Improvement of prediction tools for contaminated mine drainage: assessment of scale, geomicrobiology, and sorption issues

改进矿山排水污染预测工具：评估规模、地球微生物学和吸附问题

• 批准号: 538443-2018
• 负责人: Plante, Benoît
• 金额: $ 4.62万
• 依托单位: Université du Québec en Abitibi-Témiscamingue
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=691181
• 关键词: Improvement; prediction; tools; contaminated; mine

Despite numerous advances in the prediction of mine water quality in the last decades, the mining industry is still facing critical challenges. In particular, available water quality prediction tools are still limited by issues related to: scale effects between laboratory, field, and full-scale data; assessing the effectiveness of laboratory kinetic tests to reproduce the microbial community effects and to evaluate their involvement to the overall geochemistry of mine wastes in ambient and cold temperatures; and the impacts of sorption phenomena on contaminant concentrations. The proposal aims to tackle these issues through a combination of advanced chemical, mineralogical, and microbiological characterizations (including both genomic and culture-dependent techniques), as well as through kinetic tests at the laboratory and field scales. Kinetic testing at the laboratory scale will be performed at room temperature as well as under conditions typical of northern environments, namely sub-zero temperatures and highly saline drainage waters, while the field testing will be performed directly at the mine sites. Results from the various projects will not only improve the actual prediction tools, but also increase fundamental knowledge about scale-up issues from laboratory to field water quality prediction results, as well as the ability of kinetic tests to simulate the microbiological processes occurring in mine wastes and their effects on water quality in both temperate and arctic climates. The results from the proposed research program will improve the accuracy of mine water quality predictions, thus increasing the environmental performance of the mining industry. Furthermore, this program will provide training opportunities for future leaders in mine waste geochemistry through hands-on laboratory and field experience, as well as inter-university collaborations.

尽管在过去的几十年里，矿山水质预测取得了许多进展，但采矿业仍然面临着严峻的挑战。特别是，现有的水质预测工具仍然受到以下问题的限制：实验室、现场和全尺度数据之间的规模效应；评估实验室动力学测试的有效性，以再现微生物群落效应，并评估它们在常温和寒冷温度下对矿山废物整体地球化学的影响；以及吸附现象对污染物浓度的影响。该提案旨在通过结合先进的化学、矿物学和微生物学特征(包括基因组和依赖于培养的技术)以及通过实验室和田间规模的动力学测试来解决这些问题。实验室规模的动力测试将在室温以及北方典型环境条件下进行，即零下温度和高盐度排水，而现场测试将直接在矿场进行。不同项目的结果不仅将改进实际的预测工具，还将增加关于从实验室到现场水质预测结果的放大问题的基础知识，以及动力学测试模拟温带和北极气候下矿山废物中发生的微生物过程及其对水质影响的能力。所提出的研究方案的结果将提高矿山水质预测的准确性，从而提高矿业的环境绩效。此外，该项目将通过实验室和实地实践经验以及大学间的合作，为矿山废物地球化学领域的未来领导者提供培训机会。