Assessing the ammonium nitrate formation regime in the Paris megacity and its representation in the CHIMERE model – Archive ouverte HAL

Hervé Petetin 1, 2 Jean Sciare 3 Michael Bressi 4 Valérie Gros 4, 5 Amandine Rosso 6 Olivier Sanchez 7 Roland Sarda-Estève 4, 5 Jean-Eudes Petit 4, 5 Matthias Beekmann 8

Hervé Petetin, Jean Sciare, Michael Bressi, Valérie Gros, Amandine Rosso, et al.. Assessing the ammonium nitrate formation regime in the Paris megacity and its representation in the CHIMERE model. Atmospheric Chemistry and Physics, European Geosciences Union, 2016, 16 (16), pp.10419 – 10440. ⟨10.5194/acp-16-10419-2016⟩. ⟨hal-01587430⟩

Secondary inorganic compounds represent a major fraction of fine aerosol in the Paris megacity. The ther-modynamics behind their formation is now relatively well constrained but, due to sparse direct measurements of their precursors (in particular NH 3 and HNO 3), uncertainties remain on their concentrations and variability as well as the formation regime of ammonium nitrate (in terms of limited species among NH 3 and HNO 3) in urban environments such as Paris. This study presents the first urban background measurements of both inorganic aerosol compounds and their gaseous precursors during several months within the city of Paris. Intense agriculture-related NH 3 episodes are observed in spring/summer while HNO 3 concentrations remain relatively low, even during summer, which leads to a NH 3-rich regime in Paris. The local formation of ammonium nitrate within the city appears low, despite high NO x emissions. The data set also allows evaluating the CHIMERE chemistry-transport model (CTM). Interestingly, the rather good results obtained on ammonium nitrates hide significant errors on gaseous precursors (e.g., mean bias of −75 and +195 % for NH 3 and HNO 3 , respectively). This leads to a misrepresenta-tion of the nitrate formation regime through a highly underestimated gas ratio metric (introduced by Ansari and Pandis, 1998) and a much higher sensitivity of nitrate concentrations to ammonia changes. Several uncertainty sources are investigated , pointing out the importance of better assessing both NH 3 agricultural emissions and OH concentrations in the future. These results remind us of the caution required when using of CTMs for emission scenario analysis, highlighting the importance of prior diagnostic and dynamic evaluations.

  • 1. AIRPARIF – Surveillance de la qualité de l’air en Île-de-France
  • 2. LISA (UMR_7583) – Laboratoire Interuniversitaire des Systèmes Atmosphériques
  • 3. CyI – Cyprus Institute
  • 4. LSCE – Laboratoire des Sciences du Climat et de l’Environnement [Gif-sur-Yvette]
  • 5. CAE – Chimie Atmosphérique Expérimentale
  • 6. LPTMS – Laboratoire de Physique Théorique et Modèles Statistiques
  • 7. HEGP – Hôpital Européen Georges Pompidou [APHP]
  • 8. CNRS – Centre National de la Recherche Scientifique

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