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Carbon footprint of the nuclear energy using IO-LCA Jorge E. Zafrillaa, María Ángeles Cadarsoa, Fabio Monsalvea y Cristina de la Rúab a Universidad de Castilla-La Mancha, Albacete b Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas E-mail: [email protected] IX Congreso Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 Outline 1. Introduction 2. 2.1. Data 2.2. Methodology 2.3. Scenarios 3. Main results 4. Conclusions IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 1. Introduction Energy Roadmap 2050 establishes an 80-95% GHG reduction by 2050 within the EU. One of the main targets is to turn the electricity sector in a quasi-zero emissions sector. Nuclear power could play an important role in the fulfilling of environmental commitments. But, how clean is nuclear power from an IO-LCA perspective? The main objective is to develop a MRIO-LCA model for a nulcear power plant in Spain under different scenarios analyzing the carbon footprint of the facility IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 1. Introduction Contributions a) The data set and the methodology allow us to estimate the variability and the uncertainties of the analysis via multiple scenarios. SRIO / MRIO / hMRIO-LCA Methodological Construction period Lifetime SCENARIOS Technical Load Factor Political GHG intensities Consumption patterns Financial Uranium prices Financial comparisons IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 1. Introduction Contributions b) The use of the MRIO-LCA model to face the problems related to emissions linked to production processes of imported goods. The case of nuclear power is special because Spain does not have a covering industry behind the nuclear power. It has to import a big amount of inputs in the production process. c) This is the first study of nuclear power carbon footprint in Spain. IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.1. Data The MRIO model is based on WIOD. The technical and sectorial data set is provided by Spanish Nuclear Industry Forum. Ruesga, S.M. (2008). “Análisis económico de un proyecto de ampliación de la producción eléctrica nuclear” Nucler power LCA phases differentiation: 1) Construction/Investment 2) Nuclear Fuel cycle (fuel decommissioning included) 3) Operation & Maintenance (facility dismantle phase is included) IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.1. Data Table 1. Investments function of a nuclear power plant (2450 M€UROS, constant 2009) Years 1 2 3 4 5 6 7 8 Investment activity allowance allowance civil engineering equipments + ce equipments + ce equipments + ce equipments + ce end works + tests Total %/Total M€uros Allowances (7513) 2% 2% 10% 18% 20% 25% 15% 8% 100% 49,00 49,00 245,00 441,00 490,00 612,50 367,50 196,00 2.450,00 49,00 49,00 0,00 0,00 0,00 0,00 0,00 8,17 106,17 EG Civil Buildings Insuaran Mechan EG Electric Enineering and CE ces IMPORTS ical (311) (35500) (452) (66031) (291) 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 163,33 40,83 40,83 0,00 0,00 0,00 114,33 40,83 40,83 0,00 0,00 245,00 114,33 81,67 81,67 40,83 0,00 212,33 40,83 81,67 81,67 36,75 4,08 367,50 40,83 122,50 81,67 32,67 8,17 102,08 4,08 0,00 40,83 0,00 0,00 81,67 477,75 367,50 367,50 110,25 12,25 1.008,58 NOTE: Construction simulation of a 1.000 MW Advance Boiling Water Reactor (ABWR) (similar to the one installed in Cofrentes Nuclear Power Plant) IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.1. Data Table 2: Nuclear Fuel Cycle estimation costs and O&M (€/MWh) (2009 prices) Combustible O&M O&M (replacement) Decommissioning and final disposal Insurances Total %/Total Uranium Enrichment Fabrication 1,925 1,225 0,35 1,925 12,18% 1,225 7,75% 0,35 2,21% Fuel Cycle phase Equipments Own Personnel External Personnel 1,11 2,21 2,59 0,34 0,85 3,50 3,70 3,40 1 0,5 3,5 5,00 4,32 27,32% 3,43 21,70% 4,35 27,51% 0,21 15,81 100,00% Total Operation & Maintenance phase BASELINE SCENARIO: - LIFETIME: 60 years Production = 467.164 GWh (~ 4% of electrcity demand per year). - Load factor assumption = 81,54% Cofrentes NPP production in the last 25 years. - Disscount rate = from 5 to 6% (Ruesga, 2008). IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.1. Data Construction/Investment DFd (FBKF) DFm (FBKF) Operation & Maintenance DFd DFmT 1 Agriculture, Hunting, Forestry and Fishing 2 Mining and Quarrying 899,29 from 3 to 7 8 Coke, Refined Petroleum and Nuclear Fuel from 9 to 12 13 Machinery, Nec 14 Electrical and Optical Equipment from 15 to 17 18 Construction from 19 to 28 28 Financial Intermediation 29 30 Renting of M&Eq and Other Business Activities 31 Public Admin and Defence; Compulsory Social Security from 32 to 35 Total 735,78 367,50 367,50 482,39 521,22 588,00 0,00 12,25 4,98 559,95 605,02 98,10 0,00 106,17 1.441 426,59 426,59 2.032,17 1.009 2.983,45 2.800,05 NOTE: Sectorial structure WIOD (35 sectors). Fuel Cycle phase Table 3: Final demand (domestic and imported) vectors for the whole life cycle. IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.1. Data Figure 1: Spain´s Nuclear Fuel Cycle (IAEA, 2005). Uranium (U3O8) Australia Canada Russia Namibia Niger Portugal South Africa Conversion (UF6) Cameco (CANADA) Comurhex (FRANCE) Convedyn (USA) Minatom (RUSSIA) WH Springfields (UK) Reprocessing BNFL Reactors LWR Enrichment Eurodif (FRANCE) Minatom (RUSSIA) Urenco (GER/NETHERLANDS) USEC Inc. (USA) Fabrication Belgonucléaire (BELGIUM) Framatome ANP (GERMANY) GNF (USA) WH Columbia (USA) WH Springfields (UK) WH Västeräs (SWEDEN) NOTE: Investment phase and rest of O&M distribution between domestic and imported goods comes from WIOD structure. IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.1. Data Table 4: Imported Final Demand by region. DFm (FBKF) RUE Construction/Investment NAFTA China EastAsia BRIIAT RoW DFmT RUE Operation & Maintenance NAFTA China EastAsia BRIIAT RoW 356,13 326,18 216,98 248,22 1 2 899,29 8 735,78 265,24 222,33 559,95 605,02 428,93 372,33 21,09 26,16 2.800,05 1.066 from 3 to 8 from 9 to 12 10 11 12 13 14 from 15 to 17 18 from 19 to 35 Total 482,39 521,22 369,51 320,75 18,17 22,54 39,41 121,79 15,91 26,00 7,93 13,63 31,44 16,50 4,98 4,88 0,00 0,00 0,00 0,01 0,09 1.009 SPAIN 695 41 Rest of UE 161 42 NAFTA 22 48 CHINA 626 EAST ASIA 45,75 141,37 18,47 30,18 187 BRIIAT 49 9,21 15,82 599 36,50 19,16 273 RoW IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.2. Methodology Figure 2: WIOT, aggregation to 7 regions valued in Euros (2009). 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 SPAIN Ad Am Am Am Am Am Am SPAIN RUE NAFTA China EastAsia BRIIAT RoW 1 to 35 RUE Am Ad Am Am Am Am Am 1 to 35 NAFTA Am Am Ad Am Am Am Am 1 to 35 China Am Am Am Ad Am Am Am 1 to 35 EastAsia Am Am Am Am Ad Am Am 1 to 35 BRIIAT Am Am Am Am Am Ad Am 1 to 35 RoW Am Am Am Am Am Am Ad (245x245) x1 A11 2 21 x A 3 31 x A m m1 x A A12 A13 A 22 A 23 A 32 A 33 m2 m3 A A y 1r A1m x 1 r 2r 2 y 2m A x r A 3m x 3 y 3r r A mm x m y mr r Final Demand SPAIN yd ym RUE ym NAFTA ym China ym EastAsia ym BRIIAT ym RoW (245x35) Also expressed in compact form by: x Ax y Through Leontief Inverse [L= (I – A)-1]: x ( I A) 1 y IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.2. Methodology Figure 3: Matrix of emissions coefficients “e” (ktCO2 –eq per million of euros) [WIOD] 1 to 35 SPAIN 1 to 35 RUE 1 to 35 NAFTA 1 to 35 China 1 to 35 EastAsia 1 to 35 BRIIAT 1 to 35 RoW hMRIOLCA 1 to 35 SPAIN eWIOD 1 to 35 RUE 1 to 35 NAFTA 1 to 35 China 1 to 35 EastAsia 1 to 35 BRIIAT 1 to 35 RoW eWIOD e WIOD eWIOD eWIOD eWIOD eWIOD ECO-INVENT data for Mining and Quarrying and Coke, Refined Petroleum and Nuclear Fuel NOTE: Matrix e is combined with ECO-INVENT data for the development of the hybrid MRIO-LCA model IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.2. Methodology Summary of models used: Single Region IO model (SRIO-LCA) ^ Ee SP I AdSP 1 ^ y ^ e d SP I AtSP 1 SP Am I AdSP 1 ^ y d ^ y m where eSP is the Spanish (DTA) Multi-Regional IO model (MRIO-LCA) ^ F e I A 1 ^ y where e is the WIOD emissions coefficients Hybrid Multi-Regional IO model (HMRIO-LCA) L ( I A) 1 ( I A A 2 A3 ...) LD ( I A) LI ( A 2 A3 ...) F * [eˆ * ( I A) eˆ( A2 A3 ...)] yˆ ECO-INVENT emissions coefficients and WIOD emissions coefficients IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 2.3. Scenarios Table 5: Summary of scenarios. Variable Unit Scenario code Variation SRIO-LCA A1 g/CO2 MRIO-LCA A2 Variable hMRIO-LCA (baseline) A3 fast built (5y) -10% B1 5 B. CONSTRUCTION PERIOD years 3 years extension +10% B2 11 6 years extension +20% B3 14 early decommissioning 25Y C1 25 C. LIFETIME years intermediate 40Y F. WORLD CONSUMPTION C2 40 long lifetime 100Y PATTERN C3 100 1980 USA (75%) D1 75% D. LOAD FACTOR % intermediate (85%) D2 85% near-full load D3 95% Paner Plan 2020 E1 -35% E. GHG INTENSITY OF g/CO2 90% renewables scenario E2 PRICE-78% G. URANIUM ECONOMY Coal Decree E3 22,80% A. METHODOLOGICAL APPROACH Unit g/CO2 g/CO2 H. FINANCE COMPARISON g/CO2 I. BEST AND WORST CASE g/CO2 Scenario EU-Fuel Cycle NAFTA-Fuel Cycle BRIIAT-Fuel Cycle EU-O&M China-O&M BRIIAT-O&M RUE-Construction China-Construction BRIIAT-Construction Double price Triple price Report OCDE+IEA Report MIT 2003 Best cases compiled Worst cases compiled code Variation FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3 G1 G2 H1 H2 I1 I2 ----- 100% 200% IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 6: CO2 emissions of nuclear electricity by origin of inputs and life cycle stage (g CO2 –eq /Kwh). Domestic Foreign Total Construction 0,62 2,13 2,75 Graph 1: CO2 –eq emissions of nuclear electricity by origin of inputs and life cycle stage (g CO2/Kwh). Fuel 0,01 13,13 13,14 O&M 0,87 2,94 3,81 Total 1,50 18,20 19,70 IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Graph 2: CO2 –eq emissions of nuclear electricity by region (gCO2 –eq /Kwh intensities). IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Graph 2: hMRIO-LCA Carbon footprint (gCO2 –eq /KWh) by country. 11,08% Rest of World 27,5% BRIIAT East Asia 1,28% 11,21% China 19,86% NAFTA 21,46% Rest of EU 7,6% Spain 0.00% 5.00% 10.00% Construction 15.00% Fuel 20.00% O&M 25.00% 30.00% IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 7: Scenarios results Variable Scenario SRIO-LCA A. METHODOLOGICAL MRIO-LCA APPROACH hMRIO-LCA (baseline) fast built (5y) -10% B. CONSTRUCTION 3 years extension +10% PERIOD 6 years extension +20% early decommissioning 25Y C. LIFETIME intermediate 40Y long lifetime 100Y 1980 USA (75%) D. LOAD FACTOR intermediate (85%) near-full load Paner Plan 2020 E. GHG INTENSITY 90% renewables scenario OF ECONOMY Coal Decree EU-Fuel Cycle NAFTA-Fuel Cycle BRIIAT-Fuel Cycle EU-O&M F. WORLD CONSUMPTION China-O&M PATTERN BRIIAT-O&M RUE-Construction China-Construction BRIIAT-Construction Double price G. URANIUM PRICE Triple price H. FINANCE Report OCDE+IEA COMPARISON Report MIT 2003 Best cases compiled I. BEST AND WORST CASE Worst cases compiled code A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 E1 E2 E3 FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3 G1 G2 H1 H2 I1 I2 Variation 5 11 14 25 40 100 75% 85% 95% -35% -78% 22,80% ----- 100% 200% Emissions Emissions Fuel EmissionsO&M Total Emissions Sensitivity Construction (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) (total/baseline) (gCO2eq/kWh) 1,47 3,81 2,02 7,30 -62,97% 2,69 6,86 3,73 13,28 -32,57% 2,75 13,14 3,81 19,70 ----2,22 13,14 3,81 19,17 -2,67% 2,71 13,14 3,81 19,67 -0,16% 2,96 13,14 3,81 19,91 1,09% 6,59 13,14 3,81 23,54 19,51% 4,12 13,14 3,81 21,07 6,97% 1,65 13,14 3,81 18,60 -5,57% 2,98 13,14 3,81 19,94 1,21% 2,63 13,14 3,81 19,59 -0,57% 2,36 13,14 3,81 19,31 -1,97% 2,69 13,14 3,70 19,54 -0,82% 2,62 13,14 3,57 19,33 -1,85% 2,78 13,14 3,88 19,80 0,54% 2,75 12,94 3,81 19,49 -1,05% 2,75 12,72 3,81 19,27 -2,17% 2,75 13,75 3,81 20,30 3,07% 2,75 13,14 2,99 18,88 -4,14% 2,75 13,14 7,35 23,24 17,97% 2,75 13,14 5,53 21,41 8,71% 2,11 13,14 3,81 19,07 -3,20% 5,50 13,14 3,81 22,45 13,99% 4,08 13,14 3,81 21,03 6,78% 2,75 16,49 3,81 23,04 16,98% 2,75 19,83 3,81 26,39 33,97% 2,76 13,84 4,01 20,62 4,66% 3,22 46,23 13,40 62,86 219,12% 1,91 3,35 3,81 9,06 -54,00% 7,72 62,45 13,40 83,58 324,28% IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 7 (excerpt): Methodological scenarios. Variable Unit Emissions Sensitivity Emissions Fuel EmissionsO&M Total Emissions code Variation Construction (total/basel (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) ine) Scenario SRIO-LCA A. METHODOLOGICAL g/CO2 MRIO-LCA APPROACH hMRIO-LCA (baseline) A1 A2 A3 1,47 2,69 2,75 Comparison with other studies. 3,81 6,86 13,14 2,02 3,73 3,81 7,30 13,28 19,70 -62,97% -32,57% ----- Comparison with other technologies. Survey: SOVACOOL, 2008 Paper: BARNABY AND KEMP, 2007 Survey: SOVACOOL, 2008 Frontend (Fuel) Construction O & M (Fuel) Backend Deommissioning TOTAL Estimated (gCO2/Kwh) 25.09 8.2 11.58 9.29 12.01 66.08 % 37.97% 12.41% 17.52% 13.92% 18.17% 100.00% OECD ISA (Aus) Extern-E (UK) Estimated (gCO2/Kwh) 25.09 8.2 11.58 2.5 Mw 1.5 MW 3.1 MW 80 MW Various Estimated (gCO2/Kwh) 9 10 10 13 14-31 1000 MW 19.7 80 MW Various Various Various 38 443 778 960-1050 Capacity Wind offshore Wind onshore Hydro Solar Thermal Biomass NUCLEAR (hMRIO-LCA) Geothermal Natural Gas Diesel Coal IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 7 (excerpt): Construction phase, Load factor and GHG intensities scenarios. Variable B. CONSTRUCTION PERIOD D. LOAD FACTOR E. GHG INTENSITY OF ECONOMY Unit Scenario fast built (5y) -10% years 3 years extension +10% 6 years extension +20% 1980 USA (75%) % intermediate (85%) near-full load Paner Plan 2020 g/CO2 90% renewables scenario Coal Decree code Variation B1 B2 B3 D1 D2 D3 E1 E2 E3 5 11 14 75% 85% 95% -35% -78% 22,80% Emissions Sensitivity Emissions Fuel EmissionsO&M Total Emissions Construction (total/basel (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) ine) 2,22 2,71 2,96 2,98 2,63 2,36 2,69 2,62 2,78 13,14 13,14 13,14 13,14 13,14 13,14 13,14 13,14 13,14 3,81 3,81 3,81 3,81 3,81 3,81 3,70 3,57 3,88 19,17 19,67 19,91 19,94 19,59 19,31 19,54 19,33 19,80 MAIN IDEAS: B and D There are not big impacts over Carbon Footprint about uncertainties related to the lenght of construction phase and to Load factor operation. E As Spain main emissions are produced outside Spain (internationalized nuclear industry) changes in domestic energy mix has not too much impact over Carbon Footprint. -2,67% -0,16% 1,09% 1,21% -0,57% -1,97% -0,82% -1,85% 0,54% IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 7 (excerpt): Lifetime scenarios. Variable C. LIFETIME Unit Scenario years early decommissioning 25Y intermediate 40Y long lifetime 100Y Emissions Sensitivity Emissions Fuel EmissionsO&M Total Emissions code Variation Construction (total/basel (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) ine) C1 C2 C3 25 40 100 6,59 4,12 1,65 13,14 13,14 13,14 3,81 3,81 3,81 23,54 21,07 18,60 MAIN IDEAS: • Early decommissioning scenarios, related to new and unexpected energy policies (like the shutdown of nuclear energy generation in Germany after Fukushima) would generate an increase on emissions by almost 20%. • 40 years lifetime generates similar results. • 100 years of operation do not reduce too much the amount of emissions. The less lifetime the more emissions in construction phase 19,51% 6,97% -5,57% IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 7 (excerpt): World consumption patterns scenarios. Variable F. WORLD CONSUMPTION PATTERN Unit Scenario EU-Fuel Cycle NAFTA-Fuel Cycle BRIIAT-Fuel Cycle EU-O&M g/CO2 China-O&M BRIIAT-O&M RUE-Construction China-Construction BRIIAT-Construction code Variation FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3 ----- Emissions Sensitivity Emissions Fuel EmissionsO&M Total Emissions Construction (total/basel (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) ine) 2,75 2,75 2,75 2,75 2,75 2,75 2,11 5,50 4,08 12,94 12,72 13,75 13,14 13,14 13,14 13,14 13,14 13,14 3,81 3,81 3,81 2,99 7,35 5,53 3,81 3,81 3,81 19,49 19,27 20,30 18,88 23,24 21,41 19,07 22,45 21,03 -1,05% -2,17% 3,07% -4,14% 17,97% 8,71% -3,20% 13,99% 6,78% MAIN IDEAS: • Changes in consumption patterns of some phases are relevant. • Fuel Cycle is a high pollutant phase, differences between patterns are not too different to Baseline. • O&M If China-Spain trade relationships would be higher and higher, total Carbon Footprint would be almost a 18% higher. • Construction If the amount of Chinese construction phase inputs would be higher, Carbon Footprint almost 14%. • All the scenarios show a reduction of the Carbon Footpint if EU produce the inputs. REASON: The cleaner energy mix. IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 3. Main Results Table 7 (excerpt): Uranium prices, Financial comparison and Bests and Worts scenarios. Variable G. URANIUM PRICE H. FINANCE COMPARISON I. BEST AND WORST CASE Unit Scenario Double price Triple price Report OCDE+IEA g/CO2 Report MIT 2003 Best cases compiled g/CO2 Worst cases compiled g/CO2 Emissions Sensitivity Emissions Fuel EmissionsO&M Total Emissions code Variation Construction (total/basel (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) (gCO2eq/kWh) ine) G1 G2 H1 H2 I1 I2 100% 200% 2,75 2,75 2,76 3,22 1,91 7,72 16,49 19,83 13,84 46,23 3,35 62,45 3,81 3,81 4,01 13,40 3,81 13,40 23,04 26,39 20,62 62,86 9,06 83,58 16,98% 33,97% 4,66% 219,12% -54,00% 324,28% MAIN IDEAS: • The scarcity of Uranium in the world, and the subsequent increase of prices related to the exploit of new mining deposists would increase the Carbon Footprint a 34% (x3) and a 17% (x2). • • If we use financial data from OECD and IEA report, Carbon Footprint woul be similar. If we use the MIT 2003 report data, Carbon Footprint would be a 220% higher (closer to fossil fuels). • Adding best and worst scenarios, the interval of emissions depending on the uncertainties considered goes from 9 gCO2/kWh to 83,58 gCO2/Kwh (Fuel Cycle highest responsability). o Taking into consideration the variability and uncertainties is crucial to estimate nuclear power Carbon Footprint properly. IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 4. Conclusions The Hybrid MRIO-LCA is the most accurate model to evaluate the Nuclear Power plant Carbon Footprint. The use of the MRIO model allow to enhance the role of imports in a Spanish Nuclear Power plant life cycle (almost 90%), concentrated in the Fuel Cycle phase. Nuclear Spanish industry was dismantled because of the nuclear moratorium since eighties. The consideration of uncertainties and variability is crucial. Most of the studies presents very different results depending on the variables and assumptions considered. IX Congreso de la Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014 4. Conclusions Low Carbon Footprint compared to other technologies. Uncertainties captured by the multiple scenarios simulated. Results are coherent with other reference studies. Fuel cycle is the most pollutant phase. Most of emissions are produced in BRIIAT. The scenarios with a higher influence over emissions are: METHOLODGY LIFETIME CONSUMPTION PATTERNS URANIUM PRICES FINANCIAL DATA SETS BEST CASE: 9,06 gCO2 –eq /kWh Baseline 19,70 gCO2 –eq /kWh WORST CASE: 83,58 gCO2 –eq /kWh THANKS FOR YOUR ATTENTION! Carbon footprint of the nuclear energy using IO-LCA Jorge E. Zafrillaa, María Ángeles Cadarsoa, Fabio Monsalvea y Cristina de la Rúab a b Universidad de Castilla-La Mancha, Albacete Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas E-mail: [email protected] IX Congreso Asociación Española para la Economía Energética Madrid, 3 y 4 de febrero de 2014