Process Data set: Acetone from cumene production; technology mix; production mix, at plant; 100% active substance (en)
A more recent version of this data set exists in the database.
Process information
| Key Data Set Information | |
| Location | RER |
| Reference year | 2017 |
| Name |
Base name
; Treatment, standards, routes
; Mix and location types
; Quantitative product or process properties
Acetone from cumene production; technology mix; production mix, at plant; 100% active substance
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| Synonyms | Acetone; 2-propanone; Propanone; Dimethyl ketone; Methyl ketone; Dimethylformaldehyde; |
| Classification |
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| General comment on data set | TYPE OF DATASET For every chemical compound three datasets are created; the unit process (partially terminated system), the non-energy and transport component of the partially terminated system, and the cumulative life cycle inventory dataset (system process). For more information and flow chart see the report (ecoinvent, 2017, Data on the Production of Chemicals created for the EU Product Environmental Footprint (PEF) pilot phase implementation, www.ecoinvent.org, ecoinvent Association, Z\xc3\xbcrich, Switzerland). This dataset represent the cumulative life cycle inventory dataset (system process). PROCESS DESCRIPTION Acetone is mainly used as a solvent in the chemical industry (Gallardo Hipolito 2011). Acetone is a co-product of the cumene phenol process, also known as the Hock process (Gallardo Hipolito 2011). Phenol global production in 2008 was of 9.9 million tons, of which 98.5% was produced through this process (SRI consulting). Global production of acetone is around 5.5 million metric tons (Gallardo Hipolito 2011). The activity starts when the raw materials enter the process. Materials entering the process are included as well as energy uses, infrastructure and emissions. References ecoinvent (2017) Data on the Production of Chemicals created for the EU Product Environmental Footprint (PEF) pilot phase implementation, www.ecoinvent.org, ecoinvent Association, Z\xc3\xbcrich, Switzerland Gendorf (2016) Umwelterkl\xc3\xa4rung 2015, Werk Gendorf Industriepark, www.gendorf.de Gallardo Hipolito, M. 2011. Life Cycle Assessment of platform chemicals from fossil and lignocellulosic biomass scenarios LCA of phenolic compounds, solvent, soft and hard plastic precursors. Master in Industrial Ecology. Norwegian University of Science and Technology Department of Energy and Process Engineering. Retrieved from: http://daim.idi.ntnu.no/masteroppgaver/006/6362/tittelside.pdf, accessed 6 January 2017 SRI consulting. In: Gallardo Hipolito, M. 2011. Life Cycle Assessment of platform chemicals from fossil and lignocellulosic biomass scenarios LCA of phenolic compounds, solvent, soft and hard plastic precursors. Master in Industrial Ecology. Norwegian University of Science and Technology Department of Energy and Process Engineering. Retrieved from: http://daim.idi.ntnu.no/masteroppgaver/006/6362/tittelside.pdf, accessed 6 January 2017 Gallardo Hipolito, M. 2011. Life Cycle Assessment of platform chemicals from fossil and lignocellulosic biomass scenarios LCA of phenolic compounds, solvent, soft and hard plastic precursors. Master in Industrial Ecology. Norwegian University of Science and Technology Department of Energy and Process Engineering. Retrieved from: http://e-archivo.uc3m.es/bitstream/handle/10016/14718/Life%20Cycle%20Assessment%20of%20platform%20chemicals%20from%20fossil%20and%20lignocelulose%20scenarios.%20Martin%20Gallardo.pdf?sequence=2, accessed 6 January 2017 Saygin, D. 2009. Chemical and Petrochemical Sector Potential of best practice technology and other measures for improving energy efficiency. IEA information paper. IEA/OECD. Retrieved from: https://www.iea.org/publications/freepublications/publication/chemical_petrochemical_sector.pdf, accessed 6 January 2017 Water content of the reference product: 0.0 kg Biogenic carbon content of the reference product: 0.0 kg DATA QUALITY ASSESSMENT The data quality ratings for the datasets were determined as the average of the 5 individual ratings for Technological Representativeness, Geographical Representativeness, Time-related representativeness, Precision/uncertainty, and implementation of the End of Life Formula. The final scores for these 5 descriptors were determined by the independent, external reviewer after a discussion with the internal reviewers. The basis for this determination was generally a contribution analysis of the material and energy inputs as well as direct resource uses and emissions. This process was required by the tender. The contribution analysis is based on the most important flows in the dataset, defined in the tender specifications as \xe2\x80\x9cthe unit processes contributing cumulatively to at least to 80% of the total environmental impact based on characterised and normalised results\xe2\x80\x9d. In addition to unit processes, direct emissions also qualified as input exchanges for this approach. For the normalization, the normalisation factors \xe2\x80\x9cEC-JRC Global (2010 or 2013), per person\xe2\x80\x9d available at http://eplca.jrc.ec.europa.eu/?page_id=140 were used. For each parameter, the DQR scores were chosen to best reflect the conditions and quality of the amount value, the appropriateness of the chosen exchange for the specific needs of the system under analysis, and the quality of the foreground and background data for aggregated inputs of exchanges from the technosphere, i.e. not direct emissions or resource uses. ENERGY AND TRANSPORT INFORMATION SOURCE Energy and transport was used in both the foreground and background of this dataset. When building the dataset, energy and transport demands were supplied directly by datasets provided by thinkstep. The background for every other input from technosphere uses a modified version of the ecoinvent database, created specifically for the PEF. In this version, every instance of energy and transport supply, anywhere in the database, was replaced by a dataset from thinkstep. This ensures that every demand for energy and transport, in the foreground and in the background, is supplied by a thinkstep dataset. BILL OF MATERIALS The bill of material includes the following inputs: chemical factory, organics: 1.84575859807e-10 unit cumene: 0.620333595218 kg heat, in chemical industry: 1.08438317636 MJ nitrogen, liquid: 0.00876735334082 kg tap water: 0.0119974308874 kg wastewater, average: -1.2458870537e-06 m3 Electricity: 0.191958894199 kWh. NOT INCLUDED EXCHANGES The following exchanges have not been included in the inventory as they are not part of the official list of elementary exchanges published by the JRC. The EC and JRC were not able to provide an extended flow list during the duration of the data creation. If the JRC decides to include these exchanges in the master data, they may be added to the exchange section of the dataset by ecoinvent as part of a maintenance. The absence of these exchanges does not change the scores calculated with the ILCD recommended methods, but that might not be the case for other LCIA methods. inland water bodies, Resources, Land occupation: 3.44e-05 m2*a sodium hydroxide, Emissions to water, Emissions to water, unspecified: 2.1e-14 kg sodium hypochlorite, Emissions to water, Emissions to water, unspecified: 3.9e-14 kg PROCESS DIAGRAM LEGEND The file 'chemical_dataset_diagram.jpg' presents the relationship between partially terminated datasets, energy and transport from datasets from thinkstep, and the aggregated inputs dataset. The aggregated inputs dataset is available on the node, under the name 'Acetone from cumene production, aggregated inputs, RER.xml' The following datasets from thinkstep are used as inputs of energy: 0.192 kWh of Electricity from Electricity grid mix 1kV-60kV - EU-28+3 The following datasets from thinkstep are used as inputs of transport: 0.00504 metric ton*km of Transport from Barge - EU-28+3 0.0102 metric ton*km of Transport from Barge - ROW w/o EU-28+3 0.0342 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight >32 t (without fuel) - EU-28+3 0.00251 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight 20-26 t (without fuel) - EU-28+3 0.0148 metric ton*km of Transport from Articulated lorry transport, Total weight 20-26 t, mix Euro 0-5 - ROW w/o EU-28+3 0.0111 metric ton*km of Transport from Articulated lorry transport, Total weight 14-20 t, mix Euro 0-5 - ROW w/o EU-28+3 0.00738 metric ton*km of Transport from Articulated lorry transport, Total weight 28-32 t, mix Euro 0-5 - ROW w/o EU-28+3 0.00126 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight 28-32 t (without fuel) - EU-28+3 0.00204 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight 14-20 t (without fuel) - EU-28+3 0.00192 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight <7.5 t (without fuel) - EU-28+3 0.000156 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight 12-14 t (without fuel) - EU-28+3 0.000352 metric ton*km of Transport from Articulated lorry transport, Euro 3, Total weight 7,5-12 t (without fuel) - EU-28+3 0.0316 metric ton*km of Transport from Articulated lorry transport, Euro 4, Total weight >32 t (without fuel) - EU-28+3 0.00103 metric ton*km of Transport from Articulated lorry transport, Euro 4, Total weight 20-26 t (without fuel) - EU-28+3 0.00166 metric ton*km of Transport from Articulated lorry transport, Euro 4, Total weight 12-14 t (without fuel) - EU-28+3 0.00218 metric ton*km of Transport from Articulated lorry transport, Euro 4, Total weight 14-20 t (without fuel) - EU-28+3 0.00125 metric ton*km of Transport from Articulated lorry transport, Euro 4, Total weight <7.5 t (without fuel) - EU-28+3 0.000249 metric ton*km of Transport from Articulated lorry transport, Euro 4, Total weight 7,5-12 t (without fuel) - EU-28+3 0.0134 metric ton*km of Transport from Articulated lorry transport, Euro 5, Total weight >32 t (without fuel) - EU-28+3 0.00068 metric ton*km of Transport from Articulated lorry transport, Euro 5, Total weight 12-14 t (without fuel) - EU-28+3 0.000419 metric ton*km of Transport from Articulated lorry transport, Euro 5, Total weight 20-26 t (without fuel) - EU-28+3 0.000889 metric ton*km of Transport from Articulated lorry transport, Euro 5, Total weight 14-20 t (without fuel) - EU-28+3 0.000498 metric ton*km of Transport from Articulated lorry transport, Euro 5, Total weight <7.5 t (without fuel) - EU-28+3 0.000117 metric ton*km of Transport from Articulated lorry transport, Euro 5, Total weight 7,5-12 t (without fuel) - EU-28+3 0.372 metric ton*km of Transporting capacity from Transoceanic ship, containers - GLO 0.0934 metric ton*km of Transport from Freight train, diesel traction - EU-28+3 0.0946 metric ton*km of Transport from Freight train, electricity traction - EU-28+3 0.00393 metric ton*km of Transport from Freight train, average (without fuel) - EU-28+3 |
| Copyright | Yes |
| Owner of data set | |
| Quantitative reference | |
| Reference flow(s) |
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| Time representativeness | |
| Data set valid until | 2020 |
| Technological representativeness | |
| Technology description including background system | Acetone is produced as a co-product of the cumene phenol process (Hock process). This process consists first in the production of cumene from the reaction of benzene and propylene. Cumene then reacts with oxygen to give phenol and acetone. For each kilogram of phenol produced, 0.63 kg of acetone are obtained. For the process 0.6 MJ/kg of electricity and 9.1 MJ/kg of steam are required per kg of phenol and 0.2 MJ/kg of electricity and 9.8 MJ/kg of steam required per kg of acetone (Saygin 2009). Chemical reaction: C9H12 + O2 -> C6H6O + C3H6O This inventory representing production of a particular chemical compound is at least partially based on a generic model on the production of chemicals. The data generated by this model have been improved by compound-specific data when available. The model on production of chemicals is using specific industry or literature data wherever possible and more generic data on chemical production processes to fill compound-specific data gaps when necessary. The basic principles of the model have been published in literature (Hischier 2005, Establishing Life Cycle Inventories of Chemicals Based on Differing Data Availability). The model has been updated and extended with newly available data from the chemical industry. In the model, unreacted fractions are treated in a waste treatment process, and emissions reported are after a waste treatment process that is included in the scope of this dataset. For volatile reactants, a small level of evaporation is assumed. Solvents and catalysts are mostly recycled in closed-loop systems within the scope of the dataset and reported flows are for losses from this system. For more detailed description of the model see the sectorial report (ecoinvent (2017) Data on the Production of Chemicals created for the EU Product Environmental Footprint (PEF) pilot phase implementation, www.ecoinvent.org, ecoinvent Association, Z\xc3\xbcrich, Switzerland). |
Modelling and validation
| LCI method and allocation | |||||||||||||||||||||||||||||
| Type of data set | LCI result | ||||||||||||||||||||||||||||
| LCI Method Principle | Attributional | ||||||||||||||||||||||||||||
| Deviation from LCI method principle / explanations | The background data use the \xe2\x80\x9cRecycled content cut-off\xe2\x80\x9d approach to allocate end-of-life by-products and secondary materials. This allocation is explained in the description of the recycled content system model (http://www.ecoinvent.org/database/system-models-in-ecoinvent-3/cut-off-system-model/allocation-cut-off-by-classification.html). | ||||||||||||||||||||||||||||
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| Deviations from LCI method approaches / explanations | Allocation following the ISO 14044 hierarchy. | ||||||||||||||||||||||||||||
| Modelling constants | All modelling constants follow the requirements listed in the Tender Specifications ENV.B.1/SER/2016/0038vl. Completeness: All known environmental flows are included. All known resource uses and emissions are listed in the inventory. Water use: water use is modelled at country level using separate flows for water withdrawal, water release and water evaporation. Cut-off: All known environmental flows are included. All known resource uses and emissions are listed in the inventory. Handling multi-functional processes: the following PEF multi- functionality decision hierarchy is applied for resolving all multi- functionality problems: (1) subdivision or system expansion; (2) allocation based on a relevant underlying physical relationship (substitution may apply here); (3) allocation based on some other relationship. Direct land use change: GHG emissions from direct LUC allocated to good/service for 20 years after the LUC occurs, with IPCC default values. Carbon storage and delayed emissions: credits associated with temporary (carbon) storage or delayed emissions up to 300 years are not be considered. Emissions off-setting: are not included. Capital goods (including infrastructures) and their End of life: they are included. System boundaries: system boundaries include all processes linked to the product supply chain (e.g. maintenance). Time period: emissions and removals are modelled as if released or removed at the beginning of the assessment method. Fossil and biogenic carbon emissions and removals: removals and emissions are modelled as follows: All GHG emissions from fossil fuels (including peat and limestone) are modelled consistently with the most updated ILCD list of elementary flows. The non-fossil (biogenic) carbon flows are modelled consistently with the most updated ILCD list of elementary flows. | ||||||||||||||||||||||||||||
| Deviation from modelling constants / explanations | None | ||||||||||||||||||||||||||||
| Data sources, treatment and representativeness | |||||||||||||||||||||||||||||
| Data cut-off and completeness principles | All known environmental flows are included. All known resource uses and emissions are listed in the inventory. The dataset dry mass balance has been checked to ensure the inventory is complete. Capital goods (e.g. infrastructure) and their end-of-life are included. | ||||||||||||||||||||||||||||
| Deviation from data cut-off and completeness principles / explanations | None | ||||||||||||||||||||||||||||
| Data selection and combination principles | These datasets include, in both their foreground and background data, links to energy and transport data provided specifically for the PEF pilot projects. The relevant background data on energy and transport are from the existing LCDN data node (http://lcdn.thinkstep.com/Node/). All other background data in the supply chain of this product are from the ecoinvent v3.3 database (www.ecoinvent.org). | ||||||||||||||||||||||||||||
| Deviation from data selection and combination principles / explanations | None | ||||||||||||||||||||||||||||
| Data treatment and extrapolations principles | Several data sources have been used to model the inventory. | ||||||||||||||||||||||||||||
| Deviation from data treatment and extrapolations principles / explanations | None | ||||||||||||||||||||||||||||
| Uncertainty adjustments | None | ||||||||||||||||||||||||||||
| Completeness | |||||||||||||||||||||||||||||
| Completeness of product model | All relevant flows quantified | ||||||||||||||||||||||||||||
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| Compliance Declarations | |||||||||||||||||||||||||||||
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Approval of overall compliance
Fully compliant |
Nomenclature compliance
Fully compliant |
Methodological compliance
Fully compliant |
Review compliance
Fully compliant |
Documentation compliance
Fully compliant |
Quality compliance
Fully compliant |
| Compliance |
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Approval of overall compliance
Fully compliant |
Nomenclature compliance
Not defined |
Methodological compliance
Fully compliant |
Review compliance
Fully compliant |
Documentation compliance
Not defined |
Quality compliance
Fully compliant |
Administrative information
| Commissioner and goal | |
| Commissioner of data set | |
| Project | Provision of chemicals process-based product environmental footprint-compliant life cycle inventory datasets. Contract number ENV.A.1/SER/2016/0038vl |
| Intended applications | This dataset is to be used only within the pilot projects of the PEF/OEF. The dataset and background data contain modeling choices and data sources that are not generally recommended for use in LCAs beyond the PEF/OEF pilot projects. |
| Data generator | |
| Data set generator / modeller | |
| Data entry by | |
| Time stamp (last saved) | 2017-05-13T02:00:00+01:00 |
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| Data entry by | |
| Publication and ownership | |
| UUID | f6d691ae-025e-4c32-bee2-6137c7bbc60a |
| Date of last revision | 2017-05-13T02:00:00+01:00 |
| Data set version | 03.00.008 |
| Owner of data set | |
| Copyright | Yes |
| Reference to entities with exclusive access | |
| License type | Free of charge for some user types or use types |
| Access and use restrictions | Free of charge for all final users implementing the data in one of the 24 PEFCRs/OEFSRs developed during the Environmental Footprint pilot phase. The final users using this dataset must agree with and submit to the ecoinvent End User License Agreement - EULA \'ecoinvent Production of Chemicals datasets created for the EU Product Environmental Footprint (PEF) implementation 2016 - 2020\' of ecoinvent (www.ecoinvent.org). Any use of this dataset or any derivative data not within the specific context of one of the PEF/OEF pilot projects or after the end of 2020 is not permitted. |
Inputs and Outputs
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LCIA results
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