Options for reducing soil nitrous oxide emissions

in the NSW dryland grains industry Graeme Schwenke (northern NSW)

Guangdi Li (southern NSW) De Li Liu (simulation modelling)

NSW Department of Primary Industries

Acknowledgments Tamworth Agricultural Institute, Wagga Wagga Agricultural Institute,

Liverpool Plains Field Station, Ian Carter Bruce Haigh, Annabelle McPherson, Bill Keene, Peter Sanson, Tara

Burns, Mandy Holland, Wayne McPherson, Kamal Hossain, Helen Squires, Nicole Carrigan, Pete Formann, Jan Hosking, Steve Morphett, Jim Perfrement, Pete Perfrement, Pat Mortell, Matt Gardner, Rick Graham, Steve Kimber, Brad Keen, and Leanne Lisle (UNE).

Adam Lowrie, Richard Lowrie, Graeme Poile, Albert Oates, Binbin Xu, Vince van der Rijt, Sarah Bond and Kare Maihemuti.

John Finlayson, Muhuddin Anwar, Yuchuan Ma, Bin Wang and Changsheng Li, Yong Li, Jianmin Lin.

Peter Grace, Clemens Scheer, Dave Rowlings, Christian Brunk

Project Objectives Compare options that reduce N2O emissions and increase N

use efficiency from northern and southern NSW dryland grains cropping – Options included:

• optimise N rate applied, • split application of fertiliser N, • use of N fertiliser containing inhibitors, • substitution of fertiliser N with legume-derived N

Validation of process-based biogeochemistry models for N2O

emitted from dryland grain cropping trials.

Simulate net greenhouse gas emissions under different agronomic practices using current and projected future climate scenarios

0 kg N/ha 40 kg N/ha

120 kg N/ha 200 kg N/ha

Northern NSW Year 1 – N rate response N2O rate response?

Date

10/12 11/12 12/12 1/13 2/13 3/13 4/13 5/13 6/13 7/13 8/13 9/13 10/13

Cum

ulat

ive

N2O

em

issi

ons

(g N

2O-N

/ha)

0

1000

Date

10/12 11/12 12/12 1/13 2/13 3/13 4/13 5/13 6/13 7/13 8/13 9/13 10/13

Dai

ly ra

infa

ll (m

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oil w

ater

(%)

Ave

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tem

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(o C)

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0 kg N/ha

40 kg N/ha120 kg N/ha200 kg N/ha

Northern NSW Year 2 – How to delay soil nitrate availability: nitrification inhibitor or late-apply N?

10/13 11/13 12/13 1/14 2/14 3/14 4/14 5/14 6/14 7/14 8/14 9/14 10/14

Cum

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N2O

em

issi

ons

(g N

2O-N

/ha)

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Date

10/13 11/13 12/13 1/14 2/14 3/14 4/14 5/14 6/14 7/14 8/14 9/14 10/14

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N (sowing)

N (booting) harvest

0 kg N/ha

Urea 100 kg N/ha (sowing)Entec 100 kg N/ha (sowing)Urea 100 kg N/ha (booting)

0

500

1000

1500

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2500G

ross

mar

gin

($/h

a)

Tamworth (main site: auto chambers) – Optimise the N fertiliser rate for soil N and expected yield

• Soil N levels determined by previous sorghum (low N) or soybean brown manure (high N)

• +N vs nil N treatments – Split N treatment (33% sowing + 67% booting)

Northern NSW Year 3 – Optimise N and delay nitrate availability.

Year 3 ~ Road-testing options

Cumulative N2O emissions

10/14 11/14 12/14 1/15 2/15 3/15 4/15 5/15 6/15 7/15 8/15 9/15 10/15 C

umul

ativ

e N

2O e

mis

sion

s (g

N2O

-N/h

a)0

100

200

300

400

500

600

Date

10/14 11/14 12/14 1/15 2/15 3/15 4/15 5/15 6/15 7/15 8/15 9/15 10/15

Dai

ly ra

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ll (m

m)

Aver

age

tem

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ture

(o C)

Volu

met

ric s

oil w

ater

(%)

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10

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40

50

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sowing(+N)

harvest (sorg) + 120 kg N/ha

(soy) + 0 kg N/ha

(sorg) + 0 kg N/ha

(soy) + 40 kg N/ha

Growing season rainfall = 422 mm

(longterm = 356 mm)

Grain yields

Breeza (satellite site: manual chambers) – Delay conversion of urea -> nitrate in the soil

• DMPP-coated urea (nitrification inhibitor) [EntecTM] • Polymer coated urea (physical isolation of granule)

– Split N fertiliser (33% sowing + 67% booting)

Northern NSW Year 3 – Optimise N and delay nitrate availability.

Year 3 ~ Road-testing options

Cumulative N2O emissions

10/14 11/14 12/14 1/15 2/15 3/15 4/15 5/15 6/15 7/15 8/15 9/15 10/15

Cum

ulat

ive

N2O

em

issi

ons

(g N

2O-N

/ha)

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

Date

10/14 11/14 12/14 1/15 2/15 3/15 4/15 5/15 6/15 7/15 8/15 9/15 10/15

Dai

ly ra

infa

ll (m

m)

Aver

age

tem

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ture

(o C)

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(%)

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N (sowing)

N (booting)harvest

0 kg N/ha urea at sowing100% urea at sowing100% entec urea at sowing100% poly urea at sowing

33% urea / 67% entec at sowing33% urea / 67% poly at sowing33% urea / 33% entec / 33% poly at sowing

33% urea at sowing, 67% urea at booting33% entec at sowing, 67% urea at booting33% poly at sowing, 67% urea at booting

33% urea at sowing, 67% NV urea at booting33% entec at sowing, 67% NV urea at booting33% poly at sowing, 67% NV urea at booting

Growing season rainfall = 253 mm

(longterm = 321 mm)

0.00

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1 2 3 4 5 6 7 8 9 10 11 12 13

Gra

in y

ield

(t/

ha)

Treatment number

a

dcd

dbcd

bcd cd

ab

d d cd d

100% urea at sowing

1:3 poly’:urea at sowing

Nil N

100% poly’ urea at sowing

Grain yields

0.000

0.100

0.200

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Emis

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n f

act

or

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a a a a

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a aa

abab

Reduction in growing-season N2O emissions compared to urea applied at sowing

Year Chambers EntecTM applied at sowing

Urea applied at booting

2010-11 manual 100% -

2013-14 manual 91-97% 80%

auto 65-81% 81%

2014-15 manual 81% 58-65%

N2O mitigation strategies ~ dryland sorghum

Optimise the amount of fertiliser N applied for expected yield

Delay soil nitrate availability ~ delay N fertiliser application • post-sowing or split (sowing + booting) • N applied up to the 7 leaf stage can benefit yield

Delay soil nitrate availability ~ delay conversion of urea to

nitrate in the soil • DMPP-coated urea (nitrification inhibitor) [EntecTM]

reduces N2O, but also gross margin (no yield benefit) • Polymer coated urea (physical isolation of granule)

may reduce or increase N2O, and also costs more.

Guangdi Li Wagga Wagga Agricultural Institute

Southern NSW ~ Rotation trial conclusions

Treatments 4-year crop sequence Wheat-Canola-Legumes-Wheat Tillage

– Till vs No-till Nitrogen rate

– 0, 25, 50 and 100 kg N/ha Nitrogen type

– Urea, Green Urea, ENTEC

N2O emission and emission factors

Wheat in 2012Treatment N rate Significance

(kg N/ha) No-till Till No-till Till Urea 0 81 130 Tillage, NS

100 179 294 N rate, P< 0.01 0.10 0.16 Entec® 100 105 218 N type, P <0.05 0.02 0.09 Green Urea™ 100 172 343 0.09 0.21Canola in 2013

N rate No-till Till Significance No-till Till Entec® 0 250 332

25 305 354 Tillage, NS 0.05 0.0250 319 305 N rate, NS 0.07 -0.03100 300 306 0.05 -0.03

Canola in 2013N rate No-till Till Significance

Urea 0 154 196 Tillage, NS No-till Till100 186 263 N rate, P =0.058 0.03 0.07

Emission factor (%)

Manual chambers (219 days from 7/8/2012 to 14/3/2013)N2O-N emission (g/ha) Emission factor (%)

Manual chambers (334 days from 23/5/2013 to 22/4/2014)

Auto-chambers (366 days from 23/5/2013 to 22/4/2014)

Emission under legumes

Legumes in 2014 Treatment No-till Till Significance

191 246 Tillage, P =0.058 Pasture (Brown manured) 178 260 Crop type, NS

185 253Legumes in 2014 Crop type No-till Till Significance Emission reduction Lupin (Grain harvested) 255 335 Pea (Grain harvested) 280 353 Tillage, P =0.09 Vetch (Hay cut) 262 334 Crop type, NS Pasture (Hay cut) 321 394 Mean 280 354Pasture in 2013-2015Treatment Lucerne mono-culture (L) Subclover mono-culture (S) -19.3% (L vs S) Phalaris-lucerne mix (PL) Phalaris-subclover mix (PS) -7.6% (PL vs PS) Significance

Pea (Brown manured)

P =0.057

Auto-chambers (386 days from 22/4/14 to 13/5/15)Emission reduction

N2O-N emission (g/ha)Manual chambers 658 days from 14/5/2013 to 3/3/15)

Emission reduction

Manual chambers (279 days from 28/5/14 to 3/3/15)

23.9%20.6%21.5%18.4%21.0%

22.3%31.5%

517417438405

-15.2% (L vs PL)-3.0% (S vs PS)

N2O mitigation strategies ~ southern NSW

No-till practice can potentially reduce N2O emissions

Including perennial grasses in a pasture mix can capture more nitrate, hence reducing the risk of N2O emission during off-season rainfall events

DMPP coated N fertiliser (Entec) can reduce N2O emission, but its high price prevents adoption

Simulations of current and future N2O emissions

and

WNMM Model development

De Li Liu Wagga Wagga Agricultural Institute

MODELLING Model comparison: APSIM, DNDC & WNMM &

Model selection: WNMM & DNDC

Model improvement/development

Simulation of Tamworth previous rotation experimental data

Simulation of Tamworth and Wagga experiments conducted in the project

Simulation N2O under future climate scenarios

Model Improvement

Model comparison: APSIM, DNDC & WNMM Model selection: WNMM & DNDC

Canola+N_wheat+N_barley+N Chickpea -wheat-barley

Model Improvement

Improve WNMM: WNMM NSWDPI version – user friendly interface – graphical user interface (GUI) – Integrating all necessary inputs into

one file, ie. • Site & soil file • management file • model initial file • Model parameters/rates etc

WNMM: – Good performance – Input files ~ 100-200 – Calibration in the model codes by Yong Li

only, no report on actual values used – “Single-user-model”

The first WNMM simulation by a model user - a visiting scientist from Chinese Academy of Science

Anyone (non-modeller) can use this “WNMM NSW DPI version”

Simulation of Wagga experiment (WNMM GUI output)

Simulation of N2O emissions under future climate scenarios

IPCC AR5 CSIRO 3.6 – RCP2.6, RCP4.5, RCP 6.0 & RCP 8.5

Under four rotation system (Tamworth) – CaWB, CpWB, CpWCp & CpS (Ca = canola, W = wheat, B = barley, Cp = chickpea, S = sorghum)

1950–2098 by WNMM & DNDC

Impact of climate change on N2O emission

• RCP2.6 & 4.5 N2O emissions: less than current

• RCP6.0 & 8.5 N2O emissions vary, depending on rotation

• RCP6.0 & 8.5 CaWB, N2O emission will increase by 6–19% • Replace canola with chickpea (CpWB), increases N2O by only 4–15% • Replace barley with chickpea (CpWCp), increase N2O by only 3%

• Rotations including a legume can reduce N2O emissions under

future changing climate.

N2O mitigation strategies ~ modelling Under both current and future climate

• Less fertilizer-dependent cropping

• More legume cropping phase, less N2O emissions

• WNMM model can predict emissions of various scenarios