the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Apr 2026
Numerical modeling on the mechanisms of chlorine chemistry in snowpack and their impact on secondary atmospheric pollution
Abstract. Snow with high albedo enhances atmospheric photochemical reactions, influencing key oxidative processes. Nitryl chloride (ClNO2), as a strong oxidizing species, is generated by the heterogeneous reaction between dinitrogen pentoxide (N2O5) and chloride adsorbed on aerosol and the ground surfaces. After sunrise, the photolysis of ClNO2 rapidly releases highly reactive chlorine radicals (Cl·), which contributes to the formation of secondary pollutants. However, the pollution mechanisms in high-latitude, snow-covered regions associated with increased chlorine emissions remain unclear. In this study, we employed the WRF-CAMx model (Weather Research and Forecasting Model-Comprehensive Air Quality Model with extensions) with a modified chemical mechanism (CB6r2h_lts, Carbon Bond 6 revision 2 with heterogeneous chemistry for low-temperature and snow-covered conditions) that incorporated heterogeneous N2O5 reactions and ClNO2 photolysis on ground surfaces to assess their impact on regional atmosphere under snow-covered conditions in Northeast China. Our findings reveal that under snow-covered conditions, the YU20 aerosol scheme (from study by YU et al., 2020) outperforms the BT09 scheme (from study by Bertram et al., 2009) in simulating N2O5 and ClNO2 concentrations within the CAMx model. Incorporating anthropogenic chlorine emissions and ground surface chemistry significantly improved model performance for ClNO2, reducing the mean bias (MB) from -105.78 pptv to 2.66 pptv and increasing the index of agreement (IOA) from 0.39 to 0.86. These processes resulted in a maximum hourly increase of 3.65 µg/m³ in PM2.5 (relative contribution: 15.34 %) and 3.41 ppbv in MDA8 O3 (5.68 %). Notably, ground surface chemical processes were identified as the dominant source of nocturnal ClNO2, contributing approximately 28.36 % to nighttime accumulation across Northeast China. These findings not only highlight the pivotal role of chlorine chemistry in atmospheric processes under snow-covered conditions, but also provide crucial support for the refinement of the mechanisms governing the flux exchange of chemical substances between the atmosphere and the cryosphere.
- Preprint
(3123 KB) - Metadata XML
-
Supplement
(1752 KB) - BibTeX
- EndNote
Status: open (until 31 Jul 2026)
- RC1: 'Comment on egusphere-2025-5338', Anonymous Referee #1, 13 Jun 2026 reply
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 225 | 49 | 24 | 298 | 34 | 24 | 24 |
- HTML: 225
- PDF: 49
- XML: 24
- Total: 298
- Supplement: 34
- BibTeX: 24
- EndNote: 24
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Xie et al. applied the WRF and CAMx models over Northeast China to investigate how chlorine chemistry in the atmosphere and on the snow-covered ground influenced atmospheric concentrations of N₂O₅, ClNO₂, PM₂.₅ and O₃. They modeled February and March of 2024 when atmospheric measurements are available for N₂O₅ and ClNO₂ at a suburban location in Changchun City, Northeast China. They modified CAMx to compare two heterogeneous chemistry schemes (YU20 and BT09) that parameterize reactive uptake of N₂O₅ and HCl (from coal burning emissions) to aerosol surfaces. They also utilize the CAMx surface chemistry model to investigate how reactive uptake of N₂O₅ and HCl by snowpack may influence atmospheric N₂O₅ and ClNO₂. Xie et al. find that the YU20 scheme performed better than BT09 at describing the observed concentrations of N₂O₅ and ClNO₂. They find that reactive uptake of N₂O₅ by aerosol (YU20 scheme) is more influential than reactive uptake to snowpack and adding chlorine/chloride emissions (ACEIC inventory) in combination. They note that ClNO₂ formation from N₂O₅ uptake is influential on model results for PM2.5, ozone and other oxidants. They suggest that future modeling studies (for similar winter conditions) should include these emissions and processes. This study expands on previous 1D modeling studies by presenting a 3D picture of model sensitivity to algorithms and input data. The results can provide useful guidance for modeling similar conditions and planning future field campaigns.
In section 2.5 (and elsewhere) I understood “anthropogenic chlorine emissions” to mean specifically the ACEIC inventory, especially gaseous HCl from coal combustion. Does the MEIC emission inventory include emissions of particulate chloride (PCl)? The ISORROPIA scheme in CAMx equilibrates HCl and PCl depending on aerosol pH and consequently emissions of both PCL and HCl contribute to available reactive chloride. Most likely, simulation Y1 includes some anthropogenic chloride emissions (i.e., PCl from MEIC) and the other simulations have more chloride/chlorine emissions (i.e., from ACEIC). The manuscript should clarify whether MEIC includes chloride emissions. Add a table summarizing mass of chloride/chlorine emissions from MEIC and ACEIC. Provide a citation for ACEIC when first mentioned.
The CAMx surface model can store pollutant mass within the snowpack, and this mass can be lost to the ground, e.g., via meltwater. Was loss of chloride from the snowpack in meltwater modeled, and was it influential?
The OH concentration differences mentioned at line 460 seem large (OH concentration difference ranged from -(1.73 × 106) cm-3 to 52.22 ×106 cm-3) and I suggest double checking.
A suitable reference for the CAMx surface model is Karamchandani et al. (2015). A suitable reference for the CAMx model is Emery et al., (2024). The CAMx v7.1 User’s Guide could be cited (Ramboll, 2021).
Is Bo Sea the same as the Bohai Sea? I think Bohai Sea is more commonly seen in English.
In several places numeric values are given with more precision than needed, for example line 47 “contributing approximately 28.36% to nighttime accumulation” could be “approximately 28%”. Consider whether less precision would make numbers more readable.
I found Figure S1 difficult to read, can the resolution be improved?
References
Emery, C., Baker, K., Wilson, G. and Yarwood, G., 2024. Comprehensive air quality model with extensions: formulation and evaluation for ozone and particulate matter over the US. Atmosphere, 15(10), p.1158.
Karamchandani, P., Emery, C., Yarwood, G., Lefer, B., Stutz, J., Couzo, E. and Vizuete, W., 2015. Implementation and refinement of a surface model for heterogeneous HONO formation in a 3-D chemical transport model. Atmospheric Environment, 112, pp.356-368.
Ramboll, 2020. User’s guide, comprehensive air quality model with extensions, version 7.10. Available at: https://www.camx.com/Files/CAMxUsersGuide_v7.10.pdf