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Tendencies of Soil Microbial NO Emissions During HI‐SCALE as Predicted by a Nitrification/Denitrification Scheme.

Title:	Tendencies of Soil Microbial NO Emissions During HI‐SCALE as Predicted by a Nitrification/Denitrification Scheme.
Authors:	Gaudet, B.¹ (AUTHOR) Brian.Gaudet@pnnl.gov; Fast, J.¹ (AUTHOR); Rasool, Q.^2,3 (AUTHOR); Shrivastava, M.¹ (AUTHOR); Tai, S.‐L.¹ (AUTHOR); Zaveri, R.¹ (AUTHOR); Zhang, J.⁴ (AUTHOR)
Source:	Journal of Geophysical Research. Atmospheres. 3/28/2026, Vol. 131 Issue 6, p1-22. 22p.
Subject Terms:	Denitrification; Nitrifying bacteria; Atmospheric chemistry; Soil air; Soil moisture; Atmospheric ozone
Geographic Terms:	Great Plains; United States
Abstract:	Many atmospheric chemical processes, including the formation of secondary organic aerosol (SOA), are strongly modulated by the reactions of NO and NO2NOx ${\text{NO}}_{2}\ \left({\text{NO}}_{x}\right)$. Though NOx ${\text{NO}}_{x}$ is controlled by anthropogenic emissions near urban areas, in rural areas soil microbes can be a significant contribution to NO emission globally. The relative rates of emissions of different nitrogen‐containing species (e.g., NO, N2O ${\mathrm{N}}_{2}\mathrm{O}$, HONO, and N2 ${\mathrm{N}}_{2}$) are strong functions of soil properties such as temperature, moisture content, pH, and soil carbon and nitrogen pools. However, typical large‐scale biogeochemical models either express these emissions simplistically, or not at all. Here we investigate the potential impact of soil NO emissions on atmospheric NOx ${\text{NO}}_{x}$ chemistry and SOA formation over regional and monthly time scales, specifically the 2016 spring and summer Intensive Observational Periods (IOPs) of the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI‐SCALE) field campaign. We implement the soil NO nitrification/denitrification parameterization of Rasool et al. (2019) into the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem), supplemented by a 1‐km soil moisture analysis. We then simulate both IOPs over the U.S. Great Plains, evaluating against ground stations and flight data. We show that soil NO emissions can account for a large fraction of total NOx ${\text{NO}}_{x}$ and locally increase O3 ${\mathrm{O}}_{3}$ concentrations by up to 25%, while alleviating negative biases of gases and aerosols toward observations. Soil moisture and temperature changes between IOP1 and IOP2 lead to overall differences in emissions, but with large regional variability due to heterogeneous surface characteristics. Plain Language Summary: Nitric oxide (NO) is a gaseous species that when emitted near the surface can have strong impacts on atmospheric chemical processes that can generate various pollutants, such as nitrogen dioxide (NO2 ${\text{NO}}_{2}$) and ozone (O3 ${\mathrm{O}}_{3}$), as well as aerosols that can serve as cloud droplet nuclei and hence impact cloud structure and lifetime. While NO chiefly arises from man‐made sources, far away from local sources the emission of NO from soil microbes can be significant, and is thought to account for as much as 20%–25% of the global total. Most models that would be used to predict atmospheric chemistry over a region such as the U.S. Great Plains over timescales of less than a few months do not take soil NO emissions into account in sufficient detail, as they are complex functions of soil temperature, soil moisture, and other surface properties. In this study we take a soil NO emission model and implement it into the widely used WRF‐Chem atmospheric model. Simulations of the U.S. Great Plains over 2 months from a field campaign show better agreement with the observations when soil NO is included and we use a new data set of 1‐km soil moisture. Key Points: Microbial soil NO emissions can significantly impact modeled nitrogen/ozone chemistry over rural areas of the U.S. Great PlainsSoil NO emissions reduce but do not eliminate negative biases in gaseous/aerosol species when evaluated against aircraft and surface dataModeled soil NO emission shows seasonal dependencies based on soil moisture and temperature, but modulated by soil type [ABSTRACT FROM AUTHOR]
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