Jul 2026· International Journal Multidisciplinary (IJMI)· Vol 3, pp. 79-87· 0 citations
Abstract
Objective: Ambient atmospheric pollution represents a critical threat to human health globally. Within Iraq, air quality has drastically diminished due to harsh climatic dust events and expanding unregulated anthropogenic factors. The primary goal of this investigation is to establish a thorough comparative analysis of air quality across the urban and rural sectors of Al-Diwaniyah Province. Method: A comparative cross-sectional design was carried out from mid-September 2025 through January 2026 across six strategic sampling locations. Ground-level monitoring utilized a calibrated Temtop M2000 device to log particulate metrics, while space-borne observations were acquired via the Sentinel-5P TROPOMI satellite for gaseous pollutants. A composite Z-score air quality index (AQI) evaluated safety thresholds, with statistical analysis processed through SPSS v26 software. Results: Ground measurements revealed that average PM2.5 (34.87 µg/m³) and PM10 (101.37 µg/m³) drastically outpaced WHO safety limits (p < 0.001). Satellite monitoring demonstrated a significant abundance in tropospheric NO₂ (63.54 µmol/m²) and O₃. The index classified 73.3% of the total observations as unhealthy for sensitive demographics. Urban sectors displayed significantly higher concentrations of PM2.5, PM10, and CO₂ than rural environments (p < 0.001), though rural locations showed a high prevalence (80.0%) of air quality categorized as hazardous for sensitive groups. Novelty: Al-Diwaniyah Province experiences severe atmospheric degradation. While urban centers undergo heavier pollution loads from concentrated traffic and fuel combustion, rural zones present distinct ambient threats to vulnerable populations from agricultural operations and dust.
This study evaluates the applicability of Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) satellite observations for air quality monitoring in Tehran, a megacity characterized by complex topography and persistent air pollution challenges. A comprehensive comparison was conducted between ground-based measurements from 22 air quality monitoring stations and Sentinel-5P Level-2 products, including carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and the Ultraviolet Aerosol Index (UVAI) over the period 2019-2024. Data preprocessing included outlier removal using the Interquartile Range method, Min-Max normalization, and Air Quality Index analysis. Agreement between satellite and ground observations was evaluated using Pearson and Spearman correlation coefficients and the Kling-Gupta Efficiency metric. In addition, spatiotemporal pollutant trajectories derived from both datasets were compared. The results revealed substantial differences between satellite-derived and ground-based observations. Among the investigated pollutants, NO₂ exhibited the strongest agreement, whereas CO, SO₂, and O₃ showed generally weak correspondence. Spatiotemporal trajectory analyses also demonstrated notable discrepancies between satellite-derived and ground-based pollutant distributions, reflecting differences in spatial representativeness and measurement characteristics. Comparisons involving particulate matter should be interpreted cautiously because UVAI represents atmospheric aerosol loading rather than direct surface particulate matter concentrations. The observed discrepancies are primarily attributed to the spatial resolution of Sentinel-5P, temporal sampling limitations, and the complex meteorological and topographical conditions of Tehran, which generate highly localized pollution patterns. The findings indicate that Sentinel-5P has limited standalone capability for near-surface urban air quality assessments in complex environments, but remains valuable for identifying regional pollution gradients, long-term trends, and broader atmospheric patterns. The results support the development of hybrid monitoring frameworks that combine satellite observations with ground-based measurements, meteorological information, and advanced data-fusion techniques. More broadly, this study provides guidance for improving satellite-based air quality assessment and supports the design of more effective monitoring systems for rapidly urbanizing regions worldwide.
Amir Mohammad Kafi, Mahdi Hosseinipoor, M. Z. Shahne· Science of the Total Environ...· 0 citations
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.
Olawale Victor Oluwatuyi, F. Akinluyi, J. Adeyeye· Discover Atmosphere· 0 citations
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.
May Myint Myat, Hyung Joo Lee· Environmental Pollution· 0 citations
Abstract. Accurate air quality assessments are essential for understanding exposure to pollution and supporting environmental policy decisions. This study presents a comprehensive methodology for estimating air quality index (AQI) using satellite data and Google Earth Engine (GEE). The research process begins with identifying shortcomings in current approaches to air quality monitoring and reviewing relevant literature on satellite-based pollutant estimation and AQI calculation. To simplify the analysis, a dedicated application has been developed in GEE to enable dynamic selection of study areas and integration of satellite column density data. To estimate surface concentrations at ground level, the pollutant columns extracted from the satellite are processed through molecular weight conversion and atmospheric scaling. The concentration is then standardised from mol/m² to μg/m³ to facilitate the calculation of the AQI. For key air pollutants, individual air quality indicators are generated to provide insight into spatial patterns of air quality in the study area. This methodology demonstrates a scalable and reproducible approach to satellite-based air quality monitoring and provides the basis for future improvements, including higher-resolution datasets, predictive modelling, and integration with terrestrial measurements.
D. Rawal, Sindhu Ranganath, Neha Sharma et al.· The International Archives o...· 0 citations
The Central Area of Makkah faces severe seasonal environmental pressures from heavy vehicular traffic, particularly during Hajj. Using the DPSIR framework, this study conducts a spatial and environmental diagnosis of this high-density urban core. To assess the environmental conditions, spatial sampling and field measurements were conducted at 32 strategic locations, using a calibrated Extech VPC300 Video Particle Counter for PM2.5 and PM10, along with portable multi-parameter detectors for CO and CO2. Field measurements captured two seasonal operational extremes: Phase 1 (baseline peak congestion, 20 Dhu Al-Qi’dah 1446AH) and Phase 2 (strict traffic cordon restrictions, serving as a real-world LEZ proxy, 2 Dhu al-Hijjah 1446AH). Paired-samples t-test validation indicates that during peak congestion, localised CO2 reached 1,750 ppm and noise peaked at 95 dB, while localised PM2.5 and PM10 particle counts demonstrated elevated concentrations. Methodological baseline calculations reveal that the localised prayer shuttle fleet generates a carbon footprint four times larger (57,888 tons of CO2) than the inbound regional fleet, condition compounded by the dense ‘street canyon’ morphology. Conversely, spatial analysis identifies 2.5 million m2 of vacant land. As a targeted ‘Response’, this paper introduces the Makkah Low Emission Zone (M-LEZ) framework. Distinct from conventional urban LEZs, the M-LEZ introduces a dynamically phased seasonal framework that utilises underused peripheral land for green infrastructure and transit hubs. It aims to balance mass transit logistics with microclimate sustainability and promotes public health for pedestrians.
Abdullah Abdulhameed Bagasi· Journal of King Saud Univers...· 0 citations
Construction activities can temporarily degrade ambient air quality through fuel-combustion emissions and fugitive dust. This study assessed baseline conditions and predicted pollutant dispersion during a residential development in Jimbaran, Bali. Ambient sampling was conducted at a roadside/front-boundary point and the central project site on 22–23 May 2026 for SO?, NO?, CO, O?, non-methane hydrocarbons, TSP, Pb, PM??, and PM?.?. Construction-related increments of SO?, NO?, CO, TSP, PM??, and PM?.? were evaluated using emission-factor calculations and a Gaussian line-source screening model under atmospheric stability class B, a 1.5 m/s wind speed, and a 1.5 m receptor height. All baseline parameters complied with Indonesian ambient air standards, and the initial air quality index was classified as good. At a representative 100 m receptor, both material/equipment mobilization and building-construction scenarios remained below the standards. However, a conservative 10 m mobilization scenario increased NO? to 224.50 µg/m³ and TSP to 484.05 µg/m³ at the roadside point, exceeding the respective standards of 200 and 230 µg/m³. Modelled increments declined sharply with distance, indicating that the principal risk is localised around project access and material-handling routes. The findings support prioritizing covered loads, road wetting, speed control, immediate removal of spilled material, equipment maintenance, and targeted monitoring of NO2, TSP, PM??, and PM?.? at near-source receptors.
Contribution to Sustainable Development Goals (SDGs):SDG 3: Good Health and Well-beingSDG 11: Sustainable Cities and CommunitiesSDG 13: Climate Action
I. W. G. Sutasoma, M. A. R. Dayanti, Made Panji Tirta Prakasa et al.· AJARCDE | Asian Journal of A...· 0 citations