Assessment of Geostationary Environment Monitoring Spectrometer (GEMS) Tropospheric NO2 Measurements Using Ground-Based Pandora Instrument in Quezon City Jayra Emeryl Blanche (a*), Ellison Castro (a), Ma. Angelica De Hitta (a), James Cesar Refran (a), Jeniffer De Maligaya (a)
a) Philippine Space Agency (PhilSA)
*jayra.blanche[at]philsa.gov.ph
Abstract
Through the PAPGAPI-PAN PH project of the PhilSA, four Pandora spectrometers were installed across the Philippines in 2024 to support national air quality monitoring. On April 25-30, 2025, an AQI of 90 was reported in Quezon City, classified as moderate and approaching unhealthy levels. This enabled an initial assessment of how Geostationary Environment Monitoring Spectrometer (GEMS) aligns with ground-based measurements from Pandora at the Manila Observatory. This study compared the tropospheric nitrogen dioxide (NO2) column data retrieved from the two instruments. GEMS retrievals were filtered under different cloud conditions using cloud fraction (CF) thresholds (<0.3, <0.5, <0.7), while Pandora data were averaged 10 minutes from each GEMS observation, then corrected using a distance-weighted correction to account for the slant path, especially at high SZA. GEMS and Pandora NO2 columns exhibited good correlation (R = 0.736, RMSE = 3.62 x 10^15 molec/cm^2) under low-cloud conditions, while slightly lower agreement was found in cloudier conditions. After applying distance-weighted correction, R reached 0.752 with an RMSE of 3.88 x 10^15 molec/cm^2 for CF < 0.3. This suggests that while correlation slightly improved, overall error did not decrease. Hence, applying the correction on a limited dataset had minimal impact, indicating that this alone may not fully increase the correlation of GEMS and Pandora measurements at higher SZAs. Overall, the two instruments showed good agreement, supporting the need for continued evaluation across broader conditions and timeframes. By expanding the temporal range, future assessments can capture NO2 variability as well as long-term patterns, providing a more comprehensive performance evaluation of GEMS and other satellite-based measurements. Further refinement of correction approaches may also be needed to improve the comparisons and support their potential use in developing air quality forecasting tools and predictive models.
Keywords: GEMS, Pandora, Tropospheric NO2, Remote Sensing, Air Quality
