Table 40.1 (continued) Photochemical ozone formaƟon / Respiratory organics CharacterisaƟon model Derwent et al. (1998), Scenario reflecƟng realisƟc worst case for BriƟsh Isles Norris (2003) POCP11 from Jenkin et al. (1999) Hauschild et al. (2006) van Loon et al. (2007), Vautard et al. (2007), vanZelm et al. (2008) Based on TRACI 1.0 but updated Recommended: LOTOSEUROS fate model as used in ReCiPe, resulƟng indicator: tropospheric ozone concentraƟon increase (no effects) van Loon et al. (2007), Vautard et al. (2007), vanZelm et al. (2008) Fate modeling POCP11, detailed fate modeling of individual VOCs12 Change in Maximum Incremental ReacƟvity (MIR) (Carter 2000), ASTRAP model for source-receptor matrix, factor for NOx based on US average esƟmate POCP11 from Jenkin et al


(1999) Regression model derived from RAINS LOTOS-EUROS model 2007 Updated MIR (Maximum Incremental ReacƟvity) based on Carter (Bare 2011) LOTOS-EUROS model 2007 Exposure modeling PopulaƟon densiƟes and average daily inhalaƟon Increased exposure of humans or vegetaƟon above criƟcal threshold, populaƟon density PopulaƟon densiƟes within grid cells, atmospheric concentraƟon of O3 and average daily inhalaƟon Similar to TRACI 1.0 PopulaƟon densiƟes within grid cells, atmospheric concentraƟon of O3 and average daily inhalaƟon Effect modeling Human health only, linear dose-response model Exceedance for exposure above criƟcal level for humans and vegetaƟon based on WHO13 guidelines (AOT60 for human health, AOT40 for vegetaƟon) Human health only, linearity assumed with no threshold (based on WHO13 recommendaƟon) Human health only, linearity assumed with no threshold (based on WHO13 recommendaƟon) Marginal/average Marginal (ΔO3 per marginal ΔVOC12) Marginal for fate, average for effect

40 Overview of Existing LCIA Methods—Annex to Chapter 10

Hauschild et al., LCA: Theory and Practice


on WHO13 recommendaƟon) Human health only, linearity assumed with no threshold (based on WHO13 recommendaƟon) Marginal/average Marginal (ΔO3 per marginal ΔVOC12) Marginal for fate, average for effect Marginal and Average give same results Marginal increase in long term ozone levels Marginal (linearity checked up to 10% increase) Marginal (linearity checked up to 10% increase) Emission compartment(s) Air Air Air Air Air Air Region modelled/valid North Western Europe USA Europe Europe Europe Europe Level of spaƟal differenƟaƟon US states European countries Global generic Global generic No


of substances 127 (VOCs12, CH4, SO2, NO, NO2 and CO) ~580 ~130 4 (nmVOC14, CH4, Nox and CO) 2 (nmVOC14 and NOx) ~1200 Unit C2H4 equivalents NOx equivalents ethylene equivalents person*ppm*h and m2*ppm*h kg nmVOC14 equivalents NOx equivalents kg nmVOC14 equivalents CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) R.K. Rosenbaum


Table 40.1 (continued) Ionizing radiaƟon CharacterisaƟon model Frischknecht et al. (2000) Same as CML-IA, but without effect model, indicator: human exposure level Same as CML-IA, but without effect/damage model, indicator: human exposure level Recommended: Frischknecht et al. (2000) for human health but excluding damage assessment (only effect) Interim use of method by Garnier-Laplace et al. (2008; 2009) for ecosystem impacts possible Same as CML-IA, but without effect model, indicator: human exposure level Garnier-Laplace et al. (2008; 2009) for ecosystem impacts Fate modeling Dreicer et al. (1995), using rouƟne atmospheric and liquid discharges into rivers in French nuclear fuel cycle including surrounding condiƟons. For globally dispersed radionuclides simplified models are used


(1995), using rouƟne atmospheric and liquid discharges into rivers in French nuclear fuel cycle including surrounding condiƟons. For globally dispersed radionuclides simplified models are used. Exposure modeling EffecƟve dose [Sv] 15 via inhalaƟon, ingesƟon, external irradiaƟon, based on human body equivalence factors for α-, β-, γradiaƟon, and neutrons Effect modeling Dose-response funcƟons directly based on human subjects exposed in Nagasaki and Hiroshima (extrapolated to low-dose exposure) Time horizon(s) [y] 100, 100000 Emission compartment(s) Air, water Region modelled/valid Global, Europe (fate based on French condiƟons) Level of spaƟal differenƟaƟon No


of substances 31 (21 radionuclides to outdoor air, 13 to water, 15 to ocean) 26 for human health and 13 for ecosystem quality impacts Unit DALY C-14 Bq equivalents16 man.Sv/kBq 15, 16 Bq C-14 equivalents16 CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.1 (continued) Human toxicity Diseases considered Cancer/non-cancer Cancer/non-cancer Cancer/non-cancer Cancer/non-cancer Cancer/non-cancer Cancer/non-cancer Cancer/non-cancer Cancer/non-cancer CharacterisaƟon model USES-LCA 1.0 (Huijbregts et al. 2000) CalTOX 4.0 (Hertwich et al. 2001; McKone et al. 2001) IMPACT 2002 (Pennington et al. 2005) EDIP (Hauschild and Poƫng 2005) USES-LCA 2.0 (van Zelm et al. 2009) USEtox 1.0 (Rosenbaum et al. (2008; 2011)) USEtox 1.0 (Rosenbaum et al. (2008; 2011)) USEtox 2.0 (hƩps://usetox.org) Rosenbaum et al


(2008; 2011)) USEtox 1.0 (Rosenbaum et al. (2008; 2011)) USEtox 2.0 (hƩps://usetox.org) Rosenbaum et al. (2008;2011) Fate modeling MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, closed, mulƟmedia, mass-balance model (developed for ERA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) Key property, parƟal fate MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) Exposure modeling InhalaƟon, various ingesƟon pathways InhalaƟon, various ingesƟon pathways, dermal uptake InhalaƟon, various ingesƟon pathways InhalaƟon, various ingesƟon pathways InhalaƟon, various ingesƟon pathways InhalaƟon, various ingesƟon pathways InhalaƟon, various ingesƟon pathways InhalaƟon including indoor exposure (Hellweg et al


2009; Wenger et al. 2012; Rosenbaum et al. 2015), various ingesƟon pathways (Rosenbaum et al. 2011) including pesƟcide residues in food from Fantke et al. (2011a; 2011b; 2013) Effect modeling 17ED50 linear slope factor based on RfD18 19ED10 19ED10 17ED50 17ED50 17ED50 17ED50 (Rosenbaum et al


2011) Marginal/average Marginal (non-linear effect factor) Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Marginal (non-linear effect factor) Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Time horizon Infinite, 100 years for metals Infinite Infinite Infinite Infinite, 100 years for metals or all substances in Individualist perspecƟve Infinite Infinite Infinite Emission compartment(s) Rural air, urban air, freshwater, agricultural soil, natural soil, industrial soil Air, freshwater, soil Air, freshwater, marine water, soil Air, freshwater, soil Rural air, urban air, freshwater, agricultural soil, natural soil, industrial soil Rural air, urban air, water, agricultural soil, natural soil Rural air, urban air, water, agricultural soil, natural soil Rural air, urban air, water, agricultural soil, natural soil Region modelled Europe, version available


agricultural soil, natural soil Rural air, urban air, water, agricultural soil, natural soil Rural air, urban air, water, agricultural soil, natural soil Region modelled Europe, version available for various conƟnents USA Europe Europe Europe Generic Generic Generic global average + 9 parameterised subconƟnents Level of spaƟal differenƟaƟon sub-conƟnental level (Kounina et al


2014) No. of substances ~860 ~380 ~800 ~180 ~1000 ~1250 ~1250 ~1250 Unit 1,4-DCB equivalents20 2,4-D equivalents21 chloroethylene equivalents m3 (volume of poisoned compartment) 1,4-DCB equivalents20 cases or CTUh cases or CTUh cases or CTUh CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) R.K. Rosenbaum


Table 40.1 (continued) Ecotoxicity Ecosystems considered Freshwater, freshwater sediment, marine, marine sediment, terrestrial Freshwater, terrestrial Freshwater, marine, terrestrial Freshwater, terrestrial Freshwater, marine, terrestrial Freshwater Freshwater Freshwater, interim factors for marine and terrestrial CharacterisaƟon model USES-LCA 1.0 (Huijbregts et al. 2000) CalTOX 4.0 (Hertwich et al. 2001; McKone et al. 2001; Bare et al. 2003) IMPACT 2002 (Pennington et al. 2005) EDIP1997, combined with site dependent factors (Tørsløv et al. 2005) USES-LCA 2.0 (van Zelm et al. 2009) USEtox 1.0 (Rosenbaum et al. 2008; Henderson et al. 2011) USEtox 1.0 (Rosenbaum et al. 2008; Henderson et al. 2011) USEtox 2.0 (hƩps://usetox.org) (Rosenbaum et al. 2008; Henderson et al


2011) Fate/exposure modeling MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, closed, mulƟmedia, mass-balance model (developed for ERA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) Key property, parƟal fate MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) MechanisƟc, nested, mulƟmedia, mass-balance model (developed for LCA) Effect modeling Most sensiƟve species Most sensiƟve species Average toxicity Most sensiƟve species Average toxicity Average toxicity Average toxicity Average toxicity Marginal/average Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Marginal (non-linear effect factor) Marginal and Average give same results Marginal and Average give same results


results Marginal and Average give same results Marginal and Average give same results Marginal (non-linear effect factor) Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Time horizon Infinite Infinite Infinite Infinite Infinite, 100 years for metals Infinite Infinite Infinite Emission compartment(s) Air, freshwater, marine water, agricultural soil, industrial soil Air, freshwater Air, freshwater, soil Air, freshwater, soil Air, freshwater, marine water, agricultural soil, natural soil Air, freshwater, marine water, agricultural soil, natural soil Air, freshwater, marine water, agricultural soil, natural soil Air, freshwater, marine water, agricultural soil, natural soil Region modelled Europe USA Europe Generic Europe Generic Generic Generic global average + 9 parameterised subconƟnents Level of spaƟal differenƟaƟon sub-conƟnental level (Kounina et al


2014) No. of substances ~170 ~160 ~430 ~190 ~2650 ~2550 ~2550 ~2550 Unit 1,4-DCB equivalents20 2,4-D equivalents21 triethylene-glycol equivalents m3 (volume of poisoned compartment) 1,4-DCB equivalents20 PAF24 in [m3*day] or CTUe PAF23 in [m3*day] or CTUe PAF23 in [m3*day] or CTUe CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.1 (continued) EutrophicaƟon Ecosystems considered Freshwater, terrestrial Freshwater Freshwater Freshwater, terrestrial Freshwater, marine Same as TRACI 1.0 but with addiƟonal substances covered Freshwater, marine, terrestrial Freshwater, marine Fate modeling No mechanisƟc fate model, mineralisaƟon with full release of bioavailable nutrients, Redfield raƟo assumed for N/P raƟo, no advecƟon, no disƟncƟon between sensiƟve and insensiƟve recipients MechanisƟc (ASTRAP for atmospheric transport, WSAG topological network for water transport) except for NH3 (NOx matrices have been used as placeholder), no advecƟon, no N or P removal, disƟncƟon between sensiƟve and insensiƟve recipients Same as CML-IA, but disƟnguishing P-limited watershed, N-limited watershed, and undefined watershed (modeled as a 50% P-limited and a 50% Nlimited watershed) Atmospheric fate and transport (RAINS model pre 2000 with detailed transport and fate model (applying EMEP)), no advecƟon, removal of nutrients


as a 50% P-limited and a 50% Nlimited watershed) Atmospheric fate and transport (RAINS model pre 2000 with detailed transport and fate model (applying EMEP)), no advecƟon, removal of nutrients in hydrological cycle (using CARMEN model as fixed removal raƟo for N- and Pcompounds in different emission scenarios) MechanisƟc fate model EUTREND for atmospheric and CARMEN for waterborne emissions (Struijs et al


2009), no advecƟon leaving Europe, fixed removal raƟo for N and P in different emission scenarios RecommendaƟon for freshwater and marine: EUTREND model (Struijs et al. 2009) as implemented in ReCiPe [kg P to freshwater and kg N to freshwater for freshwater and marine respecƟvely] Recommendation for terrestrial: Accumulated Exceedance based on Seppälä et al. (2006), Posch et al. (2008), not included in any other LCIA method DisƟncƟon between exposure of N- and P-limited systems Freshwater: fate transport based on Helmes et al


(2012) at the 0.5°x0.5° resoluƟon scale Marine : GEOSchem model (from NASA hƩp://map.nasa.gov/GEOS_ CHEM.html) for atmospheric fate and transport unƟl coastal zones at the 2°x2.5° resoluƟon scale Exposure modeling DisƟncƟon of N- and Plimited recipients No disƟncƟon between freshwaters and marine waters, no criƟcal levels in water, exceedance of criƟcal load in soil considered DisƟncƟon between exposure of N- and P-limited systems DisƟncƟon between exposure of N- (marine) and P-limited (freshwater) systems Effect modeling Linear dose-response relaƟonship according to limiƟng nutrient Marginal/average Marginal Average Marginal Marginal Marginal Marginal Emission compartment(s) Air, freshwater, marine water, soil Air, freshwater Air, freshwater Air, freshwater, soil Air, freshwater, marine water Air, freshwater, marine water Time horizon Infinite Infinite Infinite Infinite Infinite Infinite Region modelled/valid Global generic USA Europe Europe Europe Global Level of spaƟal


marine water Air, freshwater, marine water Time horizon Infinite Infinite Infinite Infinite Infinite Infinite Region modelled/valid Global generic USA Europe Europe Europe Global Level of spaƟal differenƟaƟon US states European countries SpaƟal differenƟaƟon not found important for aquaƟc eutrophicaƟon (factor 3-7 between European countries) Generic, countries for NH3 and NO2 CFs1 available at global, conƟnental, country, and fine scale (0.5°x0.5° resoluƟon scale for freshwater eutrophicaƟon 2°x2.5° for marine eutrophicaƟon) No


of substances 13 (8 N-compounds, 4 P compounds, COD25) 11 (to air: NO, NO2, NOx, NH3 to water: NH4 +, N, NO3 -, PO4 3-, P, COD25) Freshw.: 12 (5 to air, 7 to water; 9 N-comp, 3 P-comp); Terrestrial: SO2, SO3,H2SO4, H2S, NO, NO2, NOx, HNO, NH3, HCL, HF 4 (N-total, P-total, NOx and NH3, but differenƟaƟon of N-total and P-total according to source) Freshwater: P, H3PO4, P-total; marine: NH3, NH4 +, NO3 -, NO2 -, NO2, NO, N-total; terrestrial: NH3, NH4 +, NO2, NO, NO3 - (to air) 8 for freshwater eutrophicaƟon, 16 for marine eutrophicaƟon Unit PO4 3- equivalents PO4 3- equivalents Freshwater: NO3 - equivalents; terrestrial: m2 unprotected ecosystem kg P to freshwater, kg N to freshwater (for marine eutrophicaƟon) kg P to freshwater, kg N to freshwater (for marine eutrophicaƟon), mol Nequivalents for terrestrial kg PO4 P-lim equivalents for freshwater eutrophicaƟon, kg N N-lim equivalents for marine eutrophicaƟon CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF


for terrestrial kg PO4 P-lim equivalents for freshwater eutrophicaƟon, kg N N-lim equivalents for marine eutrophicaƟon CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) R.K


Rosenbaum


Table 40.1 (continued) AcidificaƟon Ecosystems considered Terrestrial Terrestrial Same as CML-IA Terrestrial Terrestrial (forest soil) Same as TRACI 1.0 but with addiƟonal substances covered Terrestrial Terrestrial, freshwater, marine CharacterisaƟon model Huijbregts et al.(2001) Norris (2003) Poƫng et al. (1998) van Zelm et al. (2007), EUTREND, SMART 2 Seppälä et al. (2006) and Posch et al. (2008) Roy et al. (2012a; 2012b; 2014) Fate modeling MechanisƟc atmospheric fate model (RAINS model dated before 2000), linear increase in sensiƟve area change according to emission scenario Atmospheric fate and deposiƟon on land (ASTRAP model dated before 2000), no soil sensiƟvity to acidifying deposiƟon MechanisƟc atmospheric fate model, linear increase in sensiƟve area change, sensiƟve areas considered, incl


with limited buffer capacity, discounƟng for deposiƟon in area above criƟcal load MechanisƟc atmospheric fate model (EUTREND model) including deposiƟon on land (SMART 2 model) MechanisƟc atmospheric fate model including deposiƟon on land (EMEP model) GEOSchem model (from NASA) for atmospheric fate and transport at the 2°x2.5° resoluƟon scale for both terrestrial and freshwater acidificaƟon + receiving environment fate model for freshwater acidificaƟon Exposure modeling SensiƟve areas considered, incl. with limited buffer capacity, acidificaƟon potenƟal modelled with slope inversly proporƟonal to criƟcal load and applied above and below it SensiƟve areas consider magnitude of deposiƟon above criƟcal load and areas with limited buffer capacity for forests (extrapolated to other ecosystems) Linear increase (sensiƟve area change), sensiƟve areas, incl


with limited buffer capacity, acidificaƟon potenƟal modelled as the exceedence above the criƟcal load, potency Terrestrial acidificaƟon: Soil sensiƟvity factor giving the change in soil soluƟon H+ concentraƟon due to a change in the atmospheric deposits of pollutant using the PROFILE geochemical steady-state model Effect modeling Dose-response slope based on a midpoint hazard risk raƟo, similar to PEC / PNEC, and applied above and below criƟcal load (validity sƟll need to be verified as some doubts exist on the relevance of the doseresponse curve, as the slope over buffer capacity depends on the buffer capacity itself Marginal/average Marginal Average Marginal Marginal Marginal Marginal Emission compartments Air, freshwater, soil Air Air Air Air Air Time horizon(s) [y] 1990 and 2010 emission scenario present 1990 and 2010 emission scenario 20, 50, 100 and 500 2002 and 2010 emission scenario 2010 emission scenario Region modelled Europe North America Europe Europe + country specific


scenario present 1990 and 2010 emission scenario 20, 50, 100 and 500 2002 and 2010 emission scenario 2010 emission scenario Region modelled Europe North America Europe Europe + country specific validity Europe Global Level of spaƟal differenƟaƟon European countries US counƟes European countries European countries CFs1 available at global, conƟnental, country, and fine scale (2o x 2.5o resoluƟon scale) No


of substances 4 (NH3, NOx (NO2 and NO), SO2) 8 (H2S, SOx, NO, NO2, NOx, HCL, HF, NH3) 11 (SO2, SO3,H2SO4, H2S, NO, NO2, NOx, HNO, NH3, HCL, HF) 4 (NOx (NO, NOx), NH3, SO2) 4 (SO2, NOx (NO, NO2), NH3) Unit kg SO2 equivalents H+ equivalents kg SO2 equivalents BS26 [m2 * y] mol H+ equivalents kg SO2 equivalents CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.1 (continued) Land use Aspects considered Based on Eco-Indicator 99 endpoints: obtained by dividing damage factors from Eco-Indicator 99 by damage factor of organic arable land from EcoIndicator 99 Land surface used Erosion resistance, mechanical filtraƟon, groundwater replenishment, bioƟc producƟon; for PEF/OEF recommended to provide net blue water consumpƟon as addiƟonal environmental informaƟon Biodiversity, Ecosystem services: erosion resistance capacity/potenƟal (ERP), freshwater recharge potenƟal (FWRP), mechanical filtraƟon potenƟal (MWFP), chemical filtraƟon potenƟal (CWFP), bioƟc producƟon potenƟal (BPP) CharacterisaƟon model None, hence no disƟncƟon8 of different species composiƟon between land use types LANCA 2.0 (Bos et al. 2016) Biodiversity: de Baan et al. (2013a; 2013b) Ecosystem services: updated models from Saad et al


2016) Biodiversity: de Baan et al. (2013a; 2013b) Ecosystem services: updated models from Saad et al. (2011; 2013), and Brandão & Milà i Canals (2013) Marginal/average Average Not described Not described Region modelled Global generic Global Global Level of spaƟal differenƟaƟon Country, world default and local (site-specific) 16 WWF biomes for biodiversity; 36 Holdridge lifezones for ERP, MWPP, PCWPP, FWRP; 12 IPCC climate zones for BPP No


of land use types 3 (2 occupaƟon (compeƟƟon in agricultural area, compeƟƟon in urban area) and 1 transformaƟon) Up tp 58, although many highly correlated 8 for biodiversity; 36 for ERP, MWPP, PCWPP, FWRP; 8/26 for BPP Unit m2 equivalents of organic arable land * y m2 occupaƟon or transformaƟon Erosion resistance in kg/m2 year, mechanical filtraƟon in m3/m2 year, groundwater replenishment in m3/m2 year, bioƟc producƟon in kg/m2 year Biodiversity in ha equivalents of arable land * y, ERP in ton/ha/y, FWRP in mm/y, MWFP in cm/d, CWFP in cmol/kgsoil, BPP in tC/ha/y CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) R.K. Rosenbaum


Table 40.1 (continued) Resources Aspects considered AbioƟc: amount of nonrenewable resources (fossil fuels and minerals) extracted Same as Eco-Indicator 99 endpoint for fossil use only Based on Eco-Indicator 99 endpoints: obtained by dividing damage factors from Eco-Indicator 99 by damage factor of iron in ore from Eco-Indicator 99 AbioƟc: amount of nonrenewable resources (fossil fuels and minerals) extracted BioƟc: wood extracƟon AbioƟc: non-renewable resources (fossil fuels and minerals), based on change in availability of high grade minerals and fossil resources, mining of bulk res. covered by land use, water only as inventory parameter BioƟc: use of agricultural, silvicultural bioƟc resources covered by land use Same as TRACI 1.0 1) AbioƟc resource depleƟon; 2) CumulaƟve Energy Demand (CED); as addiƟonal informaƟon in PEF: 3) AbioƟc and bioƟc resource intensity (i.e


mass accounƟng of bioƟc and abioƟc resources; 4) CriƟcality focusing on economic and social aspects Fossil fuels and mineral resources, approaches based on dissipaƟon of resource funcƟonality (instead of depleƟon of stocks) assuming that extracƟon does not contribute to funcƟonality loss and therefore only dissipaƟon of a resource has an impact CharacterisaƟon model Guinée and Heijungs (1995) based on extracƟon rates and using ulƟmate reserves, average rock is used Hauschild and Wenzel (1998): amount of resource extracted is compared to 1990 extracƟon levels in person equivalents (fracƟon of resource which can be exploited economically is used (can be much smaller than the ulƟmate reserves)) Kirkham and Rafer (2003) AbioƟc resource depleƟon: Anthropogenic stock extended AbioƟc DepleƟon PotenƟal (AADP) model (Schneider et al. 2015); CED as in Ecoinvent (Hischier et al. 2010); CriƟcality based on Supply risk_JRC (Mancini et al


2015); CED as in Ecoinvent (Hischier et al. 2010); CriƟcality based on Supply risk_JRC (Mancini et al. 2016) Fossil fuels: primary energy content Minerals: Material compeƟƟon scarcity index from de Bruille (2014) Time horizion Infinite For renewables annual regeneraƟon used to determine supply horizon Minerals: infinite Fossil fuels: before and aŌer Infinite Infinite Region modelled Global Global Global Global Global No


of resource types 82 elements 20 (minerals) + 34 (fossil fuels) n/a n/a Unit AbioƟc DepleƟon PotenƟal (ADP) [dimensionless] kg equivalents of iron in ore Person reserve - quanƟty of resource available per person (according to economically exploitable reserve) Marginal increase of extracƟon costs AADP in t Sb-eq/t; CED in MJ; resource intensity in kg; criƟcality dimensionless Fossil fuels: MJ deprived, Minerals: kg deprived Water use Aspects considered Water deprivaƟon Water deprivaƟon CharacterisaƟon model(s) AWARE model represenƟng relaƟve Available WAter REmaining per area in a watershed aŌer demand of humans and aquaƟc ecosystems is met; it assesses potenƟal of water deprivaƟon to humans or ecosystems under assumpƟon that the less water remaining available per area, the more likely another user will be deprived (Boulay et al. 2017)


2017). AWARE model represenƟng relaƟve Available WAter REmaining per area in a watershed aŌer demand of humans and aquaƟc ecosystems is met; it assesses potenƟal of water deprivaƟon to humans or ecosystems under assumpƟon that the less water remaining available per area, the more likely another user will be deprived (Boulay et al. 2017). Marginal/average Not described Not described Region modelled Global Global Level of spaƟal differenƟaƟon Country, watershed, global average consumpƟonweighted; for agricultural, non-agricultural and unknown water use Country, watershed, global average consumpƟonweighted; for agricultural, non-agricultural and unknown water use Unit m3 world eq. deprived m3 world eq. m3 deprived CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.1 (continued) 1Characterisation Factor 2Global Warming Potential 3Intergovernmental Panel on Climate Change 4Global Temperature Potential 5Ozone Depletion Potential 6World Meteorological Organisation 7Chlorofluorocarbon 8The information given in ILCD handbook and related documents is incorrect


The correct models are given in Humbert (2009)—the ILCD recommended approach—and are reflected here as well 9Total Suspended Particulate matter 10PM—Particulate Matter (with diameters up to 2.5 and 10 μm respectively) 11Photochemical Ozone Creation Potential 12Volatile Organic Compounds 13World Health Organisation 14Non-Methane Volatile Organic Compounds 15Sievert, unit of ionizing radiation dose 16Becquerel, unit of radioactivity (1 Bq = 1 disintegration per second) 17Effective Dose affecting 50% of tested individuals 18Reference Dose (US-EPA’s acceptable daily oral exposure to the human population likely to be without risk of deleterious effects during a lifetime) 19Effective Dose affecting 10% of tested individuals 20Dichlorobenzene 21Dichlorophenoxyacetic acid 22Comparative Toxic Unit for humans 23Potentially Affected Fraction of species (not an actual unit but a fraction) 24Comparative Toxic Unit for ecosystems 25Chemical Oxygen Demand 26Base Saturation R.K. Rosenbaum


Table 40.2 Detailed characteristics of available endpoint characterisation methods [extended and updated from ILCD handbook on LCIA (EC-JRC 2010, 2011; Sala et al. 2016)] EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Reference Steen (1999) Goedkoop and Spriensma (2000) Jolliet et al. (2003) Itsubo and Inaba (2003) Itsubo and Inaba (2012) Goedkoop et al. (2012) EC-JRC (2011) Bulle et al. (in review) Verones et al. (in preparaƟon), Verones et al. (2016a) Website hƩps://cpmdatabase.cpm. chalmers.se/AboutData base_2.htm hƩps://presustainability.com/ecoindicator-99-manuals hƩps://www.quanƟsintl.com/pdf/IMPACT2002_U serGuide_for_vQ2.21.pdf hƩps://lca-forum.org/english hƩps://lcia-recipe.net hƩps://eplca.jrc.ec.europa


eu/?page_id=86 hƩps://impactworldplus.org hƩps://lc-impact.eu Update of LIME 1.0 Eco-Indicator99 IMPACT 2002+ in part: ReCiPe 2008 UncertainƟes quanƟfied full uncertainty informaƟon based on Monte Carlo Analysis ParƟally, spaƟal variability for each CF2 Qualitative, if possible quanƟtaƟve NormalisaƟon factors Integrated in CFs2 Western Europe (producƟon-based) Western Europe (producƟon-based) Integrated in CFs2 Integrated in CFs2 Europe, global (producƟonbased) European, global (producƟon-based) Global Global WeighƟng scheme Integrated in CFs2 Panel-based cultural perspecƟves: Individualist, Hierarchist, and Egalitarian Willingness to pay [Yen] (Conjoint analysis of interview survey of ~400 Japanese people (Kanto region) on opinions about environmental policy) Same as LIME 1.0, but for ~1000 people from all over Japan and with improved staƟsƟcal analysis Cultural perspecƟves: Individualist, Hierarchist, and Egalitarian No recommended weighing factors, but STEPWISE factors (Weidema et


people from all over Japan and with improved staƟsƟcal analysis Cultural perspecƟves: Individualist, Hierarchist, and Egalitarian No recommended weighing factors, but STEPWISE factors (Weidema et al


2006) are compaƟble and thus opƟonal AddiƟve impacts, including amongst others different Ɵme horizons (CF2 core and CF2 extended) Areas of protecƟon Human health [YOLL]3 , biodiversity [NEX]4 , abioƟc resources [kg], ecological producƟvity [kg] Human health [DALY]5, ecosystem quality [PDF in km2*y]6, resources [MJ surplus energy] Human health [DALY]5, ecosystem quality [PDF in m2*y]6, resources [MJ surplus energy], climate change [CO2 eq] Human health [DALY]5, social welfare [Yen], biodiversity [EINES]7 , , primary producƟon [kgDW]8 Human health [DALY]5 , social assets [Yen], biodiversity [EINES] primary producƟon [kgDW]8 Human health [DALY]5 , Ecosystems [species*y], resources [surplus cost] Human health [DALY]5, Ecosystems [PDF in m2*y]6, Resources and ecosystem services [$] Human Health [DALY]5, Ecosystems incl. vulnerability of species thus represent global exƟncƟons [PDF] 6, Resources [Surplus Ore PotenƟal]. (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.2 (continued) Climate change CharacterisaƟon model(s) (IPCC 1990) GWP9 from IPCC10 (1995) only midpoint CF GWP9 from IPPC10 (2001) GWP9 from IPPC10 (2007b) GWP9 from IPCC10 (2007b), de Schryver et al. (2009) No recommendaƟon, but interim use of ReCiPe 2008 model aGTP11 from IPCC10 2013 (Myhre et al. 2013), de Schryver et al. (2009) with corrected values for “semi natural areas” GWP9 from IPCC10 2013 (Myhre et al. 2013), de Schryver et al. (2009; 2011), Hanafiah et al


2013), de Schryver et al. (2009) with corrected values for “semi natural areas” GWP9 from IPCC10 2013 (Myhre et al. 2013), de Schryver et al. (2009; 2011), Hanafiah et al. (2011) Human health effects Thermal stress, flooding, malaria, starvaƟon (no diarhea) Thermal stress, vector borne diseases, flooding (no starvaƟon) Heat and cold stress, vector borne diseases, malnutriƟon, natural disasters Heat and cold stress, malaria, dengue, disaster damage, malnutriƟon, hunger Cardiovascular diseases, malaria, diarrhoea and malnutriƟon, flooding Cardiovascular diseases, malaria, diarrhoea and malnutriƟon, flooding Cardiovascular diseases, malaria, diarrhoea and malnutriƟon, flooding Ecosystem effects Species loss based on global assessment of ecosystem studies in different regions and different species groups Species loss based on global assessment of ecosystem studies in different regions and different species groups Species loss incl. all species for terr. (De Schryver et al


all species for terr. (De Schryver et al. 2009) and fish as proxy for aqu. (Hanafiah et al. 2011) BioƟc resources effects Decrease in crop producƟon, increase wood producƟon and species loss Links to crop producƟon and fish producƟon Agricultural producƟon, energy consumpƟon, land disappearance Ecosystem service loss (interim) Marginal/average Average Marginal Average Average Marginal Marginal Marginal Time horizon(s) [y] 100, [100-500] 100, 1000 Region modelled Global Global Global Global Global Global Global Level of spaƟal differenƟaƟon No


of substances n/a n/a Unit Willingness to pay (WTP) DALY5 DALY5 and Yen (crop loss) DALY5 and Yen DALY5 and PDF6 in [m2*y] DALY5, PDF6 in [m2*y] and $ DALY5, PDF6 in [yr/kg] EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Ozone depleƟon CharacterisaƟon model(s) ODP12 from WMO13 (1999) ODP12 from WMO13 (1999) and data from TOMS satelite ODP12 from WMO13 (2003) and US-EPA ODP12 from WMO13 (1999) Same as LIME 1.0 ODP12 from WMO13 (2003) No recommendaƟon, but interim use of ReCiPe 2008 model ODP12 from WMO13 (2014) ODP12 from WMO13 (2011), De Schryver et al. (2011) Human health effects Skin cancer Skin cancer and cataract Same as Eco-Indicator 99 (Egalitarian scenario), but with updated ODP Cataract and skin cancer (malignant melanoma, basal cell carcinoma, squamous cell carcinoma) Skin cancer and cataract (laƩer not for individualist perspect.) based on the AMOUR 2.0 model (van Dijk et al. 2008; Den Outer et al


2008; Den Outer et al. 2008) Skin cancer and cataract based on the AMOUR 2.0 model (van Dijk et al. 2008; Den Outer et al. 2008) Skin cancer, cataract BioƟc resources effects Net primary producƟvity for coniferous forests, agriculture (soybean,rice,greenpea, mustard) and phytoplancton at high laƟtudes Marginal/average Average Marginal Marginal Marginal Average Average Time horizon(s) [y] Infinite Infinite Infinite Integrated from 2007 to 100, infinite Region modelled Global Global Global Global Global Global Level of spaƟal differenƟaƟon No. of substances Unit DALY5as monetary value via willingness to pay DALY5 DALY5 DALY5 , NPP14 and kg Wood DALY5 DALY5 DALY5 (continued) R.K. Rosenbaum


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact ParƟculate maƩer formaƟon / Respiratory inorganics CharacterisaƟon model HofsteƩer (1998) Same as Eco-Indicator 99 HofsteƩer (1998), Ikeda (2001) HofsteƩer (1998), Ikeda (2001), Pope et al. (2002) van Zelm et al. (2008) RecommendaƟon: DALY5 based on Humbert (2009) Humbert et al. (2011) for fate and exposure and Gronlund et al. (2015) for effects van Zelm et al


(2002) van Zelm et al. (2008) RecommendaƟon: DALY5 based on Humbert (2009) Humbert et al. (2011) for fate and exposure and Gronlund et al. (2015) for effects van Zelm et al. (2016) Fate/exposure modeling MechanisƟc MechanisƟc MechanisƟc atmospheric fate (plume model and puff model) disƟnguishing chimneys and vehicles source types MechanisƟc, disƟnguishing low, undefined and high stack emission MechanisƟc (same as in ILCD/PEF/OEF but with updated parameters) TM5-FASST, a global chemistry transport model Effect modeling Dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity, etc.) Dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity, etc.) Similar to LIME 1.0 but disease and death rates were increased for some substances/endpoints according to newer data from Pope et al


(2002) Dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity) ; chronic bronchiƟs not considered Dose-response, massbased, surface-based, and number-based Updated region-specific effect and damage data Marginal/average Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Linear Emission compartment Air Air Air (from chimney, from automobile) Air (for low, undefined and high stack emission) Air (high stack, low stack, ground-level, undefined; remote, rura, urban and undefined environnement) Air Time horizon, discounƟng No Ɵmeframe, no discounƟng Infinite Same as LIME 1.0 No Ɵmeframe, no discounƟng No Ɵmeframe, no discounƟng No Ɵmeframe, no discounƟng Region modelled Generic conƟnent Average atmospheric condiƟons for 7 regions of Japan Europe Generic and conƟnental World Level of spaƟal


No Ɵmeframe, no discounƟng No Ɵmeframe, no discounƟng Region modelled Generic conƟnent Average atmospheric condiƟons for 7 regions of Japan Europe Generic and conƟnental World Level of spaƟal differenƟaƟon 7 Japanese regions high stack, low stack, ground-level, undefined; remote, rura, urban and undefined environnement 56 regions No


of substances 4 (primary PM10; secondary PM10 from NH3, NOx, SO2; no values for PM2.5)15 6 (primary PM10 and PM 2.5, SO2, NO2, secondary PM10 from NO2, SO2)15 4 (primary PM10; secondary PM10 from NH3, NOx, SO2)15 5 (primary PM2.5, primary PM10, secondary PM from NOx and SO2, and CO)15 PM2.5 (from PM2.5, NH3, NOx and SO2) Unit DALY5 DALY5 DALY5 DALY5 DALY5 (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Photochemical ozone formaƟon / respiratory organics Human health effects Morbidity and severe morbidity Acute mortality Same as Eco-Indicator 99 (Egalitarian scenario) Acute mortality, morbidity, no consideraƟon of NOx Same as LIME 1.0 Only acute mortality, chronic effects disregarded due to lack of empirical evidence RecommendaƟon: ReCiPe 2008 model Constant damage factor for acute mortality, chronic effects disregarded due to lack of empirical evidence van Zelm et al. (2016) Ecosystem effects All relevant mechanisms, no consideraƟon of NOx Following Van Goethem et al. (2013b) but for the World CharacterisaƟon model POCP16 (Lindfors et al. 1994) HofsteƩer (1998) Ozone conversion equivalency factors (OCEF), Schere & Demerjian, (1984), corrected by Uno and Wakamatsu (1992) van Loon et al. (2007), Vautard et al. (2007), van Zelm et al


1994) HofsteƩer (1998) Ozone conversion equivalency factors (OCEF), Schere & Demerjian, (1984), corrected by Uno and Wakamatsu (1992) van Loon et al. (2007), Vautard et al. (2007), van Zelm et al. (2008) van Loon et al. (2007), Vautard et al. (2007), van Zelm et al. (2008) Van Zelm et al. (2008) Van Goethem et al. (2013a; 2013b), van Zelm et al. (2016) Fate modeling Based on old Swedish version of POCP16 (Lindfors et al. 1994) POCP16 from Jenkin et al


(2008) Van Zelm et al. (2008) Van Goethem et al. (2013a; 2013b), van Zelm et al. (2016) Fate modeling Based on old Swedish version of POCP16 (Lindfors et al. 1994) POCP16 from Jenkin et al. (1999) Average atmospheric condiƟons for 7 regions of Japan LOTOS-EUROS model 2007 LOTOS-EUROS model 2007 TM5-FASST, a global chemistry transport model Exposure modeling PopulaƟon densiƟes and average daily inhalaƟon PopulaƟon distribuƟon for human health, integrated in dose-response model for other AOPs17 PopulaƟon densiƟes within grid cells, atmospheric concentraƟon of O3 and average daily inhalaƟon PopulaƟon densiƟes within grid cells, atmospheric concentraƟon of O3 and average daily inhalaƟon Updated region-specific effect and damage data Van Goethem et al


(2013a; 2013b) Effect modeling Based on global average situaƟon Linear exposure-response funcƟons Linear exposure-response funcƟons, also considering crops and natural vegetaƟon, wood Linearity assumed, no threshold and only including acute effects Human health only, linearity assumed with no threshold (based on WHO18 recommendaƟon) Marginal/average Average Marginal and Average give same results Marginal (ΔO3 per marginal ΔVOC19 for 8 VOC19 archetypes) Marginal (linearity checked up to 10% increase) Marginal (linearity checked up to 10% increase) Linear Emission compartment Air Air Air Air Air Air Region modelled/valid Global damage data, European fate data (POCP16) Europe Japan Europe Europe World Level of spaƟal differenƟaƟon 56 regions No. of substances 67 (nmVOCs20 and Nox) 8 archetypes from which individual VOCs19 can be esƟmated 2 (nmVOC20 and NOx) but factors for individual VOCs19 can be determined applying POCPs16, e.g


of substances 67 (nmVOCs20 and Nox) 8 archetypes from which individual VOCs19 can be esƟmated 2 (nmVOC20 and NOx) but factors for individual VOCs19 can be determined applying POCPs16, e.g. from CML-IA Ozone (from NOx and NMVOC) Unit DALY5 converted to monetary value using willingness to pay DALY5 DALY5 DALY5 DALY5 Human health [DALY]5 and Ecosystems [PDF]6 (continued) R.K. Rosenbaum


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Ionizing radiaƟon CharacterisaƟon model Frischknecht et al. (2000) Same as Eco-Indicator 99 (Egalitarian scenario) Same as Eco-Indicator 99 No recommendaƟon, but interim use of Frischknecht et al. (2000) as used in EcoIndicator 99, IMPACT 2002+, ReCiPe Same as CML-IA, but without effect model, indicator: human exposure level Garnier-Laplace et al. (2008; 2009) for ecosystem impacts Same as CML-IA, complemented with De Schryver et al. (2011) Fate modeling Dreicer et al. (1995), using rouƟne atmospheric and liquid discharges into rivers in French nuclear fuel cycle including surrounding condiƟons. For globally dispersed radionuclides simplified models are used


(1995), using rouƟne atmospheric and liquid discharges into rivers in French nuclear fuel cycle including surrounding condiƟons. For globally dispersed radionuclides simplified models are used. Exposure modeling EffecƟve dose [Sv] 21 via inhalaƟon, ingesƟon, external irradiaƟon, based on human body equivalence factors for α-, β-, γ-radiaƟon, and neutrons Effect modeling Dose-response funcƟons directly based on human subjects exposed in Nagasaki and Hiroshima (extrapolated to low-dose exposure) Time horizon(s) [y] 100, 100000 Emission compartment Air, water Region modelled/valid Global, Europe (fate based on French condiƟons) No. of substances 31 (21 radionuclides to outdoor air, 13 to water, 15 to ocean) 26 for human health and 13 for ecosystem quality impacts Unit DALY5 DALY 5 , PDF 6 in [m2*y] DALY5 (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Human toxicity Diseases considered Cancer/non-cancer Cancer Cancer/non-cancer Cancer, oral chronic noncancer diseases Cancer, oral and inhalatory chronic non-cancer diseases, sick house syndrome via indoor exposure to formaldehyde, NOx, SO2, PM Cancer/non-cancer RecommendaƟon for cancer effects: USEtox model (Rosenbaum et al. 2008) combined with DALYs 5 from Huijbregts et al. (2005) No recommendaƟon for non-cancer effects, but interim use of USEtox model (Rosenbaum et al. 2008) combined with severity factors from Huijbregts et al. (2005) Cancer/non-cancer Same as IMPACT World+ CharacterisaƟon model None EUSES 1.0 (EC and RIVM 1996) IMPACT 2002 (Pennington et al. 2005) Modified version of IMPACT 2002 model Modified version of IMPACT 2002 model USES-LCA 2.0 (van Zelm et al


2005) Modified version of IMPACT 2002 model Modified version of IMPACT 2002 model USES-LCA 2.0 (van Zelm et al. 2009) USEtox 2.0 (www.usetox.org) Fate modeling None MechanisƟc, mass-balance model (developed for risk assessment) MechanisƟc, mass-balance model (developed for LCA) MechanisƟc, mass-balance model (developed for LCA) MechanisƟc, mass-balance model (developed for LCA) (Rosenbaum et al. 2007; Rosenbaum et al. 2008; Henderson et al. 2011; Fantke et al. 2013) Exposure modeling some pathways missing inhalaƟon, various ingesƟon pathways inhalaƟon, various ingesƟon pathways inhalaƟon, various ingesƟon pathways InhalaƟon including indoor exposure (Hellweg et al. 2009; Wenger et al. 2012; Rosenbaum et al. 2015), various ingesƟon pathways (Rosenbaum et al. 2011) including pesƟcide residues from Fantke et al


2009; Wenger et al. 2012; Rosenbaum et al. 2015), various ingesƟon pathways (Rosenbaum et al. 2011) including pesƟcide residues from Fantke et al. (2011a; 2011b; 2013) Effect modeling RfD22, safety factors Unit-Risk concept ED1023 Unit-risk concept for cancer ED1023 for oral chronic diseases Improved models and data, including inhalaƟon exposure to heavy metals based on epidemiological data, sick house syndrome effect modeling via indoor inhalaƟon volumeresponse curve based on clinic survey ED5024 ED5024 (Rosenbaum et al. 2011) combined with severity factors from Huijbregts et al


2011) combined with severity factors from Huijbregts et al. (2005) Marginal/average Average, Sweden, Europe or USA taken as reference Marginal and Average give same results Marginal and Average give same results Similar to IMPACT 2002+ Similar to IMPACT 2002+ Marginal (non-linear effect factor) Marginal and Average give same results Time horizon n/a Infinite Infinite Infinite, 100 years for metals or all substances in Individualist perspecƟve Infinite, ≤100 y, >100 y for metals Emission compartment n/a Air, water, soil Air, water, soil Rural air, urban air, water, agricultural soil, natural soil rural air, urban air, indoor air, agricultural soil, natural soil, freshwater, marine water Region modelled Global average, calculated based on Swedish data Europe Europe Japan Japan Europe global average, 16 subconƟnental zones, 8 conƟnental zones Level of spaƟal differenƟaƟon sub-conƟnental level (Kounina et al. 2014) No


2014) No. of substances ~57 ~10 ~800 ~800 ~1000 ~1000 ~1250 Unit DALY5 converted to monetary value DALY5 DALY5 DALY5 DALY5 DALY5 DALY5 (continued) R.K. Rosenbaum


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Ecotoxicity Ecosystems considered n/a Freshwater, terrestrial Freshwater, marine, terrestrial Freshwater, terrestrial Freshwater, terrestrial Freshwater, marine, terrestrial No recommendaƟon Freshwater, marine, terrestrial Same as IMPACT World+, but with severity factor (PAF-PDF) of 1 and including vulnerability factors for taking species’ vulnerability into account (leading to global exƟncƟons) CharacterisaƟon model None (red list species pot. threatened by chemicals) EUSES 1.0 (EC and RIVM 1996) IMPACT 2002 (Pennington et al. 2005) Modified version of IMPACT 2002 model Modified version of IMPACT 2002 model USES-LCA 2.0 (van Zelm et al


threatened by chemicals) EUSES 1.0 (EC and RIVM 1996) IMPACT 2002 (Pennington et al. 2005) Modified version of IMPACT 2002 model Modified version of IMPACT 2002 model USES-LCA 2.0 (van Zelm et al. 2009) USEtox 2.0 (www.usetox.org) Fate/exposure modeling None MechanisƟc, mass-balance model (developed for risk assessment) MechanisƟc, mass-balance model (developed for LCA) MechanisƟc, mass-balance model (developed for LCA) MechanisƟc, mass-balance model (developed for LCA) (Rosenbaum et al. 2007; Rosenbaum et al. 2008; Henderson et al. 2011) Effect modeling None Most sensiƟve species Average toxicity Average toxicity Average toxicity (Henderson et al. 2011) with generic severity factor (PAF-PDF) of 0.5 (Jolliet et al


2011) Effect modeling None Most sensiƟve species Average toxicity Average toxicity Average toxicity (Henderson et al. 2011) with generic severity factor (PAF-PDF) of 0.5 (Jolliet et al. 2003) Marginal/average Marginal and Average give same results Marginal and Average give same results Marginal and Average give same results Marginal (non-linear effect factor) Marginal and Average give same results Time horizon n/a Infinite Infinite Infinite, 100 years for metals Infinite, ≤100 y and >100 y for metals Emission compartment n/a Air, water, soil Air, water, soil Air, water, agricultural soil, natural soil Air, freshwater, marine water, agricultural soil, natural soil Region modelled Global average Europe Europe Japan Japan Europe global average, 16 subconƟnental zones, 8 conƟnental zones Level of spaƟal differenƟaƟon sub-conƟnental level (Kounina et al. 2014) No


2014) No. of substances ~45 ~45 ~430 n/a n/a ~2650 ~3100 Unit NEX4 PDF6 in [m2*y] PDF6 in [m2*y] EINES25 EINES25 PDF6 in [y/t] PDF6 in [m2*y] (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact EutrophicaƟon Ecosystems considered Freshwater, terrestrial Terrestrial (incl. wetlands and swamps) Freshwater Marine (only benthic communiƟes in coastal water) Same as LIME 1.0 Freshwater No recommendaƟon, but interim use of ReCiPe 2008 model for freshwater eutrophicaƟon Freshwater, marine Freshwater, marine Fate modeling No mechanisƟc fate model, empirical data used, only disƟncƟon between deposiƟon on land and water for airborne emissions No atmospheric fate model, assuming 60% of emissions deposited on European natural soil (no advecƟon leaving Europe) No mechanisƟc fate model, Redfield raƟo assumed for N/P No leaching of N from land, no N or P removal processes, estuarine circulaƟon modelled MechanisƟc fate model EUTREND for atmospheric and CARMEN for waterborne emissions (Struijs et al


2009), fixed removal raƟo for N and P in different emission scenarios Freshwater: fate transport based on Helmes et al. (2012) at the 0.5°x0.5° resoluƟon scale Marine: GEOSchem model (from NASA hƩp://map.nasa.gov/GEOS_CH EM.html) for atmospheric fate and transport unƟl coastal zones at the 2°x2.5° resoluƟon scale Freshwater: fate transport based on Helmes et al


(2012) Marine: Cosme and Hauschild (2017) Exposure modeling Effects assumed for 90% of N emissions exposing Nlimited ecosystems and 10% of P emissions reaching P-limited ecosystems Change in soil nutrients for a marginal deposiƟon increase based on Dutch condiƟons MineralisaƟon with full release of nutrients in biologically available form assumed, freshwater ecosystems P-limited Empirical data for four Japanese bays DisƟncƟon between exposure of N- and Plimited systems DisƟncƟon between exposure of N- and P-limited systems Only P-limited systems for freshwater, only N-limited systems for marine Effect modeling No dose-response Linear dose-response relaƟonship, endpoint as impacts on higher plants in the Netherlands Linear dose-response relaƟonships for different classes of European Plimited freshwater ecosystems Linear dose-response relaƟonships for N and P based on empirical observaƟons on disappearance of benthic species due to oxygen depleƟon Linear dose-response relaƟonship


Plimited freshwater ecosystems Linear dose-response relaƟonships for N and P based on empirical observaƟons on disappearance of benthic species due to oxygen depleƟon Linear dose-response relaƟonship according to limiƟng nutrient Freshwater = P limited Generic effect factor from Tirado-Seco (2005) Marine = N limited Generic, empirical effect factor Freshwater: Azevedo et al


(2013a) Marine: Cosme and Hauschild (2016) Marginal/average Average Marginal Average Marginal Marginal Marginal Both linear/average Emission compartment Air, water Air Air, water, soil Air, water Air, water, soil Air, freshwater, ocean FW: soil, water Marine: air, surface water, groundwater, ocean Time horizon Infinite Infinite Infinite Infinite Infinite Infinite Not relevant Region modelled/valid Global average (extrapolated from Swedish data) Europe + country specific validity/ Dutch validity for midpoint-endpoint modeling Europe Japan Europe Global Global Level of spaƟal differenƟaƟon CFs2 available at global, conƟnental, country, and fine scale (0.5°x0.5° resoluƟon scale for freshwater eutrophicaƟon 2°x2.5° for marine eutrophicaƟon Freshwater: 0.5x0.5 arc degrees, countries, conƟnents, global average Marine: 215 country to LME values, countries, regions, world average No


of substances 5 (1 to air, 4 to water) 4 (NH3, NO, NO2, Nox) 4 P compounds and COD26 from CML 5 (2 to air, 3 to water) 4 (N-total, P-total, NOx and NH3) 8 for freshwater eutrophicaƟon, 16 for marine eutrophicaƟon Total P for freshwater NH3, NOx to air and N to surface water, ground water and ocean for marine Unit NEX4 PDF6 in [m2*y] PDF6 in [m2*y] NPP14(Loss of Benthic biomass) PDF6 in [y/t] PDF6 in [m2*y] PDF6 for freshwater and marine (continued) R.K. Rosenbaum


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact AcidificaƟon Ecosystems considered Terrestrial (incl. wetlands and swamps) Same as Eco-Indicator 99 (Egalitarian scenario) Terrestrial Terrestrial Terrestrial No recommendaƟon, but interim use of ReCiPe 2008 model Terrestrial, freshwater, marine Terrestrial CharacterisaƟon model SMART, MOVE Hayashi et al. (2004) Hayashi et al. (2004) and others van Zelm et al. (2007), EUTREND, SMART 2 Roy et al. (2012a; 2012b; 2014), Azevedo et al. (2015) Same as IMPACT World+ complemented by Azevedo et al


(2013b) Fate modeling No atmospheric fate model, assuming 60% of emissions deposited on European natural soil (no advecƟon leaving Europe) Atmospheric fate model (mixing mechanisƟc and empirical approaches - Euler-type model for SO2 and Nox, empirical values for rest of chemicals with emission and deposiƟon data between 1991-1997) including deposiƟon on land, domesƟc average Similar to LIME 1.0 but dividing Japan into 6 zones, including geographical fluctuaƟon, calculaƟng source aƩribuƟon by zone based on the raƟo of terrestrial area and marine area MechanisƟc atmospheric fate model (EUTREND model) including deposiƟon on land (SMART 2 model) GEOSchem model (NASA hƩp://map.nasa.gov/GEOS_CH EM.html) for atmospheric fate and transport at the 2°x2.5° resoluƟon scale for both terrestrial and freshwater acidificaƟon + receiving environment fate model for freshwater acidificaƟon Same as IMPACT World+ Exposure modeling Change in soil pH for a marginal deposiƟon increase based on Dutch


and freshwater acidificaƟon + receiving environment fate model for freshwater acidificaƟon Same as IMPACT World+ Exposure modeling Change in soil pH for a marginal deposiƟon increase based on Dutch condiƟons SensiƟve areas consider magnitude of deposiƟon above criƟcal load and areas with limited buffer capacity for representaƟve soils in Japan Naturally produced SO2 excluded from emissions used for calculaƟon of source aƩribuƟon of SO2 SensiƟve areas consider magnitude of deposiƟon above criƟcal load and areas with limited buffer capacity for forests (extrapolated to other ecosystems) Terrestrial: soil sensiƟvity factor giving the change in soil soluƟon H+ conc


due to a change in the atmos. deposits of pollutant using the PROFILE geochemical steady-state model (Roy et al. 2012a) Effect modeling Linear dose-response relaƟonship, endpoint as impacts on higher plants in the Netherlands Change in NPP of forestry plant species per change H+ deposiƟon: [NPP] / [H+_dep], linear funcƟon between H+ deposiƟon and NPP, laƩer calculated as a funcƟon of soil acidificaƟon and Al3 + concentraƟon Similar to LIME 1.0 but updated modeling and added biodiversity of terrestrial (plant) ecosystems Change in PotenƟally Not Occurring FracƟon of forestry plant species per change in Base SaturaƟon: [PNOF] / [BS], linear funcƟon for BS > 0.15 based on 240 vascular plants species Terrestrial: site specific effect factor based on biome regr. models from Azevedo et al. (2013b) Freshwater: locaƟon-specific effect factor linking change in H+ concentraƟon in a lake to change in potentially disappeared fracƟon (Roy et al


models from Azevedo et al. (2013b) Freshwater: locaƟon-specific effect factor linking change in H+ concentraƟon in a lake to change in potentially disappeared fracƟon (Roy et al. 2014) Marine: dose response curve for pH effect on different calcifying organisms using available data to assess EC5027 (Azevedo et al. 2015) Terrestrial: same as IMPACT World+ Marginal/average Marginal Marginal Same as LIME 1.0 Marginal Marginal Same as IMPACT World+ Emission compartment Air Air Air Air Time horizon(s) [y] Infinite Infinite 20, 50, 100 and 500 Infinite Region modelled Europe + country specific validity/ Dutch validity for midpoint-endpoint modeling Japan Europe + country specific validity/ Dutch validity for midpoint-endpoint modeling Global Level of spaƟal differenƟaƟon CFs2 available at global, conƟnental, country, and fine scale (2o x 2.5o resoluƟon scale) No


of substances 7 (SO2, SO3, SOx, NH3, NO, NO2, Nox) 5 (SO2, NO, NO2, HCL, NH3) Same as LIME 1.0 4 (Nox (NO, NOx), NH3, SO2) 3 (SOx, NOx, NH3) Unit PDF6 in [m2*y] NPP14 NPP14 and Yen PDF6 in [m2*y] species*y PDF 6 in [m2*y] PDF6 (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Land use Aspects considered biodiversity (only red list species) and primary wood producƟvity of forest Biodiversity Same as Eco-Indicator 99 (Egalitarian scenario) Biodiversity and net primary producƟon of an area Similar to LIME 1.0 but with updated data covering 30 types of vegetaƟon Biodiversity No recommendaƟon due to models’ immaturity, but interim use of Chaudhary et al


(2015) model Biodiversity, Ecosystem service loss: erosion resistance capacity/potenƟal (ERP), freshwater recharge potenƟal (FWRP), mechanical filtraƟon potenƟal (MWFP), chemical filtraƟon potenƟal (CWFP), bioƟc producƟon potenƟal (BPP) Biodiversity global exƟncƟon of species, vulnerability of species communiƟes considered taxa-specific CharacterisaƟon model (Jarvinen and Mieƫnen 1987) Koellner (2001), Species richness (based on vascular plants), species-area relaƟonship NPP based on Chikugo model. Biodiversity based on red species list and life expectancy (study by Matsuda et al. (2003)) Koellner (2001), Species richness (based on vascular plants), species-area relaƟonship Biodiversity: de Baan et al. (2013a; 2013b) Ecosystem services: updated models from Saad et al. (2011; 2013), and Brandão & Milà i Canals (2013) Chaudhary et al


(2013a; 2013b) Ecosystem services: updated models from Saad et al. (2011; 2013), and Brandão & Milà i Canals (2013) Chaudhary et al. (2015) Marginal/average Not described Marginal Marginal Marginal Not described Marginal and average Region modelled Global, but based only on Swedish data Mid Europe, based on Swiss data Japan, for NPP14, overseas areas also considered North West-Europe, based on BriƟsh and Swiss data Global Global Level of spaƟal differenƟaƟon 16 WWF biomes for biodiversity; 36 Holdridge lifezones for ERP, MWPP, PCWPP, FWRP; 12 IPCC climate zones for BPP 804 terrestrial ecoregions No


of land use types 3 (arable land, forest for forest, and forest for roads) 16 land occupaƟons + 11 land conversions n/a 18 land occupaƟons (including 3 intensiƟes for arable areas) + 4 land conversions 8 for biodiversity; 36 for ERP, MWPP, PCWPP, FWRP; 8/26 for BPP 6 (each for occupaƟon and transformaƟon) Unit For biodiversity: NEX4; for primary producƟon: 1kg dry wood PDF6 in [m2*y] EINES 7 and NPP14 EINES7 and NPP14 PDF6 in [m2*y] Biodiversity affecƟng Ecosystem quality endpoint in PDF6 in [m2*y], Ecosystem services (FWRP, MWFP, CWFP, BPP) affecƟng all three andpoints given in DALY5 , PDF6 in [m2*y], $, Ecosystem service ERP affecƟng Resources and ecosystem services in $ species-eq or PDF6 (aggregated across taxa) (continued) R.K. Rosenbaum


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Resources Aspects considered AbioƟc: non-renewable resources (fossil fuels and minerals) based on resource in average rock, water extracƟon (irrigaƟon, drinking) BioƟc: wood extracƟon, fish and meat extracƟon AbioƟc: non-renewable resources (fossil fuels and minerals), based on (long term) change in availability of high grade minerals and fossil resources, mining of bulk resources covered by land use BioƟc: use of agricultural, silvicultural bioƟc resources covered by land use AbioƟc: non-renewable resources: minerals as modelled in Eco-Indicator 99 and fossil fuels modelled in a specific way (no stock size included), mining of bulk resources covered by land use BioƟc: use of agricultural, silvicultural bioƟc resources covered by land use AbioƟc: minerals, fossil resources, fossil fuels BioƟc: living resources (terrestrial ecosystem) Same as


by land use BioƟc: use of agricultural, silvicultural bioƟc resources covered by land use AbioƟc: minerals, fossil resources, fossil fuels BioƟc: living resources (terrestrial ecosystem) Same as LIME 1.0 but with improved models and data AbioƟc: non-renewable resources (fossil fuels and minerals), based on change in availability of high grade minerals and fossil resources, mining of bulk resources covered by land use, water only as inventory parameter BioƟc: use of agricultural, silvicultural biotic resources covered by land use No recommendaƟon due to models’ immaturity, but interim use of Surplus Cost PotenƟal SCP model (Vieira et al


2016) of mining and milling acƟviƟes including all future metal extracƟons and the operaƟng mining costs accounƟng for coproducƟon; assuming that mines with lower operaƟng costs are explored first; costs assumed as measure of depleƟon; unit of SCP is USD2013/kg Endpoint: resources and ecosystem services affected due to funcƟonal deprivaƟon of fossil fuels and mineral resources, approaches based on dissipaƟon of resource funcƟonality (instead of depleƟon of stocks) assuming that extracƟon does not contribute to funcƟonality loss and therefore only dissipaƟon of a resource has an impact Mineral resources CharacterisaƟon model Numerous sources from 1990-2000, not all input data is traceable (de Vries 1988) (Müller-Wenk 1998) For minerals see EcoIndicator 99; for fossils: Ecoinvent database as of n/a Kirkham and Rafel (2003) FuncƟonality specific effect factor for fossil fuels from Fatemi (2012) and for minerals from de Bruille (2014) Vieira et al


(2012; 2017) Time horizon Long Ɵme frame, weighƟng/NormalizaƟon based on future technologies 5x the historical extracƟon before 1990 Minerals: 5x the historical extracƟon before 1990. Fossil fuels: infinite n/a Minerals: infinite Fossil fuels: before and aŌer 2030 n/a n/a Region modelled Global Global Global n/a Global Global Global No. of resource types 67 (minerals) + 3 (fossils) + 3 (bioƟc) + 1 (water) 12 (minerals) + 9 (fossil fuels) 22 (minerals) + 9 (fossil fuels) n/a 20 (minerals) + 34 (fossil fuels) + 5 (water use) n/a 18 minerals Unit kg of element or resource used Surplus energy [MJ] needed to extract one kg extra element or one MJ fuel. Surplus Energy and primary energy [MJ] Yen, EINES7, and NPP14 Marginal increase of extracƟon costs $ Surplus Ore PotenƟal (continued) Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.2 (continued) EPS 2000 Eco-Indicator99 IMPACT 2002+ LIME 1.0 (2003) LIME 2.0 (2008)1 ReCiPe 2008 ILCD/PEF/OEF IMPACT World+ LC-Impact Water use Aspects considered Human health, ecosystem quality, resources and ecosystem services Human health , ecosystem quality CharacterisaƟon model(s) Boulay et al. (2011), van Zelm et al. (2010), Hanafiah et al. (2011), Verones et al. (2010), Humbert and Maendly (2008) Pfister et al. (2009; 2014), Verones et al. (2016b) Ecosystem effects Terrestrial: van Zelm et al. (2010), regionalised using likelihood of shallow vs. deep groundwater extr. Freshwater: Hanafiah et al. (2011) as global average value, model from Verones et al. (2010) for thermal polluƟon, and model from Humbert and Maendly (2008) for water stream use Terrestrial: Plants and aquaƟc: Verones et al. (2016b) Human health effects Human health based on Boulay et al. (2011), represenƟng water stress, i.e


(2016b) Human health effects Human health based on Boulay et al. (2011), represenƟng water stress, i.e. level of compeƟƟon among users (anthropogenic and ecosystems) due to physical stress of the resource, addressing seasonal variaƟons, and disƟnguishing between surface and groundwater Pfister et al


level of compeƟƟon among users (anthropogenic and ecosystems) due to physical stress of the resource, addressing seasonal variaƟons, and disƟnguishing between surface and groundwater Pfister et al. (2009; 2014) Region modelled Global Global Level of spaƟal differenƟaƟon CFs2 available at global, conƟnental, country, and for human health also at fine scale (watershed resoluƟon scale) CFs2 for human health: 11050 watersheds, countries, global average CFs2 for ecosystems: 0.05x0.05 arc degrees, coutries, global average Unit DALY5 , PDF6 in [m2*y], $ DALY5, PDF6 Rare or emerging impact categories Noise From transport applying fate (increase in noise levels due to addiƟonal cars/km - disƟnguishing day/night and small/large cars), exposure (distribuƟon of exposed populaƟon with background levels), effect (volume-response curve based on social survey), and damage due to sleep disorder and conversaƟon disorder Waste User cost, biodiversity of terrestrial ecosystems (continued) R.K. Rosenbaum


Table 40.2 (continued) 1Version 3.0 of LIME, which is currently not documented in english but already available, includes, among other, a water use characterization model, and focuses on global coverage for many impact categories 2Characterization Factor 3Years of Life Lost (actual unit is [year]) 4Normalized Extinction of species 5Disability Adjusted Life Years (actual unit is [year]) 6Potentially Disappeared Fraction of species (not an actual unit but a fraction of 1) 7Expected Increase in Number of Extinct species 8Dry Weight 9Global Warming Potential (a measure of infrared radiative forcing in [W year/m2] or in CO2-eq if normalised to CO2) 10Intergovernmental Panel on Climate Change 11Absolute Global Temperature Potential 12Ozone Depletion Potential 13World Meteorological Organisation 14Net Primary Productivity 15PM—Particulate Matter (with diameters up to 2.5 and 10 μm respectively) 16Photochemical Ozone Creation Potential 17Area of Protection 18World Health Organisation


14Net Primary Productivity 15PM—Particulate Matter (with diameters up to 2.5 and 10 μm respectively) 16Photochemical Ozone Creation Potential 17Area of Protection 18World Health Organisation 19Volatile Organic Compounds 20Non-Methane Volatile Organic Compounds 21Sievert, unit of ionizing radiation dose 22Reference Dose (US-EPA’s acceptable daily oral exposure to the human population likely to be without risk of deleterious effects during a lifetime) 23Effective Dose affecting 10% of tested individuals 24Effective Dose affecting 50% of tested individuals 25Expected increase in Number of Extinct Species 26Chemical Oxygen Demand 27Effective Concentration affecting 50% of individuals Overview of Existing LCIA Methods—Annex to Chapter 10


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http://www.lc-impact.eu R.K. Rosenbaum


Verones, F., Pfister, S., van Zelm, R., Hellweg, S.: Biodiversity impacts from water consumption on a global scale for use in life cycle assessment. Int J Life Cycle Assess. 1–10 (2016b). doi:10. 1007/s11367-016-1236-0 Vieira, M.D.M., Goedkoop, M.J., Storm, P., Huijbregts, M.A.J.: Ore grade decrease as life cycle impact indicator for metal scarcity: the case of copper. Environ. Sci. Technol. 46, 12772–12778 (2012). doi:10.1021/es302721t Vieira, M.D.M., Ponsioen, T.C., Goedkoop, M.J., Huijbregts, M.A.J.: Surplus cost potential as a life cycle impact indicator for metal extraction. Resources 5, 2 (2016). doi:10.3390/ resources5010002 Vieira, M.D.M., Ponsioen, T.C., Goedkoop, M.J., Huijbregts, M.A.J.: Surplus ore potential as a scarcity indicator for resource extraction. J. Ind. Ecol. 21, 381–390 (2017). doi:10.1111/jiec


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47. Geneva, Switzerland (2003) WMO: Scientific Assessment of Ozone Depletion: 2010, Global Ozone Research and Monitoring Project–Report No. 52. Geneva, Switzerland (2011) WMO: Scientific Assessment of Ozone Depletion: 2014, World Meteorological Organization, Global Ozone Research and Monitoring Project Report No. 55. Geneva, Switzerland (2014) Author Biography Ralph K. Rosenbaum LCA expert and environmental modeller focusing on LCIA development since early 2000s. Contributed to several UNEP/SETAC working groups towards global harmonisation of LCA methodology. Interested in LCIA modelling of emissions and water/soil resource use, operationalisation of uncertainty management and spatial differentiation. Overview of Existing LCIA Methods—Annex to Chapter 10