Ambient measurements and improved statistical proxies for gaseous sulfuric acid in coastal Hong Kong

Gaseous sulfuric acid (SA) is a critical precursor for atmospheric new particle formation and growth. However, its direct measurement remains challenging due to low concentration and fast dynamics. Chemical Ionization Mass Spectroscopy (CIMS) has been developed as an effective technique for SA measurement, but its availability, operational complexity, and complex calibration procedures hinder widespread and long-term observations of SA. To address this gap, proxy models have been developed to estimate SA from routinely measured parameters, but their transferability across regions remains uncertain, underscoring the need for localized improvements. In this study, SA and related parameters were measured at two coastal background sites in Hong Kong, Cape D’Aguilar Supersite in 2018 and the Hong Kong University of Science and Technology Supersite in 2022. Observed SA concentrations showed distinct diurnal patterns, peaking at midday with maxima of (8.0 ± 7.5) × 10⁶ and (4.2 ± 2.9) × 106 molecule/cm³, respectively. We evaluated a series of existing proxies based on SO2, O3, alkenes, solar radiation, and condensation sink (CS), and found limited applicability under subtropical conditions. Therefore, new statistical proxies were developed, and locally optimized nonlinear proxies slightly outperformed linear ones, and replacing CS with PM2.5 yielded comparable accuracy, greatly enhancing practicality where size-resolved particle data are unavailable. For whole-day estimation, nighttime SA formation was further investigated through box model simulations. Results revealed that regenerated OH radicals (~4–6 × 105 molecule/cm³), rather than stabilized Criegee intermediates, played a dominant role in nighttime SA production. Thus, we established new nighttime and piecewise full-day proxies that reproduced observed SA concentrations across both sites. Overall, this work advances understanding of SA dynamics in subtropical coastal environments, provides improved proxies adaptable to data-limited regions, and demonstrates their potential application for long-term monitoring and air quality modeling worldwide.