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Carbon emissions pose a significant challenge to sustainable development, particularly for China, which is the world's largest emerging economy and is under pressure to achieve carbon neutrality and reduce emissions amid escalating human activities. The variation in economic development levels and carbon sequestration capacities among its provinces poses a significant hurdle. However, previous research has not adequately examined this dual discrepancy from the perspective of spatial heterogeneity, resulting in a lack of differentiated management of forest carbon sinks across diverse regions. Therefore, to mitigate this discrepancy, this study presents an assessment methodology that analyzes over 100 types of natural and plantation forests using forest age and biomass expansion factors. This study presents a model that can significantly support the efforts of both China and the whole world to achieve carbon neutrality through the improved management of forest carbon sinks. This approach facilitates the assessment of carbon offsets required to meet reduction targets, the development of a provincial framework for carbon intensity and sequestration, and the exploration of their potential for trading markets. Analysis is conducted using MATLAB. Key achievements of this study include the following: (1) The collection of a comprehensive carbon stock dataset for 50 natural and 57 plantation forest types in 31 provinces from 2009 to 2018, highlighting the significant role of new forests in carbon sequestration. (2) The development of a provincial carbon status scoring system that categorizes provinces as carbon-negative, carbon-balancing, or carbon-positive based on local forest sink data and carbon credit demand. (3) The formulation of the carbon intensity–carbon sink assessment (CISA) model, which suggests that provinces with middle- to upper-middle-level economies may have a prolonged need for carbon sink credits during their peak carbon phase. Furthermore, the results show that carbon trading may benefit Guangxi and Yunnan, but may also bring opportunities and risks to Hunan and Hubei. To address regional imbalances, this study advocates tailored policies: carbon-negative and carbon-balancing provinces should enhance carbon sink management, while carbon-positive provinces must focus on energy structure transformation to achieve sustainable development goals. [ABSTRACT FROM AUTHOR]

As the largest terrestrial organic carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle, but it is easily affected by land use and climate change. The Huang-Huai-Hai Plain (HHHP) in China, which is dominated by dry farming, is experiencing rapid farmland loss and gain (farmland use transition), which may cause drastic changes in SOC storage. To clarify the effects of farmland use transition on SOC in dry farming areas, this study adopted a land use transition matrix and spatial analyst tool to explore the characteristics of farmland use transition and its effects on SOC content and stocks in the 200 cm soil layer in the HHHP from 2000 to 2020. The results showed that the farmland use transition in this area during that time period resulted in a net decrease of 16.06 × 103 km2 of farmland, of which urban built-up land and rural settlements led to a net reduction of farmland by 9.74 × 103 km2 and 6.43 × 103 km2, respectively, which was mainly affected by climate, topography, and economic factors. In addition, the farmland use transition resulted in a net increase in SOC storage of 6.13 Tg C, contributing 44.32% of the net increase. This is likely because the change in land use type led to a change in soil bulk density and soil gravel content while altering the SOC content, which in turn affected the SOC stock. This study has important implications for addressing global climate change and maintaining sustainable agricultural resources. [ABSTRACT FROM AUTHOR]