Abstract: During wastewater treatment in surface-flow constructed wetlands (SFCWs), greenhouse gases (GHGs) are simultaneously produced and emitted. Achieving a balance between pollution reduction and carbon mitigation has therefore attracted increasing attention in the context of global climate change. This study systematically reviews the effects of key factors—including plant characteristics, temperature, hydraulic retention time (HRT), and carbon-to-nitrogen ratio (C/N)—on nitrogen and phosphorus removal as well as GHGs (CO₂, CH₄ and N₂O) emissions in SFCWs. It further summarizes the metabolic pathways and associated functional genes of GHGs, and proposes synergistic optimization strategies for pollution reduction and carbon mitigation. The results indicate that key factors, including plant characteristics, temperature, HRT, and C/N ratio, jointly regulate the redox environment, carbon availability, and microbial activity and metabolic processes in SFCWs, thereby influencing nitrogen and phosphorus removal efficiency as well as GHG production and emissions. CO₂ in SFCWs is primarily generated through organic matter decomposition and microbial respiration, while its removal is mainly achieved via fixation through plant photosynthesis. CH₄ is predominantly produced during anaerobic decomposition of organic matter, and its removal mainly occurs through aerobic oxidation. N₂O is mainly generated during nitrification and denitrification processes, and its removal largely depends on further reduction to N₂ via denitrification. To achieve synergistic optimization of nitrogen and phosphorus removal and GHG mitigation in SFCWs, strategies such as optimized vegetation configuration and management, regulation of C/N ratio and hydraulic conditions, and artificial aeration are proposed. Future research should focus on integrating multi-omics approaches to elucidate microbial processes and mechanisms, conducting life cycle assessment for comprehensive quantification of system-level carbon benefits, and developing data-driven modeling for intelligent simulation and optimization. These efforts will support the synergistic enhancement of pollution reduction and carbon mitigation, and thereby improve the operation and regulation of SFCWs.