The widely used low-cost particulate matter (PM) sensors in Thailand, such as the DustBoy, require performance improvements to ensure their data align with the established standards set by the US Environmental Protection Agency (US EPA). This study evaluates the accuracy and reliability of the DustBoy, a commonly used PM_2.5 monitoring device in Thailand. A comparative analysis was conducted between the DustBoy and the US EPA’s Federal Reference Method (FRM) and Federal Equivalent Method (FEM). The research involved both laboratory and field testing, where the DustBoy’s performance was analyzed at various particulate matter concentration levels and environmental conditions. The study demonstrated that the DustBoy readings diverged from those of standard monitors at higher PM_2.5 concentrations; however, a positive correlation between the devices remained evident. Below 100 µg/m³, the DustBoy overestimated PM concentrations compared to the FRM devices but underestimated them compared to the FEM devices. At higher concentrations, the DustBoy showed a significant overestimation, although the data trends aligned with those of standard devices. The sensor performance was also affected by factors such as the sensor age and device model. Corrections were developed to adjust the DustBoy readings to match the reference devices more closely, enhancing the accuracy post-adjustment. These corrections will refine the DustBoy’s public data reporting and serve as guidelines for other low-cost sensors in Thailand.

In this study, we examined the impact of an intelligent system and air conditioning control on power consumption. The experiment was carried out during five distinct time periods: (1) background room usage, (2) smart system setup, (3) air conditioning control to maintain room temperature at no more than 27 °C, (4) air conditioning temperature control during working hours, and (5) air conditioning operated continuously to maintain the room temperature at 27 °C. For each time period, the daily power consumption was evaluated, and outliers were identified and eliminated using a threshold derived from the hourly average. The findings demonstrated that the smart system setup period and air conditioning control resulted in lower usage compared to continuously operated air conditioning with substantial spikes in demand. The impacts of the novel system and air conditioning control on energy consumption were revealed through statistical analysis, which included regression models and hypothesis tests. According to this study’s findings, it is essential to regulate spikes and guarantee proper operation to reduce the carbon footprint while maintaining a comfortable atmosphere. Notably, the integration of the smart system and optimized scheduling resulted in a substantial decrease in greenhouse gas emissions, with annual carbon emissions reduced by up to 65% compared to continuously operated air conditioning without smart control. Moreover, these systems can optimize energy use.

Agricultural crop residue burning is a major driver of seasonal PM2.5 pollution and greenhouse gas (GHG) emissions in Northern Thailand. This study quantified GHG emissions from the open burning of rice, maize, and sugarcane residues across six provinces (Chiang Mai, Mae Hong Son, Lampang, Uttaradit, Nakhon Sawan, and Kamphaeng Phet) from 2019 to 2024 using the 2006 IPCC emission methodology. Spatiotemporal patterns of fire hotspots were characterized using MODIS and VIIRS satellite data, combined with kernel density estimation (KDE) and land-use classification in ArcGIS Pro. Total non-CO₂ GHG emissions (CH₄ and N₂O, expressed as CO₂-eq using GWP100 from IPCC AR5) over the six years totaled 2,599,551 tCO₂-eq, with major rice contributing the largest share (35%), followed by sugarcane (24%), second rice (21%), and maize (20%). Nakhon Sawan was the leading emitter (41%), reflecting its extensive rice and sugarcane cultivation. Pearson correlation analysis revealed consistently positive relationships between daily fire hotspot counts and PM2.5 concentrations (r = 0.30–0.84), with the strongest correlations observed in Mae Hong Son, where basin topography traps pollutants. Time-series analysis confirmed pronounced seasonal PM2.5 peaks that exceeded Thailand’s 24-h NAAQS limit (37.5 μg/m³) by 7–9 times in severe years. Biochar production via pyrolysis was evaluated as a zero-burning alternative, with an estimated annual carbon sequestration potential of 2.3–3.5 million tCO₂-eq, substantially exceeding emissions from open burning. These findings indicate that crop-residue valorization options—including biochar production, composting, and biochar co-compost—could theoretically offset agricultural GHG emissions and reduce field-burning PM2.5 emissions in Northern Thailand. However, the realized mitigation will depend on (i) verification of biochar long-term stability in tropical Thai soils through dedicated in situ trials, (ii) economic incentives that offset biochar production costs of approximately 1500–3500 THB per tonne, and (iii) integration within a policy mix that combines burning bans, mechanization support, and farmer extension services. Without these enabling conditions, biochar should be regarded as a future-perspective option rather than an immediately deployable solution.