Variation in Day-of-Week and Seasonal Concentrations of Atmospheric PM2.5-Bound Metals and Associated Health Risks in Bangkok, Thailand.

While effective analytical techniques to promote the long-term intensive monitoring campaign of particulate heavy metals have been well established, efforts to interpret these toxic chemical contents into policy are lagging behind. In order to ameliorate the interpretation of evidence into policies, environmental scientists and public health practitioners need innovative methods to emphasize messages concerning adverse health effects to state and local policymakers. In this study, three different types of health risk assessment models categorized by exposure pathways. Namely, ingestion, dermal contact, and inhalation were quantitatively evaluated using intensive monitoring data of 51 PM2.5-bound metals that were collected on three consecutive days, from 17 November 2010 to 30 April 2011 in the heart of Bangkok. Although different exposure pathways possess different magnitudes of risk for each PM2.5-bound metal, it can be concluded that ingestion of dust causes more extensive risk to residents compared with inhalation and dermal contact. The investigation of enrichment factors reveals the overwhelming influences of vehicular exhausts on 44 selected metal concentrations in Bangkok. These findings are in agreement with previous studies that highlight the role of public transportation and urban planning in air pollution control.

Effects of day-of-week trends and vehicle types on PM2.5-bounded carbonaceous compositions.

Carbonaceous compositions of PM2.5 were measured in the heart of Bangkok from 17th November 2010 to 19th January 2012, and a data set of 94 samples was constructed. Effects of day-of-week trends and vehicle types on PM2.5-bound TC, OC, and EC were carefully investigated. In this study, OC was the most important contributor to the total PM2.5 mass concentration. The average PM2.5-bound OC content measured at CHAOS (18.8 ± 9.18 µg m(-3)) was approximately 11 times higher than at Chaumont, Switzerland (1.7 µg m(-3)), but approximately five times lower than at Xi'an, China (93.0 µg m(-3)). The application of diagnostic binary ratios of OC/EC and estimations of secondary organic carbon (SOC) coupled with autocorrelation plots (Box and Jenkins) highlight the enhanced impacts of traffic emissions, especially from diesel vehicles, on PM2.5-bound carbonaceous compositions on weekdays relative to weekends. Hierarchical cluster analysis (HCA) coupled with principal component analysis (PCA) underline the importance of diesel emissions as the primary contributors of carbonaceous aerosols, particularly during weekdays.

Parameters influencing sulfur speciation in environmental samples using sulfur k-edge x-ray absorption near-edge structure.

This paper aims to enhance the credibility of applying the sulfur K-edge XANES spectroscopy as an innovative "fingerprint" for characterizing environmental samples. The sensitivities of sulfur K-edge XANES spectra of ten sulfur compound standards detected by two different detectors, namely, Lytle detector (LyD) and Germanium detector (GeD), were studied and compared. Further investigation on "self-absorption" effect revealed that the maximum sensitivities of sulfur K-edge XANES spectra were achieved when diluting sulfur compound standards with boron nitride (BN) at the mixing ratio of 0.1%. The "particle-size" effect on sulfur K-edge XANES spectrum sensitivities was examined by comparing signal-to-noise ratios of total suspended particles (TSP) and particulate matter of less than 10 millionths of a meter (PM(10)) collected at three major cities of Thailand. The analytical results have demonstrated that the signal-to-noise ratios of sulfur K-edge XANES spectra were positively correlated with sulfate content in aerosols and negatively connected with particle sizes. The combination of hierarchical cluster analysis (HCA) and principal component analysis (PCA) has proved that sulfur K-edge XANES spectrum can be used to characterize German terrestrial soils and Andaman coastal sediments. In addition, this study highlighted the capability of sulfur K-edge XANES spectra as an innovative "fingerprint" to distinguish tsunami backwash deposits (TBD) from typical marine sediments (TMS).