At the COP28 UN climate change conference, pivotal initiatives spotlighted the potential of digital financial inclusion (DFI) in mitigating carbon emissions. However, the impact of DFI on CO₂ emissions and its underlying mechanisms remain insufficiently explored. Leveraging county-level panel datasets, we employ a spatiotemporal econometric model to examine the spatially uneven effects of DFI on CO₂ emissions, while controlling for diverse natural and socioeconomic factors. Results show a significant mitigation effect of DFI on CO₂ emissions, which is consistent across various model specifications. Specifically, a 0.1-unit increase in DFI is associated with an approximate 41% reduction in CO₂ emissions, with 2.1% attributable to direct effects and 38.9% resulting from indirect or spatial spillover effects. Furthermore, we identify substantial heterogeneities in the effects of DFI across geography and developmental stages of DFI, highlighting the importance of context-specific dynamics. Key mediators in the DFI – CO₂ emissions link include economic growth, industrial restructuring, and progress in environmental technology. These findings provide valuable insights for the design of financial instruments to advance sustainable development goals and combat climate change.

With the recent increase in studies on spatial heterogeneity, geographically weighted (GW) models have become an essential set of local techniques, attracting a wide range of users from different domains. In this study, we demonstrate a newly developed standalone GW software, GWmodelS using a community-level house price data set for Wuhan, China. In detail, a number of fundamental GW models are illustrated, including GW descriptive statistics, basic and multiscale GW regression, and GW principle component analysis. Additionally, functionality in spatial data management and batch mapping are presented as essential supplementary activities for GW modeling. The software provides significant advantages in terms of a user-friendly graphical user interface, operational efficiency, and accessibility, which facilitate its usage for users from a wide range of domains.