ANALYSIS OF CHANGES IN THE LEVEL OF AIR POLLUTION BY PM2.5 FINE PARTICULATE MATTER IN KYIV UNDER WARTIME IMPACT

Changes of Urban and Suburban Air Quality Patterns during the Pandemic Year 2020: Longitudinal Evidence from Three Romanian Citie

Urban areas must develop and implement air pollution-reduction strategies in order to comply with progressively stricter air quality standards. Various measures imposed during the lockdowns associated to COVID-19 pandemic worldwide made the year 2020 an exceptional period for global air pollution: air pollutant emission patterns were significantly and differently altered. Atmospheric pollutant levels varied from the lowest to the highest values. Within this context, present study aim is to emphasize comparatively the changes in major air pollutants’ concentrations PM10, PM2.5, NO, NO2, NOx, CO, SO2, O3 in three important urban centers (Bucharest, Brașov, Iași) in Romania during 2020. The contrast in mass concentrations of major air pollutants in the urban and the suburban areas of above cities has been studied using longitudinal analysis, probability density functions and change point analysis. The study outcomes extend the knowledge about air pollution at local/regional scale and are of help in designing air pollution control strategies.

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.

Investigating the pollution and air quality situation in Kabul city: Focusing on the concentration of major pollutants and the air quality index

Concentration of different pollutants such as O₃ , NO₂ , SO₂ , CO, PM₁₀ , and PM2.5 in the atmosphere is called air pollution, which created several challenges in the environment and is considered one of the dangerous phenomenal in the current world, in Afghanistan urbanization in last two decades had significant impact on air quality. There is different source of air pollution in urban areas such as industries, more population, transportation system, less vegetation covers and etc. The main goal of this of this research is to analyze the pollutant levels from 2021 to 2024 in Kabul city by analyzing of six major pollutants including O₃ , NO₂ , SO₂ , CO, PM₁₀ , and PM2.5 and comparing them with national standard and by using the AQI to analyses the air quality. This is a quantitative research; data has been collected from National Environmental protection Agency air quality station based in Darulaman area of Kabul city. Significant annual and seasonal variations in pollutant concentrations were found by the results. O₃ concentrations exceeded the national norm during the winter months, ranging from 14 µg/m³ (June 2023) to 181 µg/m³ (December 2022). Particularly in late 2024, NO₂ and SO₂ exhibited significant peaks, with NO₂ reaching 258 µg/m³ and SO₂ reaching 150 µg/m³, both of which exceeded allowable limits. With maximum readings of 221 µg/m³ and 157 µg/m³, respectively, PM₁ 0 and PM₂ .5 were continuously over national norms for a number of months. According to the analysis of the Air Quality Index (AQI), PM₂ . ₅ was the main pollutant affecting the general quality of the air. The AQI rating was at its lowest (79) in September 2022 (Moderate) and at its worst (207) in January 2021 (Very Unhealthy). Seasonal trends revealed that while air quality improved somewhat during some summer months, especially in 2022, it deteriorated during the winter months of November through January. Overall, the results show a trend toward worsening air quality in 2023 and 2024, particularly as a result of particle matter pollution.

Assessing the spatiotemporal characteristics of urban air pollution in Ado-Ekiti and its environs, southwest Nigeria

Air pollution poses significant environmental and public health challenges in rapidly urbanising regions of sub-Saharan Africa, where ground-based monitoring infrastructure remains limited. This study examined the spatiotemporal distribution of key air pollutants in Ado-Ekiti and its environs, Nigeria, from 2019 to 2024. Columnar concentrations of carbon monoxide (CO) and formaldehyde (HCHO) were retrieved from Sentinel-5P, while MODIS aerosol optical depth data was used to estimate particulate matter (PM2.5 and PM10). Meteorological variables (rainfall, wind speed, and wind direction components u and v) were derived from the Weather Research and Forecasting model, and one week of ground-based measurements of pollutants were collected to enable correlation analysis with satellite-derived estimates. All datasets were aggregated to monthly and annual timescales, resampled to a 1 km spatial resolution and re-projected to UTM Zone 31 N. Results indicated that particulate matter dominated the pollutant profile, with annual mean concentrations of 59.37–65.29 µg/m³ for PM2.5 and 89.35–99.51 µg/m³ for PM10, exceeding WHO guideline limits. Peak concentrations occurred during the Harmattan season, with PM₂.₅ > 100 µg/m³ and PM₁₀ > 200 µg/m³, driven primarily by Saharan dust transport and local activities. Mann-Kendall trend analysis revealed significant increasing trends in HCHO, PM2.5, and PM10, whereas CO showed no significant trend. Satellite-derived particulate estimates showed positive but weak correlations with ground-based particulate concentrations (r < 0.20), whereas rainfall significantly reduced particulate levels, and meridional winds (v) facilitated long-range PM₁₀ transport. This study provides a significant integrated satellite model for air quality assessment in data-scarce urban environments while providing evidence to support targeted emission control strategies.

Spatio-temporal variability of ambient air quality under the influence of private vehicle-dominated traffic activity in Yogyakarta Urban Area (Indonesia)

Air quality is one of the environmental issues that has become a global concern and a priority in the Sustainable Development Goals. This study aims to evaluate the ambient air quality on secondary roads in the urban area of Yogyakarta under the influence of traffic levels. The air quality variables in this study include PM2.5, PM10, CO2, HCHO, and TVOC. Data collection was conducted through observation and literature study. A total of 134 data points were collected from 37 measurement locations in this study. The data were analyzed using matching, geographic information systems (GIS), statistical methods, and descriptive approaches. The results indicate that CO2 is the only parameter significantly correlated with traffic activity. More specifically, CO2 is significantly related to motorcycles, where an increase in the number of motorcycles corresponds to a rise in CO2 levels. Spatially, there is a difference in average CO2 levels between urban and suburban areas. CO2 levels are higher in suburban areas than in the city center due to commuter traffic from surrounding areas. HCHO and TVOC do not show a significant correlation with traffic levels. Meanwhile, the number and intensity of cars on the road, although not as numerous as motorcycles, contribute to increased levels of PM2.5 and PM10. This study provides new insights into the relationship between private vehicle activity and air quality in non-industrial cities, contributing to the development of regional theories in Southeast Asia on the environmental impact of transportation activity on secondary roads. Additionally, the findings of this study imply the need for spatiotemporal traffic management, not only to prevent traffic congestion but also to control pollution levels.

Spatio-temporal characterisation of air quality along the coastal regions of Kerala based on CPCB data