{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/9128"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/9128","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Predicting the time related generation of acid rock drainage from mine waste: a copper case study","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Simunika, Nathan N"],"institution":"Centre for Bioprocess Engineering Research","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Broadhurst, Jennifer Lee","Petersen, Jochen"],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013","date_published":"2013","updated_at":"2026-07-22T22:23:27Z","subjects":["Bioprocess Engineering Research"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/9128","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Broadhurst, Jennifer Lee","Petersen, Jochen"]},{"key":"dc:creator","label":"Author","values":["Simunika, Nathan N"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-11-05T03:49:36Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-11-05T03:49:36Z"]},{"key":"dc:date.issued","label":"Date","values":["2013"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Centre for Bioprocess Engineering Research"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Bioprocess Engineering Research"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/9128"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes bibliographical references."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Predicting the time related generation of acid rock drainage from mine waste: a copper case study"]}]}],"canonical_facts":{"dc:contributor.advisor":["Broadhurst, Jennifer Lee","Petersen, Jochen"],"dc:creator":["Simunika, Nathan N"],"dc:date.accessioned":["2014-11-05T03:49:36Z"],"dc:date.available":["2014-11-05T03:49:36Z"],"dc:date.issued":["2013"],"dc:description":["Includes bibliographical references."],"dc:description.abstract":["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."],"dc:identifier.uri":["http://hdl.handle.net/11427/9128"],"dc:language.iso":["eng"],"dc:publisher.department":["Centre for Bioprocess Engineering Research"],"dc:publisher.institution":["University of Cape Town"],"dc:subject":["Bioprocess Engineering Research"],"dc:title":["Predicting the time related generation of acid rock drainage from mine waste: a copper case study"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:23:27Z"}