Regionalization and parameterization of LCA and LCIA of energy systems

Transcription

1 39 th Discussion Forum on Life Cycle Assessment, ETH Zürich Regionalization and parameterization of LCA and LCIA of energy systems Thomas Heck Paul Scherrer Institut, Switzerland Nov 13, 2009 Heck, ETHZ,

2 Contents Space-dependent impact pathway approach including LCA (Life Cycle Assessment) Parameterization concept for LCA and LCIA (Life Cycle Impact Assessment) Space-dependent environmental impact modeling Examples for space-dependent impacts Examples for site-specific impact assessment including LCA (aggregation: external costs) Conclusions

3 Space-dependent impact pathway approach including LCA Emissions Emissions from operating plant Emissions from rest of chain Dispersion, Physical & Chemical Reactions E.g. change of pollutant concentrations, etc.. Impacts Impacts on human health, crop yields, buildings, land, ecosystems,... Aggregation / Valuation External Costs, cost indicators, ecoindicator... Life Cycle Assessment Other flows: Land use Resource use

4 Current structure of ecoinvent database for LCA researchers / data suppliers input process (m x m) cumulative process (m x m) elementary flow (n x m) cumulative LCI results (n x m) LCIA methods (r x n) cumulative LCIA results (r x m) end users m 4000, n 1000, r 200 (as of year 2009) Elementary flows = emissions, land use, resource use Source: Heck et al. 2009

5 Proposed structure of parameterized LCA system researchers / data suppliers input process (m x m) cumulative process (m x m) elementary flow (n x m) cumulative LCI results (n x m) LCIA methods (r x n) cumulative LCIA results (r x m) end users Parameters: indep. p p(a,t) p(a,t,x) GIS t = time, x = space, a = technology/other. GIS = Geographical Information System Source: Heck et al. 2009

6 Three dimensions of parameterization: Laboratory for Energy Systems Analysis Regionalization/space-dependency embedded in general parameterization concept Net electric efficiency, CHP 200kW (%) Very optimistic Optimistic-realistic Pessimistic Year t (time) a (technology/other) Parameterization concept, see: x (space) focus in this presentation T. Heck, C. Bauer, and R. Dones (2009). Development of parameterisation methods to derive transferable life cycle inventories - Technical guideline on parameterisation of life cycle inventory data. Report RS1a D4.1, NEEDS (New Energy Externalities Developments for Sustainability). European Commission. (

7 EcoSense model (Europe) for impact + EC assessment developed at IER Stuttgart, EU project ExternE Emission data needed for: Air quality model + ISC local 10km x 10km + SROM regional ozone model WTM air quality modelling domain WTM Windrose Trajectory Model Impact assessment modelling domain E(PM) E(PM) E(NO) E(NO) E(NH E(NH 3 ) 3 ) E(SO E(SO 2 ) 2 ) Emission+Transport Grid about 50km x 50km Emissions: PM (Particulate Matter), SO2, NOx, NH3, CO, organic compounds, heavy metals EC = External Costs PM PM O 3 O 3 NO NO NO NO 2 2 hν OH HNO HNO 3 3 aerosol NA NA NH 4 NO NH4 NO 3 3 Secondary hazardous pollutants are formed: Nitrates NH NH 3 3 OH H H 2 SO 2 SO 4 SO 2 4 SO2 H 2 O 2 (NH (NH 4 ) 2 SO 4 ) 2 SO 4 4 Sulfates Reaction Dry deposition Wet deposition (Trukenmüller 2001) PM = Particulate Matter NA = Non-specific Nitrate Aerosol Adopted from Derwent 1988

8 EcoSense Model, Multi-Source Versions (derived from ExternE) Europe Russia/Eastern Europe Brazil/ South America China/ Asia (IER+PSI) EcoSense multi-source versions developed at IER Stuttgart (Heck et al.)

9 Mortality due to Air Pollution Jinan (China) Coal Power Plant 1000 km radius Single-source calculation Source: Heck 2007 Coupling to LCA: Rest of chain has to be added (minor contribution in this case)

10 Mortality impacts due to Air Pollution from China Multi-source calculations Emissions from Power Sector Emissions from all Sectors India 100 Myanmar (Burma) Thailand Mongolia Laos China 110 Macau Paracel Islands 120 Taiwan Philippines North Korea East China Sea 130 South Korea Sea of Japan Japan 140 Mortality due to Air Emissions from China's Power Sector (Current situation) Years of Life Lost per yr per grid cell < > 8000 Administrative Units Rivers India 100 Myanmar (Burma) Thailand Mongolia Laos China 110 Macau Paracel Islands 120 Taiwan Philippines East China Sea 130 North Korea South Korea Sea of Japan Japan Mortality due to China's Air Emissions, All Sectors (Current situation) Years of Life Lost per yr per grid cell < > 8000 Administrative Units Rivers 10 Indonesia 100 Cambodia Vietnam South China Sea 110 Malaysia Brunei '000 Kilometers Paul Scherrer Inst./ETH, Switzerland IER, University of Stuttgart, Germany Source: EcoSense China/Asia GIS Source: ESRI Data & Maps CD Indonesia 100 Cambodia Vietnam South China Sea 110 Malaysia Brunei '000 Kilometers Paul Scherrer Inst./ETH, Switzerland IER, University of Stuttgart, Germany Source: EcoSense China/Asia GIS Source: ESRI Data & Maps CD 10 Source: Heck et al. 2003, published in Hirschberg et al. 2003

11 Mortality per Unit Air Emissions for Different Locations of the World SO2 NOx PM10 Years of Life Lost per kt (YOLL/kt) China average Shandong (China) Europe EU-15 Belgium France Germany Italy Portugal Sweden UK Zürich, Switzerland South America average Brazil State of Sao Paulo Colombia Emission location: Sources: EcoSense calculations, Krewitt et al., Heck et al., Hirschberg et al.

12 Aggregated: External costs per kwh electricity in Shandong (China) including LCA CO2 PM NOx SO Heze Jining Linyi Shiliquan Zouxian Huaneng Dezhou Huangtai, Jinan Laiwu Liaocheng Shiheng Nanding Xindian (oil) Zhanhua (oil) Huangdao Qingdao Lougkou Weifang Huaneng Weihai Yantai US Cents per kwh South/Inland West/Central Delta Coast Penninsula Source: Hirschberg et al. 2003

13 Example: Site-specific emission limits for biogas plant Assumption: The same biogas combined heat and power (CHP) plant type considered at different locations adjusted to NOx emission limits. 600 Emissions NOx (mg/nm3 (5% O2)) Sources: TA-Luft Germany 2002, LRVA Switzerland 2005, Brättig 2003, Tehlar Location of biogas plant: 0 Germany Switzerland (general) Zürich Basel Conclusion from LCIA with constant (global) impact factors would be that the first biogas plant is associated with highest impacts. But look at site-specific calculations (next sheet)...

14 Example: Site-specific EC+LCA: biogas/natural gas With 19Euro/ton CO2 Combined Heat and Power (CHP): exergy allocation NG=Natural Gas CC=Combined Cycle External costs (EUR-cent 2000/kWhe) Biogas CH biogas DE (Rostock) biogas CH (North) biogas Zürich NG CC biogas Basel NG CHP DE (Rostock) NG CHP CH (North) NG CHP Zürich NG CHP Basel NG CC CH biogas CH (North) NG CHP CH (North) NG CC CH Current systems 2030 Ionising Radiation Sulfates, primary Nitrates, primary NMVOC (via O3) Formaldehyde Nickel Lead Chromium-VI Cadmium Arsenic PM PM2.5 NOx SO2 GHG (IPCC 100a) Source: Heck et al. 2009

15 Conclusions Environmental impacts due to emissions depend in many cases strongly on the location of the emission sources. Regional or local impacts have to be considered in general (global impact factors can lead to wrong conclusions). Appropriate spatial resolution has to be considered (non-trivial) -> software solutions should be kept flexible. Coupling of life cycle assessment and environmental impact assessment is essential for a comprehensive assessment of systems. Parameterization is a practical approach to combine regional (or site-specific) Life Cycle Inventory (LCI) data and regional (or site-specific, resp.) impact assessment. Space-dependent parameters should be viewed together with other parameter dependencies (time- or technology-dependencies), e.g. in order to include future scenarios (see e.g. NEEDS project for energy systems, scenarios until year 2050).