Assessment of Transboundary PM2.5 from Biomass Burning in Northern Thailand Using the WRF-Chem Model

Abstract

Air pollution, particularly PM2.5, poses a significant environmental and public health concern, particularly in northern Thailand, where elevated PM2.5 levels are prevalent during the dry season (January-May). This study examines the influx and patterns of transboundary biomass burning PM2.5 (TB PM2.5) in this region during the 2019 dry season using the WRF-Chem model. The model's reliability was confirmed through substantial correlations between model outputs and observations from the Pollution Control Department (PCD) of Thailand at 10 monitoring stations. The findings indicate that TB PM2.5 significantly influences local PM2.5 levels, often surpassing contributions from local sources. The influx of TB PM2.5 began in January from southern directions, intensifying and shifting northward, peaking in March with the highest TB PM2.5 proportions. Elevated levels persisted through April and declined in May. Border provinces consistently exhibited higher TB PM2.5 concentrations, with Chiang Rai province showing the highest average proportion, reaching up to 45%. On days when PM2.5 levels were classified as 'Unhealthy for Sensitive Groups' or 'Unhealthy', TB PM2.5 contributed at least 50% to the total PM2.5 at all stations. Notably, stations in Chiang Rai and Nan showed detectable TB PM2.5 even at 'Very Unhealthy' levels, underscoring the significant impact of TB PM2.5 in the northern border areas. Effective mitigation of PM2.5-related health risks requires addressing PM2.5 sources both within and beyond Thailand's borders.

Keywords: PM2.5; WRF-Chem model; biomass burning; transboundary air pollution.

Figure 1

Study area (northern Thailand) and the surrounding area within WRF-Chem Domain 01, including the MODIS fire hotspot data from January to May 2019.

Figure 2

Location of the PCD air quality monitoring stations in the study area (northern Thailand).

Figure 3

Statistical relationship heatmap between observed and model data for 10 PCD stations. The coefficient r represents, in the range of 0–1, a color gradient from red to green (r = 1 refers to perfect association); the RMSE represents, in the range of minimum–maximum value, the color gradient from green to red; and the mean bias represents, in the range of minimum–maximum value, the color gradient from blue to red (optimal RMSE and bias when being 0).

Figure 4

Monthly averaged TB PM2.5 concentrations in units µg/m³ (upper) and percentages (lower) from January to May 2019.

Figure 5

Boxplot of TB PM2.5 for the 9 provinces of northern Thailand.

Figure 5

Boxplot of TB PM2.5 for the 9 provinces of northern Thailand.

Figure 6

Number of days affected by transboundary (TB) PM2.5 at 10 PCD monitoring stations based on specified criteria. The darker red shaded indicates the greater number of days.