Development of a high-resolution real-time air quality forecasting system over northern Thailand.

Biomass burning events occur consistently during the dry season in northern Thailand and neighboring Southeast Asian countries on an annual basis. The primary sources of these emissions are the burning of agricultural residues and forest fires, which contribute significantly to the presence of air pollutants in the region. Throughout the dry season, which spans from February to April, satellite data from MODIS detects fire hotspots throughout the Indochinese peninsula. These pollutants resulting from biomass burning not only degrade local air quality but also have adverse effects on public health. Numerous sectors and institutions have been actively addressing this recurring issue for several years. Nevertheless, the problem persists across the region. A major obstacle in tackling this problem is the absence of a comprehensive measurement tool, which is prohibitively expensive. Moreover, most of the available measurement instruments are concentrated in urban areas, leaving rural regions, near the emission sources, lacking in observational tools. Hence, in this study, we employ the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) as a regional air quality model to predict high-resolution real-time air quality and related meteorological conditions in northern Thailand. To achieve this, we calculate biomass burning areas using NASA MODIS Near Real-Time (NRT) active fire hotspot data and estimate pollutant emission rates using the 3BEM model. These data are then used to establish chemical profiles and initial boundary conditions for the WRF-Chem air quality model. Ultimately, this experimental air quality forecasting model is anticipated to serve as an early warning system and play a pivotal role in research and practical applications aimed at addressing air quality impacts and adaptation strategies in northern Thailand.