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    云南省威信县煤矿资源承载能力评价

    Evaluation of coal mine resources carrying capacity in Weixin County, Yunnan Province

    • 摘要:
      研究目的 矿产资源是经济社会发展的重要支撑,其承载能力大小是决定区域经济结构及发展模式的根本依据,开展区域矿产资源承载能力评价对促进地区矿产资源可持续开发利用具有十分重要的意义。
      研究方法 以云南省威信县煤矿资源为研究对象,借助承载本底(资源可利用量占比,PRO)和承载状态(矿业开发指数,MDI)两个评价因子来构建评价指标体系。在此基础上对威信县煤矿资源的承载能力进行评价,并以威信县为评价试点对矿产资源评价体系及各分指标权重分配的合理性进行了相关探讨。
      研究结果 威信县10个乡镇中,没有煤矿资源承载能力“大”的乡镇,承载能力“较大”的乡镇仅有2个,承载能力“中”的乡镇有2个,承载能力“小”的乡镇则达到了6个。
      结论 在矿产资源承载能力评价体系中,正向指标与负向指标也应并重考虑,各占50%左右为宜。此外各分指标权重的分配也应与该地区当时在经济、社会、环境方面的政策紧密呼应。

       

      Abstract:
      This paper is the result of mineral exploration engineering.
      Objective Mineral resources are an important support for economic and social development, and their carrying capacity is the fundamental basis for determining the regional economic structure and development model. It is of great significance to carry out the evaluation of the carrying capacity of regional mineral resources to promote the sustainable development and utilization of regional mineral resources.
      Methods In this paper, the coal mine resources of Weixin County of Yunnan Province are taken as the research object, and the evaluation index system is constructed by two evaluation factors of carrying background (proportion of resources available, PRO) and carrying state (mining development index, MDI). On this basis, the carrying capacity of coal mine resources in Weixin County is evaluated, and the rationality of the evaluation system of mineral resources and the weight distribution of each sub index is discussed with Weixin County as the evaluation pilot.
      Results Among the ten townships in Weixin County, there are no townships with "large" coal mine resources carrying capacity, only two with "relative large" carrying capacity, two with "medium" carrying capacity, and six with "small" carrying capacity.
      Conclusions In the evaluation system of bearing capacity of mineral resources, both positive and negative indicators should be considered equally, accounting for about 50% respectively. In addition, the distribution of the weight of each sub indicator should also closely correspond with the economic, social and environmental policies of the region at that time.

       

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