DOI: 10.62796/pijst.2024v1i601

  DOI URL: https://doi.org/10.62796/pijst.2024v1i601

Abstract- This study employs Google Earth Engine (GEE) and Sentinel-5P TROPOMI data to analyze spatial and temporal variations in nitrogen dioxide (NO2) concentrations across a specified region. The methodology involves accessing the GEE platform to import Sentinel-5P Level 2 NO2 data, defining the study area’s geographic boundaries and time frame, and filtering the dataset to include only high-quality measurements. Spatial and temporal aggregation techniques were applied to generate average NO2 concentration maps and time series data, while cloud masking algorithms ensured data reliability by excluding cloud-affected observations. The processed data were visualized to illustrate NO2 distribution and trends, and statistical analyses were conducted to summarize NO2 levels and identify significant temporal changes. Additionally, the extracted NO2 concentrations were validated against ground-based air quality monitoring data. This approach provides a comprehensive understanding of NO2 dynamics, supporting effective air quality management and policy development aimed at mitigating NO2 pollution and protecting public health.