Feasibility and Optimization of Discrete-Wavelength DOAS for NO₂ Retrieval Using TROPOMI & EMI-II Observations | #WorldResearchAwards


Introduction

Nitrogen dioxide (NO₂) is a key atmospheric trace gas that plays a critical role in air quality, climate forcing, and human health. High-spectral-resolution retrieval techniques provide detailed absorption information but are often constrained by large data volumes, high computational demands, and complex instrument requirements. To overcome these limitations, this study explores a low-spectral-information retrieval strategy aimed at enabling fast, efficient, and reliable atmospheric NO₂ monitoring. By leveraging discrete wavelength sampling instead of continuous high-resolution spectra, the proposed approach seeks to preserve essential absorption features while significantly reducing data and processing burdens.

Principle of Discrete-Wavelength Differential Optical Absorption Spectroscopy (DWDOAS)

The DWDOAS technique adapts the conventional DOAS framework by selectively sampling a limited number of representative wavelengths rather than using full spectral coverage. In this study, 14 discrete wavelengths within the 420–450 nm range are chosen to capture the dominant differential absorption structures of NO₂. This targeted sampling strategy effectively suppresses high-frequency spectral noise while retaining sufficient absorption information for accurate retrievals. As a result, DWDOAS offers a simplified yet robust alternative for trace-gas analysis, particularly suitable for low-resolution instruments and rapid monitoring applications.

Optimization of Wavelength and Spectral Resolution Configuration

To determine the most effective retrieval configuration, multiple wavelength–resolution combinations are systematically constructed and evaluated. An entropy-weighting scheme is applied to quantitatively assess the information contribution of each configuration, ensuring an objective and data-driven optimization process. The analysis reveals that a spectral resolution of approximately 2 nm provides an optimal balance between information retention and noise suppression. This resolution allows DWDOAS to maintain sensitivity to NO₂ absorption features while minimizing the impact of instrumental noise and spectral redundancy.

Application to Satellite Observations from TROPOMI and EMI-II

The performance of the DWDOAS method is demonstrated using real satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI) and the Environmental Trace Gases Monitoring Instrument (EMI-II). Retrieved NO₂ vertical column densities (VCDs) are compared with those obtained from conventional DOAS algorithms. The results show strong consistency between the two approaches, with correlation coefficients exceeding 0.7 and relative differences typically within ±30%. These findings confirm that DWDOAS can achieve reliable NO₂ retrievals even with substantially reduced spectral information.

Uncertainty Assessment and Monte Carlo Simulation Analysis

To evaluate retrieval robustness, Monte Carlo simulations are conducted under varying noise conditions. The simulations indicate that DWDOAS maintains mean uncertainties below 2 × 10¹⁴ molecules·cm⁻², demonstrating strong stability against random measurement errors. However, increased uncertainties are observed in scenarios characterized by low NO₂ background concentrations or heavy aerosol loading, where weak absorption signals become more difficult to resolve. Despite these limitations, the overall uncertainty levels remain acceptable for large-scale atmospheric monitoring applications.

Implications for Instrument Design and Rapid Atmospheric Monitoring

The results of this study highlight the significant potential of DWDOAS for next-generation atmospheric sensing. By reducing spectral resolution and data volume requirements, the method supports simplified spectrometer designs, efficient onboard data compression, and faster data processing. These advantages are particularly valuable for satellite missions, airborne platforms, and ground-based networks requiring rapid, wide-area coverage. Overall, DWDOAS provides a practical and scalable pathway for maintaining reliable NO₂ retrieval performance while enabling more efficient and cost-effective atmospheric trace-gas monitoring systems.

Hashtags

#worldresearchawards #NO2research #atmosphericmonitoring #remotesensing #DOAS #DWDOAS #satelliteretrieval #airqualityresearch #spectroscopy #environmentalscience #lowresolutionspectroscopy #tracegases #TROPOMI #EMI #climatescience #datareduction #atmosphericchemistry #sensorinnovation #researchimpact #globalairquality

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