TANGO CO₂ and NO₂ Observations: Synergistic Usage to Improve Emission Quantification and Characterize Atmospheric Chemistry

Abstract. The Twin Anthropogenic Greenhouse Gas Observers (TANGO) mission, scheduled for launch in 2028, will observe COâ‚‚, CHâ‚„, and NOâ‚‚ emission plumes from more than 10,000 industrial facilities per year using two formation-flying CubeSats. Here, NOâ‚‚ plume structures exhibit substantially lower random noise than the corresponding COâ‚‚ features, motivating a synergistic exploitation of both species for improved emission quantification and for enhanced characterization of atmospheric chemistry within plumes. Using large-eddy simulations in combination with the Integrated Mass Enhancement (IME) method, we assess NOâ‚‚-based masking of COâ‚‚ plumes for emission rates in the range 2.0–12.5 Mt yr⁻¹. This yields COâ‚‚ emission estimates with precisions between 18.5 % and 3.4 %, depending on the emission strength, and corresponding absolute biases that decrease from 15.3 % to 2.4 %. As an alternative approach, we analyze the observed COâ‚‚/NOâ‚‚ ratio. By fitting an empirical model to measurement simulations of this ratio and subsequently reconstructing the COâ‚‚ plume from NOâ‚‚ observations, we obtain a substantial reduction in the apparent noise of the reconstructed COâ‚‚ plume. For the inferred emission rates, however, the precision remains largely unchanged. Consequently, despite reduced errors in individual pixel-level observations, plume reconstruction does not enhance the precision of COâ‚‚ emission estimates, because it converts originally uncorrelated pixel noise into spatially correlated errors. Neglecting these spatial error correlations leads to a severe underestimation of the retrieval uncertainty. A key advantage of the empirical COâ‚‚/NOâ‚‚ ratio model is its ability to characterize plume chemistry. Here COâ‚‚ serves as non-decaying reference tracer. We demonstrate that an effective timescale for the NO → NOâ‚‚ conversion in emission plumes can be inferred for sources with COâ‚‚ emissions > 5.0 Mt yr⁻¹. Application of the method to Environmental Mapping and Analysis Program (EnMAP) observations demonstrates its practical utility, confirming its applicability to real satellite data.