Microplastic pollution has become a worldwide concern. However, studies on the distribution of microplastics (MPs) from inland water to the ocean and their affiliated polycyclic aromatic hydrocarbons (PAHs) are still limited in Vietnam. In this study, we investigated the distribution of MPs and PAHs associated with MPs in canals, Saigon River, and Can Gio Sea. MPs were found at all sites, with the highest average abundance of MPs being 104.17 ± 162.44 pieces/m³ in canals, followed by 2.08 ± 2.22 pieces/m³ in the sea, and 0.60 ± 0.38 pieces/m³ in the river. Fragment, fiber, and granule were three common shapes, and each shape was dominant in one sampling area. White was the most common MP color at all sites. A total of 13 polymers and co-polymers were confirmed, and polyethylene, polypropylene, and ethylene-vinyl acetate were the three dominant polymers. The total concentration of MPs-affiliated PAHs ranged from 232.71 to 6448.66, from 30.94 to 8940.99, and from 432.95 to 3267.88 ng/g in Can Gio sea, canals, and Saigon River, respectively. Petrogenic sources were suggested as a major source of PAHs associated with MPs in Can Gio Sea, whereas those found in Saigon River and canals were from both petrogenic and pyrogenic sources.

The in-traffic microenvironment can enhance personal exposure to fine particulate matter (PM). With this study, we aimed to calibrate a DustTrak instrument (DustTrak 8533 DRX Aerosol Monitor, TSI Incorporated, Shoreview, MN, USA) and low-cost sensors (AS-LUNG-P sensors) and then assess inhalation exposure to PM_2.5 and PM₁ for different commuters in central areas of Ho Chi Minh City (HCM). The DustTrak instrument and low-cost sensors were calibrated using a gravimetric method under side-by-side conditions. Relationships between the DustTrak signals and PM concentrations measured by the gravimetric method were identified using simple linear regression models for PM_2.5 (R² = 0.998, p-value < 0.05) and PM₁ (R² = 0.989, p-value < 0.05). Meanwhile, PM concentrations determined by the AS-LUNG-P sensors and the gravimetric method were correlated using two-segmented linear regressions. To obtain the corresponding two-segment regression equations, the response of the AS-LUNG-P sensors was compared with the corrected DustTrak data. The coefficient of variation (CV) evaluated for all sensors was smaller than 10%, indicating that the data were applicable for particle assessment. For inhalation exposure assessment, the results showed that commuters using open transport modes, such as bikes, motorbikes, and walking, were exposed to more PM than those using closed transport modes (e.g., cars). Specifically, the bicyclists had the highest inhaled doses of PM among the open transport groups. PM exposure levels in the morning were higher than in the afternoon. Additionally, exposure levels to PM concentrations rapidly increased when passing through intersections of major roads and moderately decreased when using surgical facemasks.

Introduction: Continuous monitoring provides real-time data which is helpful for measuring air quality; however, these systems are often very expensive, especially for developing countries such as Vietnam. The use of low-cost sensors for monitoring air pollution is a new approach in Vietnam and this study assesses the utility of low-cost, light-scattering-based, particulate sensors for measuring PM2.5 concentrations in Ho Chi Minh City. Methods: The low-cost sensors were compared with both a Beta attenuation monitor (BAM) reference method and a gravimetric method during the rainy season period of October to December 2018. Results: The results showed that there was a very strong correlation between two low-cost sensors (R = 0.97, slope = 1.0), and that the sensor precision varied from 0 to 21.4% with a mean of 3.1%. Both one-minute averaged data and one-hour averaged data showed similar correlations between sensors and BAM (R2 = 0.62 and 0.69, respectively), while 24-hour averaged data showed excellent agreement (R2 = 0.95, slope = 1.05). In addition, we also found a strong correlation between those instruments and a gravimetric method using 24-hour averaged data. A linear regression was used to calibrate the 24-hour averaged sensor data and, once calibrated, the bias dropped to zero. Conclusion: These results show that low-cost sensors can be used for daily measurements of PM2.5 concentrations in Ho Chi Minh City. The effect of air conditions, such as temperature and humidity, should be conducted. Moreover, technical methods to improve time resolution of lowcost sensors need to be developed and applied in order to provide real-time measurements at an inexpensive cost.