Comparative Assessment of Urban and Rural PM2.5 Concentrations across Physiographic Regions of Nepal

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

Spatiotemporal Variation of PM2.5 Concentration and Health Impacts in Addis Ababa, Ethiopia: Trends and Patterns

This study investigated the spatiotemporal variability of fine particulate matter (PM2.5) in Addis Ababa, Ethiopia and assessed its associated health risks and economic burden using data from January 2022 to December 2023. Hourly PM2.5 concentrations were collected through a hybrid monitoring network comprising seven low-cost sensors and two Beta Attenuation Monitors (BAM). Spatiotemporal analysis was performed using Python, and health risks were assessed by estimating the Hazard Quotient (HQ) and Excess Lifetime Cancer Risk (ELCR). The economic burden attributable to PM2.5 exposure was assessed by monetizing disease-specific Disability-Adjusted Life Years (DALYs) using a locally adapted Value of Statistical Life (VSL) approach. Over the two-year periods, mean PM2.5 concentrations ranged from 15 to 33 μg/m3 across monitoring sites, with an overall a citywide average of 27 μg/m3, exceeding the World Health Organization (WHO) Air Quality Guideline (AQG) of 5 μg/m3 by more than fivefold. Seasonal analysis revealed elevated PM2.5 concentrations during the wet season (Kiremt), while diurnal patterns showed peaks of 38 µg/m3 at 7:00 AM. The HQ values for all age groups exceeded the acceptable threshold of 1, indicating non-carcinogenic health risks. ELCR estimates calculated using a slope factor of 0.008 exceeded the risk threshold (1 ×10-4), whereas estimates based on the slope factor of 0.0012 remained within the acceptable limits, highlighting the sensitivity of cancer risk estimates to the toxicity parameter applied. The economic burden attributable to PM2.5 exposure was estimated at USD 652.95 million over the two-year study period, contributing an external cost share to national GDP of 0.25% in 2022 and 0.25% in 2023. Cardiovascular diseases, particularly ischemic heart disease (IHD), accounted for the largest share of economic losses, significantly exceeding acute respiratory infections and PM2.5 related cancers. These findings provide evidence to support targeted policies aimed at reducing PM2.5 related cancers combined.

Spatiotemporal patterns of ambient NO2 and NO pollution in Kigali Rwanda

Kigali, like many cities in sub-Saharan Africa, faces rapid urban growth alongside the need to manage air pollution and protect public health. Despite its policy efforts, systematic data on nitrogen oxides (NOx: NO2 and NO), key indicators of combustion-related pollution, have been limited. We applied a standardized protocol to characterize city-scale spatial and temporal patterns of NOx across Kigali. Between November 2022 and December 2023, we collected weekly integrated NO2 and NO samples (n = 630 each) at 130 sites representing diverse land-use types. NO2 concentrations ranged from 1.3 to 61.9 µg/m3 (mean 13.9 µg/m3), with annual-equivalent frequently exceeding the WHO annual guideline (10 µg/m3) in urban areas. Exceedances occurred in 39% of sparsely residential, 89% of commercial/industrial, and 99% of densely populated residential sites. NO2 concentrations were significantly higher in urban versus rural areas (18.2 vs. 6.3 µg/m3), near major roads (19.9 vs. 11.6 µg/m3), and at lower elevations (15.4 vs. 9.0 µg/m3). The highest levels were observed in the densely populated districts of Kicukiro and Nyarugenge. Overall, NO2 and NO exhibited strong spatial gradients related to land use, traffic, population density, and topography, highlighting the importance of targeted urban planning and air quality management in rapidly growing cities.

Micro-scale Spatial Patterns of PM2.5 in an Arid City: Evidence from Mobile Monitoring Across Urban Green and Non-green Areas

Spatiotemporal Characteristics of Atmospheric NO2 Concentration in Southeast Asia using Satellite Observations

Southeast Asia has long experienced severe air pollution, posing significant risks to public health. Contrary to global trends of declining emissions, the region’s rapid industrialization may exacerbate air quality problems. This study investigates the spatiotemporal characteristics of atmospheric nitrogen dioxide (NO2) concentrations across Southeast Asia using satellite-based observations. Two analytical approaches are employed: an analysis of tropospheric NO2 concentration fields and a flux-divergence-based assessment of NO2 emissions. First, regional and local patterns of NO2 concentrations are examined using tropospheric column density data from the Ozone Monitoring Instrument (OMI) for the period 2005–2022. The results indicate that elevated NO2 concentrations are primarily concentrated in major urban centers, likely associated with vehicular emissions and industrial activities. Notably, enhanced NO2 levels are also observed in several forested regions. These anomalies are hypothesized to be associated with biomass burning, a relationship further supported through integration with MODIS burned area products. Detailed analyses are then conducted for 12 hotspot regions using time series decomposition to isolate long-term trends, seasonal variability, and residual components. To account for the potential influence of the COVID‑19 pandemic, the analysis period for each hotspot is divided into pre‑ and post‑pandemic phases, revealing distinct concentration trends for individual regions. Second, NO₂ emission patterns are investigated using flux divergence calculations derived from TROPOspheric Monitoring Instrument (TROPOMI) observations in combination with wind fields from the ECMWF ERA5 reanalysis. Regional-scale emission maps are first produced for Southeast Asia, followed by focused analyses for three selected areas: the Bangkok Metropolitan Region, the Northern Vietnam Industrial Corridor, and the Singapore–Kuala Lumpur Region. Independent auxiliary datasets are used to reference the accuracy of the inferred emission patterns. The results demonstrate that the flux divergence approach effectively identifies major emission sources, especially in complex areas like Bangkok's urban region.

Mapping seasonal PM2.5 distribution in Novi Sad: From sensor-based observations to land use regression modelling

Air pollution in Serbia is characterized by pronounced seasonal variability, with the heating period representing the most critical phase in terms of fine particulate matter (PM2.5). Understanding both short-term dynamics and the spatial distribution of PM2.5 in urban environments remains a key challenge. This study focuses on the assessment of PM2.5 variability in Novi Sad, combining high-resolution sensor measurements with spatial modeling perspectives. A field campaign was conducted at 21 locations across urban, industrial, mixed-use, and background environments during heating and non-heating seasons. The use of low-cost sensors enabled detailed insight into short-term fluctuations and daily patterns of PM2.5 concentrations. Wind and pollution roses were employed to explore dominant dispersion patterns and to better understand the influence of prevailing meteorological conditions on pollutant transport. To support data reliability, sensor measurements were compared with reference measurements, demonstrating a satisfactory level of agreement and confirming their suitability for further analysis and spatial interpretation. As a key outcome, high-resolution seasonal prediction maps of PM2.5 are presented as an extension of previously developed Land Use Regression (LUR) models for Novi Sad, representing the first implementation of this approach in Serbia. These maps reveal spatial distribution patterns, pollution hotspots, and potential exposure gradients across the urban area. In addition, a preliminary assessment of chronic health impacts based on PM2.5 exposure at selected monitoring locations will be discussed. Particular attention will be given to the interpretation of prediction maps and their role in understanding spatial exposure patterns in urban environments.