Project No: 600413

Title: Real-time measurements of chemical composition and hygroscopic behaviors of ambient aerosols in Hong Kong

PI: CHAN Chak K; CI: NG, Nga Lee (Georgia Tech)

Award: HK$656,521



Atmospheric aerosols have impacts on different scales from climate to human health. Our understanding of those impacts is impeded by the complex and dynamic features of atmospheric aerosols. Characterization of atmospheric aerosols, especially organic aerosols, on their chemical compositions and physical properties by traditional approaches are limited by either the lack of comprehensiveness or low time-resolution. Recent developments in aerosol instrumentation have provided tools for real-time characterization of atmospheric aerosols with sufficient comprehensiveness and time-resolution to capture the fast-changing characteristics of atmospheric aerosols. In the proposed study, we will investigate ambient aerosols in Hong Kong by using a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and a Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) to measure the chemical composition and aerosol hygroscopicity, respectively. Four-month of worth real-time measurements were made at the Hong Kong University of Science and Technology (HKUST) Air Q uality Supersite from 2011 to 2012, with one month in each season. Analyses of these data will be performed to understand the source and transformation of atmospheric aerosols, especially organic aerosols. Correlations between chemical characteristics of organic aerosols, such as degree of oxygenation, and aerosol hygroscopicity indicated by growth factors or growth curves as measured by HTDMA will also be explored to obtain parameterization for prediction of hygroscopic behaviors of atmospheric aerosols. Additional measurements at the same site and by the same instruments will also be conducted to obtain another dataset for seasonal trend comparisons.  Furthermore, we will confirm the hypotheses from the preliminary results of the four-month data utilizing this new dataset.