TSEC-Biosys: Yield and spatial supply of bioenergy poplar and willow short rotation coppice in the UK

1
TSEC-Biosys Yield and spatial supply of
bioenergy poplar and willow short rotation
coppice in the UK

• M.J. Aylott, G. Taylor
• University of Southampton, UK
• E. Casella
• Forest Research, UK
• P. Smith
• University of Aberdeen, UK

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

• Introduction
• Aims
• Empirical Modelling
• Method
• Results
• Process Modelling
• Method
• Results
• General Conclusions

3
Introduction.
4
Introduction

• 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

5
How much bioenergy do we have?
18.5M hectares (ha) UK agric. land

• 310,000 ha oilseed rape (biodiesel)1
• 125,000 ha sugar beet (bioethanol)1

• 9,800 ha Miscanthus1
• 5,700 ha poplar and willow1

Renewable energy production in 20072
1. (NNFCC, 2008), 2. (BERR, 2008)
6
How much bioenergy do we need?
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
6
1. (Britt et al. 2002), 2. (DTI DEFRA, 2007),
3. (NFFCC, 2009)
7
Aims.
8
Aims

• Predict current spatial productivity of SRC
  poplar and willow using measured data from UK
  field trials (empirical)
• Predict future spatial productivity of SRC poplar
  and willow by adapting the ForestGrowth model for
  a coppice system in the UK (process)

9
Empirical Modelling.
10
Empirical modelling Method

• 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

11

• Plot data for each genotype was modelled using
  Partial Least Squares regression (Simca-P)
• Existing spatial data was used to upscale model
  outputs
• Climate
• Topography
• Soil

12
Empirical modelling Results
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 Second 10.71 (3.74) 10.72 (1.38)

• The model describes 51-75 of the variation in
  yield
• Willow yields were higher than poplar, esp. in
  the 2nd rotation

standard error in brackets
13
Empirical modelling Results

• Mean poplar yield 7.3 odt ha-1 yr-1
• Mean willow yield 8.7 odt ha-1 yr-1
• Potential to supply gt28 TW h-1 of electricity

(c) Willow var. Q83
(b) Willow var. Jorunn
(a) Poplar var. Trichobel
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Willow var. Jorunn

• 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

15

• 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

Yield in millions of odt/yr
16
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)
17
Process Modelling.
18
Process modelling Method

• 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

1. (Evans et al., 2004), 2. (Deckmyn et al.,
2004) 3. (Casella Sinoquet, 2003), 4. (Gielen
et al., 2003), 5. (Casella Aylott, unpublished)
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SRC-MOD Method

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

• Phase 2 If layer doesnt have enough light,
  stems grow and new leaves are added

• Phase 3 Carbon stored for the next years growth

• Phase 4 Leaves fall

• Phase 5 Dormancy

20
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
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Process modelling Future Climate

• 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 2020s, 2050s
  2080s
• UK wide
• Multiple species

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Carbon Dioxide Effect on Yield

• 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
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Carbon Dioxide Effect on Yield

• 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 vs. Yield map for P. trichocarpa,
second rotation
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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
25
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

26
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
27
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

28
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 site

29
General Conclusions.
30
General Conclusions

• 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

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• 2007 12,000 tonnes gt0.01 of electricity
• 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
  electricity
• Less agricultural land needed
• Breeding/technology expand potential

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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_at_soton.ac.uk
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Thank you for your attention!
www.tsec-biosys.ac.uk
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