Table 39.14 List of assumptions Assumptions Window type W WA PVC W/C Heat loss is based on the annual average temperatures indoor and outdoor in Denmark (7 and 17 °C, respectively), without considering the dynamics of temperature change during the year x x x x Windows are only used in places covered by district heating x x x x Processes for generation of heat from incinerating straw and incinerating of non-renewable waste in the Danish heat mix were modelled as incineration of bio-waste x x x x Heat generation from biomass in the EU27 heat mix was modelled as incineration of bio-waste combined with combustion of wood pellets (50:50) x x x x Energy consumption for window assembly covers all processes in the factory x x x x Chromium steel and galvanised steel are modelled using the same process x Painting activity of window frame is not modelled (but production of the paint is) x Energy used in disassembly in end of life assumed equal to 1 MJ per 1 kg of window x x x x PVC is 30%


process x Painting activity of window frame is not modelled (but production of the paint is) x Energy used in disassembly in end of life assumed equal to 1 MJ per 1 kg of window x x x x PVC is 30% recycled, and 70% landfilled x Disposal of wood preservative and acrylic binder is not modelled x x Incineration of Aluminium is modelled as municipal solid waste (MSW) x x x x Landfilling of EDPM rubber is modelled as polypropylene (PP) x x x x Incineration of silicone is modelled as incineration of plastic mixture x x x x Argon from window pane is released to the atmosphere during window disassembly x x x x Landfilling of copper and zinc in window frame is not modelled x x x x Transportation distances are the same for all windows in the distribution stage x x x x Transportation distances are the same for all windows in the end-of-life stage x x x x Packaging is the same for all windows x x x x

39 Illustrative Case Study: Life Cycle Assessment of Four Window Alternatives

Hauschild et al., LCA: Theory and Practice


Table 39.15 Inventory of the unit process “Use of window, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Window use, U, MIOW 0.5 0.5 0.67 0.5 p Process output Other outputs (waste to treatment) Disassembly of window, U, MIOW 0.5 0.5 0.67 0.5 p See Table 39.19 DE: polyethylene, incineration (PE, Adapted) kg PlasticsEurope DE: paper/cardboard, incineration (Adapted) 0.2 0.2 0.2 0.2 kg PlasticsEurope Inputs (materials, energy, resources) Assembly and packaging of window, U, MIOW 0.5 0.5 0.67 0.5 p See Table 39.16 Production of window pane, 2-layered, U, MIOW p See Table 39.18 DK: heat mix 14,820 15,040 15,620 12,400 MJ See Table 39.32 RER: alkyd paint, white, 60% in solvent, at plant 4.8 kg ecoinvent, v. 2.2 GLO: truck PE <u-so> technology mix, diesel driven, Euro4, cargo |>34–40 t total cap. /27 t payload capacity 27.3 22.5 26.8 22.4 tkm ecoinvent, v. 2.2 GLO: truck PE <u-so> technology mix, diesel driven, Euro3, cargo |>12–14 t total cap


/27 t payload capacity 27.3 22.5 26.8 22.4 tkm ecoinvent, v. 2.2 GLO: truck PE <u-so> technology mix, diesel driven, Euro3, cargo |>12–14 t total cap. /9.3 t payload capacity 9.1 7.5 8.9 7.5 tkm ecoinvent, v. 2.2 RER: diesel, low-sulphur, at regional storage 0.703 0.581 0.69 0.803 kg ecoinvent, v. 2.2 All outputs and inputs are scaled to the functional unit of the window systems, with windows used for 20 years Illustrative Case Study: Life Cycle Assessment ...


39.4.4 Unit Processes and LCI Results See Tables 39.15, 39.16, 39.17, 39.18, 39.19, 39.20, 39.21, 39.22, 39.23, 39.24, 39.25, 39.26, 39.27, 39.28, 39.29, 39.30, 39.31, 39.32, 39.33 and 39.34. 39.4.5 Normalised Sensitivity Coefficients Normalised sensitivity coefficients were computed for the perturbance of the following parameters: amount of wood, aluminium, steel (W/C window only), and PVC (PVC window only) in the window frame, the amount of glass in the pane, amount of paint, electricity needed for assembly, U-value, and transportation distance from Nor-win to retailers. Thereby, we found that impact scores are most sensitive to U-value, and three other parameters (amount of wood and steel in the frame, and amount of glass in the pane). The normalised sensitivity coefficients for these four parameters are presented in Tables 39.35,39.36, 39.37 and 39.38. 39.5 Annex (Confidential) No confidential data were used in the study


The normalised sensitivity coefficients for these four parameters are presented in Tables 39.35,39.36, 39.37 and 39.38. 39.5 Annex (Confidential) No confidential data were used in the study. Table 39.16 Inventory of the unit process “Assembly and packaging of window, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Window assembled and packed, U, MIOW p Process output Inputs (materials, energy, resources) Production of window frame, U, MIOW p See Table 39.17 Production of window pane, 2-layered, U, MIOW p See Table 39.18 DK: electricity, production mix DK MJ ecoinvent, v. 2.2 DK: heat mix MJ See Table 39.32 RER: corrugated board base paper, kraftliner, at plant kg ecoinvent, v. 2.2 RER: polyethylene film (PE-LD) 0.2 0.2 0.2 0.2 kg PlasticsEurope Note that inputs and outputs are not scaled to the functional unit of the window systems


Table 39.17 Inventory of the unit process “Production of window frame, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Window frame, U, MIOW p Process output Inputs (materials, energy, resources) RER: glued laminated timber, outdoor use, at plant [benefication] 0.06 0.0184 0.0184 m3 ecoinvent, v. 2.2 GLO: Truck PE <u-so> technology mix, diesel driven, Euro4, cargo |>34–40 t total cap. /27 t payload capacity 9.2 11.2 10.37 tkm ecoinvent, v. 2.2 RER: diesel, low-sulphur, at regional storage 0.419 0.129 0.157 0.129 kg ecoinvent, v. 2.2 RER: Aluminium extrusion profile <agg> 0.2 4.6 kg ecoinvent, v. 2.2 RER: chromium steel product manufacturing, average metal working 0.5 1.2 15.1 1.2 kg ecoinvent, v. 2.2 RER: triethylene glycol, at plant [organics] 0.00427 0.00131 0.00131 kg ecoinvent, v. 2.2 RER: acrylic binder, 34% in H2O, at plant [manufacturing] <agg> 0.168 0.0515 0.0515 kg ecoinvent, v


2.2 RER: triethylene glycol, at plant [organics] 0.00427 0.00131 0.00131 kg ecoinvent, v. 2.2 RER: acrylic binder, 34% in H2O, at plant [manufacturing] <agg> 0.168 0.0515 0.0515 kg ecoinvent, v. 2.2 RER: wood preservative, organic salt, Cr-free, at plant [manufacturing] <agg> 0.000525 0.000161 0.000161 kg ecoinvent, v. 2.2 DK: electricity, production mix DK kg ecoinvent, v. 2.2 RER: zinc coating, coils 0.151 m2 ecoinvent, v. 2.2 RER: polyvinylchloride injection moulding part (PVC) PlasticsEurope kg PlasticsEurope RER: glass fibre-reinforced plastic, polyamide, injection moulding, at plant 3.9 kg ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Illustrative Case Study: Life Cycle Assessment ...


Table 39.18 Inventory of the unit process “Production of window pane, 2-layered, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Window pane, 2-layered, U, MIOW p Process output Inputs (materials, energy, resources) REE: flat glass, coated, at plant kg ecoinvent, v. 2.2 GLO: truck PE <u-so> technology mix, diesel driven, Euro4, cargo |>34–40 t total cap. /27 t payload capacity tkm ecoinvent, v. 2.2 RER: diesel, low-sulphur, at regional storage 0.196 0.196 0.196 0.196 kg ecoinvent, v. 2.2 RER: aluminium extrusion profile <agg> 0.4 0.4 0.4 0.4 kg ecoinvent, v. 2.2 DE: polypropylene-EPDM granulate mix PE kg ecoinvent, v. 2.2 RER: silicone product, at plant 1.4 1.4 1.4 1.4 kg ecoinvent, v. 2.2 DE: argon (gaseous) 0.06 0.06 0.06 0.06 kg ecoinvent, v. 2.2 DK: electricity, production mix DK MJ ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems


Table 39.19 Inventory of the unit process “Disassembly of window, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Window disassembled, U, MIOW p Process output Other outputs (waste to treatment) Disposal of aluminium, U, MIOW 0.6 0.4 0.4 kg See Table 39.20 Disposal of wood, U, MIOW 30.2 9.25 9.25 kg See Table 39.26 Disposal of EPDM, U, MIOW Disposal of silicone, U, MIOW 1.4 1.4 1.4 1.4 kg See Table 39.22 Disposal of steel, U, MIOW 0.5 1.2 15.1 1.2 kg See Table 39.28 Disposal of polyvinyl chloride, U, MIOW kg See Table 39.30 Disposal of composite, U, MIOW kg See Table 39.31 Disposal of glass, U, MIOW kg See Table 39.23 Inputs (materials, energy, resources) DK: electricity, production mix DK MJ ecoinvent, v. 2.2 GLO: truck PE <u-so> technology mix, diesel driven, Euro4, cargo |>34–40 t total cap. /27 t payload capacity 4.485 3.695 4.4 3.67 tkm ecoinvent, v


2.2 GLO: truck PE <u-so> technology mix, diesel driven, Euro4, cargo |>34–40 t total cap. /27 t payload capacity 4.485 3.695 4.4 3.67 tkm ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.20 Inventory of the unit process “Disposal of aluminium, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Aluminium recycling, U, MIOW 0.88 0.88 0.88 0.88 kg See Table 39.21 Inputs (materials, energy, resources) Disposal of aluminium, U, MIOW kg Process input CH: disposal, aluminium, 0% water, to municipal incineration kg ecoinvent, v. 2.2 CH: disposal, wood untreated, 20% water, to sanitary landfill 0.12 0.12 0.12 0.12 kg ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Illustrative Case Study: Life Cycle Assessment ...


Table 39.21 Inventory of the unit process “Aluminium recycling, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (avoided product or function) DE: Aluminium ingot mix (Inverted) 0.97 0.97 0.97 0.97 kg ecoinvent, v. 2.2; inverted process Inputs (materials, energy, resources) Aluminium recycling, U, MIOW kg Process input Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.22 Inventory of the unit process “Disposal of EPDM, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) RER: EPDM seal PE, p-agg kg ecoinvent, v. 2.2 Inputs (materials, energy, resources) Disposal of EPDM, U, MIOW kg Process input CH: disposal, polypropylene, 15.9% water, to sanitary landfill kg ecoinvent, v


2.2 Inputs (materials, energy, resources) Disposal of EPDM, U, MIOW kg Process input CH: disposal, polypropylene, 15.9% water, to sanitary landfill kg ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.23 Inventory of the unit process “Disposal of glass, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Inputs (materials, energy, resources) Disposal of glass, U, MIOW kg Process input CH: disposal, building, glass pane (in burnable frame), to sorting plant, U, MIOW kg See Table 39.24 Note that inputs and outputs are not scaled to the functional unit of the window systems


Table 39.24 Inventory of the unit process “CH: disposal, building, glass pane (in burnable frame), to sorting plant, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) CH: disposal, building, glass pane (in burnable frame), to sorting plant, U, MIOW kg Process output Other outputs (avoided product or function) RER: flat glass, uncoated, at plant (inverted) 0.9 0.9 0.9 0.9 kg ecoinvent, v. 2.2; inverted process Inputs (materials, energy, resources) CH: disposal, building, glass pane (in burnable frame), to sorting plant 0.1 0.1 0.1 0.1 kg ecoinvent, v. 2.2 CH: disposal, glass, 0% water, to inert material landfill kg ecoinvent, v. 2.2 RER: glass, cullets, sorted, at sorting plant 0.0071 0.0071 0.0071 0.0071 kg ecoinvent, v. 2.2 RER: excavation, hydraulic digger 7.9E −06 7.9E −06 7.9E −06 7.9E −06 m3 ecoinvent, v. 2.2 CH: electricity, low voltage, at grid 0.00014 0.00014 0.00014 0.00014 MJ ecoinvent, v


2.2 RER: excavation, hydraulic digger 7.9E −06 7.9E −06 7.9E −06 7.9E −06 m3 ecoinvent, v. 2.2 CH: electricity, low voltage, at grid 0.00014 0.00014 0.00014 0.00014 MJ ecoinvent, v. 2.2 CH: sorting plant for construction waste 1.8E −12 1.8E −12 1.8E −12 1.8E −12 p ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.25 Inventory of the unit process “Disposal of silicone, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Inputs (materials, energy, resources) Disposal of silicone, U, MIOW kg Process input CH: disposal, plastics, mixture, 15.3% water, to municipal incineration kg ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Illustrative Case Study: Life Cycle Assessment ...


Table 39.26 Inventory of the unit process “Disposal of wood, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Wood incineration, U, MIOW kg See Table 39.27 Inputs (materials, energy, resources) Disposal of wood, U, MIOW kg Process input Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.27 Inventory of the unit process “Wood incineration, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) DE: wood (natural) in municipal waste incineration PE, p-agg 0.92 0.92 0.92 0.92 kg PlasticsEurope Inputs (materials, energy, resources) Wood incineration, U, MIOW kg Process input CH: disposal, aluminium, 0% water, to municipal incineration 0.00022 0.00022 0.00022 0.00022 kg ecoinvent, v. 2.2 CH: disposal, copper, 0% water, to municipal incineration 8.8E −05 8.8E −05 8.8E −05 8.8E −05 kg ecoinvent, v


2.2 CH: disposal, copper, 0% water, to municipal incineration 8.8E −05 8.8E −05 8.8E −05 8.8E −05 kg ecoinvent, v. 2.2 CH: disposal, zinc in car shredder residue, 0% water, to municipal incineration 0.0041 0.0041 0.0041 0.0041 kg ecoinvent, v. 2.2 CH: disposal, paint, 0% water, to municipal incineration 0.074 0.074 0.074 0.074 kg ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems


Table 39.28 Inventory of the unit process “Disposal of steel, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) Steel recycling, U, MIOW 0.88 0.88 0.88 0.88 kg See Table 39.29 Inputs (materials, energy, resources) Disposal of steel, U, MIOW kg Process input CH: disposal, steel, 0% water, to municipal incineration kg ecoinvent, v. 2.2 CH: disposal, steel, 0% water, to inert material landfill 0.12 0.12 0.12 0.12 kg ecoinvent, v


2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.29 Inventory of the unit process “Steel recycling, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (avoided product or function) DE: steel billet PE (inverted) kg PlasticsEurope, inverted process Inputs (materials, energy, resources) Steel recycling, U, MIOW kg Process input Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.30 Inventory of the unit process “Disposal of polyvinyl chloride, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) DE: polyvinyl chloride (PVC) PE, p-agg 0.7 kg PE Output (avoided product or function) DE: polyvinylchloride granulate mix (S-PVC) PE (inverted) 0.3 kg PE, inverted process Inputs (materials, energy, resources) Disposal of PVC, U, MIOW kg Process input CH: disposal, polyvinyl chloride, 0.2% water, to sanitary landfill kg ecoinvent, v


2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems Illustrative Case Study: Life Cycle Assessment ...


Table 39.31 Inventory of the unit process “Disposal of composite, U, MIOW” Activity W W/ALU PVC W/C Unit Source/note Output (main product or function) RER: polyamide (PA) 6.6 GF ELCD/PE-Gabi p-agg kg PE Inputs (materials, energy, resources) Disposal of composite, U, MIOW kg Process input Note that inputs and outputs are not scaled to the functional unit of the window systems Table 39.32 Inventory of the unit process “Heat, DK, SERF” Activity Value Unit Source/note Output (main product or function) Heat, DK, SERF MJ Process output Inputs (materials, energy, resources) CH: heat, wood pellets, at furnace 50 kW 0.0980 MJ ecoinvent, v. 2.2 CH: heat, softwood chips from industry, at furnace 50 kW 0.1257 MJ ecoinvent, v. 2.2 RER: heat, heavy fuel oil, at industrial furnace 1 MW 0.0235 MJ ecoinvent, v. 2.2 RER: heat, natural gas, at industrial furnace >100 kW 0.2451 MJ ecoinvent, v. 2.2 RER: heat, hard coal briquette, at stove 5–15 kW 0.2344 MJ ecoinvent, v


2.2 RER: heat, natural gas, at industrial furnace >100 kW 0.2451 MJ ecoinvent, v. 2.2 RER: heat, hard coal briquette, at stove 5–15 kW 0.2344 MJ ecoinvent, v. 2.2 CH: heat, bio-waste, at waste incineration plant, allocation price 0.25 MJ ecoinvent, v. 2.2 CH: heat, at cogen, biogas agricultural mix, allocation exergy 0.0195 MJ ecoinvent, v. 2.2 CH: heat, at heat pump 30 kW, allocation exergy 0.0005 MJ ecoinvent, v. 2.2 CH: heat, at solar + gas heating, tube collector, one-family house, combined system 0.0033 MJ ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems. The Danish heat mix is based on data from Energynet (2012). Processes for generation of heat from incinerating straw (0.077 MJ/MJ heat output) and incinerating of non-renewable waste (0.173 MJ/MJ heat output) are modelled as incineration of bio-waste


Table 39.33 Inventory of the unit process “Heat, EU27, MIOW” Activity Value Unit Source/note Output (main product or function) Heat, EU27, MIOW MJ Process output Inputs (materials, energy, resources) CH: heat, wood pellets, at furnace 50 kW 0.065 MJ ecoinvent, v. 2.2 RER: heat, heavy fuel oil, at industrial furnace 1 MW 0.21 MJ ecoinvent, v. 2.2 RER: heat, natural gas, at industrial furnace >100 kW 0.57 MJ ecoinvent, v. 2.2 RER: heat, hard coal briquette, at stove 5–15 kW 0.09 MJ ecoinvent, v. 2.2 CH: heat, bio-waste, at waste incineration plant, allocation price 0.065 MJ ecoinvent, v. 2.2 Note that inputs and outputs are not scaled to the functional unit of the window systems. The EU27 heat mix is based on data from Conolly et al. (2012) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 LCI results (elementary flows for each window product system) Substance W W/ALU PVC W/C Emission to air 1,1,1-trichloroethane 8.33E−11 1.22E−10 1.25E−10 6.49E−11 1-butanol 1.10E−12 5.10E−13 5.17E−13 4.57E−13 Acenaphthene 9.08E−11 8.27E−11 1.21E−10 8.30E−11 Acetaldehyde (ethanal) 3.62E−04 3.61E−04 3.70E−04 3.03E−04 Acetic acid 7.42E−04 6.45E−04 6.28E−04 5.81E−04 Acetone (dimethylcetone) 9.99E−05 1.02E−04 1.02E−04 8.42E−05 Acetonitrile 7.05E−08 6.35E−08 6.58E−08 6.21E−08 Acrolein 4.24E−08 3.26E−08 5.05E−08 2.75E−08 Acrylic acid 1.70E−08 7.91E−09 7.98E−09 7.09E−09 Aldehyde (unspecified) 1.61E−06 1.51E−06 3.28E−07 7.39E−06 Alkane (unspecified) 2.51E−02 4.60E−03 1.02E−02 3.97E−03 Alkene (unspecified) 8.42E−03 8.44E−03 8.73E−03 6.94E−03 Aluminium 1.56E−02 1.60E−02 1.80E−02 1.31E−02 Ammonia 6.25E−02 5.94E−02 7.32E−02 4.94E−02 Ammonium 7.86E−11 1.22E−10 2.85E−11 9.58E−11 Ammonium carbonate 9.60E−08 3.32E−08 4.78E−08 3.41E−08 Ammonium nitrate 4.55E−11 4.89E−11 3.64E−11 4.02E−11


Ammonia 6.25E−02 5.94E−02 7.32E−02 4.94E−02 Ammonium 7.86E−11 1.22E−10 2.85E−11 9.58E−11 Ammonium carbonate 9.60E−08 3.32E−08 4.78E−08 3.41E−08 Ammonium nitrate 4.55E−11 4.89E−11 3.64E−11 4.02E−11 Anthracene 1.98E−09 2.18E−09 2.11E−09 1.79E−09 Antimony 5.81E−06 7.24E−06 7.61E−06 6.32E−06 Aromatic hydrocarbons (unspecified) 9.28E−05 7.22E−05 3.22E−04 1.12E−04 Arsenic (+V) 3.53E−05 3.66E−05 4.83E−05 2.84E−05 Arsenic trioxide 2.27E−12 3.45E−12 2.41E−12 2.80E−12 Barium 7.00E−05 8.79E−05 7.78E−05 6.89E−05 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Benzal chloride 7.62E−15 3.04E−14 1.99E−14 5.85E−15 Benzaldehyde 1.29E−08 6.91E−09 1.59E−08 6.26E−09 Benzene 3.97E−03 3.91E−03 4.15E−03 3.32E−03 Benzo(a)anthracene 9.99E−10 1.10E−09 1.06E−09 9.00E−10 Benzo(a)pyrene 1.98E−06 2.21E−06 2.15E−06 1.59E−06 Benzo(ghi)perylene 8.91E−10 9.80E−10 9.46E−10 8.03E−10 Benzofluoranthene 1.78E−09 1.96E−09 1.89E−09 1.61E−09 Beryllium 3.57E−07 3.89E−07 4.30E−07 2.97E−07 Boron 1.26E−03 1.23E−03 1.40E−03 1.04E−03 Boron compounds (unspecified) 6.89E−04 7.32E−04 7.25E−04 5.80E−04 Boron trifluoride 1.42E−15 6.22E−16 6.24E−16 5.62E−16 Bromine 5.25E−04 5.37E−04 5.58E−04 4.38E−04 Butadiene 2.88E−10 2.12E−10 1.38E−10 1.78E−10 Butane 2.20E−03 2.28E−03 2.21E−03 1.95E−03 Butane (n-butane) 1.18E−03 1.22E−03 1.24E−03 9.94E−04 Butanone (methyl ethyl ketone) 3.06E−05 1.42E−05 1.44E−05 1.28E−05 Butene 1.94E−05 1.37E−05 1.75E−05 2.17E−05 Butylene glycol (butane diol) 3.53E−10 1.65E−10 1.67E−10 1.47E−10 butyrolactone


9.94E−04 Butanone (methyl ethyl ketone) 3.06E−05 1.42E−05 1.44E−05 1.28E−05 Butene 1.94E−05 1.37E−05 1.75E−05 2.17E−05 Butylene glycol (butane diol) 3.53E−10 1.65E−10 1.67E−10 1.47E−10 butyrolactone 1.02E−10 4.76E−11 4.82E−11 4.27E−11 Cadmium (+II) 8.00E−06 7.30E−06 8.45E−06 6.08E−06 Carbon dioxide 8.39E+02 8.36E+02 8.90E+02 7.10E+02 Carbon dioxide (biotic) 2.47E+02 2.46E+02 2.56E+02 2.03E+02 Carbon dioxide (biotic) 4.94E−01 4.76E−01 4.69E−01 4.15E−01 Carbon dioxide, land transformation 2.68E−03 2.18E−03 3.00E−03 2.16E−03 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Carbon disulphide 3.22E−04 3.66E−04 3.59E−04 2.27E−04 Carbon monoxide 3.35E−01 3.22E−01 2.82E−01 2.57E−01 Carbon monoxide (biotic) 2.18E−01 2.18E−01 2.25E−01 1.79E−01 Carbon tetrachloride (tetrachloromethane) 5.56E−07 1.21E−07 1.66E−07 1.05E−07 Chloride (unspecified) 2.75E−05 5.97E−05 2.88E−05 2.75E−05 Chlorine 5.43E−04 5.27E−04 1.74E−03 4.37E−04 Chloromethane (methyl chloride) 5.16E−05 3.29E−05 3.29E−05 3.29E−05 Chlorosilane, trimethyl3.06E−10 1.42E−10 1.43E−10 1.27E−10 Chromium (+III) 1.20E−08 1.28E−08 1.26E−08 1.03E−08 Chromium (+VI) 2.93E−06 4.09E−06 4.94E−05 3.98E−06 Chromium (unspecified) 1.33E−04 1.77E−04 1.99E−03 1.72E−04 Chrysene 2.45E−09 2.70E−09 2.60E−09 2.21E−09 Cobalt 1.05E−05 1.05E−05 3.20E−05 9.73E−06 Copper (+II) 1.17E−04 1.08E−04 2.09E−04 9.33E−05 Cumene (isopropylbenzene) 2.52E−05 1.38E−05 1.64E−05 3.48E−05 Cyanide (unspecified) 3.03E−03 3.09E−03 3.25E−03 2.54E−03 Cycloalkanes (unspec.) 5.15E−06 2.46E−07 3.28E−07


1.08E−04 2.09E−04 9.33E−05 Cumene (isopropylbenzene) 2.52E−05 1.38E−05 1.64E−05 3.48E−05 Cyanide (unspecified) 3.03E−03 3.09E−03 3.25E−03 2.54E−03 Cycloalkanes (unspec.) 5.15E−06 2.46E−07 3.28E−07 3.89E−06 Cyclohexane (hexahydro benzene) 1.68E−07 1.95E−07 1.27E−07 1.39E−07 Dibenz(a)anthracene 5.55E−10 6.11E−10 5.90E−10 5.00E−10 Dichlorobenzene (o-DCB; 1,2-dichlorobenzene) 4.75E−08 2.21E−08 2.24E−08 1.98E−08 Dichloroethane (1,2-dichloroethane) 4.74E−06 3.03E−06 8.26E−06 3.55E−05 Dichloroethane (ethylene dichloride) 1.01E−09 1.01E−09 4.53E−04 1.01E−09 Dichloromethane (methylene chloride) 2.79E−09 2.73E−09 2.93E−06 9.60E−09 Diethylamine 1.97E−15 3.04E−15 7.13E−16 2.40E−15 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Dioxins (unspec.) 1.95E−14 2.89E−14 2.74E−09 2.46E−14 Dust (>PM10) 2.68E−01 2.57E−01 2.89E−01 2.19E−01 Dust (PM10) 2.76E−03 3.21E−03 1.98E−02 2.40E−03 Dust (PM2,5–PM10) 2.45E−02 1.66E−02 3.42E−02 1.83E−02 Dust (PM2.5) 6.70E−02 6.42E−02 8.51E−02 5.52E−02 Dust (unspecified) 3.19E−02 4.03E−02 3.41E−02 2.71E−02 Emissions to air 4.94E+03 5.01E+03 5.08E+03 4.16E+03 Ethane 6.12E−03 6.76E−03 6.37E−03 5.71E−03 Ethanol 1.79E−04 1.92E−04 1.90E−04 1.57E−04 Ethene (ethylene) 2.36E−04 1.75E−04 4.25E−04 1.71E−04 Ethine (acetylene) 1.36E−04 1.25E−04 1.37E−04 1.24E−04 Ethyl benzene 7.63E−04 8.04E−04 7.95E−04 6.36E−04 Ethyl cellulose 6.19E−08 2.87E−08 2.90E−08 2.57E−08 Ethylene acetate (ethyl acetate) 3.06E−05 1.42E−05 1.44E−05 1.28E−05 Ethylene oxide 4.42E−07 2.31E−07 2.30E−07 4.25E−07 Ethylenediamine 6.52E−10 6.50E−10 6.58E−10 6.50E−10 Exhaust 3.54E+03 3.58E+03 3.61E+03 2.97E+03 Fluoranthene 6.46E−09 7.11E−09 6.86E−09 5.82E−09 Fluorene 2.05E−08


4.42E−07 2.31E−07 2.30E−07 4.25E−07 Ethylenediamine 6.52E−10 6.50E−10 6.58E−10 6.50E−10 Exhaust 3.54E+03 3.58E+03 3.61E+03 2.97E+03 Fluoranthene 6.46E−09 7.11E−09 6.86E−09 5.82E−09 Fluorene 2.05E−08 2.26E−08 2.18E−08 1.85E−08 Fluoride 6.62E−05 3.09E−04 5.60E−05 5.62E−05 Fluorine 1.26E−04 1.25E−04 1.36E−04 1.08E−04 Formaldehyde (methanal) 2.81E−03 2.34E−03 2.20E−03 1.97E−03 Formic acid (methane acid) 5.10E−07 4.42E−07 4.58E−07 4.31E−07 Furan 1.34E−07 1.21E−07 1.25E−07 1.18E−07 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Group NMVOC to air 2.74E−01 2.30E−01 2.40E−01 2.05E−01 Group PAH to air 5.33E−05 7.66E−05 5.71E−05 4.82E−05 Halogenated hydrocarbons (unspecified) 1.93E−07 1.93E−07 1.39E−04 1.93E−07 Halogenated organic emissions to air 4.40E−04 4.85E−04 2.23E−03 4.06E−04 Halon (1211) 5.52E−07 4.23E−07 5.58E−07 3.93E−07 Halon (1301) 5.67E−07 4.17E−07 5.54E−07 3.69E−07 Heavy metals to air 2.45E−03 2.73E−03 5.25E−03 2.07E−03 Heavy metals to air (unspecified) 7.49E−10 6.98E−10 −2.10E−08 2.78E−10 Helium 5.92E−05 4.77E−05 5.33E−05 4.14E−05 Heptane (isomers) 2.05E−04 1.56E−04 1.73E−04 1.38E−04 Hexachlorobenzene (Perchlorobenzene) 8.38E−07 8.51E−07 9.04E−07 7.00E−07 Hexafluorosilicates 1.22E−06 9.74E−07 1.19E−06 9.21E−07 Hexamethylene diamine (HMDA) 4.53E−12 6.95E−12 2.48E−12 5.52E−12 Hexane (isomers) 1.21E−03 4.15E−04 4.93E−04 3.79E−04 Hydrocarbons (unspecified) 9.01E−04 9.01E−04 3.36E−02 9.01E−04 Hydrocarbons, aromatic 1.33E−04 1.10E−04 1.88E−04 9.60E−05


2.48E−12 5.52E−12 Hexane (isomers) 1.21E−03 4.15E−04 4.93E−04 3.79E−04 Hydrocarbons (unspecified) 9.01E−04 9.01E−04 3.36E−02 9.01E−04 Hydrocarbons, aromatic 1.33E−04 1.10E−04 1.88E−04 9.60E−05 Hydrocarbons, chlorinated 3.25E−04 3.09E−04 2.17E−04 2.45E−04 Hydrogen 2.51E−03 2.17E−03 4.33E−02 2.33E−03 Hydrogen arsenic (arsine) 1.89E−10 2.86E−10 2.00E−10 2.32E−10 Hydrogen bromine (hydrobromic acid) 1.47E−08 1.54E−08 8.83E−09 1.91E−08 Hydrogen chloride 7.40E−03 8.06E−03 1.83E−02 6.71E−03 Hydrogen cyanide (prussic acid) 4.41E−08 7.64E−08 −1.41E−07 2.97E−08 Hydrogen fluoride 1.72E−03 1.98E−03 2.08E−03 1.51E−03 Hydrogen iodide 1.52E−11 1.58E−11 8.71E−12 2.01E−11 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Hydrogen phosphorous 5.23E−09 2.82E−08 4.18E−09 4.18E−09 Hydrogen sulphide −2.82E−05 −2.63E−03 1.71E−04 −2.80E−05 Indeno(1,2,3-cd)pyrene 6.63E−10 7.29E−10 7.04E−10 5.97E−10 Inorganic emissions to air 1.39E+03 1.42E+03 1.47E+03 1.18E+03 Iodine 1.27E−05 9.96E−06 1.65E−05 9.97E−06 Iron 1.05E−04 9.55E−05 2.77E−04 8.44E−05 Isocyanide acid 1.20E−03 3.67E−04 5.38E−07 3.67E−04 Isoprene 6.21E−09 5.59E−09 5.80E−09 5.47E−09 Lanthanides 1.39E−10 1.63E−10 1.09E−10 1.18E−10 Lead (+II) 1.62E−04 1.74E−04 2.80E−04 1.31E−04 Lead dioxide 5.85E−12 9.28E−12 4.08E−12 5.13E−12 Magnesium 2.28E−10 8.97E−10 5.89E−10 1.75E−10 Manganese (+II) 4.58E−04 4.57E−04 4.96E−04 3.77E−04 Mercaptan (unspecified) 5.80E−07 1.09E−06 2.97E−05 9.46E−07 Mercury (+II) 1.66E−05 1.62E−05 2.24E−05 1.32E−05 Metals (unspecified) 7.82E−06 1.81E−05 3.41E−04 1.81E−05 Methacrylate 1.93E−08 8.98E−09 9.05E−09 8.04E−09 Methane 1.86E+00 1.89E+00 2.25E+00 1.63E+00 Methane (biotic) 9.46E−03


2.24E−05 1.32E−05 Metals (unspecified) 7.82E−06 1.81E−05 3.41E−04 1.81E−05 Methacrylate 1.93E−08 8.98E−09 9.05E−09 8.04E−09 Methane 1.86E+00 1.89E+00 2.25E+00 1.63E+00 Methane (biotic) 9.46E−03 9.04E−03 1.08E−02 8.00E−03 Methanol 7.97E−04 4.35E−04 4.05E−04 4.19E−04 Methyl amine 3.69E−11 1.72E−11 1.74E−11 1.54E−11 Methyl borate 6.53E−15 3.03E−15 3.06E−15 2.71E−15 Methyl bromide 1.65E−15 6.86E−15 4.46E−15 1.26E−15 Methyl formate 7.50E−11 3.48E−11 3.51E−11 3.12E−11 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Methyl tert-butylether 1.94E−06 1.00E−06 6.17E−07 9.31E−07 Molybdenum 1.86E−06 1.63E−06 2.03E−06 1.43E−06 Monoethanolamine 1.13E−05 1.07E−05 1.09E−05 1.07E−05 Naphthalene 2.08E−07 2.29E−07 2.21E−07 1.88E−07 Nickel (+II) 8.04E−05 6.70E−05 1.04E−04 5.96E−05 Nitrate 1.05E−07 1.13E−07 1.59E−07 8.70E−08 Nitrogen (atmospheric nitrogen) 3.42E−02 3.74E−02 3.24E−02 2.93E−02 Nitrogen dioxide 9.95E−04 9.95E−04 7.04E−02 9.95E−04 Nitrogen monoxide 1.99E−09 2.17E−09 2.07E−09 1.72E−09 Nitrogen oxides 1.48E+00 1.46E+00 1.53E+00 1.24E+00 Nitrous oxide (laughing gas) 9.64E−02 9.35E−02 9.73E−02 7.88E−02 NMVOC (unspecified) 2.01E−01 1.77E−01 1.79E−01 1.60E−01 Octane 6.50E−06 1.14E−05 8.01E−06 9.83E−06 Organic chlorine compounds 6.61E−10 6.63E−10 9.66E−05 6.59E−10 Organic emissions to air (group VOC) 2.15E+00 2.13E+00 2.54E+00 1.85E+00 Other emissions to air 3.54E+03 3.59E+03 3.61E+03 2.98E+03 Oxygen 2.06E−02 2.45E−02 1.96E−02 1.87E−02 Ozone 2.05E−04


6.59E−10 Organic emissions to air (group VOC) 2.15E+00 2.13E+00 2.54E+00 1.85E+00 Other emissions to air 3.54E+03 3.59E+03 3.61E+03 2.98E+03 Oxygen 2.06E−02 2.45E−02 1.96E−02 1.87E−02 Ozone 2.05E−04 1.54E−04 2.46E−04 1.49E−04 Palladium −1.13E−14 −6.16E−14 −9.03E−15 −9.01E−15 Particles to air 4.09E−01 3.97E−01 4.80E−01 3.35E−01 Pentachlorobenzene 2.05E−06 2.09E−06 2.18E−06 1.71E−06 Pentachlorophenol (PCP) 4.09E−07 3.76E−07 4.67E−07 3.32E−07 Pentane (n-pentane) 4.00E−03 3.84E−03 4.10E−03 3.23E−03 Phenanthrene 6.55E−08 7.20E−08 6.95E−08 5.90E−08 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Phenol (hydroxy benzene) 4.46E−06 3.80E−06 6.54E−06 1.25E−05 Phosphorus 1.69E−03 1.71E−03 1.78E−03 1.41E−03 Platinum 1.70E−11 1.58E−11 2.28E−11 1.64E−11 Polychlorinated biphenyls (PCB unspecified) 3.81E−08 3.31E−08 6.03E−08 2.97E−08 Polychlorinated dibenzo-p-dioxins (2,3,7,8—TCDD) 6.50E−09 6.63E−09 6.91E−09 5.44E−09 Polycyclic aromatic hydrocarbons (PAH) 5.11E−05 7.41E−05 5.46E−05 4.63E−05 Propane 8.26E−03 9.58E−03 8.81E−03 8.00E−03 Propanol (iso-propanol; isopropanol) 6.59E−06 3.06E−06 3.08E−06 2.74E−06 Propene (propylene) 1.27E−04 1.12E−04 1.46E−04 1.19E−04 Propionaldehyde 1.32E−08 7.18E−09 1.64E−08 6.53E−09 Propionic acid (propane acid) 5.10E−06 4.23E−06 5.75E−06 3.82E−06 Propylene oxide 1.40E−06 1.12E−06 1.15E−06 1.00E−06 R 11 (trichlorofluoromethane) 4.22E−07 1.16E−06 2.11E−07 5.00E−07 R 113 (trichlorofluoroethane) 8.09E−10 3.76E−10 3.79E−10 3.36E−10 R 114 (dichlorotetrafluoroethane) 7.19E−07 1.42E−06 5.70E−07 7.41E−07 R 116


4.22E−07 1.16E−06 2.11E−07 5.00E−07 R 113 (trichlorofluoroethane) 8.09E−10 3.76E−10 3.79E−10 3.36E−10 R 114 (dichlorotetrafluoroethane) 7.19E−07 1.42E−06 5.70E−07 7.41E−07 R 116 (hexafluoroethane) 2.44E−06 8.08E−06 2.11E−06 1.88E−06 R 12 (dichlorodifluoromethane) 3.98E−06 2.73E−06 2.72E−06 3.85E−06 R 13 (chlorotrifluoromethane) 5.70E−08 1.57E−07 2.85E−08 6.76E−08 R 134a (tetrafluoroethane) 2.07E−08 1.57E−08 2.29E−08 1.55E−08 R 152a (difluoroethane) 1.91E−08 1.51E−08 2.42E−08 1.51E−08 R 21 (dichlorofluoromethane) 1.21E−11 6.81E−12 7.00E−12 6.56E−12 R 22 (chlorodifluoromethane) 2.19E−06 1.85E−06 2.17E−06 1.59E−06 R 23 (trifluoromethane) 3.84E−09 2.17E−09 2.23E−09 2.09E−09 Radioactive emissions to air 5.07E−06 4.93E−06 6.27E−06 4.09E−06 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Rhodium −1.09E−14 −5.95E−14 −8.71E−15 −8.69E−15 Scandium 1.90E−08 1.69E−08 6.06E−08 1.52E−08 Selenium 7.02E−05 7.31E−05 7.47E−05 5.87E−05 Silicium tetrafluoride 2.69E−08 1.76E−08 1.80E−08 1.72E−08 Silver 3.57E−09 2.90E−09 9.33E−09 2.93E−09 Sodium chlorate 1.21E−07 1.10E−07 1.16E−07 1.05E−07 Sodium dichromate 3.44E−07 3.37E−07 4.66E−07 2.83E−07 Sodium formate 4.91E−07 4.87E−07 4.91E−07 4.86E−07 Sodium hydro 1.71E−07 7.94E−08 8.02E−08 7.11E−08 Steam 3.05E+02 3.34E+02 3.22E+02 2.62E+02 Strontium 5.10E−06 4.19E−06 1.19E−05 3.95E−06 Styrene 5.06E−07 4.23E−07 7.34E−07 5.74E−07 Sulphate 1.99E−10 2.91E−10 2.99E−10 1.55E−10 Sulphur dioxide 5.44E−01 5.62E−01 6.95E−01 4.62E−01 Sulphur hexafluoride 2.85E−06 2.06E−06 3.11E−06 2.03E−06 Sulphuric acid 1.15E−07 1.56E−07 6.24E−08 8.50E−08 Tellurium 1.60E−09 1.70E−09 1.68E−09 1.37E−09 Terpenes 5.87E−08 5.29E−08 5.49E−08 5.17E−08 Tetrachloroethene (perchloroethylene) 1.88E−05 4.51E−05 7.56E−04 4.51E−05


1.56E−07 6.24E−08 8.50E−08 Tellurium 1.60E−09 1.70E−09 1.68E−09 1.37E−09 Terpenes 5.87E−08 5.29E−08 5.49E−08 5.17E−08 Tetrachloroethene (perchloroethylene) 1.88E−05 4.51E−05 7.56E−04 4.51E−05 Tetrafluoromethane 2.14E−05 7.25E−05 1.88E−05 1.67E−05 Thallium 1.21E−07 1.15E−07 7.95E−08 9.26E−08 Thorium (Th230) 4.10E−09 3.44E−09 5.17E−09 3.05E−09 Thorium (Th232) 6.85E−07 5.43E−07 1.18E−06 5.28E−07 Tin (+IV) 9.88E−05 1.01E−04 1.12E−04 9.27E−05 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Tin oxide 5.09E−13 8.08E−13 3.55E−13 4.46E−13 Titanium 5.62E−06 5.06E−06 1.80E−05 4.58E−06 Toluene (methyl benzene) 2.23E−03 2.22E−03 2.32E−03 1.83E−03 Trichloromethane (chloroform) 3.33E−08 1.98E−08 2.40E−08 1.88E−08 Trimethylbenzene 4.96E−12 7.87E−12 3.46E−12 4.34E−12 Uranium (total) 4.38E−06 4.38E−06 5.09E−06 3.56E−06 Used air 7.05E+00 1.56E+01 −1.50E+00 1.55E+01 Vanadium (+III) 1.14E−04 1.14E−04 1.15E−04 8.98E−05 Vinyl chloride (VCM; chloroethene) 2.91E−06 2.07E−06 5.86E−04 1.84E−05 VOC (unspecified) 3.92E−05 4.23E−05 6.96E−04 4.07E−05 Wood (dust) 1.88E−10 2.98E−10 1.31E−10 1.65E−10 Xylene (dimethyl benzene) 3.37E−03 3.51E−03 3.57E−03 2.82E−03 Xylene (meta-xylene; 1,3-dimethylbenzene) 2.97E−04 2.96E−04 3.07E−04 2.44E−04 Zinc (+II) 1.02E−03 1.27E−03 1.40E−03 8.37E−04 Zinc oxide 1.02E−12 1.62E−12 7.10E−13 8.92E−13 Zinc sulphate 4.54E−09 6.99E−09 4.81E−09 5.68E−09 Emissions to freshwater 1,2-dibromoethane 3.95E−11 4.57E−11 2.97E−11


1.27E−03 1.40E−03 8.37E−04 Zinc oxide 1.02E−12 1.62E−12 7.10E−13 8.92E−13 Zinc sulphate 4.54E−09 6.99E−09 4.81E−09 5.68E−09 Emissions to freshwater 1,2-dibromoethane 3.95E−11 4.57E−11 2.97E−11 3.27E−11 1-butanol 1.11E−07 5.16E−08 5.22E−08 4.63E−08 Acenaphthene 4.75E−09 4.54E−09 4.29E−09 3.98E−09 Acenaphthylene 6.41E−10 9.52E−10 6.95E−10 8.26E−10 Acetaldehyde (Ethanal) 2.03E−07 9.43E−08 9.53E−08 8.45E−08 Acetic acid 2.31E−05 1.56E−05 9.00E−06 1.72E−05 Acetone (dimethylcetone) 1.10E−10 4.32E−10 2.84E−10 8.43E−11 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Acid (calculated as H +) 9.13E−05 4.21E−04 2.07E−04 1.18E−04 Acrylic acid 4.03E−08 1.87E−08 1.89E−08 1.68E−08 Acrylonitrile 2.66E−10 4.08E−10 1.45E−10 3.24E−10 Adsorbable organic halogen compounds (AOX) 3.90E−05 3.41E−05 2.47E−05 3.23E−05 Alkane (unspecified) 7.90E−05 5.50E−05 6.46E−05 4.90E−05 Alkene (unspecified) 7.29E−06 5.08E−06 5.96E−06 4.52E−06 Aluminium (+III) 6.72E+00 7.10E+00 7.12E+00 5.66E+00 Aluminium (+III) 1.82E−03 2.45E−03 7.38E−03 1.80E−03 Ammonia 4.43E−07 4.70E−07 1.16E−07 3.68E−07 Ammonium/ammonia 1.64E−05 1.25E−05 2.79E−03 1.34E−05 Ammonium/ammonia 1.79E−03 1.67E−03 3.10E−03 5.15E−03 Analytical measures to freshwater 4.23E+00 3.85E+00 5.21E+00 3.25E+00 Anthracene 1.56E−09 2.98E−09 1.87E−09 2.49E−09 Antimony 3.82E−05 1.99E−05 6.67E−05 7.28E−05 Antimony 2.16E−05 1.15E−05 2.03E−05 4.03E−05 Aromatic hydrocarbons (unspecified) 3.21E−04 2.25E−04 2.78E−04 2.00E−04 Arsenic (+V) 9.48E−04 9.66E−04 1.02E−03 7.93E−04 Arsenic (+V)


6.67E−05 7.28E−05 Antimony 2.16E−05 1.15E−05 2.03E−05 4.03E−05 Aromatic hydrocarbons (unspecified) 3.21E−04 2.25E−04 2.78E−04 2.00E−04 Arsenic (+V) 9.48E−04 9.66E−04 1.02E−03 7.93E−04 Arsenic (+V) 8.62E−04 8.71E−04 9.34E−04 7.20E−04 Barium 4.92E−04 4.00E−04 2.07E−03 4.01E−04 Barium 5.56E−04 4.25E−04 9.33E−04 3.73E−04 Benzene 9.88E−05 6.16E−05 7.41E−05 1.31E−04 Benzo(a)anthracene 1.27E−10 2.53E−10 1.62E−10 2.24E−10 Benzofluoranthene 5.13E−11 1.14E−10 7.24E−11 1.07E−10 Beryllium 3.44E−06 2.66E−06 7.92E−06 2.64E−06 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Beryllium 1.12E−08 1.19E−08 1.43E−08 9.18E−09 Biological oxygen demand (BOD) 1.43E−01 9.34E−02 1.17E−01 8.63E−02 Boron 6.11E−03 6.12E−03 6.58E−03 5.10E−03 Boron 2.23E−03 2.28E−03 2.38E−03 1.88E−03 Bromate 6.12E−04 5.08E−04 5.42E−04 4.18E−04 Bromine 9.04E−04 9.18E−04 1.44E−03 7.70E−04 Bromine 4.69E−03 4.63E−03 4.93E−03 3.89E−03 Butene 1.86E−07 2.98E−07 3.77E−06 2.31E−05 Butylene glycol (butane diol) 1.41E−10 6.58E−11 6.67E−11 5.90E−11 butyrolactone 2.45E−10 1.14E−10 1.16E−10 1.02E−10 Cadmium (+II) 2.15E−05 2.16E−05 4.16E−05 1.81E−05 Cadmium (+II) 1.19E−05 1.22E−05 1.17E−05 9.81E−06 Calcium (+II) 1.74E+01 1.78E+01 1.86E+01 1.46E+01 Calcium (+II) 2.90E−01 2.90E−01 2.71E−01 2.46E−01 Carbon, organically bound 3.78E−05 6.39E−05 4.17E−05 5.21E−05 Carbonate 4.50E−04 6.78E−04 7.71E−03 7.18E−04 Cesium 6.08E−07 4.23E−07 4.97E−07 3.77E−07 Chemical oxygen demand (COD) 3.71E+00 3.61E+00 4.79E+00 3.00E+00 Chlorate 4.68E−03 3.88E−03 6.37E−03 3.21E−03


Carbonate 4.50E−04 6.78E−04 7.71E−03 7.18E−04 Cesium 6.08E−07 4.23E−07 4.97E−07 3.77E−07 Chemical oxygen demand (COD) 3.71E+00 3.61E+00 4.79E+00 3.00E+00 Chlorate 4.68E−03 3.88E−03 6.37E−03 3.21E−03 Chloride 9.62E−02 8.47E−02 3.11E+00 7.03E−02 Chloride 7.65E+00 7.62E+00 8.42E+00 6.34E+00 Chlorinated hydrocarbons (unspecified) 8.88E−08 2.13E−07 3.58E−06 2.13E−07 Chlorine (dissolved) 5.85E−05 1.51E−04 7.49E−05 6.81E−05 Chlorobenzene 9.81E−07 4.57E−07 4.63E−07 4.10E−07 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Chloromethane (methyl chloride) 1.74E−08 1.90E−08 −5.10E−09 1.49E−08 Chlorous dissolvent 1.11E−05 7.31E−06 7.49E−06 8.47E−06 Chromium (+III) 1.40E−07 3.34E−07 7.86E−08 1.58E−07 Chromium (+VI) 1.26E−03 1.13E−03 1.46E−03 9.95E−04 Chromium (+VI) 4.39E−04 3.85E−04 4.94E−04 3.39E−04 Chromium (unspecified) 1.15E−05 1.65E−05 1.00E−04 1.44E−05 Chrysene 5.36E−10 1.09E−09 7.00E−10 9.78E−10 Cobalt 4.27E−03 4.11E−03 6.06E−03 3.42E−03 Cobalt 2.95E−05 6.63E−06 2.68E−05 6.44E−06 Copper (+II) 1.42E−02 1.35E−02 1.56E−02 1.13E−02 Copper (+II) 2.49E−05 2.39E−05 7.19E−05 4.95E−05 Cresol (methyl phenol) 4.50E−10 4.65E−10 −3.99E−10 3.44E−10 Cumene (isopropylbenzene) 6.06E−05 3.31E−05 3.95E−05 8.35E−05 Cyanide 2.20E−05 2.53E−05 2.65E−05 1.94E−05 Dichloroethane (ethylene dichloride) 1.47E−06 5.60E−07 1.92E−05 6.48E−07 Dichloromethane (methylene chloride) 1.04E−05 6.90E−06 8.37E−06 6.24E−06 Dichloropropane 3.63E−15 5.58E−15 1.99E−15 4.43E−15 Dichromate


(ethylene dichloride) 1.47E−06 5.60E−07 1.92E−05 6.48E−07 Dichloromethane (methylene chloride) 1.04E−05 6.90E−06 8.37E−06 6.24E−06 Dichloropropane 3.63E−15 5.58E−15 1.99E−15 4.43E−15 Dichromate 1.25E−06 1.22E−06 1.70E−06 1.03E−06 Dissolved organic carbon, DOC (ecoinvent) 1.40E+00 1.38E+00 2.20E+00 1.14E+00 Ecoinvent long-term to freshwater 2.02E+01 2.06E+01 2.15E+01 1.69E+01 Emissions to freshwater 3.55E+01 3.53E+01 3.90E+01 2.93E+01 Ethanol 2.56E−07 1.19E−07 1.20E−07 1.06E−07 Ethene (ethylene) 6.84E−05 2.64E−05 1.52E−05 4.03E−05 Ethyl benzene 1.47E−05 1.04E−05 1.21E−05 9.23E−06 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Ethylene acetate (ethyl acetate) 1.74E−11 8.10E−12 8.19E−12 7.25E−12 Ethylene oxide 5.11E−08 2.92E−08 2.44E−08 2.83E−08 Ethylenediamine 1.58E−09 1.58E−09 1.59E−09 1.58E−09 Fatty acids (calculated as total carbon) 2.24E−03 1.56E−03 1.83E−03 1.39E−03 Fluoranthene 1.59E−10 3.41E−10 1.95E−10 2.80E−10 Fluoride 4.02E−01 4.13E−01 4.26E−01 3.38E−01 Fluorine 1.36E−07 1.48E−07 1.20E−07 1.25E−07 Formaldehyde (methanal) 7.18E−05 1.95E−05 1.57E−05 2.17E−05 Freshwater 1.94E+01 1.97E+01 2.57E+01 1.61E+01 Halogenated organic emissions to freshwater 2.43E−05 1.56E−05 1.18E−04 1.61E−05 Heavy metals to freshwater 2.37E−02 2.17E−02 3.04E−02 1.83E−02 Heavy metals to water (unspecified) 2.87E−07 3.04E−07 2.51E−07 2.40E−07 Hexafluorosilicates 2.19E−06 1.75E−06 2.13E−06 1.66E−06 Hexane (isomers) 4.94E−11 5.14E−11 −4.33E−11 3.79E−11 Hydrocarbons (unspecified) 8.69E−05 7.86E−05 3.77E−04 1.40E−04 Hydrocarbons to freshwater 4.59E−02 2.92E−02 3.60E−02 2.68E−02


2.13E−06 1.66E−06 Hexane (isomers) 4.94E−11 5.14E−11 −4.33E−11 3.79E−11 Hydrocarbons (unspecified) 8.69E−05 7.86E−05 3.77E−04 1.40E−04 Hydrocarbons to freshwater 4.59E−02 2.92E−02 3.60E−02 2.68E−02 Hydrogen chloride 1.21E−08 1.29E−08 1.24E−08 1.04E−08 Hydrogen fluoride (hydrofluoric acid) 1.23E−09 2.42E−09 −9.55E−09 1.96E−09 Hydrogen peroxide 2.22E−06 1.99E−06 2.08E−06 1.97E−06 Hydrogen sulphide 2.12E−03 2.15E−03 2.76E−03 1.77E−03 Hydrogen sulphide 2.66E−06 2.23E−06 3.36E−06 1.99E−06 Hydroxide 2.36E−04 1.27E−03 1.89E−04 1.88E−04 Hypochlorite 8.90E−06 7.61E−06 1.17E−05 7.73E−06 Inorganic emissions to freshwater 1.09E+01 1.07E+01 1.20E+01 8.93E+00 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Inorganic salts and acids (unspecified) 7.77E−04 1.86E−03 3.13E−02 1.86E−03 Iodide 7.65E−11 5.87E−11 2.88E−10 6.55E−11 Iodide 1.08E−04 9.05E−05 1.01E−04 7.74E−05 Iron 2.64E−01 2.66E−01 3.17E−01 2.21E−01 Iron 1.92E−02 1.77E−02 2.57E−02 1.49E−02 Lead (+II) 2.63E−03 1.81E−03 1.91E−03 1.57E−03 Lead (+II) 2.57E−05 3.13E−05 5.79E−05 2.32E−05 Lithium 1.18E−05 4.65E−05 3.05E−05 9.06E−06 Magnesium (+III) 2.24E+00 2.27E+00 2.38E+00 1.87E+00 Magnesium (+III) 3.90E−02 3.88E−02 4.12E−02 3.21E−02 Magnesium chloride −3.07E−09 −1.68E−08 −2.46E−09 −2.45E−09 Manganese (+II) 2.33E−02 2.33E−02 2.52E−02 1.93E−02 Manganese (+II) 6.06E−04 6.05E−04 6.33E−04 4.98E−04 Mercury (+II) 4.11E−06 4.01E−06 1.09E−05 3.70E−06 Mercury (+II) 2.19E−06 2.09E−06 2.62E−06 1.74E−06 Metal ions (unspecific) 3.41E−02 2.68E−03 1.02E−02 2.46E−03 Metal ions (unspecific) 0.00E+00 0.00E+00 −3.56E−05 0.00E+00 Metals (unspecified) 1.88E−05 4.18E−05 1.15E−03 4.18E−05 Methanol 6.61E−04


Metal ions (unspecific) 3.41E−02 2.68E−03 1.02E−02 2.46E−03 Metal ions (unspecific) 0.00E+00 0.00E+00 −3.56E−05 0.00E+00 Metals (unspecified) 1.88E−05 4.18E−05 1.15E−03 4.18E−05 Methanol 6.61E−04 6.35E−04 6.29E−04 5.82E−04 Methyl acrylate 3.78E−07 1.75E−07 1.77E−07 1.57E−07 Methyl amine 8.84E−11 4.12E−11 4.17E−11 3.69E−11 Methyl isobutyl ketone 4.60E−11 1.81E−10 1.19E−10 3.54E−11 Methyl tert-butylether 3.04E−08 1.60E−08 1.01E−08 1.49E−08 Methylformate 2.99E−11 1.39E−11 1.40E−11 1.24E−11 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Molybdenum 3.17E−04 2.98E−04 3.01E−04 2.47E−04 Molybdenum 1.01E−04 8.97E−05 1.00E−04 7.74E−05 Naphthalene 5.99E−08 1.12E−07 7.28E−08 9.66E−08 n-Butyl acetate 1.44E−07 6.71E−08 6.78E−08 6.01E−08 Neutral salts 1.60E−09 1.07E−08 −4.77E−08 6.87E−10 Nickel (+II) 5.30E−03 5.47E−03 1.22E−02 4.62E−03 Nickel (+II) 4.41E−05 4.63E−05 1.04E−04 6.68E−05 Nitrate 1.21E−01 1.24E−01 1.29E−01 1.02E−01 Nitrate 1.66E−01 6.13E−02 6.94E−02 9.12E−02 Nitrite 8.93E−07 6.79E−07 1.52E−04 7.30E−07 Nitrite 1.97E−05 2.02E−05 9.74E−05 1.84E−05 Nitrogen 1.37E−03 1.06E−03 1.59E−03 1.09E−03 Nitrogen organic bounded 2.68E−05 2.03E−05 4.57E−03 2.19E−05 Nitrogen organic bounded 2.05E−04 2.63E−04 3.59E−04 1.81E−04 Oil (unspecified) 4.17E−02 2.62E−02 3.23E−02 2.38E−02 Organic chlorine compounds (unspecified) 2.81E−09 2.81E−09 5.86E−06 2.81E−09 Organic compounds (dissolved) 2.29E−06 2.29E−06 1.26E−04 2.29E−06 Organic compounds (unspecified) 3.31E−09 3.31E−09 1.47E−03


chlorine compounds (unspecified) 2.81E−09 2.81E−09 5.86E−06 2.81E−09 Organic compounds (dissolved) 2.29E−06 2.29E−06 1.26E−04 2.29E−06 Organic compounds (unspecified) 3.31E−09 3.31E−09 1.47E−03 3.31E−09 Organic emissions to freshwater 4.60E−02 2.93E−02 3.78E−02 2.69E−02 Particles to freshwater 1.48E−01 1.68E−01 2.16E−01 1.72E−01 Phenol (hydroxy benzene) 6.40E−05 4.77E−05 5.88E−05 5.23E−05 Phosphate 1.17E−01 1.18E−01 1.25E−01 9.79E−02 Phosphate 7.05E−04 3.82E−04 1.26E−03 3.31E−04 Phosphorus 1.73E−04 8.25E−05 4.12E−04 1.37E−04 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Polychlorinated dibenzo-p-dioxins (2,3,7,8—TCDD) 1.80E−13 1.80E−13 6.17E−08 1.80E−13 Polycyclic aromatic hydrocarbons (PAH, unspec.) 4.84E−06 4.86E−06 3.84E−06 3.46E−06 Potassium 2.48E+00 2.52E+00 2.63E+00 2.08E+00 Potassium 5.19E−01 5.27E−01 5.51E−01 4.35E−01 Propene 2.88E−05 1.70E−05 2.41E−05 6.62E−05 Propylene oxide 3.37E−06 2.70E−06 2.76E−06 2.41E−06 Rubidium 8.55E−06 5.79E−06 6.88E−06 5.19E−06 Scandium 5.89E−06 4.50E−06 8.90E−06 4.41E−06 Scandium 1.40E−06 1.07E−06 2.01E−06 1.05E−06 Selenium 2.87E−04 2.92E−04 3.10E−04 2.41E−04 Selenium 1.42E−04 1.44E−04 1.51E−04 1.19E−04 Silicate particles −2.87E−09 −6.82E−09 −1.21E−07 −7.04E−09 Silicon dioxide (silica) 9.30E−21 9.30E−21 2.41E−19 9.30E−21 Silver 1.46E−07 1.20E−07 7.49E−07 1.88E−07 Silver 6.25E−07 5.22E−07 5.59E−07 3.99E−07 Sodium (+I) 1.05E+00 1.06E+00 1.13E+00 8.76E−01 Sodium (+I) 6.63E−01 5.79E−01 8.14E−01 4.96E−01 Sodium chloride (rock salt) 3.29E−10 1.75E−09 −5.74E−10 3.39E−10


6.25E−07 5.22E−07 5.59E−07 3.99E−07 Sodium (+I) 1.05E+00 1.06E+00 1.13E+00 8.76E−01 Sodium (+I) 6.63E−01 5.79E−01 8.14E−01 4.96E−01 Sodium chloride (rock salt) 3.29E−10 1.75E−09 −5.74E−10 3.39E−10 Sodium formate 1.18E−06 1.17E−06 1.18E−06 1.17E−06 Sodium hypochlorite 7.30E−09 2.43E−08 −4.24E−07 5.77E−09 Soil loss by erosion into water 1.56E−08 4.54E−08 2.09E−08 3.93E−08 Solids (dissolved) 9.07E−02 8.25E−02 2.22E−01 9.13E−02 Solids (suspended) 3.96E+00 3.92E+00 5.63E+00 3.28E+00 Solids (suspended) 1.48E−01 1.68E−01 2.15E−01 1.72E−01 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Strontium 3.98E−04 3.10E−04 1.13E−03 3.09E−04 Strontium 1.91E−03 1.62E−03 1.76E−03 1.38E−03 Sulphate 3.58E+00 3.59E+00 3.80E+00 2.97E+00 Sulphate 1.10E+00 1.12E+00 1.29E+00 9.30E−01 Sulphide 7.68E−05 1.31E−04 9.06E−05 1.14E−04 Sulphite 3.12E−04 3.13E−04 3.43E−04 2.65E−04 Sulphur 2.32E−04 8.72E−05 1.18E−04 7.93E−05 Sulphuric acid 1.56E−06 1.66E−06 1.60E−06 1.34E−06 Suspended solids, unspecified −1.91E−20 −5.54E−20 −3.19E−20 −1.06E−20 Thallium 2.74E−06 2.65E−06 5.83E−06 2.28E−06 Thallium 9.72E−08 8.37E−08 1.28E−07 8.46E−08 Tin (+IV) 3.56E−03 3.52E−03 6.24E−03 2.91E−03 Tin (+IV) 1.14E−06 1.13E−06 1.68E−06 1.09E−06 Titanium 5.92E−05 6.31E−06 1.01E−05 5.80E−06 Toluene (methyl benzene) 7.16E−05 5.16E−05 6.11E−05 4.57E−05 Total dissolved organic bounded carbon 1.41E−01 3.07E−02 3.73E−02 2.80E−02 Total organic bounded carbon 1.44E−01 3.37E−02 4.14E−02 3.83E−02 Trichloromethane (chloroform) 2.26E−09 1.05E−09 1.06E−09 9.41E−10 Tungsten 3.26E−06


bounded carbon 1.41E−01 3.07E−02 3.73E−02 2.80E−02 Total organic bounded carbon 1.44E−01 3.37E−02 4.14E−02 3.83E−02 Trichloromethane (chloroform) 2.26E−09 1.05E−09 1.06E−09 9.41E−10 Tungsten 3.26E−06 2.50E−06 4.43E−06 2.47E−06 Tungsten 1.98E−06 1.52E−06 2.67E−06 1.50E−06 Vanadium (+III) 1.07E−03 9.44E−04 1.66E−03 7.94E−04 Vanadium (+III) 8.97E−06 8.31E−06 1.11E−05 7.14E−06 Vinyl chloride (VCM; chloroethene) 1.71E−07 1.10E−07 7.84E−05 1.13E−07 VOC (unspecified) 2.17E−04 1.51E−04 1.79E−04 1.35E−04 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Xylene (isomers; dimethyl benzene) 5.89E−05 4.21E−05 4.80E−05 3.73E−05 Xylene (meta-Xylene; 1,3-Dimethylbenzene) 3.32E−10 1.31E−09 8.61E−10 2.55E−10 Xylene (ortho-xylene; 1,2-Dimethylbenzene) 2.42E−10 9.54E−10 6.27E−10 1.86E−10 Zinc (+II) 3.46E−02 1.27E−02 4.05E−03 1.23E−02 Zinc (+II) 1.78E−04 1.43E−04 2.18E−04 1.21E−04 Emissions to agricultural soil 2,4-dichlorophenoxyacetic acid (2,4-D) 2.37E−08 2.13E−08 2.21E−08 2.08E−08 Aclonifen 1.38E−05 1.49E−07 8.68E−08 1.37E−07 Aldrin 4.38E−10 2.04E−10 2.05E−10 1.82E−10 Aluminium 6.80E−03 6.79E−03 7.08E−03 5.60E−03 Antimony 1.65E−07 1.65E−07 1.65E−07 1.65E−07 Arsenic (+V) 2.26E−06 2.26E−06 2.34E−06 1.87E−06 Atrazine 1.15E−10 5.34E−11 5.39E−11 4.78E−11 Barium 3.16E−06 3.16E−06 3.16E−06 3.16E−06 Benomyl 1.51E−10 1.36E−10 1.41E−10 1.33E−10 Bentazone 7.05E−06 7.60E−08 4.43E−08 6.98E−08 Cadmium (+II) 5.35E−06 4.66E−06 4.83E−06 3.85E−06 Carbetamide 2.50E−06 3.17E−08 2.06E−08 2.95E−08 Carbofuran


Benomyl 1.51E−10 1.36E−10 1.41E−10 1.33E−10 Bentazone 7.05E−06 7.60E−08 4.43E−08 6.98E−08 Cadmium (+II) 5.35E−06 4.66E−06 4.83E−06 3.85E−06 Carbetamide 2.50E−06 3.17E−08 2.06E−08 2.95E−08 Carbofuran 8.26E−08 7.44E−08 7.72E−08 7.28E−08 Carbon (unspecified) 4.22E−03 4.20E−03 4.91E−03 3.48E−03 Chlorine 1.04E−03 1.04E−03 1.08E−03 8.58E−04 Chlorothalonil 4.78E−06 4.78E−06 4.81E−06 4.76E−06 Chromium (unspecified) 6.94E−05 6.39E−05 6.63E−05 5.27E−05 Cobalt 5.87E−06 5.87E−06 6.10E−06 4.84E−06 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Copper (+II) 4.97E−05 5.40E−05 5.68E−05 4.46E−05 Cypermethrin 6.62E−08 1.13E−08 1.15E−08 1.11E−08 Different pollutants 1.48E−01 1.48E−01 1.53E−01 1.22E−01 Emissions to agricultural soil 2.36E−01 2.14E−01 2.29E−01 1.80E−01 Fenpiclonil 6.65E−07 1.93E−07 1.92E−07 1.92E−07 Glyphosate 7.05E−07 6.56E−07 6.75E−07 5.88E−07 Heavy metals to agricultural soil 1.54E−02 1.53E−02 1.63E−02 1.26E−02 Inorganic emissions to agricultural soil 1.41E−02 1.40E−02 1.46E−02 1.16E−02 Iron 7.65E−03 7.63E−03 8.33E−03 6.30E−03 Lead (+II) 2.29E−05 2.18E−05 2.28E−05 1.81E−05 Linuron 1.06E−04 1.15E−06 6.69E−07 1.05E−06 Mancozeb 6.20E−06 6.20E−06 6.24E−06 6.18E−06 Manganese (+II) 6.51E−03 6.51E−03 6.74E−03 5.36E−03 Mercury (+II) 1.27E−07 3.69E−08 4.22E−08 3.08E−08 Metaldehyde 4.72E−07 7.20E−09 5.10E−09 6.78E−09 Metolachlor 7.71E−04 8.30E−06 4.84E−06 7.63E−06 Metribuzin 2.18E−07 2.18E−07 2.20E−07 2.18E−07 Molybdenum 1.21E−06 1.21E−06 1.27E−06 9.99E−07 Napropamide


4.72E−07 7.20E−09 5.10E−09 6.78E−09 Metolachlor 7.71E−04 8.30E−06 4.84E−06 7.63E−06 Metribuzin 2.18E−07 2.18E−07 2.20E−07 2.18E−07 Molybdenum 1.21E−06 1.21E−06 1.27E−06 9.99E−07 Napropamide 8.36E−07 1.27E−08 9.03E−09 1.20E−08 Nickel (+II) 1.74E−05 1.83E−05 1.90E−05 1.51E−05 Oil (unspecified) 5.35E−02 3.31E−02 3.96E−02 3.01E−02 Orbencarb 1.18E−06 1.18E−06 1.19E−06 1.18E−06 Organic emissions to agricultural soil 5.77E−02 3.73E−02 4.45E−02 3.36E−02 Other emissions to agricultural soil 1.49E−01 1.48E−01 1.53E−01 1.22E−01 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Pesticides to agricultural soil 9.18E−04 2.31E−05 1.91E−05 2.22E−05 Phosphorus 3.19E−03 3.19E−03 3.30E−03 2.63E−03 Pirimicarb 6.67E−07 7.19E−09 4.19E−09 6.61E−09 Strontium 2.72E−08 2.38E−08 2.73E−08 2.12E−08 Sulphur 3.02E−03 3.02E−03 3.18E−03 2.49E−03 Sulphuric acid 2.21E−11 1.03E−11 1.03E−11 9.19E−12 Tebutam 1.98E−06 3.02E−08 2.14E−08 2.84E−08 Teflubenzuron 1.46E−08 1.46E−08 1.47E−08 1.45E−08 Thiram 2.67E−10 2.41E−10 2.50E−10 2.36E−10 Tin (+IV) 3.57E−07 3.55E−07 4.20E−07 3.51E−07 Titanium 4.49E−04 4.49E−04 4.65E−04 3.70E−04 Vanadium (+III) 1.29E−05 1.29E−05 1.33E−05 1.06E−05 Zinc (+II) 5.59E−04 5.43E−04 5.65E−04 4.48E−04 Emissions to industrial soil Aluminium 4.12E−04 2.72E−04 3.31E−04 2.46E−04 Aluminium (+III) 7.37E−07 1.52E−06 9.21E−07 1.28E−06 Ammonia 3.45E−04 6.98E−04 4.33E−04 5.95E−04 Arsenic (+V) 1.65E−07 1.10E−07 1.33E−07 9.90E−08 Barium 2.06E−04 1.36E−04 1.65E−04 1.23E−04 Bromide 9.86E−08 2.03E−07 1.25E−07 1.73E−07 Cadmium


1.28E−06 Ammonia 3.45E−04 6.98E−04 4.33E−04 5.95E−04 Arsenic (+V) 1.65E−07 1.10E−07 1.33E−07 9.90E−08 Barium 2.06E−04 1.36E−04 1.65E−04 1.23E−04 Bromide 9.86E−08 2.03E−07 1.25E−07 1.73E−07 Cadmium (+II) 1.41E−08 1.24E−08 −6.97E−08 1.02E−08 Calcium (+II) 1.66E−03 1.10E−03 1.33E−03 9.91E−04 Carbon (unspecified) 1.24E−03 8.17E−04 9.92E−04 7.39E−04 Chloride 1.15E−04 2.37E−04 1.46E−04 2.02E−04 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Chlorine 2.45E−02 2.31E−02 3.62E−02 2.03E−02 Chromium (+III) 1.12E−10 1.21E−10 1.17E−10 9.63E−11 Chromium (+VI) 1.01E−05 8.42E−06 2.51E−05 7.67E−06 Chromium (unspecified) 2.78E−06 2.76E−06 2.53E−06 2.42E−06 Cobalt 1.15E−08 2.37E−08 1.45E−08 2.02E−08 Copper (+II) 7.43E−06 6.20E−06 1.66E−05 5.72E−06 Different pollutants 4.72E−05 3.15E−05 4.08E−05 2.85E−05 Emissions to industrial soil 1.90E−01 1.90E−01 2.18E−01 1.57E−01 Fluoride 1.53E−01 1.56E−01 1.61E−01 1.27E−01 Glyphosate 2.36E−06 2.00E−06 2.08E−06 1.92E−06 Heavy metals to industrial soil 5.69E−03 4.93E−03 6.12E−03 4.65E−03 Inorganic emissions to industrial soil 1.83E−01 1.84E−01 2.10E−01 1.52E−01 Iron 5.38E−03 4.42E−03 5.74E−03 4.21E−03 Lead (+II) 5.66E−07 5.11E−07 5.24E−07 4.55E−07 Magnesium (+III) 3.31E−04 2.19E−04 2.65E−04 1.98E−04 Manganese (+II) 1.66E−05 1.12E−05 1.34E−05 1.01E−05 Mercury (+II) 1.39E−11 2.78E−11 1.74E−11 2.36E−11 Nickel (+II) 4.07E−07 6.12E−07 4.28E−07 5.06E−07


(+III) 3.31E−04 2.19E−04 2.65E−04 1.98E−04 Manganese (+II) 1.66E−05 1.12E−05 1.34E−05 1.01E−05 Mercury (+II) 1.39E−11 2.78E−11 1.74E−11 2.36E−11 Nickel (+II) 4.07E−07 6.12E−07 4.28E−07 5.06E−07 Oil (unspecified) 3.21E−04 2.24E−04 2.26E−04 1.98E−04 Organic emissions to industrial soil 1.56E−03 1.04E−03 1.22E−03 9.37E−04 Other emissions to industrial soil 4.95E−05 3.35E−05 4.29E−05 3.04E−05 Pesticides to industrial soil 2.36E−06 2.00E−06 2.08E−06 1.92E−06 Phosphorus 5.64E−05 8.56E−05 6.13E−05 7.37E−05 Potassium (+I) 2.28E−04 2.67E−04 2.20E−04 2.32E−04 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Sodium (+I) 1.11E−03 1.13E−03 9.47E−03 1.07E−03 Strontium 2.24E−04 4.45E−04 2.78E−04 3.80E−04 Sulphate 1.09E−05 2.22E−05 1.36E−05 1.88E−05 Sulphide 6.56E−05 1.33E−04 8.17E−05 1.13E−04 Sulphur 2.47E−04 1.63E−04 1.98E−04 1.48E−04 Zinc (+II) 4.51E−05 3.93E−05 4.10E−05 3.50E−05 Emissions to seawater Acenaphthene 5.53E−07 5.96E−07 5.97E−07 4.97E−07 Acenaphthylene 2.10E−07 2.26E−07 2.26E−07 1.88E−07 Acetic acid 1.04E−07 1.96E−07 1.41E−07 1.82E−07 Adsorbable organic halogen compounds (AOX) 9.38E−08 5.75E−08 6.98E−08 5.22E−08 Alkane (unspecified) 3.14E−05 1.96E−05 2.38E−05 1.78E−05 Alkene (unspecified) 2.90E−06 1.81E−06 2.20E−06 1.65E−06 Aluminium (+III) 8.43E−05 6.02E−05 7.50E−05 5.52E−05 Ammonia 4.59E−08 4.73E−08 −4.07E−08 3.51E−08 Ammonium/ammonia 2.93E−05 1.77E−05 2.15E−05 1.60E−05 Analytical measures to sea water 2.64E+00 2.58E+00 3.67E+00 2.13E+00 Anthracene 1.22E−07 1.33E−07 1.32E−07 1.10E−07 Aromatic hydrocarbons (unspecified) 1.36E−04


2.93E−05 1.77E−05 2.15E−05 1.60E−05 Analytical measures to sea water 2.64E+00 2.58E+00 3.67E+00 2.13E+00 Anthracene 1.22E−07 1.33E−07 1.32E−07 1.10E−07 Aromatic hydrocarbons (unspecified) 1.36E−04 8.51E−05 1.03E−04 7.73E−05 Arsenic (+V) 1.42E−06 1.45E−06 1.10E−06 1.17E−06 Barium 4.15E−04 3.63E−04 3.83E−04 3.13E−04 Barytes 4.18E−03 2.83E−03 3.55E−03 2.59E−03 Benzene 1.18E−04 1.17E−04 1.20E−04 9.79E−05 Benzo(a)anthracene 1.25E−07 1.35E−07 1.35E−07 1.13E−07 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Benzofluoranthene 1.41E−07 1.52E−07 1.52E−07 1.26E−07 Beryllium 3.39E−07 3.79E−07 3.70E−07 3.18E−07 Biological oxygen demand (BOD) 1.19E+00 1.16E+00 1.43E+00 9.59E−01 Boron 2.06E−06 1.27E−06 1.48E−06 1.15E−06 Bromine 1.69E−04 1.06E−04 1.28E−04 9.60E−05 Cadmium (+II) 1.51E−06 1.60E−06 1.39E−06 1.28E−06 Calcium (+II) 1.55E−02 7.29E−03 8.32E−03 6.79E−03 Carbonate 1.25E−02 1.42E−02 1.36E−02 1.19E−02 Cesium 2.42E−07 1.51E−07 1.83E−07 1.37E−07 Chemical oxygen demand (COD) 2.89E−02 2.01E−02 2.43E−02 1.80E−02 Chloride 1.10E+00 1.19E+00 1.16E+00 9.99E−01 Chlorous dissolvent 3.82E−13 1.86E−13 1.10E−13 1.71E−13 Chromium (unspecified) 1.28E−06 2.37E−06 1.31E−06 1.59E−06 Chrysene 7.11E−07 7.66E−07 7.67E−07 6.39E−07 Cobalt 5.94E−06 6.63E−06 6.48E−06 5.56E−06 Copper (+II) 4.29E−06 4.29E−06 3.74E−06 3.50E−06 Cresol (methyl phenol) 3.46E−10 3.56E−10 −3.07E−10 2.65E−10 Cyanide 2.77E−06 1.41E−06 1.53E−06 1.27E−06 Emissions to sea water 4.03E+00 3.90E+00


Copper (+II) 4.29E−06 4.29E−06 3.74E−06 3.50E−06 Cresol (methyl phenol) 3.46E−10 3.56E−10 −3.07E−10 2.65E−10 Cyanide 2.77E−06 1.41E−06 1.53E−06 1.27E−06 Emissions to sea water 4.03E+00 3.90E+00 4.98E+00 3.25E+00 Ethyl benzene 3.36E−05 3.26E−05 3.41E−05 2.72E−05 Fatty acids (calculated as total carbon) 1.38E−03 8.65E−04 1.05E−03 7.87E−04 Fluoranthene 1.46E−07 1.58E−07 1.58E−07 1.31E−07 Fluoride 1.08E−04 4.22E−05 4.58E−05 4.00E−05 Glutaraldehyde 5.16E−07 3.50E−07 4.38E−07 3.20E−07 Halogenated organic emissions to sea water 3.82E−13 1.86E−13 1.10E−13 1.71E−13 (continued) Illustrative Case Study: Life Cycle Assessment ...


Table 39.34 (continued) Substance W W/ALU PVC W/C Heavy metals to sea water 9.17E−04 6.89E−04 7.79E−04 6.09E−04 Hexane (isomers) 3.78E−11 3.89E−11 −3.35E−11 2.89E−11 Hydrocarbons (unspecified) 7.85E−05 5.30E−05 6.65E−05 4.86E−05 Hydrocarbons to sea water 1.15E−02 8.14E−03 9.72E−03 7.26E−03 Hypochlorite 9.27E−06 7.93E−06 1.22E−05 8.06E−06 Inorganic emissions to sea water 1.35E+00 1.28E+00 1.26E+00 1.08E+00 Iodide 2.42E−05 1.51E−05 1.83E−05 1.37E−05 Iron 9.41E−05 8.97E−05 8.95E−05 7.58E−05 Lead (+II) 2.58E−06 1.96E−06 2.11E−06 1.71E−06 Magnesium 1.34E−03 8.38E−04 1.01E−03 7.61E−04 Manganese (+II) 1.86E−05 1.53E−05 1.65E−05 1.33E−05 Mercury (+II) 5.02E−08 5.30E−08 5.24E−08 4.45E−08 Methanol 6.30E−06 4.46E−06 5.89E−06 3.99E−06 Methyl tert-butylether 1.62E−06 9.82E−07 1.19E−06 8.92E−07 Molybdenum 5.11E−08 3.11E−08 3.75E−08 2.83E−08 Naphthalene 1.61E−05 1.75E−05 1.74E−05 1.46E−05 Nickel (+II) 3.68E−06 3.92E−06 3.65E−06 3.26E−06 Nitrate 1.33E−04 1.02E−04 1.41E−04 9.56E−05 Nitrite 1.56E−06


5.11E−08 3.11E−08 3.75E−08 2.83E−08 Naphthalene 1.61E−05 1.75E−05 1.74E−05 1.46E−05 Nickel (+II) 3.68E−06 3.92E−06 3.65E−06 3.26E−06 Nitrate 1.33E−04 1.02E−04 1.41E−04 9.56E−05 Nitrite 1.56E−06 1.19E−06 1.91E−06 1.18E−06 Nitrogen 1.17E−06 7.45E−07 9.09E−07 6.75E−07 Nitrogen organic bounded 5.62E−05 2.75E−05 3.35E−05 2.55E−05 Oil (unspecified) 9.32E−03 6.58E−03 7.91E−03 5.87E−03 Organic emissions to sea water 1.15E−02 8.16E−03 9.74E−03 7.27E−03 Other emissions to sea water 1.78E−06 9.29E−07 1.29E−06 8.62E−07 Particles to sea water 3.82E−02 3.54E−02 3.72E−02 2.99E−02 (continued)


Table 39.34 (continued) Substance W W/ALU PVC W/C Pesticides to sea water 1.78E−06 9.29E−07 1.29E−06 8.62E−07 Phenol (hydroxy benzene) 1.74E−04 1.77E−04 1.79E−04 1.49E−04 Phosphate 3.52E−04 1.14E−04 1.16E−04 1.11E−04 Phosphorus 2.00E−06 1.22E−06 1.49E−06 1.11E−06 Polycyclic aromatic hydrocarbons (PAH, unspec.) 1.92E−06 1.20E−06 1.46E−06 1.09E−06 Potassium 1.02E−03 6.38E−04 7.74E−04 5.80E−04 Selenium 7.64E−08 4.64E−08 5.63E−08 4.22E−08 Silver 1.45E−07 9.10E−08 1.10E−07 8.26E−08 Sodium (+I) 7.46E−02 4.69E−02 5.67E−02 4.25E−02 Solids (suspended) 3.82E−02 3.54E−02 3.72E−02 2.99E−02 Strontium 4.40E−04 2.75E−04 3.33E−04 2.50E−04 Sulphate 1.35E−01 1.47E−02 1.48E−02 1.33E−02 Sulphide 2.01E−03 2.31E−03 2.20E−03 1.94E−03 Sulphur 3.78E−06 2.40E−06 2.89E−06 2.17E−06 Tin (+IV) 4.71E−10 4.85E−10 −4.18E−10 3.60E−10 Titanium 2.08E−08 1.50E−08 1.85E−08 1.37E−08 Toluene (methyl benzene) 1.14E−04 1.05E−04 1.10E−04 8.81E−05 Total dissolved organic bounded carbon 8.89E−03 5.95E−03 7.29E−03 5.36E−03 Total


3.60E−10 Titanium 2.08E−08 1.50E−08 1.85E−08 1.37E−08 Toluene (methyl benzene) 1.14E−04 1.05E−04 1.10E−04 8.81E−05 Total dissolved organic bounded carbon 8.89E−03 5.95E−03 7.29E−03 5.36E−03 Total organic bounded carbon 1.41E+00 1.39E+00 2.21E+00 1.15E+00 Tributyltinoxide 1.78E−06 9.29E−07 1.29E−06 8.62E−07 Triethylene glycol 5.35E−06 3.82E−06 5.04E−06 3.43E−06 Vanadium (+III) 4.22E−06 4.64E−06 4.55E−06 3.90E−06 VOC (unspecified) 8.45E−05 5.28E−05 6.41E−05 4.80E−05 Xylene (isomers; dimethyl benzene) 4.32E−05 3.56E−05 3.80E−05 3.12E−05 Zinc (+II) 3.40E−04 2.81E−04 3.15E−04 2.47E−04 Illustrative Case Study: Life Cycle Assessment ...


Table 39.35 Normalised sensitivity coefficients computed for 10% perturbance of amount of wood in the frame Impact category Normalised sensitivity coefficient W W/ALU PVC W/C Land use 8.8E−01 7.5E−01 0.0E+00 7.3E−01 Climate change 5.4E−02 1.7E−02 0.0E+00 1.9E−02 Freshwater ecotoxicity 6.3E−02 2.0E−02 0.0E+00 2.3E−02 Freshwater eutrophication −7.3E−03 −2.2E−03 0.0E+00 −2.7E−03 Human toxicity (cancer) 2.0E−03 6.2E−04 0.0E+00 7.5E−04 Ionising radiation (human health) 7.8E−02 2.3E−02 0.0E+00 2.6E−02 Human toxicity (non-cancer) 6.1E−02 1.9E−02 0.0E+00 2.3E−02 Marine eutrophication 9.1E−03 2.9E−03 0.0E+00 3.2E−03 Resource depletion (minerals, fossils) 3.2E−02 9.8E−03 0.0E+00 8.5E−03 Stratospheric ozone depletion 2.4E−02 7.6E−03 0.0E+00 6.5E−03 Particulate matter formation 2.1E−02 6.3E−03 0.0E+00 7.0E−03 Photochemical ozone formation 1.2E−02 3.7E−03 0.0E+00 4.3E−03 Terrestrial acidification 1.7E−02 5.0E−03 0.0E+00 5.6E−03 Values >0.3 are in italics Table 39.36 Normalised sensitivity


0.0E+00 7.0E−03 Photochemical ozone formation 1.2E−02 3.7E−03 0.0E+00 4.3E−03 Terrestrial acidification 1.7E−02 5.0E−03 0.0E+00 5.6E−03 Values >0.3 are in italics Table 39.36 Normalised sensitivity coefficients computed for 10% perturbance of amount of steel in the frame Impact category Normalised sensitivity coefficient W W/ALU PVC W/C Land use 1.3E−04 9.0E−04 6.3E−02 8.8E−04 Climate change 1.0E−03 2.6E−03 4.3E−02 2.8E−03 Freshwater ecotoxicity 5.1E−03 1.3E−02 1.9E−01 1.5E−02 Freshwater eutrophication 1.8E−04 4.4E−04 7.9E−03 5.3E−04 Human toxicity (cancer) 2.4E−04 5.6E−04 1.0E−02 6.8E−04 Ionising radiation (human health) 6.7E−03 1.6E−02 2.8E−01 1.8E−02 Human toxicity (non-cancer) 6.0E−03 1.5E−02 2.2E−01 1.7E−02 Marine eutrophication 5.1E−04 1.2E−03 2.3E−02 1.4E−03 Resource depletion (minerals, fossils) 3.5E−02 8.4E−02 6.4E−01 7.3E−02 Stratospheric ozone depletion 2.7E−03 6.6E−03 1.2E−01 5.7E−03 Particulate matter formation 2.3E−03 5.4E−03 9.6E−02 6.0E−03 Photochemical ozone formation


fossils) 3.5E−02 8.4E−02 6.4E−01 7.3E−02 Stratospheric ozone depletion 2.7E−03 6.6E−03 1.2E−01 5.7E−03 Particulate matter formation 2.3E−03 5.4E−03 9.6E−02 6.0E−03 Photochemical ozone formation 5.6E−04 1.3E−03 2.4E−02 1.5E−03 Terrestrial acidification 1.4E−03 3.5E−03 7.0E−02 3.8E−03 Values >0.3 are in italics


Table 39.37 Normalised sensitivity coefficients computed for 10% perturbance of amount of glass in the pane Impact category Normalised sensitivity coefficient W W/ALU PVC W/C Land use 6.2E−03 1.7E−02 6.3E−02 2.5E−02 Climate change 2.3E−02 2.3E−02 2.1E−02 3.8E−02 Freshwater ecotoxicity 8.8E−03 9.1E−03 7.3E−03 1.6E−02 Freshwater eutrophication 1.6E−03 1.6E−03 1.5E−03 2.9E−03 Human toxicity (cancer) 2.6E−03 2.5E−03 2.4E−03 4.6E−03 Ionising radiation (human health) 1.1E−01 1.1E−01 9.8E−02 1.8E−01 Human toxicity (non-cancer) 9.1E−03 9.4E−03 7.3E−03 1.7E−02 Marine eutrophication 2.8E−02 2.9E−02 2.7E−02 4.8E−02 Resource depletion (minerals, fossils) 4.5E−01 4.5E−01 1.8E−01 5.9E−01 Stratospheric ozone depletion 6.2E−02 6.4E−02 6.2E−02 8.3E−02 Particulate matter formation 5.4E−02 5.4E−02 4.6E−02 9.0E−02 Photochemical ozone formation 3.4E−02 3.4E−02 3.1E−02 5.8E−02 Terrestrial acidification 5.7E−02 5.7E−02 4.8E−02 9.5E−02 Values >0.3 are in italics Table 39.38 Normalised sensitivity


4.6E−02 9.0E−02 Photochemical ozone formation 3.4E−02 3.4E−02 3.1E−02 5.8E−02 Terrestrial acidification 5.7E−02 5.7E−02 4.8E−02 9.5E−02 Values >0.3 are in italics Table 39.38 Normalised sensitivity coefficients computed for 10% perturbance of U-values Impact category Normalised sensitivity coefficient W W/ALU PVC W/C Land use 8.2E−01 8.6E−01 7.9E−01 7.7E−01 Climate change 9.0E−01 9.5E−01 7.9E−01 9.2E−01 Freshwater ecotoxicity 1.0E+00 1.0E+00 9.9E−01 1.0E+00 Freshwater eutrophication 9.9E−01 9.9E−01 9.9E−01 9.9E−01 Human toxicity (cancer) 5.7E−01 5.7E−01 5.4E−01 5.2E−01 Ionising radiation (human health) 9.0E−01 9.5E−01 7.7E−01 9.2E−01 Human toxicity (non-cancer) 9.0E−01 9.4E−01 9.0E−01 8.7E−01 Marine eutrophication 3.8E−01 3.9E−01 1.6E−01 2.8E−01 Resource depletion (minerals, fossils) 5.5E−01 5.7E−01 5.8E−01 4.1E−01 Stratospheric ozone depletion 8.3E−01 8.5E−01 7.5E−01 7.7E−01 Particulate matter formation 9.1E−01 9.2E−01 8.8E−01 8.7E−01 Photochemical ozone formation 8.2E−01 8.3E−01


5.7E−01 5.8E−01 4.1E−01 Stratospheric ozone depletion 8.3E−01 8.5E−01 7.5E−01 7.7E−01 Particulate matter formation 9.1E−01 9.2E−01 8.8E−01 8.7E−01 Photochemical ozone formation 8.2E−01 8.3E−01 7.3E−01 7.6E−01 Terrestrial acidification 8.2E−01 8.6E−01 7.9E−01 7.7E−01 Values >0.3 are in italics Illustrative Case Study: Life Cycle Assessment ...


Benini, L., Mancini, L., Sala, S., Schau, E., Manfredi, S., Pant, R.: Normalisation method and data for environmental footprints. Report EUR 26842 EN. Ispra (2014) doi:10.2788/16415 Ciroth, A.: Refining the pedigree matrix approach in ecoinvent: towards empirical uncertainty factors. LCA Discussion Forum Zürich, 13 Sept (2013) Connolly, D., Mathiesen, B.V., Østergaard, P.A., Möller, B., Nielsen, S., Lund, H., et al.: Heat Roadmap Europe 1: First Pre-Study for the EU27 (2012) DMI: Danish Meteorological Institute. Available at http://www.dmi.dk/dmi/index/ (Accessed May 2016) (2016) Dreicer, M., Tort, V., Manen, P.: ExternE, externalities of energy, vol. 5 9 Nuclear, Centre d’étude sur l’Evaluation de la Protection dans le domaine 10 nucléaire (CEPN). In: European Commission DGXII (ed) Science, 11 Research and development JOULE, Luxembourg (1995) Dyrelund, A., Lund, H.: Danish heating sector can be CO2 neutral before 2030


In: European Commission DGXII (ed) Science, 11 Research and development JOULE, Luxembourg (1995) Dyrelund, A., Lund, H.: Danish heating sector can be CO2 neutral before 2030. EuroHeat&Power 6, 34–37 (2009) EC-JRC: ILCD Handbook: General Guide for Life Cycle Assessment—Provisions and Action Steps, 1st edn. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy (2010) EC-JRC: Recommendations based on existing environmental impact assessment models and factors for life cycle assessment in European context. ILCD Handbook—International Reference Life Cycle Data System, European Union EUR24571EN. ISBN: 978-92-79-17451-3. http://lct.jrc.ec. europa.eu/assessment/assessment/projects#consultation_impact (2011). Accessed Jan 2012 EC-JRC: Characterization factors of the ILCD recommended life cycle impact assessment methods. Database and Supporting Information. EUR25167


Accessed Jan 2012 EC-JRC: Characterization factors of the ILCD recommended life cycle impact assessment methods. Database and Supporting Information. EUR25167. http://lct.jrc.ec.europa.eu/ (2012) Ecoinvent: Ecoinvent Data v2.2.Final reports Ecoinvent v2.2 No. 1–25. Swiss Centre for Life Cycle Inventories, Dübendorf (2010) Energynet: Technology Data for Energy Plants—Generation of Electricity and District Heating, Energy Storage and Electricity Carrier Generation and Conversion. doi:ISBN: 978-87-7844940-5 (2012) Eurostat: Treatment of waste by waste category, hazardousness and waste operations [WWW Document]. URL http://ec.europa.eu/eurostat/web/products-datasets/-/env_wastrt (Accessed 19 Sept 2016) (2016) Frischknecht, R., Braunschweig, A., Hofstetter, P., Suter, P.: Modelling human health effects of radioactive releases in life cycle impact assessment. Environ. Impact Assess. Rev


Environ. Impact Assess. Rev. 20, 159–189 (2000) Frischknecht, R., Steiner, R., Jungbluth, N.: The Ecological Scarcity Method—Eco-Factors: A method for impact assessment in LCA. 2009, Federal Office for the Environment FOEN: Zürich und Bern [WWW Document] (2006) Frischknecht, R., Althaus, H., Bauer, C., Doka, G., Heck, T., Jungbluth, N., Kellenberger, D., Nemecek, T.: The environmental relevance of capital goods in life cycle assessments of products and services. Int. J. Life Cycle Assess. 12, 7–17 (2007) Goedkoop, M.J., Heijungs, R., Huijbregts, M., De Schryver, A., Struijs, J., Van Zelm, R.:ReCiPe 2008. A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. First edition report I: characterization, 6 Jan 2009. http://www.lcia-recipe.net/


First edition report I: characterization, 6 Jan 2009. http://www.lcia-recipe.net/. Accessed July 2013 (2009) Greco, S.L., Wilson, A.M., Spengler, J.D., Levy, J.I.: Spatial patterns of mobile source particulate matter emissions-to-exposure relationships across the United States. Atmos. Environ. 41, 1011–1025 (2007) Guinée, J.B., Gorrée, M., Heijungs, R., Huppes, G., Kleijn, R., de Koning, A., Van Oers, L., Wegener Sleeswijk, A., Suh, S., Udo de Haes, H., De Bruijn, J.A., Van Duin, R., Huijbregts, M.A.J.: Handbook on Life Cycle Assessment: Operational Guide to the ISO Standards. Series: Eco-efficiency in industry and science. Kluwer Academic Publishers, Dordrecht (Hardbound, ISBN 1-4020-0228-9; Paperback, ISBN 1-4020-0557-1) (2002)


Hauschild, M.Z., Goedkoop, M., Guinee, J., Heijungs, R., Huijbregts, M., Jolliet, O., Margni, M., De Schryver, A., Humbert, S., Laurent, A., Sala, S., Pant, R.: Identifying best existing practice for characterization modeling in life cycle impact assessment. Int. J. Life Cycle Assess. 18, 683–697 (2013) ISO: ISO 14044:2006 Environmental Management—Life Cycle Assessment—Requirements and Guidelines. International Standards Organization (2006) Jolliet, O., Rosenbaum, R.K., Laurent, A.: Life cycle risks and impacts of nanotechnologies. Chapter 11 In: Malsch I., Emond C. (eds.) Nanotechnology and Human Health, CRC Press pp. 213–278 (2014). Print ISBN: 978-0-8493-8144-7, eBook ISBN: 978-0-8493-8145-4. https:// doi.org/10.1201/b15341-18 Laurent, A., Lautier, A., Rosenbaum, R.K., Olsen, S.I., Hauschild, M.Z.: Normalisation references for Europe and North America for application with USEtox characterisation factors. Int. J. Life Cycle Assess


Int. J. Life Cycle Assess. 16(8), 728–738 (2011) Milà i Canals, L., Romanyà, J., Cowell, S.: Method for assessing impacts on life support functions (LSF) related to the use of “fertile land” in life cycle assessment (LCA). J. Clean. Prod. 15, 1426–1440 (2007) Natural Resources Canada: Improving window energy efficiency. URL http://oee.nrcan.gc.ca/sites/ oee.nrcan.gc.ca/files/pdf/residential/personal/documents/windows-eng.pdf (Accessed June 2016) (2015) PlasticsEurope Database. URL: http://www.plasticseurope.org/. Accessed 21 Nov 2016 Posch, M., Seppälä, J., Hettelingh, J.P., Johansson, M., Margni, M., Jolliet, O.: The role of atmospheric dispersion models and ecosystem sensitivity in the determination of characterisation factors for acidifying and eutrophying emissions in LCIA. Int. J. Life Cycle Assess


Int. J. Life Cycle Assess. 13, 477–486 (2008) Prommer, H., Tuxen, N., Bjerg, P.L.: Fringe-controlled natural attenuation of phenoxy acids in a landfill plume: integration of field-scale processes by reactive transport modeling. Environ. Sci. Technol. 40, 4732–4738 (2006) Rabl, A., Spadaro, J.V.: The RiskPoll software, version is 1.051 (dated August 2004). www. arirabl.com (2004). Accessed Jan 2012 Rosenbaum, R.K., Bachmann, T.M., Gold, L.S., Huijbregts, M.A.J., Jolliet, O., Juraske, R., Koehler, A., Larsen, H.F., MacLeod, M., Margni, M., McKone, T.E., Payet, J., Schuhmacher, M., van de Meent, D., Hauschild, M.Z.: USEtox-the UNEP-SETAC toxicity model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int. J. Life Cycle Assess


Int. J. Life Cycle Assess. 13, 532–546 (2008) doi:10.1007/s11367-008-0038-4 Seppälä, J., Posch, M., Johansson, M., Hettelingh, J.P.: Country-dependent characterisation factors for acidification and terrestrial eutrophication based on accumulated exceedance as an impact category indicator. Int. J. Life Cycle Assess. 11, 403–416 (2006) Steinmann, Z.J.N., Hauck, M., Karuppiah, R., Laurenzi, I.J., Huijbregts, M.A.J.: Int. J. Life Cycle Assess. 19, 1146–1155 (2014) Struijs, J., Beusen, A., van Jaarsveld, H., Huijbregts, M.A.J.: ReCiPe 2008 A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. Report I: Characterisation factors, 1st edn


Report I: Characterisation factors, 1st edn. (2009) The ecoinvent database, v2.2; ecoinvent: Zürich (2010) Van Zelm, R., Huijbregts, M.A.J., Den Hollander, H.A., Van Jaarsveld, H.A., Sauter, F.J., Struijs, J., Van Wijnen, H.J., Van de Meent, D.: European characterization factors for human health damage of PM10 and ozone in life cycle impact assessment. Atmos. Environ. 42, 441–453 (2008) Disclaimer This report is based on an LCA that was delivered as part of the requirements to pass the MSc course “Life Cycle Assessment of Products and Systems”, given at the Department of Management Engineering of the Technical University of Denmark. The report has been reworked Illustrative Case Study: Life Cycle Assessment ...


somewhat to serve as an example report to illustrate to students how to perform and how to structure the report on an LCA according to the requirements of ISO 14044:2006 (ISO 2006) and the reporting template in Chap. 38 from the ILCD Handbook (EC-JRC 2010). The reader should note that it is not the intention to provide an example of “the perfect LCA study” or “the perfect LCA report”. The results of this LCA should not be directly used to inform a choice between windows, not even in Denmark. As a result of students collaborating in project teams of 5–6 members during one semester (*13 weeks, 10 ECTS MSc course), this is primarily the result of a well-achieved learning experience from LCA beginners. Its main purpose is to illustrate reporting, not good or best LCA practice, which is why many details are not necessarily handled the way they should be according to part II of the book, because there are many constraints on what can be achieved in one semester of learning LCA


LCA studies and reports produced by experienced LCA professionals can have a wide range of different structures and follow different emphases depending on the goal of the study. Author Biographies Mikołaj Owsianiak Involved in development and application of life cycle impact assessment methods in sustainability assessment of technologies. Has worked on issues associated with: soils (remediation), metals (toxic impact assessment), biodiesel (fate in the environment), and carbonaceous materials (biochar and hydrochar). Anders Bjørn Part of the LCA community since the early 2010s. Main focus is interpretations of sustainability and integration of sustainability targets in LCA to enable absolute sustainability assessments. Heidi B. Bugge Working with life cycle thinking in relation to ecolabeling since mid-2000s. LCA experience mostly by applying LCAs in developing ecolabel criteria for the Nordic Swan


Heidi B. Bugge Working with life cycle thinking in relation to ecolabeling since mid-2000s. LCA experience mostly by applying LCAs in developing ecolabel criteria for the Nordic Swan. Here focusing on how to use environmental hot spots in the life cycle to set relevant and steerable ecolabel requirements. Sónia M. Carvalho Former student at the Technical University of Denmark. Leise Jebahar Engineer specialised in LCA applied on circular economy, focusing mainly on the effect of different end-of-life scenarios and cascading and is working with waste management concerning waste from households, industries and the built environment. Jon Rasmussen Former student at the Technical University of Denmark. Caroline M. White Former student at the Technical University of Denmark. Stig Irving Olsen LCA expert both as researcher and as consultant. Involved in the development of LCA methodologies since mid 1990s. Contributed to UNEP/SETAC working groups on LCIA methodology


Stig Irving Olsen LCA expert both as researcher and as consultant. Involved in the development of LCA methodologies since mid 1990s. Contributed to UNEP/SETAC working groups on LCIA methodology. Main LCA interest is human toxicity impacts, emerging technologies, and decision making.


Chapter 40 Overview of Existing LCIA Methods—Annex to Chapter 10 Ralph K. Rosenbaum Abstract The chapter gives an overview and a systematic comparison of a selection of the most used Life Cycle Impact Assessment (LCIA) methods, focusing on methods that have been implemented and made available in LCA software. Currently available midpoint and endpoint characterisation methodologies are presented and their specific properties are qualitatively compared in detailed tables


Currently available midpoint and endpoint characterisation methodologies are presented and their specific properties are qualitatively compared in detailed tables. Learning objectives After studying this chapter the reader should be able to: • Name and summarise the LCIA methods most relevant in current LCA practice • Identify and distinguish their main features, properties, advantages and limitations • Select one or several adequate LCIA method(s) for a given goal and scope definition • Discuss the (apparent) developments from earlier LCIA methods to the current state-of-the-art The contents of this chapter have been modified from Rosenbaum, R.K.: Selection of impact categories, category indicators and characterisation models in goal and scope definition, appearing as Chapter 2 of Curran MA (ed.) LCA Compendium—The Complete World of Life Cycle Assessment—Goal and scope definition in Life Cycle Assessment pp. 63–122. Springer, Dordrecht (2017)


63–122. Springer, Dordrecht (2017). Most notably, the LCIA method comparison tables have been updated for IMPACT World+ and LC-Impact. R.K. Rosenbaum (&) IRSTEA, UMR ITAP, ELSA Research Group and ELSA-PACT—Industrial Chair for Environmental and Social Sustainability Assessment, 361 rue Jean-François Breton, BP 5095, 34196, Montpellier, France e-mail: ralph.rosenbaum@irstea.fr © Springer International Publishing AG 2018 M.Z. Hauschild et al. (eds.), Life Cycle Assessment, DOI 10.1007/978-3-319-56475-3_40


40.1 An essential element in the choice of category indicators or entire LCIA methods is sufficient knowledge and overview of their (most important) characteristics. However, this knowledge is not easy to come by or readily available in the literature, without having to study the documentation of each method respectively. A profound comparison of existing LCIA methods was performed by Hauschild et al. (2013) for the establishment of recommended LCIA models for the European context. The results can be found in the ILCD handbook on LCIA recommended practice in Europe (EC-JRC 2011) and will provide some helpful guidance, including for the non-European context, as it contains both facts and evaluative expert judgements on the models, with only the latter being partially specific to the European context. Taking Hauschild et al.’s work as a starting point, the following tables provide a complete and updated qualitative comparison of widely used LCIA methods available in current LCA software


Taking Hauschild et al.’s work as a starting point, the following tables provide a complete and updated qualitative comparison of widely used LCIA methods available in current LCA software. Only models integrated into LCIA methods (and thus readily available for practitioners in LCA software and databases) are represented here with the exception of the latest methods IMPACT World+ and LC-Impact, which by the time of writing (mid 2017) were not yet fully implemented into LCA software but readily available to be imported manually (see respective websites for further information). It is worth mentioning that the authors of the LC-Impact method intend to provide both midpoint and endpoint characterisation factors (CFs). So far, endpoint CFs have been published, while midpoint CFs are not yet available but foreseen for later publication and thus not included in Table 40.1


So far, endpoint CFs have been published, while midpoint CFs are not yet available but foreseen for later publication and thus not included in Table 40.1. During the finalisation of this chapter, a major update of the ReCiPe 2008 method, called ReCiPe 2016, has been published but could unfortunately not be included in the update of the comparison tables, so that only the latest version of ReCiPe 2008 (from 2013) is described in Tables 40.1 and 40.2. The Japanese LCIA method LIME has been updated to version 3.0, but to the author’s knowledge no documentation in another language than Japanese is available, which is why only version 2.0 is covered here. Further models (published but not yet integrated into LCIA methods) are discussed in the ILCD handbooks on LCIA (EC-JRC 2010, 2011) and of course in current scientific literature


Further models (published but not yet integrated into LCIA methods) are discussed in the ILCD handbooks on LCIA (EC-JRC 2010, 2011) and of course in current scientific literature. Models not based on mechanistic cause-effect chain modeling, such as regulatory-based distance-to-target approaches like the Swiss Eco-scarcity method (Frischknecht et al. 2006) or the MEEuP approach based on emission limit values (Kemna et al. 2005) were also excluded from this overview. Such approaches require specific interpretation, different from cause-effect-based methods, due to their non-mechanistic and often policy-priority-based nature. If a potential environmental impact is expressed based on its difference to a political target, the resulting impact score will essentially represent the importance of an emission or resource extraction relative to established political target limits but not necessarily relative to its environmental relevance (depending on how closely R.K. Rosenbaum


political targets are related to environmental issues). This is because political targets are established based on a number of influences and lobbies, and will vary substantially from one country to another, especially on a global scale. Compared to a mechanistic modelling approach, political targets are not comprehensive enough and will only cover a selected number of known issues. In other words, a number of potentially important environmental issues may not (yet) be represented in politically set targets and will therefore not be evaluated when applying a distance-to-target approach. Political thresholds for some emissions, e.g. toxic chemicals, may furthermore be established based on risk measures instead of best (average) estimates or potential impacts and thus contain (inconsistent) safety values and other potential biases


However, in specific cases, where the goal of a study is to evaluate the environmental profile of a product, service or organisation, or the consequences of an environmental policy towards their relevance regarding political targets, such a method is a meaningful choice among available LCIA methods. An important point to keep in mind is that the implementation of a given LCIA method may vary from one software to another (due to the need to adapt the LCIA method to the architecture and structure of the software, which may in some cases involve a re-interpretation) and not always all options proposed by LCIA developers may be implemented in each software. Hence, depending on which software you are using, you may find smaller (only in rare cases larger) deviations when it comes to implemented archetypes and other details and options. The descriptions in Tables 40.1 and 40.2 are mostly based on the original proposals by the LCIA method developers


The descriptions in Tables 40.1 and 40.2 are mostly based on the original proposals by the LCIA method developers. The content of these tables is restricted to facts, while judgements on quality etc. were excluded as far as possible. For a further evaluation including expert judgements, e.g. on scientific validity, environmental relevance, or stakeholder acceptance, the reader is referred to the ILCD handbook on LCIA (EC-JRC 2010, 2011). Given the large amount of information contained in these tables, mistakes cannot be excluded, but as much information as possible has been verified in the original documentation of the methods (and if required corrected when taken from the ILCD handbook, which contains a number of small errors in the method descriptions). LCIA methods are under constant improvement and may be updated and corrected over time


LCIA methods are under constant improvement and may be updated and corrected over time. Consequently, the information contained in Tables 40.1 and 40.2 is a snapshot of the situation and available information by the time of writing of this chapter (mid 2017) and is likely to change over time. Tables 40.1 and 40.2 contain a qualitative comparison of a number of specific properties of available LCIA methods. Each column represents an LCIA method, while the rows are structured by impact category. This allows easy identification of the differences (and similarities) in these properties per impact category among methods and choosing the most suitable one for a given goal and scope. Table 40.1 lists the most important midpoint characterisation methods, while Table 40.2 contains methods providing endpoint or damage assessment characterisation factors. A number of methods were published before 2000, but are not included in this Overview of Existing LCIA Methods—Annex to Chapter 10


overview as they have been replaced by their authors with newer versions or must be considered outdated and obsolete for today’s LCA practice. As a support to using and interpreting the tables, a brief description of each property reported in the tables and of its meaning are given hereafter (note that all properties may not necessarily apply to each impact category): • Aspects/diseases/ecosystems considered: lists which kinds of impacts are considered, e.g. which kinds of resources (for resource use), or which kinds of diseases (for human health), or which ecosystems out of freshwater, marine water, and terrestrial ecosystems are covered by a method. • Characterisation model: gives the name (if applicable) and points to the main reference(s) for the corresponding characterisation model used to calculate the characterisation factors for a given impact category and LCIA method. • Human health effects: details about which kind of health effects were included


• Human health effects: details about which kind of health effects were included. • Ecosystem effects: details about which kind of effects on ecosystems were included. • Biotic resources effects: consideration of potential impacts on biotic resources is still a rare property, but is included in some methods and may be an important point for some studies. • Fate modeling: details about how the modeling of the distribution of an emission in the environment is considered (the concept of fate may also be applied for modeling a part of the cause-effect chain of a resource extraction instead of an emission). • Exposure modeling: details about how the transfer of a substance from the environment into a given target (e.g. human population or an ecosystem) is considered (the concept of exposure may also be applied for modeling a part of the cause-effect chain of a resource extraction instead of an emission)


human population or an ecosystem) is considered (the concept of exposure may also be applied for modeling a part of the cause-effect chain of a resource extraction instead of an emission). • Effect modeling: details about how the effect(s) of a substance transferred from the environment into a given target (e.g. human population or an ecosystem) is considered (the concept of exposure may also be applied for modeling a part of the cause-effect chain of a resource extraction instead of an emission). • Marginal/average: these terms are used in different ways and meanings in the LCA context; here they describe two different impact modeling principles or choices: a marginal impact modeling approach represents the additional impact per additional unit emission/resource extraction within a product system on top of an existing background impact which is not coming from the modelled product system. This allows e.g


This allows e.g. considering non-linearities of impacts depending on local conditions like high or low background concentrations to which the product systems adds an additional emission/resource extraction). An average impact modeling approach is strictly linear and represents an average impact independent from existing background impacts, which is similar to dividing the overall effect by the overall emissions. • Emission compartment(s): for which emission compartment(s) the method provides characterisation factors. R.K. Rosenbaum


• Time horizon: details on the time horizon(s) used to calculate potential impacts. A prominent example are the GWP-time horizons of 20, 100, and until IPCC (2007a) also 500 years. The essential difficulty with time horizons is that a short time horizon may exclude an important amount of future potential impacts from the assessment (risking violating the sustainability principle of inter-generational equality). Whereas, a long time horizon may “dilute” large short-term impacts over a longer time (i.e. making them look smaller), which would give a small but permanently continuing impact a similar impact potential than that of a large impact occurring within a short time. In other words, it would give the same importance to a large impact within one generation as to a small impact affecting several generations of humans for example


In other words, it would give the same importance to a large impact within one generation as to a small impact affecting several generations of humans for example. An important and widely ignored issue in current LCA practice is the inconsistency among time horizons between different impact categories, with some representing 100 years and others several hundreds to even thousands of years. An inconsistency that, in principle, would disallow adding up endpoint scores into areas of protection or normalising and weighting midpoint scores. Its importance, however, needs further study and most likely it is far from being a large source of uncertainty relative to other issues in LCA. • Region modelled/valid: details on which region(s) has been modelled (i.e. which region is represented by the parameters used in the characterisation model)


• Region modelled/valid: details on which region(s) has been modelled (i.e. which region is represented by the parameters used in the characterisation model). A model may either represent one or several specific region(s) (the larger the region, the more averaging is applied and the less specific the model is representing a region) or a global (or sometimes continental) average, also referred to as generic. • Level of spatial differentiation: if the characterisation model represents more than one region, it is spatially (or geographically) differentiated. The level of differentiation may range from coarse (e.g. continental, sub-continental, countries, etc.) to fine (e.g. small grid-cells of a few km or sub-watersheds). The finer the spatial differentiation, the better a model captures variability of local conditions which may influence potential impacts by up to several orders of magnitude for some impact categories, such as toxicity or water consumption


• Number of substances/land use types/resources: the more substances or land-use types/resources are covered by a method, the more likely it will consider all important (=highly contributing to impact) emissions or resource extractions of a product system. A missing characterisation factor for any given elementary flow automatically leads to its omission in the impact profile. • Unit: the dimension of the indicator. • “n/a” means that information was not available or that a property is not applicable. Not all these properties may be of equal relevance for choosing an LCIA method for each practitioner or study, but are intended to represent the most relevant and fact-based properties. Overview of Existing LCIA Methods—Annex to Chapter 10


Table 40.1 Detailed characteristics of available midpoint characterisation methods [extended and updated from ILCD handbook on LCIA (EC-JRC 2010, 2011; Sala et al. 2016)] CML-IA TRACI 1.0 IMPACT 2002+ EDIP 2003 ReCiPe 2008 TRACI 2 ILCD/PEF/OEF IMPACT World+ Reference Guinée et al. (2002) Bare et al. (2003) Jolliet et al. (2003) Hauschild and Poƫng (2005); Poƫng and Hauschild (2005)Hauschild and Wenzel (1998) Goedkoop et al. (2012) Bare (2011) EC-JRC (2011) Bulle et al. (in review) Website hƩps://cml.leiden.edu/ soŌware/data-cmlia.html hƩps://epa.gov/chemicalresearch/tool-reducƟonand-assessment-chemicalsand-other-environmentalimpacts-traci hƩps://www.quanƟsintl.com/pdf/IMPACT2002_ UserGuide_for_vQ2.21.pdf hƩps://lcia-recipe.net hƩps://epa.gov/chemicalresearch/tool-reducƟonand-assessment-chemicalsand-other-environmentalimpacts-traci hƩps://eplca.jrc.ec.europa


eu/?page id=86 hƩps://impactworldplus.org Update of CML 1992 EDIP 97 CML-IA TRACI 1.0 IMPACT 2002+, EDIP 2003, and LUCAS UncertainƟes quanƟfied ParƟally, spaƟal variability for each CF1 NormalisaƟon factors Netherlands (1997), Europe (1995), World (1995), producƟon-based) (Huijbregts et al. 2003) USA and USA+Canada (producƟon-based) reference year 2005 (LauƟer et al. 2010) Western Europe (producƟon-based) Europe (producƟon-based), reference year 2004 (Laurent et al. 2011) Europe, global (producƟonbased), reference year 2000 (Sleeswijk et al. 2008) USA and USA+Canada (producƟon-based) reference year 2008 (Ryberg et al


2011) Europe, global (producƟonbased), reference year 2000 (Sleeswijk et al. 2008) USA and USA+Canada (producƟon-based) reference year 2008 (Ryberg et al. 2014) European, global (producƟon-based) No NormalizaƟon recommended at the midpoint level WeighƟng scheme Panel-based (~80 replies), deriving cultural perspecƟves: Individualist, Hierarchist, and Egalitarian based on HofsteƩer (1998) For emissions based on poliƟcal targets for 2000, expressed as PoliƟcal Target Person-Equivalents (PET), for resource consumpƟon based on person reserves (PR) for known reserves in 1990 Panel-based (~80 replies), deriving cultural perspecƟves: Individualist, Hierarchist, and Egalitarian based on HofsteƩer (1998) No weighƟng recommended at the midpoint level Climate change CharacterisaƟon model GWP2 from IPCC3 (2007a) GWP2 from IPCC3 (2001) GWP2 from IPCC3 (2001) GWP2 from IPCC3 (2001) GWP2 from IPCC3 (2007a) GWP2 from IPCC3 (2007a) GWP2 from IPCC3 (2007a) GWP2 and GTP4 from IPCC3 2013 (Myhre et al


2013) Indicator RadiaƟve forcing RadiaƟve forcing RadiaƟve forcing RadiaƟve forcing RadiaƟve forcing RadiaƟve forcing RadiaƟve forcing RadiaƟve forcing Marginal/average Average Average Average Average Average Average Average Average Time horizon(s) [y] GWP100 for short-term, GTP100 for long-term impacts Region modelled Global Global Global Global Global Global Global Global No


of substances Unit CO2 equivalents CO2 equivalents CO2 equivalents CO2 equivalents CO2 equivalents CO2 equivalents CO2 equivalents CO2 equivalents Ozone depleƟon CharacterisaƟon model(s) ODP5 from WMO6 (2003) ODP5 from WMO6 (1999) ODP5 from WMO6 (2003) ODP5 from WMO6 (2003) ODP5 from WMO6 (2003) ODP5 from WMO6 (2003) ODP5 from WMO6 (2003) ODP5 from WMO6 (2014) Indicator Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Global degradaƟon in stratospheric O3 concentraƟon Marginal/average Average Average Average Average Average Average Average Average Time horizon(s) [y] Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Region modelled Global Global Global Global


Average Average Average Average Average Average Average Average Time horizon(s) [y] Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Region modelled Global Global Global Global Global Global Global Global No


of substances Unit 7CFC-11 equivalents 7CFC-11 equivalents 7CFC-11 equivalents 7CFC-11 equivalents 7CFC-11 equivalents 7CFC-11 equivalents 7CFC-11 equivalents 7CFC-11 equivalents (continued) R.K. Rosenbaum


Table 40.1 (continued) ParƟculate maƩer formaƟon / Respiratory inorganics CharacterisaƟon model PM10 emissions to air considered in human toxicity impact category De Hollander et al. (1999) HofsteƩer (1998) van Zelm et al. (2008) Same as TRACI 1.0 8Humbert (2009) Humbert et al. (2011) for fate and exposure and Gronlund et al. (2015) for effects Fate/exposure modeling CALPUFF model, mechanisƟc, closed, mulƟmedia LCA model Empirical data MechanisƟc, opƟon for low, undefined and high stack emission 8Humbert (2009) (USEtox (Rosenbaum et al. 2008) is used for primary PM and CO, Greco et al. (2007) for secondary PM from SO2 and NOx, Van Zelm et al. (2008) for secondary PM from NH3 and RiskPoll (Rabl and Spadaro 2004) to differenƟate among highstack, low-stack, and ground-level emissions of primary PM for urban and rural condiƟons, respecƟvely) MechanisƟc (same as in ILCD/PEF/OEF but with updated parameters), Humbert et al


(2011) Effect modeling endpoint-based indicator, dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity). 10.9 DALY per case mortality is used Dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity) Endpoint-based indicator, dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity); chronic bronchiƟs not considered Epidemiological studies (dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity) Epidemiological studies (dose-response (chronic mortality, acute mortality, acute respiratory morbidity, acute cardiovascular morbidity) Gronlund et al


(2015) 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 Emission compartment(s) Air (point source (proxy for high stack) and mobile source (proxy for low stack) Air Air (rural, urban, and undefined) Air (high stack, low stack, ground-level, undefined; remote, rura, urban and undefined environnement) Air (high stack, low stack, ground-level, undefined; remote, rura, urban and undefined environnement) Time horizon, discounƟng Infinite Infinite No Ɵmeframe, no discounƟng No Ɵmeframe, 3% discounƟng for future cost No Ɵmeframe, no discounƟng Region modelled USA Europe Europe Generic Generic and conƟnental Level of spaƟal differenƟaƟon Urban and rural archetypes High stack, low stack, ground-level, undefined; remote, rura, urban and undefined environnement High stack, low stack, ground-level, undefined; remote, rural, urban and


Urban and rural archetypes High stack, low stack, ground-level, undefined; remote, rura, urban and undefined environnement High stack, low stack, ground-level, undefined; remote, rural, urban and undefined environnement No


of substances 7 (TSP9 , PM10, PM2.5, NO, NO2 NOx/nitrate and SO2/sulfate)10 6 (primary PM10 and PM 2.5, SO2, NO2, secondary PM10 from NO2, SO2)10 4 (primary PM10; secondary PM10 from NH3, NOx, SO2) 10 5 (primary PM2.5, primary PM10, secondary PM from NOx and SO2, and CO) 10 5 (primary PM2.5, primary PM10, secondary PM from NOx and SO2, and CO) 10 Unit PM10 equivalents10 PM2.5 equivalents10 PM10 equivalents10 PM2.5 equivalents10 PM2.5 equivalents10 PM2.5 equivalents10 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