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Orange jasmine (Murraya paniculata) leaves were collected from three different sites in the area of Bangkok and in a remote area as a control site. The leaf samples were digested and the concentrations of Cu, Fe, Pb, Mn, Ni, Cr, and Zn were then quantified by using inductively coupled plasma-atomic emission spectrometry (ICP-AES). All three Bangkok sites were polluted with heavy metals compared with the background site. Fe was found as the highest mean concentration of the metals studied, while Pb was the lowest. There was a high correlation coefficient between metals Cu-Mn, Cu-Zn, Cu-Pb, and Mn-Zn. However, Fe was not correlated with other metals. There was no significant difference in Pb between sites. The significant difference in other metals found in the study could be attributed to different anthropogenic activities between sites. The principal-component analysis (PCA) identified two factors according to the sources of metals making up the anthropogenic (traffic) and natural (soil) sources. Traffic emission was found to be the main source of metal pollution in the atmosphere of Bangkok.

Airborne particulate samples were collected in Bangkok, Thailand, using high-volume air samplers from March 2006 to March 2007. The sampling sites were the Huay-Khwang Community Housing (HCH) and the Ratburana Post Office (RPO), represented as residential and industrial areas, respectively. The samples collected were analyzed by inductively coupled plasma-atomic emission spectrometry (ICP-AES) for elemental analysis. The study reveals that total suspended particulate (TSP) concentrations are higher in the RPO (144.47 microg/m(3)) than at the HCH (110.93 microg/m(3)) site. The results also indicate that most of the metals were highest in winter and lowest in the rainy season. Na, Al, K, and Fe are the elements mostly found in the study. High-correlation coefficients of Al-K, K-Zn, and Al-Zn are observed at the HCH (R=-0.99, -0.97, and -0.97) and the RPO (R=-0.94, -0.92, and -0.83), respectively. Most of the measured metallic elements show weak correlation with meteorological parameters. Principal component analysis (PCA) indicates that soil, construction, vehicular emission, and biomass burning are the major pollutant sources of both sampling site. The HCH site is influenced by the domestic activities like vehicular emission, construction, and biomass burning. The sources of airborne metals found in the RPO come from both domestic and industrial activities.

Several studies in North American cities have reported associations between air pollution and respiratory symptoms. Replicating these studies in cities with very different population and weather characteristics is a useful way of addressing uncertainties and strengthening inferences of causality. To this end we examined the responses of three different panels to particulate matter (PM) air pollution in Bangkok, Thailand, a tropical city characterized by a very warm and humid climate. Panels of schoolchildren, nurses, and adults were asked to report daily upper and lower respiratory symptoms for 3 months. Concentrations of daily PM(10) (PM with a mass median aerodynamic diameter less than 10 microm) and PM(2.5) (airborne particles with aerodynamic diameters less than 2.5 microm) were collected at two sites. Generally, associations were found between these pollution metrics and the daily occurrence of both upper and lower respiratory symptoms in each of the panels. For example, an interquartile increase of 45 microg/m(3) in PM(10) was associated with about a 50% increase in lower respiratory symptoms in the panel of highly exposed adults, about 30% in the children, and about 15% in the nurses. These estimates were not appreciably altered by changes in the specification of weather variables, stratification by temperature, or inclusion of individual characteristics in the models; however, time trends in the data cause some uncertainty about the magnitude of the effect of PM on respiratory symptoms. These pollutants were also associated with the first day of a symptom episode in both adult panels but not in children. The estimated odds ratios are generally consistent with and slightly higher than the findings of previous studies conducted in the United States.

This paper studies the relevance between carbon dioxide (CO2) absorption rates of common trees in Chulalongkorn University (Thailand), and environmental factors -- light intensity, air temperature, leaf temperature, and CO2 concentration in air -- by forming non-linear models. The common tree species are Pterocarpus indicus, Samanea saman, Peltophorum pterocarpum, and Terminalia catappa. Measuring CO2 absorption was done by chamber analysis approach. The experiment was carried out by gauging 10 leaves, 7 hours per day, and 2 days per species. According to the models, it is obvious that light intensity is the most influential factor to CO2 absorption for all studied species. Peltophorum pterocarpum and Samanea saman reach their maximum CO2 uptake rates of 24.5 and 20.9 CO2 µmol m-2s-1, when photosynthetically active radiation is 1100 and 1500 µmol m-2s-1 respectively. The other two do not reach their maximum rate within model data range. The regressions were best fitted with Gaussian function and Sigmoidal function. It is also suggested that Peltophorum pterocarpum and Samanea saman are good carbon sink and they should be planted more in the city for optimal CO2 absorption.