Leveraging High-Resolution Satellite-Derived NO₂ Estimates to Evaluate NO₂ Exposure Representativeness and...

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Public Health

Background:

• Traditional NO2 concentration estimates cover large areas, limiting fine-scale exposure assessments.
• High-resolution NO2 data is crucial for understanding localized pollution impacts and population exposure.

Purpose of the Study:

• To estimate long-term average NO2 concentrations at 500 m spatial resolution in South Korea (2018-2022).
• To assess the representativeness of ground monitoring networks for population exposure.
• To investigate socioeconomic disparities in NO2 exposure.

Main Methods:

• Utilized tropospheric NO2 data from the TROPOspheric Monitoring Instrument (TROPOMI).
• Integrated traffic-related land use parameters with satellite data using a hybrid regression model.
• Compared population-weighted estimated NO2 with measured data from ground monitors.

Main Results:

• Achieved high predictability (R2=0.81) for NO2 estimation at 500 m resolution.
• Found significant variations in the representativeness of ground monitors across South Korean regions (ratio 0.62-1.12).
• Identified consistently higher NO2 exposures in areas with higher socioeconomic status.

Conclusions:

• High-resolution NO2 mapping enhances exposure assessment accuracy.
• Findings support improved public health strategies and regulatory applications.
• Satellite-derived data combined with land use parameters offer a robust approach for detailed air quality monitoring.