矿产保护与利用Issue(2)：40-43,51,5.DOI:10.13779/j.cnki.issn1001-0076.2018.02.008
矿业固体废弃物大数据研究
Big Data Research on Mining Solid Wastes
摘要
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%,repre-sentatively. The paper proposes a trinity-based comprehensive evaluation method based on resource attributes-environmental effects,and technological economics,and establishes classification recom-mendations for harmless disposal of tailings and waste rock,effective protection and rational use.关键词
尾矿/废石/大数据/固体废弃物Key words
tailings/mullock/big data/solid waste分类
管理科学引用本文复制引用
冯安生,吕振福,武秋杰,杨卉芃,吴彬,曹进成..矿业固体废弃物大数据研究[J].矿产保护与利用,2018,(2):40-43,51,5.基金项目
中国地质调查项目(1212011220930,121201017000160901) （1212011220930,121201017000160901）
