Vol. 16 No. 01 (2026): Journal of Materials & Construction
##common.pageHeaderLogo.altText##
JOURNAL OF MATERIALS & CONSTRUCTION

ISSN: 2734-9438

Website: www.jomc.vn

Temporal Variation of Ambient PM2.5 and PM10 and Associated Non-Carcinogenic Health Risks in Thai Nguyen City, Vietnam

Bui Thi Hieu , Nguyen Khanh Long , Nguyen Duc Luong , Nguyen Thi Hue

Keywords:

PM2.5
Seasonal variation
Non-carcinogenic health risk
Hazard quotient (HQ)
Thai Nguyen

Abstract

This study examined the monthly and seasonal variations of ambient PM2.5 and PM10 concentrations in Thai Nguyen City and quantitatively assessed the associated non-carcinogenic health risks for different population groups in 2021. The results reveal a pronounced seasonal pattern in air quality, with elevated fine particulate matter PM2.5 concentrations during the dry and cold season. Monthly average PM2.5 levels exceeded the national regulatory limit (QCVN 05:2023/BTNMT) in most months, with severe pollution episodes observed in January and December, when concentrations were more than 2.6 to over three times higher than the permissible standard. These findings indicate that PM2.5 pollution in Thai Nguyen City is persistent and seasonally intensified, driven by unfavorable meteorological conditions combined with continuous emission sources such as traffic, industrial activities, and biomass burning. In contrast, PM10 concentrations remained below regulatory limits throughout the year, suggesting that fine particulate matter is the primary air pollutant of concern. Health risk assessment results show that, under normal conditions, exposure to particulate matter poses negligible health risks for infants, children, and adults. However, under worst-case scenarios, PM2.5 exposure leads to unacceptable health risks for infants and children, with Hazard Quotient values exceeding the safety threshold, while adults remain below this threshold. Overall, PM2.5 contributes substantially more to health risks than PM10 due to its higher toxicity and deeper penetration into the respiratory system.

User Navigation

How to Cite

Bui Thi Hieu, Nguyen Khanh Long, Nguyen Duc Luong, & Nguyen Thi Hue. (2026). Temporal Variation of Ambient PM2.5 and PM10 and Associated Non-Carcinogenic Health Risks in Thai Nguyen City, Vietnam. JOURNAL OF MATERIALS & CONSTRUCTION, 16(01). https://doi.org/10.54772/jomc.v16i01.1328

References

  1. Alahamade W, Lake I, Reeves CE, Iglesia BD La (2021) Evaluation of multivariate time series clustering for imputation of air pollution data. 265–285
  2. Aldabe J, Elustondo D, Santamaría C, et al (2011) Chemical characterisation and source apportionment of PM2.5 and PM10 at rural, urban and traffic sites in Navarra (North of Spain). Atmos Res 102:191–205. https://doi.org/10.1016/j.atmosres.2011.07.003
  3. Alsaber AR, Pan J (2021) Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset : A Case Study of Kuwait Environmental Data ( 2012 to 2018 )
  4. Anh LH, Nam DT, Luan VN (2019) Ô nhiễm bụi PM tại một số thành phố ở Việt Nam - Biến động theo không gian, thời gian của PM10 và PM2.5. Tạp chí Môi trường
  5. Arriagada P, Karelovic B, Link O (2021) Automatic gap-filling of daily streamflow time series in data-scarce regions using a machine learning algorithm. J Hydrol 598:126454. https://doi.org/10.1016/j.jhydrol.2021.126454
  6. Bui QT, Nguyen DL, Bui TH (2022) Seasonal Characteristics of Atmospheric PM 2 . 5 in an Urban Area of Vietnam and the Influence of Regional Fire Activities
  7. Cesari D, Contini D, Genga A, et al (2012) Analysis of raw soils and their re-suspended PM10 fractions: Characterisation of source profiles and enrichment factors. Appl Geochemistry 27:1238–1246. https://doi.org/10.1016/j.apgeochem.2012.02.029
  8. Đăng TH, Hiền PTT, Quỳnh NT, et al (2024) ỨNG DỤNG GIS XÂY DỰNG BẢN ĐỒ Ô NHIỄM KHÔNG KHÍ THÀNH PHỐ THÁI NGUYÊN. TNU J Sci Technol 229:352–358. https://doi.org/10.34238/tnu-jst.9762
  9. Doove LL, Van Buuren S, Dusseldorp E (2014) Recursive partitioning for missing data imputation in the presence of interaction effects. Comput Stat Data Anal 72:92–104. https://doi.org/10.1016/j.csda.2013.10.025
  10. Fleming S, Thompson M, Stevens R, et al (2011) Normal ranges of heart rate and respiratory rate in children from birth to 18 years of age: a systematic review of observational studies. Lancet 377:1011–1018. https://doi.org/10.1016/S0140-6736(10)62226-X
  11. Galon-Negru AG, Olariu RI, Arsene C (2019) Size-resolved measurements of PM2.5 water-soluble elements in Iasi, north-eastern Romania: Seasonality, source apportionment and potential implications for human health. Sci Total Environ 695:133839. https://doi.org/10.1016/j.scitotenv.2019.133839
  12. Ha TM, Kühling I, Trautz D (2020) A systems approach toward climate resilient livelihoods: A case study in Thai Nguyen province, Vietnam. Heliyon 6:e05541. https://doi.org/10.1016/j.heliyon.2020.e05541
  13. Hien PD, Bac VT, Thinh NTH (2004) PMF receptor modelling of fine and coarse PM10 in air masses governing monsoon conditions in Hanoi, northern Vietnam. Atmos Environ 38:189–201. https://doi.org/10.1016/j.atmosenv.2003.09.064
  14. Hoang NK, Bui TTT (2022) Research on the impact of air pollution on social security in Thai Nguyen province. Minist Sci Technol Vietnam 64:41–45. https://doi.org/10.31276/VJST.64(4).41-45
  15. Hua V, Nguyen T, Dao M, et al (2024) The impact of data imputation on air quality prediction problem
  16. Jakhar R, Styszko K, Samek L, Szramowiat-Sala K (2025) Oxidative potential of PM1, PM2.5, and PM10 collected in car and tram tunnels to analyse their impact on public health. Sci Rep 15:21773. https://doi.org/10.1038/s41598-025-09037-4
  17. Kelly FJ, Fussell JC (2012) Size, source and chemical composition as determinants of toxicity attributable to ambient particulate matter. Atmos Environ 60:504–526. https://doi.org/10.1016/j.atmosenv.2012.06.039
  18. Kim K-H, Kabir E, Kabir S (2015) A review on the human health impact of airborne particulate matter. Environ Int 74:136–143. https://doi.org/10.1016/j.envint.2014.10.005
  19. Li W, Wang C, Wang H, et al (2014) Distribution of atmospheric particulate matter (PM) in rural field, rural village and urban areas of northern China. Environ Pollut 185:134–140. https://doi.org/10.1016/J.ENVPOL.2013.10.042
  20. Liu Y, Li S, Sun C, et al (2018) Pollution level and health risk assessment of PM2.5-bound metals in baoding city before and after the heating period. Int J Environ Res Public Health 15:1–17. https://doi.org/10.3390/ijerph15102286
  21. Makkonen U, Vestenius M, Huy LN, et al (2023) Chemical composition and potential sources of PM2.5 in Hanoi. Atmos Environ 299:. https://doi.org/10.1016/j.atmosenv.2023.119650
  22. McNeill J, Snider G, Weagle CL, et al (2020) Large global variations in measured airborne metal concentrations driven by anthropogenic sources. Sci Rep 10:1–12. https://doi.org/10.1038/s41598-020-78789-y
  23. Morakinyo OM, Adebowale AS, Mokgobu MI, Mukhola MS (2017) Health risk of inhalation exposure to sub-10 µm particulate matter and gaseous pollutants in an urban-industrial area in South Africa: an ecological study. BMJ Open 7:e013941. https://doi.org/10.1136/bmjopen-2016-013941
  24. Nguyen TNT, Du NX, Hoa NT (2023) Emission Source Areas of Fine Particulate Matter (PM2.5) in Ho Chi Minh City, Vietnam. Atmosphere (Basel) 14:. https://doi.org/10.3390/atmos14030579
  25. Nguyen TPM, Bui TH, Nguyen MK, et al (2021) Impact of Covid-19 partial lockdown on PM 2.5, SO 2, NO 2, O 3, and trace elements in PM 2.5 in Hanoi, Vietnam. Environ. Sci. Pollut. Res. 1–11
  26. Park M, Joo HS, Lee K, et al (2018) Differential toxicities of fine particulate matters from various sources. Sci Rep 8:17007. https://doi.org/10.1038/s41598-018-35398-0
  27. Province TN (2023) Thai Nguyen Province statistical Yearbook 2022. Statistics Publishing House
  28. Sarti E, Pasti L, Rossi M, et al (2015) The composition of PM1 and PM2.5 samples, metals and their water soluble fractions in the bologna area (Italy). Atmos Pollut Res 6:708–718. https://doi.org/10.5094/APR.2015.079
  29. Shah AD, Bartlett JW, Carpenter J, et al (2014) Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study. Am J Epidemiol 179:764–774. https://doi.org/10.1093/aje/kwt312
  30. Srithawirat T, Latif MT, Sulaiman FR (2016) Indoor PM10 and its heavy metal composition at a roadside residential environment, Phitsanulok, Thailand. Atmósfera 29:311–322. https://doi.org/https://doi.org/10.20937/ATM.2016.29.04.03
  31. Suriyawong P, Chuetor S, Samae H, et al (2023) Airborne particulate matter from biomass burning in Thailand: Recent issues, challenges, and options. Heliyon 9:e14261. https://doi.org/10.1016/j.heliyon.2023.e14261
  32. Trần LL, Đỗ ĐM, Lê HTCH, et al (2023) ĐÁNH GIÁ TÁC ĐỘNG CỦA PHƠI NHIỄM Ô NHIỄM KHÔNG KHÍ DO GIAO THÔNG LÊN TRẺ EM 13-14 TUỔI THÔNG QUA CARBON TRONG ĐÀM. Tạp chí Y học Việt Nam 531:. https://doi.org/10.51298/vmj.v531i2.7207
  33. Tran N, Fujii Y, Xuan Le V, et al (2023) Annual Variation of PM2.5 Chemical Composition in Ho Chi Minh City, Vietnam Including the COVID-19 Outbreak Period. Aerosol Air Qual Res 23:. https://doi.org/10.4209/aaqr.220312
  34. Wu J-Z, Ge D-D, Zhou L-F, et al (2018) Effects of particulate matter on allergic respiratory diseases. Chronic Dis Transl Med 4:95–102. https://doi.org/https://doi.org/10.1016/j.cdtm.2018.04.001
  35. Yin X, Kang S, Rupakheti M, et al (2021) Influence of transboundary air pollution on air quality in southwestern China. Geosci Front 12:101239. https://doi.org/10.1016/j.gsf.2021.101239
  36. Zhang J, Zhou X, Wang Z, et al (2018) Trace elements in PM2.5 in Shandong Province: Source identification and health risk assessment. Sci Total Environ 621:558–577. https://doi.org/10.1016/j.scitotenv.2017.11.292
  37. Zhou Y, Tang Q, Zhao G (2023) Gap infilling of daily streamflow data using a machine learning algorithm (MissForest) for impact assessment of human activities. J Hydrol 627:130404. https://doi.org/10.1016/j.jhydrol.2023.130404