A systematic analysis of the factors influencing the pollutant removal efficiency in constructed wetlands (CWs) through meta-analysis is crucial for effective CW design and evaluation. Previous meta-analyses have consistently identified design and operational variables as the dominant factors, and the impacts of climate conditions have often been considered relatively low. In this study, we revisit the drivers of CW performance by introducing the aridity index (AI) as a new indicator of climate conditions in the meta-analysis. The analysis is based on 139 cases across China, and the results reveal that the pollutant removal efficiency of CWs in China is primarily influenced by AI, hydraulic retention time (HRT), and wetland area, alongside other factors with relatively low impacts. The removal rates of COD, NH4+-N, TN, and TP were all significantly higher in arid and semi-arid regions than in dry sub-humid and humid regions. Multiple regression analysis identifies AI, HRT, and wetland area as the most significant factors affecting CW pollutant removal efficiencies. Further structural equation modeling reveals that aridity has the greatest impact on individual and paired pollutant removals, followed by wetland area, HRT, temperature, and precipitation. These findings provide new insights into the impact of climate variables on CW pollutant removal, offering valuable guidance for the design and operation of CW, an increasingly critical environmental infrastructure for advancing multiple sustainable development goals.