Nutrients recovery from piggery wastewater and starch wastewater via microalgae-bacteria consortia

Kai You, Fengru Ge, Xiaodan Wu, Kunyang Song, Zixiang Yang, Qi Zhang, Yuhuan Liu, Roger Ruan, Hongli Zheng

Research output: Contribution to journalReview articlepeer-review

29 Scopus citations

Abstract

It is a worldwide challenge to manage the total cost and efficiency ofwastewater treatment. To enhance nutrients recovery from wastewaters, nitrogen-rich piggery wastewater (PW) and carbon-rich starch wastewater (SW) treated via photosynthetic microorganisms was investigated. The results showed that the recovery efficiencies of nutrients of PW and SW treated through the cultivation of Chlorella vulgaris and Rhodobacter sphaeroides, respectively, were relatively low. C. vulgaris could not grow on SW. The recovery performance of the mixture of PW and SW was highly improved via co-culturing C. vulgaris and R. sphaeroides. The microalgae-bacteria consortia was obtained by co-culturing C. vulgaris and R. sphaeroides. The recovery efficiencies of ammonia nitrogen, total phosphorus, chemical oxygen demand, and total nitrogen of the mixture of PW and SW via co-culturing C. vulgaris and R. sphaeroides were 100%, 96%, 97%, and 95%, respectively. Carbohydrate, lipid, and protein were the three main ingredients in biomass of photosynthetic microorganisms. The developed strategies were feasible to improve nutrients recovery from the nitrogen-rich and organic carbon-rich wastewaters.

Original languageEnglish (US)
Article number102551
JournalAlgal Research
Volume60
DOIs
StatePublished - Dec 2021

Bibliographical note

Funding Information:
This work was supported in part by grants from the National Natural Science Foundation of China (Grant Nos. 21767017 & 22066016 ), and Science and Technology Project of Jiangxi Provincial Department of Science and Technology (Grant No. 20192BBH80023 ).

Publisher Copyright:
© 2021 Elsevier B.V.

Keywords

  • Co-culture
  • Mixed wastewaters
  • Nutrients recovery
  • Photosynthetic microorganisms

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