Characterization of NO2 and HCHO trace gases in Montevideo during 2024

Montevideo is a coastal city on the Río de la Plata in South America, characterized by frequent and relatively intense winds, high relative humidity, and moderate urban emissions. Furthermore, the city experiences four seasons with well-defined temperature variations.

Nitrogen dioxide (NO₂) and formaldehyde (HCHO) are atmospheric trace gases whose presence exhibit well-defined diurnal and seasonal variations. The joint analysis of NO₂ and HCHO allows for the characterization of anthropogenic source influence, as well as the evaluation of the seasonal variability of the atmosphere.

We present an initial assessment of NO₂ and HCHO detection in Montevideo in 2024. In this first step, we focused on the differential slant column densities (dSCDs) of both gases under clear skies conditions. The detection was performed using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) in the UV-Vis spectral range. To obtain the NO₂ dSCDs we analyzed the spectral window 411–445 nm, and HCHO dSCDs determination in the range of 324.5–359 nm using the software QDOAS [1].

Spectral data were available for 312 of the 366 days in 2024. According to the color index, clear skies were identified on 103 of these days [2]. In approximately 85% of the samples, NO₂ dSCDs showed typical behavior at sunrise and sunset, with its minima recorded around noon. In contrast, HCHO dSCDs showed a progressive increase, reaching their maximum around midday or in the early afternoon for all elevation angles (5°, 10°, 30°, 60°, and 90°). The remaining 15% of dSCDs exhibited pronounced behavior in one or both gases; these variations are the subject of the second stage of our investigation. Finally, we examine the obtained results and their relationship with wind direction.

[1]. Danckaert, T., Fayt, C., Roozendael, M. V., Smedt, I. D., Letocart, V., Merlaud, A., and Pinardi, G.: QDOAS Software user manual, http://uv-vis.aeronomie.be/software/QDOAS, 2017.

[2].  Wagner, T., Apituley, A., Beirle, S., Dörner, S., Friess, U., Remmers, J., and Shaiganfar, R.: Cloud detection an classification based on MAX-DOAS observations, Atmos. Meas. Tech., 7, 1289–1320, https://doi.org/10.5194/amt-7-1289-2014, 2014.