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.

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.

Source identification and characterization of atmospheric polycyclic aromatic hydrocarbons along the southwestern coastal area of Taiwan - with a GMDH approach.

Air samples of polycyclic aromatic hydrocarbons (PAHs) were collected from May 2008 to April 2009 in the Kaohsiung coastal area of Taiwan to establish a dataset. Sample analysis suggested that PAH composition (dominated by 3-ring PAHs) and seasonal patterns (high concentration in winter and low concentration in summer) are nearly identical to those previously reported (Lai et al., 2011), except for a case of road construction during the sample period. The predominant sources of PAHs were identified by isomer ratio, HCA and PCA analyses as vehicle emissions and coal/wood combustion. According to the results of parameters selection via the Group Method of Data Handling (GMDH), the variations in gaseous PAHs and particulate PAHs were related mainly to meteorological conditions and to routine monitoring of air pollutant concentrations, respectively. A comparison of model prediction accuracy between particulate and gaseous PAHs suggests better prediction for particulate PAHs than gaseous PAHs, due to dramatic variation in meteorological conditions which results in higher prediction uncertainty for gaseous PAHs. Model predictions of PAH concentrations showed satisfactory agreement with measured data, except for specific incidents, such as joss paper burning events. The results of this study suggest that the GMDH model may be applied to PAH concentration prediction for the study area and may be applicable for other countries based on routine monitoring of air pollutant concentrations and meteorological conditions.

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.