Mangroves serve as critical transitional ecosystems between land and sea. However, their large-scale possible impacts on coastal water quality have not been investigated. This study systematically examined the possible impacts of mangrove dynamics on coastal water quality in China over a 20-year period (1998–2018). Theil–Sen trend analysis and Mann-Kendall tests were employed to assess long-term trends of mangrove area and four water quality indicators: chlorophyll-a (Chl-a), colored dissolved organic matter (CDOM), particulate attenuation coefficient at 660 nm (Cp660), and seawater transparency (Secchi disk depth, SDD). Partial correlation analysis and convergent cross-mapping (CCM) techniques were applied to evaluate the relationships between mangroves and water quality parameters, while a factor detector was used to quantify the specific contribution of mangroves to water quality improvement. The results revealed the following: (1) a significant nationwide expansion of mangroves, particularly after 2005, accompanied by accelerated recovery rates; (2) notable variations in water quality indicators, with SDD and CDOM experiencing degradation, while Chl-a and Cp660 showed varying degrees of improvement; (3) statistical evidence indicating that mangrove expansion was negatively partially correlated with Chl-a concentrations, and had moderate effects on CDOM, Cp660, and SDD. These findings highlight the measurable role of mangroves in improving coastal water quality at a national scale, provide a robust scientific basis for integrated coastal zone management, and underscore the need for further investigation into the underlying mechanisms, with comprehensive consideration of the dynamic impacts of climate change and anthropogenic activities.

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.