Analysis of roadside air pollutant concentrations and potential health risk of exposure in Hanoi, Vietnam

Understanding polycyclic aromatic hydrocarbon accumulation in road dust of a tropical megacity in southern Vietnam: Implications on environmental management

This study investigated the characteristics of 23 PAHs in road dust from various areas in Ho Chi Minh City (HCMC), focusing on spatial distribution, pollution levels, human health risks, and source apportionment. PAH levels in urban samples (residential and industrial sites) ranged from 208 to 7665 (μg/kg), significantly higher than background levels (135 ± 42.2 μg/kg). A west > east gradient in PAH distribution, particularly in crowded traffic intersections, suggested traffic activities as a major source. Pollution load indices indicated moderate to very high pollution in most urban sites. Incremental lifetime cancer risk assessments showed moderate to high risks, especially for children. Statistical analyses and diagnostic ratios identified vehicular emissions as the primary PAH sources, with Positive Matrix Factorization analysis attributing 46.6% to gasoline vehicles, 21.9% to diesel vehicles and petroleum evaporation, 18.3% to tar oil, and 10.2% to coal burning. This study fills a significant information gap on PAHs in road dust, which has not been previously reported in southern Vietnam, specifically in HCMC-a dynamic and rapidly developing city in Southeast Asia. The findings highlight the need for synchronized management and technical solutions to mitigate PAH risks in road dust, contributing valuable knowledge on PAH accumulation in a major southern city of Vietnam.

Urban air pollution evaluation in downtown streets of a medium-sized Latin American city using AERMOD dispersion model

The transport sector is considered the largest contributor of air pollutants in urban areas, mainly on-road vehicles, affecting the environment and human health. Bahía Blanca is a medium-sized Latin American city, with high levels of traffic in the downtown area during peak hours. In this regard, it is necessary to analyze air pollution using an air quality model considering that there are no air pollutant measurements in the central area. Furthermore, this type of study has not been carried out in the region and since the city is expected to grow, it is necessary to evaluate the current situation in order to make effective future decisions. In this sense, the AERMOD model (US-EPA version) and the RLINE source type were used in this work. This study analyzes the variations of pollutant concentrations coming from mobile sources in Bahía Blanca's downtown area, particularly carbon monoxide (CO) and nitrogen oxides (NOx) during the period Jul-2020 to Jun-2022. It is interesting to note the results show the maximum concentration values detected are not directly associated with maximum levels of vehicle flow or emission rates, which highlights the importance of meteorological parameters in the modeling. In addition, alternative scenarios are proposed and analyzed from a sustainable approach. Regarding the scenario analysis, it can be concluded that diesel vehicles have a large influence on NOx emissions. Moreover, restrictions as strict as those proposed for a Low Emission Zone would be less applicable in the city than alternative temporary measures that modify traffic at peak hours.

Effect of ambient air pollution on hospital admission for respiratory diseases in Hanoi children during 2007-2019

Air pollution poses a threat to children's respiratory health. This study aims to quantify the association between short-term air pollution exposure and respiratory hospital admissions among children in Hanoi, Vietnam, and estimate the population-attributable burden using local data. A case-crossover analysis was conducted based on the individual records where each case is their own control. The health data was obtained from 13 hospitals in Hanoi and air pollution data was collected from four monitoring stations from 2007 to 2019. We used conditional logistic regression to estimate Percentage Change (PC) and 95% Confidence Interval (CI) in odd of hospital admissions per 10 μg/m3 increase in daily average particulate matter (e.g. PM1, PM2.5, PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), 8-h maximum Ozone and per 1000 μg/m3 increase in daily mean of Carbon Monoxide (CO). We also calculated the number and fraction of admissions attributed to air pollution in Hanoi by using the coefficient at lag 0. A 10 μg/m3 increase in the concentration of PM10, PM2.5, PM1, SO2, NO2, O3 8-h maximum and 1000 μg/m3 increase in CO concentration was associated with 0.6%, 1.2%, 1.4%, 0.8%, 1.6%, 0.3%, and 1.7% increase in odd of admission for all respiratory diseases among children under 16 years at lag 0-2. All PM metrics and NO2 are associated with childhood admission for pneumonia and bronchitis. Admissions due to asthma and upper respiratory diseases are related to increments in NO2 and CO. For attributable cases, PM2.5 concentrations in Hanoi exceeding the World Health Organization Air Quality Guidelines accounted for 1619 respiratory hospital admissions in Hanoi children in 2019. Our findings show that air pollution has a detrimental impact on the respiratory health of Hanoi children and there will be important health benefits from improved air quality management planning to reduce air pollution in Vietnam.

Large spatio-temporal variations of size-resolved particulate matter and volatile organic compounds in urban area with heavy traffic

A monitoring campaign, the first of this kind for a heavy traffic urban area of Vietnam, was conducted which generated nearly 200 daily filter samples of PM_2.5, PM₁₀, and black carbon (BC), 1300 online hourly PMx (PM₁₀, PM_2.5, and PM₁), 900 hourly/bi-hourly BTEX data, 700 h of traffic counts, and online meteorology records. PMx and BTEX levels show large horizontal gradients across this small urban area of 300 m width suggesting that the pollution data should be generated with sufficient spatial resolutions for assessment of the exposure and health effects. This paper focuses on analyzing PMx with reference to the previously published BTEX to provide a more complete picture of the traffic-related pollution in the area. Spatio-temporal variations of pollutants are analyzed in relation to traffic flows and fleet compositions, weekday-weekend effects, local and regional meteorology. PM₁₀ and BTEX levels had larger variations between the sites indicating their stronger associations with the traffic activities than the finer particles. Twenty-four-hour (24 h) PM_2.5 levels ranged between 19 and 191 µg/m³ with high PM₁/PM_2.5 ratios of above 0.8 at ambient site (AA) and above 0.7 at roadsides. Multivariate relationship analysis (PCA) for the bi-hourly datasets of meteorology, traffic flows, and pollutant levels indicated overwhelming influence of on-road traffic fleet compositions on the roadside pollutants levels. At AA, PCA results showed a complex interaction between local emissions, meteorological conditions, and regional/long-range transport. Higher pollution levels were associated with the airmass types having the continental origin and pathways.

A Comprehensive 2018-Based Vehicle Emission Inventory and Its Spatial-Temporal Characteristics in the Central Liaoning Urban Agglomeration, China

Rapid economic expansion and urbanisation have seriously affected the atmospheric environmental quality of the Central Liaoning Urban Agglomeration (CLUA). This study aimed to establish a detailed vehicle emission inventory of the CLUA with a 3 km × 3 km gridded spatiotemporal distribution. A top-down methodology using vehicle kilometres travelled annually, emission factors, and activity data of each city was established. Carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO₂), ammonia (NH₃), volatile organic compounds (VOCs), particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀), Black Carbon (BC), and organic carbon (OC) emissions were 291.0, 221.8, 3.6, 2.2, 42.8, 9.3, 10.3, 5.2, and 1.6 Gg in 2018, respectively. The contribution of diesel heavy-duty trucks to NOx, SO₂, PM_2.5, PM₁₀, BC, and OC emissions was greater than 54.5%, the largest contribution of all vehicles. Gasoline small passenger vehicles were the primary contributor to CO, VOC, and NH₃ emissions, contributing 37.3%, 39.5%, and 75.3% of total emissions, respectively. For emission standards, Pre-China 1 vehicles were the largest contributor to CO and VOC emissions and China 3 vehicles contributed the largest amount of NOx, SO₂, PM_2.5, PM₁₀, BC, and OC emissions. The spatial distribution of pollutants showed "obvious lines" and grids with high emissions were concentrated in expressways, national highways, and provincial highways. The temporal variation showed morning-evening peaks during diurnal variations, which was consistent with resident behaviour. This work can help us understand vehicular emission characteristics of the CLUA and provide basic data for air quality modelling. Future research should investigate traffic flow by vehicle types and emission factors at a local level, which will be helpful for transport management planning.

Bus Crash Severity in Hanoi, Vietnam

Recently, there has been an increasing interest in targeting the safety of bus operations worldwide; however, little is known about the determinants of the bus crash severity in developing countries. By estimating an ordered logit model using the bus-involved collision data in Hanoi (Vietnam), spanning the period from 2015 to 2019, this study investigates various factors associated with the crash severity. The results reveal that the severity risk increases for (1) large buses, (2) raining conditions, (3) evening or night, (4) sparse traffic, (5) non-urban areas, (6) roads with at least three lanes, (7) curved roads, (8) two-way roads without a physical barrier, (9) head-on collision, and (10) pedestrian-related crashes. Aside from confirming the crucial roles of a wide range of factors, this research has examined the effects of two determinants (traffic density and crash area) that have not been considered for the cases of developing countries previously. Based on the findings on the impacts of factors, a series of policy recommendations regarding improving road conditions in non-urban areas, promoting walking infrastructure, reminders of high-risk situations for drivers, safety notes when improving bus service quality, and recording bus-related crashes are proposed.