WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China

Abstract. Snow is a key component of the cryosphere and has significant impacts on surface energy balance, hydrology, atmospheric circulation, etc. In addition, numerous studies have indicated that snow impurities, especially nitrate, are sensitive to sunlight and can be photolyzed to emit reactive species including NO2 and HONO, which serve as precursors of O3 and radicals and disturb the overlying atmospheric chemistry. This makes snow a reservoir of reactive species, and this reservoir is particularly important in remote and pristine regions with limited anthropogenic emissions. The magnitude of snow chemical emissions is also influenced by snow physical properties, including snow depth, density, and concentrations of light-absorbing impurities (e.g., black carbon (BC) and dust). Exploring and elucidating the emissions and atmospheric consequences of the snow-sourced reactive species require a global or regional model with a snow module. Here, we parameterized atmospheric nitrate deposition and its distributions in snow using a regional chemical transport model, i.e., WRF-Chem (Weather Research and Forecasting Model coupled with Chemistry), and evaluated the performance of WRF-Chem in simulating snow cover; snow depth; and BC, dust, and nitrate concentrations with field observations in northern China, which is one of the regions with a dense and prolonged snow cover. In general, the model-simulated spatial variability in nitrate mass concentrations in the top snow layer (hereafter NITS) is consistent with observations. Simulated NITS values in northeast China from December 2017 to March 2018 had a maximum range of 7.11–16.58 µg g−1, minimum range of 0.06–0.21 µg g−1, and 4-month average of 2.72 ± 1.34 µg g−1. In comparison, observed values showed a maximum range of 9.35–33.43 µg g−1, minimum range of 0.09–0.51 µg g−1, and average of 3.74 ± 5.42 µg g−1. The model results show an underestimation especially in regions closes to large cities in northeastern China, most likely due to the underestimation of NOx emissions in these regions. Additionally, nitrate deposition, snowpack accumulation processes, and challenges in capturing fine-scale emission variability may also contribute to the bias. These results illustrate the ability of WRF-Chem to simulate snow properties including concentrations of reservoir species in northern China, and in the future, we will incorporate snow nitrate photolysis in the model, exploring the emissions of snow NOx from nitrate photolysis and the impacts on local and regional atmospheric chemistry and air pollutant transformations.

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Publication Details

Journal
Geoscientific model development
Published
2025-02-07
DOI
https://doi.org/10.5194/gmd-18-651-2025
Citations
1
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
1.30

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article

WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China

Shanna Yue, Chun Zhao, Xueyin Ruan, Xia Wang et al.
1 citations
Geoscientific model development
Atmospheric chemistry and aerosols
1.30
article

WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China

Shanna Yue, Chun Zhao, Xueyin Ruan, Xia Wang, Lei Geng, Tao Che, Jing Wang
article en
1 citations

Abstract

Abstract. Snow is a key component of the cryosphere and has significant impacts on surface energy balance, hydrology, atmospheric circulation, etc. In addition, numerous studies have indicated that snow impurities, especially nitrate, are sensitive to sunlight and can be photolyzed to emit reactive species including NO2 and HONO, which serve as precursors of O3 and radicals and disturb the overlying atmospheric chemistry. This makes snow a reservoir of reactive species, and this reservoir is particularly important in remote and pristine regions with limited anthropogenic emissions. The magnitude of snow chemical emissions is also influenced by snow physical properties, including snow depth, density, and concentrations of light-absorbing impurities (e.g., black carbon (BC) and dust). Exploring and elucidating the emissions and atmospheric consequences of the snow-sourced reactive species require a global or regional model with a snow module. Here, we parameterized atmospheric nitrate deposition and its distributions in snow using a regional chemical transport model, i.e., WRF-Chem (Weather Research and Forecasting Model coupled with Chemistry), and evaluated the performance of WRF-Chem in simulating snow cover; snow depth; and BC, dust, and nitrate concentrations with field observations in northern China, which is one of the regions with a dense and prolonged snow cover. In general, the model-simulated spatial variability in nitrate mass concentrations in the top snow layer (hereafter NITS) is consistent with observations. Simulated NITS values in northeast China from December 2017 to March 2018 had a maximum range of 7.11–16.58 µg g−1, minimum range of 0.06–0.21 µg g−1, and 4-month average of 2.72 ± 1.34 µg g−1. In comparison, observed values showed a maximum range of 9.35–33.43 µg g−1, minimum range of 0.09–0.51 µg g−1, and average of 3.74 ± 5.42 µg g−1. The model results show an underestimation especially in regions closes to large cities in northeastern China, most likely due to the underestimation of NOx emissions in these regions. Additionally, nitrate deposition, snowpack accumulation processes, and challenges in capturing fine-scale emission variability may also contribute to the bias. These results illustrate the ability of WRF-Chem to simulate snow properties including concentrations of reservoir species in northern China, and in the future, we will incorporate snow nitrate photolysis in the model, exploring the emissions of snow NOx from nitrate photolysis and the impacts on local and regional atmospheric chemistry and air pollutant transformations.

Geoscientific model developmentVol. 18(3)
University of Science and Technology of China (CN), Northwest Institute of Eco-Environment and Resources (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, University of Science and Technology of China, National Key Research and Development Program of China
Openalex Percentile: Top 26%
Atmospheric chemistry and aerosols
1.30
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