CAN CROP MANAGEMENT IMPROVE EMISSIONS SAVINGS?: PRELIMINARY RESULTS OF THE

OPTIMIZATION OF RYE (Secale cereale L.) AS ENERGY CROP FOR ELECTRICITY PRODUCTION IN SPAIN

Martín-Sastre C.1*, Maletta E.2, Ciria P2, Perez P.2, del Val A.2, Santos A. M.1,

González-Arechavala Y.1 and Carrasco J. E.2

1 Institute for Research in Technology (IIT) - ICAI School of Engineering - Comillas Pontifical University - E-28015, Madrid

(Spain). Phone: +34 91 542-2800, Fax: +34 91 542-3176 2 CEDER-CIEMAT. Energy Department. Biomass Unit. Autovía de Navarra A-15, salida 56.

42290 Lubia (Soria). Phone: +34 975281013 *Corresponding author: carlos.martin@iit.upcomillas.es

Several studies suggest that lignocellulosic energy crops for electricity production may have a better performance

compared to those crops for liquid biofuels production, when assessing GHG savings with respect to fossil references. Winter cereal residues and some annual winter grasses, as dedicated energy crops, are currently being grown in Spain and harvested as bales to be burned for electricity production in biomass power plants. Previous studies of our group analyzed GHG emissions and energy balances of winter cereals for electricity production by means of Life Cycle Assessment. We selected highly productive genotypes of three annual winter cereals (rye, triticale and oat) and compared them with Spanish electricity produced using natural gas. This paper compares effects of the use of different crop management practices for rye growing in the assessment of energy balances and GHG emissions. We analyzed the effects of six different management practices consisting of two different sowing doses

(suboptimal and normal) combined with three top fertilization doses (zero, 30 and 80kgN ha-1). We made a characterization analysis of biomasses to estimate the nitrogen uptake of the crops in order to compare it with the nitrogen provided by the fertilizers. This comparison evaluates if lower fertilization doses are sustainable for the soil nitrogen stocks. Our results suggest that there is trade-off between soil nitrogen and emission savings. The use of zero or low top fertilization doses (30 kg N ha-1) improves GHG emissions and energy balances even with a yield reduction. Nevertheless the use of these doses imply an annual lose in soil nitrogen stocks for the majority all of our trials. Using suboptimal sowing doses resulted in yield decreases that did not compensate the lower input consumed. Keywords: electricity, energy balance, energy crops, greenhouse gases (GHG), life cycle assessment (LCA),

sustainability criteria

1 INTRODUCTION

The climate change problem coupled with declining oil and gas reserves has led to the development of energy sources to minimize greenhouse gas (GHG) emissions

and expand energy supplies from solar, wind, hydraulic, geothermal and bioenergy sources [1]. Solid and liquid biofuels guarantee the energy security and reduce GHG emisions when compared to fossil referecences in many studies [1–3] [4–6]. Several studies suggest that lignocellulosic energy crops for electricity production may have a better performance compared to those crops for liquid biofuels production, when assessing GHG savings with respect to fossil references [7,8].

Winter cereal residues and some annual winter grasses, as dedicated energy crops, are currently being grown in Spain and harvested as bales to be burned for electricity production in biomass power plants [9]. Previous studies of our group analyzed GHG emissions and energy balances of winter cereals for electricity production by means of Life Cycle Assessment [10]. We selected highly productive genotypes of three annual

winter cereals (rye, triticale and oat) and compared them with Spanish electricity produced using natural gas.

In this article we compare the effects of the use of different crop management practices for rye, grown as dedicated energy crop for electricity production, in the assessments of GHG emissions and energy balances by means of Life Cycle Assessment. For this purpose six crop management practices were considered. These

practices consists of combining the use of low (24 kg ha-

1) and typical (120 kg ha-1) seed doses with zero top fertilizer dose (0 kg N ha-1), low fertilizer dose (30 kg N ha-1) and typical fertilizer dose (80 kg N ha-1). Also a

nitrogen balance was made to assess the sustainability of lower fertilizer doses for soil nitrogen stocks. To evaluate the effects of management practices three plots were established for each practice in the northern of Spain (Soria’s province). The parcels were grown by famers

using traditional management practices for cereals in the zone, except for sowing and top fertilization doses as objectives of the assessment. Farmers prepared the land, pesticides and NPK fertilizers were applied, seeds were spread, top fertilization was made (in case it applies for the trial) and crop was harvested through mowing, swathing and baling. The system analyzed considers real data collection from farmers, transportation of square bales and a real power biomass plant for electricity

production in northern Spain. The results were compared to electricity production from the National natural gas.

2 MATERIALS AND METHODS

Life Cycle Assessment (LCA) is the environmental tool we selected to determine the energetic and

environmental performance of rye to produce lignocellulosic biomass for electricity generation.

LCA is a systematic set of procedures for compiling and examining the inputs and outputs of materials and energy and the associated environmental impacts directly attributable to the functioning of a product or service system throughout its life cycle [11]. This environmental assessment tool is regulated by ISO 14040 [11] and ISO

14044 [12] standards, and according to this, LCAs should follow four steps: (1) goal and definition, (2) inventory analysis, (3) impact assessment and (4) interpretation.

Simapro 7.2 [13,14] software tool and Ecoinvent 2.2

[15,16] European database have been selected for the LCAs.

Also a rough nitrogen balance was made considering nitrogen supply by fertilizers and measuring the amount of nitrogen contended in the crops as the nitrogen

extracted. Prior to the description of the LCAs conducted and

the nitrogen balance methodology, some methodological aspects regarding the experimental design and the biomass characterization and productivity are described in the two following subsections.

2.1 Experimental design

To assess the effects in energy and GHG balances of

crop management practices a plot of 8500 m2 was established to grow rye. The management practices consist on the application of two different sowing doses and three top fertilization doses resulting in six possible combinations. For its possible combination three trials were done dividing the 8500m2 of the parcel eighteen smaller plots. The Table I summarizes the characteristics of the site selected for the study as well as the conditions

of the each crop management practice used. Table I: Experimental design summary

1. Location Soria

Coordinates 41º 36’ 40.0” N

2º 28’ 55.6”W

Altitude 1035 m

2. Experimental period 2010-2011

3. Climate

Continental

Mediterranean with cold

winters

Average Temperature / rainfall 10.4ºC, 446.5 mm

4. Soil type

Clay (%) / Sand (%) / Silt (%) 13.56 / 80.66 / 5.09

Texture Sandy loam

Organic matter (%) 1.07

Nitrogen (%) 0.06

5. Genotype

Specie (variety) Secale Cereale (Petkus)

6. Plots

Quantity / type / size 18 / Strips / 0.04-0.05 ha

7. Crop management practices

Typical Seed Dose (TSD) 120 kg ha-1

Low Seed Dose (LSD) 24 kg ha-1

Common Top Fertilization (TTF) 80 kg N ha-1

Low Top Fertilization (LTF) 30 kg N ha-1

Zero Top Fertilization (ZTF) 0 kg N ha-1

2.2 Biomass characterization and productivity

In order to assess the environmental and energetic performance of rye biomass as solid fuel for electricity,

the productivity of crop management trials was measured (see Table II).

Table II: Biomass productivity

Crop

Management

Seed

Dose

(kg ha-1

)

Top

Fertilizer

Dose

(kg N ha-1

)

Trial productivity

(odt ha-1

)

1st 2

nd 3

rd

TSD & ZTF 120 0 9.001 10.142 7.092

TSD & LTF 120 30 10.792 10.442 8.182

TSD & TTF 120 80 13.200 11.815 10.548

LSD & ZTF 24 0 7.758 6.992 4.773

LSD & LTF 24 30 7.860 6.447 4.403

LSD & TTF 24 80 9.045 8.099 6.087

Average data about dry basis composition and net heating value of the managment practices trials are shown in Table III. The net heating value at constant pressure has been calculated for humidity contents of 0% and 12%, as 12% is the average humidity of burned biomass in the biomass power plant selected for this research.

Table III: Aerial biomass characterization

Crop

Management

C

(%)

N

(%)

NHVcp,0

(MJ kg-1

,db(1))

NHVcp,12

(MJ kg-1

,wb(2))

TSD & ZTF 44.8 0.84 16.70 14.40

TSD & LTF 45.1 0.86 16.76 14.46

TSD & TTF 45.4 0.87 16.90 14.58

LSD & ZTF 45.10 1.00 17.11 14.76

LSD & LTF 45.40 1.03 17.17 14.81

LSD & TTF 45.7 1.04 17.31 14.94

3 RYE LCA METHODOLOGY

The following sub-sections describe the methodology follow to conducts the rye optimization life cycle assessments.

3.1 Goal and Scope definition The aim of this study is to evaluate the energy

balance and environmental impacts of six crop management practices for growing rye in Spain for electricity generation and compare them with electricity generation from natural gas, as a reference for generation from non-renewable fossil sources.

3.2 Functional unit The functional unit chosen is 1 TJ of electrical energy

generated from rye biomass for the studied system and from natural gas for the reference system. This amount of electrical energy is a round number corresponding to 12 hours of functioning of the 25Mw power plant selected for this study (see 3.3.2).

The electricity production per hectare of rye trial is the product of the crop yield (see Table II) at 12 %

humidity by the net calorific value at 12 % humidity (see Table III) and by the efficiency of the biomass conversion process into electricity (29.5 % for this case study). According to this, between 17 ha and 51 ha are needed to produce 1 TJ for the higher and the lower yielding trials.

3.3 Systems description

The bioenergy systems analyzed includes three subsystems: agricultural biomass production, electricity generation and the transport of products and raw materials.

3.3.1 Agricultural system The agricultural system could be described by the

crop schemes followed, the machinery used and the

inputs consumed. This information is shown in Table IV

for all the crop management trials made in Soria for the rye bioenergy cropping system.

Table IV: Agricultural system summary for the Soria trials.

Operation Tractor Implement Inputs

Weight Power Type Weight Operating

rate Fuel consumption

(kg) (kWh) (kg) (h ha-1

) (L ha-1

)

Primary tillage 5470 103 Moldboard

plow 1390 1 20

Secondary tillage 5470 103 Cultivator 400 0.66 10

Base fertilization 3914 66 Spreader 110 0.20 4 NPK fertilizer 8-24-8 300 kg ha-1

Sowing 5470 103 Seeder 830 0.60 8 Hybrid rye seeds (kg ha

-1):

TSD (24), LSD (120).

Herbicide

treatment 3914 66

Boom

sprayer 230 0.50 4

MCPA 0.332 kg ha-1

, Dicamba

0.125 kg ha-1

, 2 ,4-D 0.370 kg ha-1

Top fertilization 3914 66 Spreader 110 0.20 4 Calcium ammonium nitrate 27% kg

ha-1

: TTF (300), LTF (100), ZTF (0)

Rolling 3914 66 Roller 1000 0.40 8

Mowing-Swathing 3914 66 Mower 150 0.70 8

Baling 3914 66 Baling packer 1700 0.40 4

Loading Bales 5470 103 Trailer 1870 0.40 4

3.3.2 Biomass power plant system

All the data considered to model the biomass power plant system are real data from a 25 MW biomass plant located in northern Spain. This plant consumes biomass at an average humidity of 12% and produces electricity

with a conversion efficiency of 29.5%. The plant consumes natural gas for maintenance operations and pre-heating and produces ashes and slag from biomass as residues. The average consumption of natural gas and the productions of ashes and slag per kilogram of burned biomass are shown in Table V.

Table V: Biomass power plant consumptions and

residues produced

Consumed or produced

substances Amount

Natural gas consumption

(MJ Kg-1

Wet Biomass Burned)

0.0342

Slag production

(g Kg-1

Wet Biomass Burned) 82.47

Ashes production

(g Kg-1

Wet Biomass Burned)

8.25

The emissions of the plant into the air are submitted

regularly to the local government. The emissions accounted are only those which affect the global warming potential (GWP). In the power plant studied these emissions come from gas natural combustion (see Table

VI). Carbon dioxide emitted from biomass combustion was not considered because it was previously fixed from

the air by the crop. Table VI: Biomass power plant aerial emissions

Substance Origin Amount

(g Kg-1

Wet Biomass

Burned)

Fossil carbon

dioxide Natural gas 1.94

3.3.3 Transport system The transport system is summarized in Table VII.

This table shows all modes of transport used and the distances between origin and destination points for every transport in the LCAs carried out.

The transportation means and distances for the transport of agricultural inputs until the regional storehouse are taken from the Ecoinvent database [17]. The distance from the regional store house to plots was 10 km approximately. The transport of workers to the parcel has not been considered because of the highly variability of transport distances depending on cases.

Biomass, ash and slag means of transport and distances were provided by company in charge of the

biomass power plant.

Table VII: Transport system summary

Material From To Distance Vehicle

Seed Field Processing

center 30 km

Lorry

20-28t

Processing

center

Regional

storehouse 100 km

Lorry

20-28t

Regional

storehouse

Demonstration

parcel 10 km

Lorry

16-32t

Fertilizers

and

herbicides

Manufacturer Regional

storehouse 600 km Train

100 km Lorry

>16t

Regional

storehouse

Demonstration

parcel 10 km

Lorry

16-32t

Biomass Demonstration

parcel Biomass plant 60 km

Lorry

16-32t

Ash and

slag Biomass plant Disposal 37 km

Lorry

16-32t

3.3.4 Natural gas system

The natural gas system includes the gas field operations for extraction, the losses, the emissions and the purification of the main exporter counties of natural gas to Spain (Algeria 73 % and Norway 27 %). Also includes the long distance and local transport of gas to

the power plant in Spain, considering the energy consumption, loses and emissions for distribution. Finally the substances needed and the average efficiency of Spanish natural gas power plants to produce electricity are taken into account [18].

3.4 Life cycle inventory analysis

The inventories used to consider natural gas consumption [18] of the biomass power plant, transports [19] of agricultural inputs, and biomass and power plant residues are taken from Ecoinvent.

The methods used for the inventory analysis of the agricultural system mainly follow that proposed on Life cycle inventories of agricultural production systems [17].

To consider N2O emissions we follow the formula proposed by de RSB GHG Calculation Methodology v 2.0 [20]. This formula is basically based on the formula proposed in the Ecoinvent Agricultural Report [17], that considers the new IPCC guidelines [21]. Also we consider the nitrate emissions affecting to Global Warning Potential as the RSB purposes [20], making and estimation of them by means of nitrogen balance, the soil

and crop characteristics and the rainfall of the zone.

3.4.1 Fertilizers productions The fertilizer inventories consider the different steps

of the production processes, such as the use of raw materials and semi-finished products, the energy used in the process, the transport of raw materials and intermediate products, and the relevant emissions [17].

The production of calcium ammonium nitrate starts with the production of the ammonium nitrate by the neutralization of ammonia with nitric acid. The final product is then obtained by adding dolomite or limestone to the solution before drying and granulation [22].

No inventories are given in Ecoivent for multinutrient fertilizers due to the amount different possible ways to mix nitrogen, phosphorous and potassium compounds to

produce NPK fertilizers [22]. The modeling of NPK fertilizer inventories has been approximated by combining inventories of single fertilizers according to multinutrient fertilizer specific contents of N, P2O5 and K2O, as well as the form of the nitrogen provided (ammonium, nitrate or urea) [22]. 3.4.2 Herbicides production

The data related to emissions, energy and substance

consumption in the production of the herbicides sprayed is taken from Ecoinvent [23]. The quantities of active matters considered are taken from the formulations of the commercial fertilizers used. 3.4.3 Seed production

Annual cereal seeds are produced in Spain under similar conditions compared to the operations of fertilizer

and management practices used for commercial grain or forage cultivation techniques. Rye is frequently produced under irrigation in high quality soils under contract with real farmers, thus their normal operations and yield production were assumed to be similar to that of the local common management practices cosidered in this study.

Then, a grain production yield of 5.5 odt ha-1 was considered as harvest index of 35 % for Petkus variety as

a non hybrid rye genotype. The energy consumption for cleaning, drying, seed

dressing, and bag filling of the cereal seed in the procesing plant has been estimated in 32.8 kWh t-1[24].

3.4.4 Diesel consumption and combustion emissions of agricultural machinery

The diesel consumption of agricultural machinery is obtained from Table V. The inventories for the extraction, transport of petrol, the transformation into

diesel and its distribution are taken from Ecoinvent [25]. The exhaust emissions of diesel in agricultural

machinery engines are also considered [26]. 3.4.5 Agricultural machinery manufacture

The inventories for agricultural machinery manufacture are specific to the different types of machinery (tractors, harvesters, tillage implements or general implements).

The amount of machinery (AM) needed for a specific process was calculated multiplying the weight (W) of the machinery by the operation time (OT) and dividing the result by the lifetime of the machinery (LT) [17]:

AM (kg FU-1) = W (kg) OT (h FU-1) LT-1(h); Where FU (See 3.2) is the functional unit of the LCA.

The life time of the machinery was provided by its owners.

3.4.6 Nitrous oxide emissions

The calculation of the N2O emissions [20] is based on the formula in Nemecek et Kägi [17] and adopts the new IPCC guidelines [21]:

N2O= 44/28∙(EF1∙(Ntot+Ncr)+EF4∙14/17∙NH3+EF5∙14/62∙NO3-) With: N2O = emissions of N2O [kg N2O ha-1] EF1 = 0.01 (IPCC proposed factor [21]) Ntot = total nitrogen input [kg N ha-1] Ncr = nitrogen contained in the crop residues [kg N ha-1]

EF4 = 0.01 (IPCC proposed factor [21]) NH3 = losses of nitrogen in the form of ammonia [kg NH3 ha-1]. Calculated as proposed in the RSB [20] and Nemecek et Kägi [17] methodologies. 14/17= conversion of kg NH3 in kg NH3-N EF5 = 0.0075 (IPCC proposed factor [21]) NO3- = losses of nitrogen in the form of nitrate [kg NO3 ha-1]. They were estimated through the RSB formula [20] which considers nitrogen supply, the nitrogen uptake, the

soil and crop characteristics and the local rainfall. 14/62= conversion of kg NO3- in kg NO3-N. 3.4.7 Land use changes

Direct land used change does not take place because the parcel selected was previously a winter cereal crop land. Indirect land use change is a complex process that is not fully understood by the scientific community and so

is not included in this study [1].

3.5 Life cycle impact assessment Life Cycle Impact Assessment (LCIA) is the phase in

an LCA where the inputs and outputs of elementary flows that have been collected and reported in the inventory are translated into impact indicator results [27].

LCIA is composed of mandatory and optional steps.

Mandatory steps of classification and characterization have been carried out and optional steps normalization and weighting have been avoided in order to make results more comparable and to avoid introducing value choices.

In the classification steps elementary flows shall be assigned to those one or more impact categories to which they contribute. In the characterization steps each quantitative characterization factor shall be assigned to all elementary flows of the inventory for the categories

that have been included in the classification [27]. 3.5.1 Environmental impact assessment method

We have selected the software tool Simapro 7.2 [13] and the impact assessment method of the IPCC 2007 [28] to assess the 100 years time horizon Global Warming Potential (GWP).

3.5.2 Energy assessment method

In order to assess the energy consumed to generate electricity from winter cereal biomass and from natural gas, we have selected the software tool Simapro 7.2 [13] and the Cumulative Energy Requirement Analysis (CERA) [29]. This method aims to investigate the energy use throughout the life cycle of a good or service [29]. The primary fossil energy (FOSE) has been obtained using this method.

4 RYE NITROGEN BALANCE METHODOLOGY

A rough nitrogen balance was made. This estimation considers nitrogen supplied in base and top fertilizations as the entrance of the system and total nitrogen content of rye aerial biomass trials as exit of the system. The total

amount of nitrogen extracted and exported by the crop harvest is calculated by multiplying the yield of each trial (see Table II) by its respective biomass nitrogen content (see Table III). As roots remain into the soil we assumed that all nitrogen from roots return to the soil. Therefore we did not take into account any proportion of root nitrogen content as extracted nitrogen.

5 RESULTS AND DISCUSSION

In the following sub-sections the final results of rye optimization assessments are presented for GWP, fossil energy consumption and balance of nitrogen. Besides we present the contribution of the phases considered in the life cycle assessment of the systems to GWP and fossil energy consumption of the typical management practices

scenario.

5.1 Rye biomass electricity global warming potential The Figure 1 shows that for all the rye managements

there is an inverse relationship between yield obtained and the GWP emissions. The results are contended in the interval that goes from 20 to 75 Mg CO2 eq. TJe-1. This means that every trial produce less GWP than the

generation of electricity from gas natural in Spain, that is about 145 Mg CO2 eq.TJe-1 [18].

0

10

20

30

40

50

60

70

80

3000 5000 7000 9000 11000 13000 15000

GW

P (M

g C

O2 e

q T

J e

lectr

cit

y-1

)

Yield (kg d.m. ha-1)

80 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

80 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

Figure 1: Relationship between global warming potential of rye biomass electricity and whole plant yield

The Figure 2 shows that the GWP savings with respect to natural gas go from 50 % to 85%. We obtained a very high amount of savings for the typical management practices of the site (blue circles), due to the high yields of trials for this management. All the points in

red, corresponding to low sowing doses, have result in worse balances when comparing them with their equivalent management with conventional seed dose (blue points).

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

3000 5000 7000 9000 11000 13000 15000

% G

HG

Sa

vin

gs

(Na

tura

l G

as

as

refe

ren

ce)

Yield (kg d.m. ha-1)

80 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

80 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

Figure 2: Relationship between greenhouse gas emissions savings of rye biomass electricity compared to natural gas and whole plant yield.

5.2 Rye biomass electricity energy assessment The Figure 3 shows that electrical energy obtained is

between two and five times the fossil energy invested. The differences between results for different fertilization doses are lower for the fossil energy consumption than for GWP, because N2O emissions are irrelevant for energy assessments. We have again worse results for lower sowing doses (Red points) compared to typical sowing doses (Blue points).

0.4

0.9

1.4

1.9

2.4

2.9

3.4

3.9

4.4

4.9

5.4

3000 5000 7000 9000 11000 13000 15000

En

erg

y o

utp

ut

per

foss

il e

nerg

y i

np

uts

(TJ

ele

ctr

icty

T

J f

osi

l en

erg

y-1

)

Yield (kg d.m. ha-1)

80 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

80 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

Figure 3: Relationship between electrical energy output per fossil energy inputs of rye biomass and whole plant yield.

5.3 Rye biomass electricity nitrogen balance The Figure 4 shows that there is a trade-off between

emission savings and soil nitrogen deficit. This trade-off is clear for both low and typical sowing doses (24 and 120 kg ha-1). For typical seed doses and zero top fertilization there is an annual loss of 50 kg N in soil nitrogen stocks with 85 % of savings. However with typical sowing and fertilization doses the nitrogen balance is neutral and the savings are lower, about 70 %.

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

-80 -60 -40 -20 0 20 40 60

% G

HG

Sa

vin

gs

(Na

tura

l G

as

as

refe

ren

ce)

Nitrogen Balance (kg N ha-1 year-1)

80 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

80 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

NITROGEN SURPLUSNITROGEN DEFICIT

Figure 4: Relationship between greenhouse gas emissions savings of rye biomass electricity compared to

natural gas and the annual nitrogen balance.

The Figure 5 shows the same previous trade-off between nitrogen deficit and fossil energy consumption, although correlation appears to be less strong for this case. We find more red points generating nitrogen surplus because the crop did not take all the available nitrogen due to the small amount of plants per hectare.

0.4

0.9

1.4

1.9

2.4

2.9

3.4

3.9

4.4

4.9

5.4

-80 -60 -40 -20 0 20 40 60

En

erg

y o

utp

ut

per

foss

il e

nerg

y i

np

uts

(TJ

ele

ctr

icty

T

J f

osi

l en

erg

y-1

)

Nitrogen Balance (kg N ha-1 year-1)

80 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

80 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

30 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 24 Kg ha-1

Seed Dose

0 Kg N ha-1

Top Fertilization

& 120 Kg ha-1

Seed Dose

NITROGEN SURPLUSNITROGEN DEFICIT

Figure 5: Relationship between electrical energy output per fossil energy inputs of rye biomass and the annual nitrogen balance of the soil.

5.4 Relative contributions of the phases considered in the assessment

The Figure 6 shows that for the typical management practices fertilizers and nitrous oxide emissions represent about 75 % of total GWP generated. However the biomass power plant represent only 1.7% of GWP according to our modeling.

GWP; 2,6%

GWP; 46,5%

GWP; 31,8%

GWP; 11,6%

GWP; 5,8%

GWP; 1,7%Seed and Pesticides production &

transport

Fertilizers production & transport

Nitrous Oxide emissions

Field Works (Machinery amortization

and Diesel consumption & combustion

emissions)

Biomass transport to power plant

Biomass Power Plant (Residue disposal

and Natural Gas consumptions &

combustion emissions in maintenances)

Figure 6: Relative contribution of phases to Global Warning Potential (GWP) for the average of the three trials with typical seed doses and top fertilization doses as crop management practices.

The Figure 7 shows that for fossil energy consumption seed and pesticides as well as field works have double their importance with respect to GWP impacts. This happens because emissions do not affect to fossil energy consumption.

FOSE, 3.9%

FOSE, 52.6%FOSE, 25.9%

FOSE, 13.5%

FOSE, 4.1% Seed and Pesticides production &

transport

Fertilizers production & transport

Field Works (Machinery amortization

and Diesel consumption)

Biomass transport to power plant

Biomass Power Plant (Residue disposal

and Natural Gas consumptions in

maintenances)

Figure 7: Relative contribution of phases to Fossil Energy consumption (FOSE) for the average of the three trials with typical seed doses and top fertilization doses as

management practices.

5 CONCLUSIONS

Biomass square bales from rye grown in semiarid regions in Spain may be used in power biomass plants for electricity production and become a real alternative for

the replacement of electricity from natural gas as non renewable fossil reference.

Typical rye top fertilization doses of about 80 kg N ha-1 (NAC 27 %) appear to be sustainable for soil nitrogen stocks and can achieve 70 % of GHG savings when comparing to electricity from natural gas.

Although reduced and zero top fertilization doses (30 and 0 kg N ha-1) produce considerable deficit in soil nitrogen stocks, they can achieve greater GHG savings

(75-85 %). Due to this fact, if we want to obtain higher savings, we need to combine the use of reduced fertilization doses with some soil nitrogen improvement management practices as rotation with legumes, fallow management and no-tillage farming. The use of legumes in crop rotations could improve the soil nitrogen stocks from 80 to 300 kg N fixed per year [30]. The amount of N fixed by different legumes is determined by the

inherent capacity of the crop/rhizobium symbiosis to fix N, modified by the crop’s growing conditions (e.g. soil, climate, disease), crop management and length of time for which the crop is grown [30].

Other optimization in rye might be achieved through: using less emitting fertilizers (e.g. ammonia sulphate) instead of typical nitrogen products used for most farmers in our study region (like NAC 27% and UREA) and

splitting nitrogen fertilizer in two applications in order to increase nitrogen application use efficiency.

The use of lower sowing doses (24 kg ha-1) instead of typical sowing doses (120 kg ha-1) has produced worse results for both GWP and fossil energy consumption. The dose of 24 kg ha-1 appears to be very low and probably we would have obtained better balances with higher doses because with 24 kg ha-1 the number of plants per

ha has been very low to use all the available N. 6 NOTES (1) db: dry basis (2) wb: wet basis

7 REFERENCES [1] García CA, Fuentes A, Hennecke A, Riegelhaupt E,

Manzini F, Masera O. Life-cycle greenhouse gas emissions and energy balances of sugarcane ethanol production in Mexico. Applied Energy 2011;88:2088–97.

[2] Yee KF, Tan KT, Abdullah AZ, Lee KT. Life cycle

assessment of palm biodiesel: Revealing facts and benefits for sustainability. Applied Energy 2009;86, Supplement 1:S189–S196.

[3] Achten WMJ, Almeida J, Fobelets V, Bolle E, Mathijs E, Singh VP, Tewari DN, Verchot LV, Muys B. Life cycle assessment of Jatropha biodiesel as transportation fuel in rural India. Applied Energy 2010;87:3652–60.

[4] Gasol CM, Gabarrell X, Anton A, Rigola M, Carrasco J, Ciria P, Solano ML, Rieradevall J. Life cycle assessment of a Brassica carinata bioenergy

cropping system in southern Europe. Biomass Bioenergy 2007;31:543–55.

[5] Gasol CM, Gabarrell X, Anton A, Rigola M, Carrasco J, Ciria P, Rieradevall J. LCA of poplar bioenergy system compared with Brassica carinata

energy crop and natural gas in regional scenario. Biomass Bioenergy 2009;33:119–29.

[6] Butnar I, Rodrigo J, Gasol CM, Castells F. Life-cycle assessment of electricity from biomass: Case studies of two biocrops in Spain. Biomass and Bioenergy 2010;34:1780–8.

[7] Dworak T, Elbersen B, van Diepen K, Staritsky I, van Kraalingen D, Suppit I, Berglund M, Kaphengst T, Laaser C, Ribeiro M. Assessment of inter-

linkages between bioenergy development and water availability. Ecologic – Institute for International and European Environmental Policy Berlin/Vienna; 2009.

[8] Elsayed MA, Matthews R, Mortinmed ND. Carbon and Energy Balances for a range of biofuels options. Project final report. Project number B/B6/00784/REP. Resource Research Unit,

Sheffield Hallam University and Forest Research. 2003.

[9] Maletta E. A de. V and JC. El potencial de las gramíneas como cultivo energético en España. Vida Rural, Núm. 325. 2011.

[10] Martín C, Maletta E, Ciria P, Santos A, del Val MA, Pérez P, González Y, Lerga P. Energy and enviromental assessment of electricity production

from winter cereals biomass harvested in two locations of Northern Spain. 19th European Biomass Conference & Exhibition:From Research to Industry and Markets, Berlin Germany: 2011.

[11] ISO. 14040:2006. Environmental management-Life cycle assessment-Principles and framework. European Committee for Standardization. 2006.

[12] ISO. 14044:2006. Environmental Management–Life

Cycle Assessment–Requirements and Guidelines. European Committee for Standardization. 2006.

[13] Goedkoop M, De Schryver A, Oele M, Sipke D, De Roest D. Introduction to LCA with SimaPro 7. Netherlands: PRé Consultants; 2010.

[14] Goedkoop M, De Schryver A, Oele M, others. Introduction to LCA with SimaPro 7. PRé Consultants Report 2008;4.

[15] Frischknecht R, Jungbluth N, Althaus HJ, Doka G,

Dones R, Hischier R, Hellweg S, Nemecek T, Rebitzer G, Spielmann M. Overview and Methodology. Final report ecoinvent data v2.0, No. 1. Dübendorf, Switzerland: Swiss Centre for Life Cycle Inventories; 2007.

[16] Frischknecht R, Jungbluth N, Althaus H-J, Doka G, Dones R, Heck T, Hellweg S, Hischier R, Nemecek T, Rebitzer G, Spielmann M. The ecoinvent

Database: Overview and Methodological Framework (7 pp). The International Journal of Life Cycle Assessment 2005;10:3–9.

[17] Nemecek T, Kägi T, Blaser S. Life Cycle Inventories of Agricultural Production Systems. Final report ecoinvent data v2.0, No. 15. Dübendorf, Switzerland: Swiss Centre for Life Cycle Inventories; 2007.

[18] Emmenegger M. F., Heck T, Jungbluth N. Erdgas. In: Sachbilanzen von Energiesystemen: Grundlagen für den ökologischen Vergleich von Energiesystemen und den Einbezug von

Energiesystemen in Ökobilanzen für die Schweiz (ed. Dones R.). Final report ecoinvent data v2.0, No. 6-V. Dübendorf, Switzerland: Swiss Centre for Life Cycle Inventories; 2007.

[19] Spielmann M, Dones R, Bauer C. Life Cycle

Inventories of Transport Services. Final report ecoinvent data v2.0, No. 14. Dübendorf, Switzerland: Swiss Centre for Life Cycle Inventories; 2007.

[20] Faist M, Reinhard J, Zah R. RSB GHG Calculation Methodology v 2.0. Roundtable on Sustainable Biofuels; 2011.

[21] De Klein C, Novoa RSA, Ogle S, Keith A S, Rochette P, Wirth TC. Chapter 11:N2O Emissions

from Mananged soils, and CO2 emissions from Lime and Urea Application. 2006 IPCC guidelines for national greenhouse gas inventories Volume 4: Agriculture, Forestry and Other Land Use, 2006.

[22] Davis J, Haglund C. Life cycle inventory (LCI) of fertilizer production. Fertilizer products used in Sweden and Western Europe (SIK Rep. No. 654). Swedish Institute for Food and Biotechnology,

Gothenburg, Sweden 1999. [23] Sutter J. Life Cycle Inventories of Pesticides. Final

report ecoinvent v2.2. St. Gallen, Switzerland: Swiss Centre for Life Cycle Inventories; 2010.

[24] Narain M, Singh BPN. Energy profile of a seed-processing plant. Applied Energy 1988;30:227–34.

[25] Jungbluth N. Erdöl. In: Sachbilanzen von Energiesystemen: Grundlagen für den ökologischen

Vergleich von Energiesystemen und den Einbezug von Energiesystemen in Ökobilanzen für die Schweiz (ed. Dones R.). Final report ecoinvent data v2.0, No. 6-IV. Dübendorf, Switzerland: Swiss Centre for Life Cycle Inventories; 2007.

[26] SAEFL. Handbuch Offroad-Datenbank. Swiss Agency for the Environment, Forests and Landscape (SAEFL) 2000.

[27] EC-JRC-IES. International Reference Life Cycle Data System (ILCD) Handbook - General guide for Life Cycle Assessment - Provisions and Action Steps. Fisrt edition. Luxembourg: Publications Office of the European Union; 2010.

[28] Althaus H.J., EMPA. IPCC 2007 method in: Implementation of Life Cycle Impact Assessment Methods. Final report ecoinvent v2.2 No. 3. Dübendorf, Switzerland: Swiss Centre for Life

Cycle Inventories; 2010. [29] Jungbluth N, Esu-services, Frischknecht R,

Ecoinvent-Centre, EMPA. Cumulative energy demand method in: Implementation of Life Cycle Impact Assessment Methods. Final report ecoinvent v2.2 No. 3. Dübendorf, Switzerland: Swiss Centre for Life Cycle Inventories; 2010.

[30] Cuttle S, Shepherd M, Goodlass G. A review of

leguminous fertility-building crops, with particular refence to nitrogen fixation and utilisation. Written as part of DEFRA project OF0316 «The development of improved guidance on the use of fertilitybuilding crops in organic farming». Department for Environment, Food and Rural affairs. UK. Internet: http://www. organicsoilfertility. co. uk/reports/index. html 2003.

8 ACKNOWLEDGEMENTS

The authors wish to thank to Dr. Ruth Barro for her collaboration on biomass laboratory analysis.

This work has been developed in the framework of

the Spanish National and Strategic Project `On Cultivos’ co-funded by the Spanish Ministry of Economy and Competitiveness and the European Funds for Regional Development under the dossier PSE-120000-2009-15.

9 LOGO SPACE