Understanding the seasonal dynamics of surface PM2.5 mass distribution and source contributions over Thailand

被引:2
|
作者
Bran, Sherin Hassan [1 ,2 ]
Macatangay, Ronald [2 ]
Chotamonsak, Chakrit [1 ,3 ,4 ]
Chantara, Somporn [1 ]
Surapipith, Vanisa [5 ]
机构
[1] Chiang Mai Univ, Fac Sci, Environm Sci Res Ctr, Chiang Mai 50200, Thailand
[2] Natl Astron Res Inst Thailand, Atmospher Res Unit, Chiang Mai 50180, Thailand
[3] Chiang Mai Univ, Fac Social Sci, Reg Ctr Climate & Environm Studies RCCES, Chiang Mai 50200, Thailand
[4] Chiang Mai Univ, Fac Social Sci, Dept Geog, Chiang Mai 50200, Thailand
[5] Asian Disaster Preparedness Ctr, Bangkok 10400, Thailand
关键词
PM2.5; Seasons; WRF-Chem; Emission sources; Thailand; FOREST-FIRES; BIOMASS; EMISSIONS; TRANSPORT; AEROSOLS; SOUTH;
D O I
10.1016/j.atmosenv.2024.120613
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The escalating levels of aerosols have emerged as a significant concern for climate extremes in the Southeast Asian regions, particularly accentuated during El Nino Years. In this study, we utilized a combination of atmospheric measurements and modeling to investigate the seasonal and geographical distribution of PM 2.5 mass concentrations and its primary contributors across Thailand during La Nina (2017) and El Nino (2019) years. Our findings revealed the highest daily mean surface PM 2.5 mass concentration during the summer season across most regions, followed by winter, and the lowest levels during the rainy season. Notably, a significant shift in daily mean PM 2.5 mass was observed from 2017 to 2019 across all seasons, with a pronounced increase of 70.9% over northern Thailand during the summer, attributed to heightened biomass burning (BB) contributions. In terms of source attribution for PM 2.5 mass, the primary contributors in 2017 were BB at 34.3%, followed by anthropogenic emissions (AE) at 32.4%, and natural emissions (NE) at 30.1%. However, in 2019, the BB contribution surged to 47.4% nationwide. During El Nino years, BB played a significant role in shaping concentrations during summer and winter, while NE dominated the rainy season. An important implication of our findings is the significant potential for reducing daily and annual mean PM 2.5 mass levels throughout Thailand by effectively reducing BB emissions.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Fresh and aged PM2.5 and their ion composition in rural and urban atmospheres of Northern Thailand in relation to source identification
    Chansuebsri, Sarana
    Kraisitnitikul, Pavidarin
    Wiriya, Wan
    Chantara, Somporn
    CHEMOSPHERE, 2022, 286
  • [22] Seasonal variation of the chemical content and source identification of PM2.5 in a mixed landuse in Iran
    Shahne, M. Zare
    Haghighat, N. R.
    Hosseini, V.
    Uzu, G.
    Taheri, A.
    Darfeuil, S.
    Ginot, P.
    Besombes, J. -L.
    Pin, M.
    Jaffrezo, J. -L.
    Shamloo, A.
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2024, : 4157 - 4172
  • [23] Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations
    Li, Sixuan
    Chen, Lulu
    Huang, Gang
    Lin, Jintai
    Yan, Yingying
    Ni, Ruijing
    Huo, Yanfeng
    Wang, Jingxu
    Liu, Mengyao
    Weng, Hongjian
    Wang, Yonghong
    Wang, Zifa
    ATMOSPHERIC ENVIRONMENT, 2020, 222
  • [24] Molecular distribution and seasonal variation of hydrocarbons in PM2.5 from Beijing during 2006
    Li, Yushan
    Cao, Junji
    Li, Jianjun
    Zhou, Jiamao
    Xu, Hongmei
    Zhang, Renjian
    Ouyang, Zhiyun
    PARTICUOLOGY, 2013, 11 (01) : 78 - 85
  • [25] Source characterization of PM10 and PM2.5 mass using a chemical mass balance model at urban roadside
    Srimuruganandam, B.
    Nagendra, S. M. Shiva
    SCIENCE OF THE TOTAL ENVIRONMENT, 2012, 433 : 8 - 19
  • [26] Impact of assimilating multi-source observations on meteorological and PM2.5 forecast over Central China
    Liu, Jian
    Hong, Jia
    Mao, Feiyue
    Gong, Wei
    Shen, Longjiao
    Liang, Shengwen
    Chen, Jiangping
    ATMOSPHERIC RESEARCH, 2020, 241
  • [27] Characterization and Source Apportionment Analysis of PM2.5 and Ozone Pollution over Fenwei Plain, China: Insights from PM2.5 Component and VOC Observations
    Xu, Litian
    Wang, Bo
    Wang, Ying
    Zhang, Huipeng
    Xu, Danni
    Zhao, Yibing
    Zhao, Kaihui
    TOXICS, 2025, 13 (02)
  • [28] Chemical composition, source distribution and health risk assessment of PM2.5 and PM10 in Beijing
    Zhen, Shaosong
    Luo, Min
    Xin, Futao
    Ma, Lingling
    Xu, Diandou
    Cheng, Xiaomeng
    Shao, Yang
    ATMOSPHERIC POLLUTION RESEARCH, 2025, 16 (04)
  • [29] Seasonal source analysis of nitrogen and carbon aerosols of PM2.5 in typical cities of Zhejiang, China
    Zou, Deliang
    Sun, Qinqin
    Liu, Jinsong
    Xu, Chao
    Song, Shuang
    CHEMOSPHERE, 2022, 303
  • [30] Seasonal characteristics of PM1, PM2.5, and PM10 over Varanasi during 2019-2020
    Chauhan, Prashant Kumar
    Kumar, Akhilesh
    Pratap, Vineet
    Singh, Abhay Kumar
    FRONTIERS IN SUSTAINABLE CITIES, 2022, 4