About the Speaker

Professor Ta-Chih Hsiao
Professor Ta-Chih Hsiao is a leading aerosol scientist at National Taiwan University and Joint Research Fellow at Academia Sinica. His research focuses on ultrafine particle dynamics, aerosol health effects, and advanced monitoring technologies. He pioneered machine learning approaches to decouple meteorological and anthropogenic effects on air quality, developed real-time metal aerosol monitoring systems, and identified wastewater treatment plants as critical sources of airborne antibiotic resistance genes. His work spans from fundamental nanoparticle physics to practical applications in exposure assessment and public health protection. Recently, he led Taiwan's collaboration with NASA's ASIA-AQ project, coordinating ground observations for air quality research. His academic excellence was recognized with the 2022 NTU College of Engineering Research Achievement Award and the prestigious 2016 Chiu-Sen Award from Taiwan's aerosol community. Professor Hsiao hosted the 12th Asian Aerosol Conference (AAC2022) as Technical Program Chair with 613 participants from 26 countries, and will serve as Conference Chair for ICESP2026. He is Vice President of the Taiwan Association for Aerosol Research, Editorial Board Member for Journal of Hazardous Materials Letters, and Editor of Aerosol and Air Quality Research, with extensive international advisory roles for major aerosol conferences.

Abstract
Traditional air quality standards based on PM₂.₅ and PM₁₀ mass concentrations inadequately represent health risks from ultrafine particles (UFPs, <100 nm), which dominate particle number concentrations despite minimal mass contribution. This presentation examines urban aerosol physicochemical properties through integrated measurements of particle number size distributions (PNSD), new particle formation (NPF) events, traffic emission characteristics, and health-relevant metrics.

We demonstrate that lung-deposited surface area (LDSA) provides a more relevant exposure metric than mass concentration, accounting for UFPs' high deposition efficiency and surface-to-mass ratio. Source apportionment reveals traffic emissions contribute up to 79% of LDSA in motorcycle-dominated environments, while size-segregated metal analysis identifies non-exhaust emissions as emerging health concerns. Oxidative potential (OP) measurements show strong correlations with UFP metrics, highlighting their capacity to generate reactive oxygen species. Field observations from the ASIA-AQ campaign and long-term monitoring demonstrate how photochemical aging and meteorological conditions influence UFP dynamics in subtropical regions. Using interpretable machine learning to decouple meteorological effects from anthropogenic influences, we establish frameworks for characterizing UFP temporal trends. These findings support the need for regulatory strategies incorporating LDSA and OP alongside traditional mass-based standards to address both physical and chemical dimensions of particulate health risks.