Characterizing uncertainty in TROPOMI NO2 retrievals across Europe with ground-based measurements and high-resolution modeling

Satellite observations of NO₂ play a central role in air quality and climate research; however, their quantitative interpretation is limited by uncertainties arising from retrieval algorithms, instrumental characteristics, and spatial representativeness. Robust interpretation of tropospheric NO₂ columns, therefore, depends on a comprehensive assessment of these uncertainty sources. Here, we investigate the primary contributors to uncertainty in TROPOMI NO₂ retrievals by examining individual retrieval steps and validating TROPOMI observations against independent Pandora and MAX-DOAS measurements. High-resolution chemical transport model simulations over Europe and the Netherlands are used to support and contextualize the analysis. Systematic biases are found in the stratosphere–troposphere separation of NO₂ in TROPOMI retrievals, with wintertime stratospheric columns overestimated by up to 0.15 Pmolec/cm² at high northern latitudes. These biases propagate into the tropospheric product, producing errors of up to 1.5 Pmolec/cm², primarily associated with limitations in the TM5-MP assimilation and further enhanced by large air-mass factor ratios under winter conditions. High-resolution LOTOS-EUROS simulations are used to evaluate representation errors associated with sub-pixel horizontal NO₂ gradients in satellite–ground-based comparisons, resulting in uncertainty estimates of approximately 6% at polluted sites. Differences in vertical sensitivity between TROPOMI and MAX-DOAS are shown to introduce substantial smoothing errors, reaching up to 20%. Comparisons between TROPOMI and Pandora direct-sun measurements reveal good seasonal agreement. Nonetheless, TROPOMI exhibits a negative bias relative to Pandora direct-sun measurements when using the default TM5-MP a-priori profiles. This bias is partially reduced by adopting higher-resolution CAMS-European a-priori profiles and further reduced when kilometre-scale simulations over the Netherlands are applied. These results highlight the critical importance of the spatial resolution of a-priori information in satellite–ground-based comparisons. Noticeable differences in both magnitude and seasonal variability are observed between MAX-DOAS, Pandora direct-sun, and Pandora sky-scan measurements, highlighting substantial intrinsic uncertainties within ground-based remote sensing products. Finally, uncertainty estimates derived from the distribution of differences between TROPOMI and ground-based observations generally exceed expectations based on the combination of individual uncertainty contributions, suggesting that current uncertainty estimates remain optimistic.