Presentation Information
[AAS08-P37]Improving nitrate aerosol dynamics in remote regions in the GEOS-Chem model
*Mitsuki Nakajima1, Sakiko Ishino1, Yoshinori Iizuka2, Sumito Matoba2, Ryu Uemura3, Shohei Hattori4 (1.School of Geosciences and Civil Engineering, Kanazawa University, 2.Institute of Low Temperature Science, Hokkaido University, 3.Graduate School of Environmental Studies, Nagoya University, 4.International Center for Isotope Effects Research, Nanjing University, China)
Keywords:
Atmospheric nitrate,Chemical transport model,Ice core
Atmospheric nitrate (= HNO3 + p-NO3-) and its precursor NOx, mainly from fossil fuel combustion, contribute to various environmental problems, including adverse health effects, radiative forcing, and excessive nitrogen input to ecosystems (Hauglustaine et al., 2014; Gong et al., 2024). However, large uncertainties remain in quantitative assessments of the atmospheric nitrate burden. Inter-model comparisons have shown discrepancies exceeding a factor of 13 in the global burden of p-NO3- (Bian et al., 2017). The GEOS-Chem model substantially overestimates p-NO3- concentrations in the remote marine atmosphere (Nault et al., 2021). Similar model overestimations have also been found in a long-term Arctic ice core record (Iizuka et al., 2025).
Wet deposition of HNO3 and p-NO3- is one potential process that causes the high NO3- bias in models. Luo et al. (2020) improved the wet deposition scheme in GEOS-Chem and reported enhanced reproducibility of near-surface aerosol concentrations across Europe, North America, and East Asia. However, their model evaluations have mainly focused on urban and near-source regions, and their impact on long-range transport and deposition in remote regions remains unexamined.
In this study, we evaluate whether the updated wet deposition scheme by Luo et al. (2020) improves the simulation of long-range transport of atmospheric nitrate using multiple observational datasets from remote regions. We used a three-dimensional global chemical transport model GEOS-Chem (v14.4.3; Bey et al., 2001) with a horizontal resolution of 4°×5° and 47 vertical layers up to 0.01 hPa (∼81 km). Meteorological fields from MERRA-2 and emission inventories were consistent with Iizuka et al. (2025). Simulations were conducted for 1850, 1900, 1973, 2000, and 2017 using both the default configuration ("Base" model) and the updated wet deposition scheme ("Wet-scav" model; Luo et al., 2020). The model was evaluated using three different observations of NO3- in remote regions: NO3- ion concentrations from a southeastern Greenland ice core site covering 1800 to 2020 (Iizuka et al., 2025), HNO3 and p-NO3- over the Northern Hemispheric marine atmosphere from the NASA Atmospheric Tomography Mission (ATom-1 and 2) project, and total NO3- observations at the Jungfraujoch station (3571 m a.s.l.) in the Swiss Alps from 1999 to 2013 (Frohlich et al., 2015).
The Base model overestimated ice core NO3- by approximately a factor of two, consistent with Iizuka et al. (2025). The Wet-scav model improved agreement for the most recent year (2017). However, it still overestimates nitrate during pollution peak periods (1973 and 2000). Seasonal analysis revealed a reversed seasonal cycle in the model compared with observations, with maximum deposition in winter and minimum in summer. This discrepancy was particularly pronounced during polluted periods, indicating excessive wintertime nitrate transport. In comparisons with ATom aircraft data and Jungfraujoch observations, the Wet-scav model also revealed systematic overestimation in winter, confirming a widespread seasonal bias in the free troposphere. In the presentation, we discuss the causes of this persistent wintertime overestimation of nitrate in remote regions.
Wet deposition of HNO3 and p-NO3- is one potential process that causes the high NO3- bias in models. Luo et al. (2020) improved the wet deposition scheme in GEOS-Chem and reported enhanced reproducibility of near-surface aerosol concentrations across Europe, North America, and East Asia. However, their model evaluations have mainly focused on urban and near-source regions, and their impact on long-range transport and deposition in remote regions remains unexamined.
In this study, we evaluate whether the updated wet deposition scheme by Luo et al. (2020) improves the simulation of long-range transport of atmospheric nitrate using multiple observational datasets from remote regions. We used a three-dimensional global chemical transport model GEOS-Chem (v14.4.3; Bey et al., 2001) with a horizontal resolution of 4°×5° and 47 vertical layers up to 0.01 hPa (∼81 km). Meteorological fields from MERRA-2 and emission inventories were consistent with Iizuka et al. (2025). Simulations were conducted for 1850, 1900, 1973, 2000, and 2017 using both the default configuration ("Base" model) and the updated wet deposition scheme ("Wet-scav" model; Luo et al., 2020). The model was evaluated using three different observations of NO3- in remote regions: NO3- ion concentrations from a southeastern Greenland ice core site covering 1800 to 2020 (Iizuka et al., 2025), HNO3 and p-NO3- over the Northern Hemispheric marine atmosphere from the NASA Atmospheric Tomography Mission (ATom-1 and 2) project, and total NO3- observations at the Jungfraujoch station (3571 m a.s.l.) in the Swiss Alps from 1999 to 2013 (Frohlich et al., 2015).
The Base model overestimated ice core NO3- by approximately a factor of two, consistent with Iizuka et al. (2025). The Wet-scav model improved agreement for the most recent year (2017). However, it still overestimates nitrate during pollution peak periods (1973 and 2000). Seasonal analysis revealed a reversed seasonal cycle in the model compared with observations, with maximum deposition in winter and minimum in summer. This discrepancy was particularly pronounced during polluted periods, indicating excessive wintertime nitrate transport. In comparisons with ATom aircraft data and Jungfraujoch observations, the Wet-scav model also revealed systematic overestimation in winter, confirming a widespread seasonal bias in the free troposphere. In the presentation, we discuss the causes of this persistent wintertime overestimation of nitrate in remote regions.