Evidence map›Paper›PMID 41600633›Full record

ArticleToxics2026

Near Real-Time Biomass Burning PM2.5 Emission Estimation to Support Environmental Health Risk Management in Northern Thailand Using FINNv2.5.

Chakrit Chotamonsak, Punnathorn Thanadolmethaphorn, Duangnapha Lapyai, Soottida Chimla

Abstract read
In one paragraph

Article in Toxics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chakrit ChotamonsakDepartment of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai 50200, Thailand.ORCID 0000-0002-3170-0056
Punnathorn ThanadolmethaphornOffice of Strategy Management, Chiang Mai University, Chiang Mai 50200, Thailand.ORCID 0009-0004-4895-9437
Duangnapha LapyaiOffice of Research Administration, Chiang Mai University, Chiang Mai 50200, Thailand.ORCID 0009-0001-7586-9902
Soottida ChimlaDepartment of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai 50200, Thailand.

Funding

National Research Council of Thailand (NRCT) N25A680014
6 · The paper itself

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

Indexed as

biomass burningenvironmental health riskFINNv2.5near-real-time emission estimationNorthern ThailandPM2.5 emissions

Identifiers

PMID41600633
PMCPMC12846012

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.