TSEC-Biosys: Yield and spatial supply of bioenergy poplar and willow short

rotation coppice in the UKM.J. Aylott, G. Taylor

University of Southampton, UK

E. CasellaForest Research, UK

P. SmithUniversity of Aberdeen, UK

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Biomass role in the UK energy futures The Royal Society, London: 28th & 29th July 2009

Contents

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Introduction

Aims

Empirical Modelling– Method– Results

Process Modelling– Method– Results

General Conclusions

Introduction.

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Short rotation coppice (SRC) poplar and willow are two widely planted bioenergy crops

Both species are fast growing and found across a wide range of environments

Climate change presents challenges but also opportunities for bioenergy

Introduction

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Renewable energy production in 20072

310,000 ha oilseed rape (biodiesel)1

125,000 ha sugar beet (bioethanol)1

9,800 ha Miscanthus1

5,700 ha poplar and willow1

18.5M hectares (ha) UK

agric. land

How much bioenergy do we have?

1. (NNFCC, 2008), 2. (BERR, 2008)5

UK Renewable Energy Strategy= 15% renewable (2020)= 200,000 ha dedicated energy crops1

Renew. Transport Fuel Obligation = 2.5-5% biofuel (2014)

= 215,0002-870,0003 ha oilseed rape (biodiesel)

= 500,0003-525,0002 ha wheat (bioethanol)

Up to 5% of agric. land may

be needed

How much bioenergy do we need?

61. (Britt et al. 2002), 2. (DTI & DEFRA, 2007), 3. (NFFCC, 2009)

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Aims.

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1. Predict current spatial productivity of SRC poplar and willow using measured data from UK field trials (empirical)

2. Predict future spatial productivity of SRC poplar and willow by adapting the ForestGrowth model for a coppice system in the UK (process)

Aims

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Empirical Modelling.

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Measurements taken from national SRC field trials network

Largest field trial network in the UK (49 sites)

16 poplar and 16 willow varieties grown (6 yrs)

Extensive measurements taken at each site including plant productivity, soil profiles and daily climatic records

Empirical modelling: Method

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Plot data for each genotype was modelled using Partial Least Squares regression (Simca-P)

Existing spatial data was used to upscale model outputs

ClimateTopographySoil

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The model describes 51-75% of the variation in yield

Willow yields were higher than poplar, esp. in the 2nd rotation

Species

Genotype

Rotation

Observed Mean Yield

Predicted Mean Yield

Poplar Beaupré First 7.34 (2.33) 7.42 (1.25)

Poplar Ghoy First 6.45 (2.47) 6.50 (1.38)

Poplar Trichobel First 9.08 (2.67) 9.31 (1.37)

Willow Germany First 7.14 (2.94) 7.05 (1.83)

Willow Jorunn First 9.09 (3.01) 9.29 (2.09)

Willow Q83 First 8.03 (3.23) 8.21 (2.09)

Poplar Beaupré Second 4.87 (2.43) 4.90 (1.38)

Poplar Ghoy Second 5.77 (2.46) 5.85 (1.24)

Poplar Trichobel Second 9.59 (2.78) 9.70 (1.38)

Willow Germany Second 7.46 (4.00) 7.49 (2.46)

Willow Jorunn Second 9.15 (2.70) 9.30 (1.77)

Willow Q83 Second10.71 (3.74)

10.72 (1.38)

Empirical modelling: Results

12* standard error in brackets

(c) Willow var. Q83

Empirical modelling: Results

13(b) Willow var. Jorunn

(a) Poplar var. Trichobel

Mean poplar yield = 7.3 odt ha-1 yr-1

Mean willow yield = 8.7 odt ha-1 yr-1

Potential to supply >28 TW h-1 of electricity

Spring/summer precipitation highly correlates to yield, indicating both species were limited by water availability

Other factors (i.e. soil pH) gave localised yield disparity

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Willow var. Jorunn

Excluded areas:• Areas of Outstanding

Natural Beauty• National Park• Forest Park• Planted Ancient

Woodland Site• RSPB Reserve• Inland water, town

and road• National Trust land• Lowland

Heath/Bogs/Fens/Mire• Ancient woodland• Coastal sand dune• RAMSAR site• SSSI• Special Protected

Area• Local or National

Nature Reserve• Countryside Right of

Way• Registered Common

Land• Country Park• Listed building, World

Heritage Site or Monument

15Yield in millions of odt/yr

Greenhouse Gas Emission Modelling

Yield data used to produce greenhouse gas maps

20-year average using RothC

Replacing arable or grassland with SRC reduces GHG emissions

Gross CO2 emissions (tonnes/ha/yr)

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Process Modelling.

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Process-based models help us explore interactions between yield and climate

ForestGrowth1,2 is a yield model for mature forest species, which has been parameterised for SRC3,4,5

The model uses UKCIP climate change predictions

Process modelling: Method

1. (Evans et al., 2004), 2. (Deckmyn et al., 2004)3. (Casella & Sinoquet, 2003), 4. (Gielen et al., 2003), 5. (Casella & Aylott, unpublished) 18

Phase 2: If layer doesn’t have enough light, stems grow and new leaves are added

Phase 1: Root carbon used to grow leaves on existing stem

Phase 3: Carbon stored for the next years growth Phase 4: Leaves fall Phase 5: Dormancy

SRC-MOD: Method

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Process modelling: Current Climate

Parameterised for Populus trichocarpa (black cottonwood)

Yields predicted by the model are within ± 20% of measured yields (seven sites)

Average annual yield = 9.4 odt ha-1 yr-1

Productivity map of P. trichocarpa, second

rotation 20

Currently, SRC-MOD uses arbitrary increases in CO2, temperature and precipitation – UKCIP02 2050 medium emission scenario– One site (Alice Holt, clay loam soil)– One species (P. trichocarpa)

In future, SRC-MOD will use complete UKCIP09 weather datasets– Different emission scenarios for 2020’s, 2050’s &

2080’s– UK wide– Multiple species

Process modelling: Future Climate

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Carbon Dioxide Effect on Yield

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CO2 set to increase to 550 ppm by 2050

Leads to increase in photosynthetic activity

Ten years of CO2 experiments on poplar found:– 500-700 ppm leads to

mean increase in above ground productivity of +34 %

Source: NOAA, 2008

Atmospheric CO2 predicted to increase from 370 to 550 ppm– Increased

photosynthesis

– UK yields +29%

– Parts of S. England & N. Scotland +50%

– Calfapietra et al. (2003), found an increase of up to 27% in poplar yields

Carbon Dioxide Effect on Yield

Carbon Dioxide vs. Yield map for P. trichocarpa, second rotation 23

Temperature Effect on Yield

Futures temperatures are likely to rise – Summer temperatures

increasing faster than those in winter

Higher temperatures– Advance budburst– Increase photosynthesis– But increase

transpiration and respiration rates

Source: UKCIP02 Climate Change

Scenarios

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Temperature Effect on Yield

Temperature increase of +2.5oC (Summer) and +0.5oC (Autumn to Spring)– Yield increased by 0.5 odt/ha/yr (+4%) by end of

second rotation at Alice Holt site respiration costs also increase over time

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Precipitation Effect on Yield Future climate predictions

(Hulme et al., 2002)– Decreased summer

precipitation increased soil moisture deficit

– Increased winter precipitation higher risk of flooding

Souch & Stephens (1998) showed poplar yield decreased 60-75% in drought conditions

Water used in many leaf biochemical processes, by decreasing its availability photosynthesis will decrease

Source: UKCIP02 Climate Change

Scenarios 26

Precipitation Effect on Yield

Precipitation decreased by 10%– Yield decreased by 1.3 odt/ha/yr (-12%) by end of

second rotation at Alice Holt site increased soil moisture deficit

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Predicted Yield in 2050

CO2 x temperature x water– Yield increased by 2.1 odt/ha/yr (+19%) by end of

second rotation at the Alice Holt site28

General Conclusions.

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Empirical model– Current yields of the three extensively grown

poplar varieties was 7.3, and for willow was 8.7 odt ha-1 yr-1

– Water availability was largest limiting factor

Process model– By 2050, SRC-MOD predicts P. trichocarpa will

be 19% more productive (Alice Holt site)– Longer growing season and more photosynthesis

BUT plants respire and loose water more quickly

General Conclusions

2007: 12,000 tonnes = >0.01% of electricityo Current potential = 13

Modt (6.7% electricity)

2014: 2.5-5% fuel from biofuel

2020: 15% electricity from renewables

2050: +19% yield (med. emissions) = 8.0% electricityo Less agricultural land

neededo Breeding/technology

expand potential31

This research was funded by NERC as part of the Towards a Sustainable Energy Economy (TSEC) initiative

and through a PhD studentship to Matthew Aylott (NER/S/J/2005/13986). Thanks to Forest Research for the

provision of the site data.

Contact M Aylott for more information: mja13@soton.ac.uk

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Thank you for your attention!

TSEC BiosysTSEC Biosys

TSEC BiosysTSEC Biosys

www.tsec-biosys.ac.uk

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