Study on the Index System of Green Investigation and Environmental Evaluation for the Jiajika Large Lithium Mineral Resource Base, Western Sichuan, China
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摘要: 在资源、环境和经济协调发展的大背景下，发展绿色矿业已成为国家战略重点推进并得到了广泛认同。大型资源基地绿色调查及环境评价指标体系的建立、模型的技术实现将为解决生态脆弱区找矿部署与环境保护瓶颈问题发挥重要作用。本文将绿色调查与环境评价两方面工作有机结合，分四个层次构建指标框架，通过3S技术提取生态环境现状及变化信息，结合连续三年的地表水、土壤等多环境介质野外调查取样分析数据，对经过验证的、成熟的评价方法进行优化，运用更兼容、可扩展的Python语言编程建立了基于支持向量机的大型锂资源基地环境评价模型。运用该模型，将大型基地环境现状划分为环境较差区、环境一般区、环境较好区、环境良好区四类区域，总体准确率达97.77%。结果表明，本文建立的该套有针对性的评价指标体系能够对川西大型锂资源基地的环境现状作出有效的评价，通过技术创新实现了大型锂资源基地环境现状"像元级"可视化分级，较客观地反映了甲基卡矿区及周边资源开发环境问题与影响范围，在一定程度上可辅助规范大型基地矿产资源开发利用的管理及决策。Abstract:
BACKGROUNDUnder the background of coordinated development of resources, environment and economy, the development of green mining has become a national strategic focus and has been widely recognized. Environmental investigation and evaluation is one of the main content in investigation and assessment of large lithium metallic mineral bases in Sichuan Province, which will play an important role in solving the bottleneck problems, such as prospecting deployment and environmental protection in the ecologically fragile district of the Western Sichuan Plateau. OBJECTIVESTo put forward the green investigation method and to establish an index system of environmental evaluation and demonstration of typical mining areas. METHODSGreen investigation and environmental assessment were combined, an indicator framework in four levels was constructed, and the status quo and change information of the ecological environment through 3S technology were extracted. Based on three years of surface water, soil and other multi-environmental media field survey and analysis data, a mature evaluation method has been optimized, and a large-scale lithium resource base environment evaluation model based on support vector machine was established by using a more compatible and scalable Python language programming. RESULTSUsing this model, the current status of large-scale bases was divided into four categories:environmentally poor areas, general environmental areas, better environmental areas, and good environmental areas. The overall accuracy rate was 97.77%. CONCLUSIONSThe set of a targeted evaluation index system established and reported on in this paper effectively evaluates the environmental status of large-scale lithium resource bases in Western Sichuan, and realizes the visual level of 'pixel-level' environmental status of large-scale lithium resource bases through technological innovation. The method objectively reflects the development and environmental impacts of the Jiajika mining area and surrounding resources, and to a certain extent, can assist in regulating the management and decision-making of the development and utilization of large-scale mineral resources. -
Key words:
- green investigation /
- evaluation index system /
- green mine /
- ecological fragile region /
- Jiajika
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表 1 大型基地矿产资源开发不同阶段环境评价指标体系
Table 1. Environmental assessment index system for different stages of mineral resources development in large bases
目标层 指标层 勘查初期阶段 矿产资源开发阶段 环境恢复治理阶段 自然地理 地形地貌 √ √ √ 降雨量 √ √ √ 植被覆盖度 √ √ √ 地质背景 地质构造 √ √ √ 岩性组合 √ √ √ 矿业开发 主要开采方式 √ √ √ 噪声 √ √ √ 占用土地比例 √ √ √ 开采点密度 √ √ 采空区面积比 √ √ 开采回采率 √ √ 选矿回收率 √ √ 共伴生组分利用率 √ √ 尾矿利用率 √ √ 环境影响 地质灾害隐患 √ √ √ 地质灾害预警 √ √ √ 水资源破坏程度 √ √ √ 土壤资源破坏程度 √ √ √ 固废堆放占地 √ √ 废水废液排放 √ √ 大气环境质量 √ √ 荒漠化面积 √ √ 土壤侵蚀模数 √ √ 环境治理投入强度 √ 治理难度 √ 
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表 2 环境效应评价指标量化处理标准
Table 2. Quantitative processing standard of the environmental effect evaluation index
指标类型 评价指标 评价指标分级标准(分值) 1 2 3 自然地理(A) 地形地貌(A1)
降水量(A2)
植被覆盖度(A3)坡度＞35°
＜200mm
＜40%坡度20°~35°
200~900mm
40%~60%坡度＜20°
＞900mm
＞60%基础地质(B) 构造(B1)
岩性组合(B2)强烈发育
松散堆积物较发育
软质岩为主不发育
硬质岩为主矿业开发(C) 主要采选方式(C1)
噪声(C2)
占用土地比例(C3)浮选
嘈杂
＞10%重选+磁选
一般
0~10%联合选矿
安静
无矿业占地环境影响(D) 地质灾害隐患(D1)
地质灾害预警(D2)
水环境破坏程度(D3)
土壤环境破坏程度(D4)易发
较多
严重
严重轻微
一般
一般
一般基本没有
较少
无
无
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