Microalgae-bacteria consortia for urban wastewater treatment

Resumen

Microalgae-bacteria consortia appears as an ideal option within the framework of sustainable technologies for wastewater treatment. Pollutants removal mechanisms result from direct and/or indirect ecological interactions between microalgae and indigenous wastewater bacteria. Effectively designed systems that incorporate microalgae-bacteria consortia require an understanding of ecological interactions between microalgae and bacteria within wastewater treatment processes. The main objective of this research work is therefore study and explore the ecological interactions to improve microalgae-bacteria based-wastewater treatment. This thesis addresses from the operation of an outdoor membrane high rate algal pond (MHRAP) pilot plant to the development of a mathematical model that reproduces the ecological interactions observed experimentally. The common thread between the different chapters of the thesis is specifically the interaction between microalgae and nitrifying bacteria. The feasibility of wastewater treatment by microalgae-bacteria consortium was assessed at the MHRAP pilot plant by varying the hydraulic retention time (HRT) and the incoming wastewater stream. Both HRT and wastewater stream influenced the relationship between microalgae and nitrifying bacteria. Negative interactions, such as nitrite inhibition of photosynthesis and competitive interactions, were observed. The influence of nitrite on photosynthesis was then studied under laboratory conditions. Nitrite effectively had an inhibitory effect on the light-dependent phase of photosynthesis. Kinetic expression which reproduces nitrite inhibition was proposed and validated. Competitive processes reduce the potential of microalgae and bacteria consortia to recover nutrients from wastewater, therefore, a guide to identify and reduce these negative interactions was developed. Additionally, microbial ecology of five operational periods of the MHRAP pilot plant was evaluated. Massive sequencing of 16S/18S rDNA biomarkers have been applied to identify the main bacteria and microalgae communities and to detect the influence on operational and environmental parameters on bioreactor microbiology. Coelastrella and Desmodesmus were the dominant genera of microalgae, while Verrucomicrobiota and Proteobacteria were the dominant bacterial phylum in the five operating periods. All the knowledge gathered during the development of this thesis was used to develop a mathematical model, which faithfully reproduces the main interactions between microalgae and bacteria. As the literature review revealed, the metabolism of microalgae cannot be considered a well-characterized process, since some parameters of the mathematical models are uncertain and speciation-dependent. Thus, the more influential factors on microalgae kinetics and the uncertainty of the model outputs were analyzed by a global sensitivity analysis and an uncertainty analysis, respectively. The 34 parameters of the microalgae kinetics model were reduced to 11 influential factors, which should be calibrated for each microalgae culture to reduce model uncertainty. An integral microalgae-bacteria model was developed, which includes crucial physical, chemical and biokinetic processes observed during the thesis development. The model was used to reproduce microalgae and nitrifying bacteria interactions that occur in an outdoor membrane photobioreactor (MPBR) pilot plant. Moreover, nitrification control strategies were also simulated to improve both microalgae activity and nutrient recovery rates.