Inlaung Kevalin, Chotamonsak Chakrit, Macatangay Ronald, Surapipith Vanisa
Office of Research Administration, Chiang Mai University, Chiang Mai 50200, Thailand.
Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand.
Toxics. 2024 Jun 26;12(7):462. doi: 10.3390/toxics12070462.
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.
空气污染,尤其是细颗粒物(PM2.5),是一个重大的环境和公共卫生问题,在泰国北部尤为突出,该地区旱季(1月至5月)的PM2.5水平普遍升高。本研究使用WRF-Chem模型,考察了2019年旱季该地区跨境生物质燃烧产生的PM2.5(TB PM2.5)的流入情况和模式。通过该模型输出结果与泰国污染控制部门(PCD)在10个监测站的观测数据之间的高度相关性,证实了该模型的可靠性。研究结果表明,TB PM2.5对当地PM2.5水平有显著影响,其贡献往往超过本地来源。TB PM2.5于1月从南部方向开始流入,强度增加并向北转移,3月达到峰值,此时TB PM2.5占比最高。高浓度水平一直持续到4月,5月有所下降。边境省份的TB PM2.5浓度一直较高,清莱府的平均占比最高,达到45%。在PM2.5水平被归类为“对敏感人群不健康”或“不健康”的日子里,所有监测站的TB PM2.5对总PM2.5的贡献至少为50%。值得注意的是,清莱府和难府的监测站即使在“非常不健康”的水平下也能检测到TB PM2.5,这突出了TB PM2.5在北部边境地区的重大影响。有效降低与PM2.5相关的健康风险需要解决泰国境内外的PM2.5来源问题。