Impact of new retrieval settings on time-series and diurnal variation of retrieved ammonia total columns by ground-based remote sensing (OASIS observatory) over Greater Paris

Ammonia (NH3) has direct adverse effects on ecosystems and environment regarding the eutrophication and acidification of soils and water (Cape et al., 2009; Krupa, 2003). As the main alkaline molecule in the atmosphere, NH3 is also a gaseous precursor of other major secondary pollutants, such as inorganic fine particles: sulphate and ammonium nitrate particles (Seinfeld, and Pandis, 2006), which are very harmful to public health. Ammonia is an atmospheric pollutant mainly emitted by agricultural activities (e.g 80% of the emissions worldwide and 95% of the emissions in Europe) (Génermont et al., 2018; Skorupka and Nosalewicz, 2021) with part from traffic that is highly uncertain in urban areas (Cao et al., 2021). Ammonia emissions are projected to increase in the future due to population growth, rise in food demand and climate change. Despite its environmental impacts, ammonia is one of the least documented precursors of PM2.5 in France which is strongly related to the crucial lack of routine ammonia observations. One of the scientific reasons comes from the difficulty to measure atmospheric ammonia in situ due to its polar, sticky, volatile, and highly water-soluble nature (von Bobrutzki et al., 2010) resulting in strong interactions with sampling systems, recently well documented during the French AMICA* campaign. An innovative and very promising alternative for monitoring atmospheric ammonia is infrared remote sensing, from the ground or from space. The first multiyear time series of atmospheric NH3 ground-based measurements over a European megacity (Paris) was performed using Observations of the Atmosphere by Solar absorption Infrared Spectroscopy (OASIS) FTIR observatory, based on the NDACC stations’ methodology, and located in the Paris suburbs (France) (Tournadre et al., 2020). In this presentation, we test different a priori profiles and retrieval methods in order to investigate the robustness of the NH3-OASIS retrievals. We show the potential of the observatory to assess diurnal variability of ammonia focusing on spring pollution events such as in March 2012 (Kutzner et al., 2021) and compare the measured NH3-OASIS total columns to simulations from the CAMS data assimilation system (Inness et al., 2019).   *: AMICA consortium : Analysis of Multi-Instrumental Concentrations of Ammonia References Cape, J. N., et al., Environmental Pollution, 2009, 157(3), 1033–1037, https://doi.org/10.1016/j.envpol.2008.09.049 Krupa, S. V., Environmental Pollution, 2003, 124, Issue 2, 179–221, https://doi.org/10.1016/S0269-7491(02)00434-7 Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: from Air Pollution to Climate Change, third ed., John Wiley & Sons, New York, 1121 pp., 2016 Génermont, S., et al., Data in Brief, 2018, 21, 1119–1124 https://doi.org/10.1016/j.dib.2018.09.119 Skorupka, M., and Nosalewicz, A., Agriculture, 2021, 11(9). https://doi.org/10.3390/agriculture11090822 Cao H., et al., Environmental Science & Technology Letters, 2022 9 (1), 3-9 https://doi.org/10.1021/acs.estlett.1c00730 von Bobrutzki, et al., Atmos. Meas. Tech., 2010, 3, 91–112, https://doi.org/10.5194/amt-3-91-2010 Tournadre, B., et al., Atmos. Meas. Tech., 13, 3923–3937, https://doi.org/10.5194/amt-13-3923-2020, 2020. Kutzner, R. D., et al., Atmos. Chem. Phys., 21, 12091–12111, https://doi.org/10.5194/acp-21-12091-2021, 2021. Inness, A., et al., Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019.