Estimation of N2O emission factors for soils depending on environmental conditions and crop managementJ.P. LesschenG.L. VelthofJ. KrosW. de Vries

Outline

Introduction Conceptual framework Factors controlling N2O emissions Results Validation based on Stehfest and Bouwman data set Conclusions

Introduction

N2O contributes 7.9% to the global GHG emissions Agriculture is the main source of N2O and soil

emissions account for most of the emissions Soil N2O emissions often estimated with default

IPCC emission factor of 1% of applied N Large variation exists depending on environmental

and management factors

Introduction

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N2O

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Variability N2O emission factors Stehfest and Bouwman data set

Objective

To develop a simple N2O emission factor inference scheme, based on environmental and management factors

Validate the approach with the Stehfest and Bouwman data set

Conceptual framework

Emission factor approach differentiated to manure type, soil type, land use, climate, etc.

Define reference situation with emission factor of 1% Define changes in emission factor caused by factors

Factor Denitrification N2O/N2 ratioIncreasing nitrate content + +Increasing oxygen content - +Increasing available organic carbon + -Increasing temperature + - Decreasing pH - +

Reference situation

Starting point is EF for fertilizer of 1% of applied N Two-year monitoring study in Netherlands (Velthof et

al., 1996) with the following conditions: Grassland Well-drained sandy soil Fertilized with calcium ammonium nitrate fertilizer Neutral pH (> 5) Average precipitation (600-900 mm/ year)

Nitrogen input

Sources of nitrogen: Mineral fertilizer: NO3 fertilizer, NH4 fertilizer and urea Manure:

cattle, pig and poultry Manure type: solid or slurry Application technique: surface or injection

Grazing Biological N fixation Crop residues: cereals, vegetables and other crops Atmospheric N deposition Net mineralization of soil organic N

Example: effect of fertilizer type

(Pathak and Nedwell, 2001)

grassland

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Urea Ammonium sulphate Potassium nitrate Ammonium nitrate

Field capacitySubmerged

N2O emission factor, % of N applied

Example: manure and application type

(Velthof and Mosquera, 2010)

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Cattle manureshallowinjection

Cattle manurebroadcast

Pig manureinjection

Pig manurebroadcast

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Grassland

Maize land

Example: crop residues - nitrate

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Wheat Maize Barley Cabbage Sprouts Mustard Broccoli Sugarbeet

N2O-emission, % of crop residue N

(Velthof et al., NCA 2002)

Calculation rules EF factors for N input

Mineral fertilizer Grassland: NO3 : NH4 : urea = 2 : 1 : 1 Arable land: NO3 : NH4 : urea = 1.25 : 1 : 1

Manure poultry manure : solid cattle manure : solid pig manure : cattle slurry :

pig slurry = 1 : 1 : 1 : 2 : 3 EF for injected or incorporated manure is 1.5 times EF of surface-

applied manure Grazing: EF is 2 times EF of NO3 fertilizer Crop residues: cereals : vegetables : other crops = 0.2% : 2%

: 1% (for reference situation)

Oxygen content

Indirect parameters for the effects of oxygen content: Soil type: texture, organic matter and groundwater

level Precipitation: precipitation increases risk on

anaerobic conditions Land use: in grasslands more organic C and higher

oxygen consumption Manure application technique: the depth of

application affects oxygen content

Example: effect of soil type

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sand clay

no fertilizer

NH4NO3

cattle slurry

N2O emission, kg N per ha

(Van Groenigen et al., Plant & Soil. 2004)

Maize

Precipitation

Precipitation is an indicator for the risk of anaerobic conditions in soils

Several studies find significant relations between precipitation and N2O EF

Linear regression based on Stehfest and Bouwman data set (aggregated to location, n=45)

500 : 750 : 1000 mm = 0.37 : 1 : 1.63

y = 3E-05x - 0.012R2 = 0.16

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Precipitation (mm)

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Available organic Carbon content

Indirect parameters for the effects of available carbon content:

Soil type: peat soils much higher than clay and sand Sand : Clay : Peat = 1 : 1.5 : 2

Land use: grassland higher EF than arable land for mineral fertilizer but lower for manure

Three manure types Three crop residue types

Temperature

Temperature affects activity of nitrifying and denitrifying bacteria and the ratio N2O/ N2

Lower EF with lower temperature

No significant relation found based on Stehfest and Bouwman data set

Temperature influence is mainly seasonal related

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pH

pH affects the activity of nitrifying and denitrifying bacteria with optimum activities at pH 7-8

Calculation rule: in acid soils (pH < 5) N2O emission factor is 25% lower than in other soils

n = 22

n = 330

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Emission factor inference schemeSoil type Land use pH Emission factor in % of the N input

nitrate containing fertilizer

ammonium fertilizer

urea pig slurry low NH3

application

cattle slurry low NH3

application

poultry manure; low NH3

application

Sand grassland < 5 0.75 0.38 0.38 0.56 0.38 0.19> 5 1.00 0.50 0.50 0.75 0.50 0.25

Sand arable land < 5 0.38 0.30 0.30 0.84 0.56 0.28> 5 0.50 0.40 0.40 1.13 0.75 0.38

Clay grassland < 5 1.13 0.56 0.56 0.84 0.56 0.28> 5 1.50 0.75 0.75 1.13 0.75 0.38

Clay arable land < 5 0.56 0.45 0.45 1.27 0.84 0.42> 5 0.75 0.60 0.60 1.69 1.13 0.56

Peat grassland < 5 1.50 0.75 0.75 1.13 0.75 0.38> 5 2.00 1.00 1.00 1.50 1.00 0.50

Peat arable land < 5 0.75 0.60 0.60 1.69 1.13 0.56> 5 1.00 0.80 0.80 2.25 1.50 0.75

Results N2O soil emissions for EuropeINTEGRATOR: 292 kton N2O-N IPCC 1% EF: 315 kton N2O-N

Validation of the approach

Stehfest and Bouwman (2006) data set Selection agriculture in temperate zones (n = 1137) 352 cases with corrected N2O EF

Reclassification of dataset according to the factors in the inference framework

Addition of annual precipitation for missing cases in Europe Calculation of N2O emission factor for each case Comparison observed EF with:

Simulated EF (n = 225) IPCC 1% EF Empirical relation of Stehfest and Bouwman (2006):

log N2Oemission = sum Ei + A (n = 133)

Validation of N2O emission factors

Approach Average difference

RMSE Pearson correlation

n = 225 Simulation 0.88 1.59 0.440 **

IPCC 1% 1.06 1.75 -

n = 133 Simulation 0.76 1.46 0.243 **

IPCC 1% 0.87 1.49 -

Stehfest and Bouwman

0.91 1.59 0.093

Validation of N2O emission factors

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N2O emission factor (%)

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EF simulated

EF Stehfest and Bouwman (2006)

Conclusions

The presented approach takes account of environmental and management factors

The proposed approach performs better than the IPCC EF and the Stehfest and Bouwman relation

Benefits: Mitigation measures can be better accounted for Regional variation is better expressed The EF inference scheme offers possibility to use a Tier2

approach for reporting N2O emissions

Thank You!

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