湖北农业科学 ›› 2022, Vol. 61 ›› Issue (10): 213-221.doi: 10.14088/j.cnki.issn0439-8114.2022.10.038

• 经济·管理 • 上一篇    下一篇

黄河流域重金属水污染物排放的脱钩机理研究

张黄博, 吴英巨, 王稀   

  1. 河海大学商学院,江苏 常州 213022
  • 收稿日期:2021-03-22 出版日期:2022-05-25 发布日期:2022-06-14
  • 作者简介:张黄博(2000-),男,广东汕头人,在读本科生,专业方向为国际经济与贸易,(电话)15195002265(电子信箱)1863510327@hhu.edu.cn。
  • 基金资助:
    河海大学大学生创新创业训练资助项目(202010294091)

Study on the decoupling mechanism of heavy metal water pollutants discharge in Yellow River Basin

ZHANG Huang-bo, WU Ying-ju, WANG Xi   

  1. School of Business, Hohai University, Changzhou 213022, Jiangsu, China
  • Received:2021-03-22 Online:2022-05-25 Published:2022-06-14

摘要: 利用Tapio和LMDI模型获得2011—2017年黄河流域经济增长与重金属水污染物排放脱钩状态及驱动效应,结合Dagum基尼系数和Kernel密度估计,揭示区域及其子地区的关键驱动效应变化的时空差异特征、贡献率及动态演变规律,阐释黄河流域重金属水污染物排放的脱钩机理。结果表明,流域层面虽呈强脱钩状态(除2014—2015年),但上游地区脱钩情况仍十分不稳定;排污强度效应是驱动流域重金属水污染物排放脱钩的主导效应,工业化收入效应是抑制流域重金属水污染物排放脱钩的主导效应;区域及上游地区内的主导驱动效应的时空差异是流域时空差异的主要来源,排污强度效应和工业化收入效应虽然在向驱动脱钩的方向演进,但省区差异不均衡问题更加突出。据此,提出促进流域内各省区重金属水污染物排放脱钩的建议。

关键词: 脱钩, 重金属, Dagum基尼系数, Kernel密度估计, 黄河流域, 差异分析

Abstract: The Tapio and LMDI model were used to obtain the decoupling status and driving effect of the economic growth and heavy metal water pollutants discharge of the Yellow River Basin from 2011 to 2017, combined with the Dagum Gini coefficient and Kernel density estimation, the spatial and temporal difference characteristics, contribution rate and dynamic evolution laws of the key driving effects in regions and their sub-regions were revealed, and the decoupling mechanism of heavy metal water pollutants discharge in the Yellow River Basin was explained. The results showed that although there was a strong decoupling state at the basin level (except 2014—2015), the decoupling situation in the upstream region was still very unstable. The discharge intensity effect was the dominant effect driving the decoupling of heavy metal water pollutants discharge in the basin, and the income effect of industrialization was the dominant effect restraining the decoupling of heavy metal water pollutants discharge. The spatial and temporal differences of the dominant driving effects between regions and the upstream regions were the main sources of the spatial and temporal differences in the basin. Although the effects of pollutant discharge intensity and industrialization income were evolving towards the direction of driving decoupling, the imbalance between provinces and regions was more prominent. Based on this, suggestions were put forward to promote the decoupling of heavy metal water pollutants discharge in the provinces and regions within the basin.

Key words: decoupling, heavy metal, Dagum Gini coefficient, Kernel density estimation, Yellow River Basin, difference analysis

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