Biomarker-Determined Nonylphenol Exposure and Associated Risks in Children of Thailand, Indonesia, and Saudi Arabia.

Nonylphenol (NP) is an endocrine disruptor and environmental contaminant. Yet, data on individual body burdens and potential health risks in humans, especially among children, are scarce. We analyzed two specific urinary NP metabolites, hydroxy-NP (OH-NP) and oxo-NP. In contrast to parent NP, OH-NP has a much higher urinary excretion fraction (Fue), and both are insusceptible to external contamination. We investigated spot urine samples from school children of Thailand (n = 104), Indonesia (n = 89), and Saudi Arabia (n = 108) and could quantify OH-NP in 100% of Indonesian and Saudi children (median concentrations: 8.12 and 8.57 µg/L) and in 76% of Thai children (1.07 µg/L). Median oxo-NP concentrations were 0.95, 1.10, and <0.25 µg/L, respectively, in line with its lower Fue. Median daily NP intakes (DIs), back-calculated from urinary OH-NP concentrations, were significantly higher in Indonesia and Saudi Arabia [0.47 and 0.36 µg/(kg bw·d), respectively] than in Thailand [0.06 µg/(kg bw·d)]. Maximum DIs were close to the preliminary tolerable DI of 5 µg/(kg bw·d) from the Danish Environmental Protection Agency. Dominant sources of exposure or relevant exposure pathways could not be readily identified by questionnaire analyses and also potentially varied by region. The novel biomarkers provide long-needed support to the quantitative exposure and risk assessment of NP.

Association of climate factors and air pollutants with pneumonia incidence in Lampang province, Thailand: findings from a 12-year longitudinal study.

This study attempted to understand the associations between pneumonia, climate, and environmental air pollutants in Thailand. A 12-year longitudinal study was performed between 2003 and 2014 in Lampang province, the Northern region of Thailand. Spearman correlation and negative binomial regression modelling were used to explore the relationships between climate factors and environmental air pollutants and pneumonia incidence. Spearman correlation shows that pneumonia incidence was positively correlated with humidity and negatively correlated with temperature, NO2, and O3. The regression modelling produced a series of models to predict pneumonia incidence based on information on climate and air quality. The result of the models shows that humidity and PM10 were associated with pneumonia incidence. To better protect the health, public health policy and risk assessment approach for pneumonia incidence should include considerations of the effect of air pollution. This result can be used for further intervention to take care of human health.

Urinary Concentrations of Major Phthalate and Alternative Plasticizer Metabolites in Children of Thailand, Indonesia, and Saudi Arabia, and Associated Risks.

Phthalates are widely used in consumer products and are well-known for adverse endocrine outcomes. Di-(2-ethylhexyl) phthalate (DEHP), one of the most extensively used phthalates, has been rapidly substituted with alternative plasticizers in many consumer products. The aim of this study was to assess urinary phthalate and alternative plasticizer exposure and associated risks in children of three Asian countries with different geographical, climate, and cultural characteristics. Children were recruited from elementary schools of Saudi Arabia (n = 109), Thailand (n = 104), and Indonesia (n = 89) in 2017-2018, and their urine samples were collected. Metabolites of major phthalates and alternative plasticizers were measured in the urine samples by HPLC-MS/MS. Urinary metabolite levels differed substantially between the three countries. Metabolite levels of diisononyl phthalate (DiNP), diisodecyl phthalate (DiDP), di(2-ethylhexyl) terephthalate (DEHTP), and 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH) were the highest in Saudi children: Median urinary concentrations of oxo-MiNP, OH-MiDP, 5cx-MEPTP, and OH-MINCH were 8.3, 8.4, 128.0, and 2.9 ng/mL, respectively. Urinary DEHP metabolite concentrations were the highest in the Indonesian children. The hazard index (HI) derived for the plasticizers with antiandrogenicity based reference doses (RfDAA) was >1 in 86%, 80%, and 49% of the Saudi, Indonesian, and Thai children, respectively. DEHP was identified as a common major risk driver for the children of all three countries, followed by DnBP and DiBP depending on the country. Among alternative plasticizers, urinary DEHTP metabolites were detected at levels comparable to those of DEHP metabolites or higher among the Saudi children, and about 4% of the Saudi children exceeded the health based human biomonitoring (HBM)-I value. Priority plasticizers that were identified among the children of three countries warrant refined exposure assessment for source identification and relevant exposure reduction measures.

Particulate matter (PM10) prediction based on multiple linear regression: a case study in Chiang Rai Province, Thailand.

BACKGROUND: The northern regions of Thailand have been facing haze episodes and transboundary air pollution every year in which particulate matter, particularly PM10, accumulates in the air, detrimentally affecting human health. Chiang Rai province is one of the country's most popular tourist destinations as well as an important economic hub. This study aims to develop and compare the best-fitted model for PM10 prediction for different seasons using meteorological factors. METHOD: The air pollution and weather data acquired from the Pollution Control Department (PCD) spanned from the years 2011 until 2018 at two stations on an hourly basis. Four different stepwise Multiple Linear Regression (MLR) models for predicting the PM10 concentration were then developed, namely annual, summer, rainy, and winter seasons. RESULTS: The maximum daily PM10 concentration was observed in the summer season for both stations. The minimum daily concentration was detected in the rainy season. The seasonal variation of PM10 was significantly different for both stations. CO was moderately related to PM10 in the summer season. The PM10 summer model was the best MLR model to predict PM10 during haze episodes. In both stations, it revealed an R2 of 0.73 and 0.61 in stations 65 and 71, respectively. Relative humidity and atmospheric pressure display negative relationships, although temperature is positively correlated with PM10 concentrations in summer and rainy seasons. Whereas pressure plays a positive relationship with PM10 in the winter season. CONCLUSIONS: In conclusion, the MLR models are effective at estimating PM10 concentrations at the local level for each seasonal. The annual MLR model at both stations indicates a good prediction with an R2 of 0.61 and 0.52 for stations 65 and 73, respectively.

Relationship between PM10 and PM2.5 levels in high-traffic area determined using path analysis and linear regression.

The objective of this study was to determine the relationship between PM10 and PM2.5 levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Particulate matter (PM) samples were collected from Sukhumvit road, Bangkok, Thailand, at both open (104 samples) and covered (92 samples) areas along the road. Fifteen percent of all samples were separated before the statistical models were run and used for model validation. The results from the path analysis were more elaborate than those from the linear regression, thus indicating that meteorological conditions had a direct effect on the particulate levels and that the effects of traffic flow were more variable in open areas. The model also indicated that meteorological conditions had an indirect effect and that traffic flow had a direct effect on particulate levels in covered areas. The model validation results indicated that for open areas, the R2 values were not very different between the path analysis and the linear regression model, but that the path analysis was more accurate than the linear regression model at very low PM concentrations. At high PM concentrations, the path analysis model also had a better fit than did the linear regression, so the predictions from the path analysis model were more accurate than those from the linear regression.

AMBIENT PM10 AND PM2.5 CONCENTRATIONS AT DIFFERENT HIGH TRAFFIC-RELATED STREET CONFIGURATIONS IN BANGKOK, THAILAND.

This study investigated the potential exposure levels of PM10 and PM2.5 at two different road configuration sites in Bangkok, Thailand: covered and open roadside areas. One hundred samples were collected together with the meteorological data: temperature, relative humidity, wind speeds, and solar radiation. Spearman rank correlation was used to analyze the relationships between these factors, and PM10 and PM2.5 levels at different roadside areas. The PM10 and PM2.5 levels at the covered area were 1.72 and 1.60 times more than those levels at open area were. The mean levels were found to be 154.59 and 94.42 µg/m³ at the covered areas, and 89.43 and 58.69 µg/m³ at the open areas. These results suggested that a higher potential risk for workers, such as street vendors, was the exposure to particulate matters at the covered areas compared to open areas. Wind speeds and relative humidity were significantly negative-related influencing factors on PM10 and PM2.5 levels at the open area, but not significantly related for the covered areas.

Occurrence and efficacy of bisphenol A (BPA) treatment in selected municipal wastewater treatment plants, Bangkok, Thailand.

Investigations were carried out on the occurrence and fate of bisphenol A (BPA) in five wastewater treatment plants (WWTPs) in Bangkok, namely, Rattanakosin, Chong Non Si, Din Daeng (DD), Nong Khaem and Thungkru (TK) during three sampling events between October 2013 and February 2014. Based on the results, the influent and effluent BPA concentrations ranged between 128.5 ng/L and 606.0 ng/L; and 38.7 ng/L and 270.5 ng/L, respectively. The effluent BPA concentrations of most of the five WWTPs were lower than the influent levels. TK had the highest removal efficiency in October 2013 (80.4%) and December 2013 (90.7%) and the second highest in February 2014 (69.2%). DD had the highest removal efficiency in February 2014 (91.8%). The treatment processes employed at TK and DD were vertical loop reactor activated sludge process and activated sludge with nutrients removal, respectively. Thus, these processes seem to be good for BPA degradation.

Low serum lipase levels in mothers of children with stunted growth indicate the possibility of low calcium absorption during pregnancy: A cross-sectional study in North Sumatra, Indonesia.

Stunting is caused by various factors, including low nutritional intake in the first two years of life. This study aimed to investigate the differences in sociodemographic factors and mineral, vitamin, and enzyme parameters in mothers associated with the occurrence of stunting in children. We conducted a cross-sectional study from September to November 2020 on North Sumatra Island, Indonesia. The data collected included sociodemographic characteristics, pregnancy history, birth history, food intake, and laboratory examinations, including measurements of calcium, iron, zinc, vitamin D, pancreatic amylase, and serum lipase levels. This study included 50 healthy mothers aged 18-50 years old with children aged 2 to 60 months. There was a significant difference in serum calcium levels between the groups of mothers of children with normal and stunted growth (p = 0.03, mean difference±standard error (SE) = 0.23±0.12, 95% CI: 0.19-0.45). All of the study subjects were categorized as vitamin D deficient. The mean lipase level in the group of mothers of children with stunted growth was significantly lower than that in the group of mothers of children with normal growth (p = 0.02, mean difference±SE = 4.34±1.83, 95% CI: 0.62-8.06). The conclusion was that serum lipase levels were significantly lower in mothers of children with stunted growth compared to mothers of children with normal growth. Serum lipase levels this low are likely to indicate that a mother is unable to meet her child's calcium needs during pregnancy, increasing the child's risk of stunted growth.

Analyzing temperature, humidity, and precipitation trends in six regions of Thailand using innovative trend analysis.

The change of temperature and weather parameters is a major concern affecting sustainable development and impacting various sectors, such as agriculture, tourism, and industry. Changing weather patterns and their impact on water resources are important climatic factors that society is facing. In Thailand, climatological features such as ambient temperature, relative humidity, and precipitation play a substantial role in affecting extreme weather events, which cause damage to the economy, agriculture, tourism, and livelihood of people. To investigate recent serious changes in annual trends of temperature, relative humidity, and precipitation in Thailand, this study used the Mann-Kendall (MK) test and innovative trend analysis (ITA) methods. The MK test showed that all six regions had an upward trend in temperature and humidity index (humidex, how hot the weather feels to the average person), while relative humidity and precipitation showed both upward and downward trends across different regions. The ITA method further confirmed the upward trend in temperature and humidex and showed that most data points fell above the 1:1 line. However, the upward trend in most variables was not significant at the 5% level. The southern and eastern regions showed a significant upward trend in relative humidity and humidex at a 5% level of significance according to the MK test. The output of this study can help in the understanding of weather variations and predict future situations and can be used for adaptation strategies.

Association of cause-specific hospital admissions with high and low temperatures in Thailand: a nationwide time series study.

Background: Non-optimum temperatures are associated with a considerable mortality burden. However, evidence of temperature with all-cause and cause-specific hospital admissions in tropical countries like Thailand is still limited. Methods: Daily all-cause and cause-specific hospital admissions for outpatient and inpatient visits were collected from 77 provinces in Thailand from January 2013 to August 2019. A two-stage time-series approach was applied to assess the association between non-optimum temperatures and hospital admission. We first fitted the province-specific temperature-morbidity association and then obtained the national association in the second stage using a random-effects meta-analysis regression. The attributable fraction (AF) of hospital admissions with 95% empirical confidence interval (eCI) was calculated. Findings: A total of 878,513,460 all-cause outpatient admissions and 32,616,600 all-cause inpatient admissions were included in this study. We observed a J-shaped relationship with the risk of hospital admissions increasing for both cold and hot temperatures. The overall AFs of all-cause hospital admissions due to non-optimum temperatures were 7.57% (95% eCI: 6.47%, 8.39%) for outpatient visits and 6.17% (95% eCI: 4.88%, 7.20%) for inpatient visits. Hot temperatures were responsible for most of the AFs of hospital admissions, with 6.71% (95% eCI: 5.80%, 7.41%) for outpatient visits and 4.50% (95% eCI: 3.62%, 5.19%) for inpatient visits. The burden of hospital admissions was greater in females and in children and adolescents (0-19 years). The fractions of hospital admissions attributable to non-optimum temperatures exhibited variation among disease categories and geographical areas. Interpretation: The results indicate that low and high temperature has a significant impact on hospital admissions, especially among the females, and children and adolescents (0-19 years). The current investigation could provide evidence for policymakers to develop adaptation strategies and mitigate the adverse effects of climate change on public health in Thailand and other tropical countries. Funding: National Research Council of Thailand (NRCT): E-Asia Joint Research Program: Climate change impact on natural and human systems (N33A650979).

Occurrence, distribution, and ecological risk assessment of heavy metals in Chao Phraya River, Thailand.

Understanding heavy metals in rivers is crucial, as their presence and distribution impact water quality, ecosystem health, and human well-being. This study examined the presence and levels of nine heavy metals (Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in 16 surface water samples along the Chao Phraya River, identifying Fe, Mn, Zn, and Cr as predominant metals. Although average concentrations in both rainy and dry seasons generally adhered to WHO guidelines, Mn exceeded these limits yet remained within Thailand's acceptable standards. Seasonal variations were observed in the Chao Phraya River, and Spearman's correlation coefficient analysis established significant associations between season and concentrations of heavy metals. The water quality index (WQI) demonstrated varied water quality statuses at each sampling point along the Chao Phraya River, indicating poor conditions during the rainy season, further deteriorating to very poor conditions in the dry season. The hazard potential index (HPI) was employed to assess heavy metal contamination, revealing that during the dry season in the estuary area, the HPI value exceeded the critical threshold index, indicating the presence of heavy metal pollution in the water and unsuitable for consumption. Using the species sensitivity distribution model, an ecological risk assessment ranked the heavy metals' HC5 values as Pb > Zn > Cr > Cu > Hg > Cd > Ni, identifying nickel as the most detrimental and lead as the least toxic. Despite Cr and Zn showing a moderate risk, and Cu and Ni posing a high risk to aquatic organisms, the main contributors to ecological risk were identified as Cu, Ni, and Zn, suggesting a significant potential ecological risk in the Chao Phraya River's surface water. The results of this study provide fundamental insights that can direct future actions in preventing and managing heavy metal pollution in the river ecosystem.

Association between precipitation and mortality due to diarrheal diseases by climate zone: A multi-country modeling study.

Background: Precipitation could affect the transmission of diarrheal diseases. The diverse precipitation patterns across different climates might influence the degree of diarrheal risk from precipitation. This study determined the associations between precipitation and diarrheal mortality in tropical, temperate, and arid climate regions. Methods: Daily counts of diarrheal mortality and 28-day cumulative precipitation from 1997 to 2019 were analyzed across 29 locations in eight middle-income countries (Argentina, Brazil, Costa Rica, India, Peru, the Philippines, South Africa, and Thailand). A two-stage approach was employed: the first stage is conditional Poisson regression models for each location, and the second stage is meta-analysis for pooling location-specific coefficients by climate zone. Results: In tropical climates, higher precipitation increases the risk of diarrheal mortality. Under extremely wet conditions (95th percentile of 28-day cumulative precipitation), diarrheal mortality increased by 17.8% (95% confidence interval [CI] = 10.4%, 25.7%) compared with minimum-risk precipitation. For temperate and arid climates, diarrheal mortality increases in both dry and wet conditions. In extremely dry conditions (fifth percentile of 28-day cumulative precipitation), diarrheal mortality risk increases by 3.8% (95% CI = 1.2%, 6.5%) for temperate and 5.5% (95% CI = 1.0%, 10.2%) for arid climates. Similarly, under extremely wet conditions, diarrheal mortality risk increases by 2.5% (95% CI = -0.1%, 5.1%) for temperate and 4.1% (95% CI = 1.1%, 7.3%) for arid climates. Conclusions: Associations between precipitation and diarrheal mortality exhibit variations across different climate zones. It is crucial to consider climate-specific variations when generating global projections of future precipitation-related diarrheal mortality.

Influencing factors of COVID-19 spreading: a case study of Thailand.

Aim: A novel corona virus disease 2019 (COVID-19) was declared as pandemic by WHO as global level and local levels in many countries. The movement of people might be one influencing factor, this paper aims to report the situation COVID-19 and spreading in Thailand, including influencing factors of spreading and control. Subject and method: Infected, confirmed COVID-19 data were obtained from the official website of the Department of Disease Control, Ministry of Public Health. Tourist data was downloaded from Ministry of Tourism and Sports. Researchers analyzed the situation from the first found case in Thailand until 15 April 2020 with the timeline of important influencing factors. Correlation coefficients of tourist data and infected case was calculated by person correlation coefficient. Results: The number of infected cases was significant associated (correlation coefficient > 0.7) with economic factor, namely; number of visitors, generated income from both Thai and foreigner tourist (p value <0.01). The influencing factors of slow increased rate were the enforcement and implementation of both central and local government regulation, the strength of the Thai health care system, the culture and social relation, the partnership among various governmental and private sectors. Conclusion: We found that the number of tourist and their activities were significant associated with number of infected, confirmed COVID-19 cases. The public education and social supporting were the key roles for regulation enforcement and implementation.

Characteristics of Gases Emitted from Chicken Manure Wastewater and Potential Effects on Human Health.

Hazardous and odorous gas emissions from chicken manure wastewater are a public preoccupation. Odor composition measurements are crucial steps to provide appropriate air pollution control measures and design strategies to minimize the human health impact. In this study, chicken manure wastewater samples were extensively analyzed in a closed system by a portable handheld gas detector to characterize the odor and chemical compositions. A portable detector was calibrated prior to sampling. The total number of 153 chemical compounds found in the chicken manure wastewater samples had various olfactory characteristics, including strong, pleasant, and odorless smells. Depending on the route of exposure, most of these chemical compounds could cause human health effects, such as irritation, burns, and severe symptoms including carcinogenic.

The association of meteorological parameters and AirQ+ health risk assessment of PM2.5 in Ratchaburi province, Thailand.

Air quality is heavily influenced by rising pollution distribution levels which are a consequence of many artificial activities from numerous sources. This study aims to determine the relationship between meteorological data and air pollutants. The health effects of long-term PM2.5 were estimated on expected life remaining (ELR) and years of life lost (YLL) indices in Ratchaburi province during the years 2015-2019 using AirQ+ software. Values obtained from the PM2.5 averaging, and YLL data were processed for the whole population in the age range of 0-29, 30-60 and over 60. These values were entered into AirQ+ software. The mean annual concentration of PM2.5 was highly variable, with the highest concentration being 136.42 µg/m3 and the lowest being 2.33 µg/m3. The results estimated that the highest and lowest YLL in the next 10 years for all age groups would be 24,970.60 and 11,484.50 in 2017 and 2019, respectively. The number of deaths due to COPD, IHD, and stroke related to long-term exposure to ambient PM2.5 were 125, 27 and 26, respectively. The results showed that older people (> 64) had a higher YLL index than the groups aged under 64 years. The highest and lowest values for all ages were 307.15 (2015) and 159 (2017). Thus, this study demonstrated that the PM2.5 effect to all age groups, especially the the elderly people, which the policy level should be awared and fomulated the stratergies to protecting the sensitive group.

The Elemental Characteristics and Human Health Risk of PM2.5 during Haze Episode and Non-Haze Episode in Chiang Rai Province, Thailand.

Fine particle matter (PM2.5) was directly related to seasonal weather, and has become the influencing factor of air quality that is harmful for human health in Chiang Rai province. The aims were determining the elemental composition in PM2.5 and human health risk in haze (March 2021) and non-haze episodes (July-August 2021). Nine elements in PM2.5 were measured by using an Atomic Absorption Spectrophotometer, and an enrichment factor was used to identify the emission source. The results showed that the average concentration of PM2.5 was 63.07 µg/m3 in haze episodes, and 25.00 µg/m3 in a non-haze episode. The maximum concentration was 116.7 µg/m3 in March. The majority of elements originated from anthropogenic sources. In haze episodes, PM2.5 mean concentration was approximately 4.2 times that of the WHO guidelines (15 µg/m3 24 h), and 1.3 times that of the Thai Ambient Air Quality Standard (50 µg/m3). The analysis of backward air mass trajectory showed that transboundary and local sources significantly influenced PM2.5 at the monitoring site in the sampling period. In the health risk assessment, the non-carcinogenic risk of Cd was the highest, with a Hazard Quotient (HQ) of 0.048, and the cancer risk of Cr was classified as the highest cancer risk, with the values of 1.29 × 10-5, higher than the minimum acceptable level.

Children's exposures to boron and biocides from slime products in Asian regions.

BACKGROUND: Chemical exposure from slime toys can cause potential health effects. Although slime toys are popular in Asia, the regulation of boron, chloromethylisothiazolinone (CMIT), and methylisothiazolinone (MIT) in these toys has been implemented only in Korea. OBJECTIVE: In this study, we investigated boron migration levels and CMIT and MIT concentrations in 127 slime products from Asian cities and estimated children's exposure to boron and the biocides in Korea. METHODS: Slime boron migration levels were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES), according to Part 3 of the European Standard on the safety of toys (EN 71-3:2013). CMIT and MIT concentrations were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS). Exposure doses of boron, CMIT, and MIT were calculated using the exposure pattern of children slime users in Korea. RESULTS: Average boron migration levels of the slime products in Seoul, Bangkok, Hong Kong, Taipei, and Yokohama were 691.9, 851.1, 806.6, 509.0, and 956.2 mg/kg, respectively. Of the 127 slime products tested, 70.1% exceeded the EU boron migration limit of 300 mg/kg for toys made with sticky material. Boron migration levels in slime products in Korea did not differ significantly by manufacturing date, although the Korean boron regulations were enacted in January 2019. CMIT and MIT were detected from 51.2% and 36.2% of all products, respectively, and tended to be detected simultaneously. Exposure doses of boron, CMIT, and MIT were highest among infants. SIGNIFICANCE: Oral exposure was the most important for boron exposure. It is necessary to manage boron level in slime products and minimize exposure from hand to mouth action in infants.

Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries.

The low-cost and easy-to-use nature of rapidly developed PM2.5 sensors provide an opportunity to bring breakthroughs in PM2.5 research to resource-limited countries in Southeast Asia (SEA). This review provides an evaluation of the currently available literature and identifies research priorities in applying low-cost sensors (LCS) in PM2.5 environmental and health research in SEA. The research priority is an outcome of a series of participatory workshops under the umbrella of the International Global Atmospheric Chemistry Project-Monsoon Asia and Oceania Networking Group (IGAC-MANGO). A literature review and research prioritization are conducted with a transdisciplinary perspective of providing useful scientific evidence in assisting authorities in formulating targeted strategies to reduce severe PM2.5 pollution and health risks in this region. The PM2.5 research gaps that could be filled by LCS application are identified in five categories: source evaluation, especially for the distinctive sources in the SEA countries; hot spot investigation; peak exposure assessment; exposure-health evaluation on acute health impacts; and short-term standards. The affordability of LCS, methodology transferability, international collaboration, and stakeholder engagement are keys to success in such transdisciplinary PM2.5 research. Unique contributions to the international science community and challenges with LCS application in PM2.5 research in SEA are also discussed.

Effects of an incinerator project on a healthcare-waste management system.

This evaluative research study aimed to assess the effects of the central healthcare incinerator project on waste management in Yala Province. The study data were collected twice: at baseline and during the operational phase. A combination of structured interview and observation were used during data collection. The study covered 127 healthcare facilities: government hospitals, healthcare centres, and private clinics. The results showed 63% of healthcare risk waste (HCRW) handlers attended the HCRW management training. Improvements in each stage of the HCRW management system were observed in all groups of facilities. The total cost of the HCRW management system did not change, however; the costs for hospitals decreased, whereas those for clinics increased significantly. It was concluded that the central healthcare waste incinerator project positively affected HCRW management in the area, although the costs of management might increase for a particular group. However, the benefits of changing to a more appropriately managed HCRW system will outweigh the increased costs.

Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex.

We applied the model of American Meteorological Society-Environmental Protection Agency Regulatory Model (AERMOD) as a tool for the analysis of nitrogen dioxide (NO2) emissions from a cement complex as a part of the environmental impact assessment. The dispersion of NO2 from four cement plants within the selected cement complex were investigated both by measurement and AERMOD simulation in dry and wet seasons. Simulated values of NO2 emissions were compared with those obtained during a 7-day continuous measurement campaign at 12 receptors. It was predicted that NO2 concentration peaks were found more within 1 to 5 km, where the measurement and simulation were in good agreement, than at the receptors 5 km further away from the reference point. The Quantile-Quantile plots of NO2 concentrations in dry season were mostly fitted to the middle line compared to those in wet season. This can be attributed to high NO2 wet deposition. The results show that for both the measurement and the simulation using the AERMOD, NO2 concentrations do not exceed the NO2 concentration limit set by the National Ambient Air Quality Standards (NAAQS) of Thailand. This indicates that NO2 emissions from the cement complex have no significant impact on nearby communities. It can be concluded that the AERMOD can provide useful information to identify high pollution impact areas for the EIA guidelines.