Sensitivity of Modeled Soil NOx Emissions to Soil Moisture

Abstract

Nitrogen oxides (NOx = NO + NO 2 ) are direct air pollutants responsible for a range of negative health impacts and increased mortality (Forastiere & Peters, 2021). Beyond its direct health impacts, NOx also plays a crucial role in the formation of harmful secondary air pollutants, including ozone and particulate matter (Duncan et al., 2010;Hauglustaine et al., 2014). In the United States (U.S), fossil fuel combustion represents the largest source of NOx emissions, although fossil NOx emissions have been decreasing over the past two decades (Jiang et al., 2022). This decline in fossil NOx emissions has highlighted the increasing importance of other NOx sources, including soils, to the overall NOx budget (Geddes et al., 2022;Miyazaki et al., 2020). While soil NOx emissions (S NOx ) occur naturally in most soils, the most intense emissions are anthropogenic and occur in cropland regions where nitrogen-rich fertilizers are applied to soils (Almaraz et al., 2018). These anthropogenically-influenced emissions have local impacts (Lu et al., 2021). Biogenic S NOx form the bulk of background NOx concentrations, particularly in rural regions (Silvern et al., 2019). Given its growing importance to atmospheric NOx, improved understanding of processes controlling S NOx is imperative for improving our understanding of the role of NOx in the formation of secondary air pollutants and its influence on air quality (Geddes et al., 2022;Qu et al., 2021).

Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States

“…The model contains 35 vertical pressure levels from the surface to 50 hPa, with the lowest model layer height approximately 60 m. Model simulations were conducted for a 6-month period from 25 March 2019 to 30 September 2019, with the first week used for model spin up. We select 2019 as a year that was wetter than average in the Central and Eastern U.S. (Yin et al, 2020), providing a test case for the updated S NOx scheme (Huber et al, 2023) designed to minimize dry conditions that produce maximum S NOx in the original parameterization. The 6-month time period simulates the cropland growing season, including fertilizer application that heavily influences S NOx .…”

“…⎧ ⎨ ⎩ Each model grid cell has a unique combination of coefficients a, b, and c for Equation 5or Equation 6 optimized to produce g(NVSM) = 1 at the median NVSM and g(NVSM) = 0.02 at the relative wettest and driest conditions for a grid cell. While NVSM is a similar metric as WFPS, the range of modeled WFPS values at any given location throughout a year can be limited to a relatively narrow range, which can influence the magnitude of g(WFPS) and therefore modeled S NOx (Huber et al, 2023).…”

“…In this work, we run WRF-Chem for April-September 2019 using a central U.S. domain to evaluate the influence of S NOx on surface concentrations of NO 2 and secondary pollutants in cropland regions. We conduct sensitivity studies using three S NOx schemes: (a) MEGAN 2.04, (b) BDSNP, from here on referred to as the "standard BDSNP," and (c) an updated version of the BDSNP from Huber et al (2023) with a revised soil moisture parameterization. We hypothesize the updated parameterization, which produces peak S NOx at wetter soil conditions, will improve agreement with observed spatial and seasonal NO 2 trends.…”

Satellite NO2 trends reveal pervasive impacts of wildfire and soil emissions across California landscapes

“…Most soils in California have a porosity in the range of 0.4-0.6 [63] so our VSM peaks correspond to WFPS values in the approximate range of 0.05-0.35. A recent study by Huber et al [64] updated the BDSNP parameterization to fix the soil NO x emission peaks at the observed median VSM for spring/summer. Figure 3(b) shows the June-September median values of VSM by the dotted lines indicating that they are fairly similar to our observed peaks (difference <0.03) for each land type in California.…”

Large contribution of soil emissions to the atmospheric nitrogen budget and their impacts on air quality and temperature rise in North China

“…The first uncertainty comes from the amount of N fertilizer application, which has been identified as the dominant contributor to SNOx.In this study, we use the amount of agricultural N fertilizer application at the province level from the statistical yearbook to update the default N fertilizer application data in the model (the baseline year for 2006), but a recent study showed that compound fertilizer, usually with nitrogen (N), phosphorus (P), and potassium (K), were more commonly used in China; if only N fertilizer is considered to nudge the N fertilizer application data in the model, the estimated SNOx may be underestimated by 11.1%-41.5%(Huang et al, 2023). Furthermore, although we use the modeled green vegetation fraction (GVF) to determine the distribution of arid (GVF ≤ 30%) and nonarid (GVF > 30%) regions Huber et al (2023). showed that the estimated SNOx basedhttps://doi.org/10.5194/egusphere-2024-359 Preprint.…”