Name of source ESU-services data-on-demand LCIA
Provider ESU-services Ltd.
Summary text A database in the sectors of energy, basic minerals, materials, food and lifestyles, consisting of ca. 4,000 unit process datasets, of which about 1000 have been included in ecoinvent.
Contact Niels Jungbluth (+41 44 940 61 32), skype:niels.jungbluth
Licensing Fee (€160 per system data set; €240 per unit process raw data)
Language(s) English, German and French
Access – data formats and accessibility
File type Excel, xml files and EcoSpold, SimaPro, csv. and other formats on request
Software needs SimaPro, Umberto, GaBi and other software tools which can import EcoSpold v1
Contents – breadth and depth of datasets
Age 2000-present
Geography Global, Europe, Switzerland
Original Data Source(s) Collaboration with companies and producers, Industry statistics, Other LCA databases, Academic research, Environmental Reports
Other Databases Included ESU data are built on ecoinvent v2.2 methodology and background data
Life cycle stages Unit processes for different life cycle stages or system processes with cumulative data
Modeling approach Attribution ISO conform
Emissions results Total CO2e, separate GHGs, other environmental indicators
Number of datasets Ca. 4,000
Main topics Energy carriers and technologies; Agriculture, Food and renewable raw materials; Consumer goods, consumer activities, Agricultural production means; Bioenergy, Metals and semimetals; Organic chemicals; Inorganic chemicals, Textiles, tourism, household
Other topics Other systems
Data transparency – what metadata is provided for each dataset?
System boundaries Gate to gate, cradle to grave
Data Types Unit processes, system processes, cumulative LCIA results
Allocation Methods Case specific according to ISO 14040 hierarchy (no system expansion)
Technology Described for each single unit process dataset
Data year Provided for each single unit process dataset
Original source Described for each single unit process dataset
Uncertainty Pedigree Matrix or uncertainty assessed from range of data sources, Monte-Carlo simulation is possible
Quality – is information provided on data quality?
Data quality score Pedigree Matrix for each input and output
Quality assurance Internal validation, steady use in projects with external partners
Standards compliant ISO 14040, 14067, WRI, PAS 2050 and others