Health Impact Assessment of Short-Term Exposure to Particulate Matter (PM10) in Northern Thailand.

In northern Thailand, in recent decades, particulate pollution from the burning of biomass has become a serious issue with toxicological implications for human health, especially during the winter months of January to April. The purpose of this study was to explore short-term exposure to particulate matter (PM10) in northern Thailand. The high PM10 concentration in 2012 was used as a case study. We used the EPA's Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) for the health impact assessment, along with ground-based measurement data. The annual average observed PM10 concentration was in the range of 43-61 µg/m3, with a maximum observed PM10 concentration of 300 µg/m3 in March. We then assessed the impacts of PM10 exposure in northern Thailand. When the PM10 concentration was reduced to 120 µg/m3, the undesirable effects on respiratory mortality decreased by 5%-11%. When the concentration of PM10 was reduced to 45 µg/m3, the deleterious effects on respiratory mortality decreased by 11-30%. In conclusion, adherence to the WHO-AQG, particularly for PM10 (45 µg/m3), tends to result in considerable reductions in respiratory disease mortality in northern Thailand.

Human health risk assessment of PM2.5-bound heavy metal of anthropogenic sources in the Khon Kaen Province of Northeast Thailand.

The study aimed to assess the human health risk of PM2.5-bound heavy metals from anthropogenic sources in Khon Kaen Province, Thailand between December 2020 and February 2021. According to the findings, the geometric mean concentration of PM2.5 in the university area, residential area, industrial zone, and the agricultural zone was 32.78 µg/m3, 50.25 µg/m3, 44.48 µg/m3, and 29.53 µg/m3, respectively. The results showed that the estimated human health risk assessment, in terms of non-carcinogenic risks among children and adults in an urban area (residential and university), industrial zone, and the agricultural area, was of hazard index (HI) value of >1.0 indicating a greater chance of chronic effects occurring. This study showed that exposure to PM2.5-bound heavy metal may increase the likelihood that lasting effects will result in a very high carcinogenic risk (CR) in children in residential areas, and an industrial zone with total carcinogenic risk (TCR) values of 0.23 × 10 1 , and 0.12 × 10 1 , respectively while resulting in a high TCR of 3.34 × 10 - 2 and 4.11 × 10 - 2 within the university areas and agricultural zone, respectively. In addition, health risk assessments among adults demonstrate high TCR values of 4.40 × 10 - 1 (residential area), 2.28 × 10 - 1 (industrial zone), and 7.70 × 10 - 3 (agricultural zone), thus indicating a potential health risk to adults living in these areas while the university area was very low effects on carcinogenic risk ( CR ≤ 10 - 8 ) for adults. Therefore, lowering the risk of exposure to PM2.5 via the respiratory tract, for example, wearing a mask outside is a very effective self-defense strategy for people within and around the study site. This data study strongly supports the implementation of the air pollutant emission source reduction measures control and health surveillance.

Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century.

This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000-2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed to compare with the GCMs, evaluated by five performance metrics including mean annual temperature, mean bias errors, mean seasonal cycle amplitude, correlation coefficient, and root mean square error. GCMs are ranked by relative error of all performance metrics. Results show that the temperatures from most GCM simulations are below the mean reference data (i.e., average of ground-based and reanalysis datasets), with north to south gradient in the range from 19 °C to 33 °C. In addition, all the GCM biases range from -0.07 °C to 2.78 °C and show severity of the temperature changes in spatial pattern ranging from -5 °C to 15 °C. The correlations of most GCMs range from 0.70 to 0.95, while the magnitudes of error are less than 2 °C. Study cases point out that the 13-MODEL ENSEMBLE, CESM2, and CNRM-CM6-1 perform better than the other models in simulating the temperature over Thailand for land-only and sea-only, and both land and sea cases, respectively, while MIROC6 performs the worst for all study cases in this study area. From the designed methodology, CNRM-CM6-1 has the best performance and is the most appropriate choice to simulate the temperature for the overall Thailand area.