KNUSTSpace >
Research Articles >
College of Engineering >

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12249

Title: Using an integrated method for the determination of environmental TCLP arsenic for sulphide‑rich mine tailing remediation in Ghana, West Africa
Authors: Foli, Gordon
Gawu, Simon K. Y.
Keywords: Acid–base accounting
Model definition
Arsenic waste
Tailings repository
Mine drainage
Issue Date: 19-Apr-2018
Publisher: Springer-Verlag GmbH Germany, part of Springer Nature
Citation: Springer-Verlag GmbH Germany, part of Springer Nature, Environmental Earth Sciences (2018) 77:309
Abstract: Toxicity characteristic leaching procedure (TCLP) is a versatile short-term leaching protocol used to estimate the release of toxic metals from waste prior to disposal to a repository. This paper uses the integrated TCLP leachate data from tailings, tailings dam monitoring borehole data, and acidity ratio (AR) range of sulphide-rich ores to simulate the environmental TCLP As in tailings at the AngloGold Ashanti Obuasi mine in Ghana. The aim was to incorporate long-term leaching characteristics of tailings to minimise the risk of TCLP As test failure. The mean As concentration and pH value are 2.26 mg/l and 5.7 in TCLP leachate, 0.35 mg/l and 6.7 in monitoring boreholes, and < 0.01 mg/l and 5.7 in control boreholes, respectively. The evaluation of the TCLP As data using a one-sample t test performed at 80% confidence interval has the upper confidence limit (UCL) of 2.41 mg/l; this value which constitutes the short-term characterised environmental TCLP As is below the USEPA criterion of 5 mg/l and, therefore, qualifies the waste as safe for disposal. Alternatively, TCLP leachate, borehole and AR data were integrated to simulate the long-term environmental TCLP As of 2.40 mg/l and pH value of 5.7, and As concentration and pH value of 0.01 mg/l and 6.7 in monitoring boreholes, respectively. Such laboratory simulations of TCLP As leaching aimed at achieving 0.01 mg/l in field monitoring data would provide a more robust predictive value for environmental management decision making due to long-term considerations.
Description: An article published by Springer-Verlag GmbH Germany, part of Springer Nature and also available on doi.org/10.1007/s12665-018-7493-4
URI: http://hdl.handle.net/123456789/12249
Appears in Collections:College of Engineering

Files in This Item:

File Description SizeFormat
s12665-018-7493-4.pdf1.19 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback