We used a Weather Research and Forecasting Model with Chemistry (WRF-CHEM) model that includes anthropogenic emissions from EDGAR-HTAP, biomass burning from FINN, and biogenic emissions from MEGAN to investigate the main volatile organic compound (VOC) ozone precursors during high levels of biomass burning emissions in March 2014 over upper Southeast Asia. A comparison between the model and ground-based measurement data shows that the WRF-CHEM model simulates the precipitation and 2 m temperature reasonably well, with index of agreement (IOA) values ranging from 0.76 to 0.78. Further, the model predicts O3, NO2, and CO fairly well, with IOA values ranging from 0.50 to 0.57. However, the magnitude of the simulated NO2 concentration was generally underestimated compared to OMI satellite observations. The model result shows that CO and VOCs such as BIGENE play an important role in atmospheric oxidation to surface O3. In addition, biomass burning emissions are responsible for increasing surface O3 by ∼1 ppmv and increasing the reaction rate of CO and BIGENE by approximately 0.5 × 106 and 1 × 106 molecules/cm3/s, respectively, in upper Southeast Asia.

Air pollution, particularly PM2.5, poses a significant environmental and public health concern, particularly in northern Thailand, where elevated PM2.5 levels are prevalent during the dry season (January–May). This study examines the influx and patterns of transboundary biomass burning PM2.5 (TB PM2.5) in this region during the 2019 dry season using the WRF-Chem model. The model’s reliability was confirmed through substantial correlations between model outputs and observations from the Pollution Control Department (PCD) of Thailand at 10 monitoring stations. The findings indicate that TB PM2.5 significantly influences local PM2.5 levels, often surpassing contributions from local sources. The influx of TB PM2.5 began in January from southern directions, intensifying and shifting northward, peaking in March with the highest TB PM2.5 proportions. Elevated levels persisted through April and declined in May. Border provinces consistently exhibited higher TB PM2.5 concentrations, with Chiang Rai province showing the highest average proportion, reaching up to 45%. On days when PM2.5 levels were classified as ‘Unhealthy for Sensitive Groups’ or ‘Unhealthy’, TB PM2.5 contributed at least 50% to the total PM2.5 at all stations. Notably, stations in Chiang Rai and Nan showed detectable TB PM2.5 even at ‘Very Unhealthy’ levels, underscoring the significant impact of TB PM2.5 in the northern border areas. Effective mitigation of PM2.5-related health risks requires addressing PM2.5 sources both within and beyond Thailand’s borders.

Air pollution in Thailand is regarded as a serious health threat, especially in the northern region. High levels of particulate matter (PM_2.5 and PM₁₀) are strongly linked to severe health consequences and mortality. This study analyzed the relationship between exposure to ambient concentrations of PM_2.5 and PM₁₀ by using data from the Pollution Control Department of Thailand and the burden of disease due to an increase in the ambient particulate matter concentrations in northern Thailand. This study was conducted using the Life Cycle Assessment methodology considering the human health damage impact category in the ReCiPe 2016 method. The results revealed that the annual average years of life lived with disability from ambient PM_2.5 in northern Thailand is about 41,372 years, while from PM₁₀ it is about 59,064 years per 100,000 population. The number of deaths from lung cancer and cardiopulmonary diseases caused by PM_2.5 were approximately 0.04% and 0.06% of the population of northern Thailand, respectively. Deaths due to lung cancer and cardiopulmonary diseases caused by PM₁₀, on the other hand, were approximately 0.06% and 0.08%, respectively. The findings expressed the actual severity of the impact of air pollution on human health. It can provide valuable insights for organizations in setting strategies to address air pollution. Organizations can build well-informed strategies and turn them into legal plans by exploiting the study’s findings. This ensures that their efforts to tackle air pollution are successful, in accordance with regulations, and contribute to a healthier, more sustainable future guidelines on appropriate practices of air pollution act/policy linkage with climate change mitigation.

The energy spectrum of Galactic cosmic-ray (GCR) ions at Earth varies with solar activity as these ions cross the heliosphere. Thus, this “solar modulation” of GCRs provides remote sensing of heliospheric conditions throughout the ∼11 yr sunspot cycle and ∼22 yr solar magnetic cycle. A neutron monitor (NM) is a stable ground-based detector that measures cosmic-ray rate variations above a geomagnetic or atmospheric cutoff rigidity with high precision (∼0.1%) over such timescales. Furthermore, we developed electronics and analysis techniques to indicate variations in the cosmic-ray spectral index using neutron time-delay data from a single station. Here we study solar modulation using neutron time-delay histograms from two high-altitude NM stations: (1) the Princess Sirindhorn Neutron Monitor at Doi Inthanon, Thailand, with the world’s highest vertical geomagnetic cutoff rigidity, 16.7 GV, from 2007 December to 2018 April; and (2) the South Pole NM, with an atmosphere-limited cutoff of ∼1 GV, from 2013 December to 2018 April. From these histograms, we extract the leader fraction L, i.e., inverse neutron multiplicity, as a proxy of a GCR spectral index above the cutoff. After correction for pressure and precipitable water vapor variations, we find that L roughly correlates with the count rate but also exhibits hysteresis, implying a change in spectral shape after a solar magnetic polarity reversal. Spectral variations due to Forbush decreases, 27 day variations, and a ground-level enhancement are also indicated. These methods enhance the high-precision GCR spectral information from the worldwide NM network and extend it to higher rigidity.

Previous studies have determined biomass burning as a major source of air pollutants in the ambient air in Thailand. To analyse the impacts of meteorological parameters on the variation of carbonaceous aerosols and water-soluble ionic species (WSIS), numerous statistical models, including a source apportionment analysis with the assistance of principal component analysis (PCA), hierarchical cluster analysis (HCA), and artificial neural networks (ANNs), were employed in this study. A total of 191 sets of PM_2.5 samples were collected from the three monitoring stations in Chiang-Mai, Bangkok, and Phuket from July 2020 to June 2021. Hotspot numbers and other meteorological parameters were obtained using NOAA-20 weather satellites coupled with the Global Land Data Assimilation System. Although PCA revealed that crop residue burning and wildfires are the two main sources of PM_2.5, ANNs highlighted the importance of wet deposition as the main depletion mechanism of particulate WSIS and carbonaceous aerosols. Additionally, Mg²⁺ and Ca²⁺ were deeply connected with albedo, plausibly owing to their strong hygroscopicity as the CCNs responsible for cloud formation.

Fire has long been used in Southeast Asia for the purposes of cooking, protection, and warmth. However, climate change and economic pressure have modified the life of locals, including fire practices in daily life and other fire uses. The land use of forest cover in highland area (mostly deciduous forest) has shifted to cultivation, with the application of slash-and-burn techniques. This results in frequent unplanned fires causing pollution in the form of smoke and haze. A zero-burn policy has been implemented to tackle this problem but such a policy may not be appropriate as people still need fire as a basic tool for agriculture land preparation. Moreover, the deciduous forest is a fire-dependent ecosystem to maintain its ecosystem. Frequent burning by local people or excessive government intervention in preventing fires can impact this ecosystem. In the highlands, shifting cultivation has gradually been replaced by rotational agricultural practice with a cycle of 2 to 5 years. However, the fuel load for a 2-year rotation period is only 0.25 tha-1 higher than that of a mixed deciduous forest. New fire risk maps classified according to forest types were produced for Thailand, Lao PDR, and Myanmar. We report that the mixing layer (ML) height in Chiang Mai Province was, on average, 500 m during March, with common occurrence of subsidence inversion resulting in further lowering of air quality during this month. A participatory process to develop a Community Based Fire Management (CBFiM) was undertaken and it was observed that a successful implementation would need a community with a strong leadership.