Literature DB >> 29929275

Surfactant-aided coal dust suppression: A review of evaluation methods and influencing factors.

Guang Xu1, Yinping Chen2, Jacques Eksteen3, Jialin Xu4.   

Abstract

There is an increasing trend in the occurrence of coal worker's pneumoconiosis even in developed countries such as the US and Australia who have believed such an issue have been well controlled in the past. Water spray is one of the most commonly applied methods for underground coal mines dust control, and research have shown the dust suppression efficiency can be greatly improved by adding surfactants. However, the literature appears to show inconsistent results that do not provide the coal mining industry with a clearly effective solution. The breakthrough in this field relies on the achievements in prior work, but an up-to-date critical review was not found. By critically reviewing prior studies, this paper highlights the advances in the surfactant-aided coal dust suppression technology. Firstly, the surfactant chemical structure, surfactant type and mechanism of surfactant adsorption were explained. Secondly, the commonly used surfactant efficiency evaluation methods were described. This is important for producing comparable and reproducible results. After that, key aspects of the influencing factors were discussed, which are essential for developing effective and robust dust suppression products. In the discussion on the challenges and further research directions, we suggest more focus should be on the dynamic interaction between the coal particle and water droplet in wind tunnels or well controlled onsite conditions.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Coal dust suppression; Coal wettability; Coal worker's pneumoconiosis; Surfactant; Wind tunnel

Year:  2018        PMID: 29929275     DOI: 10.1016/j.scitotenv.2018.05.182

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  6 in total

1.  Use data augmentation for a deep learning classification model with chest X-ray clinical imaging featuring coal workers' pneumoconiosis.

Authors:  Hantian Dong; Biaokai Zhu; Xinri Zhang; Xiaomei Kong
Journal:  BMC Pulm Med       Date:  2022-07-15       Impact factor: 3.320

2.  Experimental and Molecular Dynamics Simulation Study for Preferring Coal Dust Wetting Agents.

Authors:  Liying Sun; Shaocheng Ge; Shuo Liu; Deji Jing; Xi Chen
Journal:  ACS Omega       Date:  2022-05-18

3.  Wetting Mechanism and Experimental Study of Synergistic Wetting of Bituminous Coal with SDS and APG1214.

Authors:  Liying Sun; Shaocheng Ge; Deji Jing; Shuo Liu; Xi Chen
Journal:  ACS Omega       Date:  2021-12-31

4.  Study on the characteristics of induced airflow and particle dispersion based on the multivariate two-factor model.

Authors:  Chaonan Fan; Qingjie Qi; Xi Chen; Shaocheng Ge
Journal:  PLoS One       Date:  2022-02-08       Impact factor: 3.240

5.  Experimental and molecular dynamics study into the surfactant effect upon coal wettability.

Authors:  Yi-Ting Liu; Hong-Mei Li; Ming-Zhong Gao; Si-Qi Ye; Yun Zhao; Jing Xie; Gui-Kang Liu; Jun-Jun Liu; Lu-Ming Li; Jie Deng; Wei-Qi Zhou
Journal:  RSC Adv       Date:  2021-07-13       Impact factor: 4.036

6.  Isolation and chemical characterization of the biosurfactant produced by Gordonia sp. IITR100.

Authors:  Arif Nissar Zargar; Sarthak Mishra; Manoj Kumar; Preeti Srivastava
Journal:  PLoS One       Date:  2022-04-14       Impact factor: 3.240

  6 in total

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