Sampling and blending in geoenvironmental campaigns – current practice and future opportunities
Sampling and blending in geoenvironmental campaigns – current practice and future opportunities
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地质环境活动中的采样和混合——当前实践和未来机遇
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Dominy
中科院分区：
文献类型：
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作者：
Anita Parbhakar;S. Dominy
在矿山价值链的各个阶段，矿山废弃物中酸性和含金属废水（AMD）的预测至关重要。然而，为了确定这种地质环境特征，必须对代表性样品进行单个废物单元的静态和动态测试。样本选择的重要性不可低估;它是任何地质环境调查中最关键的一个方面。抽样技术差和样本选择不当将造成差异过大、难以解释和评估不正确。通过进行基于高光谱矿物学数据（含硫分析数据，如果有的话）的细观结构表征，提出了改进采样策略的机会。这些数据将为低成本的总硫、膏体pH值和地质环境记录的样本选择提供信息，这些数据共同将允许实现准确的AMD预测和改进的采样实践。一旦取样，必须制定强有力的质量保证/质量控制（QA/QC）协议，其中必须使用国际认证的参考标准。目前没有这样做，导致在进行废物分类时实验室之间的差异。地质环境特性测试的进一步改进在于采用混合静态测试协议，从而可以有效地测试废物材料的混合物，以便及早预测它们是否会产生酸性或含金属的排水。这些信息是制定废物时间表的组成部分，该时间表将允许从运营阶段开始就构建非酸形成废物地貌。最终，这一学科的改进在于矿物学表征方面的技术创新，并为地球科学和矿物工程专业的学生提供该学科的合格教育。总的来说，这将使AMD的预测和废物处理发生重大变化，并将使联合国可持续发展目标的实现成为现实，而不是梦想。
The prediction of acid and metalliferous drainage (AMD) from mine waste materials is critically important during all stages of the mine value chain. However, to determine such geoenvironmental characteristics static and kinetic testing of individual waste units must be performed on representative samples. The importance of sample selection cannot be underestimated; it is the single most critical aspect of any geoenvironmental investigation. Poor sampling techniques and inadequate sample selection will contribute to excessive variance, difficulties in interpretation and incorrect assessment. By undertaking mesotextural characterisation based on hyperspectral mineralogical data (with sulfur assay data if available), opportunities to improve sampling strategies are presented. Such data will inform the selection of samples for low-cost total sulfur, paste pH and geoenvironmental logging, which collectively will allow for accurate AMD forecasting and improved sampling practices to be achieved. Once sampled, robust quality assurance/quality control (QA/QC) protocols must be developed where the use of international certified reference standards become obligatory. This is currently not practised, resulting in inter-laboratory discrepancies when undertaking waste classification. Further improvements in geoenvironmental characterisation testing lies in the adoption of blended static testing protocols, whereby blends of waste materials can be efficiently tested so as to give an early forecast as to whether they will produce acidic or metal-laden drainage. Such information is integral in developing a waste schedule that will allow for a non-acid forming waste landform to be constructed right from the start of the operational phase. Ultimately, improvements in this discipline lie in technological innovations with regards to mineralogical characterisation, and by offering geoscience and minerals engineering students a competent education in the discipline. Collectively, this will empower a step-change in AMD prediction and waste handling, and will make the realisation of the United Nations Sustainable Development Goals a reality, rather than a dream.