Integral microalgae-bacteria model (BIO_ALGAE): Application to wastewater high rate algal ponds

Abstract

An integral mechanistic model describing the complex interactions in mixed algal-bacterial systems was developed. The model includes crucial physical, chemical and biokinetic processes of microalgae as well as bacteria in wastewater. Carbon-limited microalgae and autotrophic bacteria growth, light attenuation, photorespiration, temperature and pH dependency are some of the new features included. The model named BIO_ALGAE was built using the general formulation and structure of activated sludge models (ASM), and it was implemented in COMSOL Multiphysics™ platform. Calibration and validation were conducted with experimental data from two identical pilot HRAPs receiving real wastewater. The model was able to simulate the dynamics of different components in the ponds, and to predict the relative proportion of microalgae (58-68% in average of total suspended solids (TSS) and bacteria (30-20% in average of TSS). Microalgae growth resulted strongly influenced by the light factor f(I), decreasing microalgae concentrations from 40 to 60%. Furthermore, reducing the influent organic matter concentration of 50% and 70%, model predictions indicated that microalgae production increased from (8.7gTSSmd to 13.5gTSSmd) due to the new distribution of particulate components. The proposed model could be an efficient tool for industry to predict the production of microalgae, as well as to design and optimize HRAPs.

Microalgae wastewater treatment: Biological and technological approaches

“…The RNEW® technology of Microbio Engineering (US) uses mechanically mixed, CO 2 -gassed open raceway ponds to treat N-and P-rich municipal wastewater to produce feedstock biomass for biofuel production [114][115][116]. Solimeno et al predicted the proportion of algal and bacterial biomass within the open raceway ponds to 58-68% and 23-30% of total suspended solids, respectively [117]. In a following study the algae microbiome of the high-rate algal ponds was found to be dominated by species of Micractinium ssp., Scenedesmus ssp., Chlorella ssp., and pennate diatoms [118].…”

Lab‐scale testing of operation parameters for algae based treatment of piggery wastewater

“…The ability of algae to assimilate N and phosphorus (P) allows to improve the effluent quality . Moreover, microalgae produce oxygen available for bacteria, thus reducing or eliminating the need for aeration and improving the interaction between algae and ammonia‐oxidizing and nitrite‐oxidizing bacteria …”

“…7 Moreover, microalgae produce oxygen available for bacteria, thus reducing or eliminating the need for aeration and improving the interaction between algae and ammonia-oxidizing and nitrite-oxidizing bacteria. 8 According to the intensive research conducted on the use of microalgae-bacteria consortia to treat piggery wastewater (PWW) in the last few years, pretreatment or dilution of PWW seems to be needed for adequate microalgal growth, 9 owing to its intense color, limited light penetration 10 and high ammoniacal N concentration, which can be toxic for microalgae. 11 Owing to the limitation of fresh water supply and potential problems with the management of a larger volume of water, the dilution of PWW for microalgae growth cannot be considered as a viable option.…”

Photo-Activated Sludge: a novel algal-bacterial biotreatment for nitrogen removal from wastewater

“…Other studies have also reported the successful removal of ammonium and TN up to negligible values at laboratory and pilot scale, when using microalgal-bacterial consortia without any 92 supply of external air or oxygen. This shows the ability of the system to benefit from the symbiosis of algae and bacteria García et al, 2017;Liang et al, 2013;Chapter 3;Solimeno et al, 2017;.…”

“…There are in the literature some models focused on algal-bacterial consortia (Solimeno et al, 2017;Wolf et al, 2007;Zambrano et al 2016). Solimeno et al (2017) developed the BIO-ALGAE model for suspended microalgal-bacterial biomass, which was an updated version of the algal model proposed by the same author (Solimeno et al, 2015). The model was calibrated and validated, reporting good results on the prediction of biomass characterization.…”