Agapol Junpen

Accurate, high-resolution emission inventories are essential for air quality modeling and policy evaluation, yet national-scale inventories for Thailand remain limited in spatial and temporal detail. This study develops a comprehensive national emission inventory for Thailand in 2019 (EI–TH 2019), covering 12 major air pollutants and greenhouse gases across key sectors, including energy, transport, industry, agriculture, waste, and residential activities. The inventory is constructed using country-specific activity data from official statistics and sectoral surveys, combined with GAINS-consistent emission factors and control assumptions. Emissions are resolved at 1 × 1 km spatial resolution and monthly temporal resolution to capture Thailand-specific emission dynamics. The results show that emissions across major pollutants are dominated by a limited number of source groups, with biomass burning and residential solid-fuel use driving particulate matter, transport dominating NO_x and CO emissions, large-scale combustion and industry controlling SO₂ emissions, and agriculture contributing the majority of NH₃ emissions. Strong seasonal variability is observed in PM_2.5, CO, and NH₃, primarily driven by dry-season biomass burning, whereas NO_x and SO₂ exhibit relatively stable temporal patterns. The reliability of EI–TH 2019 is supported by a multi-dimensional evaluation framework. Temporal consistency is demonstrated through strong agreement between modeled PM_2.5 emissions and ground-based observations, as well as between NO_x emissions and satellite-derived TROPOMI NO₂ (r = 0.93; ρ = 0.96). Biomass burning timing is further validated using satellite fire activity (VIIRS), showing consistent seasonal patterns. Comparisons with global inventories (EDGAR v8.1, HTAP v3.2, and GFED5.1) reveal systematic differences in sectoral contributions, temporal profiles, and emission magnitudes, particularly for biomass burning, reflecting the importance of country-specific data and assumptions. Overall, EI–TH 2019 provides a robust, high-resolution, and policy-relevant emission dataset that improves the representation of emission processes in Thailand. The results highlight key priority sectors—biomass burning, transport, industry, and agriculture—for targeted emission-reduction strategies and support applications in chemical transport modeling, exposure assessment, and integrated air-quality and climate-policy analysis.

Ammonia (NH₃) is a key precursor to secondary particulate matter in Southeast Asia, yet Thailand has lacked a country-specific, policy-focused emission inventory. This study creates the first spatially gridded (12 × 12 km) and monthly resolved national NH₃ inventory for 2019, using detailed agricultural activity data, survey-based livestock management practices, and crop-specific fertilizer application profiles. Satellite-derived burned-area data were included to constrain emissions from open burning. National NH₃ emissions are estimated at 459.1 kt per year, with an overall uncertainty of ±15.3%. Agriculture accounts for 95.8% of total emissions. Livestock and manure management contribute 225.3 kt per year (49.1%), reflecting high densities of poultry, cattle, and pigs, as well as regional differences in manure handling and storage practices that enhance ammonia volatilization. Fertilizer-related emissions total 192.4 kt per year (41.9%), with seasonal peaks during primary planting cycles, in contrast to the more episodic biomass-burning emissions. Comparison with the global EDGARv8.1 inventory shows significant sectoral and temporal differences, including considerably higher livestock emissions and lower fertilizer emissions in this study, due to Thailand-specific emission factors and temporal emission allocation methods. These findings clarify the spatial and temporal drivers of NH₃ emissions in Thailand and offer actionable insights for targeted mitigation—notably improved manure management and optimized nitrogen use in regions where dry-season emissions coincide with severe PM_2.5 episodes. The THAI-NH₃ Inventory provides a strong foundation for chemical-transport modeling and evidence-based policymaking to reduce ammonia-related haze in Thailand.

This study aimed to estimate air pollution emissions from road transportation in Thailand, supporting policymakers in planning and implementing mitigation measures, especially for fine particulate matter (PM2.5) in the Bangkok Metropolitan Region (BMR), by using the Tier-3 method, which allows for detailed analysis and reflects the country’s specific conditions. Additionally, this study seeks to evaluate the impact of older vehicles and biofuel blends on particulate matter (PM) exhaust emissions. For the first time in Thailand, a high-resolution gridded emission inventory was created at a 1 km × 1 km scale using Geographic Information Systems (GIS) and official traffic data. This spatially detailed inventory distributes PM emissions by vehicle type and road classification, enabling more accurate air quality assessments and control strategies. The results showed that in 2019, road transportation in Thailand emitted 72.2 megatons (Mt) of CO₂, 470 kilotons (kt) of NO_X, 888 kt of CO, 34.9 kt of NMVOC, 4.4 kt of NH₃, and 97.1 kt of NMVOC from gasoline evaporation. For particulate matter, road transportation produced 28.3 kt of PM2.5, with 21.7 kt (77%) coming from hot exhaust emissions. PM2.5 exhaust sources were identified as diesel vehicles, including light-duty and heavy-duty trucks, accounting for 8.9 kt (41%) and 8.0 kt (37%), respectively. Using the 2019 road transport emission inventory as a baseline, older diesel vehicles primarily contribute to tailpipe particulate matter. Therefore, scrappage alone offers limited short-term improvements if replacements continue to meet Euro 3/4 standards. The most significant and lasting reductions happen when Euro 5 fuel quality (≤10 ppm of sulfur) is combined with rapid adoption of Euro 5/6 new vehicles and targeted deployment of zero-emission vehicles in light-duty trucks, urban buses, and heavy-duty trucks. Although sales of BEV passenger cars are increasing quickly, their overall system PM impact remains modest, because gasoline-powered cars already emit minimal PM per kilometer under similar Euro standards. Policy timing is crucial: further delays in adopting Euro 5/6 could lock in higher fleet-average emissions.

Community-scale biomass power plants (CSBPPs) offer a decentralized approach for electricity generation by utilizing locally available biomass while delivering socioeconomic benefits. Site selection plays a critical role in the success of CSBPPs and requires the consideration of diverse spatial and non-spatial factors. This study presents a spatial decision-support tool for identifying suitable CSBPP sites in Thailand’s Eastern Economic Corridor (EEC), which comprises the Chachoengsao, Chonburi, and Rayong provinces. A geoprocessing workflow integrating Geographic Information Systems (GISs), Multi-Criteria Decision-Making (MCDM), and the Analytic Hierarchy Process (AHP) was developed using ModelBuilder tools in ArcGIS Pro (version 3.0.2). Thirteen sub-criteria related to geographical, infrastructural, and socioeconomic–cultural dimensions, along with exclusion zones, were evaluated by 15 experts from diverse stakeholder groups. Biomass availability from five major economic crops was combined with other spatial data layers, incorporating expert-assigned weights and suitability scores. The findings indicated a remaining biomass energy potential was 34,156 TJ, with sugarcane residues contributing over 80%. Approximately 20% of the EEC area (about 0.262 million hectares) was classified as highly suitable for CSBPP development, revealing several viable site options. The proposed model offers a flexible and replicable framework for regional biomass planning and can be adapted to other locations by adjusting the criteria and integrating optimization techniques.

Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area products are widely used to assess the damaged area after wildfires and agricultural burning have occurred. This study improved the accuracy of the assessment of the burnt areas by using the MCD45A1 and MCD64A1 burnt area products with the finer spatial resolution product from the Landsat-8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) surface reflectance data. Thus, more accurate wildfires and agricultural burning areas in the Greater Mekong Subregion (GMS) for the year 2015 as well as the estimation of the fire emissions were reported. In addition, the results from this study were compared with the data derived from the fourth version of the Global Fire Emissions Database (GFED) that included small fires (GFED4.1s). Upon analysis of the data of the burnt areas, it was found that the burnt areas obtained from the MCD64A1 and MCD45A1 had lower values than the reference fires for all vegetation fires. These results suggested multiplying the MCD64A1 and MCD45A1 for the GMS by the correction factors of 2.11−21.08 depending on the MODIS burnt area product and vegetation fires. After adjusting the burnt areas by the correction factor, the total biomass burnt area in the GMS during the year 2015 was about 33.3 million hectares (Mha), which caused the burning of 109 ± 22 million tons (Mt) of biomass. This burning emitted 178 ± 42 Mt of CO₂, 469 ± 351 kilotons (kt) of CH₄, 18 ± 3 kt of N₂O, 9.4 ± 4.9 Mt of CO, 345 ± 206 kt of NO_X, 46 ± 25 kt of SO₂, 147 ± 117 kt of NH₃, 820 ± 489 kt of PM2.5, 60 ± 32 kt of BC, and 350 ± 205 kt of OC. Furthermore, the emission results of fine particulate matter (PM2.5) in all countries were slightly lower than GFED4.1s in the range between 0.3 and 0.6 times.

In the middle of 2019, Thailand introduced an urgent measure to solve the haze and fine particles problem caused by preharvest sugarcane. The measure is to eradicate the burning of sugarcane before harvesting within the next four years. This study focuses on estimation of future reduced air emissions from the implementation of this measure. The study results showed that without the implementation of the measure in the production season 2022/23, the amount of burned sugarcane will be as high as 102.4 ± 1.0 Mt/yr, resulting in the release of small particulate matter of 2.5 microns or less in diameter (PM_2.5) emissions into the atmosphere at 30.6 ± 8.6 kt/yr, which is about a 21% increase in emissions from the 2018/19 season. However, with the government’s enforcement of the measure to reduce burned sugarcane, the amount of air emissions will immediately be reduced in the first year. In order to effectively implement the sugarcane burning reduction measure, in which the harvesting methods will change from cutting burned sugarcane to cutting fresh sugarcane with human labor and with machinery, the government must provide financial support, to farmers, of approximately 3.3 USD per ton of fresh sugarcane for the use of human labor and 2.9 USD per ton of fresh sugarcane for the use of machinery. The costs of investment to reduce PM_2.5 emissions can be calculated in the range of 9.7−11.0 million USD per kiloton of PM_2.5.

Crop residue burning negatively impacts both the environment and human health, whether in the aspect of air pollution, regional and global climate change, or transboundary air pollution. Accordingly, this study aims to assess the level of air pollutant emissions caused by the rice residue open burning activities in 2018, by analyzing the remote sensing information and country specific data. This research also aims to analyze the trend of particulate matter 10 microns or less in diameter (PM₁₀) concentration air quality sites in provinces with large paddy rice planting areas from 2010–2017. According to the results, 61.87 megaton (Mt) of rice residue were generated, comprising 21.35 Mt generated from the irrigated fields and 40.53 Mt generated from the rain-fed field. Only 23.0% of the total rice residue generated were subject to open burning—of which nearly 32% were actually burned in the fields. The emissions from such rice residue burning consisted of: 5.34 ± 2.33 megaton (Mt) of CO₂, 44 ± 14 kiloton (kt) of CH₄, 422 ± 179 kt of CO, 2 ± 2 kt of NO_X, 2 ± 2 kt of SO₂, 38 ± 22 kt of PM_2.5, 43 ± 29 kt of PM₁₀, 2 ± 1 kt of black carbon (BC), and 14 ± 5 kt of organic carbon (OC). According to the air quality trends, the results shows the higher level of PM₁₀ concentration was due to the agricultural burning activities, as reflected in the higher monthly averages of the months with the agricultural burning, by around 1.9–2.1 times. The result also shows the effect of government’s policy for farmers on the crop burning activities and air quality trends.

The purpose of this study was to assess household solid waste management in areas governed by local administrative organizations (LAOs). The obtained results would be used to assess the amount of air pollution emitted from household solid waste open burning. A survey was employed, through the use of questionnaires, to collect data from a random sample of 4300 households residing in areas governed by 96 LAOs. According to the results, it was evident that a total of 26.17 Mt of solid waste were generated per year, of which 6.39 Mt/year was not collected by the LAOs and was eliminated by households. Moreover, the percentage of waste burned on or outside the households’ property was 53.7%, or an equivalent of 3.43 Mt/year of solid waste burned in open areas. In addition, it was found that 0.66 Mt/year of solid waste collected by the LAOs was burned in open areas and was not eliminated properly. Hence, the total amount of solid waste from these two sources was 4.09 Mt/year, which resulted in the emissions of carbon dioxide equivalent, carbon monoxide, sulfur dioxide, nitric oxide, and particulate matter of 1247.3 kt/year, 103.0 kt/year, 1.2 kt/year, 7.4 kt/year, and 19.6 kt/year, respectively.

Agricultural residue is a major raw material for renewable energy production, particularly heat production, in Thailand. Meanwhile, the process-based residue, such as bagasse, rice husk, wood residue, palm fiber, palm shell, and saw dust, is used as a fuel for energy production in the agro-industry. Hence, this study is intended to assess the net potential and capacity of alternative agricultural residues, specifically rice straws, to serve as the supplementary fuel for very small power plants (VSPPs) in Thailand. According to the results obtained during the crop season of 2015/2016, approximately 26 Mt of rice straws were generated upon the harvesting process. The net potential of rice straws, including those that were burned and those that were left in the fields, was only about 15% or 3.85 Mt, which could be used for heat and electricity production at 1331 kilotons of oil equivalent (ktoe) or 457 MWe. As agro-residues vary by seasonality, the peak season of rice straws was in November, where approximately 1.64 Mt (43%) were generated, followed by December, at 1.32 Mt (34%). On the basis of the results, rice straw has the potential to serve as a fuel supply for VSPPs at 14.2%, 21.6%, 26.3%, and 29.0% for the radii of compilation at 24, 36, 48 km and 60 km, respectively.

Bangkok Metropolitan Region (BMR), including the capital city and five adjacent provinces, constitutes one of the top 10 megacities experiencing serious traffic congestion in the world, leading to air quality problems with significant adverse human health risks. Previously, there have been many operations planned to influence the fuel consumption and emissions from the on-road transport sector in the BMR area. It is necessary to estimate emissions using detailed information in order to thoroughly understand the reason for changes in emission levels and their impact on air quality. This paper aims to determine the successful implementation of energy and air pollution control policies in Thailand through an investigation of the emissions inventory of on-road transport in BMR, including ozone precursors (CO, NO_X, Non-methane volatile organic compounds (NMVOCs) ), greenhouse gases (CO₂, CH₄, N₂O), acidic substances (SO₂ and NH₃), and particulate matters (PM_2.5, PM₁₀, Black Carbon (BC), Organic Carbon (OC)) during the period from 2007 to 2015, using the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model based on the country-specific activity data together with the emission factor from the GAINS-Asia database. This study found that the amount of exhaust emissions over the BMR area in the year 2015 (and the trend during the period from 2007 to 2015) is approximately 139 kt of CO (−7.9%), 103 kt of NO_X (−4.1%), 19.9 kt of NMVOC (−6.7%), 15 kt of CO₂ (+1.6%), 8.6 kt of CH₄ (+6.8%), 0.59 kt of N₂O (+1.3%), 0.87 kt of SO₂ (−25.8%), 1.1 kt of NH₃ (+7.8%), 4.9 kt of PM_2.5 (−5.5%), 5.1 kt of PM₁₀ (−7.9%), 3.1 kt of BC (−2.5%), and 1.4 kt of OC (−7.7%). The change in emissions in each pollutant is a result of the more stringent control of fuel and engine standards, the shift in the fuel type used, and the effects of controlling some emissions. Light duty car gasoline fuel is identified as a major contributor of CO, NH₃, N₂O, and NMVOC, whereas trucks are the greatest emitters of NO_X, SO₂, and particulate matter. This study suggests that the most powerful implementation plan for the continuous, significant reduction of ozone precursor, SO₂, and particulate matter emissions is the more stringent enforcement of fuel and vehicle standard levels, especially concerning light duty vehicles.