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Terrestrial ecosystems play a critical role in the global carbon cycle, and their carbon sequestration capacity is vital for mitigating the impacts of climate change. Changes in land use and land cover (LULC) dynamics significantly alter this capacity. This study scrutinizes the LULC evolution within the Beijing metropolitan region from 1992 to 2022, evaluating its implications for ecosystem carbon storage. It also employs the Patch-Generating Land Use Simulation (PLUS) model to simulate LULC patterns under four scenarios for 2035: an Uncontrolled Scenario (UCS), a Natural Evolution Scenario (NES), a Strict Control Scenario (SCS), and a Reforestation and Wetland Expansion Scenario (RWES). The InVEST model is concurrently used to assess and forecast ecosystem carbon storage under each scenario. Key insights from the study are as follows: (1) from 1992 to 2022, Beijing's LULC exhibited a phased developmental trajectory, marked by an expansion of urban and forested areas at the expense of agricultural land; (2) concurrently, the region's ecosystem carbon storage displayed a fluctuating trend, peaking initially before declining, with higher storage in the northwest and lower in the central urban zones; (3) by 2035, ecosystem carbon storage is projected to decrease by 1.41 Megatons under the UCS, decrease by 0.097 Megatons under the NES, increase by 1.70 Megatons under the SCS, and increase by 11.97 Megatons under the RWES; and (4) the study underscores the efficacy of policies curtailing construction land expansion in Beijing, advocating for sustained urban growth constraints and intensified afforestation initiatives. This research reveals significant changes in urban land use types and the mechanisms propelling these shifts, offering a scientific basis for comprehending LULC transformations in Beijing and their ramifications for ecosystem carbon storage. It further provides policymakers with substantial insights for the development of strategic environmental and urban planning initiatives. [ABSTRACT FROM AUTHOR]

Digital inclusive finance (DIF) is a strategic tool that fosters the green transformation of the industrial economy. Based on the data from the 11 provinces and municipalities in the Yangtze River Economic Belt of China between 2012 and 2021, This paper utilizes the Tobit, intermediary effect, and threshold effect models to empirically study the impact of DIF on the industrial land carbon emission intensity (ILCEI). This paper reaches the following conclusions: (1) The ILCEI in the region revealed a downward trend during the study period. There are substantial differences in carbon ILCEI; higher upstream and lower downstream. The average ILCEI in the lower reach provinces is 0.5829 ton/m2 during the research period, while that in the upper reach region is 1.0104 ton/m2. (2) DIF has a significantly inhibitory effect on the ILCEI; this effect has nonlinear characteristics. The impact of DIF on ILCEI exhibits a marginally diminishing trend as the industrial land economic agglomeration degree improves. (3) Regarding the transmission mechanism, the level of industrial R&D investment plays a primary intermediary role in the impact of DIF on ILCEI. (4) Concerning control variables, foreign investment dependence and trade contribute significantly to inhibiting ILCEI. Lastly, this paper proposes a series of measures to promote DIF to fully utilize the emission reduction effect. The research outcomes have substantial implications for the sustainable development of industrial land. [ABSTRACT FROM AUTHOR]