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<p>Against the backdrop of the “dual-carbon” strategy and comprehensive rural revitalization, exploring the impacts and underlying mechanisms of the spatial correlation network of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction provides crucial references for green and low-carbon rural development. Based on a research sample of 30 Chinese provinces from 2010 to 2023, this paper systematically analyzes the transmission pathways through which the spatial correlation network of new quality productive forces affects the synergistic effect of agricultural pollution and carbon reduction by employing a Double Machine Learning model. The empirical findings reveal that the level of the synergistic effect of agricultural pollution and carbon reduction exhibited an upward trend over the study period, accompanied by pronounced spatial disparities. Furthermore, the spatial correlation network of new quality productive forces significantly promotes the synergistic effect of agricultural pollution and carbon reduction, with prominent spatial spillover effects being detected. Heterogeneity analyses indicate that the impacts of spatial correlation networks of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction vary across four dimensions: temporal spans, resource endowments, human capital levels, and low-carbon lifestyles. Mechanism testing demonstrates that agricultural technological innovation plays a significant mediating role in the impact of the spatial correlation networks of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction, with agricultural invention innovation serving as the primary pathway. Collectively, this study uncovers the intricate pathways of the synergistic effect of agricultural pollution and carbon reduction from the spatial correlation networks of new quality productive forces perspective, offering robust empirical evidence for the coordinated advancement of rural green development and the low-carbon economy.</p>

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Impact of the spatial correlation network of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月31日

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  • Xue Zhu,
  • Ran Gong,
  • Sheng Qu,
  • Junru Sun,
  • Shidi Shao,
  • Xiwu Shao

摘要

Against the backdrop of the “dual-carbon” strategy and comprehensive rural revitalization, exploring the impacts and underlying mechanisms of the spatial correlation network of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction provides crucial references for green and low-carbon rural development. Based on a research sample of 30 Chinese provinces from 2010 to 2023, this paper systematically analyzes the transmission pathways through which the spatial correlation network of new quality productive forces affects the synergistic effect of agricultural pollution and carbon reduction by employing a Double Machine Learning model. The empirical findings reveal that the level of the synergistic effect of agricultural pollution and carbon reduction exhibited an upward trend over the study period, accompanied by pronounced spatial disparities. Furthermore, the spatial correlation network of new quality productive forces significantly promotes the synergistic effect of agricultural pollution and carbon reduction, with prominent spatial spillover effects being detected. Heterogeneity analyses indicate that the impacts of spatial correlation networks of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction vary across four dimensions: temporal spans, resource endowments, human capital levels, and low-carbon lifestyles. Mechanism testing demonstrates that agricultural technological innovation plays a significant mediating role in the impact of the spatial correlation networks of new quality productive forces on the synergistic effect of agricultural pollution and carbon reduction, with agricultural invention innovation serving as the primary pathway. Collectively, this study uncovers the intricate pathways of the synergistic effect of agricultural pollution and carbon reduction from the spatial correlation networks of new quality productive forces perspective, offering robust empirical evidence for the coordinated advancement of rural green development and the low-carbon economy.