A field-based and engineering-linked framework for assessing carbon sequestration potential in small-scale abandoned mine restoration.

Against the backdrop of intensifying global warming, carbon accounting serves as a crucial step in controlling greenhouse gas emissions and slowing down climate deterioration. Ecological restoration of abandoned mines can generate significant carbon benefits. Currently, however, the lack of a practical framework for quantifying the carbon gains of mine ecosystems leads to underestimation in carbon accounting and an undervaluation of restoration project benefits. Remote sensing data are often applied to large-scale restoration area assessments, but this method may involve considerable uncertainty when applied to small-scale mines with substantial carbon sequestration potential. This study adopts a plot-based field measurement approach and combines major restoration measures to estimate the increase in carbon storage in aboveground and belowground carbon pools across three land use types: forest, shrubland, and grassland. Applying the framework developed in this study to a 99-ha mine ecological restoration site in Shaoguan City, Guangdong Province, China, the estimated carbon sequestration potential under the baseline restoration scenario was approximately 104,760 Mg C, with an uncertainty range of 72,507-124,884 Mg C. The pathway-level Monte Carlo simulation produced a median estimate of 101,555 Mg C and a 95% uncertainty interval of 79,367-119,395 Mg C. Among this, over 80% of the carbon sink is contributed by tree growth, while the restoration of organic matter content and soil fertility through land rehabilitation forms the foundation for tree growth and carbon accumulation. Uncertainty and sensitivity analyses confirm that vegetation parameters dominate estimation uncertainty. The methodology provides a practical quantitative basis for enhancing carbon sequestration efficiency in small-scale abandoned mine restoration under humid and subhumid climates, and supports the refinement of carbon assessment systems and environmental management decisions.