Harmonizing satellite and ground NO2 observations in China: A multi-sensor framework for scenario-specific calibration

Abstract

Satellite-based nitrogen dioxide (NO₂) retrievals exhibit scenario-dependent discrepancies due to varying environmental conditions, yet systematic evaluations of their performance across heterogeneous regions remain limited. This study presents a comparative analysis of TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) NO₂ products over China (2019–2023) using 1700+ ground-based monitoring stations through a tripartite framework: (1) evaluation of spatiotemporal consistency with ground observations, (2) analysis of long-term emission trends using deseasonalized data, and (3) scenario-specific validation across seasonal cycles and extreme pollution episodes. Results demonstrate TROPOMI’s superior performance in capturing fine-scale pollution patterns, showing strong correlations with ground measurements in urban areas (e.g. Beijing: R = 0.81) and during extreme events (R = 0.97), while OMI systematically underestimates urban concentrations by 15 % (R = 0.72). Seasonal analysis reveals that TROPOMI and OMI data correlate much more strongly with ground-based measurements under stable winter conditions (R = 0.85 and 0.82, respectively) than in summer, when performance is affected by photochemical processes (R = 0.23 and 0.13, respectively). A unified error model integrating all analytical components is developed to identify the drivers of satellite-ground discrepancies. Applied to the Beijing’s January 2022 episode, the model attributes the observed biases primarily to extreme pollution events (γ = 0.68). Our results emphasize TROPOMI’s superiority for real-time urban air quality management and OMI’s utility for regional trend assessments. This work provides actionable insights for optimizing satellite-ground monitoring systems, supporting targeted emission control strategies under China’s evolving atmospheric policies.