N₂O Emissions From Two Agroecosystems: High Spatial Variability and Long Pulses Observed Using Static Chambers and the Flux‐Gradient Technique

Abstract

With the addition of nitrogen (N), agricultural soils are the main anthropogenic source of N2O, but high spatial and temporal variabilities make N2O emissions difficult to characterize at the field scale. This study used flux‐gradient measurements to continuously monitor N2O emissions at two agricultural fields under different management regimes in the inland Pacific Northwest of Washington State, USA. Automated 16‐chamber arrays were also deployed at each site; chamber monitoring results aided the interpretation of the flux gradient results. The cumulative emissions over the six‐month (1 April–30 September) monitoring period were 2.4 ± 0.7 and 2.1 ± 2 kg N2O‐N/ha at the no‐till and conventional till sites, respectively. At both sites, maximum N2O emissions occurred following the first rainfall event after N fertilization, and both sites had monthlong emission pulses. The no‐till site had a larger N2O emission factor than the Intergovernmental Panel on Climate Change Tier 1 emission factor of 1% of the N input, while the conventional‐till site's emission factor was close to 1% of the N input. However, these emission factors are likely conservative. We estimate that the global warming potential of the N2O emissions at these sites is larger than that of the no‐till conversion carbon uptake. We recommend the use of chambers to investigate spatiotemporal controls as a complementary method to micrometeorological monitoring, especially in systems with high variability. Continued monitoring coupled with the use of models is necessary to investigate how changing management and environmental conditions will affect N2O emissions.

An evaluation of four years of nitrous oxide fluxes after application of ammonium nitrate and urea fertilisers measured using the eddy covariance method

“…Emissions observed from the fields were most varied after N application, for which fluxes varied log-normally over time, as is often observed with eddy covariance (Jones et al, 2011;Merbold et al, 2014;Liang et al, 2018) the flux-gradient method (Wagner-Riddle et al, 2007;Glenn et al, 2012;Abalos et al, 2015;Waldo et al, 2019) and chamber methods (Levy et al, 2017). Although each 30-minute flux measurement represents a large footprint (> 100 m 2 ), there remains some spatial variability in the reported measurements because the method is reporting measurements weighted towards a particular part of the field at any given time, depending on wind speed and direction.…”

Management zone‐based estimation of positive and negative nitrous oxide flux in organic corn fields

“…Peak N 2 O emissions were mostly observed immediately after rainfall by most studies, which may explain why their magnitudes of highest N 2 O emissions were larger than those observed in our work. While use of multi‐temporal sampling with automated chambers can address deficiencies in single time point sampling (Barton et al., 2008; Scheer et al., 2013; Waldo et al., 2019; Yao et al., 2009), these highly instrumented systems are likely too costly to deploy widely. Future work may consider strategically determining sampling point and time based on anticipated hotspots and hot moments for the deployment of more costly measurements.…”

Quantification of methane emitted by ruminants: a review of methods

“…Laser technologies, Fourier-transform infrared, and other optical techniques continue to grow in popularity for analyzing CH 4 concentrations because of their low detection limits, a higher degree of precision, and ability to measure multiple GHGs simultaneously at the sampling location ( Brannon et al, 2016 ; Harvey et al, 2020 ). These include quantum cascade laser (QCL) ( Nelson et al, 2002 ; Cowan et al, 2014 ), and other spectroscopic techniques with QCL like cavity ring-down spectroscopy ( Christiansen et al, 2015 ; Brannon et al, 2016 ), and off-axis integrated cavity output ( Brannon et al, 2016 ; Waldo et al, 2019 ; Harvey et al, 2020 ). Infrared adsorption measurement detectors are ideal for automated chamber systems and in situations that require frequent, high precision measurements.…”