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Near Real-Time Biomass Burning PM2.5 Emission Estimation to Support Environmental Health Risk Management in Northern
Chakrit Chotamonsak1,2, Punnathorn Thanadolmethaphorn3, Duangnapha Lapyai4
1Department of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai 50200, Thailand.
Abstract:
Northern Thailand experiences recurrent seasonal haze driven by biomass burning (BB), which results in hazardous PM2.5 exposure and elevated environmental health risks. To address the need for timely and spatially resolved emission information, this study developed and evaluated an operational near-real-time (NRT) biomass-burning PM2.5 emission estimation system using the Fire INventory from NCAR version 2.5 (FINNv2.5). The objectives of this study are threefold: (1) to construct a high-resolution (≤1 km) NRT biomass-burning PM2.5 emission inventory for Northern Thailand; (2) to assess its temporal and spatial consistency with ground-based PM2.5 measurements and satellite fire observations; and (3) to examine its potential utility for informing environmental health risk management. The developed system captured short-lived, high-intensity burning episodes that defined the haze crisis, revealing a distinct peak period from late February to early April. Cumulative emissions from January to April 2024 exceeded 250,000 tons, dominated by Chiang Mai (25.8%) and Mae Hong Son (25.5%), which together contributed 51.3% of regional emissions. Strong correspondence with MODIS/VIIRS FRP (r = 0.79) confirmed the reliability of the NRT emission signal, while regression against observed PM2.5 concentrations indicated a substantial background burden (intercept = 40.41 μg m-3) and moderate explanatory power (R2 = 0.448), reflecting additional meteorological and transboundary influences. Translating these relationships into operational metrics, an Emission Control Threshold of 1518 tons day-1 was derived to guide targeted burn permitting and reduce population exposure during peak-risk periods. This NRT biomass-burning PM2.5 emission estimation framework offers timely emissions information that may support decision makers in environmental health risk management, including the development of early warnings, adaptive burn-permit strategies, and more coordinated responses across Northern Thailand.
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