Environmental data management for gold mines

PhD (Industrial Engineering), North-West University, Potchefstroom CampusSouth Africa has various environmental concerns that escalate every year. For this reason, mines need to operate as effectively as possible. Millions of people can die due to water pollution, dangerous mining activities and nuclear waste disposal. Industries also require environmental resources in order to deliver their services or to produce their products. Effective environmental management strategies are therefore a necessity for being competitive in the market. Mining companies in South Africa dominate various business sectors and produce around 10% of the gold internationally. The problem however, is the lack of accurate environmental reporting in this industry. Without accurate reporting, companies cannot quantify the impact of their operations. This prevents them from prioritising and focusing on crucial areas when making operational changes for environmental improvement. Every gold mining company has a unique management system to report and audit their environmental data. Some use the guidelines from the ISO 14 001 standard, others the Sustainability Reporting Guidelines (SRG) from the Global Reporting Initiative (GRI), and some even use in-house guidelines. These guidelines specify the categories that organisations need to report on. The accuracy and effectiveness of these reporting systems are however, the organisation's own responsibility. An effective environmental management system should analyse, manage and continually improve the environmental impact on themselves and others. Verified data should be obtained and analysed to determine the true impact. Top level decisions can be made on accurate information. This study focuses on one of South Africa's leading gold mining companies. A detailed investigation was done on the relevant operations, which did not have a documented process for explaining their environmental reporting procedures. Each individual environmental data management process was investigated and documented. The data tracking of nine shafts and eight gold processing plants were complex and inaccurate. After comparing the different data tracking diagrams, it was discovered that each operation followed their own unique process for reporting on the same GRI data categories. Various sheets were collected and used to compile the group board report. The reporting times were also irregular and supporting documents were limited and unverified. Finally, most of the environmental representatives were unaware of where their data originated from. A new improved standardised environmental data management system for gold mines was therefore developed in this study. The new system considered the requirements for both the shafts and plants. Clear definitions for each reporting category were provided to ensure uniformity. After implementing the system, the time spent on data collection was reduced and more time was utilised for informed decision-making strategies. Data integration plays a leading role in the development of this improved system. Various technical and business techniques were implemented in order to effectively capture the most accurate data. A centralised online data management system was developed to capture, display and manage the data for the entire gold mining group. Delivering verified source documents for all reporting categories in the GRI specifications is the main priority for an environmental management system improvement. This new improved system was implemented at a gold mining company. The developed process is based on the Plan-Do-Check-Act cycle (PDCA cycle). Continuous improvements on the system were done as the investigations progressed. An audit was conducted on the data to determine the accuracy of the new system. One of the main benefits of this new system is the improvement in accuracy of the reported data. The error in the reported values for energy from electricity purchased improved from 7 .97% to 0.02%. Potable water had a 19.35% error value when compared to verified data, but was improved to 0.61 %. The total data improvement went from 20% data error to only 4% data error. This proves that reliable reporting standards and accurate decision-making strategies can improve the environmental data management process and reduce the time required to audit the source documents. The standardised GRI process layout for every operation can be used for auditing purposes. It can be represented as a single soft copy document obtained on the centralised online data management system. Each reporting category on the document is linked to its relevant source document on the online data management system. This new process successfully enhances effective and accurate auditing results.Doctora