, but in general they should be avoided. In Chapter 3, a photobioreactor design based on a rotating biological contactor (RBC) was introduced and used as a production platform for microalgal biomass cultivated in a biofilm. In the photobioreactor, referred to as the Algadisk, microalgae grow in biofilm on vertical rotating disks partially submerged in water with dissolved nutrients. The objective was to evaluate the potential of the Algadisk photobioreactor, and identify the window of operation of the process with respect to the effects of disk roughness, disk rotation speed and CO2 concentration. These parameters were evaluated in relation to biomass productivity, photosynthetic efficiency, and the long-term cultivation stability of the production process. The mesophilic green microalga Chlorella sorokiniana was used as a model organism. In the lab-scale Algadisk reactor, a productivity of 20.1 ±0.7 gram per m2 disk surface per day and a biomass yield on light of 0.9 ±0.04 gram dry weight biomass per mol photons were obtained. This productivity could be retained over 21 weeks without re-inoculation. To obtain maximal and stable productivity it was important that the disk surface provides a structure that allows biomass retention on the disk after harvest. The retained biomass acts as inoculum for the new biofilm and is therefore essential for quick biofilm regrowth. Most important process parameters were CO2 supply, temperature, and pH. Although deviations of these parameters from the optimal conditions resulted in productivity loss, the system quickly recovered when optimal conditions were restored. These results exhibit an apparent opportunity to employ the Algadisk photobioreactor and biofilm systems in general at large scale for microalgae biomass production provided CO2 supply is adequate. In order to better understand the process conditions inside the biofilm a model was developed in the further chapters. These mathematical models were calibrated and validated with dedicated experiments. In Chapter 4 first a general applicable kinetic model was developed able to predict light limited microalgal growth. This model combines a mathematical description for photoautotrophic sugar production with a description for aerobic chemoheterotrophic biomass growth. The model is based on five measurable biological parameters which were obtained from literature for the purpose of this study. The model was validated on experiments described in literature for both Chlorella sorokiniana and Chlamydomonas reinhardtii. The specific growth rate was initially predicted with a low accuracy, which was most likely caused by simplifications in the light model and inaccurate parameter estimations. When optimizing the light model and input parameters the model accuracy was improved and validated. With this model a reliable engineering tool became available to predict microalgal growth in photobioreactors. This microalgal growth model was included in the biofilm growth models introduced in Chapters 5 and 6. In Chapter 5 microalgal biofilms of Chlorella sorokiniana were grown under simulated day-night cycles at high productivity and high photosynthetic efficiency. The experimental data under day/night cycles were used to validate a microalgal biofilm growth model. For this purpose the light limited microalgal growth model from Chapter 4 was extended to include diurnal carbon-partitioning and maintenance under prolonged dark conditions. This new biofilm growth model was then calibrated and validated experimentally. Based on these experiments and model simulations no differences in the light utilization efficiency between diurnal and continuous light conditions were identified. Indirectly this shows that biomass lost overnight represents sugar consumption for synthesis of new functional biomass and maintenance related respiration. This is advantageous, as this result shows that it is possible to cultivate microalgae at high photosynthetic efficiencies on sunlight and that the night does not negatively impact overall daily productivity. Long periods of darkness resulted in reduced maintenance related respiration. Based on simulations with the validated biofilm growth model it could be determined that the photosynthetic efficiency of biofilm growth is higher than that of suspension growth. This is related to the fact that the maintenance rate in the dark zones of the biofilm is lower compared to that in the dark zones of suspension cultures, which are continuously mixed with the photic zone. In Chapter 3 it was identified that concentrated CO2 streams are required to obtain high productivities. However, over-supplying CO2 results into loss of CO2 to the environment and is undesirable for both environmental and economic reasons. In Chapter 6 the phototrophic biofilm growth model from Chapter 5 was extended to include CO2 and O2 consumption, production, and diffusion. The extended model was validated in growth experiments with CO2 as limiting substrate. Based on the validated model the CO2 utilization and productivity in biofilm photobioreactors were optimized by changing the gas flow rate, the number of biofilm reactors in series, and the gas composition. This resulted in a maximum CO2 utilization efficiency of 96% by employing flue gas, while the productivity only dropped 2% compared to non-CO2 limited growth. In order to achieve this 25 biofilm reactors units, or more, must be operated in series. Based on these results we conclude that concentrated CO2 streams and plug flow behaviour of the gaseous phase over the biofilm surface are essential for high CO2 utilization efficiencies and high biofilm productivity. In Chapter 7 the implications of these studies for the further development of biofilm photobioreactors was discussed in the light of current biofilm photobioreactor designs. Design elements of state of the art biofilm photobioreactors, were combined into a new conceptual biofilm photobioreactor design. This new design combines all advantages of phototrophic biofilms minimizing the amount of material required. Further improvements by means of process control strategies were suggested that aim for maximal productivity and maximal nutrient utilization efficiency. These strategies include: control of the biofilm thickness, control of the temperature, and optimized nutrient supply strategies.