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Process Data set: Lime colour (en) en de

Tags Dieser Datensatz ist Bestandteil der ÖKOBAUDAT.
Key Data Set Information
Location DE
Geographical representativeness description The data set represents the country specific situation in Germany, focusing on the main technologies, the region specific characteristics and / or import statistics.
Reference year 2018
Name
Lime colour
Use advice for data set This data set refers to the production of 1 kg of lime colour (ready mixed). Consumption: 0.15 - 0.25 kg/m² (per coat). Density between 1700 and 1900 kg/m³. The data set represents a cradle to gate inventory. It can be used to characterise the supply chain situation of the respective commodity in a representative manner. Combination with individual unit processes using this commodity enables the generation of user-specific (product) LCAs.
Technical purpose of product or process Lime colour is used exclusively indoors. It is moisture-resistant and counteracts mold growth.
Classification number 5.5.02
Classification
Class name : Hierarchy level
  • oekobau.dat: 5.5.02 Coverings / Interior covering / Interior paint
General comment on data set This data set has been modeled according to the European Standard EN 15804 for Sustainable Building. Results are depicted in modules that allow the structured expression of results over the entire life cycle.
Uncertainty margins 20
Description Product system depicted except for a few missing processes / flows. Technological, temporal and geographic representativeness partly given.
Copyright Yes
Owner of data set
Quantitative reference
Reference flow(s)
Time representativeness
Data set valid until 2022
Time representativeness description annual average
Technological representativeness
Technology description including background system Subject of the assessment was lime colour, consisting of slaked lime (calcium hydroxide), water, and small amounts of water glass as well as titanium dioxide. The LCA is dominated by the upstream chain of the slaked lime. Background system: Electricity: Electricity from renewable and non- renewable powerplants is modelled so that it represents a countrys specific consumption mix including transmission / distribution losses, own consumption, imports, emissions and efficiency standards, and energy carrier properties. Several factors are taken into account. (1) Energy carrier production - The exploration, mining / production, processing, and transportation of energy carrier supply chains are modelled for each country. The models account for differences among countries in production and processing, including crude oil production technologies, flaring rates, production efficiencies, emissions, etc. (2) Energy carrier supply - Each countrys specific energy carrier supply is modelled, taking into account domestic supply versus imports from abroad. Energy carrier properties (e.g. carbon and energy content), which can vary depending from where an energy carrier is sourced, are adjusted accordingly. (3) Power plants - Models are created to represent energy carrier-specific power plants and electricity generation facilities specific to different renewable energy resources. Energy carrier production and supply models are used to represent power plant inputs. Combined heat and power (CHP) plants are also considered. (4) Electricity grid - Models representing the electricity generation facilities are combined into a larger model that reflects a countrys consumption mix. The larger model accounts for a countrys production mix, internal consumption (e.g. pumped storage for hydro power), transmission / distribution losses, and imported electricity. The country model is also adjusted according to national power plant emission and efficiency standards, as well as the countrys share of electricity plants versus CHP facilities. Thermal energy, process steam: The thermal energy and process steam supply is modelled to reflect each countrys emission standards and typical energy carriers (e.g., coal, natural gas, etc.) Both thermal energy and process steam are assumed to be produced at heat plants. Thermal energy datasets assume energy carrier inputs are converted to thermal energy with 100% efficiency; process steam datasets assume conversion efficiencies of 85%, 90% to 95%. The energy carriers used for the generation of thermal energy and process steam are modelled according to each countrys import situation (see electricity above). Transportation: All relevant and known transportation processes are included. Ocean-going and inland ship transport as well as rail, truck and pipeline transport of bulk commodities are considered. Energy carriers: The energy carriers and their respective properties are modelled according to the specific supply situation (see electricity above). Refinery products: Diesel fuel, gasoline, technical gases, fuel oils, lubricants and residues such as bitumen are modelled with a parameterised country-specific refinery model. The refinery model aims to represent each countrys refining processes (e.g. emissions levels, internal energy consumption, etc.), as well as the countrys product output spectrum, which can vary significantly among countries. The supply of crude oil is likewise modelled according to the country-specific situation and accounts for differences in resource properties (e.g., crude oil energy content).

Indicators of life cycle

IndicatorDirectionUnit Production
A1-A3
Transport
C2
Disposal
C4
Input
  • 0.8126
  • 0.002722
  • 0.03136
Input
  • 0
  • 0
  • 0
Input
  • 0.8126
  • 0.002722
  • 0.03136
Input
  • 7.521
  • 0.04676
  • 0.2389
Input
  • 0
  • 0
  • 0
Input
  • 7.521
  • 0.04676
  • 0.2389
Input
  • 0
  • 0
  • 0
Input
  • 0
  • 0
  • 0
Input
  • 0
  • 0
  • 0
Input
  • 0.002217
  • 0.000002438
  • 0.00006012
Output
  • 6.596E-9
  • 1.748E-9
  • 3.642E-9
Output
  • 0.03562
  • 0.000008208
  • 1.201
Output
  • 0.0001148
  • 4.923E-8
  • 0.000002679
Output
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0

IndicatorUnit Production
A1-A3
Transport
C2
Disposal
C4
  • 0.9249
  • 0.003486
  • 0.01637
  • 4.51E-15
  • 1.152E-18
  • 9.094E-17
  • 0.00003898
  • -0.00000242
  • 0.000007885
  • 0.0006859
  • 0.000007757
  • 0.000104
  • 0.00009105
  • 0.000001862
  • 0.0000117
  • 5.34E-7
  • 2.928E-10
  • 1.659E-9
  • 7.231
  • 0.04664
  • 0.2322