HUBEI AGRICULTURAL SCIENCES ›› 2022, Vol. 61 ›› Issue (10): 213-221.doi: 10.14088/j.cnki.issn0439-8114.2022.10.038

• Economy & Management • Previous Articles     Next Articles

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

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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