Bangkok is a rapidly expanding city with existing natural areas being replaced by developed areas creating an urban heat island (UHI) phenomenon in the city. LANDSAT imagery, near-infrared wavelength data, and time series information were used to study and to monitor the phenomenon of surface urban heat island (SUHI) in Bangkok. The variation of land surface temperature (LST) and the urban heat island intensity (UHII) phenomenon during 2008-2014 were investigated and the relationship between the UHII phenomenon and urban sprawl in Bangkok was studied. Using the UHII, we compared nine LST images of the investigated areas defined as inner, urban fringe and suburb zones. The UHI in Bangkok in the winter (dry) is higher than in the summer. Satellite imageries were used to classify the land use types as open spaces with high-rise buildings, very high density of buildings and high-rise buildings. Low vegetation index was found in urban fringe areas and inner city area with high surface temperature. The vegetation index value is high in areas of agricultural land, and low density building, it appears in suburb areas with low surface temperature. The results indicate that NDVI and High-rise building zones influence LST distribution and UHII phenomenon.

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Rapid population and urban growth in Bangkok increases the need for vertical city development because of the limited territory. This might lead to increasing land surface temperatures (LST), which makes some urban areas significantly warmer and leads to hot spots known as urban heat islands. It is known that climatic factors, such as rainfall and temperature, influence increases in dengue incidences. Thus, this research uses spatial statistical analysis to consider the association of urban LST with dengue incidences. The LST calculation methods are based on LANDSAT imageries in 2009 and 2014. Pearson correlation and Bayesian hierarchical modeling were used for predicting dengue incidences. This study found the highest correlation between the density of high-rise buildings, which had a significant influence on LST, and dengue incidences. Both the number of high-rise buildings and the surface temperature of low-rise buildings increased dengue incidence between 2009 and 2014. Overall, it was found that for every increase of 1000 high-rise buildings, the dengue incidence increased 2.19 on average during that period.

In this study, a range of environmental and microbiological factors were measured at three different fitness centres in a tropical environment with contrasting ventilation regimes, including an airconditioned indoor facility, an indoor facility with natural ventilation and an outdoor, open-air facility. A parallel questionnaire survey of the attitudes of the exercisers toward their fitness centre's environment and hygiene was also conducted. Measurement results indicate that airborne inhalable particulate matter (PM 10 ), air speed (AS), temperature and relative humidity (RH) were statistically different among the three fitness centres. There were also significant differences in the bacteria and fungi levels, in the air and on equipment surfaces, in the three centres. A strong negative association between AS and PM 10 (R 2 ¼ -0.98) was observed at the air-conditioned indoor fitness centre. When the results of all three fitness centres were combined, the airborne microorganisms (bacteria and fungi) were positively correlated to AS and RH, while those on equipment surfaces were negatively correlated. Temperature was found to be significantly correlated to an increase in the numbers of all types of microorganisms studied, except on-equipment-surface fungi. The attitudinal survey indicated that the participants were less stressed during exercises in the air-conditioned fitness centre.

This study developed a novel computer program for predicting the deterioration of various types of materials from historic monuments caused by exposure to atmospheric pollution. The program was designed based on a set of materials' doseresponse functions, which take air pollutants together with climatic parameters into account. It is a web-based application that requires three input datasets: monuments' material characteristics, local meteorological data and air pollution levels over a defined exposure time. It is also capable of estimating restoration costs. Quantification of future monument deterioration is possible by extrapolation of linear temporal relationships for air pollution and meteorological parameters. This user-friendly-interface program cooperates with Google Maps™ to find the nearest air pollution and meteorological stations to the monument site. The program may be used as a tool providing quantitative information for effective policymaking in conservation of cultural heritage monuments. To illustrate its use, the program was employed to assess the accumulated deterioration of 75 Buddhist monuments comprised of various materials located in a historical area of Bangkok, Thailand. It was estimated that the total accumulated material loss from all monuments over seven years exposure in this environment to be approximately 410 cm 3 with an overall restoration cost of about 210,000 USD.