The relative humidity-dependent viscosity of single quasi aerosol particles and possible implications for atmospheric aerosol chemistry

Predicting Atmospheric Particle Phase State Using an Explainable Machine Learning Approach Based on Particle Rebound Measurements

The particle phase state plays a vital role in the gas-particle partitioning, multiphase reactions, ice nucleation activity, and particle growth in the atmosphere. However, the characterization of the atmospheric phase state remains challenging. Herein, based on measured aerosol chemical composition and ambient relative humidity (RH), a machine learning (ML) model with high accuracy (R2 = 0.952) and robustness (RMSE = 0.078) was developed to predict the particle rebound fraction, f, which is an indicator of the particle phase state. Using this ML model, the f of particles in the urban atmosphere was predicted based on seasonal average aerosol chemical composition and RH. Regardless of seasons, aerosols remain in the liquid state of mid-high latitude cities in the northern hemisphere and in the semisolid state over semiarid regions. In the East Asian megacities, the particles remain in the liquid state in spring and summer and in the semisolid state in other seasons. The effects of nitrate, which is becoming dominant in fine particles in several urban areas, on the particle phase state were evaluated. More nitrate led the particles to remain in the liquid state at an even lower RH. This study proposed a new approach to predict the particle phase state in the atmosphere based on RH and aerosol chemical composition.

Liquid-Liquid Phase Separation in Single Suspended Aerosol Microdroplets

Liquid-liquid phase separation (LLPS) is ubiquitous in ambient aerosols. This specific morphology exerts substantial impacts on the physicochemical properties and atmospheric processes of aerosols, particularly on the gas-particle mass transfer, the interfacial heterogeneous reaction, and the surface albedo. Although there are many studies on the LLPS of aerosols, a clear picture of LLPS in individual aerosols is scarce due to the experimental difficulties of trapping a single particle and mimicking the suspended state of real aerosols. Here, we investigate the phase separation in individual contactless microdroplets by a self-constructed laser tweezer/Raman spectroscopy system. The dynamic transformation of the morphology of optically trapped droplets over the course of humidity cycles is detected by the time-resolved cavity-enhanced Raman spectra. The impacts of pH and inorganic components on LLPS in aerosols are discussed. The results show that the increasing acidity can enhance the miscibility between the hydrophilic and hydrophobic phases and decrease the separation relative humidity of aerosols. Moreover, the inorganic components also have various impacts on the aerosol phase state, whose influence depends on their different salting-out capabilities. It brings possible implications on the morphology of actual atmospheric particles, particularly for those dominated by internal mixtures of inorganic and organic components.