No abstract

Daily PM10 concentrations were measured at four sampling stations located in Chiang Mai and Lamphun provinces, Thailand. The sampling scheme was conducted during June 2005 to June 2006; every 3 days for 24 h in each sampling period. The result revealed that all stations shared the same pattern, in which the PM10 (particulate matters with diameter of less than 10 microm) concentration increased at the beginning of dry season (December) and reached its peak in March before decreasing by the end of April. The maximum PM10 concentration for each sampling station was in the range of 140-182 microg/m(3) which was 1.1-1.5 times higher than the Thai ambient air quality standard of 120 microg/m(3). This distinctly high concentration of PM10 in the dry season (Dec. 05-Mar. 06) was recognized as a unique seasonal pattern for the northern part of Thailand. PM10 concentration had a medium level of negative correlation (r = -0.696 to -0.635) with the visibility data. Comparing the maximum PM10 concentration detected at each sampling station to the permitted PM10 level of the national air quality standard, the warning visibility values for the PM10 pollution-watch system were determined as 10 km for Chiang Mai Province and 5 km for Lamphun Province. From the analysis of PM10 constituents, no component exceeded the national air quality standard. The total concentrations of PM10-bond polycyclic aromatic hydrocarbons (PAHs) are calculated in terms of total toxicity equivalent concentrations (TTECs) using the toxicity equivalent factors (TEFs) method. TTECs in Chiang Mai and Lamphun ambient air was found at a level comparable to those observed in Nagasaki, Bangkok and Rome and at a lower level than those reported at Copenhagen. The annual number of lung cancer cases for Chiang Mai and Lamphun Provinces was estimated at two cases/year which was lower than the number of cases in Bangkok (27 cases/year). The principal component analysis/absolute principal component scores (PCA/APCS) model and multiple regression analysis were applied to the PM10 and its constituents data. The results pointed to the vegetative burning as the largest PM10 contributor in Chiang Mai and Lamphun ambient air. Vegetative burning, natural gas burning & coke ovens, and secondary particle accounted for 46-82%, 12-49%, and 3-19% of the PM10 concentrations, respectively. However, natural gas burning & coke ovens as well as vehicle exhaust also deserved careful attention due to their large contributions to PAHs concentration. In the wet season and transition periods, 42-60% of the total PAHs concentrations originated from vehicle exhaust while 16-37% and 14-38% of them were apportioned to natural gas burning & coke ovens and vegetative burning, respectively. In the dry period, natural gas burning & coke ovens, vehicle exhaust, and vegetative burning accounted for 47-59%, 20-25%, and 19-28% of total PAHs concentrations. The close agreement between the measured and predicted concentrations data (R(2) > 0.8) assured enough capability of PCA/APCS receptor model to be ...

State-of-the-art analytical methods for arsenic speciation rely typically on the availability of standards of defined structure, limiting the applicability of such methods to the determination of known compounds. Our previous high-energy tandem mass spectrometric studies demonstrated the strength of mass spectrometry for generating structurally diagnostic ions that allow for the identification of arsenic-containing ribofuranosides (arsenosugars) without the use of standards. We now report a more widely applicable and more sensitive approach, using negative-ion nano-electrospray low-energy tandem mass spectrometry for the generation of structurally useful product ions that allow for identification of arsenosugars at the picogram level. In the negative-ion mode, numerous product ions, suitable for characterizing naturally occurring dimethylated arsenosugars, were generated in high abundance. Application of the method to an algal extract unequivocally demonstrated the presence of a single dimethylated arsenosugar. In the positive-ion mode, characteristic tandem mass spectra were obtained for four trimethylarsonioribosides, allowing their identification without the need for standards. Overall it was demonstrated that nano-ES-MS/MS techniques can be used for characterizing arsenosugars on a routine basis, a necessary requirement for assessing potential health risks associated with consuming foods containing elevated levels of arsenosugars and for improving our understanding of arsenic biochemistry.