Anthropogenic modulation of ice-nucleating particles over the Yellow and East China Seas: Shipboard observations and...

To address the scarcity of observational data on atmospheric ice-nucleating particles (INPs) over the mixed marine-continental environments of East Asia, shipboard measurements were conducted over the Yellow Sea (YS) and East China Sea (ECS) in April 2022. Aerosol samples were collected using an electrostatic collector and subsequently activated in a water vapor diffusion cloud chamber. To characterize their physicochemical properties, a subset of selected samples underwent single-particle analysis via a scanning electron microscope equipped with an energy-dispersive spectrometer (SEM-EDS). Measured INP concentrations ranged from below the limit of detection (LOD, ∼0.17 L^-1) to 3.9 L^-1 at activation temperatures between -17 and -26 °C and relative humidity with respect to water (RH_w) of 95% to 101%, with the YS generally exhibiting higher levels than the ECS. Additionally, cold front precipitation was associated with a transient depletion in atmospheric INP concentrations. INP number concentrations exhibited a statistically significant positive correlation with 0.55-0.80 μm aerosol particles under specific thermodynamic conditions (-23 °C, 101% RH_w; p < 0.05). Furthermore, microscopic analysis of a selected subset revealed that dust, dust-sulfate mixture, carbonaceous particles, and sea salt can serve as INPs in this region. Backward trajectory analysis indicated that YS air masses were primarily influenced by terrestrial sources, including northern Chinese inland cities, the Yangtze River Delta, and the Korean Peninsula. In contrast, ECS samples were mainly influenced by adjacent marine regions, such as the Pacific Ocean and the Sea of Japan. Importantly, this study highlights how anthropogenic pollution (e.g., sulfates) potentially modulates the ice-nucleating activity of natural dust within complex marine-continental intersection zones. These findings provide valuable insights for improving the parameterization of cloud microphysics in regional climate models.