Simulation of effect of climate, soils and management on N2O emission from grassland

Nitrous oxide (N2O) is a potent greenhouse gas with a high contribution from agricultural soils and emissions that depend on soil type, climate, crops and management practices. The N2O emissions therefore need to be included as an integral part of environmental assessment of agricultural production systems. A dynamical algorithm for N2O production and emission from agricultural soils was developed and included in the FASSET whole-farm model. The model simulated carbon and nitrogen (N) turnover on a daily basis. Both nitrification and denitrification was included in the model as sources for N2O production, and the N2O emissions were simulated to depend on soil microbial and physical conditions. The model was tested on experimental data of N2O emissions from grasslands in UK, Finland and Denmark, differing in climatic conditions, soil properties and management. The model simulated the general time course of N2O emissions and captured the observed effects of fertiliser and manure management on emissions. However, emissions from a soil with high clay content were overestimated with the model. Scenario analyses for grazed and cut grasslands were conducted to evaluate the effects of soil type, climatic conditions, grassland management and N fertilisation on N2O emissions. The soils varied from sandy to sandy loam and the climatic variation was taken to represent the climatic variation within Denmark. N fertiliser rates were varied from 0 to 500 kg N ha-1. The simulated N2O emissions showed a non-linear response to increasing N rates with increasing emission factors at higher N rates. The simulated emissions increased with increasing soil clay contents. There was no effect of climatic conditions. Emissions were slightly higher from grazed grasslands compared with cut grasslands at similar rates of total N input (fertiliser and animal excreta). The results indicate higher emission factors and thus higher potentials for reducing N2O emissions for intensively grazed grasslands on fine textured soils than for extensive cut based grasslands on sandy soils

Automated chamber technique for gaseous flux measurements: evaluation of a photoacoustic infrared spectrometer-trace gas analyzer

Experiments were made in order to evaluate the accuracy and sensitivity of a photoacoustic infrared trace gas analyzer (TGA) in conjunction with an automatic opening and closing chamber system developed for near-continuous (2 min intervals) soil gaseous flux measurements. Humidity interference tests on N2O, CH4, and CO2 concentrations measured by the TGA were carried out, and the results showed a linear interference, with correction factors of 3 x 10(-5)x, 1.9 x 10(-3)x and 4.4x 10(-3)x(x = H2O vapor ppm), respectively. CO2 interference on N2O and CH4 signals were also linear, with average correction factors of 2.8 x 10(-4)x and 6 x 10(-5)x(x = CO2 ppm), respectively. Laboratory intercomparisons between the TGA and GC measurements of N2O and CH4 standards showed good agreement (R-2 > 0.993), indicating the accuracy of the TGA for measurement of these gases at concentrations up to 100 and 40 ppm N2O and CH4, respectively. The relatively rapid measurement time for up to five gases simultaneously in 2 min, linearity, and ease of operation of the TGA represent major advantages compared to gas chromatography (GC). The automated chamber system provides a continuous measurement of fluxes with minimum disturbance to the soil environment enclosed by the chamber and provides the means, for example, of quantifying diurnal variability. In situ measurements of N2O-N and CH4-C fluxes with a sensitivity <10 g ha(-1) d(-1) (11.6 ng m(-2) s(-1)), as well as of CO, and water vapor (H2O), can be measured by the TGA when used with the automated system, and fluxes at background levels (i.e., from unfertilized soils) can be determined

UK emissions of the greenhouse gas nitrous oxide

Signatories of the Kyoto Protocol are obliged to submit annual accounts of their anthropogenic greenhouse gas emissions, which include nitrous oxide (N2O). Emissions from the sectors industry (3.8 Gg), energy (14.4 Gg), agriculture (86.8 Gg), wastewater (4.4 Gg), land use, land-use change and forestry (2.1 Gg) can be calculated by multiplying activity data (i.e. amount of fertilizer applied, animal numbers) with simple emission factors (Tier 1 approach), which are generally applied across wide geographical regions. The agricultural sector is the largest anthropogenic source of N2O in many countries and responsible for 75 per cent of UK N2O emissions. Microbial N2O production in nitrogen-fertilized soils (27.6 Gg), nitrogen-enriched waters (24.2 Gg) and manure storage systems (6.4 Gg) dominate agricultural emission budgets. For the agricultural sector, the Tier 1 emission factor approach is too simplistic to reflect local variations in climate, ecosystems and management, and is unable to take into account some of the mitigation strategies applied. This paper reviews deviations of observed emissions from those calculated using the simple emission factor approach for all anthropogenic sectors, briefly discusses the need to adopt specific emission factors that reflect regional variability in climate, soil type and management, and explains how bottom-up emission inventories can be verified by top-down modelling

Contribution of nitrification and denitrification to N2O emissions from urine patches

Urine deposition by grazing livestock causes an immediate increase in nitrous oxide (N2O) emissions, but the responsible mechanisms are not well understood. A nitrogen-15 (15N) labelling study was conducted in an organic grass-clover sward to examine the initial effect of urine on the rates and N2O loss ratio of nitrification (i.e. moles of N2O-N produced per moles of nitrate produced) and denitrification (i.e. moles of N2O produced per moles of N2O + N2 produced). The effect of artificial urine (52.9 g N m-2) and ammonium solution (52.9 g N m-2) was examined in separate experiments at 45 and 35% water-filled pore space (WFPS), respectively, and in each experiment a water control was included. The N2O loss derived from nitrification or denitrification was determined in the field immediately after application of 15N-labelled solutions. During the next 24 h, gross nitrification rates were measured in the field, whereas the denitrification rates were measured in soil cores in the laboratory. Compared with the water control, urine application increased the N2O emission from 3.9 to 42.3 μg N2O-N m-2 h-1, whereas application of ammonium increased the emission from 0.9 to 6.1 μg N2O-N m-2 h-1. In the urine-affected soil, nitrification and denitrification contributed equally to the N2O emission, and the increased N2O loss resulted from a combination of higher rates and higher N2O loss ratios of the processes. In the present study, an enhanced nitrification rate seemed to be the most important factor explaining the high initial N2O emission from urine patches deposited on well-aerated soils

Simulation of greenhouse gases following land-use change to bioenergy crops using the ECOSSE model. A comparison between site measurements and model predictions

This article evaluates the suitability of the ECOSSE model to estimate soil greenhouse gas (GHG) fluxes from short rotation coppice willow (SRC-Willow), short rotation forestry (SRF-Scots Pine) and Miscanthus after landuse change from conventional systems (grassland and arable). We simulate heterotrophic respiration (Rh), nitrous oxide (N2O) and methane (CH4) fluxes at four paired sites in the UK and compare them to estimates of Rh derived from the ecosystem respiration estimated from eddy covariance (EC) and Rh estimated from chamber (IRGA) measurements, as well as direct measurements of N2O and CH4 fluxes. Significant association between modelled and EC-derived Rh was found under Miscanthus, with correlation coefficient (r) ranging between 0.54 and 0.70. Association between IRGA-derived Rh and modelled outputs was statistically significant at the Aberystwyth site (r = 0.64), but not significant at the Lincolnshire site (r = 0.29). At all SRC-Willow sites, significant association was found between modelled and measurement-derived Rh (0.44 ≤ r ≤ 0.77); significant error was found only for the EC-derived Rh at the Lincolnshire site. Significant association and no significant error were also found for SRF-Scots Pine and perennial grass. For the arable fields, the modelled CO2 correlated well just with the IRGA-derived Rh at one site (r = 0.75). No bias in the model was found at any site, regardless of the measurement type used for the model evaluation. Across all land uses, fluxes of CH4 and N2O were shown to represent a small proportion of the total GHG balance; these fluxes have been modelled adequately on a monthly time-step. This study provides confidence in using ECOSSE for predicting the impacts of future land use on GHG balance, at site level as well as at national level