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Soil organic carbon changes in the cultivation of energy crops:Implications for GHG balances and soil quality for use in LCA

Miguel Brandao a,b,*, Llorenc Mila i Canals a,c, Roland Clift a

a Centre for Environmental Strategy, University of Surrey, GU2 7XH, UKb Institute for Environment and Sustainability, Joint Research Centre, European Commission T.P. 270,

Via Enrico Fermi, 2749, I-21027 Ispra (VA), Italyc SEAC, Unilever, Colworth Park, Sharnbrook, Bedford, MK44 1LQ , UK

a r t i c l e i n f o

Article history:

Received 19 September 2007

Received in revised form

2 January 2009

Accepted 4 December 2009

Available online xxx

Keywords:

Energy crops

Oilseed rape

Miscanthus

Willow short-rotation coppice (SRC)

Forest residues

Life cycle assessment (LCA)

Land use

Soil quality

Carbon sequestration

Soil organic carbon (SOC)

* Corresponding author. Institute for EnvironFermi, 2749, I-21027 Ispra (VA), Italy. Tel.: þ

E-mail address: miguel.brandao@jrc.ec.eu1 Expressed in CO2 equivalents, excluding

ments. Had LULUFC been considered, the U

Please cite this article in press as: Brandafor GHG balances and soil quality for use

0961-9534/$ – see front matter ª 2009 Elsevidoi:10.1016/j.biombioe.2009.10.019

a b s t r a c t

The environmental impact of different land-use systems for energy, up to the farm or

forest ‘‘gate’’, has been quantified with Life Cycle Assessment (LCA). Four representative

crops are considered: OilSeed Rape (OSR), Miscanthus, Short-Rotation Coppice (SRC) willow

and forest residues. The focus of the LCA is on changes in Soil Organic Carbon (SOC) but

energy use, emissions of GreenHouse Gases (GHGs), acidification and eutrophication are

also considered. In addition to providing an indicator of soil quality, changes in SOC are

shown to have a dominant effect on total GHG emissions. Miscanthus is the best land-use

option for GHG emissions and soil quality as it sequesters C at a higher rate than the other

crops, but this has to be weighed against other environmental impacts where Miscanthus

performs worse, such as acidification and eutrophication. OSR shows the worst perfor-

mance across all categories. Because forest residues are treated as a by-product, their

environmental impacts are small in all categories. The analysis highlights the need for

detailed site-specific modelling of SOC changes, and for consequential LCAs of the whole

fuel cycle including transport and use.

ª 2009 Elsevier Ltd. All rights reserved.

1. Introduction agricultural sector – estimated at 6.9% [2] – to total national

UK greenhouse gas (GHG) emissions in 2005 were estimated at

15.7% below 1990 levels1 [1] primarily because of the shift from

coal to gas for power generation. Under the Kyoto Protocol, the

UK government agreed to reduce GHG emissions by 12.5%

below 1990 levels on average over the commitment period

2008–2012. Despite the relatively low contribution of the

ment and Sustainability,39 332 785 969; fax: þ39 3ropa.eu (M. Brandao).emissions from Land Us

K emissions would have

o M, et al., Soil organic cain LCA, Biomass and Bi

er Ltd. All rights reserved

emissions, it is the largest emitter of two of the most powerful

GHGs: methane (CH4) and nitrous oxide (N2O), which are 25

and 298 times, respectively, more potent contributors to global

warming than carbon dioxide (CO2) (100-year GWP [3]). In

addition, since agriculture occupies 77% of total UK land area

[2], the potential of agriculture to mitigate GHG emission by

acting as a C sink through its sequestration in soil and by

Joint Research Centre, European Commission, T.P. 270, Via Enrico32 786645.

e, Land-Use Changes and Forestry (LULUCF) and aircraft move-been lower in 2005, but higher in 1990.

rbon changes in the cultivation of energy crops: Implicationsoenergy (2010), doi:10.1016/j.biombioe.2009.10.019

.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 42

ARTICLE IN PRESS

producing energy crops to displace fossil fuels is promising

[4,5].

As part of the strategy to reduce GHG emissions, govern-

ment policy in the UK and elsewhere is promoting the

production and use of biomass energy (liquid biofuels for

transport and energy crops for heat and/or power). This policy

also contributes to other political and social objectives, such

as reduced reliance on fuel imports (energy security) and

increased income to farmers and rural communities [6–8]. The

UK Biomass Strategy published in 2007 sets out a clear hier-

archy for biomass which shows that the preferred uses are for

heat and combined heat and power (CHP) [5].

Debate over the advantages or otherwise of producing

biofuels or bioenergy is intense in both peer-reviewed journals

and the general media [9–17]. Biofuels and bioenergy can only

supply a small fraction of current energy demand due to the

fact that land is a finite resource. The competition for land

with food crops highlights that net energy yield per hectare is

a major concern between alternative energy crops [18–20].

Rising food prices have been attributed in part to demand for

biofuels [e.g. Ref. [19]. The potential GHG emission savings

from bioenergy and biofuels are not clear and vary widely

according to:

� the crop/feedstock chosen and how it is used (power, heat,

CHP, or ethanol and biodiesel for transport),

� the reference system for land use [21] and non-renewable

fuels, and

� the amount of agrochemical use [22].

Righelato and Spracklen [16] suggest that ‘‘the carbon

sequestered by restoring forests is greater than the emissions

avoided by the use of the liquid biofuels’’ due to the C

sequestered in the soil and in above-ground biomass, and

therefore argue for reforestation and forest maintenance. The

high variability in the impacts of bioenergy has led the WWF

to develop their own standards [23].

Despite recognition that global emissions due to land-use

changes since the Industrial Revolution have contributed to

Global Warming at the same order of magnitude as the

combustion of fossil fuels [24,25], degradation of soil carbon

has not been properly and consistently addressed in the

environmental assessment of agriculture and forestry

systems. Some studies have attempted to quantify the rates of

C sequestration/emissions associated with land use and land-

use changes, mainly using models simulating organic matter

turnover as part of the renewable carbon cycle [26]. In addition,

SOC loss is a major cause of soil quality degradation [27–30],

which is a major concern due to the scarcity of fertile land

[18,31]. Land use is recognised as the main driver of soil

degradation, although impacts on soil quality can also be

beneficial depending on land management practices. In fact, in

contrast to annual crops, perennial cropping systems tend to

accumulate SOC and some energy crops, such as Short-Rota-

tion Coppice (SRC) willow, can also serve for remediation of

contaminated soil [32,33]. It is therefore of paramount impor-

tance to include SOC changes [26] and soil quality effects when

comparing the environmental impacts of different bioenergy

land uses. As recognised by Larson [21], many LCA studies

ignore the changes in SOC associated with growing biomass;

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and B

e.g. of the 24 LCA studies published in Biomass & Bioenergy [34–

57], only six consider SOC [34,36,43,44,48,50]. Furthermore,

there is no common methodology in these studies and others

[58–60]. Clearly a systematic and harmonised method for

considering SOC changes in LCA is needed.

In addition to soil organic carbon (SOC) [31,61–64]; erosion

[64], microbial biomass, salinisation [65], and ecosystem ther-

modynamics/exergy [66] have been suggested as possible

indicators for land-use impacts in LCA. However, SOC,

expressed as kg C$year present or absent in soil due to the land

use studied, is selected as a promising stand-alone indicator

because of its close association with most soil functions; oper-

ational methods to include it in LCA have already been sug-

gested [31] and it is of obvious importance for carbon inventory

calculations. Indeed, the SOC indicator provides directly rele-

vant information for the assessment of a system’s net contri-

bution to GWP through the effect on the soil carbon pool.

Besides, the effects on SOC from the same land use in different

regions in the world are potentially very variable; thus, current

development of life cycle inventory techniques to identify the

indirect land-use changes from bioenergy production will be

highly relevant for the application of this indicator [67].

The purpose of this paper is to compare different land uses

for energy and to assess the importance of SOC changes for

the GHG balance and for the soil quality impacts of energy

crops. Four types of land use relevant to bioenergy production

in the UK have been assessed here: an arable crop, two

different ligno-cellulosic energy crops and forest. OilSeed

Rape (OSR) (Brassica napus) is chosen because of its popularity

in Europe as a non-cereal arable crop using some 43% of arable

land in the UK [2]. The ligno-cellulosic crops considered are

willow (Salix spp.) under a short-rotation coppice (SRC)

regime, and elephant grass (Miscanthus x giganteus), as these

are the most relevant for UK conditions. Their current

proportion of agricultural land use is insignificant (<0.01%) but

would grow substantially if recommendations by the Royal

Commission on Environmental Pollution [68] are followed and

the market for energy crops develops. Forest is a major land

use (11.7% of UK total). The popular forestry crop Sitka Spruce

(Picea sitchensis) and its residues are modelled.

Section 2 briefly explains the methodology followed in the

study and describes the systems under analysis, as well as the

assumptions made, goals and boundaries, data sources, etc.

The main environmental impacts are reported in Section 3,

along with the sensitivity analyses, and discussed in Section 4.

Finally Section 5 highlights the main conclusions derived from

this study.

2. Application of life cycle assessment toland use for energy

LCA is a systems analysis tool that provides information on

the full environmental effects of a product, service or system

from its cradle (extraction of raw materials) to its grave (waste

management). It gathers information on all the inputs and

outputs to and from a product system, and assesses the

potential environmental impacts associated with these inputs

and outputs. Further information on this method can be found

in Refs. [69–72]. This LCA study forms part of a larger

rbon changes in the cultivation of energy crops: Implicationsioenergy (2010), doi:10.1016/j.biombioe.2009.10.019

Propagation material

CUTTING, SWATHING and BALING

OR

CULTIVATION

OR

DRYING

STORAGE

TRANSPORT

Bioenergy Feedstocks

Machinery/spares

Agrochemicals

Diesel fuelMotor spirit

Lubricating oil

Fue loil

Electricity

SteelSoftwood

Preservative

Diesel fuel

Fig. 1 – Flow Chart for the Production of Bioenergy

Feedstocks.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 4 3

ARTICLE IN PRESS

comparison of the environmental impacts associated with

different systems for energy production and use from land in

the UK. The exposition follows the steps in LCA identified in

the relevant international standard [73].

2.1. Goal and scope of the LCA

The focus of this study is the cultivation of crops for energy.

The scope covers the ‘cradle-to-gate’ stage of the life cycle,

from extraction of raw materials through agricultural

Table 1 – Summary of the main inputs in each land use per ref

Life cycle stage O

Seeds (kg) Propagation 5

Cuttings/sets Propagation

Rhizomes (kg) Propagation

N fertiliser (kg N) Fertilisation 19

P fertiliser (kg P2O5) Fertilisation 50

K fertiliser (kg K2O) Fertilisation 48

Lime (kg CaO) Fertilisation 19

Manganese (l MnSO4) Fertilisation

Pesticidesa (kg) Pest control 2.

Softwood (kg) Weed control

Steel (kg) Weed control

Preservative (kg) Weed control

Diesel fuel (GJ) Mechanisation, transport, storage 2.

Motor spirit (GJ) Mechanisation

Fuel oil (GJ) Drying 1

Lubricating oil (MJ) Mechanisation

Electricity (kWh) Storage 33

Machinery/spares (MJ) Mechanisation

a Includes herbicides and fungicides.

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and Bi

activities and production to the point where the crop is har-

vested and ready for transport. The specific objectives are to:

1. Determine which life cycle stages of representative

biomass feedstocks contribute the greatest environmental

impacts, including land-use related soil emissions;

2. Compare different land uses in the UK for the production of

biomass/biofuels.

This paper reports on an LCA study of four specific land

uses in the UK. It is intended to be representative of average

UK practices, and care should be taken not to draw conclu-

sions from this study for comparison between different

regions within or outside the UK.

The reference unit, i.e. the reference measure for which the

environmental burdens are expressed, is taken as 1 ha of land

for one year (1 ha� yr). To show the significance of the results

for LCA of energy systems, they are converted into indicative

values for the whole fuel cycle, expressed in terms of energy-

based units (1 GJ of energy in this case), using representative

values of net energy yield and avoided energy use. However, any

detailed study will require specific figures for these parameters.

UK-specific data have been used. Input data were collected

from various studies [74–76]. Data for production of ancillary

materials and machinery has been obtained from existing

databases, as described in the relevant sections. The main

LCA database used is ecoinvent 2000 version 1.2 (http://www.

ecoinvent.ch) [77–80] which is sufficiently comprehensive to

cover the operations in the bioenergy supply chain.

2.2. Systems description

2.2.1. Land use I: oilseed rapeOilSeed Rape (OSR) is an annual arable crop, farmed primarily

for its vegetable oils, used in human food. However, OSR is

becoming increasingly popular for energy purposes: refined

rapeseed oil and biodiesel from OSR can both be used as fuels.

erence unit (haL1 yrL1) throughout, after Elsayed et al. [74].

SR Miscanthus Willow SRC Forest residues

6250/313

53

6.0 5.3

.0 4.8

.0 5.1

158

4

80 0.51 2.25

8.6

12.3

2.8

39 2.48 1.14 0.40

0.59

1 0

158 107

rbon changes in the cultivation of energy crops: Implicationsoenergy (2010), doi:10.1016/j.biombioe.2009.10.019

Table 2 – Emissions of ammonia (NH3-N as % loss of Ncontent) from mineral fertilisers (adapted from [101] in[100]).

Inputs (mineral fertilisers) Ammonia (NH3-N) emissionsto air (% loss of N content)

Ammonia, direct application 1.0

Ammonium nitrate 2.0

Ammonium phosphate 4.0

Ammonium sulphate 8.0

Calcium ammonium nitrate 2.0

Compound N 4.0

Nitrogen solutions 2.5

NK N 2.0

NPK Na 4.0

Other NP N 3.0

Other straight nitrogen 2.5

Total straight nitrogenb 4.0

Urea 15.0

a Assumed to be half nitrate, half ammonium.

b This should only be used if no information is available on

fertiliser consumption of the individual categories.

Table 3 – Emissions of nitrous oxide (N2O-N as % loss of Ncontent) from mineral fertilisers (adapted from [101] in[100]).

Inputs (mineral fertilisers) Nitrous oxide (N2O-N)emissions to air

(% loss of N content)

Ammonium (soil temperatures 0–10 �C) 0.40

Ammonium (soil temperatures 10–20 �C) 0.50

Nitrate (soil temperatures 0–10 �C) 1.70

Nitrate (soil temperatures 10–20 �C) 1.10

NPK Na (soil temperatures 0–10 �C) 1.05

NPK Na (soil temperatures 10–20 �C) 0.80

Urea (soil temperatures 0–10 �C) 0.80

Urea (soil temperatures 10–20 �C) 3.00

a Assumed to be half nitrate, half ammonium.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 44

ARTICLE IN PRESS

Rape straw is assumed here to be ploughed back into the land.

In a different scenario where straw would have been exported

from the system, the soil carbon emissions would be around

0.40 t C ha�1 yr�1 [81]; incorporating the straw reduces the loss

by typically 0.16 t C ha�1 [81] so that the total SOC loss is around

0.24 t C ha�1. If the straw were removed as a co-product, then

allocation of the total environmental burdens between the

rapeseed and the rape straw would be needed. The subsequent

stages of solvent extraction, refining and esterification, in

which dried rapeseed is processed into crude rapeseed oil and

rape meal; and the oil is further processed into refined rape-

seed oil which is then converted into biodiesel and crude

glycerine, are not part of the scope and, thus, not considered.

2.2.2. Land use II: MiscanthusMiscanthus (M. x giganteus), also known as elephant grass, is a C4

perennial energy and fibre crop. Alternative uses include

animal bedding, paper making, biopolymer manufacture, and

biodegradable products production (e.g. flowerpots). Miscanthus

is indigenous to Africa and Asia but is now grown commercially

in the UK [68,76,82–84]. There are, currently, around

12,600 ha of Miscanthus cultivation in England and Wales [85].

Miscanthus is propagated vegetatively from rhizomes or by

micro-propagation, from commercially available materials

which can be planted using existing machinery for more

common crops. Weed control and fertiliser inputs are essen-

tial at establishment but not subsequently. Miscanthus is

harvested annually in winter by cutting and baling into 5–

600 kg Heston bales, which are stored outside prior to being

transported to the end user.

Miscanthus typically has a useful cropping cycle of 20 years,

although it takes one year for establishment [86]; this study

assumes one year for establishment followed by 19 years of

production. The yield of a mature crop can be up to 20 oven-

dried tonnes (odt2) per hectare and year (odt ha�1 yr�1) [87,88].

Miscanthus takes three years to mature, during which period

2 At 0% moisture content, for practical purposes.

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and B

the yield is lower. Data on yield, inputs, outputs, and C

sequestration were obtained from the literature [74,89–92]. An

effective annual yield of 19.2 t ha�1 yr�1 (25% moisture content

– 14.4 odt ha�1 yr�1) after 20% losses during harvest and

storage is assumed3 [74]. However, improved cultivation

practices and cultivars have been shown to give higher yield

or, alternatively, to enable poorer land to be used [86,93].

Miscanthus is a simple product so no allocation of envi-

ronmental impacts is necessary.

2.2.3. Land use III: willow SRCWillow SRC is a fast-growing perennial woody crop that, when

harvested, chipped and dried, can be used as a fuel for heat

and power generation [84]. There are, currently, around

2600 ha of Willow SRC in England and Wales [85].

Like Miscanthus, willow is propagated vegetatively using

commercially available cuttings; pest and weed control are

essential in the first two years. SRC takes usually one year to

get established, followed by a productive period of 15–30 years.

The crop is harvested every three years. There are different

harvesting techniques: combined harvesting and baling, and

stick harvesting and baling. The harvested crop is commonly

stored on-farm as billets. It can then be chipped or processed

into granules [94].

The average yield of a mature crop of current cultivars is

typically 9.5 odt ha�1 yr�1 [74], but yields are rising with

the introduction of improved strains and can be in excess

of 20 odt ha�1 yr�1 [95]. A 16-year rotation averaging

9.5 odt ha�1 yr�1 is assumed here, although rotations can last for

30 years. Biomass yields for the whole rotation are therefore

assumed to be 152 odt ha�1. Stick harvesting and baling was also

assumed because it is the most dominant. No allocation is

necessary as there is no co-production. A sensitivity analysis is

presented, showing the variability of results according to

different yields, rotation periods and carbon sequestration rates.

2.2.4. Land use IV: forest residuesForest residues refer to all forest material which may be of too

poor a quality for traditional timber markets, including resi-

dues arising from forestry operations, such as tops of stems,

3 Losses are due to crop trampling by machinery, to excessivemoisture content and to fallen leaves and tops.

rbon changes in the cultivation of energy crops: Implicationsioenergy (2010), doi:10.1016/j.biombioe.2009.10.019

Table 4 – Carbon sequestration in soils under differentland uses in UK per reference unit (haL1 yrL1).

Land use C sequestereda (t C) Reference

OSR �0.24� 0.08 [81]

Miscanthus 0.62 [103]

Willow SRC 0.09 – 0.18 [103]

Forest 0.32 [103]

a Negative value indicates C-emission to atmosphere.

Quality

SOCpot

t ini tfin trelax,pot

SOCfin

SOCini

trelax

relaxation

time

Time

(tC·ha-1)

R, Relaxation rate

Fig. 2 – Calculation of impacts on soil quality measured by

SOC.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 4 5

ARTICLE IN PRESS

side branches (which may include foliage), diseased wood and

deadwood [96], as well as those derived from chunks from

sawn timber milling waste [74]. These materials are normally

treated as waste, or at best considered a by-product. The

Biomass Energy Centre [97] estimates that almost 6.5 million

odt per year can be made available from UK forest and

woodlands, considering technical and environmental

constraints, but not economic and market constraints.

Insensitive harvesting of residues from forests can have

detrimental impacts on biodiversity.

Like the other land uses, the system is based on typical

practice in the UK [74]. Since the residues will be produced

whether they are used or not, allocation of the environmental

load between forest residues and the other co-products

(sawlogs and small roundwood) was not necessary as forest

residues are essentially waste. As a result, only the environ-

mental load related to the collection, extraction, transport,

drying and storage and chipping is included. Part of the resi-

dues originates from chunks from the sawlogs route. The

environmental load of transport and milling of sawlogs were

allocated to timber as the primary product. The chunks were

considered to be a waste product and their transformation into

chips regarded as a means of valorisation; therefore, all inputs

related to chipping of chunks were allocated to the chips.

2.3. Inventory analysis

A life cycle inventory analysis has been carried out for each land

use. The stages adopted include: cultivation, regeneration,

harvesting, baling, transport, chipping, drying, and storage. The

inputs considered include agrochemicals (fertiliser, pesticides,

herbicide, manganese), seeds, tree seedlings, cutting/sets,

rhizomes, liquid fuels, lubricating oil, electricity, machinery/

spares, softwood, steel, preservative; the latter three used for

fencing (Fig. 1). Post-farm processing is not considered.

Generic LCA data used for farm operations include fuel,

farm machinery and steel production for machinery spares.

All come from the ecoinvent 2000 v 1.2 database. Fertiliser

production data have been obtained from an existing study

Table 5 – Effects on soil quality at the cropping stage (typical v

SOCini

(t C ha�1)SOCini� SOCfin

(t C ha�1)SO

(t C

OSR 80 [102] �0.24 [81] 150

Miscanthus 80 [102] þ0.62 [103] 150

Willow SRC 80 [102] þ0.14 [103] 150

Forest residues 130 [102] 0 150

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and Bi

[98] (used within the ecoinvent database), as well as common

practice in the field in the UK [74]. Generic LCA data used for

harvest and post-harvest operations include fuel and elec-

tricity (UK generating mix). Table 1 summarises the main

inputs in each land use.

Nutrient-related emissions from soil (NH3; N2O; NOx; NO3�;

PO43�; CH4) have been obtained from literature values for crops

in general:

- NH3-N emission factors (expressed as % loss of N content)

from [99] have been used following the recommendation of

[100]; see Table 2.

- For N2O emissions, the emission factors for mineral fertil-

isers [101] have been used; see Table 3. For organic fertil-

isers, the content of nitrate and ammonium N has been

used with the factors in Table 2 for nitrate and ammonium.

- NOx-N has been considered as 10% of N2O-N [100], [p. 49].

- NO3� and PO4

3� have been obtained from literature values as

15 kg N-NO3�ha�1 yr�1 and 1 kg P-PO4

3�ha�1 yr�1 [62].

- An emission of 1 kg of CH4 to the air per each 150 kg of N

applied as ammonium fertiliser has been included [100],

[p. 58].

Calculation of changes in soil quality and GHG emissions

requires estimates of the effects of the production system on

soil organic carbon (SOC). Data on these are based on Refs.

[81,102,104]. Table 4 includes values of soil carbon emissions or

sequestration for all land uses and Table 5 includes initial stocks

of carbon for all land uses. It is assumed that all C captured as

SOC comes from atmospheric CO2 through photosynthesis, and

that all SOC degraded is emitted as CO2 to the atmosphere.

alues).

Cpot

ha�1)tini� tfin

(years)trelax

(years)DC CF

(t C yr ha�1 yr�1)

[102] 1 100.8 122.7

[102] 1 98.1 �65.3

[102] 1 99.6 40.3

[102] 1 100.0 20.0

rbon changes in the cultivation of energy crops: Implicationsoenergy (2010), doi:10.1016/j.biombioe.2009.10.019

-3,000

-2,000

-1,000

0

1,000

2,000

3,000

4,000

OSR Miscanthus Willow SRC ForestResidues

Land Use

OC

gk

(s

noi

ssi

me

GH

Gl

at

oT

2)

qe Soil

Storage

Drying

Transport

Mechanisation

Pesticides

Fertilisers

Propagation

Fig. 3 – Global Warming Potential of different land uses per

reference unit (haL1 yrL1) and their relative contribution

from different sources.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 46

ARTICLE IN PRESS

2.4. Impact assessment

The impact assessment phase has been performed using

mainly the CML 2001 method [104] due to its comprehen-

DCht C yr ha�1 yr�1

i¼�SOCpot � SOCini

�� ðtrelax � tiniÞ þ 1=2ðtrelax � tiniÞ �

�SOCini � SOCfin

��tfin � tini

� (1)

siveness in terms of environmental issues covered and its

scientific soundness. The following impact categories and

indicators have been considered because of their relevance to

agricultural and forestry systems:

� Primary energy use (measured in MJ);

� Climate change (measured as GWP of the GHG emitted [104],

including emissions from SOC degradation);

� Acidification Potential [104];

� Eutrophication Potential [104];

� Soil quality (through changes in SOC [31]),

The most novel aspects in terms of life cycle impact

assessment methodology are the inclusion of SOC degrada-

tion both for GWP and soil quality assessment. In the case of

GWP, one additional kg C stored in soil (a positive value in

Table 4) is equivalent to avoided GHG emissions of �3.67 kg

DCht C yr ha�1 yr�1

i¼

�150 t C ha�1 � 80 t C ha�1

�� ð100:8 yr� 99 yrÞ þ 1=2ð100:8 yr� 99 yrÞ �

�80 t C ha�1 � 79:76 t C ha�1

�

ð100 yr� 99 yrÞ ¼ 122:7

CO2-eq. (44 kg CO2/12 kg C), whereas 1 kg C released to the

atmosphere from SOC degradation has a GWP of 3.67.

It may be argued that carbon sequestered as SOC may be

re-released to the atmosphere in a short period of time, and

therefore the GWP attributed to such sequestration should be

closer to zero. The values we have used for the sequestration

rates are calculated as mid-term trends and thus incorporate

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and B

this issue at least partially. More sophisticated modelling is

required to include the temporal aspect in the GWP values, in

a similar way as suggested for wood products [105].

Soil quality refers to the ability of soil to sustain life support

functions [31,63]: biotic production; substance cycling and

buffer capacity; climate regulation. The impacts of production

systems on soil quality have not traditionally been included in

LCA, and the recommendations of Mila i Canals et al. [33] have

been followed here. Particularly, Mila i Canals et al. [31,33] and

others argue that soil organic matter (SOM) can be used as an

indicator for soil quality within LCA of agricultural systems:

an increase in soil organic matter due to the soil management

practices implies a benefit, whereas any decrease in SOM is

accounted as damage to the system. The impact is measured

as a carbon deficit (or credit, expressed by negative values)

with the unit ‘kg C$year’, referring to the amount of extra

carbon temporarily added to or removed from the soil in the

system studied compared to a reference system [31].

The method developed for land-use LCIA by Mila i Canals

et al. [31] has been slightly modified to follow the consider-

ations in [33]. The general formula used to calculate charac-

terisation factors (CF) for land-use flows is shown in Eq. (1); see

Fig. 2 for an explanation of the formula’s parameters.

where SOCpot is the potential level of SOC if land is left

undisturbed; SOCini the SOC level at the start of the land use

studied; SOCfin is the SOC level at the end of the cultivation

period; the studied land use starts at time tini and ends at time

tfin; and at time trelax soil quality has reverted to the level prior

to land use. trelax may be calculated from the relaxation rate R

(see third assumption below). The equation assumes very

simplified shapes of the evolution of soil quality, as suggested

in [33]. The first component of the numerator refers to the

impacts due to the postponed relaxation of the system (light-

coloured area in Fig. 2), whereas the second component is the

dark-coloured ‘‘triangle’’, referring to the impacts due to the

change in quality during the occupation. The denominator

serves to express the characterisation factors per ha yr, with

all SOC values expressed as t C per ha.

For example, in calculating the soil quality impacts of OSR,

we have:

The following assumptions have been made:

– All transformation impacts are allocated to the subsequent

100 years of cropping, as opposed to the suggestion by

Ref. [106], who allocated all transformation impacts to the

first year of cropping. All land transformations took place

more than 100 years ago. For more information on the

rbon changes in the cultivation of energy crops: Implicationsioenergy (2010), doi:10.1016/j.biombioe.2009.10.019

Table 6 – Summary of yields in each land use perreference unit (haL1 yrL1) (NB: excludes gate-to-grave lifecycle stages).

OSRa Miscanthusb WillowSRCc

Forestresiduesc

Biomass yield (t) 2.9 19.2 9.5 0.5

Energy yieldd (GJ) 52.0 345.6 169.5 8.6

Energy

requirement (GJ)

14.1 6.9 6.4 0.1

Net energy

yield (GJ)

37.9 338.7 163.2 8.5

a Dried rapeseed.

b Miscanthus fuel feed (25% moisture content).

c Dried wood chips (25% moisture content).

d Net calorific value of the crop (indicative values only).

Table 7 – Summary of GHG emissions (kg CO2-eq.) in eachland use per reference unit (haL1 yrL1).

OSRa Miscanthusb WillowSRCc

Forestresiduesc

(A) Cradle-to-gate

excl. SOC

1833 707 332 10

(B) SOC 880 �2273 �497 0

(C) Cradle-to-gate

(Aþ B)

2763 �1567 �165 10

(D) Gate-to-graved 344 980 432 28

(E) Totale (CþD) 3107 �587 267 38

(F) Avoidede �3509 �10,509 �10,638 �540

(G) Total incl.

avoidedd (Eþ F)

�402 �11,096 �10,371 �502

a Dried rapeseed.

b Miscanthus fuel feed (25% moisture content).

c Dried wood chips (25% moisture content).

d Indicative values only.

e Biodiesel from OSR displaces diesel, whereas power from the

combustion of Miscanthus displaces electricity from UK grid. Heat

from the combustion of wood chips from Willow SRC and Forest

Residues displaces heat from an oil-fired boiler.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 4 7

ARTICLE IN PRESS

calculation of the characterisation factors for all land-use

flows, refer to Ref. [107].

– SOCpot for UK and all background uses is 150 t C ha�1

(temperate warm forest, [102])

– Changes in soil quality due to land use have been assessed

relative to a situation where this activity is not undertaken.

Thus, natural relaxation has been used as the reference

system4 [33]. The relaxation rate, R, during natural relaxation

has been estimated as 0.32 t C ha�1 yr�1 [103].

3. Results

For the reasons outlined in Section 2.1, the reference unit for

the study is production of the specified crop on 1 ha of land for

one year; i.e. 1 ha yr. The results in Sections 3.1–3.5 are

expressed on this basis.

3.1. Global warming potential

Fig. 3 shows the GHG emissions resulting from the different

land uses, showing the contributions of the different life cycle

stages. These emissions are clearly dominated by changes in

SOC (see Section 2.2). Table 6 gives the numerical values for

the energy balances and Table 7 shows the GHG balances.

Fertiliser use causes much of the impact for OSR, primarily

due to field emissions of greenhouse gases, mainly N2O from

soil and CO2 from oxidation of soil organic carbon, with

additional emissions of CO2 and N2O from fertiliser produc-

tion. For Miscanthus and willow SRC, SOC sequestration more

than compensates for the emissions. The impacts allocated to

recovering forest residues are low.

3.2. Soil quality (soil organic carbon)

The effect of the different land uses on soil quality is shown

diagrammatically in Fig. 4, while Fig. 5 and Tables 4 and 5 give

the quantitative estimates for SOC changes. Oilseed rape has

4 An alternative more consequential approach would assumethat, instead of natural relaxation, UK cropland would most likelybe used for food or feed production. The reference would beadopted accordingly.

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and Bi

the highest detrimental impact on soil quality because of the

differences between SOCpot and SOCini, and between SOCini

and SOCfin. In this way, not only does OSR delay relaxation,

but it also decreases levels of SOC during occupation. Most of

the impact is due to the delay of relaxation rather than the

occupation itself. Miscanthus has a beneficial impact as it

increases SOC levels at rates higher than the relaxation rate.

Willow SRC has a detrimental effect because, even though this

land use shows a net increase in SOC, this increase is smaller

than the reference system considered (0.136 t C ha�1 yr�1

compared to 0.320 t C ha�1 yr�1 during natural relaxation, see

Section 2.4).

In the case of forest residues, zero accumulation of SOC has

been assumed, even though forests tend to accumulate SOC.

SOC is assumed to increase at 0.32 t C ha�1 yr�1 [102] if the

forest residues are not removed, but removal of residues is

assumed to eliminate this increase. This is a conservative

assumption, because it assumes that all the SOC accumula-

tion results from the residues and none from leaves, twigs and

roots. The effect of removing forest residues on soil quality is

slightly lower than that of Willow SRC, but it is still

detrimental.

Most of the total impact is due to the change in relaxation

in all land uses, and occupation impacts are negligible.

3.3. Acidification potential

Fig. 6 shows the acidification potential of emissions from the

different land uses. OSR is the land use generating the highest

acidification potential. Fertiliser use contributes most to

acidification for both Miscanthus and OSR, mainly due to fer-

tiliser-related ammonia emissions. On the other hand,

nitrogen oxide emissions from diesel use dominate for willow

SRC.

rbon changes in the cultivation of energy crops: Implicationsoenergy (2010), doi:10.1016/j.biombioe.2009.10.019

Fig. 4 – Representation of the effect of OSR (top left) Miscanthus (top right), Willow SRC (bottom left) and Forest Residues on

Soil Quality (not to scale).

)

30

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 48

ARTICLE IN PRESS

3.4. Eutrophication potential

Fig. 7 shows the eutrophication potential arising from the

different land uses. Again, OSR shows the highest impact,

dominated by the estimated nutrient emissions from fertiliser

use: ammonia (NH3) and nitrate (NO3�) emissions to water.

3.5. Primary non-renewable energy use

Fig. 8 shows the primary non-renewable energy requirements

(expressed in GJ) to produce bioenergy from 1 ha of different

-100

-50

0

50

100

150

Oilseed rape Miscanthus Willow SRC Forest Residues

Land Use

)r

yC

t(

ytil

au

qli

os

no

tc

ap

mI

Fig. 5 – Impact of the different land uses on Soil Quality per

reference unit (haL1 yrL1).

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and B

land uses. It is noteworthy that oilseed rape uses more than

twice the energy per ha of any of the other land uses, even

without considering post-farm processing. This is mainly due

to the nitrogen fertiliser used. Energy use in the Miscanthus life

cycle arises mainly from herbicide production and diesel use.

Fencing and diesel use in mechanical operations in the culti-

vation, harvesting and chipping stages account for most

PA

(l

ai

tn

et

oP

no

it

ac

if

id

ic

A

OS

gk

[2

]q

e-

0

5

10

15

20

25

Oilseed rape Miscanthus Willow SRC Forest Residues

Fig. 6 – Acidification Potential per reference unit

(haL1 yrL1).

rbon changes in the cultivation of energy crops: Implicationsioenergy (2010), doi:10.1016/j.biombioe.2009.10.019

)P

E(

l

ai

tn

et

oP

n

oi

ta

ci

hp

or

tu

E

]q

e-

et

ah

ps

oh

P

gk

[

0

5

10

15

20

25

30

Oilseed rape Miscanthus Willow SRC Forest Residues

Fig. 7 – Eutrophication Potential per reference unit

(haL1 yrL1).

Table 8 – Summary of energy and carbon-equivalentbalances per GJ in each land use (NB: includes all life cyclestages – indicative values only).

OSR Miscanthus WillowSRC

Forestresidues

Land area (ha yr) 0.025 0.015 0.010 0.194

Energy requirement (GJ) 0.44 0.27 0.11 0.10

GHG emissions excl.

SOC (kg CO2-eq.)

40.7 26.0 7.5 7.4

GHG emissions from

SOC (kg CO2-eq.)

36.4 �35.0 �4.9 0.0

Total GHG emissions

(kg CO2-eq.)

77.0 �9.0 2.6 7.4

Total GHG emissions

incl. avoided

emissions (kg CO2-eq.)

�10.0 �171.0 �102.4 �97.7

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 4 9

ARTICLE IN PRESS

energy use in willow SRC, and forest residues use energy

mostly through mechanisation (diesel fuel use in the regen-

eration and harvesting stages, and chipping). The cultivation/

regeneration stages therefore represent the hotspots in

energy use, mainly due to the use of agrochemicals and fossil

fuels.

3.6. Net energy yield

Although the focus here has been on land use, it is of interest

to give broad comparisons in terms of net energy yield. Table 6

gives indicative values for the net calorific value of the

biomass leaving the ‘‘gate’’ (Energy Yield), not allowing for

energy used in subsequent processing or transport. Table 8

gives the resulting figures for the impacts and land use per GJ.

In order to show the significance of the results, they are con-

verted into indicative values for the whole fuel cycle using

representative values of net energy yield and avoided energy

use (see Tables 6–8).

The energy crops present the highest energy yield per ha,

with the yield of Miscanthus being more than twice that of

willow SRC (see Table 6). The relatively low energy yield of OSR

Fig. 8 – Primary energy use per reference unit (haL1 yrL1).

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and Bi

combined with the relatively high energy requirements

results in a low net energy yield.

3.7. Sensitivity analyses

The results obtained will vary according to the adopted

assumptions of yield, productive period, and carbon seques-

tration rates. These varying assumptions found for Willow

SRC are tested in this section and presented in Tables 9–11.

The other land uses were not subject to sensitivity analyses

since there were no data variability found for their

parameters.

The yield of wood chips from SRC can be as much as

20 odt ha�1 yr�1 (see Section 2.2) and the production period

can be up to 30 years. The crop energy yield increases

accordingly (�356 GJ ha�1 yr�1). The energy requirement of

SRC now varies between 6.4 and 7.9 GJ ha�1 yr�1, resulting in

a net energy yield of 163–348 GJ ha�1 yr�1 (see Table 9).

If we further assume that the carbon sequestration rate

varies from 0.09 to 0.18 t C ha�1 yr�1, total GHG emissions are

between �328 and 98 kg CO2-eq. ha�1 yr�1, implying that,

without considering the rest of the life cycle, SRC on its own

may not be carbon-negative. Table 10 presents indicative

values for the whole fuel cycle. These are in the range of 104–

1091 kg CO2-eq. ha�1 yr�1. Assuming that heat production

from the combustion of wood chips displaces heat provided

by a small-scale oil-fired boiler, between 10,638 and 22,340 kg

CO2-eq. ha�1 yr�1 are avoided, depending on the yield

assumptions. The total GHG emissions, therefore, vary

between �21,576 and �10,208 kg CO2-eq. ha�1 yr�1 when the

whole fuel cycle is considered. All variances are explained by

Table 9 – Analysis of sensitivity to Willow SRC yields andproductive period per reference unit (haL1 yrL1) (NB:excludes gate-to-grave life cycle stages).

Biomass yield (t) 9.5–20.0

Energy yielda (GJ) 169.5–356.0

Energy requirement (GJ) 6.4–7.9

Net energy yield (GJ) 163.2–348.1

a Net calorific value (indicative values only).

rbon changes in the cultivation of energy crops: Implicationsoenergy (2010), doi:10.1016/j.biombioe.2009.10.019

Table 10 – Sensitivity analysis of GHG emissions (kg CO2-eq.) to Willow SRC yields, productive period and carbonsequestration rates per reference unit (haL1 yrL1).

(A) Cradle-to-gate excl. SOC 332–431

(B) SOCa �660 to �334

(C) Cradle-to-gate (Aþ B) �328 to 98

(D) Gate-to-graveb 432–993

(E) Totalb (CþD) 104–1091

(F) Avoided c 10,638–22,340

(G) Total incl. avoidedb (Eþ F) �21,576 to �10,208

a Negative value indicates C sequestration from the atmosphere.

b Indicative values only.

c Heat generated from the combustion of wood chips from Willow

SRC displaces heat from small-scale oil-fired boiler.

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 410

ARTICLE IN PRESS

the extreme assumptions for the values of SOC sequestration,

yield and productive period (see Table 10).

Varying rates of SOC sequestration will also determine the

magnitude of the effects on soil quality. Willow SRC is asso-

ciated with a rate of SOC sequestration of 0.09–0.18 t

C ha�1 yr�1, which results in a change in SOC of 30.6–50.1 t

C yr ha�1 yr�1.

Table 11, finally, shows the above results per GJ of heat

produced by the small-scale combustion of wood chips from

Willow SRC. The land area required per GJ is between 0.005 and

0.010 ha. The energy requirement varies between 0.092 and

0.113 GJ GJ�1(energy input per energy output). Fossil-based

GHG emissions vary between 6.7 and 7.5 kg CO2-eq. ha�1 yr�1

which are counterbalanced by their biogenic counterparts

from soil and result in 1.0–5.1 kg CO2-eq. ha�1 yr�1. These low

figures are fully compensated by the avoided emissions from

heat generated from an oil-fired boiler, to result in a total GHG

emission that is negative (�99.9 to �104.0).

Overall, the sensitivity analyses show that the GHG

balances for Willow SRC may vary substantially, but that this

land use always yields net negative emissions.

In this paper, impacts form land transformations are allo-

cated over the subsequent 100 years of cropping. Because we

assume that, at the cropping stage, land transformations from

an undisturbed state happened more than 100 years ago, no

impacts from transformation are considered for GWP or for

soil quality. These impacts refer to the change in SOC levels

from 150 t C ha�1 (SOCpot) to 80 t C ha�1 (SOCini). The magni-

tude of these impacts is as follows:

- for GWP, soil emissions of 70 t C ha�1 (257 t CO2 ha�1)

- for soil quality, transformation is responsible for 7656 t

C yr ha�1 yr�1

Table 11 – Sensitivity analysis of energy and carbon-equivalent balances per GJ in Willow SRC (NB: includes alllife cycle stages – indicative values only).

Land area (ha yr) 0.005–0.010

Energy requirement (GJ) 0.092–0.113

GHG emissions excl. soil (kg CO2-eq.) 6.7–7.5

GHG emissions from soil (kg CO2-eq.) �6.5 to �1.6

Total GHG emissions (kg CO2-eq.) 1.0–5.1

Total GHG emissions incl. avoided emissions

(kg CO2-eq.)

�99.9 to �104.0

Please cite this article in press as: Brandao M, et al., Soil organic cafor GHG balances and soil quality for use in LCA, Biomass and B

There is no standard method for allocating the impacts

from transformation along subsequent land uses (see Section

2.4). If we consider that land transformation happened less

than 100 years prior to the land use under study, each annual

land use is responsible for 1% (1 year out of 100 years) of the

impacts from transformation. Consequently, 2.57 t CO2 ha�1

would be added to the GWP, which is more than the emissions

from the rest of the life cycles of these crops. Similarly, 77 t

C yr ha�1 yr�1 would be a significant portion of the total

impacts on soil quality. The results of the impacts of land

transformation are therefore highly sensitive to the time

period adopted between land transformation and land use

under study, as well as the period within which the impact

from land transformation is allocated to subsequent crops.

4. Discussion

Eutrophication emissions are derived from literature values,

and it should be noted that while NH3 emissions are propor-

tional to the amount of fertilisers used, a fixed rate has been

assumed for nitrate emissions (see Section 2.3). Whilst the

authors believe this value is representative, it is presented as

an indication only.

In terms of the energy balance, although it may be relevant

to have information on the energy use of a system, primary

energy use is not per se an environmental impact category.

However, Huijbregts et al. [108] found that Cumulative Energy

Demand (or the total non-renewable energy used along the

life cycle) correlates well with most environmental life cycle

impact categories and can, therefore, be considered an

appropriate proxy indicator for environmental performance.

Indeed, comparison of Figs. 3 and 5–8 shows that primary non-

renewable energy use gives the same ranking of different

crops as acidification and eutrophication. However, when SOC

is included in the analysis, primary energy use does not

correlate with GHG emissions or soil quality, so that it cannot

be used as a proxy.

Estimates of changes in SOC are highly dependent on the

input data for the initial soil quality and on the reference

system used for comparison; the latter point has also been

noted by others [109]. Furthermore, SOC evolution depends

strongly on management practices and location, and so any

decision to use one value or another should be properly

justified. In this work, the estimates are all derived from

literature values. Therefore, while the results obtained here

are plausible, they should also be interpreted as broad

comparisons only. However, the differences found between

different land uses are so large that they may be considered

significant.

5. Conclusions

Changes in SOC dominate the GHG emissions from cultivation

of energy crops, followed by diesel and fertiliser use. It is thus

important to consider changes in SOC in LCA studies of energy

crops, and challenge the results of those studies not including

them. Of the four energy crops studied, OSR shows the biggest

impacts on soil quality. This is due to OSR causing the largest

rbon changes in the cultivation of energy crops: Implicationsioenergy (2010), doi:10.1016/j.biombioe.2009.10.019

b i o m a s s a n d b i o e n e r g y x x x ( 2 0 1 0 ) 1 – 1 4 11

ARTICLE IN PRESS

degradation of SOC during the land use (i.e. the dark-coloured

area in Fig. 2); but also, and primarily, because of the change in

relaxation (SOCpot� SOCini), which adds to the magnitude of

the impact for OSR (i.e. light-coloured area in Fig. 2). It should

also be noted that land-use impacts are multi-faceted (e.g.

including effects on biodiversity and water quantity/quality

[93,110]): SOC does not indicate all possible impacts on soil

quality, so that alternative/complementary indicators may be

required in specific cases (e.g. when erosion or salinisation

dominates soil degradation).

Apart from CO2 emissions derived from SOC degradation,

other field emissions – primarily nitrogen fertiliser-related

emissions – dominate many of the impacts considered: N2O

contributing to GHGs, NH3 to acidification, and NH3 and NO3�

to eutrophication.

The focus of this study has been on the GHG balance and it is

clear that land under Miscanthus has the lowest impact, mainly

due to C sequestration. However, Miscanthus is not the best

land-use option for other impacts – acidification and eutro-

phication. The LCA approach is, therefore, a very informative

tool that, among other things, makes clear the existence of

trade-offs but does not necessarily give a simple identification

of the preferred alternative. Decision processes therefore need

to recognise trade-offs between different impacts, for example

using some form of Multi-Criteria Decision Analysis.

This work has confirmed that ligno-cellulosic energy crops

and forest residues give much higher yields and lower GHG

emissions than the arable crop OilSeed Rape. However, anal-

ysis of competition for land between food and energy crops

requires further assessment, using a consequential LCA

approach which allows for displaced land use as well as full

life cycles. This will require data on the most likely effects of

land-use change and the net energy yield associated with the

land uses. This net energy yield will help to estimate the GHG

emissions and other impacts avoided by replacing other

energy sources and other land uses. However, if food

consumption is constant, food production displaced by energy

crops will be replaced by imports so that any net environ-

mental gain will be lowered. Such displacement effects need

to be identified and their environmental consequences

included in any truly holistic assessment of energy crops.

Acknowledgements

Miguel Brandao was funded by a bursary awarded by EPSRC.

Dr. Mila i Canals was funded by the RELU programme (http://

www.relu.ac.uk), and benefited from logistic support from

GIRO CT (http://www.giroct.net) during the preparation of this

paper.

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