Use of measurements and models to improve the national IPCC based assessments of soil emissions of nitrous oxide

Vries, Wim de; Kros, J.; Kuikman, P.J.; Velthof, G.L.; Voogd, J.C.H.; Wieggers, H.J.J.; Butterbach‐Bahl, Klaus; Gon, H.A.C. Denier van der; Amstel, A.R. van

doi:10.1080/15693430500395412

Cited by 16 publications

(11 citation statements)

References 25 publications

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“…The regression (y = 0.78x − 6.5) accounts for 85% of the variation in the data, but with the simulated values (y) underestimating measured values (x) by 24%. Similar data cited by De Vries et al (2005), from a range of published studies on grasslands and cereal systems, are also presented in Fig. 6.…”

Section: Arable Fieldsupporting

confidence: 75%

Application of the DNDC model to predict emissions of N2O from Irish agriculture

et al. 2009

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Models are increasingly used to examine the potential impacts of management and climate change in agriculture. Our aim in this paper was to assess the applicability of the field-DeNitrification DeComposition (DNDC) model in Irish agriculture. This study provides the results of that evaluation, which is a prerequisite for using the model for assessing management impacts in the future. The DNDC model was tested against seasonal and annual data sets of nitrous oxide flux from a spring barley field and a cut and grazed pasture at the Teagasc Oak Park Research Centre, Co. Carlow, Ireland. In the case of the arable field, predicted fluxes of N 2 O agreed well with measured fluxes for medium to high fertilizer input (70-160 kg N ha − 1 ) but poorly described those fluxes from zero fertilizer treatments. In terms of cumulative flux values, the relative deviation of the predicted fluxes from the measured values was a maximum of 6% for the highest N fertilizer inputs but increased to 30% for the medium N and more than 100% for the zero N fertilizer treatments. There is a linear correlation of predicted against measured flux values for all fertilizer treatments (r 2 = 0.85) but the model underestimated the seasonal flux by 24%. Incorporation of literature values from a range of different studies on arable and pasture land did not significantly improve the regression. The description by DNDC for measured fluxes of N 2 O from reduced tillage plots was poor with underestimation of up to 55%. For the cut and grazed pasture the relative deviations of predicted to measured fluxes were 150 and 360% for fertilized and unfertilized plots. A sensitivity analysis suggests that the poor model fit is due to DNDC overestimating WFPS and the effect of initial soil organic carbon (SOC) on N 2 O flux. As the arable and grassland soils differed only in SOC content, reducing SOC of the grassland field to that of the arable field value significantly improved the fit of the model to measured data such that the relative deviations decreased to 9 and 5% respectively. Sensitivity analysis highlighted air temperature as the main determinant of N 2 O flux, an increase in mean daily air temperature of 1.5°C resulting in almost a 65% increase in the annual cumulative flux. This is interesting as with future global warming, N 2 O flux from the soil will have a strong positive feedback. It can be concluded that DNDC is unsuitable for predicting N 2 O from Irish grassland due to its overestimation of WFPS and effect of SOC on the flux.

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Section: Arable Fieldsupporting

confidence: 75%

Application of the DNDC model to predict emissions of N2O from Irish agriculture

et al. 2009

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“…The N input by deposition was not included, in line with common practice when calculating N 2 O emission factors from measurements [IPCC, 2006]. A similar approach was used by de Vries et al [2005] to estimate emission factors with INITIATOR on the basis of national N 2 O emission estimates. In this research no unfertilized plots were considered, but Velthof et al [1996a] measured the background emissions for an unfertilized wet and an unfertilized dry plot from the same farm during 2 years, yielding a measured background emission of 8.6 kg N ha À1 a À1 for the dry plot and 2.0 kg N ha À1 a À1 for the wet plot.…”

Section: Comparison Of Simulated Annual Average Emission Factors Withmentioning

confidence: 99%

Effect of temporal resolution on N₂O emission inventories in Dutch fen meadows

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Heuvelink

Vries

et al. 2009

Global Biogeochemical Cycles

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[1] Most countries use a 1-year-resolution emission factor approach (Tier 1 or 2) to estimate terrestrial N 2 O emissions as part of their national greenhouse gas inventory. Little attention has so far been paid to the effect of the temporal resolution of the approach (e.g., day, season, and year) on N 2 O emission estimates. The effect of lumping temporal variation can be very large because of daily or seasonal variations of processes causing N 2 O emissions. Therefore, we compared annual N 2 O emissions from a model with daily time steps (DNDC) with those of a model with annual time steps (INITIATOR). Emissions were simulated for two intensively managed grassland plots in the Dutch fen meadow landscape. Annual N 2 O emissions from the investigated grasslands were sensitive to rainfall distribution within the year, especially to summer rainfall. We recommend that Tier 2 N 2 O emission estimates for intensively managed grasslands on peat soils in the temperate climate zone are adjusted for relative summer rainfall.

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“…De Vries et al (2003a) provided an extensive description. An extended version of INITIATOR can simulate CO 2 emissions from soils, CH 4 emissions, NH 3 emissions and N 2 O emissions from housing systems, and leaching and runoff of P, base cations and heavy metals (De Vries et al, 2005), but here we focus on N 2 O emissions from soils, notably peat soils. INITIATOR uses 48 model inputs to model N 2 O emission from soils.…”

Section: The Model Initiatormentioning

confidence: 99%

“…In INITIATOR, the CO 2 emission is calculated as a function of thickness and organic matter content of the peat layer, soil wetness and land use (De Vries et al, 2005). Using the C/N ratio of the peat layer, the N mineralization is modelled.…”

Section: The Model Initiatormentioning

confidence: 99%

Uncertainty propagation analysis of an N2O emission model at the plot and landscape scale

et al. 2010

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Use of measurements and models to improve the national IPCC based assessments of soil emissions of nitrous oxide

Cited by 16 publications

References 25 publications

Application of the DNDC model to predict emissions of N2O from Irish agriculture

Application of the DNDC model to predict emissions of N2O from Irish agriculture

Effect of temporal resolution on N₂O emission inventories in Dutch fen meadows

Uncertainty propagation analysis of an N2O emission model at the plot and landscape scale

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Use of measurements and models to improve the national IPCC based assessments of soil emissions of nitrous oxide

Cited by 16 publications

References 25 publications

Application of the DNDC model to predict emissions of N2O from Irish agriculture

Application of the DNDC model to predict emissions of N2O from Irish agriculture

Effect of temporal resolution on N2O emission inventories in Dutch fen meadows

Uncertainty propagation analysis of an N2O emission model at the plot and landscape scale

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Effect of temporal resolution on N₂O emission inventories in Dutch fen meadows