首页|碳排放约束下省际矿业能源效率评价—基于SBM-Malmquist指数模型

碳排放约束下省际矿业能源效率评价—基于SBM-Malmquist指数模型

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这是一篇矿业工程领域的文章.提升矿业能源效率,减少矿业碳排放是矿业实现绿色发展的重要途径.本文采用SBM模型和Malmquist指数,基于省域(省际)矿业面板数据,探究我国矿业在碳排放水平约束条件下的矿业能源效率.结果表明,在碳排放水平约束下我国矿业能源效率总体水平偏低,各区域能源效率存在差异.2013-2018年我国矿业能源全要素生产率总体波动不大,2015-2018年我国全要素生产率逐年上升,技术进步是效率提高的主要动力.因此,应提高矿业技术水平,加大矿业环境监测力度,因地制宜指定矿业能源相关政策.
Energy Efficiency Evaluation of Provincial Mining Industry under Carbon Emission Constraint:Based on SBM-Malmquist Index Model
This is an article in the field of mining engineering.Improving energy efficiency and reducing carbon emissions in the mining industry is an important way for the mining industry to achieve green development.This essay uses the SBM model and Malmquist index to explore the mining energy efficiency of China's mining industry under the carbon emission level constraint,based on provincial(inter-provincial)mining industry panel data.The results show that the overall level of energy efficiency of China's mining industry under the carbon emission level constraint is low,and there are differences in energy efficiency among regions.The overall fluctuation of total factor productivity of China's mining industry energy from 2013 to 2018 is not significant,and China's total factor productivity increased year by year from 2015 to 2018,with technological progress being the main driver of efficiency improvement.Therefore,the level of mining technology should be improved,mining environment monitoring should be increased,and mining energy-related policies should be designated according to local conditions.

Mining engineeringMining energy efficiencySBM modelMalmquist index

董延佳、罗德江、何峙锜、李俊波

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成都理工大学数理学院,成都理工大学数学地质四川省重点实验室,四川 成都 610059

矿业工程 矿业能源效率 SBM模型 Malmquist指数

四川省自然科学基金成都理工大学哲学社会科学研究项目数学地质四川省重点实验室开放基金

2022NSFSC0510YJ2021-ZD007scsxdz2021yb01

2024

矿产综合利用
中国地质科学院矿产综合利用研究所

矿产综合利用

CSTPCD
影响因子:0.643
ISSN:1000-6532
年,卷(期):2024.45(2)
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