EWEA 2011 - Life Cycle Assessment of the Wind Turbines

Life cycle assessment of the wind turbines installed in Spain until 2008Lahuerta, Francisco CENER (Renewable Energy National Centre) C/ Ciudad de la Innovación 7, C.P.: 31621 - Sarriguren – Spain (+34) 948 25 28 00 - [email protected] Saenz, Ernesto CENER (Renewable Energy National Centre) C/ Ciudad de la Innovación 7, C.P.: 31621 - Sarriguren – Spain (+34) 948 25 28 00 - [email protected] ABSTRACT Although wind power generation systems are currently one of the fastest growing industries, the environmental impacts and decommission phase of the wind turbines components is still a matter of controversy. The primary wind turbine components are mainly manufactured with steel, aluminium, copper, concrete and reinforced plastics (composites). Most of these materials are recycled at the end of the wind turbine's service life. However, there are important issues related with the handling of composites waste considering new environmental regulations. In Spain, the installed wind power was around 15.145 MW until 2008. Considering that the service life of a wind turbine is approximately twenty years, this means that Spain faced a composite waste of 151.450 t that would have to be decommissioned in the following years. Here a life cycle analysis (LCA) on wind turbines installed in Spain until 2008 is presented, evaluating different waste scenarios for their composite parts (rotor and nacelle) in order to determine their environmental impact and effect on the energy payback of the whole system. The study concludes that the energy payback can vary up to 30% and environmental impacts, such as marine and fresh water ecotoxicity amongst others, can vary up to a 40%. Moreover, the LCA shows that the main environmental impact contributors during the manufacturing process are the components which require steel, copper and electronic parts. Based on the CO2 intensity and the energy payback results of the LCA global model, wind energy was compared with other renewable energy systems and those of conventional power generation systems. The study shows that wind energy is one of the best ways to mitigate climate change in comparison with other power generation systems, which agrees with the wind energy supporting policies of the last decades. reinforced plastics, renewable energy, electricity generation, CML method. 1 INTRODUCTION The wind industry has been growing at an ever-increasing rate since the early 1990s, with a total capacity of 19.149 MW installed at the end of 2009 and a 12,11% share of the annual electricity demand [1]. Over the last decade there have been some controversies about the government support to the wind sector. However, the wind energy sector has demonstrated its economical feasibility over the years with a cumulative contribution to the GDP of 16.150 million euros until the end of 2009 [1]. Besides economical criteria, it is also important to assess the environmental impacts that the development of wind energy sector brings. In that respect the life cycle analysis (LCA) is a tool to assess the environmental impacts and compare system over others. Currently, most of the wind turbines installed in Spain over the last twenty years are still in operation. Considering that the average wind turbine life span is 20 years, the replacement and dismantling of the existing turbines with new models of wind turbines shall be done in the forthcoming years. The technologies or methods chosen for the waste disposal of the old machines, and in particular the components manufactured with composite materials (mainly blades and nacelles), can change the overall life cycle system results on the LCA of them [2] by modifying the environmental impacts. In fact, the disposal methods for composite materials, which are a matter of controversy today, will be more important in the following years due to an increase in the volumes of waste to manage and on more restrictive regulations [3]. Previous LCAs [2, 4-17] were carried out on individual wind turbines with different purposes. Mutz [2] compares three different scenarios of waste disposal management for a Nordex N60 turbine installed in Gotland, concluding that composite materials shall be recycled. Batumbya [4], Martínez [5, 6], Vestas [7, 8] and Lenzena [9, 10] evaluates a single wind turbines installed in particular positions, where the environmental impacts, the evaluation of the waste scenarios or KEYWORDS life cycle analysis, life cycle assessment, LCA, wind turbine, wind energy farms, composite, The LCA includes the wind turbines installed in Spain until early 2008.000 11. 35. LCA 2 METHODOLOGY The methodology includes two major tasks: to prepare a wind turbines inventory on wind turbines installed in Spain until 2008 and to conduct the LCA based on the wind turbine inventory.2 LIFE CYCLE ANALYSIS. Due to the energy produced by the wind turbines included in this study were obtained using two different methods. Moreover. tower dimensions.178 10. Wind farms re-powering or substitution of damaged blades could not be included. The major questions that LCA answers are the following: 20 27 11. The initial park operation date was taken from the BOE (“Official state gazette”) and these dates were assumed as the starting year of activity for each wind turbine.hout or eutrophication from 0. which includes 151. these reviews provided data for environmental intensities such as: CO2 from 3 to 46. The 15. In this study. and the second one by an empirical forecast based on the data from wind energy electricity production between 1996 and 2008 available from REE (“Spanish electrical network”).05 grPO4eq/kW.450 t 26. and to assess the environmental impact posed by the choice of a waste disposal management method for composite materials through the LCA tool. Thus. In particular. maintenance and civil works heavily impact on the LCA final result. A strong increase on the composite waste is expected from 2019. The LCA is based on CML 2 baseline v2.245 24 25 26 20 20 20 20 20 20 20 20 20 20 20 20 20 Fig.279 21. rotor diameter and type of composite material for the rotor’s blades (epoxy or polyester resins. 1. Considering an average wind turbine lifespan of 20 years. He concluded that external aspects to the wind turbines manufacturing process such as transportation. the wind turbine inventory allowed to forecast the material waste expected for the forthcoming years.4 grCO2eq/kW.000 4.450 t that will be composite material waste (97% from blades and 3% from nacelles). The forecast for composite waste to be managed per year is shown in Fig. 1: Forecast for composite waste of wind turbines installed in Spain until 2008 2.0057 to 0.721 units of installed wind turbines will produce 10. acidification from 0.000 20.138.000 0 14 15 16 17 18 19 20 21 22 23 11.hin/kW. the wind energy environmental impact and its energy balance were compared to other energy technologies to assess their environmental impact and energy return. A wide range of LCAs studies on wind energy were analyzed in Varun [14] and Lund [15] reviews.0194 to 0. each wind turbine is correlated with the wind turbine model manufacturer data. Thus. rotor weight.04 (CML 2007) methodology with normalization "World 1990" in order to avoid subjectivity [18]. in which ranges for energy intensities between 0. Crawford [11] and Tremeac [12] demonstrated that both the size of the turbine and the method of calculation of the produced energy on a particular location can generate wide variations in the final LCA results. The aim of this work is to compare four different composites waste disposal scenarios for all wind turbines installed in continental Spain until early 2008.329 Waste forecast for wind turbines composite parts (nacelle & blades). Schleisner [13] compared the LCA of a wind farm installed onshore to an off-shore wind farm.1152 grSO2eq/kW.013 and 0. a comparison between both modelling systems was presented through the energy balance.981 15.18 software • LCA sensitivity analysis • Model validation after the comparison to literature data • LCA interpretation • Energy balance study and environmental impacts comparison between scenarios.1 WIND 2008 TURBINES INVENTORY UNTIL The wind turbines inventory on machines installed in Spain until 2008 is based on AEE [19] data.112 5.895 21. glass or carbon fibre).915 t of waste (Table 2).hout. in ton Total (since 1998): 151.909 9. the first one based on bibliographic data.hout are refer.000 25.79 kW. various characteristics of each model were extracted from their technical brochures: weight and dimensions of the nacelle.hout.the model sensitivity with the variation of different model parameters are a matter of study. The task sequences were: • Definition of the questions that the LCA have to answer • Process flow definition • System boundaries definition • Impact assessment method definition • LCI (life cycle inventory) data collection • Waste disposal scenarios definition • LCA construction using SimaPro V7. Finally.000 30.000 878 368 486 812 5.487 26. 2.260 . The validity of cutting criteria and assumptions were supported by the sensitivity analysis. Spain).2 System boundaries The LCA boundaries system can be defined in terms of nature. it was considered that for every two wind turbines . 2. 2. geography and time. transport and waste management between a continental and non continental territory. similar data were taken from the available databases. recycling into reinforced PET pellets (bibliographical method [2]) and recycling FIDIMA (method developed by FIDIMA Technological Center. Operation Transport Dismantle Recycling Landfill Incineration Energy Emissions Avoid products Wind 1GW. 1GWh of produced energy was taken as the functional unit. For the LCA study. it was not considered the possible repowering or replacement of the turbines after their decommission. assembly & installation and dismantling of the wind turbine.3 Key assumptions Due to practical limitations for the realization of this LCA. the forecast of the total electric energy to be produced by the studied wind turbines along their life span was 567. In Fig. data was compiled to an attainable level enough to answer the questions of the study. Based on each wind turbine single unit flow chart. Despite the life span of a wind turbine was estimated in 20 years. Due to the inventory only includes units installed in Spain.h of electricity System boundary for a single wind turbine LCA Fig. Four different technologies were evaluated: landfill. • Regarding operation and maintenance. The time range for the study included all wind turbine installed in mainland Spain between 1978 to early 2008.2. the process flow chart for a single wind turbine includes the following stages: production of raw materials. 3).• What is the environmental impact of wind turbines installed in Spain until 2008 based on the described life cycle model? • Comparison of the environmental impact cause by four different composite waste disposal scenarios for wind turbines composites. component manufacturing. incineration. • Comparison between environmental impact of wind turbines with other energy production technologies. the main LCA flow chart is constructed adding input flows (energy and materials) and outputs flows (emissions and produced energy) for each single unit system along its service time (see Fig. In order to reduce the complexity of the inventory data collection. the LCA geographical boundary were considered mainland Spain. Energy Material manufacturing Materials Emissions Transport 2. These stages are limit by the boundary system for a single unit. • The studied wind turbines produced electricity were obtained from REE [21-29].569 GW. 2: Flow chart for a single wind turbine LCA 2.1 Functional unit Components manufacturing Maintenance Transport Transport Wind turbine assembly & installation Due to the main objective of a wind turbine is to generate electricity.h. • The average wind turbine life span was 20 years. which is a common practice in the bibliography [20]. The model of Spanish energy mix (electricity mix / kWh / EN dated 2007 Ecoivent database) was used as energy source and the decommissioning phase was assumed to be done locally. without considering units installed in the Canary and Balear Islands because of the intrinsic differences in process.2.2. the following assumptions or hypotheses were used: • In cases where no sub-components or parts data was found. • The electricity mix data was obtained from SimaPro databases. Fig.4-dichlorobenzene eq or kg1. a detailed study on blades weight and their materials were performed according to each wind turbine model..) Wind 1GWh of electricity CML 2 baseline V2.. the process efficiency and the changes on the materials model along the period of time in study between 1980 and 2028 were not taken into account.3.1 Data collection A wind turbine consists of different type of elements: electronic. 3. each wind turbine were divided in four main components (rotor.3 LIFE CYCLE INVENTORY ANALYSIS..4-DB eq). 31. the system output flows were the total emissions and produced energy by all wind turbines set as is shown in Fig.. foundations and others) and each component in its main subcomponents. according to the literature [33. eutrophication (units gPO 4 eq o gPO4 eq). This method has been widely applied for several wind energy LCAs [2. ratios and processes for each subcomponent are shown in Table 1.. N ∑Materials ∑Emissions i =1. This was because blades have 95% of the composite material of the wind turbine.. Therefore. According with the bibliography [2. 34] the materials.4-DB eq). mechanical and electrical. 12] the impacts categories considered in this work were: abiotic depletion (units kgSb eq). 32] with the purpose of assessing the potential environmental impacts. global warming GWP100 (units kgCO2 eq). .4 Allocation. 3: LCA flow chart showing the wind turbines considered in the study Only for the rotor.one will require substitution of the three blades. processes.5 factor. tower.2. 2. human toxicity (units kg1. N ∑ Energy i =1. acidification 3(units g SO2 eq). ozone layer depletion ODP (units kgCFC-11). fresh water aquatic ecotoxicity (units kg1. The materials. • The work and materials required to connect each wind farm to the electrical network were not considered because of the required resources were considered similar no matter on the energy source [4]. The energy return assessment was carried out calculating the cumulative energy demand (CED) in order to evaluate the total direct and indirect amount of energy consumed throughout the life cycle (see Table 8). terrestrial ecotoxicity (units kg1. energy and transport for these subcomponents were increased by a 1. 2. 2. Based on the bibliography and statistical analysis of experimental data. • The time evolution of the energetic mix. it was necessary to consider the contributions of materials and processes of each wind turbine life cycle based on the process flow shown in Fig. processes and emissions require by each wind turbine..4-DB eq) and photochemical oxidation (units kgethylene eq or kgC2H4 eq).4-DB eq).. marine aquatic ecotoxicity (units kg1. the mass of wind turbine subcomponents (shown in Table 1) was calculated according the equations shown in Table 3. impact categories and impact assessment method Aggregation of the inputs and outputs required for each wind turbine LCA included in the global LCA study time frame Wind turbine|i=1 LCA i=1 Wind turbine|i=2 LCA i=2 (. N Wind turbine|i=N LCA i=N 1980 First wind turbine installation date included in the LCA 1990 2007 Last wind turbine installation date included in the LCA 2027 Year Last wind turbine dismantling date included in the LCA 2. Therefore the required flows of materials. In order to group and to simplify the LCI (see Table 2). thus the rotor is the main impact factor in the comparison between waste scenarios. LCI LCA system boundary Since this study considers wind turbines installed in Spain until early 2008. in such way that the final life cycle comprises the sum of materials. 4-8. i =1.. the drive train and the generator [30]. The material and processes type ratio assigned for each subcomponent were considered the same for all the cases. Hence.. energy and emissions flows that constitute each wind turbine life cycle inventory were accumulated.04 (CML 2007) with normalisation “World 1990” was used in this study. nacelle. 389 No O&M 15.721 812. 7.721 in the 13.103 plant/RER S Vinylester 10.649 1.206 plant/RER S Carbon fibre 1.261 22.130 166·106 832.721 119. 7.721 10. 8] [4. 8] [4. Cu 583 storage/RER S Foundation Concrete 7. Operation and maintenance. Cu Concrete Iron - Nacelle Generator 12.1% nacelle weight base on [4. 8] [4.016 plant/RER S Vinylester 1. LCI.938 prod. 7.517 storage/RER S Vynilester 3.km) (t. 8] [4. During maintenance of the wind turbines. 7.5% nacelle weight base on [4.948 15. 37] Tower Others Tower in tower or nacelle Foundation Energy Transport Subcomponent weight fraction (%) 20 40 40 60 40 60 40 100 60 40 34 63 3 98 1 1 85 8 4 1 2 100 100 100 100 97 3 - References for weight fraction [4.743 15.Component Rotor Subcomponent 3 blades (GF+CF+epoxy) 3 blades (GF+epoxy) 3 blades (GF+ vinylester) Hub Cone Material Carbon fibre Glass fibre Epoxy Glass fibre Epoxy Glass fibre Vinylester Cast iron Glass fibre Vinylester Copper Steel Silica Steel Copper Aluminium Steel Aluminium Copper Vinylester Glass fibre Steel Electronics Oil Lightning. 7. 7.938 storage/RER S Aluminium 1. 7.778·106 Table 2: Wind turbines inventory per component and subcomponent.633 plant/RER S Tower Steel 1.937. the small amount of power consumed during operation was not taken into account.353.721 56.574 552 71·106 142·106 5.076 94. energy and materials were consumed as .165 control units /RER S in tower Electronics Oil 13.456 15.034 prod. 7.281 219. 8] [6] [6] - Uncertainty (%) ±8 ±8 ±8 ±8 ±8 ±8 ±8 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±15 ±5 ±15 ±15 ±15 ±5 ±5 ±25 ±25 Uncertainty model Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Uniform Table 1: Materials distribution & LCI uncertainties by component and subcomponent Compo nent Rotor Sub compo nent Material Weight Process Subcomponent Maintenance TransTransport Weigth Energy port units (MW.103 75. 8] [4.955 plant/RER S Cone Glass fibre 2. mix plant/RER S Copper 12. O&M Hence.386 storage/RER S rator Steel 45.053 589·106 N/A 476·106 4. 37] Nacelle others 54.163 151. 7.597 plant/RER S blades Glass fibre 84.721 435. 8] [4.755 plant/RER S Glass fibre 5.186 plant/RER S Silica 2.148 1. 7. 7.743 lubricating oil /RER S or nacelle Lightning.105 No O&M 15.Copper 24. 8] [4.h) (t.915 12.593 1.799 42.138.896 plant/RER S train Copper 1.721 Included No O&M 15.258.987 plant/RER S Aluminium 25.721 1.721 1. 7. 8] [4. 7.721 process No O&M 15. 8] [4. 7.008.609 332·106 Energy (t) (t) -3 Epoxy 47.h) (t) (MW. 8] [4.4% nacelle weight base on [4.294 No O&M 406. 8] [4.193 15.617 238·106 1. 8] [6] [6] [6] [4.912 plant/RER S Hub Cast iron 138.811 No O&M 15.202.454 plant/RER S Glass fibre 2. 37] Drive train 33. 8] [4.km) 23.665. 8] [4.833 plant/RER S Other 89.344 plant/RER S Nacelle Gene. mix plant/RER S Other Steel 265. 7.219 969 969 15. the operation of a wind turbine requires virtually no resources. 8] [4.152 MG silicon plant/NO S Drive Steel 189.220 Concrete (reinforced) I Total 10. 7.227 47. 7] [7] CENER mass foundations (t ) = 128.0236 Drotor ( m ) masselectronics (kg ) = 102.1 ⋅ Drotor (m) 1. In addition. which is base on the prediction of wind distributions [2. 3 RESULTS AND DISCUSSION The environmental impact caused by wind turbines installed in Spain until 2008 for each waste management scenario was based on the method "CML 2 baseline 2000 v2. 3 recycling and 4 recycling FIDIMA.8 ⋅ Drotor (m) mass oil (kg ) = 15.875 ⋅ Drotor (m) mass nacelle (kg ) = 13. Waste scenarios Table 4 shows the four different waste disposal scenarios that have been considered. due to the big number of turbines considered and their different locations. 4 to 8]. this method use load factors around 30% which is slightly more optimistic. In the particular case of oil and electronics waste management. it was found other method to forecast the energy production of a wind turbine. For the transport modelling was assumed that 32 t trucks were used. 2 incineration. it was assumed the incineration as waste management technology [2]. this method was not suitable to forecast the production of the wind turbines set considered in the study. oil and lightning cable were not considered. The main differences between scenario 3 and 4 are that.0367 Drotor ( m ) CENER CENER [2. In the case of the foundations construction.91 ⋅ 1. 58 mass cone (kg ) = 3. .h) Produced energy forecast (GW.569. 4). In the literature. weather scenario 3 is base on bibliographical data over a theoretical scenario of recycling composites into reinforced PET pellets [2]. the required transport resources derived from the subcomponents assembly or manufacturing of the electronics.8212 when Drotor ≥ 80m [36] mass tower (kg ) = 8. [35] [35] mass hub (kg ) = 0. While energy consumption comes mainly from transportation and maintenance operations. According with NeoEnergy [30] data.85 ⋅ D rotor (m) masslightning (kg ) = 0. one gearbox and one generator. it was considered that due to maintenance reasons a full oil change for each wind turbine was required during its life span [2].h) Installed power capacity (MW) REE data.24 ⋅ Drotor (m) 2 .h) 35000 30000 25000 20000 15000 10000 5000 Year 0 20000 15000 10000 5000 0 1980 1990 2000 2010 2020 2030 Fig. with heat avoided ratios of 31 MJ / kg [42] in the case of electronics and 41. it was assumed that all materials needed for construction were within a radius of less than 60 km.resources. 4: Installed power capacity & produced energy forecast for wind turbines.9542 when Drotor < 80m [36] mass nacelle (kg ) = 0.311 MW. Subcomponent mass equations Ref.h (see Fig. every two wind turbines is required the replacement of three rotor blades.8 MJ / kg [43] in the case of oil. was estimated in 567. Moreover.672 ⋅ Drotor (m) Table 3: Subcomponent mass equations Transport The "t. 30000 25000 Installed power (MW) Produced energy (GW. Produced electricity The total electricity produced by wind turbines set throughout their 20 years life span.km" was assumed as the functional unit for transportation. The energy required for transportation of the subcomponents was estimated according the total mass of each subcomponent and the distance between the major wind turbine component production centre and the wind farms locations [39.3 ⋅ Drotor (m) 2. The energy costs for civil works or for erection machinery were not considered. is has been considered that along the lifetime of the turbines. Commonly. scenarios 3 and 4 might be consider in development. 38]. produced energy (GW. 40]. Each scenario differs from the others just in the composites materials waste management technology: 1 landfill. which implies a load factor of 21%. The accumulated produced energy was based on the electrical wind energy production fed into the grid between 1996 and 2008 according with REE [2129] data.04 / World . Non-composites materials disposal methods included in the LCI were modelled in the same way for the four waste disposal scenarios as is shown in Table 5. While scenario 1 and 2 are the common scenarios at this moment. materials consumption was related with the damaged parts substitution. scenario 4 is based on data of a recycling industrial pilot process developed by FIDMA.53 ⋅ 1.695. Nevertheless. and it represents the transport of one tonne of goods over one kilometre [5. 085 16. as it is shown on the impact categories process contribution chart in Fig. According to the LCA results shown in Fig. Moreover.0344 0.0119 21 2 0. In particular. 6). the comparative analysis showed that scenario 2. 7.2 0.0500 53 Min. 3 and 4 presented lower impact categories than scenario 1.0573 8.0630 10.0057 18 Table 5: Common waste scenario for non composite materials Regarding to the waste scenarios comparison. building. 12-16]. 6 and Table 6: Comparison between results and bibliographical review . Based on published wind energy LCAs [2. “Disposal.0212 30 Max.0116 21 BiblioEnergy CO2 AcidiEutroLoad graphy intensity intensity fication phication factor review kW. 13.hin gCO2eq gSO2eq gPO4eq % /kW. to municipal scenario 2 8. the major impact categories were on fresh water and marine ecotoxicity.hout /kW.4 0. indicates that the four scenarios are comparable between them for all impact categories with a reliability of 100% according to the uncertainty variations declared in Table 1.013 3. 6 and Table 7. [5] Process Recycling cast iron B250 Recycling Coppe Recycling [5] B250 “Recycling ECCS Recycling [5] steel B250” Disposal. However. abiotic depletion. PE/PP products. the main emissions sources are related to subcomponents that required steel.hout 1 0. the comparative uncertainty analysis shown in Fig. The absolute uncertainties are represented by the error bars in Fig. Composite material disposal method Waste scenario 1 Landfill Process Ref.0691 12.0669 11.41] to final disposal/CH S” “Disposal.115 0.hin gCO2eq gSO2eq gPO4eq % /kW.6 0.0 0.hout Mean 0.] incineration/CH S” Waste “Recycling Recycling [2] scenario 3 composites pellets” Waste Recycling Industrial pilot process Exp. SO2 intensity and PO4 intensity. mainly due to the lack of detailed data regarding the electronic components. 5: Waste scenarios comparative uncertainty analysis Waste Energy CO2 AcidiEutroLoad scenaintensity intensity fication phication factor rios kW.049 0. it can be observed that LCA results obtained in this study have values within the range observed in the literature for the following benchmarks: energy intensity. the extent of the different impact contributions varies (see Fig.hout /kW.4 0. 7] Recycling Al B250 Incineration [2] -Incineration [2] -Concrete (inert Landfill [2] to landfill S) Landfill [2] Landfill B250 Fig.0363 0. landfill Recycling [2.hout /kW. 0. copper and electronics subcomponents production. the wind turbine set life cycle processes have potential impact on all the investigated categories.790 46. Eutrophication Acidification Abiotic depletion -100% 1-Landfill >= 4-FIDMA 1-Landfill >= 2-Incineration -50% 0% 50% 100% 1-Landfill >= 3-Recycling Table 4: Composite materials waste scenarios processes Common waste scenario Material Cast iron Copper Steel Silica Aluminium Electronics Oil Concrete Rest materials Processed % 90 95 90 100 90 100 100 100 100 Method Recycling Ref. 46. PET. 6 shows an enhancement on all impact categories in either recycling waste scenarios versus landfill or incineration waste disposal scenarios.2% water. However. acidification and terrestrial ecotoxicity. 0.hout /kW. Table 6 shows a summarized review of the literature. Incineration 0. Fig. [5-7.019 0. 4. 5.7 0. 8-10.hout /kW. and only in the case of the “Human toxicity” and “Acidification” impact categories scenario 1 present lower values than scenario 2.0365 0. and slightly lower impact categories in the case of scenario 2 versus scenario 1.0118 21 3 0. A sensitivity analysis (absolute and comparative) was performed in order to validate the LCA model according the uncertainties declared in Table 1. Terrestrial ecotoxicity Photochemical oxidation Ozone layer depletion (ODP) Marine aquatic ecotoxicity Human toxicity Global warming (GWP100) Fresh water aquatic ecotox. there is a common order of magnitude. slag from Landfill MG silicon production.0287 0.1990".hout /kW. it was observed that despite the overall variation existing in the literature. Extreme case variations of 25% can be observed for the acidification category. Waste [2.0106 21 4 0. scenario 4 FIDIMA developed by FIDIMA presented in Table 7.0 0. CO2 intensity. 8 11.5147 0.0032 0.4224 0.0000011 0.2220 8.0909 0.0033 0.hout kW.4g Sb eq / eq / eq / DB eq / kW.9509 0.0041 0.8485 4105.0189 0.0000008 0.5.0042 0. at regional storage/RER S Copper I Cast iron. 7: Waste scenario 1 impact categories process contributions (shown contributions >5% or <-5%).9 20.0093 2.4 18.7690 5179.0157 0.0000006 0.6981 0.1476 5285.0363 0.0181 0.1743 13. .0164 0.6142 5937.hout kW.0000011 0.0344 0.50% 97. production mix.8805 0.3828 0.0140 5. 1990.9952 0.0118 4.0137 4.0287 0.hout 0.2656 0.7 16.4-DB / g 1.E-03 2.2255 0.50% 97.0033 0.E-03 4.1476 5867.3871 0.50% Waste Mean scenario 4 2.E-03 0.hout 12.0097 4.4 13.0116 3.1080 0.7866 4633.4 16.50% Waste Mean scenario 2 2.9542 3664. at plant/RER S Aluminium ingots B250 Eu Fr G M Te O A H Ph tic dcidifica troph esh walobal w uman t arine azone la otoch rrestr arm oxic qua yer emi ial e eple tion icati ter on aqu ing i tic e dep cal o coto tion atic (GWty coto letio xida xicit eco P10 xicit n (O tion y tox.0085 2.5052 3470.6008 0.6761 5003.2271 4774.6 15.E-03 3.6 18.hout kW.0 15.0028 0.1973 9.0932 0.8938 0.7942 0.7953 0.6142 6554.AcidiEutrowater depletion fication phication aquatic ecotox.5238 0.hout kW. 100% 80% 60% 40% 20% 0% -20% Abio Reinforcing steel.1938 8.2167 Waste scenario Waste Mean scenario 1 2.50% Table 7: LCA impact categories characterisation results for studied waste scenarios & impact categories uncertainty variations.1815 6.hout kW.0000012 0.0640 0.0934 0.0 18.50% 97.04 / World.0000009 0. liquid.8762 0.0000009 0.0784 0.0932 0.0000011 0.E+00 1-Landfill 3-Recycling 2-Incineration 4-Recycling FIDIMA Fig.0023 0.0000014 0.hout kW.1973 10.0042 0.1077 0.0530 0.7472 0.0786 0.5 20. 0) DP) y Fig. at plant/RER S Recycling ECCS steel B250 Glass fibre.0119 4.0518 0. Normalization CML 2 baseline 2000 V2.0139 4.0022 0.2061 10.0037 0.hout kW.9841 0. Fresh Abiotic.0788 0.0347 Ozone Global MarinePhotoHuman layer Terrestrial warming aquatic chemical toxicity depletion ecotoxicity (GWP100) ecotoxicity oxidation (ODP) g 1.0467 0.0000014 0.2220 11.1683 12.0000014 0.0119 0.8895 0.0000009 0.1248 0.3680 4334.1739 13.0365 0.4-DB / DB eq / eq / eq / / kW. at plant/RER S aero Electronics for control units/RER S aero Electricity mix/ES S ECCS steel sheet Copper. at plant/RER S aero Epoxy resin.hout kW. g SO2 g PO4g 1.0018 0.9417 0.0106 3.50% Waste Mean scenario 3 2.4g CFC-11 g C2H4 g CO2 eq g 1.0537 0.50% 97.2724 0.0754 0.0128 3.0097 3. at plant/RER S Aluminium.E-03 1.7 13.1584 10. 6: Normalized LCA impact categories for studied waste scenarios (include sensibility analysis absolute uncertainties deviations).0023 0.7506 0. hout /kW.h) Produced energy base on REE data (MW.569. Moreover the processes with higher environmental impact involves production of steel. scenario 4 (MW.808 35.hout 0. scenario 2 (MW.628 32. “Estudio macroeconómico del impacto del sector eólico en España” Asociación eólica española AEE (2010) 2.hin years /kW. Base on bibliographic methods (load factor 30%) Base on REE data Table 9: Energy indicators Energy technology Payback time years Hydro power Run river hydro power Photovoltaic Biomass (direct wood fire) Biomass (gasification) Oil fired plant Coal-fired plant Coal gasification plant Coal-fired plant with geosequestration Gas combined cycled Nuclear Present study. According to the energy performance indicators shown in Table 9.9 Waste scenario Energy Payback intensity time kW.0630 1.5-7 1. the recycling waste scenario 3 and 4 reduce the payback time a 10% in comparison with the landfill and incineration waste scenarios.h) Cumulative energy demand CED. scenario 3 (MW.0494 0.0669 1. energy payback time and energy yield can be determined to compare different energy technologies. However. Two different methods were considered to determine the produced system energy.99 0.3MW Wind Turbine" Project Report in Life Cycle Assessment (AG2800).38 CO2 intensity gCO2eq /kW. In addition.5-5.hout 4-18 9-18 44-217 400 50 937 1001-1154 n/a* 340 440 3-40 12 *Not available Table 10: Energy technologies vs. The results indicate an improvement between 5% and 10% in both recycling scenarios (3 and 4) impact categories versus the landfill scenario 1 or incineration scenario 2.994. REFERENCES 1.502.15 0.3 2.9 2. Moreover wind energy contribution to global warming is lower than any other energy source considered. according to the absolute and comparative sensitivity analysis it was demonstrated that results from waste management scenarios were comparable. These differences indicate that depending on the calculation method for produced energy.h) Cumulative energy demand CED.6-3. including energy intensity.873 30% 21% (-) Table 8: Cumulative system energy flows (input & outputs) Energy yield kW.2 1-Landfill 14.771. terrestrial ecotoxicity and acidification. depending on the method used for the determination of the produced system energy. despite which method is chosen.1 3. The comparison between different energy technologies indicated that wind power offers the best return rates and lower energy environmental impact categories.90 0.0573 1.752 567.h) Cumulative energy demand CED. Table 10 shows that the payback ratio and the CO2 intensity indicator point out a lower environmental impact of the wind turbines installed in Spain until 2008 in relation with others energy technologies. copper parts and electronic components. it can be observed slight differences on the indicators.5 2-Incineration 15. in the other case an empirical data of the REE to forecast the accumulated produced energy of the system (see ACKNOWLEDGEMENTS The authors express their gratitude to Gobierno de Navarra for their financial support of this work (Project DF 360/2000) and to FIDIMA for their collaboration. 4) was used.0410 0.h) 792. Likewise. a 10% improvement in the payback ratios for recycling scenarios 3 and 4 versus scenarios 1 and 2 was found.0691 1.953.0 3-Recycling 17. Whereas in one case a load factor of 30% was consider based on the bibliography (see Table 6). KTH (2009) .930 37.4 4-FIDIMA 22. scenario 1 (MW. they might appear differences of 15% on the energy balance indicators.96 0.311 15.133 39.34 0.h) Installed power capacity until 2008 (MW) Cumulative energy demand CED. There is evidence that the results can be compared with other LCAs literature results. 4 CONCLUSIONS According to the LCA model. Daniel Mutz. energy balance indicators.0479 0.7-2.9 3-Recycling 24.5 n/a* 1.Load factor Produced energy base on bibliographic method (MW.5 4-FIDIMA 15. In addition. In Table 8 are shown the system inputs and outputs for energy flows based on a 20 years average wind turbine life span.38 0. 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