• 文献标题:   Extensive data analysis and kinetic modelling of dosage and temperature dependent role of graphene oxides on anammox
  • 文献类型:   Article
  • 作  者:   GUO Z, AHMAD HA, TIAN YH, ZHAO QY, ZENG M, WU N, HAO LL, LIANG JQ, NI SQ
  • 作者关键词:   anammox, kinetic, neural network, graphene oxide, reduced graphene oxide
  • 出版物名称:   CHEMOSPHERE
  • ISSN:   0045-6535 EI 1879-1298
  • 通讯作者地址:  
  • 被引频次:   0
  • DOI:   10.1016/j.chemosphere.2022.136307
  • 出版年:   2022

▎ 摘  要

Anaerobic ammonium oxidation (anammox) is carbon friendly biological nitrogen removal process, and recently more focus is given to improving the anammox activity. Because of its high adsorption and modifiability, graphene and its derivative in wastewater treatment have received much attention. However, the specific effects and mechanisms of graphene oxide (GO) and reduced graphene oxide (RGO) on anammox are still controversial. Extensive data analysis was performed to explore the effects of GO and RGO on anammox. Statistical analysis revealed that 100 mg/L GO significantly promoted the anammox process, while 200 mg/L of GO inhibited the anammox process. The promotion of anammox performance under the influence of RGO was dependent on the temperature. The Logistic model was utilized for depicting the variation of nitrogen removal efficiency under promoting dosage of graphene oxides. A neural network model-based analysis was performed to reach anammox's potential mechanisms under the influence of two graphene oxides. Spearman correlation analysis showed that GO and RGO had significant positive correlations with nitrogen removal efficiency and specific anammox activity (p < 0.01), especially for RGO. In addition, the abundance of Planctomycetes and Nitrospirae was positively correlated with the addition of graphene oxides. This work comprehensively unraveled the role of graphene oxide materials on the anammox process and provided practical directions for the enhancement of anammox.