Published March 2021 | Version v1
Journal article

Degradation of anthraquinone dye reactive blue 19 using persulfate activated with Fe/Mn modified biochar: Radical/non-radical mechanisms and fixed-bed reactor study

  • 1. School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070 (China)
  • 2. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen 518055 (China)
  • 3. Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611 (United States)
  • 4. Department of Chemical and Environmental Engineering, University of Cincinnati, Cincinnati, OH 45221 (United States)

Description

Highlights: • Fe/MnBC exhibited highly-efficient durable activation for persulfate. • Possible radical and non-radical mechanisms were proposed. • Artificial neural network model possessed highly predictability for the fixed-bed reactor. In this study, a heterogeneous activator was prepared via the Fe/Mn modification of sludge-derived biochar (Fe/MnBC) to achieve high-efficiency activation of persulfate (PS) for reactive blue 19 (RB19) degradation. The morphologies and chemical states of Fe/MnBC were examined by various characterizations. A comprehensive assessment was conducted to reveal the effects of biochar preparation conditions and system reaction conditions. According to the results of scavenger quenching experiments and electron paramagnetic resonance (EPR) testing, the mechanisms of Fe/MnBC combined PS system on RB19 degradation were proposed, including radical and non-radical mechanisms. The formation and involvement of sulfate radical (SO4·−), hydroxyl radical (OH·), and singlet oxygen (1O2) were proved in this system, and Fe(IV)/Mn(VII) was also speculated to participate in the non-radical degradation process. These findings give a new insight into the mechanisms of PS activated by metal-biochar composite. Besides, fixed-bed reactor (FBR) experiments indicated that the Fe/MnBC has considerable PS activation potential for dyes removal. The degradation process was further modeled by the central composite design (CCD-RSM) and artificial neural networks (ANN) methods. The statistical metrics and prediction indicated that the prediction results of ANN model were better than CCD-RSM model, and the ANN model could perfectly predict the reaction process of Fe/MnBC FBR for engineering applications.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.scitotenv.2020.143584

Additional details

Identifiers

DOI
10.1016/j.scitotenv.2020.143584;
PII
S0048969720371151;

Publishing Information

Journal Title
Science of the Total Environment
Journal Volume
758
Journal Page Range
vp.
ISSN
0048-9697
CODEN
STENDL

Optional Information

Copyright
Copyright (c) 2020 Elsevier B.V. All rights reserved.