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

Assessing the Relationship Between Traffic Activity and Urban Air Pollution in Dhaka Using QGIS and Emission Factor Methods

Bad air quality is one of the most serious issues cities are struggling with today, especially in rapidly growing megacities such as Dhaka. Increasing traffic volume and congestion make vehicular emissions one of the major sources of urban air pollution. This study examines the spatial correlation between traffic activity and air pollution concentration levels on selected road segments in megacity Dhaka. Traffic volume data were collected from six road segments along Mirpur Road and Kazi Nazrul Islam Avenue using videography-based surveys. Carbon monoxide (CO), nitrogen oxides (NOx) and particulate matter (PM2. were simulated by using emission factor methods. We extracted air pollutant concentration data from the Open-Meteo Air Quality API for each of these respective times and locations. Spatial emission distribution was visualized using a grid framework of 250 m × 250 m by utilizing Quantum Geographic Information System (QGIS) tools. The relationship between emissions and pollutant concentration were analyzed using regression. The results show that there is a strong correlation between the daily traffic emissions and the concentrations of air pollutants, with R² = 0.97 for CO (carbon monoxide) and R² = 0.93 for PM2.5 (particulate matter). The study highlights pollution hotspots on some major road segments where traffic density is high. The study emphasizes the significance of both traffic control methods and sustainable transportation planning especially for Dhaka in facilitating urban air quality challenges.

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.

Linking traffic congestion, spatiotemporal pollutant patterns, and LEZ siting in a megacity: a case study of Jakarta

An Empirical Assessment of Traffic Volume Influence on Roadside NO₂ Concentration: A Micro-Scale Statistical Analysis in Makassar, Indonesia

Rapid urban motorization in Makassar has intensified roadside exposure to traffic-related pollutants. This study empirically evaluates the direct statistical relationship between traffic volume and roadside nitrogen dioxide (NO2) concentration along a major arterial corridor. Field measurements were conducted during three time periods (morning, midday, and afternoon) on one representative weekday and one weekend day. Traffic volume was converted to Passenger Car Units (PCU), and NO2 concentration was measured using the Griess-Saltzman method in accordance with national standards. Pearson correlation and simple linear regression were applied to quantify the emission–concentration relationships at the microscale level. The results indicated a strong positive correlation between traffic volume and NO2 concentration (r = 0.874, p < 0.05), with traffic density explaining 76.3% of the variability in concentration (R2 = 0.763). Despite limited temporal coverage, the findings demonstrate that traffic congestion is a dominant determinant of short-term roadside NO2 accumulation. This study provides localized empirical evidence supporting traffic-based emission control strategies in emerging urban environments.

Spatio-temporal Assessment of Air Quality Across Diverse Land-use Zones in Ranchi, Jharkhand, India

Air-quality research in India has predominantly focused on large metropolitan regions, leaving plateau-based Tier-II cities comparatively underexamined. This study assessed the spatio-temporal variability of air quality across five land-use zones in Ranchi, Jharkhand: industrial, traffic, residential, agricultural, and eco-sensitive. Monthly observations collected during 2022–2023 yielded 120 site-month records, and the National Air Quality Index framework was applied to PM₂.₅, PM₁₀, SO₂, and NO₂. Site-level differences were evaluated using one-way analysis of variance, while dominant-pollutant regimes and seasonal patterns were examined to identify spatial and temporal contrasts. Mean AQI differed significantly among sites (F(4, 115) = 11.04, p < 0.001). The traffic site recorded the highest mean AQI (267.7 ± 27.2), followed by the industrial site (243.2 ± 16.9), indicating sustained pollution pressure in high-emission zones. The eco-sensitive site recorded a higher mean AQI (175.1 ± 105.4) than the residential site (158.6 ± 58.0), suggesting that local vegetation did not consistently prevent episodic deterioration. PM₂.₅ was the most frequent AQI-determining pollutant, particularly at the traffic and industrial sites, whereas PM₁₀ governed several abrupt episodes at the agricultural and eco-sensitive locations. Winter generally showed the highest and most variable AQI, while the monsoon produced lower and less dispersed values, reflecting seasonal differences in pollutant accumulation and removal. Overall, the findings demonstrate marked land-use and seasonal heterogeneity in Ranchi. They further indicate that air-quality monitoring and management should address both persistent emissions at traffic and industrial locations and episodic pollution affecting peri-urban, agricultural, and eco-sensitive zones within the rapidly expanding plateau-based urban environment.

Assessment of urban environmental quality and spatial dynamics using integrated LULC and population data: Evidence from Eskişehir, Türkiye

This study integrates land-use/land-cover (LULC) and high-resolution population density data for 2018 and 2024 to analyze the spatiotemporal variations in urban environmental quality in the city center of Eskişehir. Land-use scores were integrated with normalized population density to develop a composite Environmental Index (EI). The EI results indicate a decline in environmental quality, with the mean value decreasing from 0.139 to −0.014. Spatial autocorrelation analysis (Moran’s I = 0.052) revealed weak but statistically significant spatial dependence, while Getis-Ord Gi* analysis identified localized hot spot and cold spot patterns of environmental change. At the district level, Odunpazarı exhibited more pronounced environmental degradation, whereas environmental quality remained relatively higher in Tepebaşı. Overall, the findings indicate that environmental change is spatially heterogeneous and characterized by localized clustering rather than strong global spatial dependence. Furthermore, the results highlight the importance of integrated land-use policies that account for spatial differences in human pressure and environmental sensitivities to support sustainable urban development.