Optimization of Fe and Mn Removal from Coal Acid Mine Drainage (AMD) with Waste Biomaterials: Statistical Modeling and Kinetic Study

  • Dámaris Núñez-Gómez
  • Flávio Rubens Lapolli
  • Maria Elisa Nagel-Hassemer
  • María Ángeles Lobo-RecioEmail author
Original Paper


The main characteristics of coal acid mine drainage (AMD) are a low pH and high concentrations of sulfate and different metallic ions. Response surface methodology using the central composite rotatable design (CCRD) model was used to optimize the parameters for AMD remediation with aquaculture farming waste [shrimp shell (SS) and mussel byssus (MB)]. SS was chosen due to its high chitin (a metal sorbent) and calcium carbonate (an acidity neutralizing agent) content, and MB because of its potential synergistic effect for the treatment. The coefficient of determination and standard error results from the analysis of variance have shown the model to be adequate. The predicted values were in good agreement with the experimental values. The best experimental conditions established from the statistical study were 136 rpm, 11.46 g L−1 SS and 71.6 g L−1 MB. CCRD can efficiently be applied for modeling the AMD remediation with biomaterials and is an economical way of obtaining the maximum amount of information in a short period of time with the fewest number of experiments. Additionally, five kinetic models, i.e., pseudo-first-order, pseudo-second-order, intraparticle diffusion, Bangham and Elovich equation, were tested to investigate the adsorption mechanisms. The kinetic studies revealed that a 200 min contact time is sufficient to transform AMD into water suitable for non-potable reuse. The pseudo-second-order model provided the best fitting of the experimental data, indicating a chemical adsorption mechanism. This research shows the suitability of the proposed treatment, and the information is valuable for designing a low-cost remediation process for AMD.

Graphical Abstract


Acid mine drainage (AMD) Biomaterials Chitin Factorial approach Sorption Kinetics models 



The authors are grateful to the Department of Environmental Engineering at the Federal University of Santa Catarina (UFSC) and the Brazil and National Council of Scientific and Technologic Development (CNPq, CT-Mineral 51/2013) for financial and technical support. This paper is an extension of the work presented at the 4th International Conference on Energy and Environment Research – ICEER 2017 (Porto/Portugal) and published in Energy Procedia.

Supplementary material

12649_2018_405_MOESM1_ESM.docx (173 kb)
Supplementary material 1 (DOCX 173 KB)


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Dámaris Núñez-Gómez
    • 1
  • Flávio Rubens Lapolli
    • 1
  • Maria Elisa Nagel-Hassemer
    • 1
  • María Ángeles Lobo-Recio
    • 1
    • 2
    Email author
  1. 1.Department of Environmental EngineeringFederal University of Santa Catarina (UFSC)FlorianópolisBrazil
  2. 2.Department of Energy and SustainabilityFederal University of Santa Catarina (UFSC)AraranguáBrazil

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