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Industrialization and increased energy use are leading to a greater influence of environmental and climate challenges on human existence and progress. China's emissions in 2023 totaled 12.6 gigatons, representing 35% of global emissions, establishing it as the top carbon emitter globally. Combined with China's industrial structure, it is essential to investigate carbon reduction in the building sector due to its significant contribution to carbon emissions. This study introduces a third-party organization into the relationship between stakeholders, based on traditional government regulation. It constructs a three-party dynamic evolution model involving the government, environmental protection organization, and construction enterprise. The study analyzes the evolution process of the three-party strategy selection using evolutionary game theory. We analyze the elements influencing decision-making for the three parties through simulation analysis and provide appropriate recommendations. The study's findings indicate that low-carbon construction in China's construction sector is an intricate system involving several stakeholders, each guided by their own interests when determining their behavioral methods. Government penalties and financial subsidies can influence construction enterprises to adopt low-carbon production practices to some degree, but excessive rewards and punishments may not support system stability. [ABSTRACT FROM AUTHOR]

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

In the pursuit of carbon neutrality, state-owned forests are prime candidates for carbon offset projects due to their unique tenure and management characteristics. Employing methodologies endorsed by the International Panel on Climate Change and logistic growth curves, this study assesses the carbon stocks and sequestration potential of established state-owned plantation forests across 31 Chinese provinces from 2023 to 2060, encompassing seven forestry industry groups. This study projects that by 2060, these forests will amass a carbon stock of 558.25 MtC, with the highest stock in Northeast China (122.09 MtC) and the lowest in Northwest China (32.27 MtC), notably showing the highest growth rate at 91.15%. Over the forecast period, they are expected to accumulate a carbon sink of 637.07 MtCO2e, translating to an average annual carbon sink of 17.22 MtCO2e and an average annual carbon sink per unit of 1.41 tons of CO2 per hectare per year. Additionally, state-owned forests have the potential to offset approximately 0.15%–0.17% of annual carbon emissions, aligning with international climate goals. However, it is essential to note that the conversion of these carbon sinks into tradable carbon credits is subject to specific methodology requirements. Therefore, the future development of carbon offset projects in China's state-owned forests should consider the advancement of carbon market mechanisms, including the Chinese Certified Emission Reduction and the introduction of a carbon inclusion mechanism and natural forest methodology, to fully realize their potential contributions to carbon neutrality. In summary, these findings offer valuable insights for shaping the future of carbon offset initiatives within China's state-owned forests. [ABSTRACT FROM AUTHOR]