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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Predicting the time related generation of acid rock drainage from mine waste: a copper case study

Simunika, Nathan N January 2013 (has links)
Includes bibliographical references. / The mining and beneficiation of coal and hard rock ores generates large volumes of sulphidic waste that may oxidise in the presence of oxygen and result in the generation of acid rock drainage (ARD). In order to effectively manage the long term effects of ARD, there is a need to reliably quantify the associated impacts and how these impacts evolve with time. Traditional laboratory-scale tests only provide a partial picture of ARD generation, and their extrapolation to full-scale deposits is highly uncertain and controversial. This has prompted the development of mathematical models which take into account the governing chemical reaction and physical transport mechanisms. Whilst the accurate and reliable quantification of the time-related ARD profiles requires rigorous mechanistic modeling of both the (bio) chemical reaction and physical transport mechanisms under non-ideal flow conditions, advanced models are complex and only suitable for site-specific studies and operational decision-making contexts. However, in the early stage screening of waste for potential environmental impacts, simple geochemical mass transport models such as PHREEQC can be used. PHREEQC V.2 has capabilities to simulate a wide range of processes that include equilibrium controlled reactions, kinetically controlled reactions and 1-D advective-dispersion transport, and has been used in a wide range of geochemical applications. However, despite its capabilities, little has been published on its applications to ARD prediction. This study focused on the development and application of a PHREEQC based predictive modeling tool, suitable for the early or screening evaluation of the potential long-term ARD risks associated with sulphidic waste deposits.

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