Atmospheric pollution is associated with microbial community stability and functional diversity in river ecosystems.

Air pollution, which poses a global threat to human and ecosystem health, has been extensively monitored by governments and researchers worldwide. However, the effects of air pollution on river ecosystems, particularly riverine microorganisms, have received limited attention. Here, we present the first national-scale investigation (105 rivers across China) to examine how spatial variation in atmospheric pollutants is associated with riverine microbial community structure and metabolic functions. We propose an air pollution index (API) as a composite indicator for multiple air pollutants and demonstrate that higher air pollution levels are associated with altered carbon (C) pools and C-nitrogen (N) stoichiometry in river water. Along the air pollution gradient, we observed lower microbial alpha diversity, polarization of ecological strategies and more fragmented co-occurrence networks, which co-occurred with suppressed C and N cycling in a pattern we term an "ecological efficiency trap". Using machine-learning models and SHAP-GAM analyses, we identified pollutant concentration thresholds at which the marginal associations with microbial functions changed from positive to negative (e.g., ∼50 μg/m3 for PM2.5). On the basis of our findings, air pollution can be viewed as a cross-media stressor, highlighting its importance as an overlooked dimension of riverine microbial risk and supporting the integration of air-quality controls into strategies for safeguarding microbial diversity and biogeochemical functions in inland waters.