Determination of field scale ammonia emissions for common slurry spreading practice with two independent methods

Abstract

At a cropland and a grassland site field scale ammonia (NH<sub>3</sub>) emissions from slurry application were determined simultaneously by two approaches based on (i) eddy covariance (EC) flux measurements using high temperature Chemical Ionisation Mass Spectrometry (HT-CIMS) and on (ii) backward Lagrangian Stochastic (bLS) dispersion modelling using concentration measurements by three optical open path Fourier Transform Infrared (FTIR) systems. Slurry was spread on the fields in sequential tracks over a period of one to two hours. In order to calculate field emissions, measured EC/HT-CIMS fluxes were combined with flux footprint analysis of individual slurry spreading tracks to parameterise the NH<sub>3</sub> volatilisation with a bi-exponential time dependence. Accordingly, track-resolved concentration footprints for the FTIR measurements were calculated using bLS. Comparison of concentrations calculated from the parameterised fluxes with concentrations measured by impingers showed that the EC/HT-CIMS emissions on the two fertilisations corresponded to the impinger concentrations within 10 % while the bLS/FTIR results showed larger deviations. For both events, the period during fertilisation and the subsequent two hours contributed by more than 80 % to the total field emissions. Averaged over the two measurement methods, the cumulated emissions of the first day amounted to 17 ± 3 % loss of applied total ammoniacal nitrogen over the cropland and 16 ± 3 % over the grassland field

Evaluation of open and closed path sampling systems for determination of emission rates of NH3 and CH4 with inverse dispersion modelling

“…The light is absorbed in the cavity, and the decay of light intensity is called the ring-down time, which is directly related to the concentration of the specific compound. It has been frequently used to study agricultural emissions (e.g., Kamp et al, 2021;Pedersen et al, 2020;Kamp et al, 2019;Sintermann et al, 2011).…”

“…The inverse dispersion method (IDM) based on backward Lagrangian Stochastic (bLS) dispersion modelling (e.g. Flesch et al, 2004Flesch et al, , 1995 has been widely used for the assessment of NH3 and methane (CH4) emissions from many agricultural sources: dairy housing (Bühler et al, 2021;VanderZaag et al, 2014;Harper et al, 2009), cattle feedlot (McGinn et al, 2019;Todd et al, 2011;van Haarlem et al, 2008;Flesch et al, 2007;McGinn et al, 2007), application of liquid animal manure (Kamp et al, 2021;Carozzi et al, 2013;Sintermann et al, 2011;Sanz et al, 2010), grazed pasture (McGinn et al, 2011;Voglmeier et al, 2018), rice field (Yang et al, 2019), lagoon (Ro et al, 2014;Wilson et al, 2001), composting stockpiles (Sommer et al, 2004), agricultural biodigester (Baldé et al, 2016b;Flesch et al, 2011), farm (Flesch et al, 2005) and stored liquid manure (Lemes et al, 2022;Baldé et al, 2016a;Grant et al, 2015;McGinn et al, 2008).…”

Measuring dry deposition of ammonia using flux-gradient and eddy covariance methods with two novel open-path instruments

“…A long-line averaging open-path gas analyser allows measurements of path integrated NH3 concentrations at 85 a high time resolution. Optical analysers now available include those based on Fourier Transform Infrared (FTIR) (Sintermann et al, 2011;Flesch et al, 2016), tuneable diode laser TDL (Bai et al, 2022) or differential optical absorption DOAS spectroscopy (Volten et al, 2012b;Sintermann et al, 2016). These instruments can be used to measure the difference in NH3 concentration between two vertically offset paths, either in slant configuration (e.g.…”

Impacts of ammonia volatilization from broadcast urea on winter wheat production

“…Although several studies have quantified NH 3 volatilization under field conditions, most of these studies have often used soil static chambers with short sampling periods (minutes to hours) (Pacholski et al., 2006; Watson, Akhonzada, Hamilton, & Matthews, 2008; Rochette et al., 2009a; Rochette et al., 2009b; Chen et al., 2015; Thapa, Chatterjee, Johnson, & Awale, 2015). Such a sampling scheme may lead to substantial errors in total N loss estimation due to the high temporal and spatial variability of NH 3 fluxes (Sintermann et al., 2011). Thus, continuous and spatially integrated NH 3 fluxes are needed and will improve our understanding of the drivers governing the NH 3 volatilization process.…”