In this study, the feasibility of integrating microalgae cultivation in a biogas production process that treats the organic fraction of municipal solid waste (OFMSW) was investigated. In particular, the biomass growth performances in the liquid fraction of the digestate, characterized by high ammonia concentrations and turbidity, were assessed together with the nutrient removal efficiency. Preliminary laboratory-scale experiments were first carried out in photobioreactors operating in a continuous mode (Continuous-flow Stirred-Tank Reactor, CSTR), to gain preliminary data aimed at aiding the subsequent scaling up to a pilot scale facility. An outdoor experimental campaign, operated from July to October 2019, was then performed in a pilot scale raceway pond (4.5 m2), located in Arzignano (VI), Italy, to assess the performances under real environmental conditions. The results show that microalgae could grow well in this complex substrate, although dilution was necessary to enhance light penetration in the culture. In outdoor conditions, nitrification by autotrophic bacteria appeared to be significant, while the photosynthetic nitrogen removal was around 12% with respect to the inlet. On the other hand, phosphorus was almost completely removed from the medium under all the conditions tested, and a biomass production between 2–7 g m−2 d−1 was obtained.

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The design of dynamic experiments (DoDE) and dynamic response surface methodology (DRSM) have been recently applied to accurately model and optimize several types of industrial and pharmaceutical processes. In this work, we apply the above methodologies to the growth of a photosynthetic microorganism, a bioprocess characterized by a high degree of complexity. Compared to conventional bioprocesses involving heterotrophic bacteria, the high adaptability of photosynthetic microorganisms to environmental conditions and the complexity of understanding the effect of light intensity on biomass growth make the development of a thorough knowledge-driven model a difficult task. Based on a predefined experimental design taking into account the effect of light, temperature, and nutrient feeding profiles, we performed a set of dynamic biomass growth experiments, from which we estimated different DRSM models. The best one was then used to predict the behavior of a new set of experiments. We show that through such a model, valuable insights into the process can be gained and that the model is fairly reliable in predicting growth behavior under different experimental conditions.

Operating conditions strongly affect the productivity of photobioreactors (PBRs). Even though it is demonstrated that continuous systems allow higher biomass productivity, the use of the semicontinuous mode is more widespread for technological reasons. However, even on such a system, tuning the residence time can improve production, in particular if the solid retention time (SRT) is adjusted. Conversely, the hydraulic residence time (HRT) should be set to minimize nutrient loss. In this work, a previously implemented model was applied to a 3.4 m 3 , artificially illuminated pilot plant cultivating Arthrospira platensis, to define the best operating conditions in terms of SRT, which is often neglected in the common operating procedures. This new approach that combines modeling and management of operating conditions allowed obtaining a biomass productivity of 0.8 g L −1 day −1 , more than 3 times higher than that obtained in the same system operated with standard procedures (0.24 g L −1 day −1 ), even though the stability of the production is strongly related to the efficiency of the separation system. The SRT also influenced the protein content of the biomass, which was found to increase at lower residence times. Finally, by optimizing the culture medium in terms of the carbonate/bicarbonate ratio, a higher CO 2 exploitation was obtained.