Seasonal air pollution dynamics, source apportionment, and health risk in industrial zones of southern Vietnam: a five-year integrated assessment

Linking ambient air pollution to health risk burden: A comparative study across urban and semi-urban regions of Karnataka, India

Introduction: Ambient air pollution poses significant public health challenges across urban and semi-urban India. Karnataka, encompassing coastal, plateau, highland, and semi-arid environments, provides an ideal setting for evaluating regional air quality variability and associated health risks. This study assessed the spatio-temporal characteristics of ten criteria and hazardous air pollutants measured at five Central Pollution Control Board (CPCB) Continuous Ambient Air Quality Monitoring Stations (CAAQMS) across Karnataka during 2024. Materials and methods: Monthly mean concentrations of Particulate Matters (PM₂.₅, PM₁₀), Nitrogen dioxide (NO₂), Sulfur dioxide (SO₂), Carbon monoxide (CO), Ozone (O₃), Ammonia (NH3), and benzene were analysed across four India Meteorological Department (IMD) seasons. Serial autocorrelation was assessed using the lag-1 Kendall statistic prior to applying the Mann–Kendall test and Sen's slope estimator as an exploratory assessment of intra-annual monotonic tendencies. Spatial variability was evaluated using one-way ANOVA with Tukey's HSD post-hoc test and validated using the Kruskal–Wallis test. Inhalation health risks were assessed using the USEPA Risk Assessment Guidance for Superfund (RAGS) methodology by estimating Hazard Quotient (HQ), Hazard Index (HI), and Lifetime Cancer Risk (LCR). Results: Bengaluru recorded the highest annual mean PM₂.₅ (40.2 μg/ m³) and PM₁₀ (80.4 μg/m³) concentrations, with PM₂.₅ equal to the CPCB National Ambient Air Quality Standard (NAAQS) and PM₁₀ exceeding it by approximately 34%. Annual mean PM₂.₅ concentrations at all stations exceeded the WHO 2021 Air Quality Guideline (15 μg/m³). The southwest monsoon produced the greatest reduction in particulate concentrations. Exploratory Mann–Kendall analysis yielded negative Sen's slopes for PM₂.₅ at all stations, although none were statistically significant (p>0.05). One-way ANOVA confirmed significant spatial heterogeneity among monitoring stations (p < 0.001). Screening-level health risk assessment indicated HI values >1.0 at all stations (1.756–3.290). Estimated PM₂.₅ LCR ranged from 1.76 × 10⁻³ to 3.34 × 10⁻³ and represents hypothetical upper-bound screening estimates rather than regulatory cancer risk values. Conclusion: Particulate matter remains the dominant air quality concern across Karnataka, particularly in Bengaluru. Strengthened emission control measures, continued multi-year monitoring, and agricultural ammonia management are recommended to support long-term improvements in air quality and public health.

Twenty-Five Years of Air Quality in Bangladesh: Trends, Seasonality, and Spatial Pollution Regimes

Air pollution is one of Bangladesh's most pressing environmental problems, yet few studies have examined it at a national scale over a long time span. To describe trends, seasonality, geographic patterns, and pollution regimes, this study examines 25 years of hourly air quality data (2000-2025), covering over 3.19 million records, eight pollutants, and 103 cities monitored from 2022 onward following expansion from a single Dhaka station. The composite AQI series showed no significant long-term trend, an artifact of this network expansion rather than a real flattening of pollution, since Dhaka's own AQI rose steadily before the network grew. Seasonality was strong and highly significant, as AQI peaked in January (162.26) and fell to its lowest in July (61.47), tracking the dry and monsoon seasons. Geographically, southeastern coastal cities, including Teknaf and Bandarban, consistently recorded the lowest AQI levels. Dhaka remained the most polluted city, and air quality improved progressively with distance from the capital. K-means clustering of city-level AQI trajectories identified four distinct pollution regimes, ranging from cleaner coastal regions to a rapidly deteriorating Dhaka-Narsingdi cluster with an average increase of 1.84 AQI per year. Correlation analysis showed that PM2.5 and PM10 were the dominant contributors to AQI variation, and so combustion-related emissions are the primary target for air quality management and policy intervention.

Interplay Between Meteorology and Seasonality in Urban Air Pollution Across Selected Cities in East, South, and Southeast Asia: A Comparative Review

Air pollution is a growing environmental issue in rapidly urbanizing Asian cities, where meteorological conditions and seasonal variability strongly influence pollutant concentrations. This review synthesizes published evidence on the interactions between meteorology, seasonality, and urban air pollution across selected cities in East Asia, South Asia, and Southeast Asia. The literature was collected from major scientific databases and organized according to meteorological drivers, seasonal characteristics, and dominant emission sources. Particular emphasis was placed on particulate matter (PM2.5 and PM10), SO2, NO2, NOx, CO, and O3. The reviewed studies indicate that wind speed and direction, precipitation, temperature, atmospheric stability, and monsoon circulation strongly influence pollutant transport, dispersion, and removal. Pollutant concentrations generally reach their highest in winter due to stagnant conditions and higher human emissions. In contrast, the summer and monsoon seasons tend to have lower PM levels due to better atmospheric mixing and wet deposition. Regional differences in dominant sources were also observed, including coal combustion and heating in East Asia, traffic and biomass burning in South Asia, and biomass burning and transboundary transport in Southeast Asia. These findings highlight the importance of seasonally adaptive and region-specific air quality management strategies in Asian cities.

Impact of air pollution on sustainable development and environmental justice: Insights from industrial cities of Bangladesh

Integrated assessment of air pollution dynamics and health impacts in Myanmar: Evidence from ground monitoring, satellite observations, and modeling.

Least Developed Countries (LDCs), such as Myanmar, experience disproportionately high air pollution burdens due to limited regulatory capacity, inadequate monitoring, and political instability. This study provides a multi-source assessment of air pollution dynamics and potential health impacts in Myanmar, combining ground-based monitoring, satellite observations, and statistical modeling to inform evidence-based policymaking. Ground-based data (2019-2024) from two monitoring stations in Yangon revealed an average PM2.5 concentration of 24.4 μg/m3 (SD = 18.6), with the highest seasonal mean in winter (39.4 μg/m3; November-February). Analysis of particulate matter (PM) components showed high contributions of sulfate (SO42-) in both winter and summer, followed by nitrate (NO3-) in winter and Ca2+ in summer. A health impact assessment estimated that compliance with the WHO PM2.5 guideline (5 μg/m3) could have prevented 2,106 (95% confidence interval 345-3,818) premature deaths (aged ≥ 30) annually in Yangon during 2020-2021. A generalized additive model revealed that relative humidity and wind speed were significantly associated with PM2.5, whereas the daily maximum 8 h average (MDA8) O3 showed a limited meteorological association with relative humidity. National daily means of TROPOMI HCHO and NO2 were strongly correlated (Pearson's r = 0.754; p = 0.001), and HCHO/NO2 ratios indicated predominantly NOx-sensitive regimes across Myanmar. These findings suggest that O3 air quality can be substantially improved by reducing NOx emissions. Despite Myanmar's limited data, this study provides a comprehensive spatiotemporal assessment of air pollution hotspots and their associated health burdens, thereby informing targeted emission control strategies.

Air pollution risks to wheat and mustard in Delhi agricultural airshed during the winter cropping season (2022–2025)