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<p>Analyzing the spatiotemporal heterogeneity, convergence, and influencing factors of livestock non-point source (NPS) pollution emission intensity is essential for implementing effective pollution reduction policies and fostering economic and environmental synergies in the livestock sector. This study employs panel data from 31 provinces in China covering the period from 2006 to 2021, integrating the livestock NPS pollution accounting formula, Theil index, Kernel density estimation, and a convergence model to investigate the spatiotemporal heterogeneity, convergence, and determinants of livestock NPS pollution emission intensity. The findings indicate a significant decline in livestock NPS pollution emission intensity over the study period, accompanied by pronounced regional gaps. Inter-regional gap is identified as the primary contributor to the overall gap, with the western region contributing most significantly. The dispersion of livestock NPS pollution emission intensity among regions exhibits a decreasing trend, signaling a pattern of convergence. Furthermore, factors such as initial emission intensity, livestock output value per capita, mechanization level, population density, urbanization level, industrial structure, and breeding scale show heterogeneous spatiotemporal impacts on livestock NPS pollution emission intensity. This study provides valuable insights for advancing pollution abatement and facilitating the livestock green transformation in China, as well as in other developing countries with similar environmental conditions.</p>

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Unraveling the spatiotemporal mosaic: convergence dynamics and multifactorial influences on livestock non-point source pollution emission intensity with a holistic five-pollutant perspective

  • 期刊论文

  • 发表日期：

    2025年3月20日

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  • Ming Li,
  • Haifeng Xiao

摘要

Analyzing the spatiotemporal heterogeneity, convergence, and influencing factors of livestock non-point source (NPS) pollution emission intensity is essential for implementing effective pollution reduction policies and fostering economic and environmental synergies in the livestock sector. This study employs panel data from 31 provinces in China covering the period from 2006 to 2021, integrating the livestock NPS pollution accounting formula, Theil index, Kernel density estimation, and a convergence model to investigate the spatiotemporal heterogeneity, convergence, and determinants of livestock NPS pollution emission intensity. The findings indicate a significant decline in livestock NPS pollution emission intensity over the study period, accompanied by pronounced regional gaps. Inter-regional gap is identified as the primary contributor to the overall gap, with the western region contributing most significantly. The dispersion of livestock NPS pollution emission intensity among regions exhibits a decreasing trend, signaling a pattern of convergence. Furthermore, factors such as initial emission intensity, livestock output value per capita, mechanization level, population density, urbanization level, industrial structure, and breeding scale show heterogeneous spatiotemporal impacts on livestock NPS pollution emission intensity. This study provides valuable insights for advancing pollution abatement and facilitating the livestock green transformation in China, as well as in other developing countries with similar environmental conditions.