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Secondary inorganic aerosols (SIA), comprising of sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+), are major constituents of fine particle (PM2.5, particle matter with aerodynamic diameter smaller than 2.5 μm). They play important roles in PM-related adverse impacts on human health, acid deposition, visibility degradation and climate system. Past studies on SIA in Hong Kong (HK) or the Pearl River Delta (PRD) mostly rely on filter-based measurements which typically need 12 h or longer to collect enough material for off-line analysis. Work in this thesis focuses on half-hourly or hourly measurements of PM2.5 SIA in two locations in HK using a continuous system, PILS (Particle-into-Liquid System) coupled to two ion chromatographs. The high-resolution data sets allow the examination of SIA temporal dynamics in the scale of hours that the filter-based approach is incapable of providing. In addition, the PILS measurements of semi-volatile SIA species, i.e., NO3- and NH4+, are more reliable as the filter-based sampling is subjected to various sampling artifacts due to gas-particle interactions and/or evaporation of semi-volatile species. The high-time resolution PM2.5 ionic chemical composition data have been explored and the main findings are summarized below: (1) Impacts of local emissions, regional transports and their interactions on chemical composition and concentrations of PM2.5 SIA and other ionic species were investigated at the Hong Kong University of Science and Technology (HKUST), a receptor site, under three synoptic conditions. It is found air masses that passed the heavy urban areas located on the HK Island most likely attributed a night time NO3- episode in fall. Low temperature and high relative humidity (RH) that was associated with an approaching cold front efficiently shifted gaseous phase HNO3 to aerosol phase. Regional transport from north PRD was likely responsible for elevated NH4+ and SO42- levels in a SO42- episode in fall. During a cold fro

Atmospheric aerosols are a complex mixture of inorganic and organic compounds from different sources. They exert a variety of effects on our macro- and micro-environments, including those to the global climate, regional visibility and human health. These effects are not very well understood because of the formation processes of atmospheric aerosols, especially organic aerosols, remain poorly constrained. For better prediction of organic aerosol formation using modeling approaches, studies of the formation processes of organic aerosols in mechanistic details are in great need. In this study, we investigated two chemical processes that can lead to formation of secondary organic aerosols (SOA), which are defined as organic aerosols involving chemical reactions after emissions as volatile organic compounds (VOCs). The first process is the gas-phase oxidation of biogenic VOCs. A sesquiterpene β-caryophyllene, which is one of the most abundant sesquiterpenes emitted by plants, was used as a model compound. The gas-phase oxidation was conducted in a continuous-flow chamber that allows steady-state equilibrium of the gas-phase oxidation and gas-to-particle partitioning, forming SOA. Particles were characterized by an ultra performance liquid chromatograph-time of flight mass spectrometer (UPLC-ToF-MS). Results show that highly oxygenated compounds are formed under ozone-rich conditions. Multi-functional products with 3 to 5 oxygen atoms, with one up to 7, were identified. In contrast to products from previous studies that focused on first-generation reactions, these second-generation products are less volatile and are predicted to be predominantly in the particle phase. The second process is the particle-phase acid-catalyzed reactions of semi-volatile organic compounds (SVOCs). An aliphatic aldehyde (octanal) and biogenic alkenes (limonene and terpineol) were used as model compounds to study the sulfuric acid-catalyzed reactions of two types of functional groups (C=O and C=

Air pollution in Hong Kong (HK) causes problems in visibility and public health, which are worsening over past few years. Out of particulate matters (PM) inhalable into respiratory system, 30% is contributed by sulfate (SO4), 40% by organic carbon (OC), and 10% by elemental carbon (EC). A meso-scale numerical modeling system CMAQ is devised to simulate the air quality in January (winter), April (spring), July (summer) and October (autumn) 2004, driven by meteorology simulated by MM5 and emission sources in China including Hong Kong. Observational and measurement data from Hong Kong Environmental Protection Department Air Quality network are compared with the model results. With respect to pollutant concentration level, model-observation agreement is reasonably well, especially in PM species sulfate, organic carbon (OC) and elemental carbon (EC); and gaseous species SO2, NOx and ozone. In terms of PM composition, the model agrees with the measurement in fractions of sulfate, OC and EC. Higher PM level in autumn and winter is associated with northeasterly winds due to continental outflow. To further investigate emission sources contributing to HK, a source apportioning method called Tagged Species Source Apportionment (TSSA) algorithm is applied to study contributions to level of SO4, SO2 and EC in HK. It is found that while sources beyond PRD are observed in entire HK during January and October 2004, emitting sectors are different among western HK, downtown area, and the east countryside. Specifically, power plants and vehicles from HK and Shenzhen affect the western new towns, while power plants, vehicles and ships within HK determine the downtown pollutants’ level. The countryside is mainly influenced by sources beyond PRD.

Air pollution in Hong Kong (HK) causes problems in visibility and public health, which are worsening over past few years. Out of particulate matters (PM) inhalable into respiratory system, 30% is contributed by sulfate (SO4), 40% by organic carbon (OC), and 10% by elemental carbon (EC). A meso-scale numerical modeling system CMAQ is devised to simulate the air quality in January (winter), April (spring), July (summer) and October (autumn) 2004, driven by meteorology simulated by MM5 and emission sources in China including Hong Kong. Observational and measurement data from Hong Kong Environmental Protection Department Air Quality network are compared with the model results. With respect to pollutant concentration level, model-observation agreement is reasonably well, especially in PM species sulfate, organic carbon (OC) and elemental carbon (EC); and gaseous species SO2, NOx and ozone. In terms of PM composition, the model agrees with the measurement in fractions of sulfate, OC and EC. Higher PM level in autumn and winter is associated with northeasterly winds due to continental outflow. To further investigate emission sources contributing to HK, a source apportioning method called Tagged Species Source Apportionment (TSSA) algorithm is applied to study contributions to level of SO4, SO2 and EC in HK. It is found that while sources beyond PRD are observed in entire HK during January and October 2004, emitting sectors are different among western HK, downtown area, and the east countryside. Specifically, power plants and vehicles from HK and Shenzhen affect the western new towns, while power plants, vehicles and ships within HK determine the downtown pollutants’ level. The countryside is mainly influenced by sources beyond PRD.

Results from the receptor modeling of atmospheric aerosols, in particular, Respirable Suspended Particulates (RSP) with aerodynamic diameter less than or equal to 10 μm, or known as PM10, in Hong Kong measured by the Environmental Protection Department between 1992 and 1994 are presented. The source apportionment techniques employed in this study include correlation matrix of logarithmic transformed chemical species concentrations and wind field data to derive source-wind direction relationships and an advanced algorithm called positive matrix factorization (PMF) in receptor modeling for identification of RSP sources subject to a rigorous approach to eliminate rotation ambiguity. The Pearson correlation coefficient was used in the wind sector analysis RSP in Hong Kong. The species analyzed in this study were Al, Ca, Mg, Pb, Naplus, V, Clminus, NH4+, NO3minus, SO42minus, Brminus, Mn, Fe, Ni, Zn, EC (elemental carbon), THC (total hydrocarbon), Cd, Kplus, Ba, Cu, As, and Be. The study aimed to develop a relationship between the sources and wind characteristics using a purely statistical analysis of the particulate database. The Kolmogorov-Smirnov goodness-of-fit test shows that the 24-hour cumulative wind speed from all directions and the mass concentrations of some chemical species follow lognormal distributions. Logarithmic transformed species concentrations and 'wind speeds were used as inputs to minimize the effect of fluctuation of wind direction due to local topography under low wind speed conditions. The four sources identified by filtered matrix were marine, crustal, "non-ferrous smelters" and fuel oil burning sources. Marine aerosols were found to be predominately associated with southeastern winds. Nevertheless, they were also -xi- correlated with some localized coastal northwesterly winds. Crustal particulates were mostly locally driven such as reclamation, large-scale construction activities or soil erosion. Although found in some residential/commercial are