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Explores carbon storage outcomes in urban agglomerations, indicating implications for climate solutions.
Research on land-use spatial pattern distributions and the prediction of carbon storage (CS) in urban agglomerations requires further improvement. Using the Chengdu–Chongqing region as an example, we employed the PLUS and InVEST models to explore the spatial and temporal evolution characteristics of land use and CS under SSP126, SSP245, SSP585, and historical scenarios. Our findings suggest that built-up land expanded cropland largely during 2005–2020, greatly contributing to CS losses. However, the transition from grassland to forest increased historical carbon storage, forming a spatial character with low values in the middle and clustered high values. The hot spots of CS were mainly distributed in forests, whereas the cold spots were built-up land and cropland. In future simulations, CS was the highest and concentrated under the SSP126 scenario, among which forests increased the fastest, reaching 11.97%. Therefore, enhancing ecological restoration is an important nature-based solution for climate change mitigation and adaptation, particularly in urban agglomerations.
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An et al. (2026) studied this question.
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