Sensitivity of Modeled Soil NOx Emissions to Soil Moisture

As emissions of nitrogen oxides (NOx) from fossil fuel combustion decrease, the relative contribution of NOx emissions from managed and unmanaged soils (S-NOx) is increasing. Modeling S-NOx presents a challenge as it requires proper characterization of emission dynamics in response to environmental conditions. S-NOx is often represented using the Berkeley Dalhousie Soil NOx Parameterization (BDSNP), which relies upon static relationships between soil moisture and S-NOx for arid and non-arid lands. However, soil chamber and atmospheric studies have shown that emission characteristics are more dynamic, with peak emissions often occurring at higher soil moisture content. Here, to better capture observational studies, we update BDSNP by creating a dynamic S-NOx response to soil moisture based on a normalized soil moisture index. We compare the standard and updated parameterizations over the contiguous United States (U.S.) for 2011-2020 using input soil moisture data from ERA5-Land, MERRA-2 and NLDAS2-Mosaic and evaluate S-NOx across these different input drivers as well as between the standard and updated parameterizations. The standard parametrization exhibits strong sensitivity to different input soil moisture products, with annual U.S. S-NOx differences of up to 0.28 Tg N yr(-1). In contrast, the updated parameterization provides a robust representation of S-NOx with reduced sensitivity to input soil moisture product with differences of at most 0.03 Tg N yr(-1). The updated parameterization simulates a broad increase in S-NOx in non-arid regions, including much of the Eastern U.S., indicating that this region may be more sensitive to climatically-driven S-NOx as anthropogenic NOx emissions continue to decline.

Automated summary

As fossil fuel combustion decreases, the contribution of NOx emissions from managed and unmanaged soils (S-NOx) is increasing. While the Berkeley Dalhousie Soil NOx Parameterization (BDSNP) is commonly used to represent S-NOx, it relies on static relationships between soil moisture and S-NOx, which do not capture the dynamic nature of emissions. In this study, the BDSNP is updated to incorporate a dynamic S-NOx response to soil moisture, resulting in improved representation of S-NOx and reduced sensitivity to input soil moisture data.