<p>Corn is central to the Mexican diet, with over 12&#xa0;million tons of tortillas produced annually. However, its production generates more than 14&#xa0;million m<sup>3</sup> of wastewater, known as nejayote, each year. This effluent is highly alkaline, turbid, and rich in organic matter (nitrogen, phosphorus, and COD). When discharged untreated, nejayote causes water contamination promoting eutrophication and disruption of aquatic ecosystems. While large tortilla producers have adopted filtration and anaerobic treatments, most small and medium-sized facilities still release untreated nejayote due to the high cost and complexity of conventional technologies. This study aims to develop a scalable microalgae-based bioprocess for the bioremediation of nejayote using <i>Haematococcus pluvialis</i> while generating a protein-rich, value-added biomass. <i>H. pluvialis</i> was selected from a previous screening of five microalgal strains, where it exhibited the highest tolerance and bioremediation efficiency in undiluted nejayote, as well as due to its ability to produce high-value biomolecules such as proteins and antioxidants. To adapt the microalgae to the extreme characteristics of nejayote, UV-C preconditioning of the culture was combined with gradual acclimatization, and the apparent volumetric mass transfer coefficient (apparent kLa) was used as the main scale-up criterion from laboratory to a 100-L raceway pond. Although apparent kLa guided a successful scale-up, spatial variations were observed in the open-pond system (3.96&#xa0;h<sup>−1</sup> near the shaft to 0.56&#xa0;h<sup>−1</sup> along the lane), reflecting the non-ideal mixing typical of plug-flow-like hydrodynamics. The novelty of this work lies in integrating physiological adaptation with kLa-guided scaling to enhance microalgal adaptability to nejayote, bioremediation performance without effluent dilution, and treatment scalability, addressing major limitations from previous approaches. <i>H. pluvialis</i>-based treatment proved robust and scalable, maintaining high nutrient removal efficiencies despite slight decreases after scale-up, with total nitrogen decreasing from 96.2% to 87.3%, total phosphate from 100% to 98.9%, and COD from 92.2% to 90.2%, mainly due to water evaporation and environmental fluctuations. Biomass analysis showed protein and ash as dominant components, with 38.7% protein and 31.3% ash at the laboratory scale, and 26.9% protein and 46.9% ash at 100&#xa0;L, supporting potential applications in biofertilizers or animal feed. Although COD levels remained above discharge limits, the process demonstrated strong stability, efficient nutrient recovery, and a promising pathway for integrating wastewater remediation with biomass valorization. Overally, <i>H. pluvialis</i> offers a viable, sustainable, and scalable alternative for nejayote treatment, providing a circular bioeconomy solution for small and medium corn processors lacking access to advanced wastewater technologies.</p>

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Bioremediation of alkaline corn wastewater with Haematococcus pluvialis under laboratory and 100 L raceway pond conditions

  • Cesar E. Najar-Almanzor,
  • Tomás García-Cayuela,
  • Janet A. Gutierrez-Uribe,
  • Danay Carrillo-Nieves

摘要

Corn is central to the Mexican diet, with over 12 million tons of tortillas produced annually. However, its production generates more than 14 million m3 of wastewater, known as nejayote, each year. This effluent is highly alkaline, turbid, and rich in organic matter (nitrogen, phosphorus, and COD). When discharged untreated, nejayote causes water contamination promoting eutrophication and disruption of aquatic ecosystems. While large tortilla producers have adopted filtration and anaerobic treatments, most small and medium-sized facilities still release untreated nejayote due to the high cost and complexity of conventional technologies. This study aims to develop a scalable microalgae-based bioprocess for the bioremediation of nejayote using Haematococcus pluvialis while generating a protein-rich, value-added biomass. H. pluvialis was selected from a previous screening of five microalgal strains, where it exhibited the highest tolerance and bioremediation efficiency in undiluted nejayote, as well as due to its ability to produce high-value biomolecules such as proteins and antioxidants. To adapt the microalgae to the extreme characteristics of nejayote, UV-C preconditioning of the culture was combined with gradual acclimatization, and the apparent volumetric mass transfer coefficient (apparent kLa) was used as the main scale-up criterion from laboratory to a 100-L raceway pond. Although apparent kLa guided a successful scale-up, spatial variations were observed in the open-pond system (3.96 h−1 near the shaft to 0.56 h−1 along the lane), reflecting the non-ideal mixing typical of plug-flow-like hydrodynamics. The novelty of this work lies in integrating physiological adaptation with kLa-guided scaling to enhance microalgal adaptability to nejayote, bioremediation performance without effluent dilution, and treatment scalability, addressing major limitations from previous approaches. H. pluvialis-based treatment proved robust and scalable, maintaining high nutrient removal efficiencies despite slight decreases after scale-up, with total nitrogen decreasing from 96.2% to 87.3%, total phosphate from 100% to 98.9%, and COD from 92.2% to 90.2%, mainly due to water evaporation and environmental fluctuations. Biomass analysis showed protein and ash as dominant components, with 38.7% protein and 31.3% ash at the laboratory scale, and 26.9% protein and 46.9% ash at 100 L, supporting potential applications in biofertilizers or animal feed. Although COD levels remained above discharge limits, the process demonstrated strong stability, efficient nutrient recovery, and a promising pathway for integrating wastewater remediation with biomass valorization. Overally, H. pluvialis offers a viable, sustainable, and scalable alternative for nejayote treatment, providing a circular bioeconomy solution for small and medium corn processors lacking access to advanced wastewater technologies.