Hu-Ching Huang

Seasonal variation of atmospheric polycyclic aromatic hydrocarbons along the Kaohsiung coast

Thirty-three air samples were collected by high-volume samplers from May 2007 to June 2008 in the coastal area of southwest Taiwan and analyzed for total suspended particulates (TSP) and polycyclic aromatic hydrocarbons (PAHs). Concentrations of TSP and total PAHs ranged from 40.4 to 251 μg m(-3) and 1.86-56.4 ng m(-3), respectively. Except for joss paper burning during the religious celebration of Ghost Month, which resulted in the highest concentration of PAHs in the summer of 2007, a seasonal variation in total PAH concentration was observed over this study period, with the highest concentrations in winter and the lowest in summer. Because of the geographical and climatic characteristics of the sampling site, monsoon activities modulate the seasonal variations of PAHs. Diagnostic ratios showed that PAHs in the atmosphere of the Kaohsiung coastal area arose predominantly from vehicle emissions (mainly from diesel exhaust), joss paper burning, and coal/wood combustion. The results of hierarchical cluster analysis (HCA) and principal component analysis (PCA) indicated that the sampling days could be divided into three groups and that the major source identification of PAHs was the same as the identification by diagnostic ratios. In addition, the results of HCA and PCA suggest that the samples collected with a prevailing northerly or northeasterly wind direction contain both local emissions and those from neighboring sources. On the other hand, the cases related to westerly or northwesterly winds indicated that local emission was the major source for the sampling site.

Inter-comparison of Seasonal Variation, Chemical Characteristics, and Source Identification of Atmospheric Fine Particles on Both Sides of the Taiwan Strait

The spatiotemporal distribution and chemical composition of atmospheric fine particles in areas around the Taiwan Strait were firstly investigated. Fine particles (PM2.5) were simultaneously collected at two sites on the west-side, one site at an offshore island, and three sites on the east-side of the Taiwan Strait in 2013–2014. Field sampling results indicated that the average PM2.5 concentrations at the west-side sampling sites were generally higher than those at the east-side sampling sites. In terms of chemical composition, the most abundant water-soluble ionic species of PM2.5 were SO42−, NO3−, and NH4+, while natural crustal elements dominated the metallic content of PM2.5, and the most abundant anthropogenic metals of PM2.5 were Pb, Ni and Zn. Moreover, high OC/EC ratios of PM2.5 were commonly observed at the west-side sampling sites, which are located at the downwind of major stationary sources. Results from CMB receptor modeling showed that the major sources of PM2.5 were anthropogenic sources and secondary aerosols at the both sides, and natural sources dominated PM2.5 at the offshore site. A consistent decrease of secondary sulfate and nitrate contribution to PM2.5 suggested the transportation of aged particles from the west-side to the east-side of the Taiwan Strait.

A new grid-scale model simulating the spatiotemporal distribution of PM2.5-PAHs for exposure assessment.

Exposure to polycyclic aromatic hydrocarbons (PAHs) associated with ambient air particulate matter (PM) poses significant health concerns. Several modeling approaches have been developed for simulating ambient PAHs, but no hourly intra-urban spatial data are currently available. The aim of this study is to develop a new modeling strategy in simulating, on an hourly basis, grid-scale PM2.5-PAH levels. PM and PAHs were collected over a one-year time frame through an established air quality monitoring network within a metropolitan area of Taiwan. Multivariate linear regression models, in combination with correlation analysis and PAH source identification by principal component analysis (PCA), were performed to simulate hourly grid-scale PM2.5-PAH concentrations, taking criteria pollutants and meteorological variables selected as possible predictors. The simulated levels of 72-h personal exposure were found to be significantly (R=0.729**, p<0.01) correlated with those analyzed from portable personal monitors. A geographic information system (GIS) was used to visualize spatially distributed PM2.5-PAH concentrations of the modeling results. This new grid-scale modeling strategy, incorporating the output of simulated data by GIS, provides a useful and versatile tool in personal exposure analysis and in the health risk assessment of air pollution.

A new conceptual model for quantifying transboundary contribution of atmospheric pollutants in the East Asian Pacific rim region.

Transboundary transport of air pollution is a serious environmental concern as pollutant affects both human health and the environment. Many numerical approaches have been utilized to quantify the amounts of pollutants transported to receptor regions, based on emission inventories from possible source regions. However, sparse temporal-spatial observational data and uncertainty in emission inventories might make the transboundary transport contribution difficult to estimate. This study presents a conceptual quantitative approach that uses transport pathway classification in combination with curve fitting models to simulate an air pollutant concentration baseline for pollution background concentrations. This approach is used to investigate the transboundary transport contribution of atmospheric pollutants to a metropolitan area in the East Asian Pacific rim region. Trajectory analysis categorized pollution sources for the study area into three regions: East Asia, Southeast Asia, and Taiwan cities. The occurrence frequency and transboundary contribution results suggest the predominant source region is the East Asian continent. This study also presents an application to evaluate heavy pollution cases for health concerns. This new baseline construction model provides a useful tool for the study of the contribution of transboundary pollution delivered to receptors, especially for areas deficient in emission inventories and regulatory monitoring data for harmful air pollutants.

Use of a numerical simulation approach to improve the estimation of air-water exchange fluxes of polycyclic aromatic hydrocarbons in a coastal zone

The air-water exchange is important for determining the transport, fate, and chemical loading of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere and in aquatic systems. Investigations of PAH air-water exchange are mostly based on observational data obtained using complicated field sampling processes. This study proposes a new approach to improve the estimation of long-term PAH air-water exchange fluxes by using a multivariate regression model to simulate hourly gaseous PAH concentrations. Model performance analysis and the benefits from this approach indicate its effectiveness at improving the flux estimations and at decreasing the field sampling difficulty. The proposed GIS mapping approach is useful for box model establishment and is tested for visualization of the spatiotemporal variations of air-water exchange fluxes in a coastal zone. The air-water exchange fluxes illustrated by contour maps suggest that the atmospheric PAHs might have greater impacts on offshore sites than on the coastal area in this study.