Preprints
https://doi.org/10.5194/egusphere-2026-1510
https://doi.org/10.5194/egusphere-2026-1510
06 May 2026
 | 06 May 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Phase-State and Humidity Trend Controls on Wintertime Nitrate Aerosol Formation

Qihua Hu and Hwajin Kim

Abstract. Particulate nitrate is a dominant component of winter haze in East Asian megacities, yet its real-world formation mechanisms remain incompletely understood. We integrate high time-resolution aerosol composition measurements, explainable machine learning (ML), and conventional analyses to disentangle key drivers of wintertime nitrate production. While NO₂ availability is the primary control, our results reveal critical but underrepresented processes: (1) persistence of nitrate formation during late-morning relative humidity (RH) decline, sustained by metastable semi-liquid particles with retained liquid water that facilitate continuous gas-to-particle partitioning of photochemically produced HNO₃, and (2) temperature threshold effects, where subfreezing conditions suppress further nitrate formation primarily due to thermodynamic precursor saturation, compounded by potential diffusion limitations in highly viscous or solid phases. Contrary to common assumptions, boundary layer height contributes minimally to peak nitrate events. These findings demonstrate the need for air quality models to incorporate RH trends, aerosol phase transitions, and temperature-dependent reactivity to accurately predict nitrate episodes. The mechanistic framework presented here is transferable to other urban environments affected by secondary inorganic aerosols and offers new leverage points for mitigation strategies.

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Qihua Hu and Hwajin Kim

Status: open (until 17 Jun 2026)

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Qihua Hu and Hwajin Kim
Qihua Hu and Hwajin Kim
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Short summary
To understand why severe winter haze persists, we analyzed Seoul air quality using real-time measurements, machine learning, and thermodynamic models. We found that morning pollution spikes occur because tiny particles trap water even as the air dries, acting like sponges to absorb newly formed polluting gases. We also discovered subfreezing temperatures halt this particle growth. Incorporating these physical behaviors into air quality models will improve severe pollution forecasts.
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