Developing high-quality regional integration requires a good-quality water environment. In this study, the impact of formal and informal environmental regulation (FIER) on water environment governance performance (WEP) is examined using a fixed-effects model and spatial Durbin model with a panel data sample of 281 cities from 2011 to 2022. It is found that (i) there is an inverted U-shaped relationship between FIER and WEP, which is first promoted and then inhibited and remains significant after endogeneity exploration and multiple robustness tests; (ii) the pressure of economic growth has weakened this elationship, while the digital economy has strengthened it; and (iii) further analysis reveals that there is an inverted U-shaped relationship between the local and spillover effects of FIER on WEP. Therefore, WEP can be improved by dynamically adjusting the intensity of FIER, optimizing the appraisal orientation of local governments, and accelerating the integration of digital economy and environmental governance

Enhancing Total Factor Energy Efficiency (TFEE) is pivotal for achieving China’s “dual carbon” goals and navigating the global challenge of sustainable development. The Digital Economy (DE) serves as a significant driver of TFEE improvement. However, China’s rapid industrialization has exacerbated energy insecurity and environmental degradation, highlighting the need to explore how the DE can address these challenges through biased technological progress. Building on panel data from 282 prefecture-level cities in China (2011–2022), this study employs the theory of biased technological progress to empirically examine the impact of the DE on TFEE from dual perspectives: skill-biased versus task-biased technological change. The findings reveal that the DE significantly enhances TFEE, a conclusion robust to rigorous testing and endogeneity controls; the DE primarily promotes TFEE through facilitating human capital and industrial transformation; the positive effect of the DE on TFEE is particularly pronounced in eastern and western regions, as well as in areas exhibiting moderate energy dependence; and the DE not only elevates local TFEE but also generates positive spatial spillover effects that significantly improve TFEE in neighboring regions. This study provides a framework for leveraging digitalization to enhance TFEE, with implications for policy design in developing countries pursuing sustainable transitions.

Promoting green industrial development and enhancing high-quality employment are crucial for advancing county-level economic growth and achieving shared prosperity. This study analyzes the spatiotemporal evolution trends of green industrial development and high-quality employment using panel data from 20 mountainous counties (cities and districts) in Zhejiang Province from 2010 to 2023. It employs panel models to investigate the effects and mechanisms through which green industrial development fosters high-quality employment. The results indicate that, during the study period, both green industry development and high-quality employment exhibited uneven progress across the 20 mountainous counties (cities and districts) in Zhejiang. Mechanism analysis revealed that green industrial development significantly promotes high-quality employment through two pathways: industrial structure upgrading and technological progress. The heterogeneity analysis indicates that the impact of green industrial development on high-quality employment varies significantly across different industrial structures, with counties dominated by the tertiary sector showing more substantial promotion effects. The threshold regression analysis reveals a dual-threshold effect of technological progress in promoting high-quality employment through green industrial development, presenting an approximately J-shaped nonlinear relationship. The research findings provide significant support for the sustainable development of the ecological environment and society by addressing current imbalances between ecological preservation and economic or social growth.