ff deliverable 6 4 final - au purepure.au.dk/portal/files/34601282/ff_deliverable_6_4_final.pdf ·...

Project no. 212117 Project acronym: FUTUREFARM Project title: Integration of Farm Management Information Systems to support real‐time

management decisions and compliance of management standards Instrument: Collaborative project Thematic Priority: THEME 2 FOOD, AGRICULTURE AND FISHERIES, AND BIOTECHNOLOGY

Deliverable 6.4: Direct and indirect energy audit in arable crop production and mitigation possibilities

Due date of deliverable: 31/12/2010 Actual submission date:

Start date of project: 1st January 2008 Duration: 36 months

Work package 6: “Influences of robotics and biofuels on economic and energetic efficiencies of farm production” Organization name of lead contractor for this deliverable: AU Oudshoorn, F.W. (AU); Gemtos, F. (GR); Sørensen, C.G. (AU)

Project No. 212177 FutureFarm D.6.4

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Project co‐funded by the European Commission within the Seven Framework Programme (2007‐2013)

Dissemination Level

PU Public X

PP Restricted to other programme participants (including the Commission Services)

RE Restricted to a group specified by the consortium (including the Commission Services)

CO Confidential, only for members of the consortium (including the Commission Services)


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1 INTRODUCTION ...................................................................................................................................... - 4 -

2 ENERGY CONSUMPTION IN DENMARK .......................................................................................... - 5 -

2.1 DIRECT AND INDIRECT ENERGY CONSUMPTION IN ARABLE FARMING IN DENMARK ......................... - 7 - 2.1.1 Direct Energy Consumption. .......................................................................................... - 8 - 2.1.2 Indirect energy consumption ........................................................................................... - 9 -

2.2 ENERGY CONSUMPTION FOR SPECIFIC CROPS AND ROTATIONS. ....................................................... - 11 - 2.3 DISCUSSION ........................................................................................................................................... - 12 -

3 ENERGY CONSUMPTION IN GREECE ............................................................................................. - 13 -

3.1 ENERGY BALANCE FOR GREECE. ANALYSIS FOR TYPICAL CROPS .................................................... - 15 - 3.1.1 Energy inputs estimation............................................................................................... - 16 - 3.1.2 Energy output estimation .............................................................................................. - 21 - 3.1.3 Energy efficiency estimation ........................................................................................ - 21 -

3.2 RESULTS................................................................................................................................................. - 21 - 3.2.1 Rape seed ...................................................................................................................... - 22 - 3.2.2 Sunflower ...................................................................................................................... - 23 - 3.2.3 Sweet sorghum .............................................................................................................. - 25 -

3.3 DISCUSSION ........................................................................................................................................... - 25 -

4 MITIGATION OPTIONS ........................................................................................................................ - 29 -

4.1 DIRECT ENERGY .................................................................................................................................... - 29 - 4.2 INDIRECT ENERGY CONSUMPTION ....................................................................................................... - 32 -

4.2.1 CO2 emissions ............................................................................................................... - 32 - 4.3 MITIGATION OF DIRECT ENERGY BY USE OF ALTERNATIVE ENERGY SOURCES. .............................. - 33 -

5 REFERENCES ......................................................................................................................................... - 33 -


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1 Introduction For the last 10 years, an increasing focus on energy consumption has been experienced. Limited fossil energy supplies for the future and the contribution to climate change have been the main motives to stimulate saving programs and energy conversion programs (change from fossil energy to renewable energy sources). Energy use has become a sustainability indicator, where the sector or production method can be evaluated in order to validate the fundament for sustainability, comprising issues involving the three P’s, people, planet and profit, also defined as social, ecological and economical issues (EES). For example, the government in Denmark has agreed to comply with EU goals of greenhouse gas emissions and fossil energy as major contributor to this source. Energy saving or conversion programs will significantly contribute to the 20% reduction in 2020 compared to 2008 figures of CO2 equivalents. Conversion from fossil energy sources to renewable sources as electricity from wind or solar energy and bio diesel, synthetic diesel or biogas like Hydrogen or Methane are possible options. Agriculture is, as all enterprises invited to contribute proportional, which would mean a reduction or conversion to alternatives which are climate neutral, of 20%. Agriculture as a production sector exists of several quite different components, which can be summarised as follows: I Crop production

A. Arable 1. For human food 2. For biomass 3. For animal feed

B. Horticulture 1. Soil based 2. Greenhouse based

C. Forestry II Livestock production In principle, a reduction of energy use can take place in several ways like mentioned below:

1. Reduced production 2. Higher production with same energy consumption (intensification) 3. Production of energy which can substitute other sectors’ energy consumption 4. Substitution of fossil energy by renewable energy

It is commonly accepted that the present growth in global population in the next many years will require an increased production output for human nutrition. Therefore, a reduction in production is not included in this study. In addition, it is commonly accepted that the source of nutrition when choosing between animal and plant production will have to be re-evaluated, as animal production requires up to 7 times the amount of feeding value and thus energy and land to produce human food. Livestock production is complex and especially the housing and mechanization including heating, ventilation and manure processing but also the construction itself is very energy consuming. However, the main energy source for livestock production is the production, processing and transport of feeding components produced in other countries, before being fed herds (FAO, 2006). This energy component is difficult to manipulate,


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as reduced import will probably not reduce the production, processing or transport abroad. Closing down production in one country will just move the production to another. The effects of the reform of the Common Agricultural Policy (CAP) with its changes in subsidies, cross compliance and the water directive are not yet apparent. As the new CAP for the period 2013-2020 is under negotiation and it seems that at least part of the subsidies will be given under conditions of adoption of certain practices it is worth studying the energy flows in EU agricultural systems. Two typical systems, one for North Europe (Denmark) and one for Southern Europe (Greece) are analyzed to provide an overview of the existing conditions and reveal possible targeted actions to improve the energy efficiency of agriculture. The following report will elucidate the possibilities to reduce energy consumption per unit of arable product on-farm and prior to further processing.

2 Energy consumption in Denmark Denmark will be used as case because it is typical for arable production in Northern Europe. Danish agriculture uses 4.42 % of the total energy consumption in the country as direct energy (Table 1), which is just within the range mentioned by Sauerbeck (2001) as the general percentage for global energy use in agriculture. Dependant on the intensity, it ranges between 3 and 4.5 % of the total energy consumption. So even a reduction of 20% will not influence the national energy levels significantly. Table 1. Agricultures energy consumption delimited by source in DK. Energy source GJ % % of total in DK

Liquefied Petroleum Gas 112,134 0.31 3.97

Petrol 195,318 0.53 25.07

Diesel‐oil 19,366,201 52.83 26.77

Nature Gas 822,374 2.24 1.03

Coal 202,699 0.55 1.87

Electricity 12,689,838 34.62 4.98

Straw 2,939,943 8.02 41.64

Biogas (Methane) 328,283 0.90 37.62

Sum Agriculture 36,656,791 100.00 4.42

Total energy consumption in DK 828,414,518 * Statistics Denmark, 2007. Direct diesel consumption (including fuel for all engine driven activities on the farm) comprises more than 50% of the energy consumption in Agriculture. Electricity consumption stands for the second largest consumption and will typically be used for heating, internal transport, ventilation and service.


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Figure. 1 Diesel consumption in the agricultural sector during the last 10 years, visualized together with the area of cultivated land (ha) and total amount of livestock units (DE) in Denmark The total area of cultivated land in Denmark derived from the EU subsidy statistics is approximately constant whereas the difference from the minimum of 2.64 million ha and the maximum of 2.71 million ha is mainly caused by different categorization of permanent grasslands. Energy efficiency (diesel consumption per ha) for crop production seems unaffected by technology development in the last 10 years (Table 2). Diesel consumption comprises both machinery for cash crop production and on-farm use, but the size of livestock production in Denmark is decreasing (Figure 1), so it can be assumed that energy consumption for heating and feeding of livestock also decreases. This further sustains the conclusion that energy efficiency in the field is decreasing and should be further investigated. Table 2. Diesel consumption in l ha-1 estimated from figures derived from Danish Statistical Institute (DST).

year diesel/ha

2007 196.62006 198.92005 197.02004 192.82003 195.32002 196.22001 191.72000 188.01999 190.11998 177.91997 176.9


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The two main sources of energy used in agriculture are diesel/oil and electricity. The development of the energy consumption the last 10 years can be seen in Figure 2

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

1996 1998 2000 2002 2004 2006 2008

diesel‐oil (GJ) electricity (GJ) total (GJ)

Figure 2. Agricultures total energy consumption (excluding horticulture and forestry), consumption of diesel oil and electricity from 1997-2007 in GJ (109 J)

2.1 Direct and indirect energy consumption in arable farming in Denmark Definitions; Direct energy consumption comprises energy consumed by machinery used for field operations, including preparing and maintenance in the field, irrigation, and harvesting the product including transport to storage. Indirect energy consumption comprises energy consumed to refine oil into diesel, transport and distribution of processed fuel, energy consumed for manufacturing and maintaining (including lubrication) the machines used, production, storage and transport of seeding materials, production, storage and transport of fertilizer (chemical or natural), production, storage waste disposal and transport of chemicals used. Quantification of direct energy usage: Different methods have been used for the quantification of direct energy use. Sørensen and Nielsen (2005) and Nielsen et al. (2004) for instance calculated engine power and efficiency in the different field operations, and compared these results with actually measured fuel consumption. Other authors have used standard fuel use data and compared these with measured use (Dalgaard et al. 2002) and finally some authors have used models including using measured results from prior studies. Obviously, direct energy consumption is dependant on cultivation methods (reduced tillage, controlled traffic farming [CTF]), crops (cereal/root/grass/whole crop harvest) and soil (structure/composition). In this survey, the different results will be presented and discussed.


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Quantification of indirect energy usage: Indirect energy consumption is more difficult to quantify than direct energy because what to include can be discussed. In this survey, the different results found in national and international literature will be presented, and it will be defined define what might be included.

2.1.1 Direct Energy Consumption. The diesel consumption for self-propelled, although tangible, is difficult. During the last 20 years different methods have been used. Indirectly, it can be estimated using the formula:

F = diesel consumption in kg per hour P = Power delivered in kW s = specific diesel consumption in g per kWh m = engine load in % In order to be able to estimate diesel consumption for specific operations, it is necessary to know the duration of an operation, and the machines’ effective power in kW, which usually has to be calibrated. In addition, the engine load has to be measured. For example, it has been measured to be 70% for seeding operations and up to 90% for ploughing or stubble harrowing. Energy consumption is most efficient (effective power per KW) when operating at 70% engine load. Increasing the engine load from 70% to 100% will increase energy consumption per KW by 20% and the same will happen if operating with only 40% of the engine capacity (Dalgaard et al., 2004). In addition, correct tire selection and correct pressure can mean a 13% reduction in energy consumption in the field and 16% reduction for road traffic (Jørgensen et al., 2003). The calculations are dependent on the duration of an operation, which again is dependent of the skilfulness of the driver. Most registrations obtained from diesel consumption are derived from actually measured diesel usage of an operation (Table 3). The problem here is that many parameters influence this consumption for the same operation such as; Parameter Remarks

Tractor power Use of high power tractor for small operations increases consumption

Operational width Larger operational width gives lower consumption per ha

Operational depth Deeper tillage consumes more power

Machine type Shape of teeth or disks influences power consumption

Soil type Clay or sand

Moisture content High moisture increases power consumption This means that the confidence interval for most measurements is quite wide (Table 3).


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Table 3. Diesel consumption for some crop production measures, according to 4 different surveys

Olesen, 2004 Dalgaard, 2002 Nielsen, 2004 Baily, 2003 SI unit

Ploughing 20.5 16‐23 19‐24 32 l ha‐1

Harrowing 7.6 7 5.7‐8.1 l ha‐1

Manure application 0.4 0.6 l t‐1

Sowing (grain / rape) 5.5 3 7.1‐8.4 7.8 l ha‐1

Sowing (maize) 1.8 l ha‐1

Plant of potatoes 3.5 l ha‐1

Chemical application 1.3 1.5 0.7‐1.5 1.4 l ha‐1

Fertilizer application 1.3 2 1.4‐2.3 0.9 l ha‐1

Limestone application 6.7 l ha‐1

Weed harrowing 3.2 2 1.5‐2.4 l ha‐1

Chaff cutter (silage) 0.5 l ha‐1

(Swath) Cutting 3 l ha‐1

Turn‐over, windrow etc. 2.3 l ha‐1

Harvesting > 4 t ha‐1 2.4 l t‐1

Harvesting < 4 t ha‐1 3.8 l t‐1

Harvesting 14 11.1‐17.4 l ha‐1

Harvest transport 0.2 l t‐1

Silage baling/storing 0.5 l t‐1

Straw baling 1.1 2 l t‐1

Straw transport 3.9 l ha‐1

Grain drying (per %) 1.22 l t‐1

Slurry application 5.7‐7.3 l ha‐1

Slurry application 0.3 l t‐1

Heavy disk 24 l ha‐1

diesel consumption

Olesen (et al.), 2004 is based on Biskupek et al. (1997), FAL (2000) and Moerschner (2000). Dalgaard (et al.), 2002 does not cite their source but mention the possibility for great inaccuracy. Nielsen (et al.), 2004 is based on Pick et al.( 1989), which again is based on measurements in 14 European countries and New Zealand. Baily (et al.) 2003 is based on Butterworth and Nix (1983, DLG (1996–1998), Department of Energy (1991), Fluck (1979), Helsel (1987), Leach (1976), Nix (1996), and Swanton et al. (1996).

2.1.2 Indirect energy consumption General. Indirect energy should be related to the crops produced. Some energy consumption sources related to the area cultivated, others to the crops produced and are expressed as per kg of product (dry matter [DM]) or per l of diesel fuel used per ha. Parallel to the direct energy consumption, the confidence interval on data for indirect energy consumption is very wide. Diesel. Energy is expressed in Joule. 1 l diesel weighs 0.863 kg and contains 35.9 MJ of energy. However, in order to use the diesel it has to be mined, pumped up, transported and refined. It has been calculated that this indirect energy consumption adds an additional 5 MJ per l (Refsgaard et al., 2001).


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Lubrication. Most machinery needs oil and lubrication. Energy consumptions are estimated to be between 3.6 and 5.6 MJ per l of diesel used. Machinery. Machinery construction consumes energy, which should be estimated using equipment longevity. In older literature, estimations are based on weight and operational time, newer estimations are based on diesel consumption, as this entity explains usage and weight, and represents energy consumption better (Dalgaard et al., 2002). It is estimated to be 12 MJ per l of diesel. Fertilizer and Lime. When applying artificial fertilizer, the mineral compounds have to be synthesized, packed and transported. Energy consumption is decisively dependant on chemical synthesis, and especially Nitrogen synthesis is energy demanding. The amounts are listed in Table 4. Pesticides (herbicides, fungicides, insecticides). Pesticides are usually based on chemical compounds, which demand energy for synthesis. In agriculture, the consumption is expressed in active agent per ha, and therefore the energy consumption is expressed as MJ per kg active agent. The energy does not comprise destruction of packing, or the cleaning of waste or polluted water reservoirs. The data in Table 5 are an average estimation of used pesticides. Sometimes the indirect energy consumption is cited as formulated agent (the actual compound spread in the field) which is greatly diluted by a factor 10. Table 4. Estimated indirect energy consumption.

Dalgaard, 2002 Refsgaard, 1998 Olesen, 2004 SI unit

Lubrication 3.6 3.6‐5.7 MJ l‐1

Machine construction** 12 MJ l‐1

Irrigation 50 MJ mm‐1

Drying of harvest (per %)* 50 44 MJ t‐1

Mineral Nitrogen (N) 50 38 MJ kg‐1

Mineral Phosphorus (P) 12 0 MJ kg‐1

Mineral Potassium (K) 7 MJ kg‐1

Lime 30 210 MJ t‐1

Chemicals (active agent) 300 MJ kg‐1

* Approximately half of the harvest needs drying of average 4%

** Computed using average lifetime and wear and diesel use Irrigation and drying of the harvest, although here accounted for as indirect, are statistically included in the data of energy consumption required from the DST (Table 2).


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2.2 Energy consumption for specific crops and rotations. Table 5. Energy consumption for growing, harvesting, transporting and drying of spring barley, on sand and clay soil, conventional and organic SPRING BARLEY sand‐irrigated sand‐not irrigated clay

Conv. Org. Conv. Org. Conv. Org.

Yield (kg DM) 5500 4125 4500 3375 5500 4125

% MJ/ha % MJ/ha % MJ/ha % MJ/ha % MJ/ha % MJ/ha

Irrigation 16 1971 23 1971 0

Drying 3 318 3 239 2 246 3 195 3 311 4 239

Slurry application 4 459 2 197 5 459 3 197 4 459 3 197

Manure application 1 62 5 414 1 62 6 414 1 62 6 414

Ploughing, cultivating & seeding 14 1718 17 1472 17 1718 23 1472 17 1718 23 1472

Harvest 4 474 4 355 4 388 4 291 5 474 6 355

Transport 1 96 1 96 1 96 1 96 1 96 1 96

sum liters diesel/ha 142 132 82 74 1 87 1 77

Not accounted for 10 1208 14 1170 12 1208 18 1170 12 1208 18 1170

Sum direct energy 52 6306 70 6047 42 4259 60 3909 43 4414 62 4021

liters diesel/ha 175 168 118 109 123 112

Seed 3 358 5 459 4 358 7 459 4 358 7 459

Fertilizer N 25 3078 30 3078 30 3078

P 1 68 1 68 34

K 1 126 1 126 24

Pesticides 2 218 2 218 2 218

Lime including spreading 1 150 2 150 1 150 2 150 1 150

Machines 16 1936 23 1968 19 1936 30 1968 19 1936 31 1968

Sum indirect energy 48 5934 30 2577 58 5934 40 2577 57 5798 38 2427

liters diesel/ha 165 72 165 72 161 67

Total 100 12240 100 8624 100 10193 100 6486 100 10212 100 6448

liters diesel/ha 341 240 284 181 284 180

MJ/kg 2.23 2.09 2.27 1.92 1.86 1.56

fraction direct/indirect 1.1 2.3 0.7 1.5 0.8 1.7

Updated using: Refsgaard et al., 1998; Olesen et al., 2004 When crops are irrigated, the energy consumption for growing crops increases dramatically, not only in total, but pr. kg product as well (Table 5 and 6). Irrigation accounts for 16% of the total energy consumption in barley and 28 in clover grass. For organic production, this fraction is even bigger. Indirect energy consumption accounts for almost half of the total energy consumption in conventional growing systems, whereas for organic growing systems this is about 10% less due to the lack of use of artificial fertilizers and pesticides which relatively cost a lot of energy. When modelling the data for direct energy consumption and validating the results with registered diesel and electricity (irrigation and drying), it is shown there was an amount of energy used which was not accounted for (Refsgaard et al, 1998). Therefore, this amount is added to the estimation of total energy consumption. For clover grass production, irrigation on sandy soils accounts for a considerable part of the energy. The organic production of clover grass uses significantly less energy (Table 6).


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Table 6. Energy consumption for growing, harvesting, and transporting of clover grass, on sand and clay soil, conventional and organic CLOVER GRASS sand‐irrigated sand‐not irrigated clay

Conv. Org. Conv. Org. Conv. Org.

Yield (SFU) 7100 5900 6000 5100 6900 6100

% MJ/ha % % % % %

Irrigation 28 5824 57 5824

Slurry application 1 148 1 137 1 148 3 137 1 148 3 137

Manure application 0 20 3 288 0 20 7 288 0 20 6 288

Ploughing, cultivating & seeding 5 951 5 525 7 951 12 525 7 951 12 525

Harvest, cut and feed 1 312 3 259 2 264 5 229 2 303 6 268

Harvest silage 8 1710 14 1421 10 1445 30 1253 11 1662 32 1469

Harvest hay 0 78 1 64 0 66 1 57 1 75 1 67

Transport cut and carry 0 80 1 66 0 67 1 58 1 77 2 68

Transport silage 0 71 1 59 0 60 1 52 0 69 1 61

Transport hay 0 10 0 8 0 9 0 7 0 10 0 9

sum liters diesel per ha 256 240 84 72 92 80

Diesel, not accounted for 2 367 2 251 2 345 6 236 3 363 6 255

sum direct energy 46 9571 87 8902 24 3375 67 2842 25 3678 70 3147

liters diesel/ha 266 247 94 79 102 87

Seed 0 65 1 65 0 65 2 94 0 65 2 94

Fertilizer N 41 8550 60 8550 59 8550

P 1 272 2 272 2 272

K 4 828 3 432 2 306

Pesticides 0 72 1 72 0 72

Lime including spreading 1 150 1 150 1 150 4 150 1 150 3 150

Machines 7 1381 11 1134 10 1381 27 1134 10 1381 25 1134

sum indirect energy 54 11318 13 1349 76 10922 33 1378 75 10796 30 1378

liters diesel /ha 2 314.39

Total 100 20889 100 10251 100 14297 100 4220 100 14474 100 4525

MJ/SFU 2.9 1.7 2.4 0.8 2.1 0.7

fraction direct/indirect 0.8 6.6 0.3 2.1 0.3 2.3 Data from Refsgaard et al., 1998. Some data adjusted using newest knowledge 51 % of the yield was harvested, 49% was grazed. Clover grass in conventional system was 2 year ley, in organic was 3 year ley.

2.3 Discussion DST estimations in Table 2 account for a direct energy consumption in Danish agriculture of approximately 200 l diesel per ha. When computing, all area under cultivation is accounted for, including permanent grasslands, fruit and vegetables and green house production. Set aside is not included. To see if this summarized diesel consumption fits with the crop estimated from Table 4 and 5 it is necessary to have information about the relative areas of the crops. In average, 146 l diesel ha-1 can be accounted for in direct diesel consumption (Table 7), this including the approximately 10% which was the missing amount of diesel when comparing registered diesel amounts with modelled diesel use for the known operations. In the farm registrations, there are often found huge variations in diesel use per farm per ha , e.g. Cederber and Flysjö (2004) reported variations between 61 and 145 l diesel per ha fodder crop.


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Table 7. Arable production in Denmark relative to total area used for agriculture and direct energy consumption in 2008 (DST, 2009).

Culture % of total diesel ha‐1

Cereals 56.4 140

Grass and wcs 19.3 153

Permanent grassland 7.1 80

Potatoe/Beets/rapeseed 11.2 206

weighted average 146 wcs= whole crop silage Possible reasons for this variation are among others the machinery on the farm, the way of operating the machinery, the logistics on the farm and the layout and soil structure of the farms. It can be concluded that 54 l diesel ha-1 (200-146) which in total sums up to 144 million l diesel a year, is used for other activities, such as heating up barns, machinery in the animal housing, farm cars etc. In Denmark, there are app. 20,000 full time agricultural enterprises (7000 crop production, 5000 dairy farms, 8000 pig and crop production) and 50,000 part-time enterprises (DL,2009). It can be assumed that most diesel is used on the farms with livestock (13,000). This diesel amount not accounted for at farm level would add to app. 7200 l diesel per year per professional farm. When addressing possible ways to save fossil energy consumption such as diesel, this unspecified amount (25%), should be included. Energy balance: Even though production of feed or food cannot be substituted with energy, it is possible to estimate an energy balance by taking into account an energy value of the produced products. E.g. barley (88% DM) contains 15 MJ/kg. For Danish conditions of growth, the energy balance (direct + indirect energy used/energy produced) can be estimated to a factor six to seven. However, if the objective for crop production would be energy production, other crops and production methods would be selected, not focusing on human consumption quality of feed quality.

3 Energy consumption in Greece Energy consumption in Greece has been increasing from 1971 till 1999 as shown in Figure 3. The energy consumption per sector of the economy is shown in Figure 4 (Dimitroulopoulou et. al.2009). It is clear, that absolute consumption within agriculture was almost stable in the period 1990-2007 (an overall increase of 5.6% for the whole period is noted by Dimitroulopoulou et l. 2009) but as the total energy consumption of the country increased, the agriculture percentage decreased.


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Figure 3. Trends of energy consumption in Greece

Figure 4. Energy consumption per sector of the economy (Source Dimitroulopoulou et al. 2009)


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Figure 5. Energy consumption by sector 1999 (Friends of the Earth ) According to the Friends of Earth, the agricultural sector in 1999 consumed 6% οf the country’s energy (Figure 5). According to YPAN (2009), it is 5% of the total available energy of the country. Table 8 shows the consumption per resource. The high dependence on fossil fuels is clear. Table 8. Energy consumption of Greek agriculture in 1000 of Tones of Oil Equivalent (TOE) (Source: YPAN 2009)

Resource type Consumption TOE

%

Total consumption 1.088 100.00 Total fossil 802 73.71 Diesel fuel 744 68.38 Electric energy 267 24.54 Petrol 29 2.67 Refinery residues 29 2.67 Total RES 19 1.75 Biomass 10 0.92 Geothermal 9 0.83

The Greek agricultural sector employs a lot of activities consuming energy. Ploughing for tillage, high fertilizer applications, high energy consumption for irrigation are some of the characteristics of the sector. High subsidies combined with the mentality of high yielding are the driving forces for these practices.

3.1 Energy balance for Greece. Analysis for typical crops The energy balances of three crops are presented here. All of them are potential energy crops to be used for producing transport fuels. Pimentel (1992) recorded the activities during the growing period and the direct and indirect energy consumption was estimated. Direct energy is the energy consumed in the farm, in the form of energy products, like fuel, lubricants and human labour. Indirect energy is the


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energy consumed outside the farm to produce any input (machinery, chemicals) used in the farm. Any material brought into the farm is considered as “input” while any product sold to the market was added to “output”. Products used in the farm were considered “neutral”.

3.1.1 Energy inputs estimation

3.1.1.1 Machinery inputs

Two tractors were used for the field operations. One 82 kW 4WD tractor to cover the heavy field operations like tillage and transportation and a smaller one 55 kW 2WD to carry out the lighter operations like sowing, spraying, fertilization. Indirect energy was estimated as the energy sequestered to the tractor and the machinery during manufacturing as well as the energy added to them during their estimated life for repairs and maintenance. The total sequestered energy was then divided by the estimated working life of the machinery and the field performance (estimated from the working width, the travel speed and the field efficiency) for each operation (Table 9). The manufacturing energy was estimated as the sum of the energy used in producing the raw materials and the energy for the machine construction. The energy estimated to be used for transportation and handling of the machine is also added at 8.8 MJ/kg (Bowers 1992). The energy used for repair and maintenance during the life of the machine was added. It was estimated as a percentage of the energy spent to produce the machine, using the CRM coefficients (Bowers 1992) (Table 9). For the direct energy, the driver, the fuel consumption and the lubricants had to be added. Human labour energy consumption estimation was rather difficult to estimate. Different literature sources gave different values depending on the boundary of the system used. Fluck (1992) presented a literature analysis of the estimation of human labour from different sources. Values ranged from 1MJ/d (only for muscular energy consumption) to 1450 MJ/d (for life style support). Most researchers agree that human energy is a very small percentage in today’s mechanized agriculture (Hülsbergen et al. 2001) and therefore it was not included in the calculation. Fuel consumption was estimated from direct measurements in the field with the help of instrumentation added to the tractors (Papathanassiou et al. 2002) that included: A dynamometer consisting of two metal Π shaped frames joined together with six loading cells. The

frames were attached between the tractor and the implement and were able to measure the forces developed between the tractor and the implement, in three dimensions.

A torque and rotating velocity measuring device attached to the PTO and used to record the moment and the angular velocity for the PTO powered implements.

A radar to record forward speed of the tractor An analogue-to-digital and a counter cards connected to a laptop were used to record the measured

data.


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Table 9. Indirect energy consumption for field operations

Weight ME(1) cRM(3)

Imple-ment Tractor Total

kg MJ*kg-1 m m*s-1 ha*h-1 hours

Main Tractor 82 kW 4200 86.8 16000 0.49

Secondary Tractor 55 kW 2520 86.8 12000 0.49

Tillage implements

Ploughing 500 52.8 1.2 4.15 0.85 0.42 2000 0.97 66.6 85.6 152.2

Subsoiler 600 52.8 1.8 3.57 0.85 0.55 2000 0.51 48.6 66.3 114.8

Heavy cultivator 370 52.8 2 4.24 0.85 0.72 2000 0.51 22.7 50.2 72.9

Cultivator 320 52.8 2 5.60 0.85 0.95 2000 0.51 14.9 38.1 52.9

Field cultivator 280 51.4 2.3 8.00 0.85 1.56 2000 0.61 8.2 18.5 26.7

Power harrow 720 52.8 2.5 3.83 0.85 0.81 1500 0.59 54.7 44.6 99.3Disc harrow 1050 50.0 3 7.82 0.80 1.88 2000 0.61 25.0 15.5 40.4

Row crop seeder 400 56.9 3 7.10 0.65 0.00 1500 0.43 1.4 1.4 2.8Sprayer 130 56.9 12 10.83 0.65 8.45 1500 0.37 0.9 3.4 4.3

Fertilizer 150 52.8 12 7.50 0.70 6.30 1200 0.49 1.7 4.6 6.3

Stalk chopper 150 52.8 1.2 10.67 0.80 1.02 1500 0.33 7.7 7.7 15.4Sunflower picker 7000 86.8 3.75 4.0 0.65 1.0 2000 0.24 417.8 417.8

years

Pump 18kW 100 84.0 12 0.55 68.1Traveler sprinkler 1039 56.9 20 0.61 199.7Main conveyence pipes 65.27 280.0 20 67.3Drip pipes 5533.33 160.0 10 1018.1

Combine 7700 86.8 5.6 5.0 0.65 1.82 2000 0.24 246.2Sillage harvester 8000 86.8 3.75 8.0 0.65 3 2500 0.24 191.0Round baler 2500 86.8 3.75 8.0 0.65 1.95 1500 0.39 110.6

kg/h hours

Platform 900 52.8 6000 3000 0.80 0.0052 0.0036 0.0088Screw press 45 86.8 17.41 10000 0.55 0.0370 0.0370

(1)ME = Manufacturing energy (Bowers 1992, Batty and Keller 1980)

(2) fe = field efficiency (ASABE D497.4)

(3) cRM = coefficient used to estimate the energy sequestered in repairs and maintenance (Bowers 1992)kg per ha was estimated for the pipelines weight

Indirect Energy

MJ*ha-1fe(2)

Other implements

Field perfor-

mance (fp)

Travel speed

(u)Estimated

Life (LE)Working

width

MJ/kg

Harvesting

Processing

Irrigation equipment

The data were used to estimate the power required and the energy consumed for the operations. The estimation is shown in 10. The pulling force, the moment and the velocities measured were used to estimate the power required for the field operations. The pulling power was transformed to Equivalent PTO power (kW) using corresponding traction coefficients (Kavalaris 2004). Specific fuel consumption (L/kWh) was estimated using the ASABE formula (ASABE 2007)

173738203.091.364.2 XXSFC Where: X is the ratio of the equivalent PTO power required for an operation, to the maximum available from the PTO. An electric PTO dynamometer (Froment XT 200) was used to measure the real maximum PTO power for the two tractors used. Fuel consumption (L/h) was estimated as the product of Specific Fuel Consumption and equivalent PTO power. Dividing the fuel consumption by Field Performance, the Fuel Consumption per unit of area (L/ha) was calculated.

Fuel consumption was converted to energy by using the energy content of the fuel (38.66 MJ/L) and the production and handling energy (9.12 MJ/L), or 47.78 MJ/L (Pimentel 1992), which is equal to 57.57 MJ/kg if the 0.83 t/m3 density is taken into account. Leach (1976) gave a value of the energy content of diesel fuel of 45.6 MJ/kg which was multiplied by 1.134 for the energy sequestered for


- 18 -

extraction, manufacturing and handling giving a total of 51.7 MJ/kg. In the present study, the Pimentel value was used. The consumed energy by lubricants was taken at 4% of the fuel energy Fluck (1992). The sum of fuel and lubricant energy was the total direct energy inputs required for each field operation (Table 10).

3.1.1.2 Consumable goods input

Consumable goods were used in several stages of crop growth. For most of them there were energy sequestered values in the literature. The values and the sources are shown in Table 11. Helsel (1992) estimated the total energy of the N fertilizer at 69.5 GJ/t for production, 2,6 GJ/t for packaging, 4,5 GJ/t for transportation and 1,6 GJ/t for the application. Energy values for pesticides were taken from the literature. A value for prometryne was not found and it was assumed that the price of the herbicide was directly connected to the energy content. Trifluralin was used for the estimates.

3.1.1.3 Energy consumed for product transportation

A specific transport platform was used to transport the products to the store. The pay load was 5,000 kg and weighted 900 kg. The energy sequestered for manufacturing was taken at 52.78 MJ/kg plus 8.8 MJ/kg for transportation and handling (Bowers 1992) giving an initial energy for the platform of 55,422 MJ. For repair and maintenance, a coefficient 0.8 of the initial energy was used or 380,01.6 MJ. Total indirect energy for the platform was 93,423.6 MJ and for the 82 kW tractor 347,980 MJ. Working life of the platform was 3,000 hours and for the tractor 16,000 hours Tsatsarelis (2000). So, the energy per hour was 31.14 MJ/h for the platform and 21.75 MJ/h for the tractor. The average transportation velocity was 20 km/h. For a travelling distance of 5+5 km and a delivery efficiency of 0.6, the travelling time was 0.83 h, the work rate 6t/h and the fixed energy was 0.0052 for the platform, 0.0036 for the tractorand the total 0.0088 MJ/kg of transported material. The direct energy consumption was estimated by considering the value given for trucks by Fluck (1992), 0.0018 MJ / kg km.

3.1.1.4 Energy for irrigation.

Irrigation water in Greece originates from underground reservoirs, pumped from different depths but also from surface waters of rivers or irrigation channels. The pumping plant had the pump and the power unit which was either an electric motor or a diesel engine. The pump was considered made by ferrous material with energy content of 84 MJ/kg (Bowers 1992) and a total weight of 150 kg giving an embodied energy for manufacturing of 12,600 MJ. Transportation and handling energy at 8.8 MJ/kg was added. For repair and maintenance energy estimation, a coefficient of 0.55 was used to give a total indirect energy of 20,850 MJ (Tsatsarelis, 2000). For 12 years of working life and irrigation of 16 ha per year (the pump discharge was 40m3/h and a 10 days cycle was taken into account) the indirect energy was 108.6 MJ/ha. Similar steps were followed to estimate the indirect energy for the electric motor or the diesel engine and the rest of the irrigation equipment (Table 12). Aluminium pipes were used to distribute the water in the field at 73.3 m per ha weighing 0.89 kg/m (Riva and Sissot 1999). The traveller irrigator was composed of ferrous material (700 kg) and polyethylene for the pipe (339 kg). For drip irrigation assuming between row spacing 0.75 m and pipes placed every second row, the total


- 19 -

length of the pipes with emitters was 6667 m/ha. The sequestered energy for the plastic pipes was taken at 160 MJ/kg (Riva and Sissot 1999). Table 10. Direct energy consumption for field operations

pull PTO X(2)

(FTR) (tPTO) (ω) (EaTR) (EaPTO) (cTR) (EeqPTO) (SFC) (FC) (EV)(ΚΝ) (kN*m) (rpm) MJ*ha-1 (L/kWh) (L/ha) MJ*ha-1

Tillage implements

Ploughing 22.7 222.3 0.53 419.5 0.73 0.42 49.21 2,445.5

Subsoiler 28.6 187.0 0.52 359.6 0.80 0.41 41.25 2,049.9

Heavy cultivator 19.6 115.0 0.53 217.1 0.64 0.44 26.71 1,327.4

Cultivator 11.2 65.9 0.53 124.4 0.48 0.51 17.76 882.5

Field cultivator 6.2 31.8 0.43 74.0 0.70 0.43 8.77 435.7

Power harrow 5.9 0.79 557 27.7 204.6 0.49 289.1 0.96 0.42 33.51 1,665.3

Disc harrow 5.9 24.5 0.41 59.9 0.68 0.43 7.16 356.0

Row crop seeder 1.6 0.04 530 8.2 5.8 0.24 6.5 45.65 0.34 0.63 337.0Sprayer 0.03 518 0.7 0.8 0.04 1.12 1.22 60.6Fertilizer 0.08 556 2.7 3.0 0.12 0.95 2.50 124.2Stalk chopper 0.09 551 18.3 20.8 0.13 0.92 5.61 278.8Sunflower picker 14.6 1,116.7

MJ / kgWagon 0.0018* 0.39 28.2Screw press 1.04 3,166.1

(1) Tractive efficiency(2) X = the ratio of equivalent PTO power to that maximum available to the PTO

* MJ/ kg km

Processing

Other implements

Direct energy

MJ*ha-1

PTO equivalent

energyTE(1)

PTO turn.

veloc.

Fuel consum-

ptionDraft force

PTO torque

Specific fuel

consum-ption

Absorbed energy

Table 11. Consumable goods sequestered energy Consumable goods Energy

content MJ/kg

Source

Fertilizers N 78.1 Helsel (1992) P2O5 17 Helsel (1992) K2O 13.7 Helsel (1992)

Seeds Oilseed rape Sunflower Kalivrousis et al. (2002) Sweet Sorghum 59.56 Heichel (1980)

Herbicides Trifluralin 150 Helsel (1992) Prometryne 460 Estimation

The pumping plant was powered by electrical motors or diesel engines. Electrical motors have an efficiency of 90% while diesel engines thermal efficiency is about 25% (Karaosmanoglou et al. 1998).


- 20 -

But the energy sequestered for producing and delivering electricity is much higher than that required for shipping, refining and delivering crude oil. The overall efficiency coefficient for electrical motors was 0.18 and for the diesel engine 0.213 (Karaosmanoglou et al. 1998).

Table 12. Indirect energy inputs for irrigation

PumpElectric

motorDiesel motor

Main conveyence

pipes Drip pipes

Material: SteelSteel - copper Steel Aluminium Polyethylene Steel

Polyethylene

Fixed Energy InputsTube length (m/ha) 73.3 6667Weight (kg) (kg/ha)* 100.00 50.00 840.00 65.26* 553.33* 700.00 339.00Manufacturing energy (MJ/kg) 84.00 122.00 86.77 280.00 160.00 56.90 160.00Transportation energy (MJ/kg) 8.80 8.80 8.80 8.80 8.80R&M coefficient (cRM) 0.55 0.29 0.49 0.22 0.90Total sequestered energy (MJ) 13900 8309 115993 22869 173083Estimated life (year) 12 12 15 20 10Indirect energy inputs (MJ/ha) 68.1 40.7 454.9 67.3 1018.1

20199.7

Traveler sprinkler

8.800.61

67913

The pump discharge was 40m3/h and the required pressure 810.6 kPa for the traveller irrigator with gun sprinkler and 253.3 kPa for the drip irrigation. Using a pump efficiency of 0.76 and water distribution efficiency of 0.75 for the traveller irrigator and 0.91 for the drip irrigation (Karaosmanoglou et al. 1998).the direct energy consumed estimation is given in Table 13.

Table 13. Direct energy inputs for irrigation for four conditions.

Electric motor

Electric motor

Diesel motor

Diesel motor

70 m pumping

depth

1 m pumping

depth

70 m pumping

depth

1 m pumping

depthSprinkler

Total dynamic head (TDH) (kPa) 1497 820 1497 820Pump power (kW) 23.0 12.6 23.0 12.6Actual pumping energy (MJ/m3) 2.07 1.14 2.07 1.14Direct energy inputs (MJ/m3) 11.5 6.3 10.1 5.5

DripTotal dynamic head (TDH) (kPa) 939.8 263.1 939.8 263.1Pump power (kW) 15.1 4.2 15.1 4.2Actual pumping energy (MJ/m3) 1.36 0.38 1.36 0.38Direct energy inputs (MJ/m3) 7.52 2.11 6.63 1.86

3.1.1.5 Harvesting energy

Rape seed and sunflower were harvested with a combine harvester. A silage harvester was used to harvest sweet sorghum. Indirect energy inputs derived from the use of the harvesting machinery were estimated as described earlier (Table 9). Direct energy was estimated by literature data (Leach 1976). For collecting sunflower and rapeseed stalks, a round baler was used. Direct energy consumption was taken from (Leach 1976).


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3.1.1.6 Over all energy consumption

An estimation of the energy consumption of European farms was made based on questionnaires filled out by the farmers. They estimated fuels consumption at 80 L/ha. An estimation based on energy consumption on the farms as direct energy inputs is own in Table 14. The values of Table 14 overestimate the fuels consumption as most farms gave an estimation of 80 L/ha without irrigation. Table 14. Energy consumption for selected crops in L /ha Crop Energy consumption without

irrigation Energy consumption for irrigation from 10 m depth

Cotton 104 267Mays 108 323Sugar beet 152 312Sunflower 105 154Wheat 108 NASource: Laboratory of Farm Mechanisation (2008)

3.1.2 Energy output estimation Rape seed outputs consist of the seed and the stalks. The seed could be processed in the farm to produce oil and the cake by cold pressing. Cold pressing gave at average 32% oil and 68% cake. The energy content of oil was 37.6 MJ/kg and for cake 15 MJ/kg (Riva and Sissot 1999).The plant stalks could be left in the field as manure or harvested as dry biomass. Field measurements gave an average dry stalk/seed ratio of 1.9. The energy content of the stalks was estimated at 18 MJ/kg (Karaosmanoglou et al. 1998). In that case, the energy consumed for stalk bailing with a round baler and for transportation was added to the analysis. Sunflower outputs were also the seed and the stalks. Field measurements gave dry stalk/seed ratio of 1.23. Cold pressing of seed gave at average 33.5% oil and 66.5% cake. The energy content for oil was 36.8 MJ/kg, for cake 15 MJ/kg (Riva and Sissot 1999)] and for the stalks 17.3 MJ/kg (Gemtos 1992) For sweet sorghum the dry matter of the plant stems were considered as the energy output. The energy content was 15.4 MJ/kg (Badger 1999). of dry material.

3.1.3 Energy efficiency estimation Three indices were used for the energy efficiency estimation. The net energy which is the energy output minus the energy input measured in MJ. The energy efficiency coefficient which was obtained by dividing the energy output by the energy input. It is a dimensionless number. The energy productivity which is the energy spent per kg of output measured in kg/MJ.

3.2 Results


- 22 -

3.2.1 Rape seed The average dry seed yield of the two best performing varieties, for 2008 was 1,618 kg/ha. The energy budgets are shown in Table 15. Without the stalks, the net energy was positive and up to 28,596 MJ/ha. When the stalks were taken into account, the net energy was doubled and reached 81,114 MJ/ha. Maximum energy efficiencies were 4.62 without and 10.68 with the stalks. The crop achieved a positive budget even in year 2007 when due to limited rainfalls the yields were extremely low. It was clear that with a better adaptation of the varieties to the Greek conditions and better knowledge of the crop, rapeseed would offer a crop with positive energy balance. Obviously, higher yields should require higher fertiliser inputs but Table 15 shows the potential together with the average (for the two years) input energy consumption. Soil tillage and fertilisation were the most important inputs accounting for 64.5% of the energy consumption while harvesting and transportation accounted for another 15.8%. Table 15. Energy budgets for the rape seed crop experiments.

2006-07 / Gianouli

2007-08 / Kalybakia AVERAGE

2006-07 / Gianouli

2007-08 / Kalybakia AVERAGE

Energy Inputs (MJ/ha)Tillage 3,390 3,390 3,390 3,390 3,390 3,390

Sowing 780 841 810 780 841 810

Fertilization 3,317 2,680 2,998 3,317 2,680 2,998

Pesticide application 809 0 405 809 0 405

Harvest 948 948 948 1,381 1,381 1,381

Transportation 12 32 22 34 86 60

Total 9,257 7,892 8,574 9,711 8,377 9,044

Yield, dry weight (kg/ha)

Seed 583 1,618 1,101 583 1,618 1,101Oil 181 540 354 181 540 354Cake 402 1,078 746 402 1,078 746Stalks 1,246 2,945 2,095

Energy Outputs (MJ/ha)Oil 6,794 20,322 13,325 6,794 20,322 13,325Cake 6,033 16,166 11,193 6,033 16,166 11,193Stalks 22,424 53,003 37,714

Total 12,827 36,488 24,517 35,251 89,491 62,231

Net Energy (MJ/ha) 3,571 28,596 15,943 25,540 81,114 53,186

Energy Efficiency 1.39 4.62 2.86 3.63 10.68 6.88

Energy Productivity (kg/MJ) 0.06 0.21 0.13 0.19 0.54 0.35

Energy budget

without the stalks with the stalks


- 23 -

Sowing9.0%

Tillage37.5%

Transportation0.7%

Harvest15.1%

Fertilization27%

Pesticide application4.5%

Figure 6. Energy input distribution for rape seed in Greece

3.2.2 Sunflower The average yield of the 4 best performing varieties was 3,398 kg/ha. The energy budgets for each experiment are shown in Table 16. Net energy ranged from 4,007 to 78,284 MJ/ha without the stalks and reached 197,059 MJ/ha when the stalks were taken into account. Energy efficiency above 1 was found in all cases. Average value was 1.88 without the stalks and 4.03 with them. The stalks offered considerable amount of energy and it is important to find uses for them to improve the energy balance. Using the stalks, large amounts of nutrients will be removed and should be added by fertilisers. Additional problems of the bare soil from erosion could arise. Cultivation systems should be developed using winter cover crops most probably mixtures of cereals and legumes to protect the soil and add organic matter and nutrients to replace the removed stalks. Figure 7 shows the average energy inputs distribution. The energy input for irrigation was the main input accounting for 54.1% of the total inputs when considering a mean water application of 2,900 m3/ha and an average pumping depth of 56.2 m. The second main input was fertilization with a 25.9% of the total inputs.


- 24 -

Table 16. Energy budgets for the sunflower crop experiments.

Without the stalks With the stalks

2007 / Stef/kio

2007 / Trikala

2008 / Kalybakia

2008 / Vasilika AVERAGE

2007 / Stef/kio

2007 / Trikala

2008 / Kalybakia

2008 / Vasilika AVERAGE

Energy Inputs (MJ/ha)Tillage 5,694 4,326 4,722 3,787 4,722 5,694 4,326 4,722 3,787 4,722

Sowing 595 585 592 614 596 595 585 592 614 596

Fertilization 10,364 10,364 6,501 8,602 10,573 10,364 10,364 6,501 8,602 10,573

Pesticide application 940 459 1,174 1,184 1,115 940 459 1,174 1,184 1,115

Irrigation 25,960 8,635 10,579 32,658 22,058 25,960 8,635 10,579 32,658 22,058

Harvest 1,117 1,117 1,117 1,117 1,117 1,585 1,585 1,585 1,585 1,585

Transportation 43 68 92 70 68 101 160 216 165 161

Total 44,713 25,553 24,776 48,032 40,249 45,240 26,114 25,370 48,596 40,810

Yield, dry weight (kg/ha)

Seed 2,138 3,376 4,576 3,499 3,398 2,138 3,376 4,576 3,499 3,398Oil 763 1,067 1,579 1,127 1,138 763 1,067 1,579 1,127 1,138Cake 1,375 2,310 2,997 2,372 2,259 1,375 2,310 2,997 2,372 2,259Stalks 3,225 5,090 6,900 5,275 5,123

Energy Outputs (MJ/ha)

Oil 28,094 39,264 58,099 41,463 41,885 28,094 39,264 58,099 41,463 41,885Cake 20,625 34,643 44,961 35,586 33,891 20,625 34,643 44,961 35,586 33,891Stalks 55,787 88,065 119,368 91,263 88,621

Total 48,720 73,907 103,061 77,050 75,776 104,507 161,971 222,428 168,313 164,397

Energy budget

Net Energy (MJ/ha) 4,007 48,353 78,284 29,018 35,527 59,267 135,857 197,059 119,717 123,586

Energy Efficiency 1.09 2.89 4.16 1.60 1.88 2.31 6.20 8.77 3.46 4.03

Energy Productivity (kg/MJ) 0.05 0.13 0.18 0.07 0.08 0.12 0.32 0.45 0.18 0.21

Irrigation52.2%

Harvest4.0%

Transportation0.4%

Pesticide application2.8%

Fertilization27.0%

Sowing1.5%

Tillage12.0%

Figure 7. Energy input distribution for sunflower in Greece


- 25 -

3.2.3 Sweet sorghum Sweet sorghum energy analysis is shown in Table 17. Yield was generally high around 32 t/ha of dry matter which led to high net energy of 400,596 – 440,157 MJ/ha. High energy efficiencies of 7.5-10.8 were also found. High sweet sorghum yield were experienced in other Greek experiments CRES (2006). It is important that the plant can be good quality raw material for second generation bio-ethanol production (Christakopoulos et al. 1993). Figure 8 shows the analysis of the energy used for the production. About 67% of the energy was devoted to irrigation by pumping water from an average depth of 53 m and an average application of 5,200 m3/ha. Sweet sorghum required high water depth and pumping from deep reservoirs increased significantly energy inputs. Fertilization was the second important energy input accounting for the 17% of total.

3.3 Discussion The above results are based on field measurements and literature data. However, the literature data present a range of values that can lead to different results. A brief discussion for each case is presented below. Manufacture energy: It is well known that the technological progress affects the energy sequestered to tractor and machinery. Mikkola and Ahokas (2010) agree that in the time of about 20 years from Bowers (1992) calculations, a lot of changes were observed in the farm machinery construction. While energy spent for metal materials was reduced, at the same time a lot of new material like plastics and aluminum with high energy content were added to the modern tractors to achieve lower weight per power output. Mikkola and Ahokas (2010) refer to literature that despite the energy savings in metal production the energy spent in the car industry was not changed due to the new materials added. It is therefore reasonable to accept Bowers (1992) values for the present study. However, a possible change in the manufacture energy would affect the energy balance. A 50% reduction of the values of Bowers (1992) would improve energy efficiency at 0.12, 0.24 and 0.39 for sunflower, rapeseed and sweet sorghum respectively. The energy savings represent 3-4.3% of the total energy inputs to the crops.


- 26 -

Table 17. Energy budgets for the sweet sorghum crop experiments.

2007 / Kalybakia

2007 / Psychico

2008 / Velestino AVERAGE

Energy Inputs (MJ/ha)Tillage 3.985 6.123 5.292 4.558

Sowing 1.296 1.339 1.296 1.310

Fertilization 13.895 6.604 7.925 9.475

Irrigation 18.222 47.794 39.889 37.263

Harvest 406 406 406 406

Transportation 2.846 3.767 2.615 3.076

Total 40.649 66.033 57.423 56.087

Yield, dry weight (kg/ha)Stalks 28.652 32.220 32.310 31.761

Energy Outputs (MJ/ha)Stalks 441.245 496.193 497.580 489.115

Energy Budget

Net Energy (MJ/ha) 400.596 430.160 440.157 433.028

Energy Efficiency 10,86 7,51 8,67 8,72

Energy Productivity (kg/MJ) 0,70 0,49 0,56 0,57

Irrigation67%

Fertilization17%

Transportation5%

Tillage8%

Sowing2%

Harvest1%

Figure 8. Energy input distribution for sweet sorghum in Greece


- 27 -

Repairs and maintenance energy: In the present study the estimation of the repairs and maintenance (R&M) energy was based on Bowers (1992) values. Different sources however are quoting different percentages. In many cases a monetary approach is accepted correlating the energy inputs to the economic cost for R&M. ASABE (2007) suggested for the estimation of the cumulative repair and maintenance economic cost a formula based on the initial value of the machine, the estimated life and two given coefficients. The standard noted that the cost of R&M found by the formula is within 25% of the real. Accepting the R&M cost should give an overestimation of the energy spent. Fluck and Baird (1980) presented two models to estimate the energy consumption for R&M. An Industry Cost Model estimated a mean percentage of 55% of the energy needed for machinery manufacture while a Lifetime Machine Repair Cost Model estimated R&M energy consumption for a series of machinery with an average of 138%. They admitted that the second model was overestimating the real R&M energy use. Bowers (1992) tried to combine the two models by giving a table of R&M energy use for 14 machines with an average of 55%. Mikkola and Ahokas (2010) referred also to the luck of sufficient data for estimating the actual R&M energy consumed. It should be stressed that the R&M cost was directly connected to the machine use. It is a fact that during the working life of a machine there is an initial period of the first year of relatively high R&M costs (covering any damages from transportation and handling), a period of 5 to 6 years of low costs and then the cost is increasing with the use (Mygdakos and Gemtos 1996). The tractor working life of 12,000 or 16,000 hours was a very optimistic assumption. Most probably values even less than 10,000 hours should be taken into account. Using the ASABE formula for 10,000 hours use, the cumulative R&M cost becomes 70% of the initial. It is quite clear that we are far away from the average R&M coefficient of 0.55 that was assumed by Bowers (1992) and taken to the present analysis. In the case presented by Fluck and Baird (1980) with 138% coefficient, the R&M energy would increase energy inputs by 235 to 2834 MJ/ha (for rapeseed and sorghum respectively) representing 3.2 to 5.1% of the total inputs and would decrease the energy efficiency by 0.21 to 0.42s. On the other hand, use of smaller R&M coefficients (27.5% of the manufacture energy) would benefit 90 – 938 MJ/ha, for rapeseed and sweet sorghum respectively, a reduction equal to 1.0 -1.7% of the total energy inputs and would improve efficiency 0.07 - 0.15 units.

Machinery estimated life: The estimated life of machinery and the tractor is another problem in the estimation of energy budgets. (ASABE 2007) and other authors following Tsatsarelis (2000) quoted a working life which was 16,000 and 12,000 hours for 2WD and 4WD tractors respectively and smaller use for the other machinery. In a 1990 study of tractors use in Greece, Gemtos et al. (1998) gave 355.8 h/y use for tractors not used for irrigation but around 924.3 h/y for tractors used for irrigation. Maydenof and Geddy (1993) gave for tractors an yearly use of 580-1130 h/y for Bulgaria, 100-600 h/y for the ex Western Germany regions and 1000-1500 for the ex East Germany regions, 400-500 h/y for France, Holland, Denmark, Austria and Belgium. It is obvious that machinery use vary widely among the countries according to the farm sizes, mechanization intensity, crops e.t.c. Reducing working life to 50% would increase energy inputs by 415 – 3418 MJ/ha (for rapeseed and sorghum respectively), an increase of 4.4-5.7% in the total energy inputs and would decrease efficiency 0.30 – 0.50 units. Consumable goods: Consumable goods energy estimation were also based on literature data which however are limited and also may have changed through the years. For example a lot of efforts have been made to reduce the energy sequestered to the N fertiliser production. The International Fertilizer Association IFA (2010) estimates that a modern factory producing NH3 consumes 28.3 GJ/t of NH3 (equivalent to36.38 GJ/t of N) with the thermodynamic limit at 20GJ/t. Several agricultural practices are


- 28 -

aiming at increasing N efficiency by improving application technology (application with water, variable rate application, use of legumes in the rotations) which could have a positive impact. Reduction of the energy consumed in the industry at 50% resulted in 1,098, 3,980 and 4,515 MJ/ha savings (in rapeseed, sorghum and sunflower respectively and a reduction of 12.2%, 7.1% and 11.1% to the total energy inputs. Energy efficiency was improved by 0.95, 0.67 and 0.50 for the three crops. Savings in the production of pesticides is less as the embodied energy comes mainly from the active ingredients but the industries always tend to improve their efficiencies. Seed for sowing also accounted for a small part of the energy budgets. Irrigation: For sunflower and sweet sorghum, irrigation was the main energy input accounting for 32.7% – 72.4% of the total inputs. The variation was caused by the different water application rates and the pumping depth. Reducing the water application could cause significant energy savings but such a treatment would require experiments to investigate the effect to yields. Different pumping depths which would affect the energy consumption but not the productivity of the crops were analysed. Using surface water instead of pumping from a depth of 100 m, the total energy consumption would be reduced by 44.2% in the sunflower and 53.8% in the sweet sorghum leading to an increase in energy efficiency of 2.57 units in sunflower and 7.57 units in sorghum. Two of the tested crops, rapeseed and sunflower produce oil containing seeds with significant content in oil which can be easily extracted in the farm by cold pressing. The raw oil after some filtering and sedimentation processes can be used as fuel in diesel engines (Hossain and Davies 2010). Ozsezena et al.2009). This option can lead to energy self sufficient farms.

Irrigation - pumping depth

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

0 20 40 60 80 100 120 140

pumping depth (m)

En

erg

y ef

fici

ency

Sunflow er

Sorghum

Figure 9. Effect different pumping depths in the energy efficiency of sunflower and sweet sorghum.


- 29 -

4 Mitigation options Reducing energy consumption in arable production by intensification (producing more per ha with the same or less energy) can be done by reviewing the direct energy entries and the indirect entries.

4.1 Direct energy Irrigation is identified as an energy consuming operation which could be avoided in Denmark but it is the only way to produce most of the crops in Greece. This would deprive a great deal of farmers their income. Especially in Jutland, it is estimated that approximately 500,000 ha can be irrigated (DST, 2008), only in the areas coloured blue (Fig 11). Approximately 17% of this area is grass, and 65% is cereal. Theoretically, an abolition of irrigation could save 1120 TJ which would be 31.126 million litre diesel (11.7 l ha-1 agricultural area in DK).

Fig 11. Coloured areas show where permissions for irrigation are provided. Light blue <1000 ha, blue between 1000 and 5000 ha, dark blue between 5000 and 10000 ha The Institute of Food and Resource Economics (IFRE) has made an analysis of the possibilities and costs for reducing irrigation on 50000 ha. Gross annual losses for stopping irrigation would be 34 million kr. which is ±620 DKr ha-1 (Table 18) (IFRE, 2009). Table 18. Gross economical deficit for not irrigating in some cultures in Denmark. Culture gross deficit

(DKr ha‐1)

Potatoes 12287

Strch potatoes 2725

Maize 1142

Rape seed 979

Grass 401

Winter wheat 346

Weighted average 620


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The estimation is based on fixed costs for irrigation of 1900-2200 DKr. ha-1 and marginal costs of 7.66 DKr. mm-1 (Danish manual for arable practice, 2008). In Greece, irrigation permits the cropping during the hot dry summers. It is clear that pumping water from deep aquifers has a high energy consumption but the high yields of sweet sorghum can compensate for the additional energy input. A problem with pumping from deeper aquifers is the problem of sea water entering the aquifer causing water salinisation and then similar problem for the irrigated fields. It is clear that better use of surface waters can reduce all relevant problems but irrigation will remain important practice for South EU countries. Ploughing and cultivating the soil for drilling and planting seed is another measure which consumes a lot of energy, especially in annual crops (Table 19). When areas are not irrigated, ploughing is the one measure which uses most energy. During the nineties, a great deal of research was focused on reduced soil tillage. Not only because of energy consumption but also the fact that ploughing is time consuming, which makes it expensive and ploughing was seen as an important factor in soil compaction. Research results comparing normal tillage including the plough with reduced tillage, using different kinds of cultivators and direct seeding equipment were presented. Older literature states that reduced tillage can save up to 54% of energy consumption where no ploughing can save up to 71%. A real energy saver is to stop ploughing (Table 19).This can reduce energy consumption with 70%. It should be taken in account that when using this system, one or two extra herbicide sprayings are necessary, including the use of more active agent, which increases the indirect energy consumption (Nielsen et al., 2004). Reduced tillage saves from 22-60% energy, dependant on which machinery is used (Olesen, 2005). Combining cultivation and seeding might be an energy saver but Nielsen et al. (2001) and Sørensen and Nielsen (2005) concluded that even though many new techniques for combined cultivation and seeding have been developed this doesn’t save energy, mainly due to the fact that the tractors have become so much larger. Yet, this does save labour. Experiments comparing harrowing in sandy soils and clay soils showed no difference in energy consumption (Nielsen et al., 2004), however, the depth of cultivation had great influence. Increasing stubble harrowing depth from 5 cm to 15 cm increased fuel consumption with 30% (Nielsen et al., 2004). Ploughing experiments showed increasing fuel consumption with increasing clay content of the soil (Nielsen et al. 2004) e.g. from sand to heavy clay gave an increase of 17%. In addition, disk coulter seed drills of stubble harrows are affected by soil clay content. Table 19. Fuel consumption in practice using different machinery using the same depth Machinery l ha‐1

Plough, harrow 2x, and traditional seed drill 44‐48

Plough and rotary harrow seed drill 42‐53

Plough, Disk coulter seed drill (heavy type) 36‐40

No plough, stubble cultivator 2x, disk coulter seed drill 22‐25

No plough, stubble cultivator 1x, disk coulter seed drill(heavy type) 19‐25

No plough, stubble cultivator 1x, hoe tine seed drill 18‐24

No plough, disk coulter seed drill 12‐14


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Ploughing is the general practise for Greek farmers. Although some reduced tillage applications are used, especially for winter cereals, the applications are very limited. Several experiments showed that in most cases reduced yields are the result of reduced or no tillage practices (Gemtos et al. 2002, Cavalaris and Gemtos 2000). But long term applications were not carried out in field experiments and new technology planting machines were not introduced. It should be tested in the next years to assess the effects of the use of N fertilisers if legumes are introduced in it. The new soil directive is expected, when in force, to enhance conservation tillage in Greece and improve energy balance and efficiency. Field management comprises route planning, logistics, choice of machinery, driving technique, choice of tires and tire pressure, and crop rotation. Soil structure and the compactness of soil is assumingly an important factor influencing draft force needed and thereby energy consumption for all tillage measures, such as ploughing, stubble cultivating, harrowing and hoeing (Table 20). Table 20. Mitigation of energy in primary tillage

Clay content in % Mitigation of energy consumption for primary tillage by zero trafic in %

21,0 % 1323,0 % 1559,5 % 27

(Chamen et.al. 1992) The same effect (reducing energy) can be achieved when implementing soil structure preserving measures such as using the correct dimensions for machinery, tires and their pressure (reduced ground pressure; RGP), controlled traffic farming (CTF) where all operations are carefully planned including timing of work, avoiding unnecessary compaction . Compaction can be measured by power requirement for the tractor or by penetration measurements. Penetration measurements are measured by driving a metal spear vertically through the soil and registering how much power is needed. Chamen & Longstaff (1995) measured 1.51 MPa in conventional traffic systems and 1.24MPa in zero traffic systems, a reduction of 17.9 %. CTF can be organized so most (all) operations can be performed from the same pair of tracks in the field. Modelling of field operations for normal managed cereal crop, showed that after a season with slurry application, more than 60% of the field had been “hit” by direct tire contact (Green, 2006). A slight change in where to begin the next year can result in 100% direct tire compaction in two years. Tire compaction of the soil, if within the tolerable weight/pressure radius, can be corrected by soil tillage. However, if the compaction and destruction of soil structure occurs beneath ploughing depth, restoration of soil structure must be restored by nature (roots, insects, bacteria and earth worms). When soil becomes compact, the resistance by friction between soil and machinery increases causing larger energy consumption. Increased energy consumption is also caused by changing tire-surface interaction. Different literature references suggest potential energy mitigation from 20-70% on soil tillage measures (Green, 2006; Chamen, et.al. 1994; Dickson & Ritchie,1996a). Some individual measures such as shallow cultivation and drilling have increased energy consumption of up to 250% when tillage is


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disrupted by compaction through trafficking (Chamen et al., 1990). Conclusion from different research done with CTF was that a fuel reduction of 25% is estimated as average for all cultivated land. Using correct tires and pressure could save 10-13% energy for slurry application in the field and 14-16% of the energy for driving slurry on the road for transport from tank to field. For loader wagons app. 12% energy was saved in the field and 7% on the road (Jørgensen et al., 2003). In average, this measure is accounting for a mitigation potential of 10%. Best practice is a soft parameter which can be difficult to quantify. Appropriate speed, ploughing depth, choice of tractor power and RPM, cultivation width, tine or coulter dimensions and soil moisture content when operating are estimated to have a mitigation potential of 10-20% (Dalgaard et al., 2004). Energy mitigation by yield increase will be obtained if the energy consumption calculations are made per functional unit, in this case per kg of corn, grass, cereal etc. The reduction of energy use will only have effect if the amount of ha cultivated is reduced, or if the energy consumption is measured as a linear progression together with needed food production increase worldwide. In a survey, on possible crop yield response for zero traffic, yield increase between 16 and 25% have been measured and modelled. There is seen an increase in yield response with increase of clay amount (Green, 2006; Dickens and Richie, 1996b)). A yield increase of 20% will amount to an energy reduction of 20%.

4.2 Indirect energy consumption Possibilities for mitigation of indirect energy consumption (within the boundary of arable production) lie more at a conceptual level. The decision to apply organic practice will be able to save indirect energy pr. ha. mainly because no artificial fertilizer is used (Dalgaard et al., 2004). Local, self sufficiency can reduce indirect energy use for transport (Oudshoorn et al., 2010). However, the energy consumption per kg produced product is often not altered. Alternative tillage methods have been evaluated in terms of resource inputs including indirect and direct energy input. Literature shows that the total energy input in connection with the establishment of plants, fertilizing, plant care and harvest as compared with conventional methods is reduced by 26% for tillage without ploughing and the reduction is 41% for direct seeding. The indirect energy input amounts to an average of 16.2% of the total energy input. There is no consistent information on how much extra indirect energy consumption a direct seeding strategy will provoke. It has been registered that extra pesticides, especially Glyphosat up to extra 350%, are necessary to keep weeds under control (Melander et al., 2010).

4.2.1 CO2 emissions

Reduction of fossil energy is often related to Carbon emissions to the atmosphere. However, climate changing effects are not the sole reason for seeking reduction of energy consumption. The shortage of availability of fossil energy is of great importance and guaranteed production of food for the global population needs crop production and therefore energy savings. However, CO2 emission amounts, sources and mitigation have been investigated for arable farming, in the maelstrom of scientific efforts


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to reduce climate change. The largest contributor to the emission of C02 (56-60%) is caused by the mineralization of the carbon in the soil, while the fertilizer production contributes with 28-33% for the different systems. The usage of machines for tillage and other operations contribute with 5-7% by the direct energy input and only 1-2% by the indirect energy input.

4.3 Mitigation of direct energy by use of alternative energy sources. For guarantee of food production for a global population there is a need for energy, other than fossil, to drive the machines to cultivate and harvest the soil. As agriculture uses little energy compared to other industrial activities and domestic use, alternative fuels for tractor drive have not been prioritized. There are some alternative options:

1. Other fuels for combustion engines 2. Electric engines 3. Other draft options

1. Diesel powered engines best documented efficiency for use is maximum 42% (typical 30%).

Even when boosted with hydrogen, this doesn’t improve much. Pure hydrogen driven engines can obtain an efficiency of maximum 50%. Petrol driven combustion engines have an even lower efficiency, maximum 37.2% (typically 20%). Methane and biodiesel can match the efficiency of petrol. All in all a rather poor result, as it is still not economically profitable and environmentally questionable to generate Hydrogen, Methane, Ethanol or Biodiesel. However, there are alternatives when fossil energy supply dries out. Of these alternatives, the use of hydrogen seems most interesting, as it can be generated by wind turbines, and hydrogen engines have been tested on tractors (New Holland)

2. Electrical engines have the advantage of being very efficient. Up to 80% of the energy can be transformed to driving traction. However, the electricity has to be stored, unless the tractor or gantry is connected by electrical cables. Even though the technology of battery storage is improving by the year, a battery that should be able to deliver 100 MJ would weigh several tonnes. For small vehicles, autonomous observers, sprayers or harrowers, the electrical powered engine is a realistic offer, but would need a total mindset revolution of arable production.

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