Dndc model paper edited

1Application of the DNDC model to predict emissions of N 2O from Irish

2agriculture.

3
4M. Abdalla1, M. Wattenbach2, P. Smith2, P. Ambus3, M. Jones1 and M. Williams1
5
61Department of Botany, School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland
72School of Biological Sciences, University of Aberdeen, Cruickshank Building, St. Machar Drive,
8Aberdeen, AB24 3UU, UK.
93Riso Research Centre, Technical University of Denmark, Frederikborgvej 399, DK-4000,
10Roskilde
11
12Key words: Nitrous oxide, DNDC model, arable, pasture
13
14ABSTRACT
15
16A mechanistic model that describes N fluxes from the soil, DeNitrification
17DeComposition (DNDC), was tested against seasonal and annual data sets of nitrous
18oxide flux from a spring barley field and a cut and grazed pasture at the Teagasc Oak
19Park Research Centre, Co. Carlow, Ireland. In the case of the arable field, predicted
20fluxes of N2O agreed well with measured fluxes for medium to high fertilizer input values
21(70 to 160 kg N ha-1) but described poorly measured fluxes from zero fertilizer
22treatments. In terms of cumulative flux values, the relative deviation of the predicted
23fluxes from the measured values was a maximum of 6% for the highest N fertilizer inputs
24but increased to 30% for the medium N and more than 100% for the zero N fertilizer
25treatments. A linear correlation of predicted against measured flux values for all fertilizer
26treatments (r2 = 0.85) was produced, the equation of which underestimated the seasonal
27flux by 24%. Incorporation of literature values from a range of different studies on arable
28and pasture land did not significantly affect the regression slope. DNDC describe poorly
29measured fluxes of N2O from reduced tillage plots of spring barley. Predicted cumulative
30fluxes of N2O on plots disc ploughed to 10cm, underestimated measured values by up to
3155%.
32

1 1

1For the cut and grazed pasture the relative deviations of predicted to measured fluxes
2were 150 and 360% for fertilized and unfertilized plots. This poor model fit is considered
3due to DNDC overestimating the effect of initial soil organic carbon (SOC) on N 2O flux,
4as confirmed by a sensitivity analysis of the model. As the arable and grassland soils
5differed only in SOC content, reducing SOC to the arable field value significantly
6improved the fit of the model to measured data such that the relative deviations decreased
7to 9 and 5% respectively. Sensitivity analysis highlighted air temperature as the main
8determinant of N2O flux, an increase in mean daily air temperature of 1.5oC resulting in
9almost 90% increase in the annual cumulative flux. Using the Hadley Centre Global
10Climate Model data (HCM3) and the IPCC emission scenarios A2 and B2, DNDC
11predicted increases in N2O fluxes of approximately 30% (B2) and 60% (A2) from the
12spring barley field and approximately 20% (A2 and B2) from the cut and grazed pasture
13by the end of this centaury (2061-2090).
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31

1 2

1INTRODUCTION
2
3National inventories of N2O fluxes from agricultural soils, as required by signatory
4countries to the United Nations Framework Convention of Climate Change (UNFCC),
5are in the main derived from the use of the default IPCC Tier 1 method, where 1.25% of
6applied inorganic nitrogen to agricultural soils is assumed to be released to the
7atmosphere as nitrous oxide-N (Bouwman, 1996; IPCC, 1997; 2000). This standard
8reporting procedure has advantages in collating annual inventories but may mask
9significant variations in emission factors (EFs) on a regional scale (Schmid et al., 2001;
10Laegreid and Aastveit, 2002). For instance in Ireland, published EFs derived from field
11measurements of N2O using either eddy covariance or static chamber methods vary from
123.4% for Cork grassland and 0.7 to 4.9% of the applied N fertilizer for the Wexford
13grassland depending on soil type, land management, climate and year (Hsieh et al., 2005;
14Hyde et al., 2005; Flechard et al., 2007).
15
16Given the considerable expense of establishing and maintaining relevant flux
17measurement sites, the use of simulation models to estimate N 2O fluxes from agricultural
18soils using soil and climate data has obvious benefits. Modelling also allows easy
19interpretation of the complex links between soil physical, chemical and microbial
20processes that underpin nitrification, denitrification and decomposition. Models can
21simulate the processes responsible for production, consumption and transport of N 2O in
22both the long and short term, and also on a spatial scale (Williams et al., 1992).
23
24Simulation models range from simple empirical relationships based on statistical analyses
25to complex mechanistic models that consider all factors affecting N 2O production in the
26soil (Li et al., 1992; Frolking et al., 1998; Stenger et al., 1999; Freibauer 2003; Roelandt
27et al., 2005; Jinguo et al., 2006). Variations in soil moisture, soil temperature, carbon and
28nitrogen substrate for microbial nitrification and denitrification are critical to the
29determination of N2O emissions (Leffelaar and Wessel, 1988; Tanji, 1982; Frissel and
30Van Veen, 1981; Batlach and Tiedje, 1981; Cho et al., 1979). One widely used
31mechanistic model is DeNitrification DeComposition (DNDC) developed to assess N 2O,

1 3

1NO, N2 and CO2 emissions from agricultural soils (Li et al., 1992a, 1994; Li 2000). The
2rainfall driven process-based model DNDC (Li et al., 1992) was originally written for
3USA conditions. It has been used for simulation at a regional scale for the United States
4(Li et al., 1996) and China (Li et al., 2001). Advantages of DNDC are that it has been
5extensively tested and has shown reasonable agreement between measured and modelled
6results for many different ecosystems such as grassland (Brown et al., 2001; Hsieh et al.,
72005; Saggar et al., 2007), cropland (Li, 2003; Cai et al., 2003, Yeluripati et al., 2006;
8Pathak et al., 2006; Tang et al., 2006) and forest (Li, 2000; Stange et al., 2000; Kesik et
9al., 2006). The model has reasonable data requirement and is suitable for simulation at
10appropriate temporal and spatial scales.

11The DNDC model contains 4 main sub-models (Li et al., 1992; Li, 2000); the soil climate
12sub-model calculates hourly and daily soil temperature and moisture fluxes in one
13dimension, the crop growth sub-model simulates crop biomass accumulation and
14partitioning, the decomposition sub-model calculates decomposition, nitrification, NH 3
15volatilization and CO2 production whilst the denitrification sub-model tracks the
16sequential biochemical reduction from nitrate (NO3) to NO2-, NO, N2O and N2 based on
17soil redox potential and dissolved organic carbon.
18
19This paper presents a field evaluation of DNDC for an Irish sandy loam soil under both
20arable and grassland crops with different fertilizer and tillage regimes. Results are
21discussed in terms of the suitability of this model for estimating annual and seasonal
22fluxes of N2O from Irish agriculture. In addition, DNDC is used to estimate future N2O
23fluxes from Irish agriculture due to climate change using climate data generated by the
24Hadley Centre Global Climate models (HadCM3; Sweeney and Fealy, 2003).
25
26
27
28
29
30

1 4

1MATERIALS AND METHODS
2
3Experiments
4Measurements of N2O flux were carried out for a spring barley field from April–August for
5two consecutive seasons (2004/05), and for a cut and grazed pasture from October 2003 to
6November 2004. Both fields were located at the Oak Park Research Centre, Carlow,
7Ireland (52o86′ N, 6o54′ W). The arable field was seeded with spring barley (cv. Tavern) at
8a density of 140 kg ha-1 and managed under two different tillage regimes; conventional
9tillage where inversion ploughing to a depth of 22 cm was carried out in March, five weeks
10prior to planting, and reduced tillage to a depth of 15 cm which was carried out in
11September of the year before. The field was sprayed with weed killer (Roundup Sting) at
124.0L ha-1, three times per season, once pre- and twice post-planting.

13The cut and grazed pasture has been permanent grassland for at least the past eighty years
14and was ploughed and reseeded in October 2001 with perennial ryegrass (Lolium perenne
15L., cv Cashel) at a density of 13.5 kg ha -1 and white clover (Trifolium repens L., cv Aran)
16at a density of 3.4 kg ha-1. Daily minimum and maximum air temperature (oC) and rainfall
17in (mm) were recorded at the Teagasc Research Centre Weather Station (Met Eireann).
18Initial soil properties and climate factors of both sites are summarized in Table 1.

19

20For the arable field in 2004, three rates of N-fertilization 140 (N1), 70 (N2) and 0 (N3) kg
21N ha-1, were applied once on the 27th of April, whereas in 2005, two fertilizer applications
22took place on the 12th of April 106 (N1), 53 (N2) and 0 (N3) kg N ha-1, and on the10th of
23May 53 (N1), 26 (N2) and 0 (N3) kg N ha-1. The total amount of N-fertilization applied in
242005 was therefore 159 (N1), 79 (N2) and 0 (N3) kg N ha-1. For the cut and grazed pasture,
25nitrogen fertilizer was applied at a total rate of 200 kg N ha -1 y-1 divided in to two
26applications of 128 and 72 kg N ha -1 on the 2nd of April and the 27th of May respectively.
27Separate areas of the field were kept unfertilized as control plots. Fertilizer was applied in
28the form of Calcium Ammonium Nitrate (CAN). Animal grazing was from July to
29November 2003 and from July to November 2004 with a stocking rate of 2 cattle ha-1.
30Field N2O fluxes

1 5

1Nitrous oxide fluxes were measured from 24 replicated chambers at the arable field and 7
2replicated chambers at the cut and grazed pasture, using the methodology of Smith et al.,
3(1995). Measurements were taken every week except for times of fertilizer application
4where sampling was increased to 2 times per week. Samples were taken using a 60 ml
5gas-tight syringe after flushing of the syringe to ensure adequate mixing of air within the
6chamber. All 60 ml of the sample was then injected into a 3ml gas-tight vial with a vent
7needle inserted into the top, and stored until analysis. Gas samples were measured within
8one month of collection using a gas chromatograph (Shimadzu GC 14B, Kyoto, Japan)
9with electron capture detection.
10
11DNDC model
12In this study the DNDC model (version 8.9; http://www.dndc.sr.unh.edu/) was tested for
13both the arable field and the cut and grazed pasture. All field management variables,
14including grain yield, fertilizer application and tillage system (where reduced tillage was
15defined as disk or chisel ploughing to 10cm) were input into the model. Soil properties
16and climate input data are summarized in Table 1. For the arable field model testing was
17possible only for the growth period of the crop, whilst for the cut and grazed pasture 12
18months of data were used. The model testing was carried out by (1) comparing the
19measured and modelled temporal pattern of weekly N 2O flux values, (2) comparing the
20measured and modelled cumulative N2O fluxes (using weekly values), and (3) comparing
21the measured and modelled emission factors.
22
23The relative deviation (y) of the modelled flux from measured flux values was calculated
24by the following equation:
25
26Y = (XS – XO)/XO x 100,
27
28where XO and XS are the measured and modelled fluxes respectively. Annual and
29seasonal cumulative flux for DNDC outputs were calculated as the sum of simulated
30daily fluxes (Cai et al., 2003). EFs for the modelled data were calculated by subtracting
31cumulative DNDC flux data for unfertilized soils from that of the fertilized soils and

1 6

1dividing by the N fertilizer input corrected for ammonia volatilization (10%). Sensitivity
2analysis was carried out by varying a single determinant factor whilst keeping other
3factors constant for one annual cycle of the model. Determinant factors tested are listed in
4Table 4.
5
6Simulation of future N2O flux
7Climate change impact on N2O fluxes from the spring barley and the cut and grazed
8pasture was studied using climate data generated from the Hadley Centre Global Climate
9Model (HadCM3; Sweeney and Fealy, 2003). A baseline climate period (1961-1990) and
10two future climate scenarios 2055 (2041-2070) and 2075 (2061-2090) were investigated
11along with the IPCC emission scenarios A2 and B2 (Nakicenovic et al., 2000; IPCC,
122007). Data generation was provided by the Department of Geography, National
13University of Ireland, Maynooth (Sweeney and Fealy, 2003). Elevations in CO2 were
14assumed by 2055 to be 581 ppmv and by 2075 to be 700 ppmv compared with a baseline
15concentration of 365 ppmv CO2 compatible with the IS95a (IPCC, 1995). Field
16managements for both the spring barley and the cut and grazed pasture were assumed to
17be the same management as in 2004 for all scenarios (Table 1).
18
19
20
21
22
23
24
25
26
27
28
29
30
31RESULTS AND DISCUSSION

1 7

1
2Results presented in this paper assess the reliability of the DNDC model for estimating
3N2O fluxes from both a spring barley field and a cut and grazed pasture by validating
4model output with flux measurements collected on a weekly basis for up to two years.
5Several management practices were examined, including conventional tillage, reduced
6tillage and variable rates of N-fertilizer application. Climate and soil input variables for
7DNDC are illustrated in Table 1. Field data measurements were used for all of the
8variables listed except for atmospheric CO2, rainfall N, clay fraction and depth of the soil
9water retention layer. Here default values were used. Collectively DNDC was better at
10predicting N2O fluxes for high inputs of N fertilizer (>140 kg N ha -1) than for zero or low
11N input treatments (0 to 70 kg N ha-1). In addition the model appeared to be unduly
12sensitive to the influence of soil organic carbon. DNDC predicted a significant increases
13of approximately 20 to 60% in future N2O fluxes from Irish cereal and grassland fields,
14by the end of this centaury.
15
16Arable field
17Measurements of N2O flux were limited to the growth period of the barley crop hence
18annual estimates of flux were not produced. Figures 1 to 3 relate to a comparison of the
19modelled and measured fluxes for 2004/2005 as either daily values (Figures 1 to 2), or
20cumulative flux (Figure 3). In general the temporal pattern of N 2O flux was different
21between modelled and measured data, DNDC extending the influence of added fertilizer
22over a wider time period and producing smaller peaks. This is more pronounced for the
23higher fertilizer treatments in 2004 than 2005 (Figures 1A, 1C and 2A) and can be clearly
24seen in the cumulative flux plots (Figures 3A and 3B). This discrepancy between the
25years maybe related to DNDC overestimating the water filled pore space (WFPS) in 2004
26as opposed to 2005, WFPS being a critical determinant of N 2O flux at the time of
27fertilizer application (Keller and Reiners, 1994; Ruser et al., 1998; Dobbie and Smith,
282001). This is illustrated in Figure 4A where modelled WFPS values were consistently
29higher than measured values in 2004, with maximum differences of 25 to 30% being
30recorded. In comparison, modelled values for 2005 approximated to measured values
31with maximum differences of only 13 to 16%.

1 8

1The tillage options provided by DNDC do not allow the reduced, non-inversion tillage
2used in our study to be fully described. In contrast to the conventional tillage plots,
3DNDC significantly underestimated the N2O flux from the reduced tillage plots for the
4medium and higher fertilizer treatments by up to 55% (Figures 3B and 3D). This may not
5be critical for modeling N2O fluxes from Irish agriculture as reduced cultivation and
6direct drilling of cereal crops represents at most only 10% of arable land, < 40,000 ha
7(Fortune et al., 2003; ECAF, 2004).
8
9Cumulative fluxes from sowing to harvest are given in Table 2. Modelled fluxes for the
10high fertilizer inputs agreed with field measured values, giving the smallest relative
11deviations from field data of -1 and -6%. These deviations increase significantly as
12fertilizer input is reduced. The largest % deviation, and hence the worst fit was obtained
13for the zero fertilizer treatments, with relative deviations of -35 to more than 5000%
14calculated. Clearly DNDC is best suited for medium to high N input treatments and does
15not account for negative flux values that can occur in low to zero N input treatments
16where the soil acts as a sink for N 2O (Ryden, 1981; Clayton et al., 1997). Similar DNDC
17results for high and medium N fertilizer inputs have been reported for rice fields by
18Zheng et al., 1999 (381 kg N ha-1; 8% deviation), for maize fields by Crill et al., 2000
19(181 kg N ha-1; 3.5% deviation), for grass by Hsieh et al., 2005 (337 kg Nha-1; 33%
20deviation) and for barley fields by Flessa et al., 1995 (50 kg N ha-1; 36% deviation).
21However, these observations are not consistent in the literature. In contrast to our results
22far better agreements between modelled and measured flux values have been obtained for
23low to zero N inputs by Li, (1992), Mosier et al., (1996), Terry et al., (1981) and Crill et
24al., (2000).
25
26The wide range of CAN input values provided by this study allowed a linear regression of
27modelled vs measured cumulative fluxes underlining the suitability of DNDC for
28predicting N2O flux. This is illustrated in Figure 5, where observed and modelled data
29from Table 2 have been plotted. The regression (y = 0.78x - 6.5) accounts for 85% of the
30variation in the data, the predicted y values underestimating measured values by 24%.
31Similar data cited by De Vries et al., (2005), from a range of published studies on

1 9

1grasslands and cereal systems, is also presented in Figure 5. Data from our study fits well
2within this group and improves the slope of the regression to y = 1.1x + 0.35, (r2 = 0.76).
3
4Cut and grazed pasture
5Our results suggest that DNDC is unduly sensitive to initial soil organic carbon content.
6Measured and modelled cumulative fluxes of N 2O from the cut and grazed pasture are
7shown in Table 3 (annual) and Figure 6 (weekly) and highlight the poor fit of the model
8where high relative deviation values were calculated. The only major difference between
9the arable and the cut and grazed pasture soils is that the latter has significantly higher
10organic carbon content (0.038 as opposed to 0.019 kg C kg-1 dwt). Changing the initial
11soil organic C content for the model to the lower, arable soil value greatly improved the
12fit of the model to the observed values (Figure 6). Using these new values the annual N 2O
13flux for the fertilized plots is 2797 g N 2O-N ha-1 (a relative deviation of 9%) and for the
14control plots is 1110 g N2O-N ha-1 (a relative deviation of 5%) as shown in Table 3. This
15would question the present algorithms in the model describing the effect of soil organic
16carbon on N2O flux. The model is very sensitive to SOC; a 20% increase in SOC
17corresponds to a 62% increase in N2O flux (see below). Similar over-estimations of the
18effects of initial SOC by DNDC have also been reported by Li et al., (1992a), Brown et
19al., (2002) and Hsieh et al., (2005).
20
21Sensitivity analysis
22Given the good fit of the model to the conventional tillage data, the sensitivity of the
23model outputs for the arable field to changes in soil characteristics, fertilizer N and
24climate were also investigated. The following scenarios were chosen:
25(1) Changes in bulk density
26(2) Changes in initial SOC
27(3) Changes in fertilizer use
28(4) Changes in rainfall and air temperature.
29
30The model appears highly sensitive to changes in bulk density and as mentioned
31previously, SOC. Increasing the bulk density of the soil from 1.4 to 1.8 g cm-1, an

1 10

1increase of 29%, resulted in a more than equivalent increase in both the apparent rate of
2denitrification (53%) and the predicted N2O flux (89%), these increases presumably due
3to more substrate N being made available through increased mineralization (Table 4).
4Thus according to DNDC, any management treatment that increases the bulk density of
5the soil, such as reduced tillage, would also significantly increase N 2O flux as has been
6observed by Aulakh et al., (1984); Baggs et al., (2003) and Six et al., (2004). Reduced
7tillage is also associated with increases in SOC. By increasing the baseline SOC value by
820% increases N2O flux by 85%. Hence for at least two associated aspects of reduced
9tillage, N2O flux has been predicted to increase significantly questioning the use of this
10management technique as a means of lowering total greenhouse gas emissions from the
11soil (Six et al., 2004; Li et al., 2005).
12
13Model outputs were also highly sensitive to changes in fertilizer type, with a switch from
14the principle form of N fertilizer used in cereal production in Ireland, CAN, to urea or
15ammonium sulphate fertilizers resulting in predicted increases in N2O flux of 76 and 81%
16respectively. Model outputs however, proved the most sensitive to changes in air
17temperature. Here an increase of 1.5oC in the daily average air temperature resulted in a
1889% increase in N2O flux and a 73% increase in the rate of soil denitrification. In
19contrast, changes in rainfall of ± 20% resulted in changes in N2O flux of the order of ±
2026%.
21
22For the arable field, emission factors for the modelled data ranged from 0.3 to 0.6% of the
23fertilizer N applied, whereas measured EFs ranged from 0.4 to 0.7% of the fertilizer N
24applied. Modelled and measured EFs are comparable, but are both significantly lower
25than the IPCC default value of 1.25%. However, literature EF values for cereal crops are
26extremely variable, ranging from 0.2 to 8% (Eichner, 1990; Kaiser et al., 1998; Smith et
27al., 1998, Dobbie et al., 1999) and are dependent upon temperature, moisture and soil
28type (Flechard et al., 2007).
29
30
31Simulation of future N2O flux

1 11

1Figures 7 and 8 illustrate the DNDC predicted fluxes of N 2O from both the barley field
2(conventional tillage only) and the cut and grazed pasture for emission scenarios A2 and
3B2 using data generated by the Hadley Centre Global Climate Model. A baseline climate
4period (1961-1990) and two future climate scenarios for 2055 (2041-2070) and 2075
5(2061-2090) were investigated.

6Future temperatures are expected to increase especially during the spring and summer
7periods of crop growth and fertilizer application. ICARUS (2006) predicts the July mean
8temperature to increase by up to 2.5oC by the end of this century which will influence soil
9denitrification and consequently N2O flux (Addiscott, 1983; Scott et al., 1986;
10Beauchamp et al., 1989; Flessa et al., 2002). Wetter winters are also predicted, increasing
11by as much as 11% by the end of the century (ICARUS, 2006). Besides displacement of
12N2O by soil water, as the WFPS increase, the diffusion of oxygen into soil aggregates
13will decrease stimulating denitrification (Dobbie and Smith, 2001). These increases in
14temperature and rainfall effects will result in seasonal increases in N 2O flux as clearly
15seen in Figure 7.
16In all cases DNDC simulates three specific peaks in N 2O flux throughout the year, the
17magnitude of these peaks being greatest for the cut and grazed pasture. The first peak
18from day 50 to 75 is primarily due to seasonal rainfall, as is the third peak from day 225
19to 350, the second peak however, from day 100 to 150 relates to fertilizer application. A
20major difference between the two fields is that the third peak for the spring barley field
21also coincides with crop residue incorporation resulting in a more spiked appearance. For
22both crops however, DNDC simulated an increase in N 2O emissions with each climate
23scenario due to increasing CO2, temperature and rainfall variability. This increase is
24particularly prominent for each seasonal peak in the spring barley field, but for the cut
25and grazed pasture seems primarily associated with the third peak (Figures 7 and 8).

26Annual cumulative fluxes derived from the modelled outputs are summarised in Table 5,
27and illustrate a significantly greater flux of N2O-N from the cut and grazed pasture due to
28higher N fertilizer application rate in addition to organic N inputs from grazing cattle.
29However the modelled baseline value of approximately 15 kg N 2O-N ha-1 y-1 is almost 5
30times higher than the measured annual flux for 2004 (Table 3), even assuming the same

1 12

1initial SOC value as the cereal field. Major seasonal differences between the modelled
2and measured flux values appear to centre on the first and third seasonal peaks, none of
3which were seen to occur for the grassland field in 2004 (data not shown). Accepting this
4limitation on model outputs there would appear to be no significant difference between
5the emission scenarios A2 and B2 with regard to both grassland and cereal fluxes of N2O
6by the year 2075. Here fluxes are predicted to increase by approximately 20% for
7grassland sites to 18 kg N2O-N ha-1 and by approximately 30 to 60% for the cereal sites to
86 kg N2O-N ha-1 y-1 (Table 5).
9
10CONCLUSIONS
11
12In its present format DNDC is only suitable for medium to high N input systems, the
13accuracy of the prediction being highly dependant on the level of fertilizer application,
14with high fertilizer inputs producing low relative deviations between modelled and
15measured fluxes of the order of 1 to 6% for the arable field under conventional tillage.
16Prediction of N2O fluxes from reduced tillage plots however was poor with DNDC
17consistently underestimating measured field values. Here relative deviations ranged from
18-20 to -93%. One major disadvantage of the model was the limited choice of tillage input
19options available, none describing the reduced tillage treatment used in this study.
20Prediction of N2O fluxes from the cut and grazed grassland was also poor with model
21outputs significantly overestimating measured field values giving relative deviations of
22150 to 360%. From the sensitivity analysis we tentatively suggest that DNDC
23overestimates the effect of SOC on mineralization and denitrification. By reducing the
24SOC input values to those of the cereal field we could significantly improve the fit of the
25model, reducing relative deviation scores to approximately 5 -10%.
26
27Accepting the limitations of the model we used DNDC to predict future increases in N 2O
28flux due to climate change for our cereal and grassland fields in Ireland using the Hadley
29Centre Global Climate Model data and the IPCC emission scenarios A2 and B2. Both
30fields resulted in significant increases in N2O flux by the year 2075, grassland flux
31increasing by 19 to 22% and arable flux increasing by 31 to 59%. In actual terms the

1 13

1predicted flux for 2075 is significantly higher for grassland fields (18 kg N 2O-N ha-1 y-1)
2than for the cereal fields (6 kg N2O-N ha-1 y-1) with little difference being observed
3between the A2 and B2 scenarios.
4
5ACKNOWLEDGEMENTS
6
7This work was funded by the EU sixth framework program (contract EVK2-CT2001-
800105, Greengrass Project Europe) and Irish EPA project No: 2001-CD-C1M1.
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31REFERENCES

1 14

1
2Addiscott, T.M., 1983. Kinetics and temperature relationships of mineralization and

3 nitrification in Rothamsted soils with differing histories. Soil Science 34, 343-
4 353.

5Aulakh, M.S., Rennie D.A., Paul, E.A., 1984. The influence of plant residues on

6 denitrification rates on conventional and zero-tilled soils. Soil Science Society of
7 America Journal 48, 790-794.

8Baggs, E.M., Stevenson, M., Pihlatie, M., Regar, A., Cook, H., Cadish, G. 2003. Nitrous

9 oxide emissions following application of residues and fertilizer under zero and
10 conventional tillage. Plant and Soil 254, 361-370.

11Batlach, R.M. and Tiedje, J.M., 1981. Kinetic explanation for accumulation of nitrite,

12 nitric oxide and nitrous oxide during bacterial denitrification. Applied and
13 Environmental Microbiology 42, 1074-1084.

14Beauchamp E.G., Trevors J.T., Paul J.W., 1989. Carbon sources for bacterial

15 denitrification. Advances in Soil Sciences 10, 113-142.

16Bouwman, A.F., 1996. Direct emissions of nitrous oxide from agricultural soils. Nutrient

17 Cycling in Agro-ecosystems 46, 53-70.

18Brown, L., Jarvis, S.C., Headon, D., 2001. A farm scale bases for predicting nitrous oxide

19 emissions from dairy farms. Nutrient Cycling in Agro-ecosystems 60, 149-158.

20Brown, L., Syed, B., Javris, S.C., Sneath, R.W., Philips, V.R., Goudling, K.W.T., Li, C.,

21 2002. Development and application of mechanistic model to estimate emission of
22 nitrous oxide from UK agriculture. Atmospheric Environment 36, 917-928.

23Cai, Z., Swamoto, T., Li, C., Kang, G., Boonjawat, J., Mosier, A., Wassmann, R.,

24 Tsuruta, H., 2003. Field validation of the DNDC-model for greenhouse gas
25 emissions in East Asian cropping systems. Global Biogeochemical Cycles 17, No.
26 4, 1107.

1 15

1Cho, C.M., Sakdinan, L., Chang, C., 1979. Denitrification intensity and capacity of three

2 irrigated Alberta soils. Soil Science Society of America Journal 43, 949-950.

3Clayton, H., McTaggart, I.P., Parker, J., Swan, L., Smith, K.A., 1997. Nitrous oxide

4 emissions from fertilized grassland: A 2-year study of the effects of N fertilizer
5 form and environmental conditions. Biology and Fertility of Soils 25, 252-260.

6Crill, P., Keller, M., Weitz, A., Grauel, B., Veldkamp, E., 2000. Intensive field

7 measurements of nitrous oxide emissions from a tropical agricultural soil. Global
8 Biogeochemical Cycles 14, 85-96.

9De Vries, W., Kros, J., Kuikman, P.J., Velthof, G.L., Voogd, J.C.H., Weiggers, H.J.J.,

10 Butterbach-Bahl, Denier Van der Gon, H.A.C., Van Amstel, A.R., 2005. Use of
11 measurements and models to improve the national IPCC based measurements of
12 soil emissions of nitrous oxide. Environmental Sciences 2, 217-233.

13Dobbie, K. E., McTaggart, I.P., Smith K. A., 1999. Nitrous oxide emissions from

14 intensive agricultural systems: variations between crops and seasons; key driving
15 variables; and mean emission factors. Journal of Geophysical Research 104,
16 26891-26899. Eaton, I.J. and Patriquin, D.J., 1989. Denitrification in low bush
17 blue berry soils. Canadian Journal of Soil Science 69, 303-312.

18Dobbie, K. E. and Smith K. A., 2001. The effects of temperature, water filled pore space

19 and land use on N2O emissions from imperfectly drained gleysol. European
20 journal of Soil Science, 52, 667-673.

21Eichner, M.J., 1990. Nitrous oxide emissions from fertilized soils: summary of available

22 data. Journal of Environment Quality 19, 272-280.

23ECAF, 2004. European Conservation Agriculture Federation, 2004. http:// www.ecaf.org

24Flechard, C., Ambus, P., Skiba, U., Rees, R.M., Hensen, A., Van den Pol, A., Soussana,

25 J.F., Jones, M., Clifton-Brwon, J., Raschi, A., Horvath, L., Van Amstel, A.,Neftel,
26 A., Jocher, M., Ammann, C., Fuhrer, J., Calanca, P., Thalman, E., Pilegaard, K.,

1 16

1 Di Marco, C., Campbell, C., Nemitz, E., Hargreaves, K.J., Levy, P., Ball, B.,
2 Jones, S., Van de Bulk, W.C.M., Groot, T., Blom, M., Gunnink, H., Kasper, G.,
3 Allard, V., Cellier, P., Laville, P., Henault, C., Bizouard, F., Jolivot, D., Abdalla,
4 M., Williams, M., Baronti, S., Berretti, F., Grosz, B., Dominques, R., 2007.
5 Effects of climate and management intensity on nitrous oxide emissions in
6 grassland systems across Europe. Agriculture, Ecosystems and Environment 121.
7 135-152.

8Flessa, H., Dorsh, P., Beese, F., 1995. Seasonal variation of N2O and CH4 fluxes
9 in differently managed arable soils in southern Germany. Journal of Geophysical
10 Research 100, 23115-23124.
11Flessa, H, Ruser, R., 2002. N2O and CH4 fluxes in potato fields: automated

12 measurement, management effects and temporal variation. Geoderma 105, 307-
13 325.

14Fortune, T., Kennedy, T., Mitchell, B., Dunne, B., 2003. Reduced cultivation- Agronomic
15 and Environmental Aspects. www.teagasc.ie/publications/2003.
16Freibauer, A. and Kaltschmitt, 2003. Regionalized inventory of biogenic greenhouse gas

17 emissions from European agriculture. European Journal of Agronomy 19, 135-
18 160.

19Frissel, M. and Van Veen, J.A., 1981.Simulation of nitrogen behaviour of soil plant

20 systems (eds). PUDOC, Wageningen. P. 277.

21Frolking, S.E., Mosier, A.R., Ojima, D.S., Li, C., Parton, W.J., Potter, C.S., Priesack, E.,

22 Stenger, R., Haberbosch, C., Dorsch, P., Flessa, H., Smith, K.A., 1998.
23 Comparisons of N2O emissions from soils at three temperate agricultural sites:
24 simulations of year-round measurements by four models. Nutrients Cycling in
25 Agro-ecosystems 52, 77-105.

26Hsieh, C.I., Leahy, P., Kiely, G., Li, C., 2005. The effect of future climate perturbations

27 on N2O emissions from a fertilized humid grassland. Nutrient Cycling in Agro-
28 ecosystems 73, 15-23.

1 17

1Hyde, B., Ryan, M., Hawkins, M., Connolly, J., Carton, O.T., 2005. Nitrous oxide

2 emissions. End of Project Report, RMIS 4974. Teagasc, Johnstown Castle
3 Research Centre, Co. Wexford.

4ICARUS, 2006. Irish Climate Analysis and Research Unit. www.icarus.nuim.ie

5IPCC, 1995. Greenhouse gases and aerosols. Climate Change. Cambridge University

6 Press, Cambridge, pp. 1-41.

7IPCC, 1997. Revised 1996 IPCC guidelines for national greenhouse gas inventories.

8 IPCC/OECD/IEA, IPCC, Geneva, Switzerland.

9IPCC, 2000. Good practice guidance and uncertainty management in national greenhouse

10 gas inventories. In: Liep, A., Dammgen, U., Kuikman, P., Van Amstel, A., 2005.
11 The quality of European (EU-15) greenhouse gas inventories from agriculture.
12 Environmental Sciences 2, 177-192.

13IPCC, 2007.Climate Impacts, Adaptation and Vlunerability. IPCC WGII Fourth

14 Assessment Report, Geneva, Switzerland.

15Jinguo Y., Zheng N., Chenli W., 2006. Vegetation NPP distribution based on MODIS

16 data and CASA model–A case study of northern Hebei province. Chinese
17 Geographical Science 16, 334-341.

18Kaiser, E.A., Kohrs, K., Kucke, M., Schnug, E., Heinemeyer, O., Munch, J.C., 1998.

19 Nitrous oxide release from arable soil: Importance of fertilization, crops and
20 temporal variation. Soil and Biochemistry 30, 1553-1563.

21Keller, M. and Reiners, W.A. 1994. Soil-atmosphere exchange of nitrous oxide, nitric

22 oxide, and methane under secondary succession of pasture to forest in the Atlantic
23 lowlands of Cost Rica. Global Biogeochemical Cycles 8, 399-409.

24Keisk, M., Ambus, P., Baritz, R., Bruggemann, N., Butterbach-bahl, K., Damm, M.,

1 18

1 Duyzer, J., Hovarth, L., Kiese, R., Kitzler, B., Leip, A., Li, C., Pihlatie, M.,
2 Pilegaard, K., Seufert, G., Simpson, D., Smaiatek, G., Skiba, U., Vesala, T.,
3 Zechmeisster-Boltenstern, S., 2006. Inventory of N 2O and NO emissions from
4 European forest soils. Biogeosciences. Physiological Research111, GO2018.

5Laegreid M. and Aastveit A.H., 2002. Nitrous oxide emissions from field applied

6 fertilizers. In: Petersen S.O and Olesen J.E. (Eds.). Greenhouse gas inventories for
7 agric. In the Nordic Countries, DIAS Report. Plant production no, 81. Danish
8 Institute of Agriculture. Sciences, pp. 122-134.

9Leffelaar, P.A. and Wessel, W.W., 1988. Denitrification in a homogenous closed system:

10 experiment and simulation. Soil Science 146, 335-349.

11Li, C., 2000. Modelling trace gas emissions from agricultural ecosystems. Nutrients

12 Cycling in Agro-ecosystems 58, 259-276.

13Li, C., 2003. Greenhouse gas emissions from croplands of China. Quaternary

14 Sciences 23, 493-503.

15Li, C., Frolking, S., Frolking, T.A., 1992. A model of nitrous oxide evolution from soil

16 driven by rainfall events.1. Model structure and sensitivity. Geophysical Research
17 97, 9759-9776.

18Li, C., Frolking, S., Harris, R., 1994. Modelling carbon biogeochemistry in agricultural

19 soils. Global Biogeochemical Cycles 8, 237-254.

20Li, C., Narayanan, V., Harriss, R., 1996. Model estimate of N2O emissions from

21 agricultural lands in the United States. Global Bio-geophysical Cycles

22 10, 297-306.

23Li, C., Frolking, S., Butterbach-Bahl, K., 2005. Carbon sequestration in arable soils is

24 likely to increase nitrous oxide emissions, offsetting reductions in climate
25 radiative forcing. Climate Change 72, 321-338.

1 19

1Nakicenovic, N., and Intergoervmental Panel on Climate Change. Special Report on

2 Emissions Scenarios. Pp 599 S., Cambridge University Press, Cambridge, UK,
3 2000.

4Pathak, H., Li, C., Wassmann, H., Ladha, J.K., 2006. Simulation of Nitrogen balance in

5 Rice-wheat systems of the Indoigangetic plains. Soil Science Society of America
6 Journal 70, 1612-1622.

7Roelandt, C., Van Wesemael, B., and Rounsevell, M., 2005. Estimating annual N2O

8 emissions from agricultural soils in temperate climate. Global Change Biology 11,
9 1701-1711.

10 Ruser, R., Flessa, H., Schilling, R., Steidl, H., Beese, F., 1998. Soil compaction
11 and fertilization effects on nitrous oxide and methane fluxes in potato fields. Soil
12 Science Society of America Journal 62, 1587-1595.

13Ryden, J.C., 1981. Nitrous oxide exchange between a grassland soil and atmosphere.

14 Nature (London) 292, 235-237.

15Saggar, S., Giltrap, D.L., Li, C., Tate, K.R., 2007. Modelling nitrous oxide

16 emissions from grazed grassland in New Zealand. Journal of Agriculture
17 Ecosystems and Environment 119, 205-216.

18Schmid, M., Neftel, A., Riedo, M., Fuhrer, J., 2001. Process-based modelling of nitrous

19 oxide emissions from different nitrogen sources in mown grassland. Nutrient
20 Cycling of Agro-ecosystem 60, 177-187.

21Six, J., Ogle, S., Breidt, F.J., Contant, R.T., Mosier, A.R., Paustian, K., 2004. The

22 potential to mitigate global warming with no-tillage management is only realized
23 when practised in the long term. Global Change Biology 10, 155-160.

24Smith, K.A., Clayton, H., McTaggart, I.P., 1995. The measurement of nitrous oxide

25 emissions from soil by using chambers. Philosophical Transactions of the Royal
26 Society of London, Series a 351, 327-337.

1 20

1Smith, K.A., McTaggart, I.P., Dobbie, K.E., Konen, F., 1998. Emissions of N2O from

2 Scottish agricultural soils, as a function of fertilizer N. Nutrient Cycling in Agro-
3 ecosystems 52, 123-130.

4Stange, F., Butterbach-Bahl, K., Papen, H., Zechmeister-Boltenstern, S., Li, C., Aber, J.,

5 2000. A process oriented model of N 2O and NO emissions from forest soils:
6 Sensitivity analysis and validation. Journal Geophsical Research 105, 4385-4398.

7Stenger R., Priesack E., Barkle G., Sperr C., 1999. A tool for simulating nitrogen and

8 carbon dynamics in the soil–plant –atmosphere systems. NZ land treatment
9 collective. Proceedings Technical Session 20: Modelling of land treatment
10 systems. M. Tomer, M. Robinson, G. Gielen (Eds). New Plymouth, 14-15
11 October 1999; Pp 19-28.

12Sweeney, J and Fealy, R., 2003. Establishing Reference Climate Scenarios. In: J.

13 Sweeney (Ed.), Climate Change Scenarios and Impacts for Ireland. ERTDI report
14 Series No. 15. Environmental Protection Agency, Johnstown Castle, Wexford, pp.
15 5-32.

16Tang, H., Qiu, J., Van Ranst, E., Li, C., 2006. Estimation of soil organic carbon storage in

17 cropland of China based on DNDC model. Goederma 134, 200-206.

18Tanji, K.K., 1982. Modelling of the soil nitrogen cycle. Agronomy 22, 721-772.

19Terry, R.E., III, R.L.T. & Duxbury, J.M. 1981. The effect of flooding on nitrous

20 oxide emissions from and organic soil. Soil Science, 132: 228-232.

21Willams, E.J., Hutchinson, G.L., Feshsenfeld, F.C., 1992. NOx and N2O emissions from

22 soil. Global Biogeochemical Cycles 6, 351-388.

23Yeluripati, J.B., Li, C., Frolking, S., Nayak, D.R., Adhya, D.K., 2006. Field validation of

24 DNDC model for methane and nitrous oxide emissions from rice-based
25 production systems of India. Nutrients Cycling in Agro-ecosystems 74, 157-174.

1 21

1Zheng, X.H., Wang, M.X., Wang, Y.S., Shen, R.X., Li, J., Heyer, J., Kögge, M.,
2 Papen H., Jin, J.S., Li, L.T., 1999. Characters of greenhouse gas (N2O, NO, CH4)
3 emissions from croplands of Southeast China, World Resource Review 11, 229–
4 246
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34TABLES
35
36Table 1: DNDC model input data for both the spring barley and the pasture fields
37
Climate data Spring barley field Pasture field

1 22

Latitude (degree) 52o86′ N 52o86′ N
Yearly maximum of average 13 13
o
Daily temperature ( C)
Yearly minimum of average 4.0 4.0
o
Daily temperature ( C)
Yearly accumulated precipitation 792 792
(mm).
N concentration in rainfall (mg Nl-1) 0.001* 0.001*
Atmospheric CO2 concentrations (ppm) 380* 380*
Soil properties (0-10 cm depth)
Vegetation type Barley crop Moist pasture
Soil texture Sandy loam Sandy loam
Bulk density (g cm-3) 1.4 1.0
*
Clay fraction 0.19 0.34*
Soil pH 7 7.3
Initial organic C content at surface soil 0.019 0.038
(kg Ckg-1).
Harvest Grain harvest, mulch/till Grazing/ cutting
Soil tillage Conventional and reduced None
WFPS at field capacity 0.68 0.87
WFPS at wilting point 0.12 0.09
Depth of water-retention layer (cm) 100* 100*
Slope (%) 0.0 0.0
1*Default values
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18Table 2: Observed and modelled seasonal N2O emissions from the arable conventional
19and reduced tillage plots.
20
Seasonal emissions (g N2O-N ha-1) Relative
2004 season Treatment Observation Model Difference deviation (%)

1 23

Conventional 140 kg N ha-1 788 780 -8 -1
tillage
70 kg N ha-1 269 350 +81 30
-1 5400
0 kg N ha 2 110 +108
-1 -40
Reduced tillage 140 kg N ha 978 590 -388
-1 -55
70 kg N ha 494 220 -274
-1 -66
0 kg N ha 87 30 -57
2005 season
Conventional 159 kg N ha-1 1053 993 -60 -6
tillage
79 kg N ha-1 563 450 -113 -20
-1 -35
0 kg N ha 170 110 -60
-1 -25
Reduced tillage 159 kg N ha 1058 793 -265
-1 -44
79 kg N ha 567 320 -247
-1 -93
0 kg N ha 135 10 -125
1
2
3Table 3: Observed and modelled annual N2O emissions from the cut and grazed pasture
4(2004).
5
Seasonal emissions (g N2O-N ha-1) Relative Deviation (%)
Treatment Observation Model Difference

Before adjusting SOC
200 kg N ha-1 2573 6613 4040 157
0 kg N ha-1 1054 3970 2926 360
After adjusting SOC
200 kg N ha-1 2573 2797 224 9
-1
0 kg N ha 1054 1110 56 5
6
7
8
9
10
11
12
13
14
15
16
17Table 4: Sensitivity of DNDC to changes in soil characteristics, management and climate
18for the spring barley field (conventional tillage, 2004).
19
Scenario Mineralization Annual N2O flux (kg N Denitrification
(kg N ha-1y-1) ha-1y-1) (kg N ha-1y-1)

1 24

*Baseline 257.4 1.4 4
Bulk density (g cm-1)
1 194 0.67 1.67
1.6 290.8 2.11 4.33
1.8 324.2 2.65 6.13
Initial soil organic
carbon
+20% 305.8 2.59 6.1
-20% 211.1 0.69 1.74
Fertilizer type
Urea 257.4 2.46 4.81
Ammonium sulphate 257.4 2.54 4.9
Rainfall
+20% 267.1 1.76 4.51
-20% 244.5 1.41 2.98
Air temperature
+20% 269.6 2.65 6.92
-20% 243.2 0.93 2.34
1
2*Baseline scenario: Bulk density 1.4gcm -3, SOC 0.0194 kg C kg-1, fertilizer applied and timing (140kg N/ha
3CAN, on the 27th of April), annual average max. and min. air temperature 13.7 and 4.8 oC and average
4daily precipitation 2.2cm and soil tillage to 22cm depth carried in March five weeks before planting.
5
6Table 5: DNDC future simulated annual cumulative N 2O flux values for the grassland
7and arable fields under emission scenarios A2 and B2.
8
Time Period Cumulative Flux Increase from (1961-1990)-base
line value (%)
(Kg N O-N ha-1)
2

Grassland A2 B2 A2 B2
1961-1990 14.8 14.7
2041-2070 16.6 15.8 12.2 7.8
2061-2090 18 17.4 21.6 18.7
Barley
1961-1990 4.0 3.9
2041-2070 5.3 4.0 33.7 3.61
2061-2090 6.3 5.1 58.6 31.4
9FIGURES
10
11
12

1 25

60 60
A B
50 50
d -1 )

40
-1

40
N 2O flu x (g N 2O -N h a

30 30

20 20

10 10

0 0

-10 -10

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230

30 30
C D
N 2 O f l u x ( g N 2 O - N h a -1 d -1 )

20 20

10 10

0 0

-10 -10

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230

30 30
E F
N 2 O f l u x ( g N 2 O - N h a -1 d -1 )

20 20

10 10

0 0

-10 -10

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230
st st
Time (days after the 1 of January) Time (days after the 1 of January)

1
2Figure 1: Comparison of model-simulated (○) and field measured N 2O (●) flux from the
3high (upper), medium (bottom) and low (lower) fertilized conventional tillage in 2004
4(A,C,E) and 2005 (B,D,F). Arrows show time of fertilizer application.
5
6
7

1 26

60 60
A B
50 50
N 2 O f l u x ( g N 2 O - N h a -1 d -1 )

40 40

30 30

20 20

10 10

0 0

-10 -10

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230

30 30
C D
N 2 O f l u x ( g N 2 O - N h a -1 d -1 )

20 20

10 10

0 0

-10 -10

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230

30 30
E F
N 2 O f l u x ( g N 2 O - N h a -1 d -1 )

20 20

10 10

0 0

-10 -10

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230
st st
Time (days after the 1 of January) Time (days after the 1 of January)

1
2
3Figure 2: Comparison of model-simulated (○) and field measured N 2O (●) flux from the
4high (upper), medium (bottom) and low (lower) fertilized reduced tillage in 2004 (A, C,
5E) and 2005 (B, D, F). Arrows show time of fertilizer application.
6
7
8
9
10

1 27

1000 1000
900
A 900 B
800 800
C u m u lativ e N 2O flu x

700 700
( g N 2 O - N h a -1 )

600 600
500 500
400 400
300 300
200 200
100 100
0 0
-100 -100

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230

1200 1200
C D
1000 1000
C u m u lativ e N 2O flu x

800 800
( g N 2 O - N h a -1 )

600 600

400 400

200 200

0 0

90 110 130 150 170 190 210 230 90 110 130 150 170 190 210 230
Time (days from 1st January) Time (days from 1st January)

2Figure 3: Comparisons of cumulative model-simulated (open symbol) and field measured
3(solid symbol) N2O fluxes from the high (•), medium (■) and low (▲) fertilized plots in
42004 and 2005 for conventional (A and C) and reduced (B and D) tillage system.
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

1 28

1
2 A
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19 B
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34Figure 4: Comparison between the measured (●) and modelled (○) WFPS from CN 1
35treatment in 2004 (A) and 2005 (B). Arrows indicate time of N fertilizer application
36
37
38
39
40
41
42
43
44
45
46

1 29

1
2
3 A
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18 B
19
20
21
22
23
24
25
26
27
28
29
30
31
32Figure 5: Comparison between the measured (●) and modelled cumulative N 2O from the
33fertilized (A) and control (B) pasture plots before (○) and after (∆) adjusting soil organic
34carbon.
35

36

37

38

39

1 30

1

2

3

4

5

6

7

8

9

10

11

12

13Figure 6: (A) Correlation between the model-simulated and field measured N 2O fluxes
14for the arable field. y = 0.78x -6.5 (r2 = 0.85). (B) Correlation between the model-
15simulated and field measured N2O fluxes from our arable (●), pasture (∆) and other
16literature DNDC studies (○). y = 1.1x + 0.35, (r2 = 0.76).

1 31

85
80
A
75
70
65
N2 O fluxes (gN 2 O-N ha-1 d-1 )

60
55
50
45
40
35
30
25
20
15
10
5
0
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400

1

65

60 B
55

50

45
40

35

30

25
20

15

10
5

0
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400
Julian days

2
3Figure 7: DNDC simulated N2O flux from the barley field soil at baseline climate; 1961-
41990 (●), 2055 (○) and 2075 (∆) for the emission scenarios HCM3-A2 (A) and HCM3-
5B2 (B).

1 32

320 A
300
280
260
240

220
200
180
160
140
120
100
80
60
40
20
0
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400
Julian days

1

320
300
B
280
260
240

220
200
180
160
140
120
100
80
60
40
20
0
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400

2
3Figure 8: DNDC simulated N2O flux from the cut and grazed pasture soil at baseline
4climate; 1961-1990 (●), 2055 (○) and 2075 (∆) for the emission scenarios HCM3-A2 (A)
5and HCM3-B2 (B).

1 33

Dndc model paper edited

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (20)

Similar to Dndc model paper edited

Similar to Dndc model paper edited (20)

Dndc model paper edited