In recent years, the rise in global warming has significantly increased forest fires, affecting the environment and economy. Predicting forest fire dynamics under climate change is now a crucial research field. To address this need, this study focuses on the impact of climate change on forest fires, with a particular focus on the fire dynamics in Yunnan Province. This study utilizes the RegCM regional climate model and the Canadian Fire Weather Index (FWI) to simulate and analyze forest fire dynamics in Yunnan Province from 2019 to 2033 under three climate scenarios: RCP2.6, RCP4.5, and RCP8.5. Findings indicate climate change will increase temperatures, alter humidity and wind speed, and reduce precipitation in Yunnan, extending the fire danger period, especially under RCP8.5 scenarios. The FWI values rise across Yunnan, particularly in the west under RCP2.6 and RCP8.5. The study concludes that future carbon emissions correlate with these changes, leading to more frequent, longer, and severe forest fires. This research is vital for managing and preventing forest fires in Yunnan, a region prone to such disasters.

In the context of accelerating global transitions toward low-carbon and digitally enabled energy systems, firm-embedded new energy industry chain modernization (NEICM) has become a critical pathway for industrial upgrading. This study examines the relationship between digital–intelligent empowerment (DIE) and firm-embedded NEICM based on a panel dataset of Chinese A-share listed new energy firms from 2010 to 2024. This study develops a firm-level DIE measure based on publicly disclosed digital–intelligent transformation practices, serving as an observable proxy for firms’ disclosed efforts in applying intelligent technologies, improving information integration, and enhancing organizational coordination. It also constructs a multidimensional firm-embedded NEICM index covering efficiency, resilience, innovation, sustainability, and value creation. A two-way fixed effects model is employed to examine the relationship between DIE and NEICM, with robustness tests and instrumental variable approaches further employed to address potential endogeneity concerns. The empirical results show that DIE has a significant positive relationship with NEICM, and the findings remain robust under alternative specifications and endogeneity treatments. Further heterogeneity analysis shows that the impact of DIE on NEICM varies across firm characteristics. Specifically, the positive effect of DIE is more evident among high-tech firms and large-scale firms, while significant positive effects are observed across firms with different levels of energy intensity. Mechanism analysis indicates that DIE promotes NEICM through enhancing information transparency and alleviating financing constraints. Moreover, ESG performance strengthens the positive relationship between DIE and NEICM, highlighting the importance of corporate sustainability governance.