Spatiotemporal Dynamics of Urban Air Pollution in Dhaka City (2020–2024) Using Time-Series Sentinel-5P Satellite Images and Google Earth Engine (GEE)

This study investigated the spatiotemporal dynamics of four major air pollutants—carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and ozone (O3)—across Dhaka from 2020 to 2024 using Sentinel-5P TROPOMI satellite data. A 60-month time-series analysis was conducted, integrating spatial mapping, seasonal composites, and Mann–Kendall trend testing. Results indicated clear seasonal variations: CO and NO2 concentrations peaked during winter, with maximum monthly averages of 0.05287 mol/m2 and 0.00035 mol/m2, respectively, while SO2 reached a high of 0.00043 mol/m2 in pre-monsoon months. In contrast, O3 peaked in May (0.13023 mol/m2), following an inverse seasonal trend driven by photochemical activity. Spatial analysis revealed persistent pollution hotspots in central-western zones like Tejgaon and Mirpur for CO and NO2, while SO2 was concentrated in southern industrial zones such as Keraniganj and Jatrabari. The Mann–Kendall test identified moderate to strong increasing trends for CO (τ = 0.8, p = 0.086 in June and September) and SO2 (τ = 0.8, p = 0.086 in April and May), although most trends lacked statistical significance due to the limited temporal window. This study demonstrates the viability of combining satellite remote sensing and cloud-based processing for urban air quality monitoring and provides actionable insights for targeted seasonal interventions and evidence-based policymaking in Dhaka’s evolving urban context.

Authors

Institutions

Publication Details

Journal
Environments
Published
2025-08-10
DOI
https://doi.org/10.3390/environments12080274
Citations
2
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
2.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatiotemporal Dynamics of Urban Air Pollution in Dhaka City (2020–2024) Using Time-Series Sentinel-5P Satellite Images and Google Earth Engine (GEE)

Mst Ilme Faridatul, Md. Kamruzzaman, György Szabó, Md. Mostafizur Rahman
2 citations
Environments
Air Quality and Health Impacts
2.40
article

Spatiotemporal Dynamics of Urban Air Pollution in Dhaka City (2020–2024) Using Time-Series Sentinel-5P Satellite Images and Google Earth Engine (GEE)

Mst Ilme Faridatul, Md. Kamruzzaman, György Szabó, Md. Mostafizur Rahman
article en
2 citations

Abstract

This study investigated the spatiotemporal dynamics of four major air pollutants—carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and ozone (O3)—across Dhaka from 2020 to 2024 using Sentinel-5P TROPOMI satellite data. A 60-month time-series analysis was conducted, integrating spatial mapping, seasonal composites, and Mann–Kendall trend testing. Results indicated clear seasonal variations: CO and NO2 concentrations peaked during winter, with maximum monthly averages of 0.05287 mol/m2 and 0.00035 mol/m2, respectively, while SO2 reached a high of 0.00043 mol/m2 in pre-monsoon months. In contrast, O3 peaked in May (0.13023 mol/m2), following an inverse seasonal trend driven by photochemical activity. Spatial analysis revealed persistent pollution hotspots in central-western zones like Tejgaon and Mirpur for CO and NO2, while SO2 was concentrated in southern industrial zones such as Keraniganj and Jatrabari. The Mann–Kendall test identified moderate to strong increasing trends for CO (τ = 0.8, p = 0.086 in June and September) and SO2 (τ = 0.8, p = 0.086 in April and May), although most trends lacked statistical significance due to the limited temporal window. This study demonstrates the viability of combining satellite remote sensing and cloud-based processing for urban air quality monitoring and provides actionable insights for targeted seasonal interventions and evidence-based policymaking in Dhaka’s evolving urban context.

EnvironmentsVol. 12(8)
Rajshahi University of Engineering and Technology (BD), University of Nyíregyháza (HU)
Sustainable cities and communities
Openalex Percentile: Top 11%
Air Quality and Health Impacts
2.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.