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<p>This study investigates how the digital economy reduces pollution and carbon emissions (RPCE) in the Yellow River Basin through three core mechanisms: (1) enabling real-time environmental monitoring and precision regulation, (2) fostering enterprise green production via digital transformation, and (3) driving technological innovation and industrial upgrading, proposing three testable hypotheses on these pathways. Indicators for the digital economy and RPCE are developed, and a spatiotemporal analysis of RPCE levels is conducted at both the municipal and grid scales. Employing the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model to comprehensively examine population, affluence, and technology drivers, and innovatively integrating analysis at both municipal and grid scales to overcome traditional limitations, this study examines the direct and mediating effects of the digital economy on RPCE, along with heterogeneity analysis, endogeneity discussions, and exogenous shock tests, providing a more refined framework for revealing the mechanisms. Based on empirical findings, future RPCE trends in the basin are projected, with a proposed three-pronged strategy: digital infrastructure deployment, sector-specific interventions, and place-based prioritization (technology-upgrading midstream; clean-energy transition upstream). The main conclusions are as follows: (1) During the study period, RPCE in the Yellow River Basin showed significant improvement, with an upstream &gt; downstream &gt; midstream pattern and a block-like distribution. (2) The statistically significant regression coefficient (β = -0.476, <i>p</i> &lt; 0.01) indicates a positive impact of the digital economy on RPCE, thus validating Hypothesis 1. Both technological innovation and industrial structure upgrading serve as positive mediators in the influence of the digital economy on RPCE, confirming Hypotheses 2 and Hypotheses 3. (3) The growth rate of population size is a major factor driving divergence in the RPCE index across the basin. To advance RPCE in the Yellow River Basin, policies should prioritize the development of the digital economy while promoting high-quality economic growth and stabilizing population growth rates.</p>

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Mechanisms and Scenario Predictions of the Digital Economy’s Impact on Pollution and Carbon Emission Reduction: A Case Study of the Yellow River Basin in China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月10日

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  • Tianle Shi,
  • Zhengmeng Hou,
  • Jianhua Liu,
  • Hao Fang,
  • Qichen Wang,
  • Yilin Guo,
  • Ru Zhang,
  • Liangchao Huang

摘要

This study investigates how the digital economy reduces pollution and carbon emissions (RPCE) in the Yellow River Basin through three core mechanisms: (1) enabling real-time environmental monitoring and precision regulation, (2) fostering enterprise green production via digital transformation, and (3) driving technological innovation and industrial upgrading, proposing three testable hypotheses on these pathways. Indicators for the digital economy and RPCE are developed, and a spatiotemporal analysis of RPCE levels is conducted at both the municipal and grid scales. Employing the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model to comprehensively examine population, affluence, and technology drivers, and innovatively integrating analysis at both municipal and grid scales to overcome traditional limitations, this study examines the direct and mediating effects of the digital economy on RPCE, along with heterogeneity analysis, endogeneity discussions, and exogenous shock tests, providing a more refined framework for revealing the mechanisms. Based on empirical findings, future RPCE trends in the basin are projected, with a proposed three-pronged strategy: digital infrastructure deployment, sector-specific interventions, and place-based prioritization (technology-upgrading midstream; clean-energy transition upstream). The main conclusions are as follows: (1) During the study period, RPCE in the Yellow River Basin showed significant improvement, with an upstream > downstream > midstream pattern and a block-like distribution. (2) The statistically significant regression coefficient (β = -0.476, p < 0.01) indicates a positive impact of the digital economy on RPCE, thus validating Hypothesis 1. Both technological innovation and industrial structure upgrading serve as positive mediators in the influence of the digital economy on RPCE, confirming Hypotheses 2 and Hypotheses 3. (3) The growth rate of population size is a major factor driving divergence in the RPCE index across the basin. To advance RPCE in the Yellow River Basin, policies should prioritize the development of the digital economy while promoting high-quality economic growth and stabilizing population growth rates.