China’s economy is faced with mounting pressure to reduce CO₂ emissions. This study estimates the impact of green innovation and institutional quality on CO₂ emissions, and examines the moderating effect of institutional quality. The results show that: (1) Green innovation significantly reduced CO₂ emissions. Institutional quality has a negative moderating effect on the relationship between green innovation and CO₂ emissions, such that when institutional quality is high, green innovation has a stronger reduction in CO₂ emissions. (2) Green innovation significantly reduced CO₂ emissions in the eastern and western regions. Moreover, as institutional quality improves, the reduction of CO₂ emissions through green innovation increased in the western region. (3) Green innovation in 2013–2017 had a greater effect on CO₂ emissions reduction than 2005–2012. Moreover, with the improvement of institutional quality, green innovation’s reduction of CO₂ emissions in 2005–2012 was weakened, whereas the reduction of CO₂ emissions by green innovation increased in 2013–2017.

The industrial structure of forestry-based can promote and drive the sustainable development of forestry. Based on the databases of Chinese Forestry Statistics, this paper applies the grey theory to calculate the correlation degree of forestry industrial structure in different years and further explores the changes of the forestry-based industrial structure in China. The results show that the scale of forestry-based industry expands unceasingly, the structure is characterized by “the secondary sector taking the lead, followed by the primary and tertiary sectors” during 2006–2015. The results of GM (1,1) prediction show that China’s forestry-based industries will secure a stable growth from 2017–2025, but it does not mean that the industrial structure will be optimized in the future. The structure is still unreasonable and incongruous, the forestry-based industry is growing fast but not well. This may imply that the optimized structures of China’s forestry-based industry can promote the high quality and sustainable development of forestry and even socio-economic development. Hence, it still needs much improvement on the efficiency of synergy, and to underline the need for market regulation and state macro-control in the dynamic process of forestry-based industrial structure adjustment.

Promoting municipal solid waste (MSW) sorting is critical to advancing sustainable and low-carbon urban development. While existing research often focuses separately on external policy tools or internal behavioral drivers, limited attention has been given to their joint effects within an integrated framework. This study addresses this gap by analyzing micro-survey data from 1983 residents across 34 prefecture-level and above cities in China, using a bivariate probit model to examine how policy tools and policy perception—both independently and interactively—shape residents’ active and passive compliance with MSW sorting policies. The findings reveal five key insights. First, the adoption and spatial distribution of policy tools are uneven: environment-type tools dominate, supply-type tools are moderately deployed, and demand-type tools are underutilized. Second, both policy tools and policy perception significantly promote compliance behaviors, with policy cognition exerting the strongest effect. Third, differential effects are observed—policy cognition primarily drives active compliance, whereas policy acceptance more strongly predicts passive compliance. Fourth, synergistic effects emerge when supply-type tools are combined with environment-type or demand-type tools. Finally, policy perception not only directly enhances compliance but also moderates the effectiveness of policy tools, with notable heterogeneity among residents with higher cognitive or emotional alignment. These findings contribute to a deeper understanding of compliance mechanisms and offer practical implications for designing perception-sensitive and regionally adaptive MSW governance strategies.

Promoting the transformation of green consumption has emerged as a critical pathway to address ecological constraints. However, existing research exhibits significant discrepancies in understanding the relationship between green attributes and purchase intention and lacks a deep unpacking of the underlying individual psychological mechanisms. Employing three situational experiments, this study integrates the chain effects of green attribute centrality (GAC), environmental concern (EC), and green trust (GT) to systematically explore the formation mechanism of consumers’ green purchase decisions. Results show three key findings: (1) When consumers exhibit high EC, GAC enhances their green purchase intention (GPI) more effectively; however, when EC is low, GAC demonstrates no significant differential impact on GPI. (2) The interaction between GAC and EC influences GPI via green perceived value (GPV) (i.e., this interaction effect is mediated by GPV). (3) GT further moderates these relationships: under high GT conditions, consumers with high EC show a stronger preference for high-centrality green products; conversely, under low GT conditions, such consumers exhibit a greater preference for low-centrality green products. This study provides a novel theoretical explanation and practical pathway for bridging the “attitude-behavior gap” in green consumption. It not only deepens the understanding of the mechanisms underlying green consumption decision-making but also offers precise references for enterprises to implement differentiated green marketing strategies and for policymakers to guide public green consumption.