Nitrous oxide emissions from irrigated cotton soils of northern Australia

An automated gas sampling methodology has been used to estimate nitrous oxide (N2O) emissions from heavy black clay soil in northern Australia where split applications of urea were applied to furrow irrigated cotton. Nitrous oxide emissions from the beds were 643 g N/ha over the 188 day measurement period (after planting), whilst the N2O emissions from the furrows were significantly higher at 967 g N/ha. The DNDC model was used to develop a full season simulation of N2O and N2 emissions. Seasonal N2O emissions were equivalent to 0.83% of applied N, with total gaseous N losses (excluding NH3) estimated to be 16% of the applied N

Parameter-induced uncertainty quantification of soil N 2 O, NO and CO 2 emission from Höglwald spruce forest (Germany) using the LandscapeDNDC model

Assessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development. The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used. Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes

What is needed for reducing the greenhouse gas footprint?

Livestock production is responsible for a large amount of greenhouse gas (GHG) emissions. However, numerous approaches have been developed to reduce these emissions and thus lower environmental pollution caused by livestock husbandry. This article shows where interventions are possible and which hurdles have to be cleared in implementing the various measures needed

Digestibility and metabolizable energy of selected tropical feedstuffs estimated by in vitro and prediction equations

In vivo determination of digestible organic matter (dOM) and metabolisable energy (ME) concentrations of feeds is laborious and expensive, whereas analysis of their nutrient contents is routinely performed. Prediction equations based on the chemical composition of feeds can be a compromise. This study compared dOM and ME estimates of tropical feeds derived from selected equations (Yan and Agnew, 2004; Stergiadis et al., 2015a; Stergiadis et al., 2015b; AFRC, 1993) with those determined by the in vitro gas production method (Menke and Steingass, 1988). Samples of supplement feedstuffs (n = 12) and the herbaceous and ligneous vegetation on native pastures (n = 12) were collected in Lower Nyando, Kenya, over two seasons of one year. Samples were analysed for dry matter (DM; in % of fresh matter), crude ash, crude protein, ether extract, neutral and acid detergent fiber (NDF, ADF) (all in % of DM). Gross energy was determined by calorimetry. Nutrient concentrations varied across all samples with 8.5 – 87.9% DM, 5.2 – 16.8% crude ash, 36.7 – 74.1% NDF, 25.5 – 39.4% ADF, 3.2 – 14.2% crude protein, and 0.6 – 4.5% ether extract. The gross energy, in vitro dOM, and ME concentrations were 14.5 – 18.8 MJ/kg DM, 26.3 – 54.5%, and 3.8 – 8.4 MJ/kg DM, respectively. Compared with the in vitro method, all nutrient-based equations overestimated dOM (P 0.5). Nutrient-based equations do not sufficiently account for differences in nutrient availability, an aspect better simulated in vitro. Further development and/or validation of nutrient-based equations might be needed to more accurately predict dOM and ME of tropical feeds. AFRC. 1993. Wallingford: CAB International. Stergiadis et al. 2015a. J Dairy Sci, 98(5), 3257–3273 Stergiadis et al 2015b. Brit J Nutr, 113(10), 1571–1584. Yan and Agnew. 2004. J Anim Sci., 82, 1367–1379

Estimating global terrestrial denitrification from measured N2_{2}O:(N2_{2}O + N2_{2}) product ratios

The use of nitrogen (N) fertilizers and cultivation of N-fixing crops has grown exponentially over the last century, with severe environmental consequences. Most of the anthropogenic reactive nitrogen will ultimately be returned by denitrification to the atmosphere as inert N$_{2}$, but the magnitude of denitrification and the ratio of N$_{2}$O to (N$_{2}$O + N$_{2}$) emitted (R$_{N_{2}O}$) is unknown for the vast majority of terrestrial ecosystems. This paper provides estimates of terrestrial denitrification and R$_{N_{2}O}$ by reviewing existing literature and compiling a N budget for the global land surface. We estimate that terrestrial denitrification has doubled from 80 Tg-N year$^{-1}$ in pre-industrial times to 160 Tg-N year$^{-1}$ in 2005 with a mean R$_{N_{2}O}$ of approximately 0.08. We conclude that upscaling of R$_{N_{2}O}$ can provide spatial estimates of terrestrial denitrification when data from acetylene inhibition methods are excluded. Recent advances in methodologies to measure N$_{2}$ emissions and R$_{N_{2}O}$ under field conditions could open the way for more effective management of terrestrial N flows

Soil-atmosphere exchange of N 2 O, CH 4 , and CO 2 and controlling environmental factors for tropical rain forest sites in western Kenya

[1] N 2 O, CH 4 and CO 2 soil-atmosphere exchange and controlling environmental factors were studied for a 3-month period (dry-wet season transition) at the Kakamega Rain forest, Kenya, Africa, using an automated measurement system. The mean N 2 O emission was 42.9 ± 0.7 mg N m À2 h À1 (range: 1.1-324.8 mg N m À2 h À1 ). Considering the duration of dry and wet season the annual N 2 O emission was estimated at 2.6 ± 1.2 kg N ha À1 yr À1 . Large pulse emissions of N 2 O were observed after the first rainfall events of the wet season, and the magnitude of N 2 O emissions steadily declined thereafter. A comparable trend in soil CO 2 emissions (mean: 71.8 ± 0.3 mg C m À2 h À1 ) indicates that the rapid mineralization of litter accumulated during the dry period produced the high N 2 O emissions at the start of the wet season. Manual N 2 O emission measurements at four additional rain forest sites were comparable to those measured at the main site, whereas N 2 O emissions measured at a regrowth site were significantly lower. Spatial differences in N 2 O emissions could be explained by differences in soil texture and topsoil C:N-ratio (CO 2 : subsoil C and N concentrations), whereas the temporal variability of N 2 O and CO 2 emissions was primarily driven by soil moisture. Soils predominantly acted as sinks for CH 4 (À56.4 ± 0.8 mg C m À2 h À1 ). For some chamber positions, episodes of net CH 4 release were observed, which could be due to high WFPS and/or termite activity. CH 4 fluxes were weakly correlated with soil moisture levels but showed no relation to temperature, texture, pH, carbon or nitrogen contents. Citation: Werner, C., R. Kiese, and K. Butterbach-Bahl (2007), Soil-atmosphere exchange of N 2 O, CH 4 , and CO 2 and controlling environmental factors for tropical rain forest sites in western Kenya

Nitrous oxide emission factors for cattle dung and urine deposited onto tropical pastures: A review of field-based studies

Livestock excreta on pastures is an important source of nitrous oxide (N2O) emissions, however studies measuring these emissions in tropical regions, particularly Africa, remain limited. Therefore we measured N2O emissions from different quantities of dung patches during three observation periods (dry, wet and transition from dry to wet season) and different volumes of urine patches during wet and dry seasons. Dung patches did not stimulate soil N2O emissions in any of the three observation periods, while urine application stimulated soil N2O emissions during both seasons, with higher emissions observed during the wet season. The dung EFs (0.00–0.03%) and the urine EFs (0.04–0.40%) showed no detectable effects of dung quantity or urine volume. We further synthesized observations from other studies in wet and dry tropical regions, which indicated that the excreta N2O EFs were similar to the default values provided in the IPCC 2019 refinement (0.11% vs 0.07% for dung and 0.41% vs 0.32% for urine in dry climates, and 0.13% vs 0.13% for dung and 0.65% vs 0.77% for urine in wet climates). However, sub-Saharan African (SSA) studies had consistently lower EFs, possibly due to the lower urine-N: dung-N ratio in SSA compared with the other tropical regions, suggesting that the refinement may still overestimate excreta emissions in SSA. Moreover, considering the large variations in the summarized tropical excreta N2O EFs, from -0.01 to 1.77% for dung and 0.00 to 4.90% for urine, more studies under diverse conditions across tropical regions are recommended

From research to policy: optimizing the design of a national monitoring system to mitigate soil nitrous oxide emissions

Nitrous oxide (N2O) emissions from agricultural soils are a key source of greenhouse gas emissions in most countries. In order for governments to effectively reduce N2O emissions, a national inventory system is needed for monitoring, reporting and verifying emissions that provides unbiased estimates with the highest precision feasible. Inventory frameworks could be advanced by incorporating experimental research networks targeting key gaps in process understanding and drivers of emissions, with a multi-stage survey to collect data on agricultural management and N2O fluxes that allow for development, parameterization and application of models to estimate national-scale emissions. Verification can be accomplished with independent estimation of fluxes from atmospheric N2O concentration data. A robust monitoring system would provide accurate emission estimates, and allow policymakers to develop programs to more sustainably manage reactive N and target mitigation measures for reducing N2O emissions from agricultural soils