矿业固体废弃物大数据研究

Big Data Research on Mining Solid Wastes

  • 摘要: 通过我国20个重要矿种12 366座矿山固体废弃物大数据研究,得到了我国主要矿产平均入选原矿品位、不同矿种采矿废石排放强度和选矿尾矿排放强度、废石和尾矿利用水平等技术指标。结果表明:我国矿山废石年产生量大于尾矿年产生量,20种矿种矿山的废石加权平均利用率为17.77%,尾矿加权平均利用率为18.97%。文章提出基于资源属性-环境效应和技术经济等三位一体的综合评价方式,建立尾矿和废石无害化处置、有效保护和合理利用分类建议。

     

    Abstract: The big data of mining wastes of 20 ore types from 12 366 mines in China were studied. Relationships among mullocks, tailings and concentrates were interpreted by the concepts of mullocks discharge intensity and tailings discharge intensity. Recycling levels of mining and processing wastes were summarized. The results showed that the grades of major ores are relatively low, which results in enormous waste rocks and tailings generated during mining and processing process. Moreover, the weighted average utilization ratio of waste rocks and tailings are about 17.77% and 18.97%, representatively. The paper proposes a trinity-based comprehensive evaluation method based on resource attributes-environmental effects, and technological economics, and establishes classification recommendations for harmless disposal of tailings and waste rock, effective protection and rational use.

     

/

返回文章
返回