Modeling growth kinetics and community interactions in microalgal cultures for bioremediation of anaerobically digested swine wastewater Academic Article in Scopus uri icon

abstract

  • Uncontrolled release of swine wastewater into the environment causes the eutrophication of water bodies, as well as soil and air pollution, among other environmental and health issues. Microalgal-based wastewater treatment (MbWT) is a cost-effective alternative to traditional wastewater treatment methods that offers the opportunity to harvest valuable biomass while simultaneously removing nutrients and organic matter, thus making wastewater treatment a circular bioeconomy process. The aim of this work was to test three microalgal strains, Chlorella vulgaris, Scenedesmus acutus, and Arthrospira maxima, in mono-cultures and co-cultures using raw (undiluted, non-sterilized) anaerobically digested swine wastewater (ADSWW). An overall performance index (OPI) proposed herein showed that the treatments that included C. vulgaris were the most efficient in terms of biomass growth, along with COD and nutrient removal. The co-culture of C. vulgaris and S. acutus achieved the highest OPI of 0.68, displaying a maximum biomass concentration of 2.97 ± 0.36 g/L, as well as 89 %, 56 %, and 67 % removal efficiencies for COD, TN, and TP, respectively. Three mathematical models were used to estimate relevant growth kinetic parameters, including the specific growth rate, lag-phase duration, interspecific interaction, affinity constant, and biomass productivity. The growth curve of the C. vulgaris monoculture was adjusted using a double Gompertz model, showing a growth rate of 0.625 d¿1 and a lag phase of 0.71 days in the first growth stage. The Lotka-Volterra model was used to assess interactions between both strains in the co-culture, showing a commensalistic relationship as denoted by the interspecific parameters (ßcs = 1.99 ± 0.92 and ßsc = ¿0.007 ± 0.008). Finally, the growth kinetics as a function of the three substrates (COD, TN, and TP) were adjusted to the Monod model, and the resulting parameters were used to simulate a continuous process that evidenced the requirement of P supplementation.

publication date

  • March 1, 2023