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Mechanochemical immobilization of heavy metals in contaminated soils: a novel mathematical modeling of experimental outcomes

Alessandro Concas, Massimo Pisu, Giacomo Cao
Journal of Hazardous Materials, Volume 388, Number 121731, page 1--12 - 2020
Télécharger la publication : Concas_et_al_HAZMAT_2019.pdf [1Mo]  
Mechanochemical processing to immobilize heavy metals in contaminated soils has been proposed few years ago by our research group. The corresponding experimental results have shown that, under specific operating conditions, the mechanical energy provided by suitable ball mills, can greatly reduce heavy metals mobility without the addition of any reactant. Such results, together with the extreme simplicity of the proposed technique, are still very promising in view of its industrial transposition. Along these lines, the use of suitable mathematical models might represent a valuable tool which would permit to design and control mechano-chemical reactors for field applications. In this work, a simple albeit exhaustive model is proposed for the first time to quantitatively describe the effects of the dynamics of milling process, such as impact frequency and energy, on the immobilization kinetics. Model results and experimental data obtained so far are successfully compared in terms of leached heavy metals and immobilization efficiency evolution with treatment time. Finally, the potential capability of the model to contribute to the industrial scale transposition of the proposed technique is addressed.

Références BibTex

@Article{CPC20,
  author       = {Concas, A. and Pisu, M. and Cao, G.},
  title        = {Mechanochemical immobilization of heavy metals in contaminated soils: a novel mathematical modeling of experimental outcomes},
  journal      = {Journal of Hazardous Materials},
  number       = {121731},
  volume       = {388},
  pages        = {1--12},
  year         = {2020},
  publisher    = {Elsevier},
  keywords     = {mechano-chemical treatment; heavy metals immobilization; soil remediation; mathematical modelling; technology scale-up},
  doi          = {10.1016/j.jhazmat.2019.121731},
  url          = {https://publications.crs4.it/pubdocs/2020/CPC20},
}

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