Land

Rising greenhouse gas concentrations have exacerbated global warming, elevating the importance of land use and land cover (LULC) changes in achieving carbon neutrality. This is especially true in coastal areas, which face dual pressures from rapid urbanization and the need to protect carbon sinks. This study developed an SD-MCCA coupling framework to predict the dynamic changes in LULC in four SSP scenarios (SSP126, SSP245, SSP370, SSP585) in the coastal zone of Zhejiang Province from 2020 to 2100. Among them, the carbon storage was estimated by the InVEST model, and the dual-target optimization was carried out using the NSGA-II algorithm. Results indicated that construction land expanded significantly across all scenarios (50.3–110.2%), leading to a decline in carbon storage. However, outcomes were highly scenario-dependent; by 2100, carbon storage under the SSP126 pathway (1032.94 Mt) was notably higher than under the SSP585 pathway (1012.90 Mt). Coastal wetlands and forests emerged as major contributors to carbon storage, exhibiting high positive contribution scores, while construction land sites show significant negative correlations. Dual-target optimization achieved collaborative improvement: the optimized SSP126 scenario increased carbon storage by 1.16%, while economic benefits increased by 9.05%. The policy proposal emphasizes the priority of the SSP126 scenario, restricts the expansion of construction land, and enforces the ecological red line of wetlands and forests, guided by the phased Pareto optimal strategy.

Informal settlements are home to more than one billion people worldwide, with forecasts suggesting this number may increase to nearly three billion by 2050. Although informal settlements constitute a significant component of urbanization in the Global South, they are unsafe and unhealthy places to live, as residents are exposed to various environmental challenges, including increasing temperatures. However, relative to other climate-related hazards, heat stress in informal settlements is under-researched. This paper, therefore, aims to analyze land surface temperatures (LSTs) in informal settlements relative to those in surrounding areas. Focusing on the study areas of Masiphumelele and Dunoon in Cape Town, South Africa, the study utilized downscaled 10 m resolution satellite imagery from 2020 to 2025. The LST was derived from Landsat 8 Collection 2 Level 2 Surface Reflectance and Surface Temperature products. Four indices were also generated to further analyze the spatial distribution of LSTs: the normalized difference vegetation index, the normalized difference built-up index, the bare soil index, and the normalized difference water index. Showing that heat intensity in informal settlements is a relative phenomenon influenced by many factors, Dunoon had a lower mean LST than the surroundings, while Masiphumelele demonstrated elevated mean LST relative to the surroundings. The study provides empirical evidence of heat-related patterns to inform planning and climate adaptation strategies in informal settlements, including the equitable provision of green and blue infrastructure.

The Rimac River Basin supplies drinking water to more than ten million people in Lima, Peru, yet its hydrological regulation capacity is increasingly constrained by land degradation, with over 35% of the basin lacking vegetation cover. Nature-based solutions implemented through conservation and restoration of natural ecosystem offer a potential complement to grey infrastructure, although their basin-scale hydrological benefits remain scantily quantified. This study proposes an inverse assessment framework that uses future degraded states as hydrological benchmarks to quantify redistributed water as a proxy for the volumetric benefits that conservation or restoration could potentially provide. Degraded Andean shrubland and grasslands were identified and prioritized using the RIOS investment assessment tool, resulting in three degradation portfolios (2826; 6566; and 10,720 ha) for the 2011–2016 period. Their hydrological responses were then simulated using the SWAT model, with a focus on dry-season dynamics. The model achieved a Kling Gupta Efficiency of 46.9% and a seasonally targeted Nash–Sutcliffe efficiency of 70% during the dry season, ensuring that despite the basin anthropization, the low flow dynamics key for water security are reliably represented. Water availability indicators and flow-duration curve metrics were applied to evaluate changes in hydrological regulation. Results show that all portfolios increased dry-season streamflow relative to baseline conditions, with the largest portfolio producing a 2.39% increase, equivalent to approximately 4 hm³ during the critical June–August period. These findings indicate that degradation alters flow redistribution within the basin water cycle and suggest that conservation or restoration may reverse these effects. The intermediate and large portfolios provided the most informative benchmarks, supporting spatially explicit decision making for basin-scale water regulation.