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Spatiotemporal distribution of PM2.5 in Ho Chi Minh city: Model - Observation comparison and the influence of Biomass Burning and Transboundary Transport

Linh Do Thi Thuy 1, 2, *
Tam Nguyen Thoai 1, 2
Nguyen Nguyen Ngoc Thao 1, 2
Nhang Nguyen Thi Cam 1
  1. Institute for Environment and Resources (IER), Vietnam National University, Ho Chi Minh City, Vietnam
  2. Department of Science and Technology, Vietnam National University, Ho Chi Minh City, Vietnam
Correspondence to: Linh Do Thi Thuy, Institute for Environment and Resources (IER), Vietnam National University, Ho Chi Minh City, Vietnam; Department of Science and Technology, Vietnam National University, Ho Chi Minh City, Vietnam. Email: [email protected].
Volume & Issue: Vol. 10 No. 1 (2026) | Page No.: 1147-1155 | DOI: 10.32508/vnuhcmj-ees.v10i1.851
Published: 2026-06-22

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Copyright The Author(s) 2018. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

Understanding the spatiotemporal characteristics and regional influences of fine particulate matter (PM2.5) is crucial for effective air quality management in rapidly urbanizing cities. This study evaluates the spatiotemporal distribution of PM2.5 in Ho Chi Minh City in 2022 by integrating multi-site observations with a coupled meteorology–chemistry simulation. Results indicate that high PM2.5 concentrations are concentrated in the urban center and traffic - industrial hotspots, gradually decreasing toward suburban and coastal areas. Seasonal variability is pronounced, with elevated concentrations during the dry season (January and December) and lower levels during the rainy season (September), consistent with observations. A pollution episode occurred in January 2022, during which PM2.5 increased to 31 - 46 µg m-3 alongside rises in O3 and CO. Analysis of HYSPLIT trajectories, MERRA - 2 data, and FIRMS fire counts suggests that northeast air masses combined with regional biomass burning were likely major contributors to this episode. The WRF - CMAQ model reproduces the overall spatial patterns but tends to smooth extreme values and reduce spatial contrasts. This study highlights the importance of refining emission inventories, improving meteorological parameterizations, and enhancing coordinated pollution control at both local and regional scales.

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