Purpose: There is no conclusive whether environmental regulation is a constraint or an incentive to the production development. The purpose of this paper is to analyze the non-linear effects of environmental regulations on economic outcomes from the combined perspective of labor productivity and environmental regulation costs. Design/methodology/approach: Under the assumption of maximizing the utility of residents and maximizing the profit of firms, this research introduces a mathematical model that incorporates the promotion effect of environmental regulations on labor productivity and the costs of environmental regulations. On this basis, the authors analyze the non-linear relationship between environmental regulations and economic outcomes theoretically. This paper also conducts an empirical test using the panel data of 28 provinces in China from 1998 to 2015 through threshold regression. Findings: Theoretical analysis shows that environmental regulations impose both the environmental regulation cost effect and the compensation effect on the labor productivity enhancement. The ultimate impact of environmental regulation on economic outcomes depends on the comparison of these two effects. Under the different intensities of environmental regulation, the magnitude of these two effects may not be equal. The empirical results further confirm the nonlinear relationship between environmental regulations and economic outcomes. Originality/value: Previous studies have neglected the role of environmental regulations in improving labor productivity. This work’s main contribution is to propose a novel framework to study the non-linear relationship between environmental regulation and the growth of economic outcomes from perspective of labor productivity and the costs of environmental regulations.

This paper investigates the role of the digital economy in reducing carbon emissions, with a particular focus on the moderating and threshold effects of green finance. An analysis of data from 30 Chinese provinces shows that the digital economy significantly reduces carbon emission intensity by restructuring energy consumption and promoting green technological innovation. Green finance plays a crucial moderating role by alleviating financial barriers to digital transformation and supporting the implementation of emission-reducing technologies. The study reveals a nonlinear relationship, with green finance exhibiting a “strong initial, weak subsequent” threshold effect. At the same time, the digital economy’s impact on carbon reduction strengthens over time as technological development progresses. These findings contribute to understanding how digitalisation and green finance can work synergistically to drive sustainable low-carbon development.

Digital technologies hold significant potential for addressing environmental issues, such as air pollution and rising global temperatures. China is focusing on accelerating the dual transformation of industrial greening and digitization to accomplish the UN’s 2030 Agenda for Sustainable Development and sustainable economic growth. By combining a two-way fixed effect model, a mediated effect model, and a panel threshold model, this research endeavors to explore the effect that the expansion of the digital economy has on the level of carbon emission intensity that is produced by industry. The research yielded the following primary conclusions. (1) The digital economy effectively reduces the industrial carbon intensity via three distinct mechanisms: enhancements to the technological and innovative capacities of China, improvements in energy efficiency, and enhancements to the country’s overall industrial structure. (2) Regions where industrialization and digitization are highly integrated and developing, as well as the early pilot regions of the Comprehensive Big Data Pilot Zones, are particularly susceptible to this inhibitory effect. This research offers a theoretical backing for advancements in the digital economy; the achievement of energy-saving and carbon-reducing sustainable development objectives; and the establishment of green, ecologically friendly, and recycling development strategies.

Integrated ocean management (IOM) aligns with the United Nations’ Sustainable Development Goals (SDGs) and serves as a crucial strategy for promoting the enduring health of marine ecosystems and the sustainable utilization of marine resources. An analysis of the evolution of China’s integrated ocean management policy (IOMP) is crucial for providing valuable guidance in achieving sustainable growth in marine management and the marine economy for both China and other coastal nations worldwide. This paper studies the evolution characteristics, challenges, and prospects of IOMP in China since 1978 using content analysis. The findings indicate that the evolution of IOMP can be categorized into four stages: the germination period (1978–1998), the construction period (1999–2009), the systematization period (2010–2017), and the strategization period (2018–present), based on the state of international marine management. The IOMP has transitioned over time from its initial emphasis on resource development during the germination period to a strategization period that prioritizes the full development of all parts of the system. However, the ultimate goal has consistently been to achieve harmonious coexistence between people and the sea. China’s IOMP has experienced a progressive development; nevertheless, it continues to encounter obstacles such as the pressing requirement to revise sea-related policies and the absence of policy alignment. The objective of this paper is to explore the evolution, challenges, and prospects of China’s IOMP to better improve the land–sea coordination policy, strengthen international judicial cooperation. and provide effective policy reference for other maritime countries.

Taking “blue granary” as the research object, this study focuses on the mechanism and evolution of coupling coordination relationship between green transformation and the quality of economic development, to explore the path of sustainable development. Firstly, the theoretical framework of coupling relationship between green transformation and the quality of development is constructed. Secondly, an evaluation index system is established to measure green transformation and the quality of economic development. Thirdly, the entropy approach and coupled coordination degree model are used to calculate the coordination of green transformation and the quality of economic development in different provinces in China from 2009 to 2018. The results show that: (1) Green transformation affects the quality of economic development through resource effect, social effect, and technological effect; the quality of economic development affects green transformation through new growth momentum effect, income distribution effect, scale effect, and opening up effect. (2) Both the quality of economic development and the level of green transformation continue to improve, but the growth rate of green transformation is relatively slow. (3) The overall coupled coordination relationship improves from a barely balanced stage to a favorably balanced stage, but it has not reached the ideal state of superiorly balanced, and there is significant regional heterogeneity. It will help to clarify the difference in coordinated development levels in different regions and provide a reference value for the precise implementation of eco-economic coordinated development.

The deep integration of intelligent technology and the manufacturing industry is a crucial driving force for promoting green and low-carbon development, which is a key strategy for achieving sustainable development. Using panel data from 30 provinces in mainland China from 2010 to 2022, this study measures the level of intelligent development and the total factor carbon emission performance (TFCEP). Additionally, a mediating effect model is constructed to explore the impact of intelligent manufacturing (IM) on carbon emission performance (CEP) and its underlying mechanisms. The findings reveal that (1) the intellectualization of the manufacturing industry significantly enhances CEP, a conclusion that remains robust under various tests; (2) the impact of IM on CEP varies by regional geographical locations, the degree of economic agglomeration (EA), and whether the province is a low-carbon pilot area; and (3) the mechanism analysis indicates that IM improves CEP by promoting EA. Given that China is the world’s largest manufacturing country and the largest carbon emitter, analyzing the impact of its IM on CEP provides valuable theoretical insights and practical experiences for China and other manufacturing countries aiming to achieve a win–win situation of sustainable economic development and environmental improvement.