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

Quantification of methane emitted by ruminants: A review of methods

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH₄), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH₄ emissions. This review documents existing methods and methodologies to measure and estimate CH₄ emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH₄ have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH₄ for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH₄ from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH₄ emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH₄ emissions from manure depends on the type of storage, animal housing, CH₄ concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH₄ emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH₄ in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.

Nitrous oxide flux observed with tall-tower eddy covariance over a heterogeneous rice cultivation landscape

Although croplands are known to be strong sources of anthropogenic N₂O, large uncertainties still exist regarding their emission factors, that is, the proportion of N in fertilizer application that escapes to the atmosphere as N₂O. In this study, we report the results of an experiment on the N₂O flux in a landscape dominated by rice cultivation in the Yangtze River Delta, China. The observation was made with a closed-path eddy covariance system on a 70-m tall tower from October 2018 to December 2020 (27 months). Temperature and precipitation explained 78% of the seasonal and interannual variability in the observed N₂O flux. The growing season (May to October) mean flux (1.14 nmol m^-2 s^-1) was much higher than the median flux found in the literature for rice paddies. The mean N₂O flux during the observational period was 0.90 ± 0.71 nmol m^-2 s^-1, and the annual cumulative N₂O emission was 7.6 and 9.1 kg N₂O-N ha^-1 during 2019 and 2020, respectively. The corresponding landscape emission factor was 3.8% and 4.6%, respectively, which were much higher than the IPCC default direct (0.3%) and indirect emission factors (0.75%) for rice paddies.

Identifying hotspots and representative monitoring locations of field scale N2O emissions from agricultural soils: A time stability analysis

Greenhouse gas sampling from agricultural fields is laborious and time-consuming. Soil and topographical heterogeneity cause spatiotemporal variations, making nitrous oxide (N₂O) estimation and management a challenge. Identification of representative monitoring locations, hotspots, and coldspots could facilitate the mitigation of agricultural N₂O emissions. The objective of this study was to identify and characterize representative monitoring locations, hotspots, and coldspots of N₂O emissions in agricultural fields (Baggs farm; BF and Research North farm; RN) in Cambridge, Ontario, Canada, under humid continental climate. Soil in both fields was classified as Orthic Melanic Brunisol, with some areas categorized as Gleyed Brunisolic Gray Brown Luvisol and Orthic Humic Gleysol. In total, 28 sampling points were selected following conditional Latin hypercube design using topographical parameters (digital elevation, slope, topographical wetness index, and Pennock landform classification). Gas samples were collected over a two-year crop rotation with corn (2019) and soybean (2020). Additional sampling was conducted at BF at spring thaw (2020). Time stability analysis using mean relative difference (MRD) and standard deviation of mean relative difference (SDRD) was performed to test the hypothesis that "simultaneous analysis of spatiotemporal variations in N₂O emissions could help to identify and characterize representative monitoring locations, hotspots, coldspots and areas with few hot and cold moments. Most of the hotspots were located at shoulder positions, coldspots, and cold moments at backslope, and representative monitoring points were located at leveled positions or localized depressions. Time stability analysis coupled with multivariate groping analysis supported our hypothesis and helped successfully identify hotspots, coldspots, and representative locations based on landform classification with few exceptions. However, inclusion of additional topographical (curvature, contributing area, aspect) and morphological parameters (texture, thickness of soil horizon, depth to bedrock, and water table) are suggested for consideration in future research to manage variable-rate fertilizer application and mitigate N₂O hotspots at landscape level.

Impact of climate change on greenhouse gas emissions and water balance in a dryland-cropping region with variable precipitation

Wheat covers a significant fraction of the US Pacific Northwest (PNW) dryland agriculture. Past studies have suggested that management practices can differentially affect productivity and emission of greenhouse gases (GHGs) across the different agro-ecological Zones (AEZs) in PNW. In this study we used CropSyst, a biophysically-based cropping systems model that simulates crop processes and water and nitrogen cycles, with the purpose of evaluating relevant scenarios and contributing analyses to inform adaptation and mitigation strategies aimed at reducing and managing the risks of climate change. We compared the baseline historical period of 1980-2010 with three future periods: 2015-2045 (2030s), 2035-2065 (2050s), and 2055-2085 (2070s). The uncertainty of the future climate was captured using 12 general circulation models (GCMs) forced with two representative carbon dioxide concentration pathways (RCP 4.5 and 8.5). The study region was divided into three AEZs: crop-fallow (CF), continuous cropping to fallow transition (CCF), and continuous cropping (CC). The results indicated that areas with higher precipitation, N fertilization, and mineralization produced more N₂O emissions during both baseline and future periods. The average annual N₂O emission during the baseline period was between 1.8 and 4.1 kg ha^-1 depending on AEZ. The overall N₂O emission showed decreasing future trends from 2030s to 2070s which resulted from a higher proportion of N used by crops. From 2015 to 2085 under RCP 4.5, the average N₂O emission was between 1.8 and 4.4 kg ha^-1 year^-1. They are slightly higher under RCP 8.5 since it is a warmer scenario. The soil organic carbon (SOC) content decreased during the baseline period while SOC did not reach equilibrium with the cropping systems considered in the study. SOC decreased during the future periods as well, with rate of change ranging from -146 to -352 kg ha^-1year^-1 depending on AEZ and RCP. Warming increased SOC oxidation in future scenarios, but after an initial increase of SOC losses during the 2030s period, the rate of SOC losses decreased in the 2050s, and more so in the 2070s as SOC and carbon input reached equilibrium with losses. Higher carbon input resulted from higher biomass production under elevated CO₂ scenarios. The total GHG emissions were 1.95, 3.16 and 4.84 Mg CO₂-equivalent ha^-1year^-1 under RCP 4.5, and 1.99, 3.43 and 5.49 Mg CO₂-equivalent ha^-1year^-1 under RCP 8.5 during 2070s in CF, CCF and CC respectively, with N₂O accounting for about 81% of total GHG emissions.

Global Research Alliance N2 O chamber methodology guidelines: Recommendations for air sample collection, storage, and analysis

Certain aspects in the collection, handling, storage, and subsequent analysis of discrete air samples from non-steady-state flux chambers are critical to generating accurate and unbiased estimates of nitrous oxide (N₂ O) fluxes. The focus of this paper is on air sample collection and storage in small vials (<12 ml) primarily for gas chromatography (GC) analysis. Sample integrity is assured through following simple procedures including storage under pressure and analysis within a few months of collection. Concurrent storage of standards in an identical manner to samples is recommended and allows the storage period to be reliably extended. In the laboratory, an autosampler is typically used in batch analysis of ∼200 sequentially analyzed samples by GC with an electron capture detector (ECD). Some comparisons are given between GC and alternatives including optical N₂ O detectors that are increasingly being used for high-precision N₂ O measurement. The importance of calibration and traceability of gas standards is discussed, where high-quality standards ensure the most accurate assessment of N₂ O concentration and comparability between laboratories. The calibration allows a consistent and best estimate of flux to be derived.