Research Areas
Research Areas
Effects of Anthropogenic Pollutants on Biogenic Organic Aerosol Formation
Biogenic volatile organic compounds (BVOC, e.g., isoprene and monoterpenes) are important contributors to secondary organic aerosol (SOA) globally. However, the extent to which human activities alter SOA formation from BVOC in the atmosphere is largely undetermined. We perform integrated laboratory chamber studies and field measurements to investigate the influence of anthropogenic emissions on biogenic SOA formation using a suite of instruments including advanced mass spectrometry techniques. A particular focus is on elucidating the effects of sulfate and NOx on isoprene and monoterpene SOA formation.
Aerosol Formation from Nitrate Radical Oxidation of Biogenic Volatile Organic Compounds
We perform laboratory chamber experiments and field studies to investigate SOA and organic nitrate formation and fates from nitrate radical (NO3) oxidation of BVOC. We aim to gain a deep understanding of the formation mechanisms and yields of organic nitrates, their properties, and their lifetimes with respect to further gas-phase oxidation and particle-phase reactions. Results from laboratory chamber studies provide fundamental data to evaluate the contribution of BVOC+NO3 to ambient aerosols, as well as parameters that can be used in models to predict organic nitrate formation and their impacts on NOx recycling and SOA formation.
Atmospheric Oxidation of Biomass Burning Smoke
Biomass burning is a major source of trace gases and aerosols with profound impacts on air quality. It is also a major source of brown carbon, which absorbs solar radiation and impacts climate. Biomass burning smoke contains large amounts of furan and phenolic compounds but their chemistry in the atmosphere is not well characterized. We conduct laboratory chamber experiments and field studies to investigate SOA formation from daytime and nighttime oxidation of furan and phenolic compounds emitted from biomass burning smoke, focusing on oxidation mechanisms, chemical composition, SOA and brown carbon formation, aqueous-phase processing, and aging.
Aerosol Composition, Properties, and Health Effects
Ambient PM2.5 is a complex mixture of hundreds to thousands of different chemical compounds. Despite numerous studies, it remains unclear which components or characteristics of PM2.5 best account for its toxicity. Utilizing high-throughput, physiologically relevant cell models (e.g., air-blood barrier lung model, miniaturized microfluidic cell array; macrophage, epithelial, and endothelial cells), we investigate how the chemical composition and properties of aerosols drive biological and immunological responses. By combining air-liquid interface exposure systems, advanced imaging, and multi-omics approaches with detailed aerosol characterization, we aim to better understand how different types and components of aerosol mixtures drive cellular toxicity.
Atmospheric Science and Chemistry mEasurement NeTwork (ASCENT)
ASCENT is a comprehensive, high-time-resolution, long-term measurement network in the U.S. for characterizing aerosol chemical composition and physical properties. There are 12 measurement sites across the country, each equipped with a suite of advanced aerosol instrumentation for real-time measurements of fine aerosol chemical composition and properties. Dr. Ng serves as the Principal Investigator of ASCENT. The Ng Research Group operates the Los Angeles and Atlanta sites. More information can be found on ASCENT.
Application of Low-Cost Sensors in Indoor and Outdoor Air Quality Studies
Low (and mid)-cost air quality sensors typically cost a small fraction of research-grade instrumentation and can provide air quality measurements with high temporal and spatial resolution. We have deployed a network of low-cost sensors indoors to monitor indoor air quality, gaining insights into hourly ventilation patterns and indoor pollutant trends across different building types and seasons. Low-cost sensors are also deployed at ASCENT measurement site across the U.S. for evaluation of sensor performance under different environmental conditions and their capability for advanced pollution source apportionment studies.
Data Science for Atmospheric Research
The availability of high-time-resolution aerosol physicochemical data from long-term networks such as ASCENT, combined with satellite observations, model outputs, and low-cost sensor measurements, enables the study of aerosols across broad spatial and temporal scales. We are developing and applying advanced data analysis, large-scale analytics, and machine learning approaches to integrate and analyze multidimensional aerosol data. These approaches will allow us to identify aerosol sources, track their transformation in the atmosphere, and quantify their variability and impacts on air quality, climate, and human health across diverse geographic regions, from local to continental scales.